diff --git a/AI_Engine_Development/AIE-ML/AIE-ML.rst b/AI_Engine_Development/AIE-ML/AIE-ML.rst index af3216cb51..6f876b7cea 100644 --- a/AI_Engine_Development/AIE-ML/AIE-ML.rst +++ b/AI_Engine_Development/AIE-ML/AIE-ML.rst @@ -16,15 +16,15 @@ The tutorials under the AI Engine for Machine Learning (AIE-ML) Development help .. important:: - Before beginning a tutorial, ensure you have installed the Vitis 2024.2 software. The Vitis release includes all the embedded base platforms, including the VEK280 base platform that is used in these tutorials. In addition, ensure you have downloaded the Common Images for Embedded Vitis Platforms from `Downloads `_. + Before beginning a tutorial, ensure you have installed the Vitis 2025.2 software. The Vitis release includes all the embedded base platforms, including the VEK280 base platform that is used in these tutorials. In addition, ensure you have downloaded the Common Images for Embedded Vitis Platforms from `Downloads `_. The `common image` package contains a prebuilt Linux kernel and root file system that can be used with the AMD Versal™ board for embedded design development using the Vitis software platform. Before starting a tutorial, run the following steps: 1. Go to the directory where you have unzipped the Versal Common Image package. -2. In a Bash shell, run the ``/Common Images Dir/xilinx-versal-common-v2024.2/environment-setup-cortexa72-cortexa53-amd-linux`` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run ``/Common Images Dir/xilinx-versal-common-v2024.2/sdk.sh``. -3. Set up your ROOTFS and IMAGE to point to the ``rootfs.ext4`` and Image files located in the ``/Common Images Dir/xilinx-versal-common-v2024.2`` directory. +2. In a Bash shell, run the ``/Common Images Dir/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux`` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run ``/Common Images Dir/xilinx-versal-common-v2025.2/sdk.sh``. +3. Set up your ROOTFS and IMAGE to point to the ``rootfs.ext4`` and Image files located in the ``/Common Images Dir/xilinx-versal-common-v2025.2`` directory. 4. Set up your PLATFORM_REPO_PATHS environment variable to ``$XILINX_VITIS/base_platforms``. diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/01-AIE-ML-programming-and-optimization/AIEngineMLArchitecture.md b/AI_Engine_Development/AIE-ML/Design_Tutorials/01-AIE-ML-programming-and-optimization/AIEngineMLArchitecture.md index 2576fcf932..4ab3f8e904 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/01-AIE-ML-programming-and-optimization/AIEngineMLArchitecture.md +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/01-AIE-ML-programming-and-optimization/AIEngineMLArchitecture.md @@ -15,14 +15,11 @@ # AI Engine-ML Architecture - - - ## Introduction -Versal™ AI Edge ACAPs have been develop to target any applications at the edge where balancing performance and power consumption, low latency, size and thermal constraints, and safety and reliability are paramount. +The Versal™ AI Edge Series has been develop to target any applications at the edge where balancing performance and power consumption, low latency, size and thermal constraints, and safety and reliability are paramount. -As the Versal™ AI Core series they contain also an array of SIMD VLIW DSP processors but with different functionality. +Like the Versal™ AI Core Series, it also contains an array of SIMD VLIW DSP processors but with different functionality. ![AI Engine-ML overview](images/AIE-ML-Overview.png) diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/01-AIE-ML-programming-and-optimization/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/01-AIE-ML-programming-and-optimization/Makefile index e6e2f3a271..f866f5cb62 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/01-AIE-ML-programming-and-optimization/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/01-AIE-ML-programming-and-optimization/Makefile @@ -22,7 +22,7 @@ OPT ?= 0 # hw_emu|hw TARGET ?= hw_emu -PFM_NAME := xilinx_vek280_base_202510_1 +PFM_NAME := xilinx_vek280_base_202520_1 PFM_NAME := $(strip $(PFM_NAME)) PLATFORM := ${PLATFORM_REPO_PATHS}/${PFM_NAME}/${PFM_NAME}.xpfm PNAME := aieml_pl_${TARGET} @@ -97,16 +97,16 @@ guard-PLATFORM_REPO_PATHS: $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded your platform) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) ### .PHONY: all_hw all_hw_emu run upd_host_hw aie postaie data aiesim aieviz aiesim-fifo compareaie x86 x86sim comparex86 allcases @@ -194,11 +194,12 @@ package_${TARGET}: ${LIBADF} ${XCLBIN} ${HOST_EXE} clean: - rm -rf _x v++_* ${XOS} ${OS} ${LIBADF} *.o.* *.o *.xpe *.xo.* \ + rm -rf _x v++_* ${XOS} ${OS} ${LIBADF} *.o.* *.o *.xpe *.xo.* analyzer_input\ vek280*.xclbin* *.xsa *.log *.jou xnwOut Work Map_Report.csv \ ilpProblem* sol.db drivers .Xil *bin *BIN *.bif launch_hw_emu.sh cfg emu_qemu_scripts \ - [!d]*.json *.txt *.wdb *.wcfg *.pdi v++.package_summary sim qemu_dts_files sd_card sd_card.img \ - dtb_creation.sh .ipcache *summary *.sh .AIE_SIM_CMD_LINE_OPTIONS .crashReporter + [!d]*.json *.txt *.wdb *.wcfg *.pdi v++.package_summary sim qemu_dts_files \ + sd_card sd_card.img \ + dtb_creation.sh .ipcache *summary *.sh .AIE_SIM_CMD_LINE_OPTIONS .crashReporter baremetal_metadata_package.cpp make -C ${AIE_DIR} clean make -C ${KERNELS_DIR} clean make -C ${HOST_DIR} clean diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/01-AIE-ML-programming-and-optimization/README.md b/AI_Engine_Development/AIE-ML/Design_Tutorials/01-AIE-ML-programming-and-optimization/README.md index 1c9530075d..a29d5fcdac 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/01-AIE-ML-programming-and-optimization/README.md +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/01-AIE-ML-programming-and-optimization/README.md @@ -15,22 +15,22 @@ # AI Engine-ML Programming -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction ->**IMPORTANT**: Before beginning the tutorial make sure you have installed the AMD Vitis™ 2025.1 software. The Vitis release includes all the embedded base platforms including the VEK280 base platform that is used in this tutorial. In addition, ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). +>**IMPORTANT**: Before beginning the tutorial make sure you have installed the AMD Vitis™ 2025.2 software. The Vitis release includes all the embedded base platforms including the VEK280 base platform that is used in this tutorial. In addition, ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). The ‘common image’ package contains a prebuilt Linux kernel and root file system that can be used with the AMD Versal™ board for embedded design development using the Vitis software platform. Before starting this tutorial, run the following steps: 1. Go to the directory where you have unzipped the Versal Common Image package. -2. In a Bash shell, run the ``/Common Images Dir/xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux`` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ``/Common Images Dir/xilinx-versal-common-v2025.1/sdk.sh``. -3. Set up your ROOTFS and IMAGE to point to the ``rootfs.ext4`` and Image files located in the ``/Common Images Dir/xilinx-versal-common-v2025.1`` directory. +2. In a Bash shell, run the ``/Common Images Dir/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux`` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ``/Common Images Dir/xilinx-versal-common-v2025.2/sdk.sh``. +3. Set up your ROOTFS and IMAGE to point to the ``rootfs.ext4`` and Image files located in the ``/Common Images Dir/xilinx-versal-common-v2025.2`` directory. 4. Set up your PLATFORM_REPO_PATHS environment variable to ``$XILINX_VITIS/base_platforms``. -This tutorial targets VEK280 board for 2025.1 version. +This tutorial targets VEK280 board for 2025.2 version. Data generation for this tutorial requires [Python 3](https://www.python.org/downloads/). The following packages are required: @@ -67,10 +67,9 @@ The various memory levels contains DMAs used to receive/transfer data to/from me Matrix multiplication is very common algorithm that can be found in numerous standard applications. The basic equation is: -``` $$ C = A.B $$ $$ \left( c_{ij} \right)_{\substack{0\leq i \lt M \\ 0 \leq j \lt N}} = \sum_{k=0}^{k #include #include diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/Makefile index ab28fa69d2..1c751ab0b2 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/Makefile @@ -7,9 +7,9 @@ ECHO = @echo export TARGET ?= hw -RELEASE=2025.1 +RELEASE=2025.2 BOARD=vek280 -BASE_NUM=202510_1 +BASE_NUM=202520_1 # Platform Selection... VERSAL_VITIS_PLATFORM = xilinx_${BOARD}\_base_${BASE_NUM} diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/README.md b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/README.md index 86eb1c78ee..e730f25f7e 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/README.md +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/README.md @@ -15,7 +15,7 @@ # Prime Factor FFT-1008 on AIE-ML -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents @@ -32,15 +32,16 @@ [License](#license) ## Introduction + The Prime Factor Algorithm (PFA) [[1]] is a Fast Fourier Transform (FFT) algorithm [[2]] discovered by Good & Thomas before the more popular Cooley-Tukey algorithm with some interesting properties. The PFA is another "divide and conquer" approach for computing a Discrete Fourier Transform (DFT) of size $N = N_1 \cdot N_2$ as a two-dimensional DFT of size $N_1 \times N_2$ as long as $N_1$ and $N_2$ are relatively prime (ie. share no common divisors). The smaller transforms of size $N_1$ and $N_2$ may be computed by some other technique, for example using the Winograd FFT Algorithm, or the PFA technique may be applied recursively again to both $N_1$ and $N_2$. It turns out Versal AI Engines compute DFT with small dimensions $N < 32$ very efficiently using direct vector/matrix multiplication. Consequently, the PFA approach using DFT on the individual prime factors provides an efficient approach to the FFT on Versal AI Engines. A second advantage of the PFA approach is that unlike the popular Cooley-Tukey FFT, no extra multiplications by "twiddle factors" need be performed between stages. This fact falls out of the DFT factorization when $N_1$ and $N_2$ share no common factors. This provides a computational advantage compared to the more traditional Cooley-Tukey formulation, but the PFA incurs a drawback in that a complicated re-indexing or permutation of it's I/O samples is required. For Versal devices with both AI Engines and Programmable Logic (PL), however, this drawback is solved easily by leveraging the PL to implement these permutations as part of a custom data flow tailored to the PFA signal flow graph. An [earlier tutorial](../../../AIE/Design_Tutorials/05-Prime-Factor-FFT) implemented a PFA-1008 transform on AIE architecture in the VC1902 device. This tutorial maps the PFA-1008 transform to AIE-ML architecture in the VE2802 device. Once again we map the short-length DFT-7, DFT-9 and DFT-16 transforms to AI Engine using vector-matrix DFT's but this time to the AIE-ML architecture. The intermediate "memory transpose" operations mapped earlier to the programmable logic (PL) are instead mapped here to the Memory Tiles contained in the AIE-ML array. This simplifies data flow and keeps most of the graph inside the the array. The input and output permutation blocks remain implemented in the PL as RTL obtained using VItis High Level Synthesis (HLS) from untimed C++ models. These cannot be mapped to Mem Tiles as they require a type of modulo addressing not supported by the Memory Tile buffer descriptors (BDs). -## Matlab Models +## MATLAB Models -This tutorial relies on the same Matlab models from the [original tutorial](../../../AIE/Design_Tutorials/05-Prime-Factor-FFT). These models have been replicated here in the `matlab` folder of the repo. These apply to both the signal processing functions as well as the I/O permutations and matrix transpose addressing operations. All remain identical. +This tutorial relies on the same MATLAB® models from the [original tutorial](../../../AIE/Design_Tutorials/05-Prime-Factor-FFT). These models have been replicated here in the `matlab` folder of the repo. These apply to both the signal processing functions as well as the I/O permutations and matrix transpose addressing operations. All remain identical. ## Design Overview @@ -157,16 +158,16 @@ The figure below summarizes the PL resources required to implement the design. T ### Setup & Initialization -IMPORTANT: Before beginning the tutorial ensure you have installed Vitis™ 2025.1 software. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). +IMPORTANT: Before beginning the tutorial ensure you have installed Vitis™ 2025.2 software. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). Set the environment variable ```COMMON_IMAGE_VERSAL``` to the full path where you have downloaded the Common Images. Then set the environment variable ```PLATFORM_REPO_PATHS``` to the value ```$XILINX_VITIS/base_platforms```. Additional information on this process may be found [here](../../../AIE#environment-settings). The remaining environment variables are configured in the top level Makefile ```/02-Prime-Factor-FFT/Makefile``` file. ``` -RELEASE=2025.1 +RELEASE=2025.2 BOARD=vek280 -BASE_NUM=202510_1 +BASE_NUM=202520_1 # Platform Selection... VERSAL_VITIS_PLATFORM = xilinx_${BOARD}\_base_${BASE_NUM} diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/dft16/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/dft16/Makefile index 2f65fbf9c8..cc779ab100 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/dft16/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/dft16/Makefile @@ -10,8 +10,7 @@ MY_APP := dft16_app MY_SOURCES := ${MY_APP}.cpp dft16_graph.h dft16_mmul0.h dft16_mmul0.cpp dft16_mmul1.h dft16_mmul1.cpp \ dft16_twiddle.h -PLATFORM_USE := xilinx_vek280_base_202510_1 -PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcve2802-vsvh1760-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing @@ -21,8 +20,7 @@ DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ AIE_OUTPUT := libadf.a -AIE_FLAGS := ${DSPLIB_OPTS} --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} - +AIE_FLAGS := ${DSPLIB_OPTS} --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} endif diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/dft7/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/dft7/Makefile index 2944e1e98b..898e0fd0c3 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/dft7/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/dft7/Makefile @@ -10,8 +10,7 @@ MY_APP := dft7_app MY_SOURCES := ${MY_APP}.cpp dft7_graph.h dft7_mmul0.h dft7_mmul0.cpp dft7_mmul1.h dft7_mmul1.cpp \ dft7_twiddle.h -PLATFORM_USE := xilinx_vek280_base_202510_1 -PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcve2802-vsvh1760-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing @@ -21,8 +20,7 @@ DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ AIE_OUTPUT := libadf.a -AIE_FLAGS := ${DSPLIB_OPTS} --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} - +AIE_FLAGS := ${DSPLIB_OPTS} --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} endif diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/dft9/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/dft9/Makefile index 8f89ebfa51..2a6cee7cb9 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/dft9/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/dft9/Makefile @@ -10,15 +10,13 @@ MY_APP := dft9_app MY_SOURCES := ${MY_APP}.cpp dft9_graph.h dft9_mmul0.h dft9_mmul1.h dft9_mmul0.cpp dft9_mmul1.cpp \ dft9_mmul3.h dft9_mmul3.cpp dft9_twiddle.h -PLATFORM_USE := xilinx_vek280_base_202510_1 -PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcve2802-vsvh1760-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing AIE_OUTPUT := libadf.a -AIE_FLAGS := --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} - +AIE_FLAGS := ${DSPLIB_OPTS} --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} endif diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/permute_i/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/permute_i/Makefile index bd648cd4f1..9a5531fe5f 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/permute_i/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/permute_i/Makefile @@ -9,8 +9,7 @@ SIM_FIFO := false MY_APP := permute_i_app MY_SOURCES := ${MY_APP}.cpp permute_i_graph.h permute_i_bd.h -PLATFORM_USE := xilinx_vek280_base_202510_1 -PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcve2802-vsvh1760-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing @@ -20,8 +19,7 @@ DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ AIE_OUTPUT := libadf.a -AIE_FLAGS := ${DSPLIB_OPTS} --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} - +AIE_FLAGS := ${DSPLIB_OPTS} --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} endif diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/pfa1008/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/pfa1008/Makefile index f93c5bc53a..6fb3c64e14 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/pfa1008/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/pfa1008/Makefile @@ -25,8 +25,7 @@ MY_SOURCES := ${MY_APP}.cpp pfa1008_graph.h ${DFT7_SOURCE:%=../dft7/%} ${ ${DFT16_SOURCE:%=../dft16/%} \ ${TRANSPOSE0_SOURCE:%=../transpose0/%} ${TRANSPOSE1_SOURCE:%=../transpose1/%} -PLATFORM_USE := xilinx_vek280_base_202510_1 -PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcve2802-vsvh1760-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing @@ -38,7 +37,7 @@ MY_INCLUDES := --include=../dft7 \ AIE_OUTPUT := libadf.a -AIE_FLAGS := ${MY_INCLUDES} --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} +AIE_FLAGS := ${MY_INCLUDES} --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/transpose0/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/transpose0/Makefile index 5e0972c204..2b85d714cc 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/transpose0/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/transpose0/Makefile @@ -9,8 +9,7 @@ SIM_FIFO := false MY_APP := transpose0_app MY_SOURCES := ${MY_APP}.cpp transpose0_graph.h -PLATFORM_USE := xilinx_vek280_base_202510_1 -PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcve2802-vsvh1760-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing @@ -20,8 +19,7 @@ DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ AIE_OUTPUT := libadf.a -AIE_FLAGS := ${DSPLIB_OPTS} --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} - +AIE_FLAGS := ${DSPLIB_OPTS} --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} endif diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/transpose1/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/transpose1/Makefile index 5b882e43ed..f7991990a9 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/transpose1/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/aie/transpose1/Makefile @@ -9,8 +9,7 @@ SIM_FIFO := false MY_APP := transpose1_app MY_SOURCES := ${MY_APP}.cpp transpose1_graph.h -PLATFORM_USE := xilinx_vek280_base_202510_1 -PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcve2802-vsvh1760-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing @@ -20,8 +19,7 @@ DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ AIE_OUTPUT := libadf.a -AIE_FLAGS := ${DSPLIB_OPTS} --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} - +AIE_FLAGS := ${DSPLIB_OPTS} --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} endif diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_dma_snk/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_dma_snk/Makefile index 17fd7503b6..d76f46d59d 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_dma_snk/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_dma_snk/Makefile @@ -5,6 +5,7 @@ # Author: Mark Rollins DO_COSIM := false +DO_OOCPAR := false ECHO := @echo KERNEL := pfa1008_dma_snk_wrapper @@ -28,6 +29,8 @@ ${XO}: ${KERNEL_SRC} ifeq (${DO_COSIM},true) vitis-run --mode hls --config hls.cfg --csim --work_dir ${KERNEL} vitis-run --mode hls --config hls.cfg --cosim --work_dir ${KERNEL} +endif +ifeq (${DO_OOCPAR},true) vitis-run --mode hls --config hls.cfg --impl --work_dir ${KERNEL} endif diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_dma_snk/pfa1008_dma_snk.cpp b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_dma_snk/pfa1008_dma_snk.cpp index b12cba9fd1..ef32ef0c2d 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_dma_snk/pfa1008_dma_snk.cpp +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_dma_snk/pfa1008_dma_snk.cpp @@ -11,19 +11,30 @@ using namespace pfa1008_dma_snk; // Stream Capture // ------------------------------------------------------------ -void capture_streams( TT_DATA (&buff)[DEPTH], TT_STREAM& sig_i, - const int& loop_sel, const int& loop_cnt ) +unsigned capture_streams( TT_DATA (&buff)[DEPTH], TT_STREAM& sig_i, unsigned int word_count ) { - CAPTURE: for (int ll=0; ll < loop_cnt; ll++) { -#pragma HLS LOOP_TRIPCOUNT min=1 max=8 - SAMPLE_IN: for (int dd=0; dd < DEPTH; dd++) { + unsigned cnt_smp = 0; + unsigned cnt_cyc = 0; + bool saw_first = 0; + TT_ADDR dd = 0; + unsigned base = word_count - DEPTH; + while (cnt_smp < word_count) { #pragma HLS pipeline II=1 + bool empty = sig_i.empty(); + bool capture = (cnt_smp < base) ? 0 : 1; + if (empty == 0) { + saw_first = 1; TT_DATA val = sig_i.read(); - if ( ll == loop_sel ) { + if (capture == 1) { buff[dd] = val; + dd = dd + 1; } - } //dd - } // ll + cnt_smp++; + } + if (saw_first == 1) + cnt_cyc++; + } + return(cnt_cyc); } // ------------------------------------------------------------ @@ -42,28 +53,31 @@ void read_buffer( TT_DATA mem[DEPTH], TT_DATA (&buff)[DEPTH] ) // Wrapper // ------------------------------------------------------------ -void +unsigned pfa1008_dma_snk_wrapper( pfa1008_dma_snk::TT_DATA mem[pfa1008_dma_snk::DEPTH], - int loop_sel, - int loop_cnt, + unsigned int word_count, pfa1008_dma_snk::TT_STREAM& sig_i ) { -#pragma HLS interface m_axi port=mem bundle=gmem offset=slave depth=DEPTH -#pragma HLS interface axis port=sig_i -#pragma HLS interface s_axilite port=loop_sel bundle=control -#pragma HLS interface s_axilite port=loop_cnt bundle=control -#pragma HLS interface s_axilite port=mem bundle=control -#pragma HLS interface s_axilite port=return bundle=control +#pragma HLS interface mode=axis port=sig_i +#pragma HLS interface mode=m_axi port=mem offset=slave bundle=gmem1 depth=DEPTH +#pragma HLS interface mode=s_axilite port=mem bundle=control +#pragma HLS interface m_axi port=mem num_write_outstanding=1 max_write_burst_length=1 +#pragma HLS interface m_axi port=mem num_read_outstanding=1 max_read_burst_length=1 +#pragma HLS interface mode=s_axilite port=word_count bundle=control +#pragma HLS interface mode=s_axilite port=return bundle=control #pragma HLS DATAFLOW // Internal buffer: TT_DATA buff[DEPTH]; + unsigned cycle_count; // Front end load from DDR4 to PL BRAM: - capture_streams( buff, sig_i, loop_sel, loop_cnt ); + cycle_count = capture_streams( buff, sig_i, word_count ); // Back end transmit from PL BRAM to AIE: read_buffer( mem, buff ); + + return(cycle_count); } diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_dma_snk/pfa1008_dma_snk.h b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_dma_snk/pfa1008_dma_snk.h index 49b1260de6..cc1ba87324 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_dma_snk/pfa1008_dma_snk.h +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_dma_snk/pfa1008_dma_snk.h @@ -24,7 +24,6 @@ namespace pfa1008_dma_snk { // Run: // Assume 312.5 MHz clock. // We have 32-bit I/O's @ 1250 MHz AIE clock or 128-bit I/O's @ 312.5 MHz -void pfa1008_dma_snk_wrapper( pfa1008_dma_snk::TT_DATA mem[pfa1008_dma_snk::DEPTH], - int loop_sel, - int loop_cnt, - pfa1008_dma_snk::TT_STREAM& sig_i ); +unsigned pfa1008_dma_snk_wrapper( pfa1008_dma_snk::TT_DATA mem[pfa1008_dma_snk::DEPTH], + unsigned int word_count, + pfa1008_dma_snk::TT_STREAM& sig_i ); diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_dma_snk/tb_wrapper.cpp b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_dma_snk/tb_wrapper.cpp index 81bb245983..a5f71adadf 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_dma_snk/tb_wrapper.cpp +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_dma_snk/tb_wrapper.cpp @@ -16,8 +16,6 @@ using namespace pfa1008_dma_snk; // Main // ------------------------------------------------------------ -extern void pfa1008_dma_snk_wrapper( TT_DATA mem[DEPTH], int loop_sel, int loop_cnt,TT_STREAM& sig_i ); - int main( void ) { // Create DDR4 contents: @@ -25,32 +23,32 @@ int main( void ) TT_STREAM sig_i; // Configure the same as 'host.cpp' for top level application: - int loop_cnt = 4; - int loop_sel = 1; + unsigned word_count = 8*1008; // Load stimulus (in order produced by DFT): std::minstd_rand gen; - for (int ll=0; ll < loop_cnt; ll++) { - for (int mm=0; mm < DEPTH; mm++) { - TT_DATA data = TT_DATA( gen() ); - if ( ll == loop_sel ) { - ddr4_g[mm] = data; - } - sig_i.write( data ); + for (unsigned ww=0,mm=0; ww < word_count; ww++) { + TT_DATA data = TT_DATA( gen() ); + if (ww >= (word_count-DEPTH)) { + ddr4_g[mm++] = data; } + sig_i.write( data ); } // Run DUT: TT_DATA ddr4_o[DEPTH]; - pfa1008_dma_snk_wrapper( ddr4_o, loop_sel, loop_cnt, sig_i ); + unsigned cycle_count = pfa1008_dma_snk_wrapper( ddr4_o, word_count, sig_i ); + std::cout << "cycle_count: " << cycle_count << std::endl; // Check output streams: bool flag = 0; for (int mm=0; mm < DEPTH; mm++) { TT_DATA act_g = ddr4_g[mm]; TT_DATA act_o = ddr4_o[mm]; - flag |= (act_o != act_g); - cout << "mm: " << mm << " act_o: " << act_o << " act_g: " << act_g << endl; + bool this_flag = (act_o != act_g); + flag |= this_flag; + if (this_flag == 1) + cout << "mm: " << mm << " act_o: " << act_o << " act_g: " << act_g << endl; } if ( flag == 0 ) cout << "--- PASSED ---" << endl; else cout << "*** FAILED ***" << endl; diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_dma_src/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_dma_src/Makefile index 6098aa2b7c..622aac778b 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_dma_src/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_dma_src/Makefile @@ -5,6 +5,7 @@ # Author: Mark Rollins DO_COSIM := false +DO_OOCPAR := false ECHO := @echo KERNEL := pfa1008_dma_src_wrapper @@ -27,6 +28,8 @@ ${XO}: ${KERNEL_SRC} ifeq (${DO_COSIM},true) vitis-run --mode hls --config hls.cfg --csim --work_dir ${KERNEL} vitis-run --mode hls --config hls.cfg --cosim --work_dir ${KERNEL} +endif +ifeq (${DO_OOCPAR},true) vitis-run --mode hls --config hls.cfg --impl --work_dir ${KERNEL} endif diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_permute_i/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_permute_i/Makefile index da520f89a0..1d75eb700d 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_permute_i/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_permute_i/Makefile @@ -5,6 +5,7 @@ # Author: Mark Rollins DO_COSIM := false +DO_OOCPAR := false ECHO := @echo KERNEL := pfa1008_permute_i_wrapper @@ -28,6 +29,8 @@ ${XO}: ${KERNEL_SRC} ifeq (${DO_COSIM},true) vitis-run --mode hls --config hls.cfg --csim --work_dir ${KERNEL} vitis-run --mode hls --config hls.cfg --cosim --work_dir ${KERNEL} +endif +ifeq (${DO_OOCPAR},true) vitis-run --mode hls --config hls.cfg --impl --work_dir ${KERNEL} endif diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_permute_o/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_permute_o/Makefile index ca6aafb727..e6395f08e6 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_permute_o/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/hls/pfa1008_permute_o/Makefile @@ -5,6 +5,7 @@ # Author: Mark Rollins DO_COSIM := false +DO_OOCPAR := false ECHO := @echo KERNEL := pfa1008_permute_o_wrapper @@ -28,6 +29,8 @@ ${XO}: ${KERNEL_SRC} ifeq (${DO_COSIM},true) vitis-run --mode hls --config hls.cfg --csim --work_dir ${KERNEL} vitis-run --mode hls --config hls.cfg --cosim --work_dir ${KERNEL} +endif +ifeq (${DO_OOCPAR},true) vitis-run --mode hls --config hls.cfg --impl --work_dir ${KERNEL} endif diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/ps_apps/hw_emu/host.cpp b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/ps_apps/hw_emu/host.cpp index 039fe0408c..58c98c2e33 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/ps_apps/hw_emu/host.cpp +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/ps_apps/hw_emu/host.cpp @@ -4,11 +4,7 @@ // // Author: Mark Rollins -#include "pfa1008_graph.h" - -// Instantiate AIE graph: -pfa1008_graph<18,0> aie_dut; - +#include #include #include #include @@ -33,7 +29,7 @@ typedef int TT_DATA; // Assume cint16 data static constexpr int32_t NUM_ITER = -1; // Let the graph run and have DMA_SNK terminate things static constexpr int32_t LOOP_CNT_I = 8; -static constexpr int32_t LOOP_CNT_O = 6; // Try to stop it early +static constexpr int32_t LOOP_CNT_O = 6; static constexpr int32_t LOOP_SEL = 0; // ID of loop to capture by DDR SNK PL HLS block static constexpr unsigned DEPTH = 1008; // 4 transform x 1008-pt / 4 samples @ 128-bit static constexpr unsigned DDR_WORD_DEPTH_I = DEPTH; @@ -43,6 +39,10 @@ static constexpr unsigned NUM_SAMPLES_O = DDR_WORD_DEPTH_O * 4; // 32-bit (ci static constexpr unsigned DDR_BUFFSIZE_I_BYTES = NUM_SAMPLES_I * 4; // Each sample is 4 bytes (32-bits) static constexpr unsigned DDR_BUFFSIZE_O_BYTES = NUM_SAMPLES_O * 4; // Each sample is 4 bytes (32-bits) +static constexpr double THROUGHPUT_TARGET = 1000; +static constexpr double THROUGHPUT_ERROR_LIMIT = 5; + +static unsigned int word_count = LOOP_CNT_O * NUM_SAMPLES_I / 4; // # of 128-bit words passing through monitor // ------------------------------------------------------------ // Main @@ -88,6 +88,9 @@ int main(int argc, char* argv[]) auto dma_snk = xrt::kernel(my_device, xclbin_uuid, "pfa1008_dma_snk_wrapper:{dma_snk}"); std::cout << STR_PASSED << "auto dma_snk = xrt::kernel(my_device, xclbin_uuid, \"pfa1008_dma_snk_wrapper:{dma_snk}\")" << std::endl; + auto dma_snk_ip = xrt::ip(my_device, xclbin_uuid, "pfa1008_dma_snk_wrapper:{dma_snk}"); + std::cout << STR_PASSED << "auto dma_snk_ip = xrt::ip(my_device, xclbin_uuid, \"pfa1008_dma_snk_wrapper:{dma_snk}\")" << std::endl; + xrt::run dma_src_run = xrt::run(dma_src); std::cout << STR_PASSED << "xrt::run dma_src_run = xrt::run(dma_src)" << std::endl; @@ -142,11 +145,8 @@ int main(int argc, char* argv[]) dma_snk_run.set_arg( 0, dma_snk_bo ); std::cout << STR_PASSED << "dma_snk.run.set_arg( 0, dma_snk_bo )" << std::endl; - dma_snk_run.set_arg( 1, LOOP_SEL ); - std::cout << STR_PASSED << "dma_snk_run.set_arg( 1, LOOP_SEL=" << LOOP_SEL << " )" << std::endl; - - dma_snk_run.set_arg( 2, LOOP_CNT_O ); - std::cout << STR_PASSED << "dma_snk_run.set_arg( 2, LOOP_CNT_O=" << LOOP_CNT_O << " )" << std::endl; + dma_snk_run.set_arg( 1, word_count ); + std::cout << STR_PASSED << "dma_snk_run.set_arg( 1, word_count=" << word_count << " )" << std::endl; // ------------------------------------------------------------ // Start Application @@ -166,6 +166,18 @@ int main(int argc, char* argv[]) dma_snk_run.wait(); std::cout << STR_PASSED << "dma_snk_run.wait()" << std::endl; + // ------------------------------------------------------------ + // Throughput + // ------------------------------------------------------------ + + unsigned cycle_count = dma_snk_ip.read_register(0x10); + std::cout << "cycle_count: " << cycle_count << std::endl; + double throughput_MSPS = (4.0*word_count)/(1.0*cycle_count)*312.5; + std::cout << "Throughput (Msps): " << throughput_MSPS << " vs. Target (Msps): " << THROUGHPUT_TARGET << std::endl; + double tp_err = 100.0*abs(throughput_MSPS-THROUGHPUT_TARGET)/THROUGHPUT_TARGET; + std::cout << "Througput Error (%): " << tp_err << " vs. Error Limit (%): " << THROUGHPUT_ERROR_LIMIT << std::endl; + bool flag_t = (tp_err > THROUGHPUT_ERROR_LIMIT); + // ------------------------------------------------------------ // Retrieve Results // ------------------------------------------------------------ @@ -209,8 +221,16 @@ int main(int argc, char* argv[]) // Done: if ( flag == 0 ) + std::cout << STR_INFO << "--- REGRESSION PASSED ---" << std::endl; + else + std::cout << STR_ERROR << "*** REGRESSION FAILED ***" << std::endl; + if ( flag_t == 0 ) + std::cout << STR_INFO << "--- THROUGHPUT PASSED ---" << std::endl; + else + std::cout << STR_ERROR << "*** THROUGHPUT FAILED ***" << std::endl; + if (flag == 0 && flag_t == 0) std::cout << STR_INFO << "--- PASSED ---" << std::endl; else - std::cout << STR_INFO << "*** FAILED ***" << std::endl; - return(flag); + std::cout << STR_ERROR <<"*** FAILED ***" << std::endl; + return(flag || flag_t); } diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/vitis/system.cfg b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/vitis/system.cfg index 1b7e8633c4..9172043c7e 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/vitis/system.cfg +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/02-Prime-Factor-FFT/vitis/system.cfg @@ -29,7 +29,7 @@ nk = pfa1008_dma_snk_wrapper:1:dma_snk # ------------------------------------------------------------ # LPDDR to PL DMA SOURCE: -sp=dma_src.mem:LPDDR +sp=dma_src.mem:LPDDR1 # PL DMA Source to PL PERMUTE_I sc = dma_src.sig_o:permute_i.sig_i @@ -37,14 +37,14 @@ sc = dma_src.sig_o:permute_i.sig_i # PL PERMUTE_I to AIE DFT-7: sc = permute_i.sig_o:ai_engine_0.PLIO_sig_i -# AIE DFT-16 to PL PERMUTE_O: +# AIE DFT-16 to PERMUTE_O: sc = ai_engine_0.PLIO_sig_o:permute_o.sig_i -# PL PERMUTE_O to PL DMA SINK: +# PERMUTE to PL DMA SINK: sc = permute_o.sig_o:dma_snk.sig_i # PL DMA SINK to LPDDR -sp=dma_snk.mem:LPDDR +sp=dma_snk.mem:LPDDR1 # ------------------------------------------------------------ # Vivado PAR diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/03-AIE-ML-lenet_tutorial/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/03-AIE-ML-lenet_tutorial/Makefile index fa43ae5bd5..0cecf3a4ee 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/03-AIE-ML-lenet_tutorial/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/03-AIE-ML-lenet_tutorial/Makefile @@ -266,7 +266,7 @@ VPP_LINK_FLAGS += --vivado.prop run.synth_1.STEPS.SYNTH_DESIGN.ARGS.CONTROL_SET_ ifeq ($(EN_TRACE),1) ifeq ($(TARGET),hw) VPP_LINK_FLAGS += --profile.data $(DATAMOVER_KERNEL_TOP):all:all - VPP_LINK_FLAGS += --profile.trace_memory LPDDR + VPP_LINK_FLAGS += --profile.trace_memory LPDDR1 endif endif diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/03-AIE-ML-lenet_tutorial/README.md b/AI_Engine_Development/AIE-ML/Design_Tutorials/03-AIE-ML-lenet_tutorial/README.md index 8c9d296d4c..1cfaff277d 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/03-AIE-ML-lenet_tutorial/README.md +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/03-AIE-ML-lenet_tutorial/README.md @@ -15,7 +15,7 @@ # Versal AI Engine-ML LeNet Tutorial -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents @@ -41,12 +41,10 @@ This tutorial uses the LeNet algorithm to implement a system-level design to per The tutorial takes you through hardware emulation and hardware flow in the context of a complete Versal adaptive SoC system integration. A Makefile is provided that you can modify to suit your needs in a different context. -
- Objectives - ### Objectives After completing the tutorial, you should be able to: + * Build a complete system design by going through the various steps in the AMD Vitis™ unified software platform flow, including creating the AI Engine-ML Adaptive Data Flow (ADF) API graph, compiling the A72 host application and compiling PL kernels, using the Vitis compiler (V++) to link the AI Engine-ML and HLS kernels with the platform, and packaging the design. You will also be able to run the design through the hardware emulation and hardware flow in a mixed System C/RTL cycle-accurate/QEMU-based simulator. * Develop an understanding of Convolutional Neural Network (CNN) layer details using the LeNet algorithm and how the layers are mapped into data processing and compute blocks. * Develop an understanding of the kernels developed in the design; AI Engine-ML kernels to process fully connected convolutional layers and PL kernels to process the input rearrange and max pool and rearrange functions. @@ -56,12 +54,11 @@ After completing the tutorial, you should be able to: * Develop an understanding of graph control APIs to enable run-time updates using the run-time parameter (RTP) interface. * Develop an understanding of performance measurement and functional/throughput debug at the application level. -
-
Tutorial Overview ## Tutorial Overview + In this application tutorial, the LeNet algorithm is used to perform image classification on an input image using five AI Engine-ML tiles and PL resources, including block RAM. A top-level block diagram is shown in the following figure. An image is loaded from DDR memory through the Network on Chip (NoC) to block RAM and then to the AI Engine-ML. The PL input pre-processing unit receives the input image and sends the output to the first AI Engine-ML tile to perform matrix multiplication. The output from the first AI Engine-ML tile goes to a PL unit to perform the first level of max pool and data rearrangement (M1R1). The output is fed to the second AI Engine-ML tile and the output from that tile is sent to the PL to perform the second level max pooling and data rearrangement (M2R2). The output is then sent to a fully connected layer (FC1) implemented in two AI Engine-ML tiles and uses the rectified linear unit layer (ReLu) as an activation function. The outputs from the two AI Engine-ML tiles are then fed into a second fully connected layer implemented in the `core04` AI Engine-ML tile. The output is sent to a data conversion unit in the PL and then to the DDR memory through the NoC. In between the AI Engine-ML and PL units is a datamover module (refer to the LeNet Controller in the following figure) that contains the following kernels: * `mm2s`: a memory-mapped to stream kernel to feed data from DDR memory through the NoC to the AI Engine-ML Array. * `s2mm`: a stream to memory-mapped kernel to feed data from the AI Engine-ML Array through NoC to DDR memory. @@ -124,9 +121,9 @@ Tools Documentation: To build and run the LeNet tutorial,the following tools should be downloaded/installed: -* Install the [Vitis Software Platform 2025.1](https://docs.amd.com/r/en-US/ug1701-vitis-accelerated-embedded/Vitis-Software-Platform-Installation) +* Install the [Vitis Software Platform 2025.2](https://docs.amd.com/r/en-US/ug1701-vitis-accelerated-embedded/Vitis-Software-Platform-Installation) -* Obtain a license to enable Beta Devices in AMD tools (to use the `xilinx_vek280_es1_base_202510_1` platform) +* Obtain a license to enable Beta Devices in AMD tools (to use the `xilinx_vek280_es1_base_202520_1` platform) * Obtain licenses for AI Engine-ML tools @@ -136,6 +133,7 @@ To build and run the LeNet tutorial,the following tools should be downloaded/ins Environment: Setting Up the Shell Environment ## Environment: Setting Up the Shell Environment + When the elements of the Vitis software platform are installed, update the shell environment script. Set the environment variables to your system-specific paths. Edit `sample_env_setup.sh` script with your file paths: @@ -166,7 +164,7 @@ platforminfo --list | grep -m 1 -A 9 vek280_es1_base ``` Output of the above command should be as follows: ```bash -"baseName": "xilinx_vek280_es1_base_202510_1", +"baseName": "xilinx_vek280_es1_base_202520_1", "version": "1.0", "type": "sdsoc", "dataCenter": "false", @@ -225,7 +223,7 @@ make run TARGET=hw_emu make kernels: Compile PL Kernels ### make kernels: Compile PL Kernels -In this step, the Vitis compiler takes any Vitis compiler kernels (RTL or HLS C) in the PL region of the target platform (`xilinx_vek280_es1_base_202510_1`) and the AI Engine-ML kernels and graph and compiles them into their respective XO files. In this design, the `dma_hls` kernel is compiled as an XO file and the `Lenet_kernel` has already been pre-compiled as an XO file. You can access the source code by unzipping the XO file. +In this step, the Vitis compiler takes any Vitis compiler kernels (RTL or HLS C) in the PL region of the target platform (`xilinx_vek280_es1_base_202520_1`) and the AI Engine-ML kernels and graph and compiles them into their respective XO files. In this design, the `dma_hls` kernel is compiled as an XO file and the `Lenet_kernel` has already been pre-compiled as an XO file. You can access the source code by unzipping the XO file. `unzip lenet_kernel.xo` @@ -244,7 +242,7 @@ mkdir -p ./build/hw_emu cd ./build/hw_emu v++ --target hw_emu \ - --platform xilinx_vek280_es1_base_202510_1 \ + --platform xilinx_vek280_es1_base_202520_1 \ --save-temps \ --temp_dir _x \ --verbose \ @@ -344,7 +342,7 @@ The expanded command is as follows: cd ./build/hw_emu; v++ -l \ - --platform xilinx_vek280_es1_base_202510_1 \ + --platform xilinx_vek280_es1_base_202520_1 \ --save-temps \ --temp_dir _x \ --verbose \ @@ -364,7 +362,7 @@ If EN_TRACE=1, the command is expanded as follows: cd ./build/hw; v++ -l \ - --platform xilinx_vek280_es1_base_202510_1 \ + --platform xilinx_vek280_es1_base_202520_1 \ --save-temps \ --temp_dir _x \ --verbose \ @@ -438,31 +436,31 @@ or aarch64-linux-gnu-g++ -O \ -c \ -D__linux__ \ - --sysroot=$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-xilinx-linux \ + --sysroot=$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-xilinx-linux \ -DXAIE_DEBUG \ - -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-xilinx-linux/usr/include/xrt \ + -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-xilinx-linux/usr/include/xrt \ -I $(XILINX_VITIS_AIETOOLS)/include \ - -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-xilinx-linux/usr/include \ - -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-xilinx-linux/usr/lib \ + -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-xilinx-linux/usr/include \ + -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-xilinx-linux/usr/lib \ ../build//Work/ps/c_rts/aie_control_xrt.cpp \ -o ../build/app_control.o aarch64-linux-gnu-g++ -O \ -c \ -D__linux__ \ - --sysroot=$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-xilinx-linux \ + --sysroot=$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-xilinx-linux \ -DXAIE_DEBUG \ - -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-xilinx-linux/usr/include/xrt \ + -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-xilinx-linux/usr/include/xrt \ -I $(XILINX_VITIS_AIETOOLS)/include \ - -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-xilinx-linux/usr/include \ - -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-xilinx-linux/usr/lib \ + -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-xilinx-linux/usr/include \ + -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-xilinx-linux/usr/lib \ ../design/aie_src/main.cpp \ -o ../build/lenet_app.o aarch64-linux-gnu-g++ ./build/app_control.o \ ./build/lenet_app.o \ - --sysroot=$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-xilinx-linux \ - -L$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-xilinx-linux/usr/lib\ + --sysroot=$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-xilinx-linux \ + -L$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-xilinx-linux/usr/lib\ -L$(XILINX_VITIS_AIETOOLS)/lib/aarch64.o \ -L$(XILINX_VITIS_AIETOOLS)/lib/lnx64.o \ -ladf_api_xrt \ @@ -515,10 +513,10 @@ v++ -p \ -t hw_emu \ --save-temps \ --temp_dir ./build/hw_emu/_x \ - -f xilinx_vek280_es1_base_202510_1 \ + -f xilinx_vek280_es1_base_202520_1 \ --package.sd_dir $(PLATFORM_REPO_PATHS)/sw/versal/xrt \ - --package.rootfs $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/rootfs.ext4 \ - --package.kernel_image $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/Image \ + --package.rootfs $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/rootfs.ext4 \ + --package.kernel_image $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/Image \ --package.boot_mode=sd \ --package.out_dir ./build/hw_emu/package \ --package.sd_dir ./design/aie_src/aiesim_data \ @@ -542,10 +540,10 @@ v++ -p \ -t hw_emu \ --save-temps \ --temp_dir ./build/hw_emu/_x \ - -f xilinx_vek280_es1_base_202510_1 \ + -f xilinx_vek280_es1_base_202520_1 \ --package.sd_dir $(PLATFORM_REPO_PATHS)/sw/versal/xrt \ - --package.rootfs $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/rootfs.ext4 \ - --package.kernel_image $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/Image \ + --package.rootfs $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/rootfs.ext4 \ + --package.kernel_image $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/Image \ --package.boot_mode=sd \ --package.out_dir ./build/hw_emu/package \ --package.sd_dir ./design/aie_src/aiesim_data \ @@ -572,8 +570,8 @@ cd ../../; |Inputs Sources|Description| | --- | --- | |$(PLATFORM_REPO_PATHS)/sw/versal/xrt|The PS host application needs the XRT headers in this folder to execute.| -|$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/rootfs.ext4|The root filesystem file for Petalinux.| -|$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/Image|The pre-built Petalinux Image the processor boots from.| +|$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/rootfs.ext4|The root filesystem file for Petalinux.| +|$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/Image|The pre-built Petalinux Image the processor boots from.| |design/aie_src/aiesim_data|The data folder that contains the input data stored in DDR memory. It also contains the output golden refernece data the PS host application uses to verify the output data from the AI Engine-ML.| |build/hw_emu/lenet_aie_xrt.elf|The PS host application executabled created in the `make application` step.| |build/hw_emu/vek280_aie_lenet.hw_emu.xsa|The XSA file created in the `make xsa` step.| @@ -605,12 +603,12 @@ cd ./build/hw_emu/package ``` When launched, you will see the QEMU simulator load. Wait for the autoboot countdown to go to zero, and after a few minutes, you will see the root Linux prompt display: ```bash -root@versal-rootfs-common-2025_1:~# +root@versal-rootfs-common-2025_2:~# ``` In some cases, the following error might display: ``` -root@versal-rootfs-common-2025_1:~## xinit: giving up +root@versal-rootfs-common-2025_2:~## xinit: giving up xinit: unable to connect to X server: Connection refused xinit: server error Enabling notebook extension jupyter-js-widgets/extension... @@ -673,7 +671,7 @@ Transmit delay: 0 msec/char 0 msec/line **Step 7.** Power on the board. -**Step 8.** Wait until you see the `root@versal-rootfs-common-2025_1` Linux command prompt. Press enter a few times to get past any `xinit` errors. +**Step 8.** Wait until you see the `root@versal-rootfs-common-2025_2` Linux command prompt. Press enter a few times to get past any `xinit` errors. **Step 9.** Run the following commands into the TeraTerm terminal: @@ -999,7 +997,7 @@ auto in_bomapped = reinterpret_cast(xrtBOMap(in_bohdl)); Additionally, the `memcpy` and `memset` functions are used to initialize the data in global memory. #### 5. Open Graph, Obtain Handle, and Execute Graph -The following registration function was added in 2025.1 for XRT to use ADF API callbacks: +The following registration function was added in 2025.2 for XRT to use ADF API callbacks: `adf::registerXRT(dhdl, top->m_header.uuid);` @@ -1069,7 +1067,7 @@ Throughput = (no of images / Processing time) ``` ## Power Measurement Details -Power is measured using vcdanalyze and Xilinx Power Estimator (XPE) for Versal (2025.1 version) tools. +Power is measured using vcdanalyze and Xilinx Power Estimator (XPE) for Versal (2025.2 version) tools. The vcdanalyze tool is used to generate a `graph.xpe` file, which can be an input to XPE for viewing the AI Engine-ML resource utilization and power. The steps are as follows: @@ -1083,7 +1081,7 @@ vcdanalyze --vcd x$(VCD_FILE_NAME).vcd --xpe ``` -2. If you do not already have it installed, download and install [PDM for Versal Version 2025.1](https://www.xilinx.com/products/design-tools/power-design-manager.html). For full documentation of PDM, see [this page](https://docs.amd.com/r/en-US/ug1556-power-design-manager). +2. If you do not already have it installed, download and install [PDM for Versal Version 2025.2](https://www.xilinx.com/products/design-tools/power-design-manager.html). For full documentation of PDM, see [this page](https://docs.amd.com/r/en-US/ug1556-power-design-manager). 3. Create the project and choose the default part as XCVE2802-VSVH1760-2MP-E-S. @@ -1096,7 +1094,7 @@ A summary of resource utilization and power is given in the following table. | Number of Compute Cores|Vector Load|Number of Active Memory Banks|Mem R/W Rate|Memory Tiles|Memory Tile Memory Banks|Memory Tile Memory R/W Rate|AIE-ML Mem Tiles|Interconnect Load|Dynamic Power
(in W)| |:----------------------:|:---------:|:---------------------------:|:----------:|:----------:|:----------------------:|:-------------------------:|:--------------:|:---------------:|:-----------------------| -| 5 | 31.61% | 60 | 16.05% | 4 | 12 | 20.00% | 4 | 11.04% | 1.116 | +| 5 | 31.62% | 58 | 16.30% | 4 | 12 | 20.00% | 4 | 11.04% | 1.116 | ## Note diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/03-AIE-ML-lenet_tutorial/description.json b/AI_Engine_Development/AIE-ML/Design_Tutorials/03-AIE-ML-lenet_tutorial/description.json index 9225a32127..e20c440517 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/03-AIE-ML-lenet_tutorial/description.json +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/03-AIE-ML-lenet_tutorial/description.json @@ -13,8 +13,7 @@ "pre_exec": "./env_setup_versal.sh" }, "board": { - "pre_exec": "./env_setup_versal.sh", - "post_exec": "./addon/copy_perf_files.sh" + "pre_exec": "./env_setup_versal.sh" } }, "user": { @@ -51,7 +50,6 @@ "all": "run", "hw": "sd_card" }, - "custom_board_target": "run_test", - "customized_params": "multi_params.json" + "custom_board_target": "run_test" } } diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/03-AIE-ML-lenet_tutorial/sample_env_setup.sh b/AI_Engine_Development/AIE-ML/Design_Tutorials/03-AIE-ML-lenet_tutorial/sample_env_setup.sh index 5cd111d22a..d75e7632e3 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/03-AIE-ML-lenet_tutorial/sample_env_setup.sh +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/03-AIE-ML-lenet_tutorial/sample_env_setup.sh @@ -6,9 +6,9 @@ # ======================================================= # Set Platform ,Vitis and Versal Image repo # ======================================================= -export PLATFORM_REPO_PATHS= -export XILINX_VITIS = /2025.1 -export COMMON_IMAGE_VERSAL= +export PLATFORM_REPO_PATHS= +export XILINX_VITIS = /2025.2 +export COMMON_IMAGE_VERSAL= # ==================================================== # Source Versal Image ,Vitis and Aietools @@ -20,7 +20,7 @@ source $XILINX_VITIS/settings64.sh # ========================================================= # Platform Selection... # ========================================================= -tgt_plat=xilinx_vek280_base_202510_1 +tgt_plat=xilinx_vek280_base_202520_1 export PLATFORM=$PLATFORM_REPO_PATHS/$tgt_plat/$tgt_plat\.xpfm # ========================================================== diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/04-AIE-API-based-FFT-for-many-instances-applications/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/04-AIE-API-based-FFT-for-many-instances-applications/Makefile index 5806e40462..fc563d7be1 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/04-AIE-API-based-FFT-for-many-instances-applications/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/04-AIE-API-based-FFT-for-many-instances-applications/Makefile @@ -8,7 +8,7 @@ ECHO = @echo ################################################################################ # Variables needed for AMD tools version checking, PLEASE DO NOT MODIFY # ################################################################################ -REQUIRED_VERSION = 2025.1 +REQUIRED_VERSION = 2025.2 VITIS_VERSION := $(shell vitis -version 2>/dev/null | grep "Vitis " | sed 's/\*//g') ############## diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/04-AIE-API-based-FFT-for-many-instances-applications/README.md b/AI_Engine_Development/AIE-ML/Design_Tutorials/04-AIE-API-based-FFT-for-many-instances-applications/README.md index cee5e6cd2e..ff3fafb4fe 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/04-AIE-API-based-FFT-for-many-instances-applications/README.md +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/04-AIE-API-based-FFT-for-many-instances-applications/README.md @@ -15,15 +15,15 @@ # AIE API based FFT for Many Instances Applications on AIE-ML -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction This tutorial intends to show how to design a complex Digital Signal Processing application using the AI Engine ML with its exclusive features through Vitis Unified IDE. In the tutorial the GUI flow is used. Moreover, Python scripts are provided to automate project creation and build. To run such Python scripts, first set up your `PLATFORM_REPO_PATHS` environment variable to `$XILINX_VITIS/base_platforms`, then clone this repository, locate inside it, and run the following commands: -- ``vitis -s Step1_3Dbuf.py`` to automate the first hands-on part of the tutorial. -- ``vitis -s Step2_4Dbuf.py`` to automate the second hands-on part of the tutorial. +- `vitis -s Step1_3Dbuf.py` to automate the first hands-on part of the tutorial. +- `vitis -s Step2_4Dbuf.py` to automate the second hands-on part of the tutorial. ### Table of Contents @@ -80,7 +80,7 @@ To thoroughly understand the content of this tutorial, it is necessary to know a For further information, please refer to the following documentation: - [AI Engine-ML Kernel and Graph Programming Guide (UG1603)](https://docs.amd.com/r/en-US/ug1603-ai-engine-ml-kernel-graph) -- [AI Engine API User Guide (UG1529)](https://www.xilinx.com/htmldocs/xilinx2025_1/aiengine_api/aie_api/doc) +- [AI Engine API User Guide (UG1529)](https://www.xilinx.com/htmldocs/xilinx2025_2/aiengine_api/aie_api/doc) - [AI Engine Tools and Flows User Guide (UG1076)](https://docs.amd.com/r/en-US/ug1076-ai-engine-environment) - [Versal Adaptive SoC AIE-ML Architecture Manual (AM020)](https://docs.amd.com/r/en-US/am020-versal-aie-m) - [Versal Adaptive SoC Technical Reference Manual (AM011)](https://docs.amd.com/r/en-US/am011-versal-acap-trm) @@ -150,7 +150,7 @@ The resulting system follows the diagram shown in figure 1, where 128 instances In this section it is explained the rationale of the kernel and graph implementation, that has been done following the coding guidelines found in: - [AI Engine-ML Kernel and Graph Programming Guide (UG1603)](https://docs.amd.com/r/en-US/ug1603-ai-engine-ml-kernel-graph) -- [AI Engine API User Guide (UG1529)](https://www.xilinx.com/htmldocs/xilinx2025_1/aiengine_api/aie_api/doc) +- [AI Engine API User Guide (UG1529)](https://www.xilinx.com/htmldocs/xilinx2025_2/aiengine_api/aie_api/doc) ### Designing the Kernel with the AI Engine API @@ -224,7 +224,7 @@ The file structure of choice to write the kernels is: ##### Twiddles Header File The first header file, that contains all the twiddle factor entries, is a rather long file. Because of the regular structure of the code, and because the mathematical formula to compute the twiddles is well known, the better choice is to generate the header file using a script. -The twiddle generation script, written in Python following the [AIE API](https://www.xilinx.com/htmldocs/xilinx2025_1/aiengine_api/aie_api/doc/group__group__fft.html) guidelines, along with an explanation of its functionalities can be found in the [support twiddles folder](./support/twiddles/) of this repository. +The twiddle generation script, written in Python following the [AIE API](https://www.xilinx.com/htmldocs/xilinx2025_2/aiengine_api/aie_api/doc/group__group__fft.html) guidelines, along with an explanation of its functionalities can be found in the [support twiddles folder](./support/twiddles/) of this repository. In particular, the defined twiddles vectors are organized with two subscripts, the first indicating the FFT stage, and the second indicating the stage entry. Thus for instance, the third entry of the fifth stage of a radix-4 FFT stage will be named *TWID4_2*. Because this project is about a radix-4 staged implementation, the generated header file contains 15 twiddle tables, three per each of the five stages. @@ -601,31 +601,32 @@ To create the AIE-ML project in Vitis Unified IDE, follow those steps: 1. Clone this repository. 2. Open Vitis Unified IDE. 3. Select "Set Workspace" and choose a folder for the project. -4. Create a new AI engine component by either clicking on "Create Component" under the "AI Engine Graph Development" menu, or opening the "File" → "New Component" menu, and clicking on AI Engine, as shown in the following figure. +4. Create a new AI engine component by either clicking on "New AI Engine Component" under the "AI Engine Graph Development" menu, or opening the "File" → "New Component" menu, and clicking on AI Engine, as shown in the following figure. ![AI Engine Component Creation in Vitis Unified IDE](./images/2_1_Vitis.png) > *Fig. 4*: AI Engine Component Creation in Vitis Unified IDE -5. Select the project name and component director and press "next". +5. Select the project name and component directory and press "next". 6. Select "Add folder" and import the `src` folder of this repository. Make sure that `fft1k_128_graph.cpp` is the top-level file and press "next". - ![AIE Component Creation - Source Files Selection](./images/2_2_Vitis.png) - > *Fig. 5*: AIE Component Creation - Source Files Selection + ![AIE Component Creation - Source Files Selection](./images/2_2_Vitis.png) + > *Fig. 5*: AIE Component Creation - Source Files Selection 7. When chosing the hardware, select the VEK280 board-based platform, as shown in the following figure, and press "next", and then "finish". ![AIE Component Creation - Platform Selection](./images/2_3_Vitis.png) > *Fig. 6*: AIE Component Creation - Platform Selection -8. Open the compiler configuration clicking on ```aiecompiler.cfg``` under the AI Engine Component's setting folder on the left hand side of the GUI, then click on AI Engine and set the PL frequency to 500MHz, as decided in the design phase of the tutorial. +8. Open the compiler configuration clicking on `aiecompiler.cfg` under the AI Engine Component's setting folder on the left hand side of the GUI, then click on AI Engine and set the PL frequency to 500MHz, as decided in the design phase of the tutorial. ![Selecting the Programmable Logic Frequency in the AI Engine Compile Settings](./images/2_4_Vitis.png) > *Fig. 7*: Selecting the Programmable Logic Frequency in the AI Engine Compile Settings ### x86 Simulation and Functional Validation 1. Build the x86 simulation for the graph by clicking "Build" under the "X86 SIMULATION" tab on the "FLOW" menu located on the bottom left corner of the GUI. -2. Open the ```launch.json``` simulation configuration file under the "settings" folder of the workspace. +2. Open the `launch.json` simulation configuration file under the "settings" folder of the workspace. 3. Create a new x86 simulation by clicking on "New Launch Configuration", and then "x86sim". -4. Run the simulation by clicking "Run" under the "X86 SIMULATION" tab in the "FLOW" menu. This functional simulation takes the input data from the text files present in the ```./src/verif_i_128```, that represent the 16 PLIOs. - > **Note**: By default the input data is a set of three rectangular waves per each instance. Those files can be replaced the text files present in the three folders in the ``verification/v_inputs`` folder to test also random signals. -5. Check the execution outputs under the ``Output/x86sim/x86simulator_output/verif_o_128`` in the GUI, as shown in the following figure. +4. Run the simulation by clicking "Run" under the "X86 SIMULATION" tab in the "FLOW" menu. This functional simulation takes the input data from the text files present in the `./src/verif_i_128`, that represent the 16 PLIOs. + >**Note**: By default the input data is a set of three rectangular waves per each instance. Those files can be replaced the text files present in the three folders in the `verification/v_inputs` folder to test also random signals. +5. Check the execution outputs under the `Output/x86sim/x86simulator_output/verif_o_128` in the GUI, as shown in the following figure. ![Visualizing the x86 Simulation Output Files](./images/2_5_Vitis.png) + > *Fig. 8*: Visualizing the x86 Simulation Output Files 6. Perform a functional verification using the Python script in the `support/verification` folder of this repository. - - This script analyzes the text files inside the `v_inputs` and `v_outputs` folder and creates some functional verification charts. + - This script analyzes the text files inside the "v_inputs" and "v_outputs" folder and creates some functional verification charts. For more information refer to [this document](./support/verification/Readme.md). - If you did not modify the input files, you can just run the `Basic_verification` Python script with the following terminal command, while being located into the `support/verification` directory: `python -i ./Basic_verification`. - If you replaced the simulator input files, replace also the text files inside the `support/verification/v_inputs` folder with the ones you used, keeping the same names. Then, copy the output files from `[project-folder]/build/x86sim/x86simulato_output/verif_o_128` into the `support/verification/v_outputs` folder and run the python script with the aforementioned command. @@ -633,21 +634,24 @@ To create the AIE-ML project in Vitis Unified IDE, follow those steps: Note that, since this is a fixed point implementation and Numpy performs the FFT with a float datatype, the error could spike when the transform approaches zero. ![Validation Script Graph](./images/2_6_1_Vitis.png) ![Validation Script Graph](./images/2_6_2_Vitis.png) - + > *Fig. 9*: Validation Script Graphs ### AI Engine Simulation, Array and Trace Analysis 1. Build the Hardware project for the graph by clicking on "Build" under the "AIE SIMULATOR / HARDWARE" tab on the "FLOW" menu located on the bottom left corner of the GUI. 2. When the build finishes, under the "REPORTS" tab in the "FLOW" menu, click "array" and check the AI Engine utilization. Observe in particular the mapping and routing for the 64 kernels and of the shared buffers. ![Vitis AI Engine array view of the implemented graph](./images/2_7_Vitis.png) -3. Create a new "AIESim" run in the `launch.json` file, by clicking on the "+" ("Add Configuration") icon at the top of the interface. + > *Fig. 10*: Vitis AI Engine array view of the implemented graph +3. Create a new "AIESim" run in the `launch.json` file, by clicking on the "+" ("Add Configuration") icon at the top of the interface. 4. Enable tracing for the simulation, selecting the "aiesim" run and clicking "Enable Trace". ![Creating a new run and enabling trace for AI Engine simulation](./images/2_8_Vitis.png) + > *Fig. 11*: Creating a new run and enabling trace for AI Engine simulation 5. Run the AI Engine simulation by clicking "Run" under the "AIE SIMULATOR / HARDWARE" tab on the "FLOW" menu. 6. When the simulation ends, open the Trace reports and collapse all the signals, as shown in the following figure. ![Opening and analyzing the AIE simulator trace report](./images/2_9_Vitis.png) + > *Fig. 12*: Opening and analyzing the AIE simulator trace report -> **Note**: The kernels are running for less than 25% of the time, being locked for the remaining time. Moreover, the memory tiles are almost empty because each shared buffer serves four kernels, thus the shared buffer mapping to the memory tiles is highly port-limited. +Observe that the kernels are running for less than 25% of the time, being locked for the remaining time. Moreover, the memory tiles are almost empty because each shared buffer serves four kernels, thus the shared buffer mapping to the memory tiles is highly port-limited. Considering the previous validation steps, it can be concluded that the design is functionally correct, but a further optimization can be performed. Indeed, because the AIE-ML is much faster than the data rate, the computation can be serialized, reducing utilization and power consumption. To look into the optimization step, see the final step of this tutorial. @@ -663,7 +667,7 @@ To do so, a further dimension that represents time, can be added for the shared The resulting code restructuring is minimal and involves the aforementioned reshaping of the shared buffer tensor though a new parameter $\text{KER\\_ILV}$, that expresses the number of times that a kernel must run during the acquisition time, at steady state. The $\text{KER\\_ILV}$ parameter effectively counteracts the $\text{IO\\_ILV}$ effect, decoupling the spatial-temporal interleaving done for the IOs and the one done inside the AIE-ML, enabling seralization. -The graph header file ``fft1k_128_new_graph.h`` contains the new modified code. Note that the only changes done to the code are the following: +The graph header file `fft1k_128_new_graph.h` contains the new modified code. Note that the only changes done to the code are the following: - The shared buffer now has four dimensions: the time dimesion has been added as the third one, and the dimension of the samples (previously the third) is now the fourth. - Every time that $\text{IO\\_ILV}$ appears in the code, it has to be divided by $\text{KER\\_ILV}$. @@ -699,31 +703,40 @@ In the following code block shows an excerpt of the third loop. Note the differe } ``` -To use the new graph, open the ``"fft1k_128_graph.cpp"`` graph source code file and change the first line: - ``#include "fft1k_128_graph.h"`` with ``#include "fft1k_128_new_graph.h"`` +To use the new graph, open the `"fft1k_128_graph.cpp"` graph source code file and change the first line: + `#include "fft1k_128_graph.h"` with `#include "fft1k_128_new_graph.h"` ### x86 Simulation and Functional Validation The steps for building and verifying the project are the same as those for the second part of the tutorial. 1. Build the x86 simulation for the graph by clicking "Build" under the "X86 SIMULATION" tab on the "FLOW" menu located on the bottom left corner of the GUI. -2. Make sure that all the required verification text files are under the ``./src/verif_i_128`` folder, and run the simulation by clicking "Run", under the same tab of the previous step. -3. Copy the graph's outputs text files in the ``Output/x86sim/x86simulator_output/verif_o_128`` folder and paste them into the ``support\verification\v_outputs`` folder to make sure that the verification Python script works on the new output data. -4. Run the Python verification script while being located into the ```support/verification``` directory with the following command ```python -i ./Basic_verification``` and make sure that the results are correct. +2. Make sure that all the required verification text files are under the `./src/verif_i_128` folder, and run the simulation by clicking "Run", under the same tab of the previous step. +3. Copy the graph's outputs text files in the `Output/x86sim/x86simulator_output/verif_o_128` folder and paste them into the `support\verification\v_outputs` folder to make sure that the verification Python script works on the new output data. +4. Run the Python verification script while being located into the `support/verification` directory with the following command `python -i ./Basic_verification` and make sure that the results are correct. ### AI Engine Simulation, Array and Trace analysis The steps for building the hardware and analyzing the reports are the as those for the second part of the tutorial. +An optional step for enhancing the AI Engine compiler's placement is to make use of the *UtilOpt* option. +To do so, open the `aiecompiler.cfg` file under the AI Engine Component's setting folder on the left hand side of the GUI, click on Miscellaneous Chess and add `enableUtilOpt` under the Mapper options, as shown in the figure below. +![Enhancing graph placement with the enableUtilOpt mapper option](./images/3_0_Vitis.png) +> *Fig. 13*: Enhancing graph placement with the enableUtilOpt mapper option + 1. Build the Hardware project for the graph by clicking "Build" under the "AIE SIMULATOR / HARDWARE" tab on the "FLOW" menu located on the bottom left corner of the GUI. 2. When the build finishes, under the reports in the "FLOW" menu, click "array" and check the AI Engine utilization. Observe that the number of kernels is 16 instead of 64, and that there are six well-filled memory tiles, instead of 23 mostly empty. Note that this great reduction in utilization also translates to a huge reduction in dynamic power. ![4D Buffer Implementation's AI Engine Array Report](./images/3_1_Vitis.png) -3. Enable tracing for the simulation by opening the ```launch.json``` configuration file, selecting the "aiesim" run and clicking "Enable Trace". If you modified the ``launch.json`` settings in the second part of the tutorial, skip this step. + > *Fig. 14*: 4D Buffer Implementation's AI Engine Array Report +3. Enable tracing for the simulation by opening the `launch.json` configuration file, selecting the "aiesim" run and clicking "Enable Trace". If you modified the `launch.json` settings in the second part of the tutorial, skip this step. 4. Launch the AIE simulation by clicking "Run" under the "AIE SIMULATOR / HARDWARE" tab on the "FLOW" menu. 5. When the simulation ends, open the Trace reports and collapse all the signals. - > **Note**: The kernels are now running for more than 90% of the time at steady state, as expected. - ![4D buffer Implementation's Trace Report](./images/3_2_Vitis.png) + +Now observe that the kernels are running for more than 90% of the time at steady state, as expected. + +![4D buffer Implementation's Trace Report](./images/3_2_Vitis.png) +> *Fig. 15*: 4D buffer Implementation's Trace Report ## Support diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/04-AIE-API-based-FFT-for-many-instances-applications/Step1_3Dbuf.py b/AI_Engine_Development/AIE-ML/Design_Tutorials/04-AIE-API-based-FFT-for-many-instances-applications/Step1_3Dbuf.py index 49ae216bec..77015cbcbe 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/04-AIE-API-based-FFT-for-many-instances-applications/Step1_3Dbuf.py +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/04-AIE-API-based-FFT-for-many-instances-applications/Step1_3Dbuf.py @@ -9,7 +9,7 @@ # Current directory and various path variables cwd = os.getcwd()+'/' -vek280_base = os.environ.get('PLATFORM_REPO_PATHS') + '/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm' +vek280_base = os.environ.get('PLATFORM_REPO_PATHS') + '/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm' my_workspace = cwd + 'AIEML_API_FFT_Tutorial' sources = cwd + 'src/' diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/04-AIE-API-based-FFT-for-many-instances-applications/Step2_4Dbuf.py b/AI_Engine_Development/AIE-ML/Design_Tutorials/04-AIE-API-based-FFT-for-many-instances-applications/Step2_4Dbuf.py index 900f2fba57..22d9316a20 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/04-AIE-API-based-FFT-for-many-instances-applications/Step2_4Dbuf.py +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/04-AIE-API-based-FFT-for-many-instances-applications/Step2_4Dbuf.py @@ -9,7 +9,7 @@ # Current directory and various path variables cwd = os.getcwd()+'/' -vek280_base = os.environ.get('PLATFORM_REPO_PATHS') + '/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm' +vek280_base = os.environ.get('PLATFORM_REPO_PATHS') + '/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm' my_workspace = cwd + 'AIEML_API_FFT_Tutorial' sources = cwd + 'src/' @@ -28,6 +28,7 @@ # Updating the configuration file aiecomp_cfg = client.get_config_file(fft_component.component_location+'/aiecompiler.cfg') aiecomp_cfg.set_value(section='aie', key='pl-freq', value="500") +aiecomp_cfg.set_value(section='aie', key='Xmapper', value="enableUtilOpt") # Updating the graph file #______________________________________________________________________________ diff --git 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a/AI_Engine_Development/AIE-ML/Design_Tutorials/04-AIE-API-based-FFT-for-many-instances-applications/images/3_2_Vitis.png and b/AI_Engine_Development/AIE-ML/Design_Tutorials/04-AIE-API-based-FFT-for-many-instances-applications/images/3_2_Vitis.png differ diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/05-Softmax-Function/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/05-Softmax-Function/Makefile index 8356047e57..ea5de18f37 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/05-Softmax-Function/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/05-Softmax-Function/Makefile @@ -8,9 +8,9 @@ ECHO = @echo export TARGET = hw_emu -RELEASE=2025.1 +RELEASE=2025.2 BOARD=vek280 -BASE_NUM=202510_1 +BASE_NUM=202520_1 # Platform Selection... VERSAL_VITIS_PLATFORM = xilinx_${BOARD}\_base_${BASE_NUM} diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/05-Softmax-Function/README.md b/AI_Engine_Development/AIE-ML/Design_Tutorials/05-Softmax-Function/README.md index 9f5108fa69..fe6ee5b156 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/05-Softmax-Function/README.md +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/05-Softmax-Function/README.md @@ -15,7 +15,7 @@ # Softmax Function -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents @@ -31,9 +31,8 @@ [Support](#support) - - ## Introduction + Machine Learning is pervasive in just about any modern application. Whereas machine learning tends to infer processing of structured data, the sub-class of deep learning is often applied to unstructured data where more abstraction is required to extract significant features from a data set. Some applications that have proven to benefit from the application of deep learning are natural language processing and image classification, where the relationship between input data and desired output can be exceedingly complex. Deep learning solutions are often created in the form of a neural network, as depicted in the following figure. @@ -77,7 +76,9 @@ $$ which is attractive because no division is required. However, it has been shown that in practice this formula tends to produce larger computational errors [[1]]. ## Computing the Exponential Function + ### IEEE 754 Format Trick + In addition to basic arithmetic operations, softmax computation depends on efficient evaluation of the exponential function. While there are several ways to accomplish this, an attractive alternative is to estimate the exponential function using a trick based on IEEE 754 floating-point format [[2]]. A double-precision, floating-point number represented by IEEE 754 format is shown in the following figure. ![figure3](images/ieee754_format.png) @@ -95,6 +96,7 @@ $$ A factor of $2^{20}$ represents a binary shift necessary to align with the exponent field of the IEEE 754 format. Residual mantissa bits help provide a degree of interpolation between exponent values. The parameter $C$ is a correction factor meant to mitigate estimation error. It was found that a value of $C=60801$ minimizes RMS error [[2]]. This estimation method might be adapted for other variations of floating-point number representations, such as bfloat16 data type. ### Improving Accuracy + While this trick is computationally very efficient, it can result in an estimation error as large as ~4% of the true value. To reclaim lost accuracy, a method was proposed in [[3]] where all 64 bits are used in computation and a correction function $F$ is defined. To derive the solution, begin by expressing the exponential function in the form $$ @@ -112,6 +114,7 @@ $$ as a 64-bit signed integer then reinterpreting the result as a double-precision floating-point value. Since all 64 bits are used, a factor $2^{52}$ is necessary to align to the exponential field of the IEEE 754 format. ### Adapting for bfloat16 Floating-Point + AMD Versal™ Edge Adaptive SoCs primarily contain a variant of AI Engine processor, which has bfloat16 floating-point as a native data type. The structure of a bfloat16 number is shown in the following figure. ![figure4](images/bfloat16_format.png) diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/05-Softmax-Function/aie-ml/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/05-Softmax-Function/aie-ml/Makefile index b29b194f01..86fc0e72ba 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/05-Softmax-Function/aie-ml/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/05-Softmax-Function/aie-ml/Makefile @@ -7,7 +7,7 @@ SRC_DIR := ./src MY_SOURCES := $(shell find $(SRC_DIR) -name *.cpp) $(shell find $(SRC_DIR) -name *.h) -PLATFORM_USE := xilinx_vek280_base_202510_1 +PLATFORM_USE := xilinx_vek280_base_202520_1 PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/README.md b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/README.md index 6f3c345349..16dd753f3a 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/README.md +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/README.md @@ -15,7 +15,7 @@ # Migrating Fractional Delay Farrow Filter from AIE to AIE-ML Architecture -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction @@ -42,22 +42,24 @@ The design requirements are identical here as you are simply migrating the desig | Coefficients data type | `int16` | | Delay input data type | `int16` | -**IMPORTANT**: Before beginning the tutorial, make sure that you have read and followed the *Vitis Software Platform Release Notes* (v2025.1) for setting up the software and installing the VEK280 base platform. +**IMPORTANT**: Before beginning the tutorial, make sure that you have read and followed the *Vitis Software Platform Release Notes* (v2025.2) for setting up the software and installing the VEK280 base platform. Before starting this tutorial, run the following steps: -1. Set up your platform by running the `xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux` script as provided in the platform download. This script sets up the `SYSROOT` and `CXX` variables. If the script is not present, you _must_ run `xilinx-versal-common-v2025.1/sdk.sh`. -2. Set up your ROOTFS to point to the `xilinx-versal-common-v2025.1/rootfs.ext4`. -3. Set up your IMAGE to point to `xilinx-versal-common-v2025.1/Image`. +1. Set up your platform by running the `xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux` script as provided in the platform download. This script sets up the `SYSROOT` and `CXX` variables. If the script is not present, you _must_ run `xilinx-versal-common-v2025.2/sdk.sh`. +2. Set up your ROOTFS to point to the `xilinx-versal-common-v2025.2/rootfs.ext4`. +3. Set up your IMAGE to point to `xilinx-versal-common-v2025.2/Image`. 4. Set up your `PLATFORM_REPO_PATHS` environment variable based upon where you downloaded the platform. ## Table of Contents + - [Migrating the Design from AIE to AIE-ML architecture](#migrating-the-design-from-aie-to-aie-ml-Architecture) - [Optimizing the Design for Performance](#optimizing-the-design-for-performance) - [Changing the Interface to GMIO](#changing-the-plio-interface-to-gmio-interface) - [Running the Design on the Board](#building-and-running-the-design-on-the-board) ### Objectives + - Migrate the farrow filter from AIE to AIE-ML architecture - Optimize the design to meet the required performance - Modify the interface to GMIO @@ -66,32 +68,49 @@ Before starting this tutorial, run the following steps: - Run the design on the board ### Migrating the Design from AIE to AIE-ML Architecture + #### Change the Project Path + Switch the device from AIE to AIE-ML and then compile the design to ensure it compiles without errors. \ Enter the following command to navigate to the project path of the final AIE design: + ``` cd /designs/farrow_final_aie ``` + Make sure to set the `PLATFORM_REPO_PATHS` environment variable. #### Source the Vitis Tool + Enter the following command to source the Vitis tool: + ``` -source //Vitis/2025.1/settings.sh +source //Vitis/2025.2/settings.sh ``` + #### Update the Makefile to switch the device from AIE to AIE-ML. + Open the Makefile and modify the device from AIE to AIE-ML as shown below: + ``` -PLATFORM_USE := xilinx_vek280_base_202510_1 +PLATFORM_USE := xilinx_vek280_base_202520_1 ``` + Save the file. + #### Compile the Design for x86 Simulation + Enter the following command to compile for x86 simulation: + ``` make x86compile + ``` + Notice the compilation error as shown below: + ``` + In file included from wrap_farrow_kernel1.cpp:2: ./../../farrow_kernel1.cpp:58:19: error: constraints not satisfied for alias template 'sliding_mul_sym_xy_ops' [with Lanes = 8, Points = 8, CoeffStep = 1, DataStepXY = 1, CoeffType = short, DataType = cint16, AccumTag = cacc48] 58 | acc_f3 = aie::sliding_mul_sym_xy_ops<8,8,1,1,int16,cint16>::mul_antisym(f_coeffs,0,v_buff,9); @@ -100,11 +119,15 @@ In file included from wrap_farrow_kernel1.cpp:2: 1154 | requires(arch::is(arch::AIE)) | ^ + ``` + ##### What does the compile error indicate? + The error message indicates that the AIE API **sliding_mul_sym_xy_ops<>** only supports the AIE architecture and not AIE-ML. You can see the error as `'arch::is(arch::AIE)' evaluated to false` ##### Why is the AIE API **sliding_mul_sym_xy_ops<>** not supported for AIE-ML? + This API uses only half the tap values because it uses the pre-adder to compute the rest of the samples. Based on the comparison provided between the AIE and AIE-ML architectures regarding fixed-point multiplication paths, it appears that the AIE architecture utilizes a pre-adder mechanism that is absent in the AIE-ML architecture. @@ -112,13 +135,15 @@ Based on the comparison provided between the AIE and AIE-ML architectures regard ![Pipeline Diagram for AIE and AIE-ML](./images/Pipeline_Diagram_of_AIE_and_AIE-ML.png) ##### How to fix this for AIE-ML? -Additional AIE APIs that can make full use of the tap values for computation need to be identified. One such API is `aie::sliding_mul_ops;`. You should now adjust the parameter values according to the API details provided in the documentation in the this link **[AIE APIs Special Multiplication](https://download.amd.com/docnav/aiengine/xilinx2025_1/aiengine_api/aie_api/doc/group__group__mul__special.html#structaie_1_1sliding__mul__ops)**. + +Additional AIE APIs that can make full use of the tap values for computation need to be identified. One such API is `aie::sliding_mul_ops;`. You should now adjust the parameter values according to the API details provided in the documentation in the this link **[AIE APIs Special Multiplication](https://download.amd.com/docnav/aiengine/xilinx2025_2/aiengine_api/aie_api/doc/group__group__mul__special.html#structaie_1_1sliding__mul__ops)**. The following figure shows the supported parameters type (coeff x data) for AIE and AIE-ML architecture. **coeff** is *int16* and **data** is *cint16*. ![AIE API Parameters](./images/AIE_API_Parameters.png) ### Initial Porting of Farrow Filter to AIE-ML + #### Modify the Kernel code using AIE API aie::sliding_mul_ops<> The parameters for **aie:sliding_mul_ops<>** are Lanes, Points, CoeffStep, DataStepX, DataStepY, CoeffType, DataType, AccumTag. @@ -137,10 +162,13 @@ Other parameters use the same value used for AIE architecture:\ So, it will be as follows **aie::sliding_mul_ops<16, 8, 1, 1, 1,int16,cint16>;** Enter the following command to navigate to the project path of the design: + ``` cd ../farrow_port_initial ``` + Review the kernel code located under `/designs/farrow_port_initial/farrow_kernel1.cpp` file. The necessary changes are already made. Study the code and observe the following changes: + - Accumulator size has been changed to `cacc64` (acc_f3, acc_f2, acc_f1, acc_f0) as per the AIE API. - Load the full coefficient values (f_coeffs). - Vector iterator size updated for 16 lanes (p_sig_i, p_y3, p_y2, p_y2, p_y0), compared to eight lanes in AIE code. @@ -158,56 +186,69 @@ No changes to the `farrow_kernel2.cpp` file. After finishing the review of the kernel code, proceed to compile and then simulate the design. #### Compile and Simulate the Design + Enter the following command to compile (x86compile) and simulate (x86sim) to verify the functional correctness of the design: + ``` $ make x86compile $ make x86sim ``` + The first command compiles the graph code for simulation on an x86 processor, the second command runs the simulation. To verify the results, make sure you have already invoked MATLAB in your command line and run the following command: + ``` $ make check_sim_output_x86 ``` + This command invokes MATLAB to compare the simulator output against golden test vectors. The console should output `Max error LSB = 1`. To understand the performance of your initial implementation, you can perform AI Engine emulation using the SystemC simulator by entering the following sequence of commands: + ``` $ make compile $ make sim $ make check_sim_output_aie ``` + The first command compiles graph code for the SystemC simulator, the second command runs the AIE simulation, and the final command invokes MATLAB to compare the simulation output with test vectors and compute raw throughput. The average throughput for the IO ports is displayed at the end of AIE simulation. + After the final command execution, the console should output as below: + ``` -Raw Throughput = 438.8 MSPS +Raw Throughput = 449.0 MSPS Max error LSB = 1 ``` + #### Analyze the Reports Enter the following command to launch the Vitis Analyzer and review the reports. + ``` $ vitis_analyzer aiesimulator_output/default.aierun_summary ``` + Select the `Graph` view. ![Initial_Port_Graph](./images/Initial_Port_Graph.png) The Graph view shows the kernels in the graph and the input/output ports of the graph. Select the I/O tabs as shown in the above diagram. Observe the Throughput column in the I/O tab. -The output PLIO port throughput shows the value 1755.227974 MBYTES PER SEC (MBPS). To get the throughput in Sample per second, this throughput needs to be divided by four because the data type used is `cint16`, which is four bytes in size. This gives a throughput value of 438.8 MSPS. +The output PLIO port throughput shows the value 1795.8611 MBYTES PER SEC (MBPS). To get the throughput in Sample per second, this throughput needs to be divided by four because the data type used is `cint16`, which is four bytes in size. This gives a throughput value of 449.0 MSPS. -A more accurate throughput measurement can be made by measuring the steady state achieved in the final graph iteration. In vitis_analyzer, select the trace view and set markers to measure the throughput of this final iteration as shown below. Because each graph iteration processes 1024 samples, throughput = 1024/2.839 = 360.69 MSPS. +A more accurate throughput measurement can be made by measuring the steady state achieved in the final graph iteration. In vitis_analyzer, select the trace view and set markers to measure the throughput of this final iteration as shown below. Because each graph iteration processes 1024 samples, throughput = 1024/2.77 = 369.68 MSPS. Note: In the graph, select the output port which will show the net name, in this case it is net6. Then select the `Trace` view, which will show the selected net. ![Initial_Port_Graph](./images/Initial_Port_Trace.png) -The design requirement is to reach 1 GSPS, but the current performance is only **360.69 MSPS**. +The design requirement is to reach 1 GSPS, but the current performance is only **369.68 MSPS**. Close the Vitis Analyzer. ##### How to find the bottleneck in the design? + Begin by examining the compiler report for each kernel to assess its performance. In the context of AI Engine processors, Initiation Interval (II) is defined as how often (in cycles) a new iteration of the loop can start. @@ -217,9 +258,10 @@ For example, if a new iteration of the loop can start every II=16 cycles, and ea Assuming your AI Engine clock is 1.25 GHz, that means your throughput can potentially reach 1.25 GSPS excluding any processor overhead. Output throughput is defined as the number of samples produced from your kernel per second. ##### How to determine the II required for farrow_kernel1? + Navigate to the compiler reports for each tile located at `designs/farrow_port_initial/Work/aie`. -The *farrow_kernel1* is specifically implemented on tile `19_0`. Locate the `19_0.log` file within the `19_0` folder. Search for "minimum length due to resources" in this file. The AIE Compiler optimizes in three stages; use the results from the final stage output. Each loop iteration takes *II=108 cycles*. +The *farrow_kernel1* is specifically implemented on tile `19_0`. Locate the `19_0.log` file within the `19_0` folder. Search for "minimum length due to resources" in this file. The AIE Compiler optimizes in three stages; use the results from the final stage output. Each loop iteration takes *II=112 cycles*. In `designs/farrow_port_initial/farrow_kernel1.cpp`, examine line 55 where the loop is implemented. This loop processes 32 samples per iteration, equivalent to BUFFER_SIZE/32 = 1024 samples/32 => 32 samples. Therefore, the goal is to achieve an II of 32. @@ -227,7 +269,7 @@ In `designs/farrow_port_initial/farrow_kernel1.cpp`, examine line 55 where the l #### First Optimization -After reviewing the previous analysis, it is evident that the kernel requires II=102 cycles to execute each loop iteration. Now, explore strategies to optimize the `farrow_kernel1.cpp` kernel to achieve an II of 32. +After reviewing the previous analysis, it is evident that the kernel requires II=112 cycles to execute each loop iteration. Now, explore strategies to optimize the `farrow_kernel1.cpp` kernel to achieve an II of 32. In the `designs/farrow_port_initial/farrow_kernel1.cpp` file, within the for loop located at line number 55, the kernel currently performs four filter operations. To optimize, we propose splitting these operations; execute two filter operations in one tile and the remaining two in another tile. @@ -235,14 +277,16 @@ Compare the code below. The initial version using four filter operations versus ![Farrow_Inital_and_opt_1](./images/Farrow_inital_and_opt_1.png) - ##### Enhancing Performance Through Computation Split Across Multiple Tiles + By dividing the computations across multiple tiles, each kernel is tasked with fewer operations. Instead of handling four filters, each kernel now manages only two filter operations. This adjustment has the potential to enhance the II, thereby improving overall performance. Enter the following command to change project path: + ``` cd ../farrow_opt_1 ``` + Review the kernel code `farrow_kernel1.cpp` and `farrow_kernel1.h` located under the `farrow_opt_1` directory. - `farrow_kernel1.cpp` - Only two filters operations are done @@ -257,65 +301,71 @@ Review the graph code `farrow_graph.h` located under the `farrow_opt_1` director - Observe the connections made between the kernels #### Compile and Simulate the Design + Enter the following command to compile (x86compile) and simulate (x86sim) to verify the functional correctness of the design: + ``` $ make x86compile $ make x86sim $ make check_sim_output_x86 ``` + The console should output `Max error LSB = 1`. To understand the performance of your initial implementation, you can perform AI Engine emulation using the SystemC simulator by entering the following sequence of commands: + ``` $ make compile $ make sim $ make check_sim_output_aie ``` + The console should output as below: + ``` -Raw Throughput = 755.4 MSPS +Raw Throughput = 754.9 MSPS Max error LSB = 1 ``` -This design was able to reach 755.4 MSPS. But still it does not meet goal of 1 GSPS. -Note: In trace view, the measured throughput is 1024/1.535 = 667.1 MSPS. +This design was able to reach 754.9 MSPS. But still it does not meet goal of 1 GSPS. +Note: In trace view, the measured throughput is 1024/1.535 = 664.7 MSPS. Run the script which will read the II from the compiler log for each tile. + ``` $ make get_II ``` + The console should output as below: + ``` *** [LOOP_II] *** Tile 19_0 minII = 29 achieves II = 29 *** [LOOP_II] *** Tile 19_0 minII = 29 achieves II = 29 -*** [LOOP_II] *** Tile 19_0 minII = 29 achieves II = 29 -*** [LOOP_II] *** Tile 19_0 minII = 29 achieves II = 29 -*** [LOOP_II] *** Tile 19_2 minII = 6 achieves II = 6 -*** [LOOP_II] *** Tile 19_2 minII = 6 achieves II = 6 *** [LOOP_II] *** Tile 19_2 minII = 6 achieves II = 6 *** [LOOP_II] *** Tile 19_2 minII = 6 achieves II = 6 *** [LOOP_II] *** Tile 19_2 minII = 6 achieves II = 6 -*** [LOOP_II] *** Tile 19_2 minII = 6 achieves II = 6 -*** [LOOP_II] *** Tile 19_4 minII = 29 achieves II = 29 -*** [LOOP_II] *** Tile 19_4 minII = 29 achieves II = 29 *** [LOOP_II] *** Tile 19_4 minII = 29 achieves II = 29 *** [LOOP_II] *** Tile 19_4 minII = 29 achieves II = 29 ``` + The implementation of `farrow_kernel1.cpp` spans across tiles 19_0 and 19_4 to perform four filter computations. According to the kernel `farrow_kernel1.cpp`, it contains two `for loops`, each with an II of 29. Consequently, it necessitates 58 cycles for each loop iteration. But the goal is to achieve an II of 32 to achieve 1 GSPS. Close the Vitis Analyzer. #### Second Optimization + The previous setup employs three tiles: two tiles for filters and another for final computations. -As you noticed, the performance has been improved from 371.5 MSPS to 667.1 MSPS. The II has been reduced from 105 to 58 cycles. But the required goal of 1 GSPS has not yet been achieved. +As you noticed, the performance has been improved from 369.68 MSPS to 664.9 MSPS. The II has been reduced from 112 to 58 cycles. But the required goal of 1 GSPS has not yet been achieved. Instead of managing two filters per tile, each kernel will now handle just one filter operation. You will use four tiles to carry out each filter operation. This adjustment could improve the II and enhance overall performance. Enter the following command to change the project path: + ``` cd ../farrow_opt_2 ``` + Review the kernel code `farrow_kernel1.cpp` and `farrow_kernel1.h` located under the `farrow_opt_2` directory. - farrow_kernel1.cpp - Only one filter operation is performed @@ -327,39 +377,49 @@ Review the graph code `farrow_graph.h` located under the `farrow_opt_2` director - Observe the connections made between the kernels #### Compile and Simulate the Design + Enter the following command to compile (x86compile) and simulate (x86sim) to verify the functional correctness of the design: + ``` $ make x86compile $ make x86sim $ make check_sim_output_x86 ``` + The console should output `Max error LSB = 1`. To understand the performance of your initial implementation, you can perform AI Engine emulation using the SystemC simulator by entering the following sequence of commands: + ``` $ make compile $ make sim $ make check_sim_output_aie ``` + The console should output as below: + ``` -Raw Throughput = 1062.2 MSPS +Raw Throughput = 1060.9 MSPS Max error LSB = 1 ``` + #### Analyze the Reports + Enter the following command to launch the Vitis Analyzer and review the reports. ``` $ vitis_analyzer aiesimulator_output/default.aierun_summary ``` + ![Farrow_Opt2_Graph](./images/Farrow_Opt2_Graph.png) + Graph view shows the five kernels (four for filters and one for final computation). Select the I/O tabs as shown in the above diagram. Observe the Throughput column in the I/O tab. -The output PLIO port throughput shows the value 4248.962656. This throughput value needs to be divided by four because the data type used is `cint16`, which is four bytes in size. You will get the throughput value as 1062.2 MSPS. +The output PLIO port throughput shows the value 4243.680066. This throughput value needs to be divided by four because the data type used is `cint16`, which is four bytes in size. You will get the throughput value as 1060.9 MSPS. A more accurate throughput measurement can be made by measuring the steady state achieved in the final graph iteration. In vitis_analyzer, select the trace view and set markers to measure the throughput of this final iteration as shown below. -Because each graph iteration processes 1024 samples, throughput is 1024/1.012 = **1011.8 MSPS**. +Because each graph iteration processes 1024 samples, throughput is 1024/1.015 = **1008.9 MSPS**. Note: In the graph, select the output port which will show the net name, in this case it is net9. ![Farrow_Opt2_Trace](./images/Farrow_Opt2_Trace.png) @@ -369,25 +429,19 @@ The design was able to meet the desired 1 GSPS. After reviewing the report, close the Vitis Analyzer. Run the script which will read the II from the compiler log for each tiles. + ``` $ make get_II ``` + The console should output as below: ``` *** [LOOP_II] *** Tile 18_1 minII = 29 achieves II = 29 -*** [LOOP_II] *** Tile 18_1 minII = 29 achieves II = 29 -*** [LOOP_II] *** Tile 19_0 minII = 29 achieves II = 29 *** [LOOP_II] *** Tile 19_0 minII = 29 achieves II = 29 *** [LOOP_II] *** Tile 19_1 minII = 29 achieves II = 29 -*** [LOOP_II] *** Tile 19_1 minII = 29 achieves II = 29 -*** [LOOP_II] *** Tile 19_2 minII = 6 achieves II = 6 *** [LOOP_II] *** Tile 19_2 minII = 6 achieves II = 6 *** [LOOP_II] *** Tile 19_2 minII = 6 achieves II = 6 -*** [LOOP_II] *** Tile 19_2 minII = 6 achieves II = 6 -*** [LOOP_II] *** Tile 19_2 minII = 6 achieves II = 6 -*** [LOOP_II] *** Tile 19_2 minII = 6 achieves II = 6 -*** [LOOP_II] *** Tile 19_4 minII = 29 achieves II = 29 *** [LOOP_II] *** Tile 19_4 minII = 29 achieves II = 29 ``` @@ -397,9 +451,9 @@ The implementation of `farrow_kernel1.cpp` spans across tiles 18_1, 19_0, 19_1, | Design | Number of Tiles | Throughput | |---------------------|-----------------|-------------| -| farrow_port_initial | 2 | 360.6 MSPS | -| farrow_opt_1 | 3 | 667.1 MSPS | -| farrow_opt_2 | 5 | 1011.8 MSPS | +| farrow_port_initial | 2 | 369.7 MSPS | +| farrow_opt_1 | 3 | 664.9 MSPS | +| farrow_opt_2 | 5 | 1008.9 MSPS | Note: Throughput values are measured from Trace. @@ -409,10 +463,12 @@ A `input_gmio` or `output_gmio` object is used to make external memory-mapped co Now, we will change the PLIO interface to GMIO interface and do the necessary changes to the graph and test bench (`farrow_graph.h` and `farrow_app_adf.cpp`). Enter the following command to change project path: + ``` cd ../farrow_gmio/aie_ml ``` -Review the `farrow_graph.h` file. Observe the `class dut_graph` where the input and output ports are declared as GMIO. + +Review the `farrow_graph.h` file. Observe the `class dut_graph` where the input and output ports are declared as GMIO. ```sig_i = input_gmio::create("sig_i", 256, 1000);``` @@ -424,94 +480,115 @@ In Linux, the virtual address passed to GMIO::gm2aie_nb, GMIO::aie2gm_nb, GMIO:: 1. Memory allocated by `GMIO::malloc` for input and ouput data as shown below. -``` + ``` short int* sig_i_Array=(short int*)GMIO::malloc(BLOCK_SIZE_sig_in_Bytes); int32* del_i_Array=(int32*)GMIO::malloc(BLOCK_SIZE_del_in_Bytes); short int* sig_o_Array=(short int*)GMIO::malloc(BLOCK_SIZE_out_Bytes); -``` + ``` 2. Copy the test vectors to the allocated memory. -``` + + ``` /* Copy the samples to the buffer */ memcpy(sig_i_Array, input_sig_i, BLOCK_SIZE_sig_in_Bytes); /* Copy the delay values to the buffer */ memcpy(del_i_Array, input_del_i,BLOCK_SIZE_del_in_Bytes); -``` + ``` + 3. Initiate the memory-mapped AXI4 transactions for the AI Engine_ML to read from DDR memory spaces. -``` + + ``` aie_dut.sig_i.gm2aie_nb(sig_i_Array, BLOCK_SIZE_sig_in_Bytes); aie_dut.del_i.gm2aie_nb(del_i_Array, BLOCK_SIZE_del_in_Bytes); -``` + ``` + - The first argument `sig_i_Array` is the pointer to the start address of the memory space for the transaction - The second argument is the transaction size in bytes. 4. Similarly, `aie2gm()` is used to initiate memory-mapped AXI4 transactions for the AI Engine-ML to write to DDR memory spaces. -``` -aie_dut.sig_o.aie2gm(sig_o_Array, BLOCK_SIZE_out_Bytes); -``` -`aie_dut.sig_o.aie2gm_nb()` is a non-blocking function in a sense that it returns immediately when the transaction is issued, that is, it does not wait for the transaction to complete. + + ``` + aie_dut.sig_o.aie2gm(sig_o_Array, BLOCK_SIZE_out_Bytes); + ``` + + `aie_dut.sig_o.aie2gm_nb()` is a non-blocking function in a sense that it returns immediately when the transaction is issued, that is, it does not wait for the transaction to complete. 5. The results are compared with the golden values and printed out. 6. When PS has completed processing, the memory space allocated by GMIO::malloc can be released by GMIO::free. -``` + + ``` GMIO::free(sig_i_Array); GMIO::free(del_i_Array); GMIO::free(sig_o_Array); -``` + ``` #### Compile and Simulate the Design Enter the following command to compile (x86compile) and simulate (x86sim) to verify the functional correctness of the design: + ``` $ make x86compile $ make x86sim $ make check_sim_output ``` + The console should output as below: + ``` Max error LSB = 1 ``` + In the PLIO design, the simulator outputs data to a file, while in GMIO, the data is written to memory. For GMIO, first read the output from global memory and then write it to a file. You can perform AI Engine emulation using the SystemC simulator by entering the following sequence of commands: + ``` $ make compile $ make sim $ make check_sim_output ``` + The console should output as below: + ``` Max error LSB = 1 ``` ### Building and Running the Design on the Board -#### Review of Tool Flow +#### Review of Tool Flow + The diagram below illustrates the entire Vitis tool flow, encompassing the development stages for AI kernels, PL kernels, and PS code. Once the development of AIE kernels and PL kernels is completed, the subsequent step involves linking `libadf.a` and all `.xo` kernels with the designated platform. Following the linking stage, the output of the linker, which includes `.xsa` and `host.exe`, is packaged together to generate `.xclbin` and the `SD card image` required for programming the SD card. ![Tool_Flow](./images/Tool_Flow.png) #### Setup and Initialization -IMPORTANT: Before beginning the tutorial ensure you have installed AMD Vitis™ 2024.2 software. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from this link. -https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms/2025-1.html +IMPORTANT: Before beginning the tutorial ensure you have installed AMD Vitis™ 2025.2 software. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from this link. + +https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms/2025-2.html Set the environment variable ```COMMON_IMAGE_VERSAL``` to the full path where you have downloaded the Common Images. The remaining environment variables are configured in the top level Makefile ```/designs/farrow_gmio/Makefile```. ##### Host Code with XRT APIs + It is recommended to use the XRT APIs for the host code. The host code has been modified with XRT API. Review the code and then build the project and run it on board. Enter the following command to change project path: + ``` $ cd ../ps_apps/hw_emu ``` + Review the `host.cpp` file. The XRT APIs are used and XRT profiling is also used to measure the throughput of the design. ###### Hardware Emulation + Enter the following command to build the design for hardware emulation: + ``` $ cd /designs/farrow_gmio/ $ make clean all TARGET=hw_emu @@ -520,6 +597,7 @@ $ make clean all TARGET=hw_emu This will take about 15 minutes to run. The build process will generate a folder `designs/farrow-gmio/package` containing all the files required for hardware emulation. Enter the following command to run hardware emulation: + ``` $ cd /designs/farrow_gmio/package $ ./launch_hw_emu.sh -run-app embedded_exec.sh @@ -536,8 +614,8 @@ PASSED: xrt::aie::profiling handle(my_device); INFO: Started profiling timers... PASSED: my_graph.run( ITERATION=4 ) -Throughput of the graph: 4247.2 MB/s -Throughput of the graph: 1061.8 MSPS +Throughput of the graph: 4241.92 MB/s +Throughput of the graph: 1060.48 MSPS ... ``` @@ -549,6 +627,7 @@ After the hardware emulation run is complete, you can analyze the reports in Vit ###### Hardware Run Enter the following command to build the design for hardware emulation: + ``` $ cd /designs/farrow_gmio/ $ make clean all TARGET=hw @@ -569,8 +648,8 @@ PASSED: xrt::aie::profiling handle(my_device); INFO: Started profiling timers... PASSED: my_graph.run( ITERATION=4 ) -Throughput of the graph: 4499.12 MB/s -Throughput of the graph: 1124.78 MSPS +Throughput of the graph: 4497.15 MB/s +Throughput of the graph: 1124.29 MSPS --- PASSED --- GMIO transactions finished @@ -579,18 +658,21 @@ GMIO transactions finished Note: You can safely ignore the warnings. ## Comparison of AIE vs AIE-ML Farrow Filter Design Implementation + The following table compares the implementation of a farrow filter in AIE and AIE-ML architectures. This indicates that approximately twice the number of tiles is required for kernel computation in AIE_ML compared to the AIE architecture to achieve the same performance. + | Design | Tiles for AIE Kernels | Tiles for Buffers | Total Tiles | Throughput | Relative MSPS per tile | |------------------------|-----------------------|-------------------|-------------|---------------------|------------------------| | farrow - AIE (PLIO) | 2 | 5 | 5 | 1138 MSPS (HW_EMU) | 227.6 | -| farrow - AIE-ML (GMIO) | 5 | 9 | 9 | 1061 MSPS (HW_EMU) | 124.8 | +| farrow - AIE-ML (GMIO) | 5 | 8 | 8 | 1061 MSPS (HW_EMU) | 132.6 | -```* Total Tiles: Represents the total count of tiles, including those that have both kernels and buffers within the same tile.``` +**Note:**Total Tiles: Represents the total count of tiles, including those that have both kernels and buffers within the same tile. ## Conclusion This tutorial has demonstrated the following: + - How to migrate the design from AI Engine to AIE-ML architecture. - How to optimize the design to meet the required sampling rate. - Using the GMIO interface and host code with XRT APIs. diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_final_aie/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_final_aie/Makefile index 6bbc845cdb..ac85701dfc 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_final_aie/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_final_aie/Makefile @@ -6,7 +6,7 @@ AIE_SIM_ONLY ?= true -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm MY_APP = farrow_app.cpp diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_gmio/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_gmio/Makefile index 31322e5f24..760043eaa4 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_gmio/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_gmio/Makefile @@ -9,10 +9,10 @@ export TARGET ?= hw_emu export AIE_SIM_ONLY := false -PLATFORM_USE := xilinx_vek280_base_202510_1 +PLATFORM_USE := xilinx_vek280_base_202520_1 PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm -#export COMMON_IMAGE_VERSAL = < PATH to xilinx-versal-common-v2025.1 > +#export COMMON_IMAGE_VERSAL = < PATH to xilinx-versal-common-v2025.2 > export PLATFORM = ${PLATFORM_PATH}/${PLATFORM_NAME}/export/${PLATFORM_NAME}/${PLATFORM_NAME}.xpfm export SYSROOT = ${COMMON_IMAGE_VERSAL}/sysroots/cortexa72-cortexa53-amd-linux export KERNEL_IMAGE = ${COMMON_IMAGE_VERSAL}/Image diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_gmio/aie_ml/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_gmio/aie_ml/Makefile index 135bbc74e4..3db6e398d4 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_gmio/aie_ml/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_gmio/aie_ml/Makefile @@ -6,8 +6,8 @@ AIE_SIM_ONLY ?= true -# PLATFORM_USE := xilinx_vck190_base_202410_1 -PLATFORM_USE := xilinx_vek280_base_202410_1 +# PLATFORM_USE := xilinx_vck190_base_202520_1 +PLATFORM_USE := xilinx_vek280_base_202520_1 PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm MY_APP = farrow_app_adf.cpp diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_gmio/ps_apps/hw_emu/host.cpp b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_gmio/ps_apps/hw_emu/host.cpp index 6f7bfd48cd..9ff8330345 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_gmio/ps_apps/hw_emu/host.cpp +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_gmio/ps_apps/hw_emu/host.cpp @@ -24,8 +24,8 @@ static const char* STR_PASSED = "PASSED: "; static const char* STR_USAGE = "USAGE: "; static const char* STR_INFO = "INFO: "; -static constexpr double TARGET_THROUGHPUT = 1061; // Measured in HW_EMU 2025.1 - 1061 -// TARGET_THROUGHPUT = 1124; // Measured in HW 2025.1 // Keep this as reference for future tool performance +static constexpr double TARGET_THROUGHPUT = 1061; // Measured in HW_EMU 2025.2 - 1061 +// TARGET_THROUGHPUT = 1124; // Measured in HW 2025.2 // Keep this as reference for future tool performance typedef int TDATA; diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_gmio/vitis/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_gmio/vitis/Makefile index 03ab555797..85ac7d942b 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_gmio/vitis/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_gmio/vitis/Makefile @@ -9,7 +9,7 @@ ECHO := @echo TARGET ?= hw # Platform Selection... -VERSAL_VITIS_PLATFORM = xilinx_vek280_base_202510_1 +VERSAL_VITIS_PLATFORM = xilinx_vek280_base_202520_1 VITIS_PLATFORM_DIR = ${PLATFORM_REPO_PATHS}/${VERSAL_VITIS_PLATFORM} VITIS_PLATFORM_XPFM = ${VITIS_PLATFORM_DIR}/${VERSAL_VITIS_PLATFORM}.xpfm @@ -30,12 +30,13 @@ DATA_DIR := ../aie_ml GRAPH_O := ${IP_DIR}/libadf.a XSA := my.xsa # STIMULUS_IO := ${DATA_DIR}/input_sig_i.h ${DATA_DIR}/del_i_optimized.txt ${DATA_DIR}/sig_o.txt -XRT_INI := xrt.ini +XRT_INI := xrt.ini PS_EXE := ../ps_apps/hw_emu/host.exe SD_CARD := $(abspath ../package) BUILD_DIR := build_${TARGET} +export EMBD_EXC := embedded_exec.sh SYSTEM_CFG := system.cfg .PHONY: clean all @@ -62,8 +63,22 @@ ${BUILD_DIR}/${XSA}: ${BUILD_DIR} ${GRAPH_O} ${SYSTEM_CFG} ../${GRAPH_O} \ --output ${XSA} \ 2>&1 | tee vpp_link.log - -${SD_CARD}: ${BUILD_DIR}/${XSA} ${PS_EXE} ${GRAPH_O} ${KERNEL_IMAGE} ${ROOTFS} + +${EMBD_EXC}: + @echo "#!/bin/bash" >> ${EMBD_EXC} + @echo "#" >> ${EMBD_EXC} + @echo "# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved." >> ${EMBD_EXC} + @echo "# SPDX-License-Identifier: MIT" >> ${EMBD_EXC} + @echo "#" >> ${EMBD_EXC} + @echo "" >> ${EMBD_EXC} + @echo "export XILINX_XRT=/usr" >> ${EMBD_EXC} +ifeq ("$(TARGET)","hw_emu") + @echo "export XCL_EMULATION_MODE=hw_emu" >> ${EMBD_EXC} +endif + @echo "" >> ${EMBD_EXC} + @echo "./host.exe a.xclbin" >> ${EMBD_EXC} + +${SD_CARD}: ${BUILD_DIR}/${XSA} ${PS_EXE} ${GRAPH_O} ${KERNEL_IMAGE} ${ROOTFS} ${EMBD_EXC} cd ${BUILD_DIR} && \ v++ --package --debug --save-temps \ --target ${TARGET} \ @@ -77,10 +92,10 @@ ${SD_CARD}: ${BUILD_DIR}/${XSA} ${PS_EXE} ${GRAPH_O} ${KERNEL_IMAGE} ${ROOTFS} ../${GRAPH_O} \ ${XSA} \ $(addprefix --package.sd_file=../, ${PS_EXE}) \ - $(addprefix --package.sd_file=../,embedded_exec.sh) \ + $(addprefix --package.sd_file=../, ${EMBD_EXC}) \ $(addprefix --package.sd_file=../, ${XRT_INI}) \ 2>&1 | tee vpp_pack.log echo ${PLATFORM_CUSTOM} > ${SD_CARD}/sd_card/platform_desc.txt clean: - rm -rf ${SD_CARD} ${BUILD_DIR} + rm -rf ${SD_CARD} ${BUILD_DIR} ${EMBD_EXC} diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_gmio/vitis/embedded_exec.sh b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_gmio/vitis/embedded_exec.sh deleted file mode 100644 index b6bfdff581..0000000000 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_gmio/vitis/embedded_exec.sh +++ /dev/null @@ -1,10 +0,0 @@ -#!/bin/bash -# -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -# -# Author: Chandra Sekar Balakrishnan - -export XILINX_XRT=/usr - -./host.exe a.xclbin \ No newline at end of file diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_opt_1/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_opt_1/Makefile index f8dd7762db..7110c05b29 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_opt_1/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_opt_1/Makefile @@ -6,8 +6,8 @@ AIE_SIM_ONLY ?= true -# PLATFORM_USE := xilinx_vck190_base_202320_1 -PLATFORM_USE := xilinx_vek280_base_202510_1 +# PLATFORM_USE := xilinx_vck190_base_202520_1 +PLATFORM_USE := xilinx_vek280_base_202520_1 PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm MY_APP = farrow_app.cpp diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_opt_2/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_opt_2/Makefile index fc30aa00a3..ffb468a837 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_opt_2/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_opt_2/Makefile @@ -6,8 +6,8 @@ AIE_SIM_ONLY ?= true -# PLATFORM_USE := xilinx_vck190_base_202410_1 -PLATFORM_USE := xilinx_vek280_base_202510_1 +# PLATFORM_USE := xilinx_vck190_base_202520_1 +PLATFORM_USE := xilinx_vek280_base_202520_1 PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm MY_APP = farrow_app.cpp diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_port_initial/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_port_initial/Makefile index f8dd7762db..7110c05b29 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_port_initial/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/designs/farrow_port_initial/Makefile @@ -6,8 +6,8 @@ AIE_SIM_ONLY ?= true -# PLATFORM_USE := xilinx_vck190_base_202320_1 -PLATFORM_USE := xilinx_vek280_base_202510_1 +# PLATFORM_USE := xilinx_vck190_base_202520_1 +PLATFORM_USE := xilinx_vek280_base_202520_1 PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm MY_APP = farrow_app.cpp diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/images/Farrow_Opt2_Graph.png b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/images/Farrow_Opt2_Graph.png index 47b0ebfa61..a51d67ce42 100755 Binary files a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/images/Farrow_Opt2_Graph.png and b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/images/Farrow_Opt2_Graph.png differ diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/images/Farrow_Opt2_Trace.png b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/images/Farrow_Opt2_Trace.png index cf9e12e452..76d2537c72 100755 Binary files a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/images/Farrow_Opt2_Trace.png and b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/images/Farrow_Opt2_Trace.png differ diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/images/Initial_Port_Graph.png b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/images/Initial_Port_Graph.png index 09682fb4bc..49a797db96 100755 Binary files a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/images/Initial_Port_Graph.png and b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/images/Initial_Port_Graph.png differ diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/images/Initial_Port_Trace.png b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/images/Initial_Port_Trace.png index 054078699e..1258370dd2 100755 Binary files a/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/images/Initial_Port_Trace.png and b/AI_Engine_Development/AIE-ML/Design_Tutorials/06-farrow_filter/images/Initial_Port_Trace.png differ diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/Makefile index 1a0e1114d7..11529780c9 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/Makefile @@ -4,15 +4,11 @@ # # Author: Faisal El-Shabani -export AIE_SIM_ONLY := false ECHO = @echo export TARGET ?= hw_emu -BOARD=vek280 -BASE_NUM=202510_1 - # Platform Selection... -VERSAL_VITIS_PLATFORM = xilinx_${BOARD}_base_${BASE_NUM} +VERSAL_VITIS_PLATFORM = xilinx_vek280_base_202520_1 VITIS_PLATFORM_DIR = ${PLATFORM_REPO_PATHS}/${VERSAL_VITIS_PLATFORM} export VITIS_PLATFORM_XPFM = ${VITIS_PLATFORM_DIR}/${VERSAL_VITIS_PLATFORM}.xpfm @@ -45,9 +41,9 @@ channelizer: $(MAKE) all -C hls/channelizer_dma_src $(MAKE) all -C hls/split_1x16 $(MAKE) all -C hls/merge_4x1 - $(MAKE) all -C hls/ifft_front_transpose - $(MAKE) all -C hls/ifft_transpose - $(MAKE) all -C hls/ifft_back_transpose + $(MAKE) all -C hls/ifft_mid_splitter + $(MAKE) all -C hls/ifft_mid_transpose + $(MAKE) all -C hls/ifft_mid_joiner $(MAKE) all -C hls/merge_8x4 $(MAKE) all -C hls/channelizer_dma_snk $(MAKE) all -C ps_apps @@ -58,9 +54,9 @@ clean: $(MAKE) clean -C hls/channelizer_dma_src $(MAKE) clean -C hls/split_1x16 $(MAKE) clean -C hls/merge_4x1 - $(MAKE) clean -C hls/ifft_front_transpose - $(MAKE) clean -C hls/ifft_transpose - $(MAKE) clean -C hls/ifft_back_transpose + $(MAKE) clean -C hls/ifft_mid_splitter + $(MAKE) clean -C hls/ifft_mid_transpose + $(MAKE) clean -C hls/ifft_mid_joiner $(MAKE) clean -C hls/merge_8x4 $(MAKE) clean -C hls/channelizer_dma_snk $(MAKE) clean -C ps_apps diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/README.md b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/README.md index 7f306fc8f7..90131214b6 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/README.md +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/README.md @@ -15,7 +15,7 @@ # Polyphase Channelizer on AIE-ML using Vitis Libraries -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents @@ -158,7 +158,7 @@ This causes the storage requirement to increase beyond the predicted 32 tiles. T ![figure6](images/filterbank_characterize_array_view_zoom.png) -We also observe that the achieved throughput is higher than the requirement, 4096/1.256 = 3261 MSPS. +We also observe that the achieved throughput is higher than the requirement, 4096/1.257 = 3258 MSPS. ![figure7](images/filterbank_characterize_trace_view.png) @@ -195,7 +195,7 @@ Compile and simulate the design to confirm it works as expected. [shell]% vitis_analyzer aiesimulator_output/default.aierun_summary ``` -Inspecting vitis_analyzer, we observe that our resource count dropped to 32 tiles with a throughput = 4096/1.836us = 2231 MSPS. +Inspecting vitis_analyzer, we observe that our resource count dropped to 32 tiles with a throughput = 4096/1.837us = 2230 MSPS. ![figure8](images/filterbank_array_view.png) @@ -206,22 +206,30 @@ Inspecting vitis_analyzer, we observe that our resource count dropped to 32 tile In this tutorial, we explore the use of 2D IFFT IP to implement a 4K-pt IFFT @ 2 GSPS. The resources span AIE + PL. To learn more about this IP, refer to [Vitis Libraries - 2D FFT/IFFT Vitis subsystem](https://docs.amd.com/r/en-US/Vitis_Libraries/dsp/user_guide/L2/func-fft-vss.html). -The IP offers two modes to implement the IFFT set via VSS_MODE parameter: Mode 1 and Mode 2. +The IP offers two modes to implement the IFFT set via VSS_MODE parameter: Mode 1 and Mode 2. This tutorial will use Mode 1. -Mode 1 implements the row and column transforms in AI Engine while implementing the tranpose operations in PL. +Mode 1 implements the row and column transforms in AI Engine while implementing the transpose operations in AIE+PL as follows: +* The middle transpose is implemented using resources in AIE+PL and is able to use single buffering (half the resources) compared to 2025.1 Vitis Libraries. +* For powers-of-two SSRs, the front and back transpose operations are implemented in AIE leveraging either DMA or memory tiles, depending on datatype and transform sizes. + ![figure10](images/2D_4k_IFFT_VSS_MODE_1_SSR_POWER_2.png) -![figure10](images/2D_4k_IFFT_VSS_MODE_1.png) + Otherwise, the front and back transpose operations are implemented in the PL. + + ![figure11](images/2D_4k_IFFT_VSS_MODE_1.png) Mode 2 splits the IFFT into a front section mapped to AI Engine and a back section mapped to PL. This architecture results in less memory requirements in PL but requires some DSPs. -![figure10](images/2D_4k_IFFT_VSS_MODE_2.png) +![figure12](images/2D_4k_IFFT_VSS_MODE_2.png) #### Available Workflows for IFFT-2D IP -There are two entry points when using the IFFT-2D IP. +The IFFT-2D IP can be used through two different approaches: + +1) **Vitis Subsystem (VSS) - Recommended**: The IP automatically handles leaf block connectivity and produces a `.vss` file. This is the recommended workflow for most users. See the [Vitis Libraries IFFT-2D VSS example](https://github.com/Xilinx/Vitis_Libraries/tree/main/dsp/L2/examples/vss_fft_ifft_1d) for reference. -1) Instantiate IP as a Vitis subsystem (VSS) -> Recommended flow, IP takes care of leaf block connectivity producing a .vss. Example of this shown in [Vitis Libraries IFFT-2D VSS example](https://github.com/Xilinx/Vitis_Libraries/tree/main/dsp/L2/examples/vss_fft_ifft_1d) -2) Instantiate leaf blocks of IFFT-2D -> User responsible for leaf blocks connectivity. This tutorial walks through this flow. +2) **Manual Leaf Block Instantiation**: You manually instantiate and connect the individual leaf blocks that make up the IFFT-2D IP. This tutorial demonstrates this workflow, which provides greater control over design placement and avoids reserving full columns for the FFT implementation. + +**Note**: To understand which leaf blocks are required and how they should be connected, you can first use approach 1 to instantiate the IP as a VSS, examine the generated leaf blocks and their connectivity, and then manually instantiate and connect these blocks in your custom configuration. #### IFFT-2D Library Characterization @@ -265,17 +273,18 @@ The next step is to characterize its performance. ``` Inspecting vitis_analyzer, we can read two throughput numbers: -First, 4096/9.232us = 444 MSPS, corresponding to the tile performing front 64-point IFFT + point-wise twiddle multiplication. -Second, 4096/7.604us = 537 MSPS, corresponding to the tile performing the back 64-point IFFT. +* First, 4096/8.392us = 488 MSPS, corresponding to the tile performing front 64-point IFFT + point-wise twiddle multiplication. +* Second, 4096/6.913us = 593 MSPS, corresponding to the tile performing the back 64-point IFFT. -![figure11](images/ifft4096_2d_characterize_trace_view.png) +![figure13](images/ifft4096_2d_characterize_trace_view.png) This means, we need SSR=5 to meet our target throughput of 2 GSPS. #### IFFT-2D Library Optimization -While an SSR=5 should be sufficient from a resource count perspective, using a SSR that is a power of 2 simplifies the overall design and allows thr direct mapping of TDM FIR outputs into 2D IFFT input. -For this reason, we proceed with SSR=8. We can also apply the `single_buffer` constraint on the input and output buffer to reduce the storage requirements at the expense of some degradation in throughput. +While an SSR=5 should be sufficient from a resource count perspective, using a SSR that is a power of 2 simplifies the overall design and allows the direct mapping of TDM FIR outputs into 2D IFFT input. For this reason, we proceed with SSR=8. + +We can also apply the `single_buffer` constraint on some of the I/Os of this block to reduce the storage requirements at the expense of some degradation in throughput. Using `single_buffer` on the I/Os of the front FFT and on the input of the back FFT allows us to place the design in a compact (8x2) placement. ``` [shell]% cd /aie/ifft4096_2d @@ -283,39 +292,32 @@ For this reason, we proceed with SSR=8. We can also apply the `single_buffer` co [shell]% vitis_analyzer aiesimulator_output/default.aierun_summary ``` -Inspecting vitis_analyzer, we observe a resource count of 16 AIE-ML tiles. +Inspecting vitis_analyzer, we observe a resource count of 16 AIE-ML tiles and 6 Memory Tiles. Achieved throughput for: -* Front 64-point IFFT + point-wise twiddle multiplication = 2300 MSPS -* Back 64-pint IFFT = 2300 MSPS +* Front 64-point IFFT + point-wise twiddle multiplication = 2386 MSPS +* Back 64-point IFFT = 2376 MSPS -![figure12](images/ifft4096_2d_array_view.png) +![figure14](images/ifft4096_2d_array_view.png) -For the transpose blocks, you can implement these in the PL using block RAMs. The PL is assumed to be clocked at 312.5 MHz. -A single block RAM stores up to 36 Kbits, and can be configured as 512 x 72 bits with one write and one read port. -For more information on block RAMS, refer to [Versal ACAP Memory Resources Architecture Manual](https://docs.amd.com/r/en-US/am007-versal-memory/Block-RAM?tocId=4P4QDFML7TiXdlJaQlcRog). -A single transform contains 4096 samples, 64 bits each. To achieve our desired throughput, we require two write and two read ports. -The IFFT transpose blocks that exist in `${DSPLIB_ROOT}/L1/src/hw` are implemented using ping-pong buffers for storage. +The AI Engine portion of the design is implementing the front/back transpose operations. What remains is the middle transpose block, done in PL. -Given this, we expect our BRAM count per transpose block to be = 4096 / 512 x 2 x 2 = 32. +The IFFT mid transpose block that exist in `${DSPLIB_ROOT}/L1/src/hw/mid_transpose`. The PL will run at 312.5 MHz and use 128-bit interfaces. A 128-bit interface contains two cint32 samples, so this block needs to be instantiated with 2x SSR value chosen for AIE portion i.e. 16. A PL splitter/merger block shall be connected on each side of this transpose block to match these SSR assumptions. These exist in `${DSPLIB_ROOT}/L1/src/hw/common_fns/axis_split_join`. ### Design Summary - TDM FIR uses 32 AI Engine tiles with 32 IO streams -- The 4k-pt IFFT is implemented using 2D architecture with resources split between 16 AI Engine tiles (compute) and PL (data transpose). +- The 4k-pt IFFT is implemented using 2D architecture (with Mode 1) with resources split between 16 AI Engine tiles (compute), 6 memory tiles (front/back transpose) and PL (middle transpose). - From a bandwidth perspective, the design requires 2 input and 4 output streams. -- Custom HLS blocks (merge and split) are built to manage connectivity between the IPs. +- Custom HLS blocks (split and merge) are built to manage connectivity between the IPs. +- Output ports of AI Engine going to PL may arrive at different times causing minor throughput loss. Those can be compensated by adding FIFOs during v++ linking step, [Specifying-Streaming-Connections](https://docs.amd.com/r/en-US/ug1701-vitis-accelerated-embedded/Specifying-Streaming-Connections). -![figure13](images/channelizer_solution_synthesis.png) +![figure15](images/channelizer_solution_synthesis.png) ## Design Resources The following figure summarizes the AI Engine and PL resources required to implement the design in the VE2802 device on the VEK280 eval board. The design is using 48 AI Engine tiles for compute. The PL design includes the resources required to implement the DMA Source, Stream Split/Merge, Memory Transpose, and DMA Sink kernels. -![figure14](images/channelizer_resources.png) - -Below is a list of potential improvements that could be made to reduce resource count: -- Reduce the number of AIE-ML tiles used by 2D FFT IP from 16 to 10 (by changing TP_SSR from 8 to 5). This requires increased complexity of the HLS managing the connectivity from the TDM FIR output to the 2D FFT input due to state handling. -- Optimize implementation of HLS transpose blocks to avoid use of ping-pong buffers. This should half the number of the required block RAMs. +![figure16](images/channelizer_resources.png) ## Build and Run Design @@ -323,7 +325,7 @@ You can build the polyphase channelizer design from the command line. ### Setup & Initialization -IMPORTANT: Before beginning the tutorial, ensure you have installed AMD Vitis™ 2025.1 software. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). +IMPORTANT: Before beginning the tutorial, ensure you have installed AMD Vitis™ 2025.2 software. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). Set the environment variable ```COMMON_IMAGE_VERSAL``` to the full path where you have downloaded the Common Images. Then set the environment variable ```PLATFORM_REPO_PATHS``` to the value ```$XILINX_VITIS/base_platforms```. @@ -344,11 +346,15 @@ An optional `-g` can be applied to the ```launch_hw_emu.sh``` command to launch ``` [shell]% cd /package -[shell]% ./launch_hw_emu.sh -run-app embedded_exec.sh +[shell]% ./launch_hw_emu.sh -g -run-app embedded_exec.sh ``` After hardware emulation run is complete, the following is displayed on the terminal. -![figure15](images/channelizer_hw_emu.png) +![figure17](images/channelizer_hw_emu.png) + +Throughput can be measured by inspecting the traces. The design processes 8 transforms, each with 4k samples in 15.56us. Throughput = 8 x 4096 / 14.57 = 2250 Msps. + +![figure18](images/channelizer_hw_emu_trace.png) ### Hardware @@ -363,7 +369,7 @@ The build process generates the SD card image in the ```package/sd_card``` folde After flashing sd_card.img into the sd card, power on the board and run the design. The following is displayed on the terminal. -![figure16](images/channelizer_hw.png) +![figure18](images/channelizer_hw.png) ## References diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/Makefile index f0437dcc30..60786887ad 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/Makefile @@ -4,7 +4,6 @@ # # Author: Faisal El-Shabani -AIE_SIM_ONLY ?= true SIM_FIFO := false MY_APP := channelizer_app @@ -16,6 +15,8 @@ CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancin DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ --include=${DSPLIB_ROOT}/L1/include/aie \ + --include=${DSPLIB_ROOT}/L1/include/vss/common \ + --include=${DSPLIB_ROOT}/L1/include/vss/vss_fft_ifft_1d \ --include=${DSPLIB_ROOT}/L1/src/aie OTHER_INCLUDE := --include=../ifft4096_2d \ @@ -29,10 +30,6 @@ ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} endif -ifeq (${AIE_SIM_ONLY},true) - AIE_FLAGS := ${AIE_FLAGS} --aie.Xpreproc="-DAIE_SIM_ONLY" -endif - .PHONY: help clean x86com x86sim sim profile throughput help:: diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/channelizer_app.cpp b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/channelizer_app.cpp index 68d4289ffd..a679ebfdd5 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/channelizer_app.cpp +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/channelizer_app.cpp @@ -44,13 +44,8 @@ class dut_graph : public graph { single_buffer(dut.firbank.tdmfir.m_firKernels[ii+0].in[0]); std::string file_i0 = "data/filterbank_i_" + std::to_string(ii) + ".txt"; std::string file_o0 = "data/filterbank_o_" + std::to_string(ii) + ".txt"; -#ifdef AIE_SIM_ONLY sig_i[ii] = input_plio::create("PLIO_i_"+std::to_string(ii), plio_64_bits, file_i0 ); sig_o[ii] = output_plio::create("PLIO_o_"+std::to_string(ii), plio_64_bits, file_o0 ); -#else - sig_i[ii] = input_plio::create("PLIO_i_"+std::to_string(ii), plio_64_bits ); - sig_o[ii] = output_plio::create("PLIO_o_"+std::to_string(ii), plio_64_bits ); -#endif connect<>( sig_i[ii].out[0], dut.sig_i[ii] ); connect<>( dut.sig_o[ii], sig_o[ii].in[0] ); location (dut.firbank.tdmfir.m_firKernels[ii]) = tile(start_fb+FBX[ii],FBY[ii]); @@ -65,13 +60,8 @@ class dut_graph : public graph { single_buffer(dut.firbank.tdmfir.m_firKernels[ii+1].in[0]); std::string file_i1 = "data/filterbank_i_" + std::to_string(ii+1) + ".txt"; std::string file_o1 = "data/filterbank_o_" + std::to_string(ii+1) + ".txt"; -#ifdef AIE_SIM_ONLY sig_i[ii+1] = input_plio::create("PLIO_i_"+std::to_string(ii+1), plio_64_bits, file_i1 ); sig_o[ii+1] = output_plio::create("PLIO_o_"+std::to_string(ii+1), plio_64_bits, file_o1 ); -#else - sig_i[ii+1] = input_plio::create("PLIO_i_"+std::to_string(ii+1), plio_64_bits ); - sig_o[ii+1] = output_plio::create("PLIO_o_"+std::to_string(ii+1), plio_64_bits ); -#endif connect<>( sig_i[ii+1].out[0], dut.sig_i[ii+1] ); connect<>( dut.sig_o[ii+1], sig_o[ii+1].in[0] ); location (dut.firbank.tdmfir.m_firKernels[ii+1]) = tile(start_fb+FBX[ii+1],FBY[ii+1]); @@ -86,13 +76,8 @@ class dut_graph : public graph { single_buffer(dut.firbank.tdmfir.m_firKernels[ii+2].in[0]); std::string file_i2 = "data/filterbank_i_" + std::to_string(ii+2) + ".txt"; std::string file_o2 = "data/filterbank_o_" + std::to_string(ii+2) + ".txt"; -#ifdef AIE_SIM_ONLY sig_i[ii+2] = input_plio::create("PLIO_i_"+std::to_string(ii+2), plio_64_bits, file_i2 ); sig_o[ii+2] = output_plio::create("PLIO_o_"+std::to_string(ii+2), plio_64_bits, file_o2 ); -#else - sig_i[ii+2] = input_plio::create("PLIO_i_"+std::to_string(ii+2), plio_64_bits ); - sig_o[ii+2] = output_plio::create("PLIO_o_"+std::to_string(ii+2), plio_64_bits ); -#endif connect<>( sig_i[ii+2].out[0], dut.sig_i[ii+2] ); connect<>( dut.sig_o[ii+2], sig_o[ii+2].in[0] ); location (dut.firbank.tdmfir.m_firKernels[ii+2]) = tile(start_fb+FBX[ii+2],FBY[ii+2]); @@ -107,13 +92,8 @@ class dut_graph : public graph { single_buffer(dut.firbank.tdmfir.m_firKernels[ii+3].in[0]); std::string file_i3 = "data/filterbank_i_" + std::to_string(ii+3) + ".txt"; std::string file_o3 = "data/filterbank_o_" + std::to_string(ii+3) + ".txt"; -#ifdef AIE_SIM_ONLY sig_i[ii+3] = input_plio::create("PLIO_i_"+std::to_string(ii+3), plio_64_bits, file_i3 ); sig_o[ii+3] = output_plio::create("PLIO_o_"+std::to_string(ii+3), plio_64_bits, file_o3 ); -#else - sig_i[ii+3] = input_plio::create("PLIO_i_"+std::to_string(ii+3), plio_64_bits ); - sig_o[ii+3] = output_plio::create("PLIO_o_"+std::to_string(ii+3), plio_64_bits ); -#endif connect<>( sig_i[ii+3].out[0], dut.sig_i[ii+3] ); connect<>( dut.sig_o[ii+3], sig_o[ii+3].in[0] ); location (dut.firbank.tdmfir.m_firKernels[ii+3]) = tile(start_fb+FBX[ii+3],FBY[ii+3]); @@ -134,17 +114,10 @@ class dut_graph : public graph { std::string fname_o1 = "data/fft_back_o_" + std::to_string(ff) + ".txt"; std::string pname_i1 = "PLIO_back_in_" + std::to_string(ff) + ""; std::string pname_o1 = "PLIO_back_out_" + std::to_string(ff) + ""; -#ifdef AIE_SIM_ONLY front_i[ff] = input_plio::create(pname_i0,plio_64_bits,fname_i0); front_o[ff] = output_plio::create(pname_o0,plio_64_bits,fname_o0); back_i[ff] = input_plio::create(pname_i1,plio_64_bits,fname_i1); back_o[ff] = output_plio::create(pname_o1,plio_64_bits,fname_o1); -#else - front_i[ff] = input_plio::create(pname_i0,plio_64_bits); - front_o[ff] = output_plio::create(pname_o0,plio_64_bits); - back_i[ff] = input_plio::create(pname_i1,plio_64_bits); - back_o[ff] = output_plio::create(pname_o1,plio_64_bits); -#endif connect<>( front_i[ff].out[0], dut.front_i[ff] ); connect<>( dut.front_o[ff], front_o[ff].in[0] ); connect<>( back_i[ff].out[0], dut.back_i[ff] ); @@ -168,9 +141,8 @@ class dut_graph : public graph { location(dut.ifft4096_2d.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = tile(30+ff,4); single_buffer (dut.ifft4096_2d.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].in[0]); location(dut.ifft4096_2d.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].in[0]) = bank(30+ff,4,0); - single_buffer (dut.ifft4096_2d.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].out[0]); - location(dut.ifft4096_2d.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].out[0]) = bank(30+ff,4,1); - location (dut.ifft4096_2d.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = bank(30+ff,4,2); + location(dut.ifft4096_2d.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].out[0]) = {bank(30+ff,4,1),bank(30+ff,4,2)}; + location (dut.ifft4096_2d.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = bank(30+ff,4,3); location(back_i[ff]) = shim(22); location(back_o[ff]) = shim(22); } @@ -192,9 +164,8 @@ class dut_graph : public graph { location(dut.ifft4096_2d.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = tile(30+ff-4,5); single_buffer (dut.ifft4096_2d.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].in[0]); location(dut.ifft4096_2d.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].in[0]) = bank(30+ff-4,5,0); - single_buffer (dut.ifft4096_2d.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].out[0]); - location(dut.ifft4096_2d.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].out[0]) = bank(30+ff-4,5,1); - location (dut.ifft4096_2d.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = bank(30+ff-4,5,2); + location(dut.ifft4096_2d.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].out[0]) = {bank(30+ff-4,5,1),bank(30+ff-4,5,2)}; + location (dut.ifft4096_2d.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = bank(30+ff-4,5,3); location(back_i[ff]) = shim(21); location(back_o[ff]) = shim(21); } diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/data/fft_back_i_0.txt b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/data/fft_back_i_0.txt index eab71c8841..03888ac89d 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/data/fft_back_i_0.txt +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/data/fft_back_i_0.txt @@ -1,2048 +1,2048 @@ 1581 -480 --2745 377 -1986 -2298 -2424 761 -2030 -523 -892 -891 -973 -2849 --322 -1387 -489 1041 --880 523 -912 -1202 --1322 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a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/data/fft_front_i_0.txt b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/data/fft_front_i_0.txt index 0076b178ad..e0954dc094 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/data/fft_front_i_0.txt +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/data/fft_front_i_0.txt @@ -1,2048 +1,2048 @@ 1560 -444 +343 1446 +2044 459 +823 60 +-16 57 +93 -87 +154 -22 +32 34 -2 4 +131 -29 +76 -290 +-38 -107 +-1 -50 +2 -6 +8 8 +-2 15 -25 -25 +47 -110 +67 25 +-30 -81 +17 -80 +-2 -15 +-7 -9 +13 -23 -17 17 +-5 65 +72 53 +83 -82 +4 19 +4 7 +9 -25 +-6 28 -8 -25 +-17 -58 +-94 65 +-4 -64 +17 -28 +33 38 +15 10 +5 18 -3 17 +20 30 +-26 -50 +21 19 +34 0 +49 0 +45 -16 +3 -39 -23 41 +-14 -2 +-6 -28 +-3 -67 +-62 7 +14 16 +38 29 +-45 -11 69 14 +30 -70 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a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/data/fft_front_i_3.txt +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/data/fft_front_i_3.txt @@ -1,2048 +1,2048 @@ 2407 1002 +-1180 508 +-1618 -248 +-369 35 +56 -77 +108 -289 +-4 182 +19 -57 -90 -91 +-108 -90 +39 -127 +-114 98 +-31 0 +6 -2 +-6 -7 +5 1 15 115 +107 -66 +26 69 +1 -3 +-6 -43 +6 7 +-9 1 +-29 12 -5 32 +-55 -20 +-133 49 +-48 38 +12 -41 +-44 -2 +-35 33 +-10 -3 5 -27 +-30 -5 +8 43 +-9 40 +25 -21 +37 -5 +0 -16 +65 54 -17 -14 +-1 20 +-49 -30 +-36 8 +-99 -60 +36 18 +-47 -33 +39 -31 -2 25 +35 -99 +-43 -9 +70 -21 +11 -16 +-10 1 +-54 -48 +-18 -45 32 -5 +3 -38 +34 49 +-6 -12 +-52 -11 +-6 -50 +35 51 +-40 -56 -61 -67 +119 -36 +-25 33 +25 12 +-32 16 +-41 -28 +11 -4 +6 -12 26 -25 +39 25 +-25 -63 +10 16 +-52 29 +66 -13 +-3 -18 +69 31 37 20 +27 -21 +-117 25 +-19 16 +30 2 +26 -20 +-14 64 +2 -17 0 -55 +55 -49 +20 -5 +61 78 +-1 -50 +-1 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b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/data/fft_front_i_5.txt index 13766eae73..e9e9257232 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/data/fft_front_i_5.txt +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/data/fft_front_i_5.txt @@ -1,2048 +1,2048 @@ 1147 -925 +-1137 -1399 +-390 101 +47 364 +193 -100 +-62 88 +30 37 +-8 6 156 48 +-179 -158 +170 96 +113 46 +9 -18 +10 2 +-1 0 +-32 -1 -36 -81 +-15 20 +-27 33 +-71 96 +-19 20 +4 23 +-9 -3 +-50 33 -33 -21 +-24 9 +71 -1 +-33 26 +-7 -7 +15 10 +-18 17 +-13 -47 3 -7 +2 31 +-51 12 +6 -38 +-16 -22 +9 32 +27 -37 +2 -21 -4 -52 +-49 65 +-69 -29 +-12 -26 +-4 -8 +-50 14 +17 -26 +22 -20 -71 -31 +50 43 +-32 27 +5 -71 +3 37 +-15 -22 +40 51 +12 43 17 51 +-80 -26 +-7 93 +-3 -9 +-53 56 +-20 4 +-10 45 +-12 -24 -50 14 +1 28 +-35 -12 +-1 30 +-23 -13 +-15 16 +23 12 +-28 -29 18 66 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+458 -140 -118 362 +-1915 -1427 3006 2833 +-1060 900 1582 -2082 +773 223 -1261 -1352 +-2320 222 -642 530 +-2863 1663 -1151 -1140 +112 2914 473 3638 +1521 1212 1671 1632 diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/gen_vectors.m b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/gen_vectors.m index 826418dc0b..6bb9b0fec0 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/gen_vectors.m +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/channelizer/gen_vectors.m @@ -195,7 +195,7 @@ data = reshape(filterbank_o(:,tt),Nfft,Nfft); for pp = 1 : FFT_SSR fid = fopen(sprintf('data/fft_front_i_%d.txt',pp-1),'a'); - data_u = reshape(transpose(data(pp:FFT_SSR:end,:)),1,[]); + data_u = reshape(data(pp:FFT_SSR:end,:),1,[]); for ii = 1 : numel(data_u) fprintf(fid,'%d %d\n',real(data_u(ii)).int,imag(data_u(ii)).int); end @@ -203,38 +203,41 @@ end end -% --> Outputs of 'front' transforms taken in polyphase order for tt = 1 : Niter data = squeeze(front_o(:,:,tt)); for pp = 1 : FFT_SSR fid = fopen(sprintf('data/fft_front_o_%d.txt',pp-1),'a'); - data_u = reshape(transpose(data(pp:FFT_SSR:end,:)),1,[]); - for ii = 1 : numel(data_u) - fprintf(fid,'%d %d\n',real(data_u(ii)).int,imag(data_u(ii)).int); + data_r = data(pp:FFT_SSR:end,:); + for rr = 1 : 2 : size(data_r,1) + data_u = reshape(data_r(rr:rr+1,:),1,[]); + for ii = 1 : numel(data_u) + fprintf(fid,'%d %d\n',real(data_u(ii)).int,imag(data_u(ii)).int); + end end fclose(fid); end end -% --> Inputs to 'back' taken in polyphase order for tt = 1 : Niter data = squeeze(front_o(:,:,tt)); for pp = 1 : FFT_SSR fid = fopen(sprintf('data/fft_back_i_%d.txt',pp-1),'a'); - data_u = reshape(data(:,pp:FFT_SSR:end),1,[]); - for ii = 1 : numel(data_u) - fprintf(fid,'%d %d\n',real(data_u(ii)).int,imag(data_u(ii)).int); + data_r = data(:,pp:FFT_SSR:end); + for rr = 1 : 2 : size(data_r,2) + data_u = reshape(transpose(data_r(:,rr:rr+1)),1,[]); + for ii = 1 : numel(data_u) + fprintf(fid,'%d %d\n',real(data_u(ii)).int,imag(data_u(ii)).int); + end end fclose(fid); end end -% --> Outputs of 'back' taken in polyphase order for tt = 1 : Niter data = squeeze(back_o(:,:,tt)); for pp = 1 : FFT_SSR fid = fopen(sprintf('data/fft_back_o_%d.txt',pp-1),'a'); - data_u = reshape(data(:,pp:FFT_SSR:end),1,[]); + data_u = reshape(transpose(data(:,pp:FFT_SSR:end)),1,[]); for ii = 1 : numel(data_u) fprintf(fid,'%d %d\n',real(data_u(ii)).int,imag(data_u(ii)).int); end diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d/Makefile index 8af760d2d7..3fb72cf645 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d/Makefile @@ -15,6 +15,8 @@ CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancin DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ --include=${DSPLIB_ROOT}/L1/include/aie \ + --include=${DSPLIB_ROOT}/L1/include/vss/common \ + --include=${DSPLIB_ROOT}/L1/include/vss/vss_fft_ifft_1d \ --include=${DSPLIB_ROOT}/L1/src/aie AIE_OUTPUT := libadf.a diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d/gen_vectors.m b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d/gen_vectors.m index 2d89ac093d..26d5879e72 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d/gen_vectors.m +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d/gen_vectors.m @@ -52,7 +52,7 @@ for tt = 1 : Ntransform data = squeeze(reshape(sig_i(:,tt),Nfft,Nfft)); for rr = 1 : Nfft - tmp = ifft_stockham_dit(data(rr,:),WW,FF,TT,FF); + tmp = double(fi(Nfft*ifft(double(data(rr,:))),TT,FF)); data_r(rr,:,tt) = tmp .* twid(rr,:); end end @@ -65,7 +65,7 @@ data_b = complex(zeros(Nfft,Nfft,Ntransform)); for tt = 1 : Ntransform for cc = 1 : Nfft - data_b(:,cc,tt) = ifft_stockham_dit(front_o(:,cc,tt),WW,FF,TT,FF); + data_b(:,cc,tt) = double(fi(Nfft*ifft(double(front_o(:,cc,tt))),TT,FF)); end end back_o = fi(data_b,TT,FF); @@ -79,12 +79,11 @@ [~,~,~] = rmdir('data','s'); [~,~,~] = mkdir('data'); -% --> Inputs to 'front' transforms taken in polyphase order for tt = 1 : Ntransform data = reshape(sig_i(:,tt),Nfft,Nfft); for pp = 1 : Nports fid = fopen(sprintf('data/front_i_%d.txt',pp-1),'a'); - data_u = reshape(transpose(data(pp:Nports:end,:)),1,[]); + data_u = reshape(data(pp:Nports:end,:),1,[]); for ii = 1 : numel(data_u) fprintf(fid,'%d %d\n',real(data_u(ii)).int,imag(data_u(ii)).int); end @@ -93,40 +92,43 @@ end disp('Done front_i'); -% --> Outputs of 'front' transforms taken in polyphase order for tt = 1 : Ntransform data = squeeze(front_o(:,:,tt)); for pp = 1 : Nports fid = fopen(sprintf('data/front_o_%d.txt',pp-1),'a'); - data_u = reshape(transpose(data(pp:Nports:end,:)),1,[]); - for ii = 1 : numel(data_u) - fprintf(fid,'%d %d\n',real(data_u(ii)).int,imag(data_u(ii)).int); + data_r = data(pp:Nports:end,:); + for rr = 1 : 2 : size(data_r,1) + data_u = reshape(data_r(rr:rr+1,:),1,[]); + for ii = 1 : numel(data_u) + fprintf(fid,'%d %d\n',real(data_u(ii)).int,imag(data_u(ii)).int); + end end fclose(fid); end end disp('Done front_o'); -% --> Inputs to 'back' taken in polyphase order for tt = 1 : Ntransform data = squeeze(front_o(:,:,tt)); for pp = 1 : Nports fid = fopen(sprintf('data/back_i_%d.txt',pp-1),'a'); - data_u = reshape(data(:,pp:Nports:end),1,[]); - for ii = 1 : numel(data_u) - fprintf(fid,'%d %d\n',real(data_u(ii)).int,imag(data_u(ii)).int); + data_r = data(:,pp:Nports:end); + for rr = 1 : 2 : size(data_r,2) + data_u = reshape(transpose(data_r(:,rr:rr+1)),1,[]); + for ii = 1 : numel(data_u) + fprintf(fid,'%d %d\n',real(data_u(ii)).int,imag(data_u(ii)).int); + end end fclose(fid); end end disp('Done back_i'); -% --> Outputs of 'back' taken in polyphase order for tt = 1 : Ntransform data = squeeze(back_o(:,:,tt)); for pp = 1 : Nports fid = fopen(sprintf('data/back_o_%d.txt',pp-1),'a'); - data_u = reshape(data(:,pp:Nports:end),1,[]); + data_u = reshape(transpose(data(:,pp:Nports:end)),1,[]); for ii = 1 : numel(data_u) fprintf(fid,'%d %d\n',real(data_u(ii)).int,imag(data_u(ii)).int); end diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d/ifft4096_2d_app.cpp b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d/ifft4096_2d_app.cpp index 68b5ca3db9..7e0df96517 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d/ifft4096_2d_app.cpp +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d/ifft4096_2d_app.cpp @@ -36,50 +36,50 @@ class dut_graph : public graph { #ifndef __X86SIM__ if (ff (dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = tile(34+ff,4); + location (dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = tile(15+ff,1); location (dut.ifft4096_2d.m_fftTwRotKernels[ff]) = location(dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0]); single_buffer (dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0].in[0]); - location (dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0].in[0]) = bank(34+ff,4,0); + location (dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0].in[0]) = bank(15+ff,1,0); single_buffer (dut.ifft4096_2d.m_fftTwRotKernels[ff].out[0]); - location (dut.ifft4096_2d.m_fftTwRotKernels[ff].out[0]) = bank(34+ff,4,2); + location (dut.ifft4096_2d.m_fftTwRotKernels[ff].out[0]) = bank(15+ff,1,2); single_buffer (dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0].out[0]); - location (dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0].out[0]) = bank(34+ff,4,1); - location (dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = bank(34+ff,4,3); - location(dut.ifft4096_2d.m_fftTwRotKernels[ff].param[0]) = bank(34+ff,4,3); - location(dut.ifft4096_2d.m_fftTwRotKernels[ff].param[1]) = bank(34+ff,4,3); + location (dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0].out[0]) = bank(15+ff,1,1); + location (dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = bank(15+ff,1,3); + location(dut.ifft4096_2d.m_fftTwRotKernels[ff].param[0]) = bank(15+ff,1,3); + location(dut.ifft4096_2d.m_fftTwRotKernels[ff].param[1]) = bank(15+ff,1,3); location(front_i[ff]) = shim(16); location(front_o[ff]) = shim(16); - location(dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = tile(30+ff,4); + location(dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = tile(11+ff,1); single_buffer (dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].in[0]); - location(dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].in[0]) = bank(30+ff,4,0); - single_buffer (dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].out[0]); - location(dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].out[0]) = bank(30+ff,4,1); - location (dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = bank(30+ff,4,2); + location(dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].in[0]) = bank(11+ff,1,0); + //single_buffer (dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].out[0]); + location(dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].out[0]) = {bank(11+ff,1,1),bank(11+ff,1,2)}; + location (dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = bank(11+ff,1,3); location(back_i[ff]) = shim(14); location(back_o[ff]) = shim(14); } else{ - location(dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = tile(34+ff-4,5); + location(dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = tile(15+ff-4,2); location(dut.ifft4096_2d.m_fftTwRotKernels[ff]) = location(dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0]); single_buffer (dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0].in[0]); - location(dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0].in[0]) = bank(34+ff-4,5,0); + location(dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0].in[0]) = bank(15+ff-4,2,0); single_buffer (dut.ifft4096_2d.m_fftTwRotKernels[ff].out[0]); - location(dut.ifft4096_2d.m_fftTwRotKernels[ff].out[0]) = bank(34+ff-4,5,2); + location(dut.ifft4096_2d.m_fftTwRotKernels[ff].out[0]) = bank(15+ff-4,2,2); single_buffer (dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0].out[0]); - location(dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0].out[0]) = bank(34+ff-4,5,1); - location (dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = bank(34+ff-4,5,3); - location(dut.ifft4096_2d.m_fftTwRotKernels[ff].param[0]) = bank(34+ff-4,5,3); - location(dut.ifft4096_2d.m_fftTwRotKernels[ff].param[1]) = bank(34+ff-4,5,3); + location(dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0].out[0]) = bank(15+ff-4,2,1); + location (dut.ifft4096_2d.frontFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = bank(15+ff-4,2,3); + location(dut.ifft4096_2d.m_fftTwRotKernels[ff].param[0]) = bank(15+ff-4,2,3); + location(dut.ifft4096_2d.m_fftTwRotKernels[ff].param[1]) = bank(15+ff-4,2,3); location(front_i[ff]) = shim(15); location(front_o[ff]) = shim(15); - location(dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = tile(30+ff-4,5); + location(dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = tile(11+ff-4,2); single_buffer (dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].in[0]); - location(dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].in[0]) = bank(30+ff-4,5,0); - single_buffer (dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].out[0]); - location(dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].out[0]) = bank(30+ff-4,5,1); - location (dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = bank(30+ff-4,5,2); + location(dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].in[0]) = bank(11+ff-4,2,0); + //single_buffer (dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].out[0]); + location(dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0].out[0]) = {bank(11+ff-4,2,1),bank(11+ff-4,2,2)}; + location (dut.ifft4096_2d.backFFTGraph[ff].FFTwinproc.m_fftKernels[0]) = bank(11+ff-4,2,3); location(back_i[ff]) = shim(13); location(back_o[ff]) = shim(13); } diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d/ifft_stockham_dit.m b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d/ifft_stockham_dit.m deleted file mode 100755 index 13413b6050..0000000000 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d/ifft_stockham_dit.m +++ /dev/null @@ -1,33 +0,0 @@ -% -% Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -% SPDX-License-Identifier: MIT -% -% Author: Mark Rollins - -function [ifft_o] = ifft_stockham_dit(ifft_i,nt_twid,fi_twid,nt_sig,fi_sig) - N = numel(ifft_i); - Nstage = log2(N); - buff_i = ifft_i; - buff_t = zeros(size(buff_i)); - for stage = Nstage : -1 : 1 - Nhalf = N / 2^stage; - twid = double(fi(exp(-1i*2*pi*[0:Nhalf-1]/(2*Nhalf)),nt_twid,fi_twid)); - stride = 2^(stage-1); - for p = 0 : Nhalf-1 - for q = 0 : stride-1 - % Note: address is not "in-place" - idx0_i = q + stride*(2*p+0); - idx1_i = q + stride*(2*p+1); - idx0_o = q + stride*(p+0 ); - idx1_o = q + stride*(p+Nhalf); - a = buff_i(1+idx0_i); - b = buff_i(1+idx1_i) * conj(twid(1+p)); - buff_t(1+idx0_o) = a + b; - buff_t(1+idx1_o) = a - b; - end - end - buff_i = buff_t; - end - ifft_o = buff_i; - ifft_o = double(fi(ifft_o,nt_sig,fi_sig)); -end diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d_characterize/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d_characterize/Makefile index 10cf108878..e5840a186d 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d_characterize/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d_characterize/Makefile @@ -15,6 +15,8 @@ CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancin DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ --include=${DSPLIB_ROOT}/L1/include/aie \ + --include=${DSPLIB_ROOT}/L1/include/vss/common \ + --include=${DSPLIB_ROOT}/L1/include/vss/vss_fft_ifft_1d \ --include=${DSPLIB_ROOT}/L1/src/aie AIE_OUTPUT := libadf.a diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d_characterize/gen_vectors.m b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d_characterize/gen_vectors.m index 5d7eed5272..236b013cd4 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d_characterize/gen_vectors.m +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d_characterize/gen_vectors.m @@ -52,7 +52,7 @@ for tt = 1 : Ntransform data = squeeze(reshape(sig_i(:,tt),Nfft,Nfft)); for rr = 1 : Nfft - tmp = ifft_stockham_dit(data(rr,:),WW,FF,TT,FF); + tmp = double(fi(Nfft*ifft(double(data(rr,:))),TT,FF)); data_r(rr,:,tt) = tmp .* twid(rr,:); end end @@ -65,7 +65,7 @@ data_b = complex(zeros(Nfft,Nfft,Ntransform)); for tt = 1 : Ntransform for cc = 1 : Nfft - data_b(:,cc,tt) = ifft_stockham_dit(front_o(:,cc,tt),WW,FF,TT,FF); + data_b(:,cc,tt) = double(fi(Nfft*ifft(double(front_o(:,cc,tt))),TT,FF)); end end back_o = fi(data_b,TT,FF); @@ -79,12 +79,11 @@ [~,~,~] = rmdir('data','s'); [~,~,~] = mkdir('data'); -% --> Inputs to 'front' transforms taken in polyphase order for tt = 1 : Ntransform data = reshape(sig_i(:,tt),Nfft,Nfft); for pp = 1 : Nports fid = fopen(sprintf('data/front_i_%d.txt',pp-1),'a'); - data_u = reshape(transpose(data(pp:Nports:end,:)),1,[]); + data_u = reshape(data(pp:Nports:end,:),1,[]); for ii = 1 : numel(data_u) fprintf(fid,'%d %d\n',real(data_u(ii)).int,imag(data_u(ii)).int); end @@ -93,40 +92,43 @@ end disp('Done front_i'); -% --> Outputs of 'front' transforms taken in polyphase order for tt = 1 : Ntransform data = squeeze(front_o(:,:,tt)); for pp = 1 : Nports fid = fopen(sprintf('data/front_o_%d.txt',pp-1),'a'); - data_u = reshape(transpose(data(pp:Nports:end,:)),1,[]); - for ii = 1 : numel(data_u) - fprintf(fid,'%d %d\n',real(data_u(ii)).int,imag(data_u(ii)).int); + data_r = data(pp:Nports:end,:); + for rr = 1 : 2 : size(data_r,1) + data_u = reshape(data_r(rr:rr+1,:),1,[]); + for ii = 1 : numel(data_u) + fprintf(fid,'%d %d\n',real(data_u(ii)).int,imag(data_u(ii)).int); + end end fclose(fid); end end disp('Done front_o'); -% --> Inputs to 'back' taken in polyphase order for tt = 1 : Ntransform data = squeeze(front_o(:,:,tt)); for pp = 1 : Nports fid = fopen(sprintf('data/back_i_%d.txt',pp-1),'a'); - data_u = reshape(data(:,pp:Nports:end),1,[]); - for ii = 1 : numel(data_u) - fprintf(fid,'%d %d\n',real(data_u(ii)).int,imag(data_u(ii)).int); + data_r = data(:,pp:Nports:end); + for rr = 1 : 2 : size(data_r,2) + data_u = reshape(transpose(data_r(:,rr:rr+1)),1,[]); + for ii = 1 : numel(data_u) + fprintf(fid,'%d %d\n',real(data_u(ii)).int,imag(data_u(ii)).int); + end end fclose(fid); end end disp('Done back_i'); -% --> Outputs of 'back' taken in polyphase order for tt = 1 : Ntransform data = squeeze(back_o(:,:,tt)); for pp = 1 : Nports fid = fopen(sprintf('data/back_o_%d.txt',pp-1),'a'); - data_u = reshape(data(:,pp:Nports:end),1,[]); + data_u = reshape(transpose(data(:,pp:Nports:end)),1,[]); for ii = 1 : numel(data_u) fprintf(fid,'%d %d\n',real(data_u(ii)).int,imag(data_u(ii)).int); end diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d_characterize/ifft_stockham_dit.m b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d_characterize/ifft_stockham_dit.m deleted file mode 100755 index 13413b6050..0000000000 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/ifft4096_2d_characterize/ifft_stockham_dit.m +++ /dev/null @@ -1,33 +0,0 @@ -% -% Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -% SPDX-License-Identifier: MIT -% -% Author: Mark Rollins - -function [ifft_o] = ifft_stockham_dit(ifft_i,nt_twid,fi_twid,nt_sig,fi_sig) - N = numel(ifft_i); - Nstage = log2(N); - buff_i = ifft_i; - buff_t = zeros(size(buff_i)); - for stage = Nstage : -1 : 1 - Nhalf = N / 2^stage; - twid = double(fi(exp(-1i*2*pi*[0:Nhalf-1]/(2*Nhalf)),nt_twid,fi_twid)); - stride = 2^(stage-1); - for p = 0 : Nhalf-1 - for q = 0 : stride-1 - % Note: address is not "in-place" - idx0_i = q + stride*(2*p+0); - idx1_i = q + stride*(2*p+1); - idx0_o = q + stride*(p+0 ); - idx1_o = q + stride*(p+Nhalf); - a = buff_i(1+idx0_i); - b = buff_i(1+idx1_i) * conj(twid(1+p)); - buff_t(1+idx0_o) = a + b; - buff_t(1+idx1_o) = a - b; - end - end - buff_i = buff_t; - end - ifft_o = buff_i; - ifft_o = double(fi(ifft_o,nt_sig,fi_sig)); -end diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/tdm_fir/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/tdm_fir/Makefile index 4c92c82731..f8beefb025 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/tdm_fir/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/tdm_fir/Makefile @@ -15,6 +15,8 @@ CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancin DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ --include=${DSPLIB_ROOT}/L1/include/aie \ + --include=${DSPLIB_ROOT}/L1/include/vss/common \ + --include=${DSPLIB_ROOT}/L1/include/vss/vss_fft_ifft_1d \ --include=${DSPLIB_ROOT}/L1/src/aie AIE_OUTPUT := libadf.a diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/tdm_fir_characterize/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/tdm_fir_characterize/Makefile index 4c92c82731..f8beefb025 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/tdm_fir_characterize/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/aie/tdm_fir_characterize/Makefile @@ -15,6 +15,8 @@ CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancin DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ --include=${DSPLIB_ROOT}/L1/include/aie \ + --include=${DSPLIB_ROOT}/L1/include/vss/common \ + --include=${DSPLIB_ROOT}/L1/include/vss/vss_fft_ifft_1d \ --include=${DSPLIB_ROOT}/L1/src/aie AIE_OUTPUT := libadf.a diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_back_transpose/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_back_transpose/Makefile deleted file mode 100755 index 4c9f3aa0b0..0000000000 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_back_transpose/Makefile +++ /dev/null @@ -1,87 +0,0 @@ -# -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -# -# Author: Faisal El-Shabani - -DO_COSIM := false -ECHO := @echo - -PART :=xcve2802-vsvh1760-2MP-e-S - -SSR :=8 -POINT_SIZE :=4096 -VSS_MODE :=1 -KERNEL := ifft_back_transpose_wrapper -KERNEL_SRC := ${DSPLIB_ROOT}/L1/src/hw/ifft_back_transpose/ifft_back_transpose.cpp -XO := ${KERNEL}.xo -HLS_CFG := hls.cfg - -.PHONY: clean all help - -help:: - $(ECHO) "Makefile Usage:" - $(ECHO) " make all" - $(ECHO) " Command to generate the kernel used in this design" - $(ECHO) "" - $(ECHO) " make clean" - $(ECHO) " Command to remove all the generated files." - -all: ${XO} - -${XO}: ${HLS_CFG} ${KERNEL_SRC} - v++ --config ${HLS_CFG} --compile --mode hls --work_dir ${KERNEL} -ifeq (${DO_COSIM},true) - vitis-run --mode hls --config ${HLS_CFG} --csim --work_dir ${KERNEL} - vitis-run --mode hls --config ${HLS_CFG} --cosim --work_dir ${KERNEL} - vitis-run --mode hls --config ${HLS_CFG} --impl --work_dir ${KERNEL} -endif - -${HLS_CFG}: - @echo "#" >> ${HLS_CFG} - @echo "# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved." >> ${HLS_CFG} - @echo "# SPDX-License-Identifier: MIT" >> ${HLS_CFG} - @echo "#" >> ${HLS_CFG} - @echo "part=${PART}" >> ${HLS_CFG} - @echo "[hls]" >> ${HLS_CFG} - @echo "flow_target=vitis" >> ${HLS_CFG} - @echo "clock=3.2ns" >> ${HLS_CFG} - @echo "# C-Synthesis:" >> ${HLS_CFG} - @echo "syn.top=${KERNEL}" >> ${HLS_CFG} - @echo "syn.file=${KERNEL_SRC}" >> ${HLS_CFG} - @echo "syn.file_cflags=${KERNEL_SRC}, -DSSR=${SSR} -DPOINT_SIZE=${POINT_SIZE} -DVSS_MODE=${VSS_MODE}" >> ${HLS_CFG} - @echo "syn.file_csimflags=${KERNEL_SRC}" >> ${HLS_CFG} - @echo "# Testbench:" >> ${HLS_CFG} - @echo "tb.file=tb_wrapper.cpp " >> ${HLS_CFG} - @echo "tb.file=data/stream0_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream1_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream2_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream3_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream4_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream5_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream6_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream7_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream0_o.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream1_o.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream2_o.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream3_o.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream4_o.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream5_o.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream6_o.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream7_o.txt" >> ${HLS_CFG} - @echo "tb.file_cflags=tb_wrapper.cpp,-I${DSPLIB_ROOT}/L1/src/hw/ifft_back_transpose -DSSR=${SSR} -DPOINT_SIZE=${POINT_SIZE} -DVSS_MODE=${VSS_MODE}" >> ${HLS_CFG} - @echo "# C-Simulation:" >> ${HLS_CFG} - @echo "csim.clean=true" >> ${HLS_CFG} - @echo "csim.setup=false" >> ${HLS_CFG} - @echo "# C/RTL Co-Simulation:" >> ${HLS_CFG} - @echo "cosim.setup=false" >> ${HLS_CFG} - @echo "# Package:" >> ${HLS_CFG} - @echo "package.output.file=${KERNEL}.xo" >> ${HLS_CFG} - @echo "package.output.format=xo" >> ${HLS_CFG} - @echo "# OOC Place & Route:" >> ${HLS_CFG} - @echo "vivado.flow=impl" >> ${HLS_CFG} - -clean: - rm -f $(XO)* ${HLS_CFG} *.log vitis-comp.json - rm -rf .Xil _x/ .crashReporter* - rm -rf ${KERNEL} diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_back_transpose/gen_vectors.m b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_back_transpose/gen_vectors.m deleted file mode 100755 index 39e25dd6ef..0000000000 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_back_transpose/gen_vectors.m +++ /dev/null @@ -1,55 +0,0 @@ -% -% Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -% SPDX-License-Identifier: MIT -% -% Author: Faisal El-Shabani - -clear all; -close all; - -% ------------------------------------------------------------ -% Create Permutation Mapping -% ------------------------------------------------------------ - -NSTREAM = 8; -NFFT_1D = 64; -NFFT = NFFT_1D * NFFT_1D; -NSAMP = NFFT_1D; - -% ------------------------------------------------------------ -% Create Testbench Stimulus -% ------------------------------------------------------------ - -% Generate walking sequence pattern for easy testing: -seq_i = [0:NFFT-1]; % These samples are a proxy for 'cint32' values (ie. 64-bits each) -tmp = reshape(seq_i,NFFT_1D,NFFT_1D); -sig_i = tmp; - -% ------------------------------------------------------------ -% Write I/O Files -% ------------------------------------------------------------ - -[~,~,~] = rmdir('data','s'); -[~,~,~] = mkdir('data'); - -% Write streams in polyphase order: -for ss = 1 : NSTREAM - fid = fopen(sprintf('data/stream%d_i.txt',ss-1),'w'); - data = sig_i(:,ss:NSTREAM:end); - for cc = 1 : size(data,2) - for rr = 1 : size(data,1) - fprintf(fid,'%d\n',data(rr,cc)); - end - end - fclose(fid); -end - -% Write streams taken row-wise in polyphase order: -data = reshape(transpose(sig_i),NSTREAM,[]); -for ss = 1 : NSTREAM - fid = fopen(sprintf('data/stream%d_o.txt',ss-1),'w'); - for ii = 1 : size(data,2) - fprintf(fid,'%d\n',data(ss,ii)); - end - fclose(fid); -end diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_back_transpose/tb_wrapper.cpp b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_back_transpose/tb_wrapper.cpp deleted file mode 100755 index 372b9694d6..0000000000 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_back_transpose/tb_wrapper.cpp +++ /dev/null @@ -1,85 +0,0 @@ -// -// Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -// SPDX-License-Identifier: MIT -// -// Author: Faisal El-Shabani - -#include "ifft_back_transpose.h" -#include -#include -#include - -using namespace std; - -// ------------------------------------------------------------ -// Main -// ------------------------------------------------------------ - -int main( void ) -{ - using TT_STREAM = backTransposeCls::TT_STREAM; - using TT_SAMPLE = backTransposeCls::TT_SAMPLE; - - // Create DDR4 contents: - TT_STREAM sig_i[SSR]; - TT_SAMPLE sig_g[SSR][POINT_SIZE/SSR*2]; - - // Load stream stimulus: - for (int ss=0; ss < SSR; ss++) { - std::ifstream ss_i; - ss_i.open("stream" + std::to_string(ss) + "_i.txt",std::ifstream::in); - for (int dd=0; dd < POINT_SIZE/SSR; dd+=2) { - int d0,d1; - ss_i >> d0; - ss_i >> d1; - sig_i[ss].write( ( TT_SAMPLE(d1), TT_SAMPLE(d0) ) ); - } - ss_i.close(); - } - - // Load golden outputs: - for (int ss=0; ss < SSR; ss++) { - std::ifstream ss_i; - ss_i.open("stream" + std::to_string(ss) + "_o.txt",std::ifstream::in); - for (int dd=0; dd < POINT_SIZE*2/SSR; dd++) { - int d0; - ss_i >> d0; - sig_g[ss][dd] = TT_SAMPLE(d0); - } - ss_i.close(); - } - - for (int ss=0; ss < SSR; ss++) { - cout << "Stream sig_i" << ss << " Size: " << sig_i[ss].size() << endl; - } - - // Run DUT: - TT_STREAM sig_o[SSR]; - ifft_back_transpose_wrapper( sig_i, sig_o ); - - for (int ss=0; ss < SSR; ss++) { - cout << "Stream sig_o" << ss << " Size: " << sig_o[ss].size() << endl; - } - - // Check output streams: - bool flag = 0; - for (int ss=0; ss < SSR; ss++) { - for (int dd=0; dd < POINT_SIZE/SSR; dd+=2) { - TT_SAMPLE act0_o, act1_o; - (act1_o,act0_o) = sig_o[ss].read(); - TT_SAMPLE act0_g, act1_g; - act0_g = sig_g[ss][dd]; - act1_g = sig_g[ss][dd+1]; - bool this_flag = (act0_o != act0_g) || (act1_o != act1_g); - flag |= this_flag; - if ( this_flag ) { - cout << "ss: " << ss << " dd: " << dd << " act0_o: " << act0_o << " act0_g: " << act0_g << endl; - cout << "ss: " << ss << " dd: " << dd+1 << " act1_o: " << act1_o << " act1_g: " << act1_g << endl; - } - } - } - if ( flag == 0 ) cout << "--- PASSED ---" << endl; - else cout << "*** FAILED ***" << endl; - return( flag ); -} - diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_front_transpose/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_front_transpose/Makefile deleted file mode 100755 index 7d5b4ceb94..0000000000 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_front_transpose/Makefile +++ /dev/null @@ -1,86 +0,0 @@ -# -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -# -# Author: Faisal El-Shabani - -DO_COSIM := false -ECHO := @echo - -PART :=xcve2802-vsvh1760-2MP-e-S - -SSR :=8 -POINT_SIZE :=4096 -KERNEL := ifft_front_transpose_wrapper -KERNEL_SRC := ${DSPLIB_ROOT}/L1/src/hw/ifft_front_transpose/ifft_front_transpose.cpp -XO := ${KERNEL}.xo -HLS_CFG := hls.cfg - -.PHONY: clean all help - -help:: - $(ECHO) "Makefile Usage:" - $(ECHO) " make all" - $(ECHO) " Command to generate the kernel used in this design" - $(ECHO) "" - $(ECHO) " make clean" - $(ECHO) " Command to remove all the generated files." - -all: ${XO} - -${XO}: ${HLS_CFG} ${KERNEL_SRC} - v++ --config ${HLS_CFG} --compile --mode hls --work_dir ${KERNEL} -ifeq (${DO_COSIM},true) - vitis-run --mode hls --config ${HLS_CFG} --csim --work_dir ${KERNEL} - vitis-run --mode hls --config ${HLS_CFG} --cosim --work_dir ${KERNEL} - vitis-run --mode hls --config ${HLS_CFG} --impl --work_dir ${KERNEL} -endif - -${HLS_CFG}: - @echo "#" >> ${HLS_CFG} - @echo "# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved." >> ${HLS_CFG} - @echo "# SPDX-License-Identifier: MIT" >> ${HLS_CFG} - @echo "#" >> ${HLS_CFG} - @echo "part=${PART}" >> ${HLS_CFG} - @echo "[hls]" >> ${HLS_CFG} - @echo "flow_target=vitis" >> ${HLS_CFG} - @echo "clock=3.2ns" >> ${HLS_CFG} - @echo "# C-Synthesis:" >> ${HLS_CFG} - @echo "syn.top=${KERNEL}" >> ${HLS_CFG} - @echo "syn.file=${KERNEL_SRC}" >> ${HLS_CFG} - @echo "syn.file_cflags=${KERNEL_SRC}, -DSSR=${SSR} -DPOINT_SIZE=${POINT_SIZE}" >> ${HLS_CFG} - @echo "syn.file_csimflags=${KERNEL_SRC}" >> ${HLS_CFG} - @echo "# Testbench:" >> ${HLS_CFG} - @echo "tb.file=tb_wrapper.cpp" >> ${HLS_CFG} - @echo "tb.file=data/stream0_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream1_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream2_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream3_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream4_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream5_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream6_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream7_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream0_o.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream1_o.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream2_o.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream3_o.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream4_o.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream5_o.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream6_o.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream7_o.txt" >> ${HLS_CFG} - @echo "tb.file_cflags=tb_wrapper.cpp,-I${DSPLIB_ROOT}/L1/src/hw/ifft_front_transpose -DSSR=${SSR} -DPOINT_SIZE=${POINT_SIZE}" >> ${HLS_CFG} - @echo "# C-Simulation:" >> ${HLS_CFG} - @echo "csim.clean=true" >> ${HLS_CFG} - @echo "csim.setup=false" >> ${HLS_CFG} - @echo "# C/RTL Co-Simulation:" >> ${HLS_CFG} - @echo "cosim.setup=false" >> ${HLS_CFG} - @echo "# Package:" >> ${HLS_CFG} - @echo "package.output.file=${KERNEL}.xo" >> ${HLS_CFG} - @echo "package.output.format=xo" >> ${HLS_CFG} - @echo "# OOC Place & Route:" >> ${HLS_CFG} - @echo "vivado.flow=impl" >> ${HLS_CFG} - -clean: - rm -f $(XO)* ${HLS_CFG} *.log vitis-comp.json - rm -rf .Xil _x/ .crashReporter* - rm -rf ${KERNEL} diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_front_transpose/gen_vectors.m b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_front_transpose/gen_vectors.m deleted file mode 100755 index 0091d7660b..0000000000 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_front_transpose/gen_vectors.m +++ /dev/null @@ -1,55 +0,0 @@ -% -% Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -% SPDX-License-Identifier: MIT -% -% Author: Faisal El-Shabani - -clear all; -close all; - -% ------------------------------------------------------------ -% Create Permutation Mapping -% ------------------------------------------------------------ - -NSTREAM = 8; -NFFT_1D = 64; -NFFT = NFFT_1D * NFFT_1D; -NSAMP = NFFT_1D; - -% ------------------------------------------------------------ -% Create Testbench Stimulus -% ------------------------------------------------------------ - -% Generate walking sequence pattern for easy testing: -seq_i = [0:NFFT-1]; % These samples are a proxy for 'cint32' values (ie. 64-bits each) -tmp = reshape(seq_i,NFFT_1D,NFFT_1D); -sig_i = tmp; - -% ------------------------------------------------------------ -% Write I/O Files -% ------------------------------------------------------------ - -[~,~,~] = rmdir('data','s'); -[~,~,~] = mkdir('data'); - -% Write streams in polyphase order: -for ss = 1 : NSTREAM - fid = fopen(sprintf('data/stream%d_i.txt',ss-1),'w'); - data = reshape(sig_i,NSTREAM,[]); - for rr = 1 : size(data(ss,:),2) - fprintf(fid,'%d\n',data(ss,rr)); - end - fclose(fid); -end - -% Write streams taken row-wise in polyphase order: -for ss = 1 : NSTREAM - data = sig_i(ss:NSTREAM:end,:); - fid = fopen(sprintf('data/stream%d_o.txt',ss-1),'w'); - for ii = 1 : size(data,1) - for jj = 1 : size(data,2) - fprintf(fid,'%d\n',data(ii,jj)); - end - end - fclose(fid); -end diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_front_transpose/tb_wrapper.cpp b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_front_transpose/tb_wrapper.cpp deleted file mode 100755 index 8efc8f0d20..0000000000 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_front_transpose/tb_wrapper.cpp +++ /dev/null @@ -1,85 +0,0 @@ -// -// Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -// SPDX-License-Identifier: MIT -// -// Author: Faisal El-Shabani - -#include "ifft_front_transpose.h" -#include -#include -#include - -using namespace std; - -// ------------------------------------------------------------ -// Main -// ------------------------------------------------------------ - -int main( void ) -{ - using TT_STREAM = frontTransposeCls::TT_STREAM; - using TT_SAMPLE = frontTransposeCls::TT_SAMPLE; - - // Create DDR4 contents: - TT_STREAM sig_i[SSR]; - TT_SAMPLE sig_g[SSR][POINT_SIZE/SSR*2]; - - // Load stream stimulus: - for (int ss=0; ss < SSR; ss++) { - std::ifstream ss_i; - ss_i.open("stream" + std::to_string(ss) + "_i.txt",std::ifstream::in); - for (int dd=0; dd < POINT_SIZE/SSR; dd+=2) { - int d0,d1; - ss_i >> d0; - ss_i >> d1; - sig_i[ss].write( ( TT_SAMPLE(d1), TT_SAMPLE(d0) ) ); - } - ss_i.close(); - } - - for (int ss=0; ss < SSR; ss++) { - cout << "Stream sig_i" << ss << " Size: " << sig_i[ss].size() << endl; - } - - // Load golden outputs: - for (int ss=0; ss < SSR; ss++) { - std::ifstream ss_i; - ss_i.open("stream" + std::to_string(ss) + "_o.txt",std::ifstream::in); - for (int dd=0; dd < POINT_SIZE*2/SSR; dd++) { - int d0; - ss_i >> d0; - sig_g[ss][dd] = TT_SAMPLE(d0); - } - ss_i.close(); - } - - // Run DUT: - TT_STREAM sig_o[SSR]; - ifft_front_transpose_wrapper( sig_i, sig_o ); - - for (int ss=0; ss < SSR; ss++) { - cout << "Stream sig_o" << ss << " Size: " << sig_o[ss].size() << endl; - } - - // Check output streams: - bool flag = 0; - for (int ss=0; ss < SSR; ss++) { - for (int dd=0; dd < POINT_SIZE/SSR; dd+=2) { - TT_SAMPLE act0_o, act1_o; - (act1_o,act0_o) = sig_o[ss].read(); - TT_SAMPLE act0_g, act1_g; - act0_g = sig_g[ss][dd]; - act1_g = sig_g[ss][dd+1]; - bool this_flag = (act0_o != act0_g) || (act1_o != act1_g); - flag |= this_flag; - if ( this_flag ) { - cout << "ss: " << ss << " dd: " << dd << " act0_o: " << act0_o << " act0_g: " << act0_g << endl; - cout << "ss: " << ss << " dd: " << dd+1 << " act1_o: " << act1_o << " act1_g: " << act1_g << endl; - } - } - } - if ( flag == 0 ) cout << "--- PASSED ---" << endl; - else cout << "*** FAILED ***" << endl; - return( flag ); -} - diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_mid_joiner/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_mid_joiner/Makefile new file mode 100755 index 0000000000..e52c761844 --- /dev/null +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_mid_joiner/Makefile @@ -0,0 +1,56 @@ +# +# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +ECHO := @echo + +PART :=xcve2802-vsvh1760-2MP-e-S + +DATAWIDTH := 64 +SSR := 8 +KERNEL := joiner +KERNEL_SRC := ${DSPLIB_ROOT}/L1/src/hw/common_fns/axis_split_join.cpp +XO := ${KERNEL}.xo +HLS_CFG := hls.cfg + +.PHONY: clean all help + +help:: + $(ECHO) "Makefile Usage:" + $(ECHO) " make all" + $(ECHO) " Command to generate the kernel used in this design" + $(ECHO) "" + $(ECHO) " make clean" + $(ECHO) " Command to remove all the generated files." + +all: ${XO} + +${XO}: ${HLS_CFG} ${KERNEL_SRC} + v++ --config ${HLS_CFG} --compile --mode hls --work_dir ${KERNEL} + +${HLS_CFG}: + @echo "#" >> ${HLS_CFG} + @echo "# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved." >> ${HLS_CFG} + @echo "# SPDX-License-Identifier: MIT" >> ${HLS_CFG} + @echo "#" >> ${HLS_CFG} + @echo "part=${PART}" >> ${HLS_CFG} + @echo "[hls]" >> ${HLS_CFG} + @echo "flow_target=vitis" >> ${HLS_CFG} + @echo "clock=3.2ns" >> ${HLS_CFG} + @echo "# C-Synthesis:" >> ${HLS_CFG} + @echo "syn.top=${KERNEL}_wrapper" >> ${HLS_CFG} + @echo "syn.file=${KERNEL_SRC}" >> ${HLS_CFG} + @echo "syn.file_cflags=${KERNEL_SRC}, -I${DSPLIB_ROOT}/L1/include -DSSR=${SSR} -DSAMPLE_SIZE=${DATAWIDTH}" >> ${HLS_CFG} + @echo "# Package:" >> ${HLS_CFG} + @echo "package.output.file=${KERNEL}.xo" >> ${HLS_CFG} + @echo "package.output.format=xo" >> ${HLS_CFG} + @echo "# OOC Place & Route:" >> ${HLS_CFG} + @echo "vivado.flow=impl" >> ${HLS_CFG} + +clean: + rm -f $(XO)* ${HLS_CFG} *.log vitis-comp.json + rm -rf .Xil _x/ .crashReporter* + rm -rf ${KERNEL} + diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_mid_splitter/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_mid_splitter/Makefile new file mode 100755 index 0000000000..8cd93387a3 --- /dev/null +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_mid_splitter/Makefile @@ -0,0 +1,56 @@ +# +# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +ECHO := @echo + +PART :=xcve2802-vsvh1760-2MP-e-S + +DATAWIDTH := 64 +SSR := 8 +KERNEL := splitter +KERNEL_SRC := ${DSPLIB_ROOT}/L1/src/hw/common_fns/axis_split_join.cpp +XO := ${KERNEL}.xo +HLS_CFG := hls.cfg + +.PHONY: clean all help + +help:: + $(ECHO) "Makefile Usage:" + $(ECHO) " make all" + $(ECHO) " Command to generate the kernel used in this design" + $(ECHO) "" + $(ECHO) " make clean" + $(ECHO) " Command to remove all the generated files." + +all: ${XO} + +${XO}: ${HLS_CFG} ${KERNEL_SRC} + v++ --config ${HLS_CFG} --compile --mode hls --work_dir ${KERNEL} + +${HLS_CFG}: + @echo "#" >> ${HLS_CFG} + @echo "# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved." >> ${HLS_CFG} + @echo "# SPDX-License-Identifier: MIT" >> ${HLS_CFG} + @echo "#" >> ${HLS_CFG} + @echo "part=${PART}" >> ${HLS_CFG} + @echo "[hls]" >> ${HLS_CFG} + @echo "flow_target=vitis" >> ${HLS_CFG} + @echo "clock=3.2ns" >> ${HLS_CFG} + @echo "# C-Synthesis:" >> ${HLS_CFG} + @echo "syn.top=${KERNEL}_wrapper" >> ${HLS_CFG} + @echo "syn.file=${KERNEL_SRC}" >> ${HLS_CFG} + @echo "syn.file_cflags=${KERNEL_SRC}, -I${DSPLIB_ROOT}/L1/include -DSSR=${SSR} -DSAMPLE_SIZE=${DATAWIDTH}" >> ${HLS_CFG} + @echo "# Package:" >> ${HLS_CFG} + @echo "package.output.file=${KERNEL}.xo" >> ${HLS_CFG} + @echo "package.output.format=xo" >> ${HLS_CFG} + @echo "# OOC Place & Route:" >> ${HLS_CFG} + @echo "vivado.flow=impl" >> ${HLS_CFG} + +clean: + rm -f $(XO)* ${HLS_CFG} *.log vitis-comp.json + rm -rf .Xil _x/ .crashReporter* + rm -rf ${KERNEL} + diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_mid_transpose/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_mid_transpose/Makefile new file mode 100755 index 0000000000..d81fd3d829 --- /dev/null +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_mid_transpose/Makefile @@ -0,0 +1,62 @@ +# +# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +ECHO := @echo + +PART :=xcve2802-vsvh1760-2MP-e-S + +DATAWIDTH := 64 +SSR := 16 +POINT_SIZE := 4096 +DATA_TYPE := cint32 +TWIDDLE_TYPE := cint16 +VSS_MODE := 1 + +KERNEL := mid_transpose_wrapper +KERNEL_SRC := ${DSPLIB_ROOT}/L1/src/hw/mid_transpose/mid_transpose.cpp +XO := ${KERNEL}.xo +HLS_CFG := hls.cfg + +.PHONY: clean all help + +help:: + $(ECHO) "Makefile Usage:" + $(ECHO) " make all" + $(ECHO) " Command to generate the kernel used in this design" + $(ECHO) "" + $(ECHO) " make clean" + $(ECHO) " Command to remove all the generated files." + +all: ${XO} + +${XO}: ${HLS_CFG} ${KERNEL_SRC} + v++ --config ${HLS_CFG} --compile --mode hls --work_dir ${KERNEL} + +${HLS_CFG}: + @echo "#" >> ${HLS_CFG} + @echo "# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved." >> ${HLS_CFG} + @echo "# SPDX-License-Identifier: MIT" >> ${HLS_CFG} + @echo "#" >> ${HLS_CFG} + @echo "part=${PART}" >> ${HLS_CFG} + @echo "[hls]" >> ${HLS_CFG} + @echo "flow_target=vitis" >> ${HLS_CFG} + @echo "clock=3.2ns" >> ${HLS_CFG} + @echo "# C-Synthesis:" >> ${HLS_CFG} + @echo "syn.top=${KERNEL}" >> ${HLS_CFG} + @echo "syn.cflags= -I${DSPLIB_ROOT}/L1/include/vss/common -I${DSPLIB_ROOT}/L1/include/vss/vss_fft_ifft_1d" >> ${HLS_CFG} + @echo "syn.file=${KERNEL_SRC}" >> ${HLS_CFG} + @echo "syn.file_cflags=${KERNEL_SRC}, -DSSR=${SSR} -DPOINT_SIZE=${POINT_SIZE} -DDATAWIDTH=${DATAWIDTH} -DDATA_TYPE=${DATA_TYPE} -DTWIDDLE_TYPE=${TWIDDLE_TYPE} -DVSS_MODE=${VSS_MODE}" >> ${HLS_CFG} + @echo "# Package:" >> ${HLS_CFG} + @echo "package.output.file=${KERNEL}.xo" >> ${HLS_CFG} + @echo "package.output.format=xo" >> ${HLS_CFG} + @echo "# OOC Place & Route:" >> ${HLS_CFG} + @echo "vivado.flow=impl" >> ${HLS_CFG} + +clean: + rm -f $(XO)* ${HLS_CFG} *.log vitis-comp.json + rm -rf .Xil _x/ .crashReporter* + rm -rf ${KERNEL} + diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_transpose/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_transpose/Makefile deleted file mode 100755 index 1752c847e1..0000000000 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_transpose/Makefile +++ /dev/null @@ -1,87 +0,0 @@ -# -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -# -# Author: Faisal El-Shabani - -DO_COSIM := false -ECHO := @echo - -PART :=xcve2802-vsvh1760-2MP-e-S - -SSR :=8 -POINT_SIZE :=4096 -KERNEL := ifft_transpose_wrapper -KERNEL_SRC := ${DSPLIB_ROOT}/L1/src/hw/ifft_transpose/ifft_transpose.cpp -XO := ${KERNEL}.xo -HLS_CFG := hls.cfg - -.PHONY: clean all help - -help:: - $(ECHO) "Makefile Usage:" - $(ECHO) " make all" - $(ECHO) " Command to generate the kernel used in this design" - $(ECHO) "" - $(ECHO) " make clean" - $(ECHO) " Command to remove all the generated files." - -all: ${XO} - -${XO}: ${HLS_CFG} ${KERNEL_SRC} - v++ --config ${HLS_CFG} --compile --mode hls --work_dir ${KERNEL} -ifeq (${DO_COSIM},true) - vitis-run --mode hls --config ${HLS_CFG} --csim --work_dir ${KERNEL} - vitis-run --mode hls --config ${HLS_CFG} --cosim --work_dir ${KERNEL} - vitis-run --mode hls --config ${HLS_CFG} --impl --work_dir ${KERNEL} -endif - -${HLS_CFG}: - @echo "#" >> ${HLS_CFG} - @echo "# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved." >> ${HLS_CFG} - @echo "# SPDX-License-Identifier: MIT" >> ${HLS_CFG} - @echo "#" >> ${HLS_CFG} - @echo "part=${PART}" >> ${HLS_CFG} - @echo "[hls]" >> ${HLS_CFG} - @echo "flow_target=vitis" >> ${HLS_CFG} - @echo "clock=3.2ns" >> ${HLS_CFG} - @echo "# C-Synthesis:" >> ${HLS_CFG} - @echo "syn.top=${KERNEL}" >> ${HLS_CFG} - @echo "syn.file=${KERNEL_SRC}" >> ${HLS_CFG} - @echo "syn.file_cflags=${KERNEL_SRC}, -DSSR=${SSR} -DPOINT_SIZE=${POINT_SIZE}" >> ${HLS_CFG} - @echo "syn.file_csimflags=${KERNEL_SRC}" >> ${HLS_CFG} - @echo "# Testbench:" >> ${HLS_CFG} - @echo "tb.file=tb_wrapper.cpp" >> ${HLS_CFG} - @echo "tb.file=data/stream0_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream1_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream2_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream3_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream4_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream5_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream6_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream7_i.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream0_o.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream1_o.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream2_o.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream3_o.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream4_o.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream5_o.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream6_o.txt" >> ${HLS_CFG} - @echo "tb.file=data/stream7_o.txt" >> ${HLS_CFG} - @echo "tb.file_cflags=tb_wrapper.cpp,-I${DSPLIB_ROOT}/L1/src/hw/ifft_transpose -DSSR=${SSR} -DPOINT_SIZE=${POINT_SIZE}" >> ${HLS_CFG} - @echo "# C-Simulation:" >> ${HLS_CFG} - @echo "csim.clean=true" >> ${HLS_CFG} - @echo "csim.setup=false" >> ${HLS_CFG} - @echo "# C/RTL Co-Simulation:" >> ${HLS_CFG} - @echo "cosim.setup=false" >> ${HLS_CFG} - @echo "# Package:" >> ${HLS_CFG} - @echo "package.output.file=${KERNEL}.xo" >> ${HLS_CFG} - @echo "package.output.format=xo" >> ${HLS_CFG} - @echo "# OOC Place & Route:" >> ${HLS_CFG} - @echo "vivado.flow=impl" >> ${HLS_CFG} - -clean: - rm -f $(XO)* ${HLS_CFG} *.log vitis-comp.json - rm -rf .Xil _x/ .crashReporter* - rm -rf ${KERNEL} - diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_transpose/compute_addr_2d.m b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_transpose/compute_addr_2d.m deleted file mode 100755 index 86891d3185..0000000000 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_transpose/compute_addr_2d.m +++ /dev/null @@ -1,23 +0,0 @@ -% -% Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -% SPDX-License-Identifier: MIT -% -% Author: Mark Rollins - -function [addr_o] = compute_addr_2d(N1,N2,dim) - N = N1 * N2; - addr_i = [0:N-1]; - pattern_i = reshape(addr_i,N1,N2); - switch (dim) - % Linear addressing for N1 dimension: - case 1, - addr_o = addr_i; - - case 2, - % Step-by-N2 addressing for N2 dimension: - addr_o = []; - for rr = 1 : N1 - addr_o = [addr_o,reshape(pattern_i(rr,:),1,[])]; - end - end -end \ No newline at end of file diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_transpose/gen_vectors.m b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_transpose/gen_vectors.m deleted file mode 100755 index e148595e56..0000000000 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_transpose/gen_vectors.m +++ /dev/null @@ -1,75 +0,0 @@ -% -% Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -% SPDX-License-Identifier: MIT -% -% Author: Mark Rollins - -clear all; -close all; - -% ------------------------------------------------------------ -% Create Permutation Mapping -% ------------------------------------------------------------ - -Ntransform = 1; -NSTREAM = 8; -NFFT_1D = 64; -NFFT = NFFT_1D * NFFT_1D; -NSAMP = NFFT_1D; - -% ------------------------------------------------------------ -% Create Testbench Stimulus -% ------------------------------------------------------------ - -pattern = 1; - -seq_i = zeros(NFFT_1D,NFFT_1D,Ntransform); - -if (pattern == 1 ) - % Use pattern to prove out functionality: - for tt = 1 : Ntransform - tmp = reshape(compute_addr_2d(NFFT_1D,NFFT_1D,1),NFFT_1D,NFFT_1D); - seq_i(:,:,tt) = tmp; - end -else - limit = 2^16-1; - seq_i = randi([-(limit+1),limit],NSAMP,NSAMP,Ntransform); -end - -% ------------------------------------------------------------ -% Write I/O Files -% ------------------------------------------------------------ - -[~,~,~] = rmdir('data','s'); -[~,~,~] = mkdir('data'); - - -% Write streams in polyphase order: -for ss = 1 : NSTREAM - fid = fopen(sprintf('data/stream%d_i.txt',ss-1),'a'); - for tt = 1 : Ntransform - data = seq_i(ss:NSTREAM:end,:,tt); - for rr = 1 : size(data,1) - for cc = 1 : size(data,2) - % Data is coming in along rows: - fprintf(fid,'%d\n',data(rr,cc)); - end - end - end - fclose(fid); -end - -% Write streams in polyphase order: -for ss = 1 : NSTREAM - fid = fopen(sprintf('data/stream%d_o.txt',ss-1),'a'); - for tt = 1 : Ntransform - data = seq_i(:,ss:NSTREAM:end,tt); - for cc = 1 : size(data,2) - for rr = 1 : size(data,1) - % Data is leaving along columns: - fprintf(fid,'%d\n',data(rr,cc)); - end - end - end - fclose(fid); -end \ No newline at end of file diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_transpose/tb_wrapper.cpp b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_transpose/tb_wrapper.cpp deleted file mode 100755 index a16f1b76ce..0000000000 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/ifft_transpose/tb_wrapper.cpp +++ /dev/null @@ -1,85 +0,0 @@ -// -// Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -// SPDX-License-Identifier: MIT -// -// Author: Faisal El-Shabani - -#include "ifft_transpose.h" -#include -#include -#include - -using namespace std; - -// ------------------------------------------------------------ -// Main -// ------------------------------------------------------------ - -int main( void ) -{ - using TT_STREAM = midTransposeCls::TT_STREAM; - using TT_SAMPLE = midTransposeCls::TT_SAMPLE; - - // Create DDR4 contents: - TT_STREAM sig_i[SSR]; - TT_SAMPLE sig_g[SSR][POINT_SIZE/SSR]; - - // Load stream stimulus: - for (int ss=0; ss < SSR; ss++) { - std::ifstream ss_i; - ss_i.open("stream" + std::to_string(ss) + "_i.txt",std::ifstream::in); - for (int dd=0; dd < POINT_SIZE/SSR; dd+=2) { - int d0,d1; - ss_i >> d0; - ss_i >> d1; - sig_i[ss].write( ( TT_SAMPLE(d1), TT_SAMPLE(d0) ) ); - } - ss_i.close(); - } - - // Load golden outputs: - for (int ss=0; ss < SSR; ss++) { - std::ifstream ss_o; - ss_o.open("stream" + std::to_string(ss) + "_o.txt",std::ifstream::in); - for (int dd=0; dd < POINT_SIZE/SSR; dd++) { - int d0; - ss_o >> d0; - sig_g[ss][dd] = TT_SAMPLE(d0); - } - ss_o.close(); - } - - for (int ss=0; ss < SSR; ss++) { - cout << "Stream sig_i" << ss << " Size: " << sig_i[ss].size() << endl; - } - - // Run DUT: - TT_STREAM sig_o[SSR]; - ifft_transpose_wrapper( sig_i, sig_o ); - - for (int ss=0; ss < SSR; ss++) { - cout << "Stream sig_o" << ss << " Size: " << sig_o[ss].size() << endl; - } - - // Check output streams: - bool flag = 0; - for (int ss=0; ss < SSR; ss++) { - for (int dd=0; dd < POINT_SIZE/SSR; dd+=2) { - TT_SAMPLE act0_o, act1_o; - (act1_o,act0_o) = sig_o[ss].read(); - TT_SAMPLE act0_g, act1_g; - act0_g = sig_g[ss][dd]; - act1_g = sig_g[ss][dd+1]; - bool this_flag = (act0_o != act0_g) || (act1_o != act1_g); - flag |= this_flag; - if ( this_flag ) { - cout << "ss: " << ss << " dd: " << dd << " act0_o: " << act0_o << " act0_g: " << act0_g << endl; - cout << "ss: " << ss << " dd: " << dd+1 << " act1_o: " << act1_o << " act1_g: " << act1_g << endl; - } - } - } - if ( flag == 0 ) cout << "--- PASSED ---" << endl; - else cout << "*** FAILED ***" << endl; - return( flag ); -} - diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/merge_4x1/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/merge_4x1/Makefile index e608fe3741..7836b76971 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/merge_4x1/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/merge_4x1/Makefile @@ -28,7 +28,7 @@ ${XO}: ${KERNEL_SRC} ifeq (${DO_COSIM},true) vitis-run --mode hls --config hls.cfg --csim --work_dir ${KERNEL} vitis-run --mode hls --config hls.cfg --cosim --work_dir ${KERNEL} - vitis-run --mode hls --config hls.cfg --impl --work_dir ${KERNEL} +# vitis-run --mode hls --config hls.cfg --impl --work_dir ${KERNEL} endif clean: diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/merge_4x1/hls.cfg b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/merge_4x1/hls.cfg index 07ed971f6d..6bc457c2d7 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/merge_4x1/hls.cfg +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/merge_4x1/hls.cfg @@ -27,7 +27,8 @@ csim.setup=false # C/RTL Co-Simulation: cosim.setup=false -cosim.wave_debug=false +cosim.wave_debug=true +cosim.tool=xsim cosim.trace_level=port # Package: diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/merge_4x1/merge_4x1.cpp b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/merge_4x1/merge_4x1.cpp index 1cbe2825e7..93053e714f 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/merge_4x1/merge_4x1.cpp +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/merge_4x1/merge_4x1.cpp @@ -11,30 +11,28 @@ using namespace merge_4x1; // Consumer // ------------------------------------------------------------ -void consumer( TT_STREAM sig_i[NSTREAM_I], hls::stream_of_blocks& ss ) +void consumer( TT_STREAM sig_i[NSTREAM_I], TT_BLOCK& ss ) { -#pragma HLS pipeline II=8 - hls::write_lock WL(ss); - WL[ 0] = sig_i[ 0].read(); - WL[ 1] = sig_i[ 1].read(); - WL[ 2] = sig_i[ 2].read(); - WL[ 3] = sig_i[ 3].read(); +#pragma HLS pipeline II=4 + ss[ 0] = sig_i[ 0].read(); + ss[ 1] = sig_i[ 1].read(); + ss[ 2] = sig_i[ 2].read(); + ss[ 3] = sig_i[ 3].read(); } // ------------------------------------------------------------ // Producer // ------------------------------------------------------------ -void producer( hls::stream_of_blocks& ss, TT_STREAM& sig_o ) +void producer( TT_BLOCK& ss, TT_STREAM& sig_o ) { -#pragma HLS pipeline II=8 +#pragma HLS pipeline II=4 // We produce 8 samples over 8 cycles (two cint32 @ 312.5 MHz) // Inputs arrive in polyphase order: - hls::read_lock RL(ss); - TT_SAMPLE v00, v04; (v04,v00) = RL[ 0]; - TT_SAMPLE v01, v05; (v05,v01) = RL[ 1]; - TT_SAMPLE v02, v06; (v06,v02) = RL[ 2]; - TT_SAMPLE v03, v07; (v07,v03) = RL[ 3]; + TT_SAMPLE v00, v04; (v04,v00) = ss[ 0]; + TT_SAMPLE v01, v05; (v05,v01) = ss[ 1]; + TT_SAMPLE v02, v06; (v06,v02) = ss[ 2]; + TT_SAMPLE v03, v07; (v07,v03) = ss[ 3]; // Restore linear order: sig_o.write( (v01,v00) ); sig_o.write( (v03,v02) ); @@ -51,15 +49,13 @@ void merge_4x1_wrapper( TT_STREAM sig_i[NSTREAM_I], TT_STREAM& sig_o ) #pragma HLS interface mode=ap_ctrl_none port=return #pragma HLS interface axis port=sig_i #pragma HLS interface axis port=sig_o +#pragma HLS dataflow - hls::stream_of_blocks ss; + TT_BLOCK ss; #pragma HLS bind_storage variable=ss type=ram_s2p impl=lutram +#pragma HLS array_partition variable=ss complete dim=1 -#pragma HLS dataflow consumer( sig_i, ss ); producer( ss, sig_o ); } - - - diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/merge_8x4/hls.cfg b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/merge_8x4/hls.cfg index 001a0276ac..019c21977c 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/merge_8x4/hls.cfg +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/hls/merge_8x4/hls.cfg @@ -38,7 +38,8 @@ csim.setup=false # C/RTL Co-Simulation: cosim.setup=false -cosim.wave_debug=false +cosim.wave_debug=true +cosim.tool=xsim cosim.trace_level=port # Package: diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/images/2D_4k_IFFT_VSS_MODE_1_SSR_POWER_2.png 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b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/images/ifft4096_2d_characterize_trace_view.png differ diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/ps_apps/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/ps_apps/Makefile index 2403d109c7..e359314a92 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/ps_apps/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/ps_apps/Makefile @@ -23,6 +23,8 @@ GCC_INCLUDES := -I${SYSROOT}/usr/include \ -I../aie/tdm_fir \ -I${DSPLIB_ROOT}/L2/include/aie \ -I${DSPLIB_ROOT}/L1/include/aie \ + -I${DSPLIB_ROOT}/L1/include/vss/common \ + -I${DSPLIB_ROOT}/L1/include/vss/vss_fft_ifft_1d \ -I${DSPLIB_ROOT}/L1/src/aie \ -I${DSPLIB_ROOT}/L1/tests/aie/inc \ -I${DSPLIB_ROOT}/L1/tests/aie/src \ diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/ps_apps/host.cpp b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/ps_apps/host.cpp index fc7a04714b..587058d98a 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/ps_apps/host.cpp +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/ps_apps/host.cpp @@ -36,9 +36,6 @@ static constexpr unsigned NUM_SAMPLES_O = 4 * 4096; // 4 transforms worth of static constexpr unsigned DDR_BUFFSIZE_I_BYTES = NUM_SAMPLES_I * 4; // Each real/imag sample is 4 bytes static constexpr unsigned DDR_BUFFSIZE_O_BYTES = NUM_SAMPLES_O * 8; // Each real/imag sample is 8 bytes -static constexpr unsigned TOTAL_O_BYTES = DDR_BUFFSIZE_O_BYTES * LOOP_CNT_O; -static constexpr double TARGET_THROUGHPUT = 2394; // Measured in hw_emu 2025.1 - // ------------------------------------------------------------ // Main @@ -147,11 +144,6 @@ int main(int argc, char* argv[]) dma_snk_run.set_arg( 2, LOOP_CNT_O ); std::cout << STR_PASSED << "dma_snk_run.set_arg( 2, LOOP_CNT_O=" << LOOP_CNT_O << " )" << std::endl; - // Start throughput profiling. Design has 8 output PLIOs. Measure on one and scale the result accordingly. - xrt::aie::profiling handle(my_device); - std::cout << STR_PASSED << "xrt::aie::profiling handle(my_device);" << std::endl; - handle.start(xrt::aie::profiling::profiling_option::io_stream_start_to_bytes_transferred_cycles,"aie_dut.back_o[0]","",TOTAL_O_BYTES/8); // Measure on one PLIO, scale to get total design throughput - dma_snk_run.start(); std::cout << STR_PASSED << "dma_snk_run.start()" << std::endl; @@ -164,14 +156,6 @@ int main(int argc, char* argv[]) dma_snk_run.wait(); std::cout << STR_PASSED << "dma_snk_run.wait()" << std::endl; - // ------------------------------------------------------------ - // Measure Throughput - // ------------------------------------------------------------ - - long long cycle_count = handle.read(); - handle.stop(); - double throughput = (double) TOTAL_O_BYTES / ((cycle_count) * 0.8 * 1e-3); // Measure on one PLIO, scale to get total design throughput - // ------------------------------------------------------------ // Retrieve Results // ------------------------------------------------------------ @@ -208,12 +192,12 @@ int main(int argc, char* argv[]) int err_re = abs(val_g_re - val_a_re); int err_im = abs(val_g_im - val_a_im); bool this_flag = ( err_re > level ) || ( err_im > level ); // Matlab is not bit accurate - std::cout << "ss: " << (ss>>1) - << " Gld: " << val_g_re << " " << val_g_im - << " Act: " << val_a_re << " " << val_a_im - << " Err: " << err_re << " " << err_im; - if ( this_flag == 1 ) std::cout << " ***"; - std::cout << std::endl; + if ( this_flag == 1 ) { + std::cout << "ss: " << (ss>>1) + << " Gld: " << val_g_re << " " << val_g_im + << " Act: " << val_a_re << " " << val_a_im + << " Err: " << err_re << " " << err_im << std::endl; + } flag |= this_flag; max_err = ( err_re > max_err ) ? err_re : max_err; max_err = ( err_im > max_err ) ? err_im : max_err; @@ -221,21 +205,13 @@ int main(int argc, char* argv[]) ss_o.close(); ss_a.close(); - std::cout << "Level: " << level << std::endl; - std::cout << "Max Error: " << max_err << std::endl; - - std::cout << "==============================" << std::endl; - std::cout << "Cycle count: " << cycle_count << std::endl; - std::cout << "Approx Throughput: " << throughput << " MB/sec" << std::endl; - std::cout << "Approx Throughput: " << throughput/8 << " Msps" << std::endl; - std::cout << "==============================" << std::endl; - - bool flag_tp = ( abs(throughput/8 - TARGET_THROUGHPUT) > 0.05*TARGET_THROUGHPUT ) ? 1 : 0; + std::cout << "Max Allowed Error: " << level << std::endl; + std::cout << "Max Actual Error: " << max_err << std::endl; // Done: - if ( flag == 0 && flag_tp == 0 ) + if ( flag == 0 ) std::cout << std::endl << "--- PASSED ---" << std::endl; else std::cout << std::endl << "*** FAILED ***" << std::endl; - return(flag|flag_tp); + return(flag); } diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/vitis/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/vitis/Makefile index b286cde09f..21708d58e6 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/vitis/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/vitis/Makefile @@ -12,9 +12,9 @@ IP_DIR := ../aie/channelizer DATA_DIR := ../aie/channelizer/data XO_VSS := ../hls/split_1x16/split_1x16_wrapper.xo \ ../hls/merge_4x1/merge_4x1_wrapper.xo \ - ../hls/ifft_front_transpose/ifft_front_transpose_wrapper.xo \ - ../hls/ifft_transpose/ifft_transpose_wrapper.xo \ - ../hls/ifft_back_transpose/ifft_back_transpose_wrapper.xo \ + ../hls/ifft_mid_splitter/splitter.xo \ + ../hls/ifft_mid_transpose/mid_transpose_wrapper.xo \ + ../hls/ifft_mid_joiner/joiner.xo \ ../hls/merge_8x4/merge_8x4_wrapper.xo XO := ../hls/channelizer_dma_src/channelizer_dma_src_wrapper.xo \ @@ -33,6 +33,7 @@ PART := xcve2802-vsvh1760-2MP-e-S SD_CARD := $(abspath ../package) BUILD_DIR := build_${TARGET} +EMBD_EXC := embedded_exec.sh SYSTEM_CFG := system.cfg .PHONY: clean all @@ -64,7 +65,26 @@ ${BUILD_DIR}/${XSA}: ${BUILD_DIR}/${VSS} ${XO} ${SYSTEM_CFG} --output ${XSA} \ 2>&1 | tee vpp_link.log -${SD_CARD}: ${BUILD_DIR}/${XSA} ${PS_EXE} ${KERNEL_IMAGE} ${ROOTFS} ${STIMULUS_IO} +${EMBD_EXC}: + @echo "#!/bin/bash" >> ${EMBD_EXC} + @echo "#" >> ${EMBD_EXC} + @echo "# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved." >> ${EMBD_EXC} + @echo "# SPDX-License-Identifier: MIT" >> ${EMBD_EXC} + @echo "#" >> ${EMBD_EXC} + @echo "" >> ${EMBD_EXC} +ifeq ("$(TARGET)","hw_emu") + @echo "export XCL_EMULATION_MODE=hw_emu" >> ${EMBD_EXC} +endif + @echo "" >> ${EMBD_EXC} + @echo "./host.exe a.xclbin" >> ${EMBD_EXC} + @echo 'return_code=$$?' >> ${EMBD_EXC} + @echo 'if [ $$return_code -ne 0 ]; then' >> ${EMBD_EXC} + @echo ' echo "ERROR: Embedded host run failed, RC=$$return_code"' >> ${EMBD_EXC} + @echo 'fi' >> ${EMBD_EXC} + @echo echo '"INFO: Embedded host run completed."' >> ${EMBD_EXC} + @chmod 755 ${EMBD_EXC} + +${SD_CARD}: ${BUILD_DIR}/${XSA} ${PS_EXE} ${KERNEL_IMAGE} ${ROOTFS} ${STIMULUS_IO} ${EMBD_EXC} cd ${BUILD_DIR} && \ v++ --package --debug --save-temps \ --target ${TARGET} \ @@ -79,9 +99,9 @@ ${SD_CARD}: ${BUILD_DIR}/${XSA} ${PS_EXE} ${KERNEL_IMAGE} ${ROOTFS} ${STIMULUS_I ${XSA} \ $(addprefix --package.sd_file=../, ${PS_EXE}) \ $(addprefix --package.sd_file=../,${STIMULUS_IO}) \ - $(addprefix --package.sd_file=../,embedded_exec.sh) \ + $(addprefix --package.sd_file=../,${EMBD_EXC}) \ 2>&1 | tee vpp_pack.log echo ${PLATFORM_CUSTOM} > ${SD_CARD}/sd_card/platform_desc.txt clean: - rm -rf ${SD_CARD} ${BUILD_DIR} _x *.xo ${VSS} xcd.log v++* .Xil \ No newline at end of file + rm -rf ${SD_CARD} ${BUILD_DIR} _x *.xo ${VSS} xcd.log v++* .Xil .ipcache analyzer_input ${EMBD_EXC} \ No newline at end of file diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/vitis/embedded_exec.sh b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/vitis/embedded_exec.sh deleted file mode 100755 index 7c8b25d376..0000000000 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/vitis/embedded_exec.sh +++ /dev/null @@ -1,10 +0,0 @@ -#!/bin/bash -# -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -# -# Author: Mark Rollins - -export XILINX_XRT=/usr - -./host.exe a.xclbin diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/vitis/system.cfg b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/vitis/system.cfg index 7bc46b1bae..49ee042654 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/vitis/system.cfg +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/vitis/system.cfg @@ -8,7 +8,7 @@ # Clocks # ------------------------------------------------------------ -freqhz=312500000:dma_src.ap_clk,channelizer_split0.ap_clk,channelizer_split1.ap_clk,channelizer_merge0.ap_clk,channelizer_merge1.ap_clk,channelizer_merge2.ap_clk,channelizer_merge3.ap_clk,channelizer_merge4.ap_clk,channelizer_merge5.ap_clk,channelizer_merge6.ap_clk,channelizer_merge7.ap_clk,channelizer_ifft_front_transpose.ap_clk,channelizer_ifft_transpose.ap_clk,channelizer_ifft_back_transpose.ap_clk,channelizer_merge_8x4.ap_clk,dma_snk.ap_clk +freqhz=312500000:dma_src.ap_clk,channelizer_split0.ap_clk,channelizer_split1.ap_clk,channelizer_merge0.ap_clk,channelizer_merge1.ap_clk,channelizer_merge2.ap_clk,channelizer_merge3.ap_clk,channelizer_merge4.ap_clk,channelizer_merge5.ap_clk,channelizer_merge6.ap_clk,channelizer_merge7.ap_clk,channelizer_splitter.ap_clk,channelizer_mid_transpose.ap_clk,channelizer_joiner.ap_clk,channelizer_merge_8x4.ap_clk,dma_snk.ap_clk [connectivity] @@ -25,7 +25,7 @@ nk = channelizer_dma_snk_wrapper:1:dma_snk # ------------------------------------------------------------ # LPDDR to PL DMA SOURCE: -sp=dma_src.mem:LPDDR +sp=dma_src.mem:LPDDR1 # PL DMA Source to PL split sc = dma_src.sig_o_0:channelizer_split0.sig_i @@ -38,7 +38,7 @@ sc = channelizer_merge_8x4.sig_o_2:dma_snk.sig_i_2 sc = channelizer_merge_8x4.sig_o_3:dma_snk.sig_i_3 # PL DMA SINK to LPDDR -sp=dma_snk.mem:LPDDR +sp=dma_snk.mem:LPDDR1 # ------------------------------------------------------------ # Vivado PAR @@ -63,7 +63,7 @@ prop=run.impl_1.steps.phys_opt_design.is_enabled=1 prop=run.impl_1.steps.post_route_phys_opt_design.is_enabled=0 prop=run.impl_1.steps.opt_design.args.directive=Explore prop=run.impl_1.steps.place_design.args.directive=Explore -prop=run.impl_1.{steps.place_design.args.MORE OPTIONS}={-net_delay_weight low} +prop=run.impl_1.{steps.place_design.args.MORE OPTIONS}={-net_delay_weight high} prop=run.impl_1.steps.phys_opt_design.args.directive=AggressiveExplore prop=run.impl_1.steps.route_design.args.directive=NoTimingRelaxation diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/vitis/vss.cfg b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/vitis/vss.cfg index 45f730c1c2..e304fe58d7 100755 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/vitis/vss.cfg +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/07-Channelizer-Using-Vitis-Libraries/vitis/vss.cfg @@ -10,14 +10,14 @@ # VSS sources: # ------------------------------------------------------------ -vss=amd.com:mrlib:channelizer:1.0:split0,split1,ai_engine_0,merge0,merge1,merge2,merge3,merge4,merge5,merge6,merge7,ifft_front_transpose,ifft_transpose,ifft_back_transpose,merge_8x4 +vss=amd.com:mrlib:channelizer:1.0:split0,split1,ai_engine_0,merge0,merge1,merge2,merge3,merge4,merge5,merge6,merge7,splitter,mid_transpose,joiner,merge_8x4 # Sources/Sinks Data Movers to/from LPDDR/PL: nk = split_1x16_wrapper:2:split0,split1 nk = merge_4x1_wrapper:8:merge0,merge1,merge2,merge3,merge4,merge5,merge6,merge7 -nk = ifft_front_transpose_wrapper:1:ifft_front_transpose -nk = ifft_transpose_wrapper:1:ifft_transpose -nk = ifft_back_transpose_wrapper:1:ifft_back_transpose +nk = splitter_wrapper:1:splitter +nk = mid_transpose_wrapper:1:mid_transpose +nk = joiner_wrapper:1:joiner nk = merge_8x4_wrapper:1:merge_8x4 # ------------------------------------------------------------ @@ -93,62 +93,78 @@ sc = ai_engine_0.PLIO_o_29:merge5.sig_i_3 sc = ai_engine_0.PLIO_o_30:merge6.sig_i_3 sc = ai_engine_0.PLIO_o_31:merge7.sig_i_3 -# PL Merge to PL ifft_front_transpose: -sc = merge0.sig_o:ifft_front_transpose.sig_i_0 -sc = merge1.sig_o:ifft_front_transpose.sig_i_1 -sc = merge2.sig_o:ifft_front_transpose.sig_i_2 -sc = merge3.sig_o:ifft_front_transpose.sig_i_3 -sc = merge4.sig_o:ifft_front_transpose.sig_i_4 -sc = merge5.sig_o:ifft_front_transpose.sig_i_5 -sc = merge6.sig_o:ifft_front_transpose.sig_i_6 -sc = merge7.sig_o:ifft_front_transpose.sig_i_7 +# PL Merge to AI Engine front FFT +sc = merge0.sig_o:ai_engine_0.PLIO_front_in_0 +sc = merge1.sig_o:ai_engine_0.PLIO_front_in_1 +sc = merge2.sig_o:ai_engine_0.PLIO_front_in_2 +sc = merge3.sig_o:ai_engine_0.PLIO_front_in_3 +sc = merge4.sig_o:ai_engine_0.PLIO_front_in_4 +sc = merge5.sig_o:ai_engine_0.PLIO_front_in_5 +sc = merge6.sig_o:ai_engine_0.PLIO_front_in_6 +sc = merge7.sig_o:ai_engine_0.PLIO_front_in_7 -# PL ifft_front_transpose to AI Engine front FFT -sc = ifft_front_transpose.sig_o_0:ai_engine_0.PLIO_front_in_0 -sc = ifft_front_transpose.sig_o_1:ai_engine_0.PLIO_front_in_1 -sc = ifft_front_transpose.sig_o_2:ai_engine_0.PLIO_front_in_2 -sc = ifft_front_transpose.sig_o_3:ai_engine_0.PLIO_front_in_3 -sc = ifft_front_transpose.sig_o_4:ai_engine_0.PLIO_front_in_4 -sc = ifft_front_transpose.sig_o_5:ai_engine_0.PLIO_front_in_5 -sc = ifft_front_transpose.sig_o_6:ai_engine_0.PLIO_front_in_6 -sc = ifft_front_transpose.sig_o_7:ai_engine_0.PLIO_front_in_7 +# AIE front FFT to PL splitter: +sc = ai_engine_0.PLIO_front_out_0:splitter.sig_i_0 +sc = ai_engine_0.PLIO_front_out_1:splitter.sig_i_1 +sc = ai_engine_0.PLIO_front_out_2:splitter.sig_i_2 +sc = ai_engine_0.PLIO_front_out_3:splitter.sig_i_3 +sc = ai_engine_0.PLIO_front_out_4:splitter.sig_i_4 +sc = ai_engine_0.PLIO_front_out_5:splitter.sig_i_5 +sc = ai_engine_0.PLIO_front_out_6:splitter.sig_i_6 +sc = ai_engine_0.PLIO_front_out_7:splitter.sig_i_7 -# AIE front FFT to PL ifft_transpose: -sc = ai_engine_0.PLIO_front_out_0:ifft_transpose.sig_i_0 -sc = ai_engine_0.PLIO_front_out_1:ifft_transpose.sig_i_1 -sc = ai_engine_0.PLIO_front_out_2:ifft_transpose.sig_i_2 -sc = ai_engine_0.PLIO_front_out_3:ifft_transpose.sig_i_3 -sc = ai_engine_0.PLIO_front_out_4:ifft_transpose.sig_i_4 -sc = ai_engine_0.PLIO_front_out_5:ifft_transpose.sig_i_5 -sc = ai_engine_0.PLIO_front_out_6:ifft_transpose.sig_i_6 -sc = ai_engine_0.PLIO_front_out_7:ifft_transpose.sig_i_7 +# PL splitter to PL mid_transpose: +sc = splitter.sig_i_int_0:mid_transpose.sig_i_0 +sc = splitter.sig_i_int_1:mid_transpose.sig_i_1 +sc = splitter.sig_i_int_2:mid_transpose.sig_i_2 +sc = splitter.sig_i_int_3:mid_transpose.sig_i_3 +sc = splitter.sig_i_int_4:mid_transpose.sig_i_4 +sc = splitter.sig_i_int_5:mid_transpose.sig_i_5 +sc = splitter.sig_i_int_6:mid_transpose.sig_i_6 +sc = splitter.sig_i_int_7:mid_transpose.sig_i_7 +sc = splitter.sig_i_int_8:mid_transpose.sig_i_8 +sc = splitter.sig_i_int_9:mid_transpose.sig_i_9 +sc = splitter.sig_i_int_10:mid_transpose.sig_i_10 +sc = splitter.sig_i_int_11:mid_transpose.sig_i_11 +sc = splitter.sig_i_int_12:mid_transpose.sig_i_12 +sc = splitter.sig_i_int_13:mid_transpose.sig_i_13 +sc = splitter.sig_i_int_14:mid_transpose.sig_i_14 +sc = splitter.sig_i_int_15:mid_transpose.sig_i_15 -# PL ifft_transpose to AIE back FFT: -sc = ifft_transpose.sig_o_0:ai_engine_0.PLIO_back_in_0 -sc = ifft_transpose.sig_o_1:ai_engine_0.PLIO_back_in_1 -sc = ifft_transpose.sig_o_2:ai_engine_0.PLIO_back_in_2 -sc = ifft_transpose.sig_o_3:ai_engine_0.PLIO_back_in_3 -sc = ifft_transpose.sig_o_4:ai_engine_0.PLIO_back_in_4 -sc = ifft_transpose.sig_o_5:ai_engine_0.PLIO_back_in_5 -sc = ifft_transpose.sig_o_6:ai_engine_0.PLIO_back_in_6 -sc = ifft_transpose.sig_o_7:ai_engine_0.PLIO_back_in_7 +# PL mid_transpose to PL joiner: +sc = mid_transpose.sig_o_0:joiner.sig_o_int_0 +sc = mid_transpose.sig_o_1:joiner.sig_o_int_1 +sc = mid_transpose.sig_o_2:joiner.sig_o_int_2 +sc = mid_transpose.sig_o_3:joiner.sig_o_int_3 +sc = mid_transpose.sig_o_4:joiner.sig_o_int_4 +sc = mid_transpose.sig_o_5:joiner.sig_o_int_5 +sc = mid_transpose.sig_o_6:joiner.sig_o_int_6 +sc = mid_transpose.sig_o_7:joiner.sig_o_int_7 +sc = mid_transpose.sig_o_8:joiner.sig_o_int_8 +sc = mid_transpose.sig_o_9:joiner.sig_o_int_9 +sc = mid_transpose.sig_o_10:joiner.sig_o_int_10 +sc = mid_transpose.sig_o_11:joiner.sig_o_int_11 +sc = mid_transpose.sig_o_12:joiner.sig_o_int_12 +sc = mid_transpose.sig_o_13:joiner.sig_o_int_13 +sc = mid_transpose.sig_o_14:joiner.sig_o_int_14 +sc = mid_transpose.sig_o_15:joiner.sig_o_int_15 -# AIE back FFT to PL ifft_back_transpose: -sc = ai_engine_0.PLIO_back_out_0:ifft_back_transpose.sig_i_0 -sc = ai_engine_0.PLIO_back_out_1:ifft_back_transpose.sig_i_1 -sc = ai_engine_0.PLIO_back_out_2:ifft_back_transpose.sig_i_2 -sc = ai_engine_0.PLIO_back_out_3:ifft_back_transpose.sig_i_3 -sc = ai_engine_0.PLIO_back_out_4:ifft_back_transpose.sig_i_4 -sc = ai_engine_0.PLIO_back_out_5:ifft_back_transpose.sig_i_5 -sc = ai_engine_0.PLIO_back_out_6:ifft_back_transpose.sig_i_6 -sc = ai_engine_0.PLIO_back_out_7:ifft_back_transpose.sig_i_7 +# PL joiner to AIE back FFT: +sc = joiner.sig_o_0:ai_engine_0.PLIO_back_in_0 +sc = joiner.sig_o_1:ai_engine_0.PLIO_back_in_1 +sc = joiner.sig_o_2:ai_engine_0.PLIO_back_in_2 +sc = joiner.sig_o_3:ai_engine_0.PLIO_back_in_3 +sc = joiner.sig_o_4:ai_engine_0.PLIO_back_in_4 +sc = joiner.sig_o_5:ai_engine_0.PLIO_back_in_5 +sc = joiner.sig_o_6:ai_engine_0.PLIO_back_in_6 +sc = joiner.sig_o_7:ai_engine_0.PLIO_back_in_7 -# PL ifft_back_transpose to PL merge_8x4: -sc = ifft_back_transpose.sig_o_0:merge_8x4.sig_i_0 -sc = ifft_back_transpose.sig_o_1:merge_8x4.sig_i_1 -sc = ifft_back_transpose.sig_o_2:merge_8x4.sig_i_2 -sc = ifft_back_transpose.sig_o_3:merge_8x4.sig_i_3 -sc = ifft_back_transpose.sig_o_4:merge_8x4.sig_i_4 -sc = ifft_back_transpose.sig_o_5:merge_8x4.sig_i_5 -sc = ifft_back_transpose.sig_o_6:merge_8x4.sig_i_6 -sc = ifft_back_transpose.sig_o_7:merge_8x4.sig_i_7 +# AIE back FFT to PL merge_8x4: +sc = ai_engine_0.PLIO_back_out_0:merge_8x4.sig_i_0:256 +sc = ai_engine_0.PLIO_back_out_1:merge_8x4.sig_i_1:256 +sc = ai_engine_0.PLIO_back_out_2:merge_8x4.sig_i_2:256 +sc = ai_engine_0.PLIO_back_out_3:merge_8x4.sig_i_3:256 +sc = ai_engine_0.PLIO_back_out_4:merge_8x4.sig_i_4:256 +sc = ai_engine_0.PLIO_back_out_5:merge_8x4.sig_i_5:256 +sc = ai_engine_0.PLIO_back_out_6:merge_8x4.sig_i_6:256 +sc = ai_engine_0.PLIO_back_out_7:merge_8x4.sig_i_7:256 diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/README.md b/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/README.md index bac2dbe589..6ac2b808ed 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/README.md +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/README.md @@ -15,7 +15,7 @@ # MNIST ConvNet on AIE-ML -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents @@ -145,7 +145,7 @@ This tutorial adopts a simple design approach to building the MNIST ConvNet clas ### Vitis Functional Simulation -This tutorial uses a new tool feature called Vitis Functional Simulation (VFS) to validate the MNIST ConvNet classifier AI Engine implementation against its Python behavioral models. The VFS feature generates executable "shared objects" of the AI Engine and PL portions of your heterogenous Versal design, allowing it to be brought into familiar simulation frameworks, namely MATLAB and Python. This allows functional verification of your Versal AI Engine and PL designs without leaving your preferred simulation framework and without creating I/O files for this purpose. Vitis Functional Simulation is an production tool feature in 2025.1. +This tutorial uses a new tool feature called Vitis Functional Simulation (VFS) to validate the MNIST ConvNet classifier AI Engine implementation against its Python behavioral models. The VFS feature generates executable "shared objects" of the AI Engine and PL portions of your heterogenous Versal design, allowing it to be brought into familiar simulation frameworks, namely MATLAB and Python. This allows functional verification of your Versal AI Engine and PL designs without leaving your preferred simulation framework and without creating I/O files for this purpose. The Python version of Vitis Functional Simulation is used to validate each network layer in the MNIST ConvNet design. The screen capture below shows how the `conv2d_w1()` layer is called from the Jupyter notebook [gen_vectors.ipynb](aie/conv2d_w1/gen_vectors.ipynb) used to validate that layer. A similar notebook is built for each layer in the design. The VFS infrastructure compiles the AI Engine graph automatically under the hood when any source code files change, and then passes the I/O vectors between the Jupyter notebook and the x86 functional simulator. diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/conv2d_w1/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/conv2d_w1/Makefile index a00a8204aa..ff10af6762 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/conv2d_w1/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/conv2d_w1/Makefile @@ -12,7 +12,7 @@ MY_APP := conv2d_w1_app MY_SOURCES := ${MY_APP}.cpp conv2d_w1_graph.h conv2d_w1.h conv2d_w1.cpp \ ../wts_init/wts_init.h ../wts_init/wts_init.cpp ../wts_init/wts_init_graph.h -PLATFORM_USE := xilinx_vek280_base_202510_1 +PLATFORM_USE := xilinx_vek280_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/conv2d_w3/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/conv2d_w3/Makefile index efa0cf4099..857870c8d8 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/conv2d_w3/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/conv2d_w3/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := conv2d_w3_app MY_SOURCES := ${MY_APP}.cpp conv2d_w3_graph.h conv2d_w3.h conv2d_w3.cpp ../wts_init/wts_init_graph.h -PLATFORM_USE := xilinx_vek280_base_202510_1 +PLATFORM_USE := xilinx_vek280_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/conv2d_w5/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/conv2d_w5/Makefile index bc74258e7f..8108db057a 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/conv2d_w5/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/conv2d_w5/Makefile @@ -14,7 +14,7 @@ MY_SOURCES := ${MY_APP}.cpp conv2d_w5_graph.h \ conv2d_w5A.h conv2d_w5A.cpp conv2d_w5B.h conv2d_w5B.cpp conv2d_w5C.h conv2d_w5C.cpp \ conv2d_w5D.h conv2d_w5D.cpp -PLATFORM_USE := xilinx_vek280_base_202510_1 +PLATFORM_USE := xilinx_vek280_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/dense_w7/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/dense_w7/Makefile index 76da1580c1..0aabe40493 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/dense_w7/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/dense_w7/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := dense_w7_app MY_SOURCES := ${MY_APP}.cpp dense_w7_graph.h dense_w7.h dense_w7.cpp ../wts_init/wts_init_graph.h -PLATFORM_USE := xilinx_vek280_base_202510_1 +PLATFORM_USE := xilinx_vek280_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/max_pooling2d_w2/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/max_pooling2d_w2/Makefile index 28a0c89463..3935583a84 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/max_pooling2d_w2/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/max_pooling2d_w2/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := max_pooling2d_w2_app MY_SOURCES := ${MY_APP}.cpp max_pooling2d_w2_graph.h max_pooling2d_w2.h max_pooling2d_w2.cpp -PLATFORM_USE := xilinx_vek280_base_202510_1 +PLATFORM_USE := xilinx_vek280_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/max_pooling2d_w4/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/max_pooling2d_w4/Makefile index eeb2906faf..014791d2e1 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/max_pooling2d_w4/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/max_pooling2d_w4/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := max_pooling2d_w4_app MY_SOURCES := ${MY_APP}.cpp max_pooling2d_w4_graph.h max_pooling2d_w4.h max_pooling2d_w4.cpp -PLATFORM_USE := xilinx_vek280_base_202510_1 +PLATFORM_USE := xilinx_vek280_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/mnist/Makefile b/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/mnist/Makefile index 13ccd6a81c..4511e0db9b 100644 --- a/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/mnist/Makefile +++ b/AI_Engine_Development/AIE-ML/Design_Tutorials/08-MNIST-ConvNet/aie/mnist/Makefile @@ -22,7 +22,7 @@ MY_SOURCES := ${MY_APP}.cpp mnist_graph.h \ ../dense_w7/dense_w7.h ../dense_w7/dense_w7.cpp ../dense_w7/dense_w7_graph.h \ ../wts_init/wts_init.h ../wts_init/wts_init.cpp ../wts_init/wts_init_graph.h -PLATFORM_USE := xilinx_vek280_base_202510_1 +PLATFORM_USE := xilinx_vek280_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/01-aie_a_to_z/README.md b/AI_Engine_Development/AIE-ML/Feature_Tutorials/01-aie_a_to_z/README.md index e1f9b622de..37c59bbd79 100755 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/01-aie_a_to_z/README.md +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/01-aie_a_to_z/README.md @@ -15,11 +15,11 @@ # AI Engine Versal Integration -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction -The tutorial introduces a complete end-to-end flow for a bare-metal host application using AI Engines and PL kernels. The tutorial is based on the 2025.1 Vitis unified software platform. +The tutorial introduces a complete end-to-end flow for a bare-metal host application using AI Engines and PL kernels. The tutorial is based on the 2025.2 Vitis unified software platform. The version for AIE is compatible with AIE-ML. Refer to the following tutorial and change the VCK190 to VEK280 for each step the VCK190 board is used: [AI Engine A-to-Z](../../../AIE/Feature_Tutorials/01-aie_a_to_z/README.md) diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/02-using-gmio/README.md b/AI_Engine_Development/AIE-ML/Feature_Tutorials/02-using-gmio/README.md index 57279ebc9c..c8d8ad8f35 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/02-using-gmio/README.md +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/02-using-gmio/README.md @@ -15,24 +15,24 @@ # GMIO Tutorial -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction This tutorial targets AIE-ML device, but shares test cases and description files with [AIE 02-using-gmio](../../../AIE/Feature_Tutorials/02-using-gmio). ->**IMPORTANT**: Before beginning the tutorial make sure you have installed the AMD Vitis™ 2025.1 software. The Vitis release includes all the embedded base platforms including the VEK280 base platform that is used in this tutorial. In addition, ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). +>**IMPORTANT**: Before beginning the tutorial make sure you have installed the AMD Vitis™ 2025.2 software. The Vitis release includes all the embedded base platforms including the VEK280 base platform that is used in this tutorial. In addition, ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). The ‘common image’ package contains a prebuilt Linux kernel and root file system that can be used with the AMD Versal™ board for embedded design development using the Vitis software platform. Before starting this tutorial, run the following steps: 1. Go to the directory where you have unzipped the Versal Common Image package. -2. In a Bash shell, run the ``/Common Images Dir/xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux`` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ``/Common Images Dir/xilinx-versal-common-v2025.1/sdk.sh``. -3. Set up your ROOTFS and IMAGE to point to the ``rootfs.ext4`` and Image files located in the ``/Common Images Dir/xilinx-versal-common-v2025.1`` directory. +2. In a Bash shell, run the ``/Common Images Dir/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux`` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ``/Common Images Dir/xilinx-versal-common-v2025.2/sdk.sh``. +3. Set up your ROOTFS and IMAGE to point to the ``rootfs.ext4`` and Image files located in the ``/Common Images Dir/xilinx-versal-common-v2025.2`` directory. 4. Set up your PLATFORM_REPO_PATHS environment variable to ``$XILINX_VITIS/base_platforms``. -This tutorial targets VEK280 board for 2025.1 version. +This tutorial targets VEK280 board for 2025.2 version. ## Objectives diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/03-rtp-reconfiguration/README.md b/AI_Engine_Development/AIE-ML/Feature_Tutorials/03-rtp-reconfiguration/README.md index 5b989a67b9..951901c378 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/03-rtp-reconfiguration/README.md +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/03-rtp-reconfiguration/README.md @@ -15,24 +15,24 @@ # Runtime Parameter Reconfiguration -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction This tutorial targets AIE-ML device, but shares test cases and description files with [AIE 03-rtp-reconfiguration](../../../AIE/Feature_Tutorials/03-rtp-reconfiguration). ->**IMPORTANT**: Before beginning the tutorial make sure you have installed the AMD Vitis™ 2025.1 software. The Vitis release includes all the embedded base platforms including the VEK280 base platform that is used in this tutorial. In addition, ensure that you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). +>**IMPORTANT**: Before beginning the tutorial make sure you have installed the AMD Vitis™ 2025.2 software. The Vitis release includes all the embedded base platforms including the VEK280 base platform that is used in this tutorial. In addition, ensure that you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). The ‘common image’ package contains a prebuilt Linux kernel and root file system that can be used with the AMD Versal™ board for embedded design development using Vitis tools. Before starting this tutorial, run the following steps: 1. Go to the directory where you have unzipped the Versal Common Image package. -2. In a Bash shell, run the ``/Common Images Dir/xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux`` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ``/Common Images Dir/xilinx-versal-common-v2025.1/sdk.sh``. -3. Set up your ROOTFS and IMAGE to point to the `rootfs.ext4` and Image files located in the ``/Common Images Dir/xilinx-versal-common-v2025.1`` directory. +2. In a Bash shell, run the ``/Common Images Dir/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux`` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ``/Common Images Dir/xilinx-versal-common-v2025.2/sdk.sh``. +3. Set up your ROOTFS and IMAGE to point to the `rootfs.ext4` and Image files located in the ``/Common Images Dir/xilinx-versal-common-v2025.2`` directory. 4. Set up your PLATFORM_REPO_PATHS environment variable to ``$XILINX_VITIS/base_platforms``. -This tutorial targets the VEK280 board for the 2025.1 version. +This tutorial targets the VEK280 board for the 2025.2 version. ## Objectives @@ -45,7 +45,7 @@ After completing this tutorial, you will be able to: * Use XRT API to control graph execution and RTP operations. * Verify the system by HW co-simulation and running in hardware. -**Known issue in 2025.1**: There may exist hardware execution issue in asynchronous array RTP update & read. When it happens, please wait for an update in the tool or a patch. Otherwise, you may continue to use 2024.1 instead. +**Known issue in 2025.2**: There may exist hardware execution issue in asynchronous array RTP update & read. When it happens, please wait for an update in the tool or a patch. Otherwise, you may continue to use 2024.1 instead. ## Steps diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/04-packet-switching/README.md b/AI_Engine_Development/AIE-ML/Feature_Tutorials/04-packet-switching/README.md index f51c9f7d02..da70d5cbce 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/04-packet-switching/README.md +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/04-packet-switching/README.md @@ -15,22 +15,22 @@ # Packet Switching Tutorial -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** This tutorial targets AIE-ML device, but shares test cases and description files with [AIE 04-packet-switching](../../../AIE/Feature_Tutorials/04-packet-switching). ->**IMPORTANT**: Before beginning the tutorial make sure you have installed the AMD Vitis™ software platform 2025.1. The Vitis release includes all the embedded base platforms including the VEK280 base platform that is used in this tutorial. In addition, ensure that you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). +>**IMPORTANT**: Before beginning the tutorial make sure you have installed the AMD Vitis™ software platform 2025.2. The Vitis release includes all the embedded base platforms including the VEK280 base platform that is used in this tutorial. In addition, ensure that you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). The ‘common image’ package contains a prebuilt Linux kernel and root file system that can be used with the AMD Versal™ board for embedded design development using the Vitis tools. Before starting this tutorial, run the following steps: 1. Go to the directory where you have unzipped the Versal Common Image package. -2. In a Bash shell, run the ``/**Common Images Dir**/xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux`` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ``/**Common Images Dir**/xilinx-versal-common-v2025.1/sdk.sh``. -3. Set up your ROOTFS and IMAGE to point to the `rootfs.ext4` and Image files located in the ``/**Common Images Dir**/xilinx-versal-common-v2025.1`` directory. +2. In a Bash shell, run the ``/**Common Images Dir**/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux`` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ``/**Common Images Dir**/xilinx-versal-common-v2025.2/sdk.sh``. +3. Set up your ROOTFS and IMAGE to point to the `rootfs.ext4` and Image files located in the ``/**Common Images Dir**/xilinx-versal-common-v2025.2`` directory. 4. Set up your PLATFORM_REPO_PATHS environment variable to ``$XILINX_VITIS/base_platforms``. -This tutorial targets VEK280 board for 2025.1 version. +This tutorial targets VEK280 board for 2025.2 version. ## Objectives diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/LICENSE.txt b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/LICENSE.txt index 9f81dade70..d071efe45b 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/LICENSE.txt +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/LICENSE.txt @@ -1,4 +1,4 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/Makefile b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/Makefile index ec6092cd3a..9d32480b7f 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/Makefile +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/Makefile @@ -1,12 +1,12 @@ # /* -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +# Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. # SPDX-License-Identifier: X11 # */ F_PROJ_ROOT ?= $(shell bash -c 'export MK_PATH=$(MK_PATH); echo $${MK_PATH%/AI_Engine_Development/*}') -ROOTFS ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/rootfs.ext4 -IMAGE ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/Image +ROOTFS ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/rootfs.ext4 +IMAGE ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/Image SDKTARGETSYSROOT ?= ${SYSROOT} # Makefile input options @@ -26,7 +26,7 @@ EMCONFIG_FILE = emconfig.json EXECUTABLE = host.exe PACKAGE_OUT = ./package.$(TARGET) -BASE_PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm +BASE_PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm # Command-line options VPP := v++ @@ -72,19 +72,19 @@ __check_defined = \ $(error Undefined $1$(if $2, ($2)))) guard-PLATFORM_REPO_PATHS: - $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vek280_base_202510_1) + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vek280_base_202520_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-aarch64-xilinx-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-aarch64-xilinx-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-aarch64-xilinx-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-aarch64-xilinx-linux) ### diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/README.md b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/README.md index 74e9ddd8e2..e083e72122 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/README.md +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/README.md @@ -15,7 +15,7 @@ # AI Engine Versal Integration -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction @@ -25,19 +25,19 @@ This tutorial demonstrates creating a system design running on the AI Engine, PS This tutorial steps through hardware emulation, and hardware flow in the context of a complete Versal adaptive SoC system integration. By default, the Makefile is set for `hw_emu`. If you need to build for `hw`, use the corresponding TARGET option as described in corresponding sections. -**IMPORTANT**: Before beginning the tutorial ensure you have installed Vitis™ 2025.1 software. The software includes all the embedded base platforms including the VEK280 base platform that is used in this tutorial. In addition, ensure you have downloaded the Common Images for Embedded Vitis Platforms from this link. +**IMPORTANT**: Before beginning the tutorial ensure you have installed Vitis™ 2025.2 software. The software includes all the embedded base platforms including the VEK280 base platform that is used in this tutorial. In addition, ensure you have downloaded the Common Images for Embedded Vitis Platforms from this link. -https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms/2025.1.html +https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms/2025.2.html The 'common image' package contains a prebuilt Linux kernel and root file system that can be used with the Versal board for embedded design development using Vitis. Before starting this tutorial run the following steps: 1. Navigate to the directory where you have unzipped the Versal Common Image package. -2. In a Bash shell, run the ```/Common Images Dir/xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux``` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ```/Common Images Dir/xilinx-versal-common-v2025.1/sdk.sh```. -3. Set up your ROOTFS, and IMAGE to point to the ```rootfs.ext4``` and Image files located in the ```/Common Images Dir/xilinx-versal-common-v2025.1``` directory. -4. Set up your PLATFORM_REPO_PATHS environment variable to ```$XILINX_VITIS/base_platforms/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm```. +2. In a Bash shell, run the ```/Common Images Dir/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux``` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ```/Common Images Dir/xilinx-versal-common-v2025.2/sdk.sh```. +3. Set up your ROOTFS, and IMAGE to point to the ```rootfs.ext4``` and Image files located in the ```/Common Images Dir/xilinx-versal-common-v2025.2``` directory. +4. Set up your PLATFORM_REPO_PATHS environment variable to ```$XILINX_VITIS/base_platforms/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm```. -This tutorial targets VEK280 board for 2025.1 version. +This tutorial targets VEK280 board for 2025.2 version. ## Objectives @@ -95,7 +95,7 @@ make aie TARGET=hw Or ```bash -v++ -c --mode aie --target hw --platform $PLATFORM_REPO_PATHS/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm --include "$XILINX_VITIS/aietools/include" --include "./aie" --include "./data" --include "./aie/kernels" --include "./" --aie.xlopt=0 --work_dir=./Work aie/graph.cpp +v++ -c --mode aie --target hw --platform $PLATFORM_REPO_PATHS/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm --include "$XILINX_VITIS/aietools/include" --include "./aie" --include "./data" --include "./aie/kernels" --include "./" --aie.xlopt=0 --work_dir=./Work aie/graph.cpp ``` The generated output from `aiecompiler` is the `Work` directory, and the `libadf.a` file. This file contains the compiled AI Engine configuration, graph, and Kernel `.elf` files. @@ -168,8 +168,8 @@ After the graph has been compiled, you can simulate your design with the `aiesim You should see something similar to this: ```bash -aiesim_options.txt memconfig.json profile_funct_18_1.txt profile_funct_19_0.xml profile_instr_18_0.txt profile_instr_18_1.xml profile_instr_19_1.txt data profile_funct_18_0.txt profile_funct_18_1.xml profile_funct_19_1.txt profile_instr_18_0.xml profile_instr_19_0.txt profile_instr_19_1.xml -default.aierun_summary profile_funct_18_0.xml profile_funct_19_0.txt profile_funct_19_1.xml profile_instr_18_1.txt profile_instr_19_0.xml + aiesim_options.txt memconfig.json profile_funct_18_1.txt profile_funct_19_0.xml profile_instr_18_0.txt profile_instr_18_1.xml profile_instr_19_1.txt data profile_funct_18_0.txt profile_funct_18_1.xml profile_funct_19_1.txt profile_instr_18_0.xml profile_instr_19_0.txt profile_instr_19_1.xml + default.aierun_summary profile_funct_18_0.xml profile_funct_19_0.txt profile_funct_19_1.xml profile_instr_18_1.txt profile_instr_19_0.xml ``` The files prefixed with `profile_` are the outputs of the profiling and calculated per tile. In this tutorial, profiling is done for all tiles that are used, but you can limit profiling to specific tiles by providing the row and column of the tile. For more information about profiling with `aiesimulator` see https://docs.amd.com/r/en-US/ug1076-ai-engine-environment/Simulating-an-AI-Engine-Graph-Application. You can open up these files to see what was calculated, but it is better to view it in Vitis Analyzer where it is curated. The `data` directory is generated here with the output file(s) you have in the `graph.cpp` for the PLIO objects. Finally, the `default.aierun_summary` is generated, which contains all the information generated by `aiesimulator` with profiling and trace information. Opening this file in Vitis Analyzer allows you to browse all the output files, and profile/trace data. @@ -265,8 +265,8 @@ make kernels TARGET=hw_emu or ```bash -v++ -c --mode hls --platform $PLATFORM_REPO_PATHS/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm --config pl_kernels/s2mm.cfg -v++ -c --mode hls --platform $PLATFORM_REPO_PATHS/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm --config pl_kernels/mm2s.cfg +v++ -c --mode hls --platform $PLATFORM_REPO_PATHS/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm --config pl_kernels/s2mm.cfg +v++ -c --mode hls --platform $PLATFORM_REPO_PATHS/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm --config pl_kernels/mm2s.cfg ``` To get more details about several options of `v++` command line, refer to the **Compiling HLS Kernels Using V++** topic in **Section 3** @@ -295,7 +295,7 @@ make xsa TARGET=hw_emu or ```bash -v++ -l --platform $PLATFORM_REPO_PATHS/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm s2mm.xo mm2s.xo libadf.a -t hw_emu --save-temps -g --config system.cfg -o tutorial.xsa +v++ -l --platform $PLATFORM_REPO_PATHS/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm s2mm.xo mm2s.xo libadf.a -t hw_emu --save-temps -g --config system.cfg -o tutorial.xsa ``` Now you have a generated `.xsa` that will be used to execute your design on the platform. @@ -336,11 +336,11 @@ Or ```bash cd ./sw v++ --package -t hw_emu \ - -f $PLATFORM_REPO_PATHS/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm \ - --package.rootfs=$PLATFORM_REPO_PATHS/sw/versal/xilinx-versal-common-v2025.1/rootfs.ext4 \ + -f $PLATFORM_REPO_PATHS/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm \ + --package.rootfs=$PLATFORM_REPO_PATHS/sw/versal/xilinx-versal-common-v2025.2/rootfs.ext4 \ --package.image_format=ext4 \ --package.boot_mode=sd \ - --package.kernel_image=$PLATFORM_REPO_PATHS/sw/versal/xilinx-versal-common-v2025.1/Image \ + --package.kernel_image=$PLATFORM_REPO_PATHS/sw/versal/xilinx-versal-common-v2025.2/Image \ --package.defer_aie_run \ --package.sd_file host.exe ../tutorial.xsa ../libadf.a cd .. @@ -428,7 +428,7 @@ Compare this with the latency you got during the aiesimulation where the AI Engi or ```bash - v++ -l --platform $PLATFORM_REPO_PATHS/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm s2mm.xo mm2s.xo libadf.a -t hw --save-temps -g --config system.cfg -o tutorial.xsa + v++ -l --platform $PLATFORM_REPO_PATHS/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm s2mm.xo mm2s.xo libadf.a -t hw --save-temps -g --config system.cfg -o tutorial.xsa ``` 2. Then re-run the packaging step with: @@ -442,11 +442,11 @@ Compare this with the latency you got during the aiesimulation where the AI Engi ```bash cd ./sw v++ --package -t hw \ - -f $PLATFORM_REPO_PATHS/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm \ - --package.rootfs=$PLATFORM_REPO_PATHS/sw/versal/xilinx-versal-common-v2025.1/rootfs.ext4 \ + -f $PLATFORM_REPO_PATHS/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm \ + --package.rootfs=$PLATFORM_REPO_PATHS/sw/versal/xilinx-versal-common-v2025.2/rootfs.ext4 \ --package.image_format=ext4 \ --package.boot_mode=sd \ - --package.kernel_image=$PLATFORM_REPO_PATHS/sw/versal/xilinx-versal-common-v2025.1/Image \ + --package.kernel_image=$PLATFORM_REPO_PATHS/sw/versal/xilinx-versal-common-v2025.2/Image \ --package.defer_aie_run \ --package.sd_file host.exe ../tutorial.xsa ../libadf.a cd .. @@ -472,7 +472,7 @@ You should see **TEST PASSED**. You have successfully run your design on hardwar In this tutorial you learned the following: * How to compile PLIO and PL Kernels using `v++ -c`. -* How to link the `libadf.a`, PLIO, and PL kernels to the `xilinx_vek280_base_202510_1` platform. +* How to link the `libadf.a`, PLIO, and PL kernels to the `xilinx_vek280_base_202520_1` platform. * How to use Vitis Analyzer to explore the various reports generated from compilation and emulation/simulation. * How to package your host code, and the generated `xclbin` and `libadf.a` into an SD card directory. * How to execute the design for hardware emulation. diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/graph.cpp b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/graph.cpp index 555e2d6417..11dcf5031e 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/graph.cpp +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/graph.cpp @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/graph.h b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/graph.h index e16f212b58..ff454bc3d4 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/graph.h +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/graph.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/include.h b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/include.h index fd61914a84..d4aeb10ed2 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/include.h +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/include.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels.h b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels.h index 28e8e3d526..c24676bc3b 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels.h +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/classifiers/classify.cc b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/classifiers/classify.cc index 95167702bd..bc91de62a9 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/classifiers/classify.cc +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/classifiers/classify.cc @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/decimators/hb27.cc b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/decimators/hb27.cc index 43c67e9e1a..4c4a9b8981 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/decimators/hb27.cc +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/decimators/hb27.cc @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/interpolators/hb27_2i.cc b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/interpolators/hb27_2i.cc index 876aa7d898..992c119b3c 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/interpolators/hb27_2i.cc +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/interpolators/hb27_2i.cc @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/polar_clip.cpp b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/polar_clip.cpp index a6e21c3387..162379febf 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/polar_clip.cpp +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/polar_clip.cpp @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/pl_kernels/mm2s.cpp b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/pl_kernels/mm2s.cpp index 34388760b1..3e85a90269 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/pl_kernels/mm2s.cpp +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/pl_kernels/mm2s.cpp @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/pl_kernels/s2mm.cpp b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/pl_kernels/s2mm.cpp index db02f5abfd..16c7a3b8c8 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/pl_kernels/s2mm.cpp +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/pl_kernels/s2mm.cpp @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/sw/data.h b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/sw/data.h index b84c8cba1c..2e05870ca6 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/sw/data.h +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/sw/data.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/sw/host.cpp b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/sw/host.cpp index a59721886e..e62c5d43af 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/sw/host.cpp +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/sw/host.cpp @@ -1,9 +1,10 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ #include +#include #include #include "experimental/xrt_kernel.h" diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/sw/host.h b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/sw/host.h index 593b8f30a2..0f26b5a81b 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/sw/host.h +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/sw/host.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/system.cfg b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/system.cfg index db1b577ebf..f996b6a683 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/system.cfg +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/05-AI-engine-versal-integration/system.cfg @@ -1,5 +1,5 @@ ## -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +# Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. # SPDX-License-Identifier: X11 ## diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/README.md b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/README.md index 7e48d67ca9..15d59ef74a 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/README.md +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/README.md @@ -15,7 +15,7 @@ # Matrix Compute with Vitis Libraries on AIE and AIE-ML -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction @@ -31,7 +31,7 @@ For example, value at c11, is the product of a11 * b11 + a12 * b21. Similarly, ![Matrix Product](./images/2_Matrix_Product.png) -**IMPORTANT**: Before beginning the tutorial, make sure that you have read and followed the *Vitis Software Platform Release Notes* (v2024.2) for setting up the software and installing the VEK280 base platform. +**IMPORTANT**: Before beginning the tutorial, make sure that you have read and followed the *Vitis Software Platform Release Notes* (v2025.2) for setting up the software and installing the VEK280 base platform. Before starting this tutorial, run the following steps: 1. Set up your `PLATFORM_REPO_PATHS` environment variable based upon where you downloaded the platform. @@ -41,7 +41,7 @@ Before starting this tutorial, run the following steps: # AMD Versal Devices with AI Engine Variants -AMD Versal™ AI Core and Versal AI Edge devices come in both AIE and AIE-ML variants. You need to choose your device carefully. The following table lists the devices that have AIE and AIE-ML variants. +AMD Versal™ AI Core and Versal AI Edge devices come in AIE, AIE-ML and AIE-MLv2 variants. You need to choose your device carefully. The following table lists the devices that have AIE and AIE-ML variants. ![AIE Variants](./images/0_AMD_Versal_Devices.png) @@ -75,7 +75,7 @@ The data type of both input matrices can be configured, and the data type of the The Matrix Multiply supports a matrix of elements of integer type (int16, cint16, int32, or cint32) multiplied by a matrix of elements of integer type. It also supports a matrix of elements of float type (float, cfloat) multiplied by a matrix of elements of float type. However, a mix of integer types and float types is not supported. -The Matrix Multiply for AIE-ML supports integer types (int16, int32, cint16, and cint32) but does not support floating-point types (float, cfloat). +The Matrix Multiply for AIE-ML and AIE-MLv2 support integer types (int16, int32, cint16, and cint32) but does not support floating-point types (float, cfloat). The graph entry point as follows: ```xf::dsp::aie::blas::matrix_mult::matrix_mult_graph``` @@ -364,7 +364,7 @@ Close the Vitis Analyzer. | Design | TP_CASC_LEN | TP_SSR | NPORT_I | NPORT_O | Throughput | |---------------------|-------------|--------|---------|---------|-------------| -| Design Variant 1 | 2 | 1 | 1 | 1 | 1112 MBPS | +| Design Variant 1 | 1 | 1 | 1 | 1 | 1112 MBPS | ## Design Variant 2: 4-tile design with TP_CASC_LEN=4 @@ -436,8 +436,8 @@ Close the Vitis Analyzer. | Design | TP_CASC_LEN | TP_SSR | NPORT_I | NPORT_O | Throughput | |---------------------|-------------|--------|---------|---------|-------------| -| Design Variant 1 | 2 | 1 | 1 | 1 | 1112 MBPS | -| Design Variant 2 | 4 | 1 | 4 | 1 | 2452 MBPS | +| Design Variant 1 | 1 | 1 | 1 | 1 | 1112 MBPS | +| Design Variant 2 | 4 | 1 | 4 | 1 | 2447 MBPS | ## Design Variant 3: 8-tile design with TP_CASC_LEN=4 and TP_SSR=2 @@ -511,9 +511,9 @@ Close the Vitis Analyzer. | Design | TP_CASC_LEN | TP_SSR | NPORT_I | NPORT_O | Throughput | |---------------------|-------------|--------|---------|---------|-------------| -| Design Variant 1 | 2 | 1 | 1 | 1 | 1112 MBPS | -| Design Variant 2 | 4 | 1 | 4 | 1 | 2452 MBPS | -| Design Variant 3 | 4 | 2 | 8 | 2 | 3815 MBPS | +| Design Variant 1 | 1 | 1 | 1 | 1 | 1112 MBPS | +| Design Variant 2 | 4 | 1 | 4 | 1 | 2447 MBPS | +| Design Variant 3 | 4 | 2 | 8 | 2 | 3770 MBPS | ## Migrate the Design from AIE to AIE-ML and Evalute the Performance Differences @@ -532,7 +532,7 @@ cd ../../aie-ml/gemm_16x32x8 Open the ```Makefile``` file and review the code. The only modification is the updated platform name. ``` -PLATFORM_USE := xilinx_vek280_base_202510_1 +PLATFORM_USE := xilinx_vek280_base_202520_1 ``` ### Design Variant 1: Single Tile (AIE-ML) @@ -568,9 +568,9 @@ Close the Vitis Analyzer. | Design | TP_CASC_LEN | TP_SSR | NPORT_I | NPORT_O | Throughput (AIE)|Throughput (AIE-ML)| |---------------------|-------------|--------|---------|---------|-----------------|-------------------| -| Design Variant 1 | 2 | 1 | 1 | 1 | 1137 MBPS | 1529 MBPS | -| Design Variant 2 | 4 | 1 | 4 | 1 | 2578 MBPS | | -| Design Variant 3 | 4 | 2 | 8 | 2 | 3935 MBPS | | +| Design Variant 1 | 1 | 1 | 1 | 1 | 1112 MBPS | 1529 MBPS | +| Design Variant 2 | 4 | 1 | 4 | 1 | 2447 MBPS | | +| Design Variant 3 | 4 | 2 | 8 | 2 | 3770 MBPS | | ## Design Variant 2: 4-tile design with TP_CASC_LEN=4 (AIE-ML) @@ -612,9 +612,9 @@ Close the Vitis Analyzer. | Design | TP_CASC_LEN | TP_SSR | NPORT_I | NPORT_O | Throughput (AIE)|Throughput (AIE-ML)| |---------------------|-------------|--------|---------|---------|-----------------|-------------------| -| Design Variant 1 | 2 | 1 | 1 | 1 | 1137 MBPS | 1529 MBPS | -| Design Variant 2 | 4 | 1 | 4 | 1 | 2578 MBPS | 3029 MBPS | -| Design Variant 3 | 4 | 2 | 8 | 2 | 3935 MBPS | | +| Design Variant 1 | 1 | 1 | 1 | 1 | 1112 MBPS | 1529 MBPS | +| Design Variant 2 | 4 | 1 | 4 | 1 | 2447 MBPS | 3033 MBPS | +| Design Variant 3 | 4 | 2 | 8 | 2 | 3770 MBPS | | ## Design Variant 3: 8-tile design with TP_CASC_LEN=4 and TP_SSR=2 (AIE-ML) @@ -656,9 +656,9 @@ Close the Vitis Analyzer. | Design | TP_CASC_LEN | TP_SSR | NPORT_I | NPORT_O | Throughput (AIE)|Throughput (AIE-ML)| |---------------------|-------------|--------|---------|---------|-----------------|-------------------| -| Design Variant 1 | 2 | 1 | 1 | 1 | 1137 MBPS | 1529 MBPS | -| Design Variant 2 | 4 | 1 | 4 | 1 | 2578 MBPS | 3029 MBPS | -| Design Variant 3 | 4 | 2 | 8 | 2 | 3935 MBPS | 6702 MBPS | +| Design Variant 1 | 1 | 1 | 1 | 1 | 1112 MBPS | 1529 MBPS | +| Design Variant 2 | 4 | 1 | 4 | 1 | 2447 MBPS | 3033 MBPS | +| Design Variant 3 | 4 | 2 | 8 | 2 | 3770 MBPS | 6754 MBPS | From the preceding table, for **Design Variant 3**, the AIE-ML architecture achieves a performance that is roughly **1.7** times faster than the AIE architecture. diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie-ml/gemm_16x32x8/Makefile b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie-ml/gemm_16x32x8/Makefile index db2ca07103..046b52a01c 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie-ml/gemm_16x32x8/Makefile +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie-ml/gemm_16x32x8/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := gemm_16x32x8_app MY_SOURCES := ${MY_APP}.cpp gemm_16x32x8_graph.h -PLATFORM_USE := xilinx_vek280_base_202510_1 +PLATFORM_USE := xilinx_vek280_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie-ml/gemm_16x32x8_cascade/Makefile b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie-ml/gemm_16x32x8_cascade/Makefile index db2ca07103..046b52a01c 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie-ml/gemm_16x32x8_cascade/Makefile +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie-ml/gemm_16x32x8_cascade/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := gemm_16x32x8_app MY_SOURCES := ${MY_APP}.cpp gemm_16x32x8_graph.h -PLATFORM_USE := xilinx_vek280_base_202510_1 +PLATFORM_USE := xilinx_vek280_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie-ml/gemm_16x32x8_cascade/gemm_16x32x8_graph.h b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie-ml/gemm_16x32x8_cascade/gemm_16x32x8_graph.h index c538187469..ec53d0f165 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie-ml/gemm_16x32x8_cascade/gemm_16x32x8_graph.h +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie-ml/gemm_16x32x8_cascade/gemm_16x32x8_graph.h @@ -70,7 +70,7 @@ class gemm_16x32x8_graph : public graph { sig_o[ii] = output_plio::create(pname, plio_64_bits, fname); connect<>(gemm.out[ii],sig_o[ii].in[0]); } - location(gemm) = bounding_box(18,0,21,0); + adf::location(*this) = adf::area_group({{adf::aie_tile, 18, 0, 21, 0},{adf::shim_tile,18,0,21,0}}); } }; diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie-ml/gemm_16x32x8_cascade_ssr/Makefile b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie-ml/gemm_16x32x8_cascade_ssr/Makefile index f7e5540c82..d83e57944a 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie-ml/gemm_16x32x8_cascade_ssr/Makefile +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie-ml/gemm_16x32x8_cascade_ssr/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := gemm_16x32x8_app MY_SOURCES := ${MY_APP}.cpp gemm_16x32x8_graph.h -PLATFORM_USE := xilinx_vek280_base_202510_1 +PLATFORM_USE := xilinx_vek280_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing @@ -51,7 +51,7 @@ help:: @echo " make clean" @echo " Command to remove all the generated files." -all: ${AIE_OUTPUT} profile +all: ${AIE_OUTPUT} x86all: clean x86com x86sim diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie-ml/gemm_16x32x8_cascade_ssr/gemm_16x32x8_graph.h b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie-ml/gemm_16x32x8_cascade_ssr/gemm_16x32x8_graph.h index 5a9151b956..46b00ce1e9 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie-ml/gemm_16x32x8_cascade_ssr/gemm_16x32x8_graph.h +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie-ml/gemm_16x32x8_cascade_ssr/gemm_16x32x8_graph.h @@ -70,7 +70,7 @@ class gemm_16x32x8_graph : public graph { sig_o[ii] = output_plio::create(pname, plio_64_bits, fname); connect<>(gemm.out[ii],sig_o[ii].in[0]); } - location(gemm) = bounding_box(18,0,21,1); + adf::location(*this) = adf::area_group({{adf::aie_tile, 18, 0, 21, 1},{adf::shim_tile,18,0,21,0}}); } }; diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie/gemm_16x32x8/Makefile b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie/gemm_16x32x8/Makefile index 6d240d4243..6dc44d3009 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie/gemm_16x32x8/Makefile +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie/gemm_16x32x8/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := gemm_16x32x8_app MY_SOURCES := ${MY_APP}.cpp gemm_16x32x8_graph.h -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie/gemm_16x32x8_cascade/Makefile b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie/gemm_16x32x8_cascade/Makefile index 6d240d4243..6dc44d3009 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie/gemm_16x32x8_cascade/Makefile +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie/gemm_16x32x8_cascade/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := gemm_16x32x8_app MY_SOURCES := ${MY_APP}.cpp gemm_16x32x8_graph.h -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie/gemm_16x32x8_cascade/gemm_16x32x8_graph.h b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie/gemm_16x32x8_cascade/gemm_16x32x8_graph.h index c538187469..ec53d0f165 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie/gemm_16x32x8_cascade/gemm_16x32x8_graph.h +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie/gemm_16x32x8_cascade/gemm_16x32x8_graph.h @@ -70,7 +70,7 @@ class gemm_16x32x8_graph : public graph { sig_o[ii] = output_plio::create(pname, plio_64_bits, fname); connect<>(gemm.out[ii],sig_o[ii].in[0]); } - location(gemm) = bounding_box(18,0,21,0); + adf::location(*this) = adf::area_group({{adf::aie_tile, 18, 0, 21, 0},{adf::shim_tile,18,0,21,0}}); } }; diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie/gemm_16x32x8_cascade_ssr/Makefile b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie/gemm_16x32x8_cascade_ssr/Makefile index db91f19cca..1b2927b8a0 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie/gemm_16x32x8_cascade_ssr/Makefile +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie/gemm_16x32x8_cascade_ssr/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := gemm_16x32x8_app MY_SOURCES := ${MY_APP}.cpp gemm_16x32x8_graph.h -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing @@ -51,7 +51,7 @@ help:: @echo " make clean" @echo " Command to remove all the generated files." -all: ${AIE_OUTPUT} profile +all: ${AIE_OUTPUT} x86all: clean x86com x86sim diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie/gemm_16x32x8_cascade_ssr/gemm_16x32x8_graph.h b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie/gemm_16x32x8_cascade_ssr/gemm_16x32x8_graph.h index 5a9151b956..46b00ce1e9 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie/gemm_16x32x8_cascade_ssr/gemm_16x32x8_graph.h +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/06-gemm/aie/gemm_16x32x8_cascade_ssr/gemm_16x32x8_graph.h @@ -70,7 +70,7 @@ class gemm_16x32x8_graph : public graph { sig_o[ii] = output_plio::create(pname, plio_64_bits, fname); connect<>(gemm.out[ii],sig_o[ii].in[0]); } - location(gemm) = bounding_box(18,0,21,1); + adf::location(*this) = adf::area_group({{adf::aie_tile, 18, 0, 21, 1},{adf::shim_tile,18,0,21,0}}); } }; diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/DeepDiveBufferDescriptors.md b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/DeepDiveBufferDescriptors.md index 366851d1d6..a6356d3ec3 100755 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/DeepDiveBufferDescriptors.md +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/DeepDiveBufferDescriptors.md @@ -12,16 +12,14 @@ + # Buffer Descriptors ## Introduction DMA programming is performed through _Tiling Parameters_. These parameters describe how the data should be accessed in the memory on a tile basis. Dimension 0 is the dimesion where the data are contiguous in memory. The overall dimension of the buffer is specified and then the tile dimension and the number of tiles to read in each dimension. -This is actually aa EoU layer above the real hardware. The actual DMA programming is controlled through _Buffer Descriptors_. Their usage is cumbersome compared to tiling parameters, that's why the latter are used for DAM programming. Unfortunately from time to time, during AI Engine compilation, you may have error messages like: - -```shell -``` +This is actually an EoU layer above the real hardware. The actual DMA programming is controlled through _Buffer Descriptors_. Their usage is cumbersome compared to tiling parameters, that's why the latter are used for DAM programming. Unfortunately from time to time, during AI Engine compilation, you may have error messages like: In order to understand why you get this type of message, I encourage you to read this small section. diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/Makefile b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/Makefile index 43cf0ae0df..fd57684a74 100755 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/Makefile +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/Makefile @@ -30,7 +30,7 @@ VPP_SPEC = $(ADDON_DIR)/system_ExtBuf.cfg # Targets -.PHONY: data disp_repetition full_extbuf_hw full_extbuf_hwemu full_extbuf_sim_hwemu run_hw_emu clean preprocessor run_tests +.PHONY: data disp_repetition full_extbuf_hw full_extbuf_hwemu full_extbuf_sim_hwemu run_hw_emu clean preprocessor run_tests aie_run run_tests: make SECTION=doc clean_all data aie aiesim @@ -126,6 +126,8 @@ aie: ${LIBADFAIE} ${LIBADFAIE}: $(SRC_DIR)/* preprocessor ${AIE_CMPL_CMD} $(PreProc) +aie_run: $(SRC_DIR)/* preprocessor + ${AIE_CMPL_CMD} --aie.compile-testbench-only $(PreProc) @@ -249,6 +251,7 @@ clean: rm -f *.zip *.img *.wcfg *.wdb plm.bin pmc_cdo.bin qemu_resize_img.sh v++.package_summary rm -f *.xclbin aie.merged.cdo.bin BOOT* boot_image.bif ExtBuf.* launch_hw_emu.sh rm -rf sd_card .ipcache emu_qemu_scripts cfg sim sw_extbuf/host.exe sw_extbuf/host.o + rm -rf analyzer_input baremetal_metadata_package.cpp clean_all: clean rm -rf data diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/MemoryTiles.md b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/MemoryTiles.md index 91d13d35bb..a8ea7ed43c 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/MemoryTiles.md +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/MemoryTiles.md @@ -118,6 +118,7 @@ make SECTION=memtile T1 aie ``` This ends up with this error message + ```shell INFO: [aiecompiler 77-6570] For port 'TG.G1.mtxin.in[0]', allocated DMA is 'tile: memory, col:10, row:0, channel:0, dir:s2mm' INFO: [aiecompiler 77-6570] For port 'TG.G1.mtxin.out[0]', allocated DMA is 'tile: memory, col:10, row:0, channel:0, dir:mm2s' diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/README.md b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/README.md index 7d609f35a4..f2f62b12c6 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/README.md +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/README.md @@ -15,22 +15,22 @@ # Tiling Parameter Programming -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction ->**IMPORTANT**: Before beginning the tutorial make sure you have installed the AMD Vitis™ 2025.1 software. The Vitis release includes all the embedded base platforms including the VEK280 base platform that is used in this tutorial. In addition, ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). +>**IMPORTANT**: Before beginning the tutorial make sure you have installed the AMD Vitis™ 2025.2 software. The Vitis release includes all the embedded base platforms including the VEK280 base platform that is used in this tutorial. In addition, ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). The ‘common image’ package contains a prebuilt Linux kernel and root file system that can be used with the AMD Versal™ board for embedded design development using the Vitis software platform. Before starting this tutorial, run the following steps: 1. Go to the directory where you have unzipped the Versal Common Image package. -2. In a Bash shell, run the ``/Common Images Dir/xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux`` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ``/Common Images Dir/xilinx-versal-common-v2025.1/sdk.sh``. -3. Set up your ROOTFS and IMAGE to point to the ``rootfs.ext4`` and Image files located in the ``/Common Images Dir/xilinx-versal-common-v2025.1`` directory. +2. In a Bash shell, run the ``/Common Images Dir/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux`` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ``/Common Images Dir/xilinx-versal-common-v2025.2/sdk.sh``. +3. Set up your ROOTFS and IMAGE to point to the ``rootfs.ext4`` and Image files located in the ``/Common Images Dir/xilinx-versal-common-v2025.2`` directory. 4. Set up your PLATFORM_REPO_PATHS environment variable to ``$XILINX_VITIS/base_platforms``. -This tutorial targets VEK280 board for 2025.1 version. +This tutorial targets VEK280 board for 2025.2 version. Data generation for this tutorial requires [Python 3](https://www.python.org/downloads/). The following packages are required: @@ -44,8 +44,6 @@ Data generation for this tutorial requires [Python 3](https://www.python.org/dow - jmespath - json - - ## Objectives After completing this tutorial, you will be able to: @@ -104,8 +102,6 @@ This is the same behaviour for x86 compilation and simulation: make SECTION=[doc | memtile | extbuf | memmodule] [T1] [T2] [T3] [T4] x86 x86sim ``` - - ## Basics of Tiling Parameter Programming ### Introduction @@ -157,16 +153,18 @@ In order to be able to view the Tiling Parameter Programming effects on data, th ### CreateNDData.py This script is used to generate data so that it is easy to see the dimensions and coordinates of each data. For example 2D data where all dimension length are less than 10 will be: + ``` 0 1 2 3 4 5 6 7 -10 11 12 13 14 15 16 17 -20 21 22 23 24 25 26 27 -30 31 32 33 34 35 36 37 -40 41 42 43 44 45 46 47 -50 51 52 53 54 55 56 57 -60 61 62 63 64 65 66 67 -70 71 72 73 74 75 76 77 -``` + 10 11 12 13 14 15 16 17 + 20 21 22 23 24 25 26 27 + 30 31 32 33 34 35 36 37 + 40 41 42 43 44 45 46 47 + 50 51 52 53 54 55 56 57 + 60 61 62 63 64 65 66 67 + 70 71 72 73 74 75 76 77 + ``` + As you can see, the unit digit is the column number and the 10s digit is the row number. Now If there are 3 dimensions, the 100s digit will be the layer number and so on. If one dimension length is between 10 and 99, two digits will be used in each dimension to represent the index. Here are the generated data for dimensions: 16 8 and 2: @@ -196,6 +194,7 @@ Layer = 0 In these case I specified a base of 10 and 100. A base of 16 or 256 could have been chosen if the display was in hexadecimal. Here is the usage of this script: + ```SHELL Usage: CreateNDData NbDataPerLine Base Dimensions LengthDim0 [LengthDim1 ...] NbDataPerLine: Number of data printed per line. @@ -211,6 +210,7 @@ Output must be redirected to a file to be stored. ### GetTiles.py `GetTiles.py` is used to visualize the tiles of the data. It is a simple script that reads the data from a file and displays the tiles. Here is the usage of this script: + ```SHELL Usage: GetTiles filename TileDim NCols [ NRows [ NLayers [ NImages ]]] [ Tile# | Tile_start Tile_end] filename: input file containing the matrix (without timestamps) @@ -234,7 +234,9 @@ Display optimization is just a question of adding ellipsis for large number of c ```Shell 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 ``` - Optimized display of the same 256 element vector: + +Optimized display of the same 256 element vector: + ```SHELL 0 1 2 3 4 5 6 7 8 9 ... 246 247 248 249 250 251 252 253 254 255 ``` @@ -244,6 +246,7 @@ Display optimization is just a question of adding ellipsis for large number of c After AI Engine compilation with hardware target (not x86 simulation), all tiling parameters are converted into Buffer Descriptor initialization. In order to know which BD are initialized the python script `CompilerReport.py`can be used giving the AIE Work directory as parameter. This can be used to extract various information about the implementation solution of the AIE compiler, mapper, router. Script can be used to extract DMA channels, BD numbers and Tiling parameters: + ```shell Usage: ExtractBDNumbers.py WorkDirectory option1 [option2 [...]] -bd_memtile: extract Memory Tile BDs diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/addon_files/embedded_exec.sh b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/addon_files/embedded_exec.sh index 15e269ad1f..4c1c1fc36e 100755 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/addon_files/embedded_exec.sh +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/addon_files/embedded_exec.sh @@ -7,5 +7,5 @@ export XILINX_XRT=/usr -./host.exe a.xclbin 1 +./host.exe a.xclbin 2 diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_doc/graph.cpp b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_doc/graph.cpp index a37afcb69a..9ae00472f1 100755 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_doc/graph.cpp +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_doc/graph.cpp @@ -3,7 +3,8 @@ #include "graph.h" -TopGraph<1,1,1,1, 1,1,1,1, 1,1,1> TG; +// TopGraph<1,1,1,1, 1,1,1,1, 1,1,1> TG; +TopGraph<0,0,0,0,0,0,0,1, 0,0,0> TG; int main(int argc, char ** argv) { diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_doc/graph.h b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_doc/graph.h index 0819d27391..53288cde35 100755 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_doc/graph.h +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_doc/graph.h @@ -16,6 +16,7 @@ class TopGraph : public adf::graph // I do not use index 0 for the sake of simplicity: 1 --> G1, ... static constexpr int NGraphs = 11; static constexpr int noutput[NGraphs + 1] = {0, 3, 1, 1, 1, 2, 1, 1,2,1,1,1}; + static constexpr int ninput[NGraphs + 1] = {0, 1, 1, 1, 1, 1, 1, 1,2,1,1,1}; adf::input_plio plin[50]; adf::output_plio plout[50]; @@ -47,10 +48,12 @@ class TopGraph : public adf::graph { // Input PLIO std::string filename = "data/Input" + ext + ".txt"; - plin[idxin] = adf::input_plio::create("input_" + std::to_string(idxin), adf::plio_64_bits, filename, 625); - adf::connect(plin[idxin].out[0], G.din); - idxin++; - + for(int i=0;i din; + adf::port din[1]; adf::port dout[3]; adf::shared_buffer mtxin; @@ -41,7 +41,7 @@ class Graph1_1D : public adf::graph adf::location(k3) = adf::tile(COL, 2); // Connections - adf::connect (din,mtxin.in[0]); + adf::connect (din[0],mtxin.in[0]); adf::write_access(mtxin.in[0]) = adf::tiling({ .buffer_dimension = {256}, .tiling_dimension = {256}, @@ -81,7 +81,7 @@ class Graph2_1D : public adf::graph private: public: adf::kernel k1; - adf::port din; + adf::port din[1]; adf::port dout[1]; adf::shared_buffer mtxin; @@ -102,7 +102,7 @@ class Graph2_1D : public adf::graph adf::location(k1) = adf::tile(COL, 0); // Connections - adf::connect(din, mtxin.in[0]); + adf::connect(din[0], mtxin.in[0]); adf::write_access(mtxin.in[0]) = adf::tiling({ .buffer_dimension = {256}, .tiling_dimension = {256}, @@ -128,7 +128,7 @@ class Graph3_1D : public adf::graph private: public: adf::kernel k1; - adf::port din; + adf::port din[1]; adf::port dout[1]; adf::shared_buffer mtxin; @@ -149,7 +149,7 @@ class Graph3_1D : public adf::graph adf::location(k1) = adf::tile(COL, 0); // Connections - adf::connect(din, mtxin.in[0]); + adf::connect(din[0], mtxin.in[0]); adf::write_access(mtxin.in[0]) = adf::tiling({.buffer_dimension = {256}, .tiling_dimension = {256}, .offset = {0}}); @@ -174,7 +174,7 @@ class Graph3_1D : public adf::graph private: public: adf::kernel k1; - adf::port din; + adf::port din[1]; adf::port dout[1]; adf::shared_buffer mtxin; @@ -195,7 +195,7 @@ class Graph3_1D : public adf::graph adf::location(k1) = adf::tile(COL, 0); // Connections - adf::connect(din, mtxin.in[0]); + adf::connect(din[0], mtxin.in[0]); adf::write_access(mtxin.in[0]) = adf::tiling({ .buffer_dimension = {256}, .tiling_dimension = {256}, diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_doc/graph_2D.h b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_doc/graph_2D.h index 93c097339d..2b8c25b635 100755 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_doc/graph_2D.h +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_doc/graph_2D.h @@ -12,7 +12,7 @@ private: public: adf::kernel k1, k2; - adf::port din; + adf::port din[1]; adf::port dout[2]; adf::shared_buffer mtxin; @@ -37,7 +37,7 @@ // Connections - adf::connect(din, mtxin.in[0]); + adf::connect(din[0], mtxin.in[0]); adf::write_access(mtxin.in[0]) = adf::tiling({.buffer_dimension = {128, 2}, .tiling_dimension = {128, 2}, .offset = {0,0}}); @@ -70,7 +70,7 @@ private: public: adf::kernel k1; - adf::port din; + adf::port din[1]; adf::port dout[1]; adf::shared_buffer mtxin; @@ -90,7 +90,7 @@ // Connections - adf::connect(din, mtxin.in[0]); + adf::connect(din[0], mtxin.in[0]); adf::write_access(mtxin.in[0]) = adf::tiling({.buffer_dimension = {128, 2}, .tiling_dimension = {128, 2}, .offset = {0, 0}}); @@ -114,7 +114,7 @@ private: public: adf::kernel k1; - adf::port din; + adf::port din[1]; adf::port dout[1]; adf::shared_buffer mtxin; @@ -133,7 +133,7 @@ adf::location(k1) = adf::tile(COL, 0); // Connections - adf::connect(din, mtxin.in[0]); + adf::connect(din[0], mtxin.in[0]); adf::write_access(mtxin.in[0]) = adf::tiling({.buffer_dimension = {16, 4}, .tiling_dimension = {16, 4}, .offset = {0, 0}}); @@ -156,7 +156,7 @@ private: public: adf::kernel k1,k2; - adf::port din; + adf::port din[2]; adf::port dout[2]; adf::shared_buffer mtxin1,mtxin2; @@ -184,7 +184,7 @@ adf::location(k2) = adf::tile(COL, 1); // k1 Connections - adf::connect(din, mtxin1.in[0]); + adf::connect(din[0], mtxin1.in[0]); adf::write_access(mtxin1.in[0]) = adf::tiling({.buffer_dimension = {32,1}, .tiling_dimension = {32,1}, .offset = {0, 0}}); @@ -199,7 +199,7 @@ adf::connect(k1.out[0], dout[0]); // k2 Connections - adf::connect(din, mtxin2.in[0]); + adf::connect(din[1], mtxin2.in[0]); adf::write_access(mtxin2.in[0]) = adf::tiling({.buffer_dimension = {32, 8}, .tiling_dimension = {32, 8}, .offset = {0, 0}}); diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_doc/graph_3D.h b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_doc/graph_3D.h index 9096315360..644f8ab822 100755 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_doc/graph_3D.h +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_doc/graph_3D.h @@ -12,7 +12,7 @@ class Graph1_3D : public adf::graph public: adf::kernel k1; - adf::port din; + adf::port din[1]; adf::port dout[1]; adf::shared_buffer mtxin; @@ -31,7 +31,7 @@ class Graph1_3D : public adf::graph adf::location(k1) = adf::tile(COL,0); // Connections - adf::connect (din,mtxin.in[0]); + adf::connect (din[0],mtxin.in[0]); adf::write_access(mtxin.in[0]) = adf::tiling({ .buffer_dimension = {32,4,2}, .tiling_dimension = {32,4,2}, @@ -56,7 +56,7 @@ class Graph2_3D : public adf::graph private: public: adf::kernel k1; - adf::port din; + adf::port din[1]; adf::port dout[1]; adf::shared_buffer mtxin; @@ -77,7 +77,7 @@ class Graph2_3D : public adf::graph adf::location(k1) = adf::tile(COL, 0); // Connections - adf::connect(din, mtxin.in[0]); + adf::connect(din[0], mtxin.in[0]); adf::write_access(mtxin.in[0]) = adf::tiling({ .buffer_dimension = {32,4,2}, .tiling_dimension = {32,4,2}, diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_doc/graph_4D.h b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_doc/graph_4D.h index ed5b4f22bf..efe62cccbe 100755 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_doc/graph_4D.h +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_doc/graph_4D.h @@ -12,7 +12,7 @@ class Graph1_4D : public adf::graph public: adf::kernel k1; - adf::port din; + adf::port din[1]; adf::port dout[1]; adf::shared_buffer mtxin; @@ -31,7 +31,7 @@ class Graph1_4D : public adf::graph adf::location(k1) = adf::tile(COL,0); // Connections - adf::connect (din,mtxin.in[0]); + adf::connect (din[0],mtxin.in[0]); adf::write_access(mtxin.in[0]) = adf::tiling({ .buffer_dimension = {4,4,4,4}, .tiling_dimension = {4,4,4,4}, diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_extbuf/graph.cpp b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_extbuf/graph.cpp index e650eaca99..5b37013039 100755 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_extbuf/graph.cpp +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/07-tiling-parameters/src_extbuf/graph.cpp @@ -12,97 +12,76 @@ Graph1<10> G1; int main(int argc, char ** argv) { // How many GMIOs in the graph - int Ngraphs = 1; int IterationLength = Dim0*Dim1*Dim2*Dim3; - int TotalLength = NIterations*IterationLength; - + int TotalLength = IterationLength; // *NIterations + // Allocate memory for input and output GMIOs - int **GMin,**GMout; + int *GMin,*GMout; - GMin = new int*[Ngraphs]; - for (int i = 0; i < Ngraphs; ++i) - { - GMin[i] = (int32*)adf::GMIO::malloc(TotalLength*sizeof(int32)); - } - GMout = new int*[Ngraphs]; - for (int i = 0; i < Ngraphs; ++i) - { - GMout[i] = (int32 *)adf::GMIO::malloc(TotalLength * sizeof(int32)); - } - // Initialize memory - for(int i = 0; i < Ngraphs; ++i) { - for (int j = 0; j < TotalLength; ++j) - { - GMin[i][j] = (i+1)*(j+1); - } - } - for (int i = 0; i < Ngraphs; ++i) - { - for (int j = 0; j < TotalLength; ++j) - { - GMout[i][j] = -999; - } - } - - G1.init(); + GMin = (int32*)adf::GMIO::malloc(TotalLength*sizeof(int32)); + GMout = (int32 *)adf::GMIO::malloc(TotalLength * sizeof(int32)); - for(int iter=0;iter #include #include #include @@ -50,8 +51,8 @@ int load_data_file(std::string fname,T * data,int L) int run(int argc, char *argv[]) { - int NGraphs = 1; - int NIter = 1; + // int NGraphs = 1; + int NIter = 2; if(argc != 2 && argc != 3) { std::cout << "Usage: " << argv[0] <<" [Number of iterations]" << std::endl; @@ -87,37 +88,35 @@ int run(int argc, char *argv[]) const int REPETITION = Dim2*Dim3; const int FRAME_LENGTH = TILE_SIZE*REPETITION; - xrt::aie::bo *InputBufferObject[NGraphs]; - xrt::aie::bo *OutputBufferObject[NGraphs]; + xrt::aie::bo *InputBufferObject; + xrt::aie::bo *OutputBufferObject; - int32_t* InputMem[NGraphs]; - int32_t* OutputMem[NGraphs]; + int32_t* InputMem; + int32_t* OutputMem; - xrt::aie::buffer *outbuf[NGraphs]; - xrt::aie::buffer *inbuf[NGraphs]; + xrt::aie::buffer *outbuf; + xrt::aie::buffer *inbuf; - for(int g=0;g: xrt::device object of the accelerator card. - // : Size of the buffer in bytes - // : xrt::bo::flags:: normal | cacheable | device_only | host_only | p2p | svm - // : Defines the memory bank on the device where the buffer should be allocated for IP access. The memory bank specified must match with the corresponding IP port's connection inside the .xclbin file. Otherwise you will get bad_alloc when running the application. - - InputBufferObject[g] = new xrt::aie::bo(device, FRAME_LENGTH * sizeof(int), xrt::bo::flags::normal, 0); - InputMem[g] = InputBufferObject[g]->map(); - for(int k=0;k: xrt::device object of the accelerator card. + // : Size of the buffer in bytes + // : xrt::bo::flags:: normal | cacheable | device_only | host_only | p2p | svm + // : Defines the memory bank on the device where the buffer should be allocated for IP access. The memory bank specified must match with the corresponding IP port's connection inside the .xclbin file. Otherwise you will get bad_alloc when running the application. + + InputBufferObject = new xrt::aie::bo(device, FRAME_LENGTH * sizeof(int), xrt::bo::flags::normal, 0); + InputMem = InputBufferObject->map(); + printf("Input memory virtual addr 0x%px\n",InputMem); + inbuf = new xrt::aie::buffer(device, xclbin_uuid, "G1.ddrin"); - OutputBufferObject[g] = new xrt::aie::bo(device, FRAME_LENGTH * sizeof(int), 0, 0); - OutputMem[g] = OutputBufferObject[g]->map(); - for (int k = 0; k < FRAME_LENGTH; k++) - OutputMem[g][k] = -999; - printf("Graph %d Input memory virtual addr 0x%px\n",g, OutputMem[g]); - } + OutputBufferObject = new xrt::aie::bo(device, FRAME_LENGTH * sizeof(int), 0, 0); + OutputMem = OutputBufferObject->map(); + printf("Output memory virtual addr 0x%px\n",OutputMem); + outbuf = new xrt::aie::buffer(device, xclbin_uuid, "G1.ddrout"); + // Storage for final comparison + int OverallInput[NIter*FRAME_LENGTH]; + int OverallOutput[NIter*FRAME_LENGTH]; ////////////////////////////////////////// @@ -128,105 +127,112 @@ int run(int argc, char *argv[]) auto cghdl = xrt::graph(device,xclbin_uuid,"G1"); cghdl.reset(); - printf("graph run\n"); - cghdl.run(NIter); - - - // Start the output buffers DMAs - for (int g = 0; g < NGraphs; g++) + for(int iter=0; iterasync(*OutputBufferObject[g], XCL_BO_SYNC_BO_AIE_TO_GMIO, FRAME_LENGTH * sizeof(int), /*offset*/ 0); - } + // Input/Output array initialization + int offset = iter*FRAME_LENGTH; + for(int k=0;kasync(*InputBufferObject[g], XCL_BO_SYNC_BO_GMIO_TO_AIE, FRAME_LENGTH * sizeof(int), /*offset*/ 0); - } + printf("graph runs for 1 iteration\n"); + cghdl.run(1); - // Wait for the end of Output buffer DMAs - for (int g = 0; g < NGraphs; g++) - { - outbuf[g]->wait(); + // Start the output buffers DMAs + outbuf->async(*OutputBufferObject, XCL_BO_SYNC_BO_AIE_TO_GMIO, FRAME_LENGTH * sizeof(int), /*offset*/ 0); + + // Start the input buffers DMAs + inbuf->async(*InputBufferObject, XCL_BO_SYNC_BO_GMIO_TO_AIE, FRAME_LENGTH * sizeof(int), /*offset*/ 0); + + // Wait for the end of Input and Output buffer DMAs + inbuf->wait(); + memcpy(&OverallInput[iter*FRAME_LENGTH],InputMem,FRAME_LENGTH*sizeof(int)); + + outbuf->wait(); + memcpy(&OverallOutput[iter*FRAME_LENGTH],OutputMem,FRAME_LENGTH*sizeof(int)); + + for (int k=0;k (" << inrow << "," << incol << ")"; - cout << " insample=k=" << insample << " [" << InputMem[g][insample] << "] --> (" << outrow << "," << outcol << ")" ; - cout << " outsample=" << outsample << " [" << OutputMem[g][outsample] << "]" << endl; - } - if(match==11) - cout << "..." << endl; - match++; - } + cout << " Iter=" << it << " Rep=" << rep << " k=" << k; + cout << " --> (" << inrow << "," << incol << ")"; + cout << " insample=" << insample << " [" << OverallInput[insample] << "] --> (" << outrow << "," << outcol << ")" ; + cout << " outsample=" << outsample << " [" << OverallOutput[outsample] << "]" << endl; } + if(match==11) + cout << "..." << endl; + match++; } - } } + + + } - std::cout << "\n\nDisplays Input and Output" << std::endl; - for (int g = 0; g < NGraphs; g++) + std::cout << "\n\nDisplays Input and Output" << std::endl; + iter_offset = 0; + for (int it = 0; it < NIter; it++, iter_offset += FRAME_LENGTH) + { + int rep_offset = 0; + for (int rep = 0; rep < REPETITION; rep++, rep_offset += TILE_SIZE) { - int iter_offset = 0; - for (int it = 0; it < NIter; it++, iter_offset += FRAME_LENGTH) + int L = 8; + for (int k = 0; k < TILE_SIZE; k+=L) { - int rep_offset = 0; - for (int rep = 0; rep < REPETITION; rep++, rep_offset += TILE_SIZE) - { - int L = 8; - for (int k = 0; k < TILE_SIZE; k+=L) - { - for (int j = 0; j < L; j++) - cout << setw(5) << InputMem[g][k + j + iter_offset + rep_offset]; - cout << " "; - for (int j = 0; j < L; j++) - cout << setw(5) << OutputMem[g][k + j + iter_offset + rep_offset]; + for (int j = 0; j < L; j++) + cout << setw(5) << OverallInput[k + j + iter_offset + rep_offset]; + cout << " "; + for (int j = 0; j < L; j++) + cout << setw(5) << OverallOutput[k + j + iter_offset + rep_offset]; - cout << std::endl; + cout << std::endl; - if (k % TILE_SIZE == TILE_SIZE - L) - cout << std::endl; + if (k % TILE_SIZE == TILE_SIZE - L) + cout << std::endl; - } - } } } + } + return ((match) != 0); - } +} int main(int argc, char* argv[]) { diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/README.md b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/README.md index 7a98f3b14a..477842c0b4 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/README.md +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/README.md @@ -15,22 +15,22 @@ # AIE-ML Performance Analysis Tutorial -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** This tutorial introduces you on design partitioning into AIE-ML device. By various performance analysis techniques introduced, the design is optimized. The performance is also verified in hardware in each optimization step. ->**IMPORTANT**: Before beginning the tutorial make sure you have installed the Vitis software platform 2025.1. The Vitis release includes all the embedded base platforms including the VEK280 base platform that is used in this tutorial. In addition, ensure that you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). +>**IMPORTANT**: Before beginning the tutorial make sure you have installed the Vitis software platform 2025.2. The Vitis release includes all the embedded base platforms including the VEK280 base platform that is used in this tutorial. In addition, ensure that you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). The ‘common image’ package contains a prebuilt Linux kernel and root file system that can be used with the AMD Versal™ board for embedded design development using the Vitis tools. Before starting this tutorial, run the following steps: 1. Go to the directory where you have unzipped the Versal Common Image package. -2. In a Bash shell, run the `/**Common Images Dir**/xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the `/**Common Images Dir**/xilinx-versal-common-v2025.1/sdk.sh`. -3. Set up your ROOTFS and IMAGE to point to the `rootfs.ext4` and Image files located in the `/**Common Images Dir**/xilinx-versal-common-v2025.1` directory. +2. In a Bash shell, run the `/**Common Images Dir**/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the `/**Common Images Dir**/xilinx-versal-common-v2025.2/sdk.sh`. +3. Set up your ROOTFS and IMAGE to point to the `rootfs.ext4` and Image files located in the `/**Common Images Dir**/xilinx-versal-common-v2025.2` directory. 4. Set up your PLATFORM_REPO_PATHS environment variable to `$XILINX_VITIS/base_platforms`. -This tutorial targets VEK280 board for 2025.1 version. +This tutorial targets VEK280 board for 2025.2 version. ## Objectives @@ -53,7 +53,7 @@ Where: $$ {\mu}=\sum_{i=0}^{ROW}\sum_{i=0}^{COL}{x} / {(ROW*COL)} $$ -$$\sigma=\sqrt{{\sum_{i=0}^{ROW}\sum_{i=0}^{COL}{{(x-\mu)}^2}} / {(ROW\*COL-1)}} \approx \sqrt{\sum_{i=0}^{ROW}\sum_{i=0}^{COL}{{(x-\mu)}^2} / {(ROW*COL)}} $$ +$$\sigma=\sqrt{{\sum_{i=0}^{ROW}\sum_{i=0}^{COL}{{(x-\mu)}^2}} / {(ROW*COL-1)}} \approx \sqrt{\sum_{i=0}^{ROW}\sum_{i=0}^{COL}{{(x-\mu)}^2} / {(ROW*COL)}} $$ For designs in the tutorial, following specifications are chosen: diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v1/Makefile b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v1/Makefile index 3bf5563b98..444d83b9de 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v1/Makefile +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v1/Makefile @@ -3,7 +3,7 @@ #SPDX-License-Identifier: MIT TARGET = hw -PLATFORM = ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm +PLATFORM = ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm XSA = vek280_aie_base_graph_${TARGET}.xsa HOST_EXE = host.exe diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v1/aie/graph.h b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v1/aie/graph.h index 28a87aeca8..6836d22954 100755 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v1/aie/graph.h +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v1/aie/graph.h @@ -56,9 +56,9 @@ public : connect(k_norm.out[0], out.in[0]); dimensions(k_mean.in[0])={K_ROW*K_COL};//elements - dimensions(k_mean.out[0])={1};//elements + dimensions(k_mean.out[0])={2};//elements dimensions(k_deviation.in[0])={K_ROW*K_COL};//elements - dimensions(k_deviation.in[1])={1};//elements + dimensions(k_deviation.in[1])={2};//elements dimensions(k_deviation.out[0])={2};//elements dimensions(k_norm.in[0])={K_ROW*K_COL};//elements dimensions(k_norm.in[1])={2};//elements diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v1/pl_kernels/Makefile b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v1/pl_kernels/Makefile index e4c9dd6f31..635642ccb9 100755 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v1/pl_kernels/Makefile +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v1/pl_kernels/Makefile @@ -2,7 +2,7 @@ #Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT -PLATFORM = ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm +PLATFORM = ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm .PHONY: clean diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v1/sw/Makefile b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v1/sw/Makefile index 16d279f0b9..6965a19661 100755 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v1/sw/Makefile +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v1/sw/Makefile @@ -6,7 +6,7 @@ HOST_EXE = ../host.exe HOST_INC = -I../ -I../aie HOST_OBJ = host.o AIE_CTRL_CPP = ../Work/ps/c_rts/aie_control_xrt.cpp -SYSROOT = ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-amd-linux/ +SYSROOT = ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-amd-linux/ CXXFLAGS += -std=c++17 -I$(XILINX_HLS)/include/ -I${SYSROOT}/usr/include/xrt/ -g -Wall -c -fmessage-length=0 --sysroot=${SYSROOT} -I${XILINX_VITIS}/aietools/include ${HOST_INC} diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v2/Makefile b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v2/Makefile index 7371c1eb13..4620b431ab 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v2/Makefile +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v2/Makefile @@ -3,7 +3,7 @@ #SPDX-License-Identifier: MIT TARGET = hw -PLATFORM = ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm +PLATFORM = ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm XSA = vek280_aie_base_graph_${TARGET}.xsa HOST_EXE = host.exe diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v2/aie/graph.h b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v2/aie/graph.h index 3a0d79c9a4..f71fec3fc6 100755 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v2/aie/graph.h +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v2/aie/graph.h @@ -58,9 +58,9 @@ public : connect(k_norm.out[0], out.in[0]); dimensions(k_mean.in[0])={K_ROW*K_COL};//elements - dimensions(k_mean.out[0])={1}; + dimensions(k_mean.out[0])={2}; dimensions(k_deviation.in[0])={K_ROW*K_COL}; - dimensions(k_deviation.in[1])={1}; + dimensions(k_deviation.in[1])={2}; dimensions(k_deviation.out[0])={2}; dimensions(k_norm.in[0])={K_ROW*K_COL}; dimensions(k_norm.in[1])={2}; diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v2/pl_kernels/Makefile b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v2/pl_kernels/Makefile index e4c9dd6f31..635642ccb9 100755 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v2/pl_kernels/Makefile +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v2/pl_kernels/Makefile @@ -2,7 +2,7 @@ #Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT -PLATFORM = ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm +PLATFORM = ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm .PHONY: clean diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v2/sw/Makefile b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v2/sw/Makefile index 16d279f0b9..6965a19661 100755 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v2/sw/Makefile +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v2/sw/Makefile @@ -6,7 +6,7 @@ HOST_EXE = ../host.exe HOST_INC = -I../ -I../aie HOST_OBJ = host.o AIE_CTRL_CPP = ../Work/ps/c_rts/aie_control_xrt.cpp -SYSROOT = ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-amd-linux/ +SYSROOT = ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-amd-linux/ CXXFLAGS += -std=c++17 -I$(XILINX_HLS)/include/ -I${SYSROOT}/usr/include/xrt/ -g -Wall -c -fmessage-length=0 --sysroot=${SYSROOT} -I${XILINX_VITIS}/aietools/include ${HOST_INC} diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/Makefile b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/Makefile index 7371c1eb13..4620b431ab 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/Makefile +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/Makefile @@ -3,7 +3,7 @@ #SPDX-License-Identifier: MIT TARGET = hw -PLATFORM = ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm +PLATFORM = ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm XSA = vek280_aie_base_graph_${TARGET}.xsa HOST_EXE = host.exe diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/aie/mean_dev_norm_first.cc b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/aie/mean_dev_norm_first.cc index 8eef632169..281c1e684a 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/aie/mean_dev_norm_first.cc +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/aie/mean_dev_norm_first.cc @@ -6,7 +6,7 @@ SPDX-License-Identifier: MIT #include #include using namespace adf; -alignas(aie::vector_decl_align) static float accum_zero[32]={0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0}; +alignas(aie::vector_decl_align) /*static*/ float accum_zero[32]={0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0}; static bfloat16 mean_val=0; static bfloat16 dev_val=0; diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/aie/mean_dev_norm_last.cc b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/aie/mean_dev_norm_last.cc index cab5471f5c..af40e4bfe9 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/aie/mean_dev_norm_last.cc +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/aie/mean_dev_norm_last.cc @@ -6,7 +6,7 @@ SPDX-License-Identifier: MIT #include #include using namespace adf; -alignas(aie::vector_decl_align) static float accum_zero[32]={0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0}; +alignas(aie::vector_decl_align) /*static*/ float accum_zero[32]={0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0}; static bfloat16 mean_val=0; static bfloat16 dev_val=0; diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/aie/mean_dev_norm_middle.cc b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/aie/mean_dev_norm_middle.cc index ca9fea6a31..52125126bb 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/aie/mean_dev_norm_middle.cc +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/aie/mean_dev_norm_middle.cc @@ -6,7 +6,7 @@ SPDX-License-Identifier: MIT #include #include using namespace adf; -alignas(aie::vector_decl_align) static float accum_zero[32]={0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0}; +alignas(aie::vector_decl_align) /*static*/ float accum_zero[32]={0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0}; static bfloat16 mean_val=0; static bfloat16 dev_val=0; diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/pl_kernels/Makefile b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/pl_kernels/Makefile index e4c9dd6f31..635642ccb9 100755 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/pl_kernels/Makefile +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/pl_kernels/Makefile @@ -2,7 +2,7 @@ #Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT -PLATFORM = ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm +PLATFORM = ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm .PHONY: clean diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/sw/Makefile b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/sw/Makefile index 16d279f0b9..6965a19661 100755 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/sw/Makefile +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v3/sw/Makefile @@ -6,7 +6,7 @@ HOST_EXE = ../host.exe HOST_INC = -I../ -I../aie HOST_OBJ = host.o AIE_CTRL_CPP = ../Work/ps/c_rts/aie_control_xrt.cpp -SYSROOT = ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-amd-linux/ +SYSROOT = ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-amd-linux/ CXXFLAGS += -std=c++17 -I$(XILINX_HLS)/include/ -I${SYSROOT}/usr/include/xrt/ -g -Wall -c -fmessage-length=0 --sysroot=${SYSROOT} -I${XILINX_VITIS}/aietools/include ${HOST_INC} diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/Makefile b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/Makefile index 7371c1eb13..4620b431ab 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/Makefile +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/Makefile @@ -3,7 +3,7 @@ #SPDX-License-Identifier: MIT TARGET = hw -PLATFORM = ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm +PLATFORM = ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm XSA = vek280_aie_base_graph_${TARGET}.xsa HOST_EXE = host.exe diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/aie/mean_dev_norm_first.cc b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/aie/mean_dev_norm_first.cc index 8eef632169..281c1e684a 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/aie/mean_dev_norm_first.cc +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/aie/mean_dev_norm_first.cc @@ -6,7 +6,7 @@ SPDX-License-Identifier: MIT #include #include using namespace adf; -alignas(aie::vector_decl_align) static float accum_zero[32]={0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0}; +alignas(aie::vector_decl_align) /*static*/ float accum_zero[32]={0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0}; static bfloat16 mean_val=0; static bfloat16 dev_val=0; diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/aie/mean_dev_norm_last.cc b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/aie/mean_dev_norm_last.cc index cab5471f5c..af40e4bfe9 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/aie/mean_dev_norm_last.cc +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/aie/mean_dev_norm_last.cc @@ -6,7 +6,7 @@ SPDX-License-Identifier: MIT #include #include using namespace adf; -alignas(aie::vector_decl_align) static float accum_zero[32]={0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0}; +alignas(aie::vector_decl_align) /*static*/ float accum_zero[32]={0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0}; static bfloat16 mean_val=0; static bfloat16 dev_val=0; diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/aie/mean_dev_norm_middle.cc b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/aie/mean_dev_norm_middle.cc index ca9fea6a31..52125126bb 100644 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/aie/mean_dev_norm_middle.cc +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/aie/mean_dev_norm_middle.cc @@ -6,7 +6,7 @@ SPDX-License-Identifier: MIT #include #include using namespace adf; -alignas(aie::vector_decl_align) static float accum_zero[32]={0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0}; +alignas(aie::vector_decl_align) /*static*/ float accum_zero[32]={0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0}; static bfloat16 mean_val=0; static bfloat16 dev_val=0; diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/pl_kernels/Makefile b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/pl_kernels/Makefile index e4c9dd6f31..635642ccb9 100755 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/pl_kernels/Makefile +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/pl_kernels/Makefile @@ -2,7 +2,7 @@ #Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT -PLATFORM = ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm +PLATFORM = ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm .PHONY: clean diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/sw/Makefile b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/sw/Makefile index 16d279f0b9..6965a19661 100755 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/sw/Makefile +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/13-aie-ml-performance-analysis/normalization_v4/sw/Makefile @@ -6,7 +6,7 @@ HOST_EXE = ../host.exe HOST_INC = -I../ -I../aie HOST_OBJ = host.o AIE_CTRL_CPP = ../Work/ps/c_rts/aie_control_xrt.cpp -SYSROOT = ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-amd-linux/ +SYSROOT = ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-amd-linux/ CXXFLAGS += -std=c++17 -I$(XILINX_HLS)/include/ -I${SYSROOT}/usr/include/xrt/ -g -Wall -c -fmessage-length=0 --sysroot=${SYSROOT} -I${XILINX_VITIS}/aietools/include ${HOST_INC} diff --git a/AI_Engine_Development/AIE-ML/Feature_Tutorials/20-aiecompiler-features/README.md b/AI_Engine_Development/AIE-ML/Feature_Tutorials/20-aiecompiler-features/README.md index 353838bdcc..df23377a38 100755 --- a/AI_Engine_Development/AIE-ML/Feature_Tutorials/20-aiecompiler-features/README.md +++ b/AI_Engine_Development/AIE-ML/Feature_Tutorials/20-aiecompiler-features/README.md @@ -15,18 +15,18 @@ # AI Engine Compiler Features -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction This tutorial targets AIE-ML device, but shares test cases and description files with [AIE 20-aiecompiler-features](../../../AIE/Feature_Tutorials/20-aiecompiler-features). ->**IMPORTANT**: Before beginning the tutorial make sure you have installed the AMD Vitis™ 2025.1 software. The Vitis release includes all the embedded base platforms including the VEK280 base platform that is used in this tutorial. +>**IMPORTANT**: Before beginning the tutorial make sure you have installed the AMD Vitis™ 2025.2 software. The Vitis release includes all the embedded base platforms including the VEK280 base platform that is used in this tutorial. Set up your PLATFORM_REPO_PATHS environment variable to ``$XILINX_VITIS/base_platforms``. -This tutorial targets VEK280 board for 2025.1/ version. +This tutorial targets VEK280 board. ## Objectives diff --git a/AI_Engine_Development/AIE-ML/README.md b/AI_Engine_Development/AIE-ML/README.md index a97c173f55..55ff965f34 100644 --- a/AI_Engine_Development/AIE-ML/README.md +++ b/AI_Engine_Development/AIE-ML/README.md @@ -23,15 +23,15 @@ The tutorials under the AI Engine for Machine Learning (AIE-ML) Development help - The AIE-ML Development [**Design Tutorials**](./Design_Tutorials/) showcase the two major phases of AI Engine-ML application development: architecting the application and developing the kernels. Both phases are demonstrated in these tutorials. ->**IMPORTANT**: Before beginning a tutorial, ensure you have installed the AMD Vitis™ 2025.1 software. The Vitis release includes all the embedded base platforms, including the VEK280 base platform that is used in these tutorials. In addition, ensure you have downloaded the Common Images for Embedded Vitis Platforms from [Downloads](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). +>**IMPORTANT**: Before beginning a tutorial, ensure you have installed the AMD Vitis™ 2025.2 software. The Vitis release includes all the embedded base platforms, including the VEK280 base platform that is used in these tutorials. In addition, ensure you have downloaded the Common Images for Embedded Vitis Platforms from [Downloads](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). The `common image` package contains a prebuilt Linux kernel and root file system that can be used with the AMD Versal™ board for embedded design development using the Vitis software platform. Before starting a tutorial, run the following steps: 1. Go to the directory where you have unzipped the Versal Common Image package. -2. In a Bash shell, run the `/Common Images Dir/xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run `/Common Images Dir/xilinx-versal-common-v2025.1/sdk.sh`. -3. Set up your ROOTFS and IMAGE to point to the `rootfs.ext4` and Image files located in the `/Common Images Dir/xilinx-versal-common-v2025.1` directory. +2. In a Bash shell, run the `/Common Images Dir/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run `/Common Images Dir/xilinx-versal-common-v2025.2/sdk.sh`. +3. Set up your ROOTFS and IMAGE to point to the `rootfs.ext4` and Image files located in the `/Common Images Dir/xilinx-versal-common-v2025.2` directory. 4. Set up your PLATFORM_REPO_PATHS environment variable to `$XILINX_VITIS/base_platforms`. ### Feature Tutorials diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/Makefile b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/Makefile new file mode 100644 index 0000000000..0ddd314cbc --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/Makefile @@ -0,0 +1,37 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani +# + +export TARGET ?= hw_emu +export SYSROOT = ${YOCTO_ARTIFACTS}/amd-cortexa78-mali-common_meta-edf-app-sdk/sdk/sysroots/cortexa72-cortexa53-amd-linux + +export PLATFORM = ${PLATFORM_REPO_PATHS}/vek385_base_reva/vek385_base_reva.xpfm + +############## +# Build Flow # +############## +.PHONY: help clean all + +help: + @echo "Makefile Usage:" + @echo "Run 'make my-venv' to build a Python Virtual Environment for this tutorial" + @echo "Afterwards run 'make all' to build the design for AIE-ML v2" + @echo "Run 'make clean' to remove all the generated files" + +all: + $(MAKE) all -C aie/radioml_top + $(MAKE) all -C ps_apps + $(MAKE) all -C vitis + +my-venv: create_venv.sh + ./create_venv.sh + +clean: + $(MAKE) clean -C aie/radioml_top + $(MAKE) clean -C ps_apps + $(MAKE) clean -C vitis + @/bin/rm -rf .Xil vivado* +# @/bin/rm -rf my-venv .ipynb_checkpoints diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/README.md b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/README.md new file mode 100755 index 0000000000..a97a00ccb9 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/README.md @@ -0,0 +1,496 @@ + + + + + +
+ + + + +

AI Engine Development

+ See Vitis™ Development Environment on amd.com
 + See Vitis™ AI Development Environment on amd.com +
+ + +# Radio-ML on AMD Versal™ AI Edge Series Gen 2 (AIE-ML v2) + +***Version: Vitis 2025.2*** + +## Table of Contents + +1. [Introduction](#introduction) +2. [Jupyter Notebook Model](#jupyter-notebook-model) +3. [AIE-ML v2 Inference Solution](#aie-ml-v2-inference-solution) +4. [Individual Layer Designs](#individual-layer-designs) +5. [Design Resources](#design-resources) +6. [Build and Run Design](#build-and-run-design) +7. [Summary](#summary) + +[References](#references) + +[Support](#support) + +[License](#license) + +## Introduction + +This tutorial implements a Convolutional Neural Network classifier on [AMD Versal™ AI Edge Series Gen 2](https://www.amd.com/en/products/adaptive-socs-and-fpgas/versal/gen2/ai-edge-series.html) for radio signal classification. + +The model architecture follows what is defined in [[1]]. DeepSig Dataset 2018.01A [[2]] is used to train the model. This tutorial example illustrates a number of key topics fundamental to custom coding machine learning designs using the AIE API including: + +* Using multi-node matrix multiply intrinsics to vectorize ConvNet layer compute workloads +* Using 2D addressing patterns of memory tiles to access layer I/O in the order required for consumption by the compute +* Using zero-padding capability of the memory tiles when feeding input data to ConvNet layers to preserve the original input size +* Using async RTPs to send network weights from host at startup and using local tile memory for storing them +* Using custom coding to implement [SeLU activation function](https://www.tensorflow.org/api_docs/python/tf/keras/activations/selu) + +### Virtual Python Environment Setup + +This tutorial implements computer models of the Radio-ML ConvNet in Python using Jupyter Notebooks. This is best managed using a Python virtual environment. + +The first step of this tutorial involves setting up such a virtual environment with the required versions of all the associated open source Python packages. + +The top level Makefile of this tutorial builds the Python virtual environment based on a script `create_venv.sh`. It creates the environment and then loads a set of specific versions of all required Python packages. + +To create this Python virtual environment, run the following code: + +``` +% make venv +% source my-venv/bin/activate +% python --version +``` + +This creates a folder `my-venv` in the top-level folder. This folder contains all the required packages for Jupyter Notebooks, TensorFlow, matplotlib, pydot, and bfloat16 (including all dependencies) required by the tutorial. + +The second command activates the Python environment. The third command displays the version of Python used to create the virtual environment. This tutorial is and tested using Python 3.12.6. + +## Jupyter Notebook Model + +The first step of this tutorial is to build a computer model of the Radio-ML ConvNet modulation classifier and to train the model to obtain a set of weights that may be used for inference. The full Jupyter Notebook of this model is provided by [radio-ml-model.ipynb](radio-ml-model.ipynb). + +Begin by downloading the DeepSig Dataset 2018.01A [[2]] and set environment variable RADIOML_DATA to point to dataset. + +To run the notebook, execute the following command: + +``` +% jupyter-notebook radio-ml-model.ipynb +``` + +The Keras model for the Radio-ML ConvNet modulation classifier attempts to follow closely what is defined in [[1]] and is given by the following Python code: + +``` + inputs = keras.Input(shape=(1024,2),name="input") + x1 = Conv1D(filters=64,kernel_size=7,strides=1,padding="same",name="conv1D_w1",activation='relu')(inputs) + x2 = MaxPooling1D(pool_size=2,strides=2,padding="valid",name="max_pool1d_w2")(x1) + x3 = Conv1D(filters=64,kernel_size=7,strides=1,padding="same",name="conv1D_w3",activation='relu')(x2) + x4 = MaxPooling1D(pool_size=2,strides=2,padding="valid",name="max_pool1d_w4")(x3) + x5 = Conv1D(filters=64,kernel_size=7,strides=1,padding="same",name="conv1D_w5",activation='relu')(x4) + x6 = MaxPooling1D(pool_size=2,strides=2,padding="valid",name="max_pool1d_w6")(x5) + x7 = Conv1D(filters=64,kernel_size=7,strides=1,padding="same",name="conv1D_w7",activation='relu')(x6) + x8 = MaxPooling1D(pool_size=2,strides=2,padding="valid",name="max_pool1d_w8")(x7) + x9 = Conv1D(filters=64,kernel_size=7,strides=1,padding="same",name="conv1D_w9",activation='relu')(x8) + x10 = MaxPooling1D(pool_size=2,strides=2,padding="valid",name="max_pool1d_w10")(x9) + x11 = Conv1D(filters=64,kernel_size=7,strides=1,padding="same",name="conv1D_w11",activation='relu')(x10) + x12 = MaxPooling1D(pool_size=2,strides=2,padding="valid",name="max_pool1d_w12")(x11) + x13 = Conv1D(filters=64,kernel_size=7,strides=1,padding="same",name="conv1D_w13",activation='relu')(x12) + x14 = MaxPooling1D(pool_size=2,strides=2,padding="valid",name="MaxPool1D_w14")(x13) + x15 = Flatten(name="flatten_w15")(x14) + x16 = Dense(128, activation="selu",name="dense_w16")(x15) + x18 = Dense(128, activation="selu",name="dense_w17")(x16) + outputs = Dense(24,activation="softmax",name="dense_w18")(x18) + model = keras.Model(inputs=inputs,outputs=outputs) + optimizer = keras.optimizers.RMSprop(learning_rate=0.0005) + model.compile(optimizer=optimizer, + loss="categorical_crossentropy", + metrics=["accuracy"]) +``` + +The network contains eighteen layers: + +* The first layer is a 1D convolutional layer with two input nodes (corresponding to I and Q paths) and 64 compute nodes with a kernel_size=7. Correspondingly, the number multiplicative weights is 64 x 7 x 2 = 896 and the number of additive biases = 64. The number of input I/Q samples is 1024, corresponding to the incoming frame size. The number of output samples is 1024 x 64. +* The second layer implements a 1D max-pooling layer that performs a decimation-by-two in the samples dimension. There are no weights associated with this layer. All the remaining max-pooling layers perform similar functionality. +* The third layer implements another 1D convolutional layer with 64 input and compute nodes with a kernel_size=7 and applying a ReLU activation function at its output. This layer involves a total of 64 x 64 x 7 = 28,672 multiplicative weights and 64 additive biases weights. All the remaining 1D convolutional layer perform similar functionality. +* The fifteenth layer performs a flattening function, collapsing the total of 8 x 64 = 512 connections into a single 1D bus. +* The sixteenth layer consists of a fully connected dense network of 512 x 128 = 65,536 multiplicative weights and 128 additive biases and applies a SeLU activation function at its output. +* The seventeenth layer consists of a fully connected dense network of 128 x 128 = 16,384 multiplicative weights and 128 additive biases and applies a SeLU activation function at its output. +* The eighteenth layer consists of a fully connected dense network of 128 x 24 = 3,072 multiplicative weights and 128 additive biases and applies a softmax activation function at its output. + +The total number of parameters for this network is 258,648. The following diagram summarizes the layers of the Radio-ML ConvNet. + +![figure](images/radio-ml-convnet-layers.png) + +### Import the Radio-ML Database + +You must train the Radio-ML ConvNet modulation classifier on the Radio-ML database. This database contains 24 modulation types, each with 26 Signal-to-Noise Ratio (SNR) levels, each with 4k frames, each containing 1024 I/Q samples. + +``` +data_file = os.environ["RADIOML_DATA"] + 'GOLD_XYZ_OSC.0001_1024.hdf5' +file_handle = h5.File(data_file,'r') + +myData = file_handle['X'][:] #1024x2 samples +myMods = file_handle['Y'][:] #mods +mySNRs = file_handle['Z'][:] #snrs + +modulation_classes = json.load(open(os.environ["RADIOML_DATA"] + "classes-fixed.json", 'r')) +``` + +Examine the dataset by plotting a few samples for all modulation types at the highest SNR. + +![figure](images/modulation_timedomain.png) + +### Split the Training and Testing Data + +The dataset is split into training and testing data using scikit-learn's [train_test_split](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html) using a ratio of 20% of the dataset for testing. + +![figure](images/split_train_test.png) + +### Training the Model + +The Keras framework provides built-in functions for training and testing the model. Here, an EarlyStopping callback is used. This stops the training when the monitored metric stops improving for five epochs. + +``` +callback = keras.callbacks.EarlyStopping(monitor='val_loss', + restore_best_weights=True, + patience=10) + +history = model.fit(X_train,Y_train,epochs=100,validation_data=(X_test, Y_test),batch_size=1024,callbacks=[callback]) +``` + +The following plots show the accuracy and the loss of the model against the training versus test data. + +![figure](images/training_accuracy.png) + +![figure](images/training_loss.png) + +### Using the Radio-ML ConvNet Modulation Classifier for Inference + +You can use another built-in Keras routine for inference to predict new model outputs from test input images. The following code finds the accuracy of the model against each of the input SNR levels available in the dataset. + +``` +snrlist = np.unique(Z_test) +acc_arr = [] + +# iterate over SNRs +for snr in snrlist: + i_SNR = np.where(Z_test==snr) + X_SNR = X_test[i_SNR[0],:,:] + Y_SNR = Y_test[i_SNR[0],:] + X_SNR_len = np.shape(X_SNR)[0] + + # model prediction + pred = model.predict(X_SNR) + + #Pediction values are onehot, corresponding to indices representing different modulation types + pred_ind = np.argmax(pred, axis=1) + expected_ind = np.argmax(Y_SNR, axis=1) + matches = sum(np.equal(pred_ind, expected_ind)) + acc = matches/X_SNR_len + acc_arr.append(acc) +``` + +The following figure is a plot of the SNR vs Correct Classification probability. + +![figure](images/SNR_Accuracy.png) + +You can use the following code to generate a plot of the [Confusion Matrix](https://en.wikipedia.org/wiki/Confusion_matrix) for the classifier across all 24 modulation classes for frames where the SNR is greater than or equal to zero. + +``` +X_test_SNR = X_test[(Z_test>=0)[:,0],:,:] +Y_test_SNR = Y_test[(Z_test>=0)[:,0],:] + +test_Y_hat = model.predict(X_test_SNR, batch_size=1024) +conf = np.zeros([24,24]) +confnorm = np.zeros([24,24]) +for i in range(0,X_test_SNR.shape[0]): + j = list(Y_test_SNR[i,:]).index(1) + k = int(np.argmax(test_Y_hat[i,:])) + conf[j,k] = conf[j,k] + 1 +for i in range(0,24): + confnorm[i,:] = conf[i,:] / np.sum(conf[i,:]) + +plot_confusion_matrix(confnorm, labels=modulation_classes) +``` + +![figure](images/confusion_matrix.png) + +### Extracting Weights and Biases for AIE-ML Inference Solution + +After obtaining a trained model for the Radio-ML ConvNet Modulation Classifier, the last step before building an inference solution on AIE-ML v2 is to obtain a quantized set of weights to be used by the implementation. + +For simplicity in this tutorial, a `bfloat16` implementation is chosen because quantization is straightforward. + +The following code extracts the weights and biases from the Keras model. Then, it quantizes them to `bfloat16`. It then saves them in files for validating each layer of the network to be designed in AIE-ML v2 below. + +![figure](images/extract_weights_biases.png) + +## AIE-ML v2 Inference Solution + +This section provides an overview of the final AIE-ML v2 design for the Radio-ML ConvNet Modulation Classifier. It includes a review of key principles that are leveraged across all the layers in the design. +Details for each individual layer are then given in [Individual Layer Designs](#individual-layer-designs) section. + +### Design Approach + +* The `bfloat16` data type is chosen for both layer I/O data and for weights and biases. This simplifies the quantization of trained network parameters. No special tools nor quantization strategies are required. +* No specific throughput target is chosen. +* The design partitions each network layer to its own AIE-ML v2 tile where feasible. This simplifies system partitioning and allows you to build a well-defined scope for each kernel. +* Memory tile pre/post zero-padding capability is leveraged for 1D convolutional layers to expand input tensor shapes to satisfy model requirements that use `padding="same"`. The model uses `kernel_size=7` which requires the input samples dimension to be pre-padded and post-padded with three zeros. +* Memory tile multi-dimensional addressing capabilities are leveraged to efficiently transfer I/O data for compute consumption with minimal core cycles being required for data shuffling or lane adjustments within the core. +* Compute workloads for 1D convolutional layers leverage the efficient `mac_4x8_8x8()` intrinsic for `bfloat16` data types to achieve a maximum efficiency of 256 MAC operations per cycle when feasible by a particular layer. +* Compute workloads leverage the less efficient `mac_elem_64()` intrinsic for `bfloat16` data types with a maximum efficiency of 64 MAC operations per cycle in cases where `mac_4x8_8x8()` is not feasible (for example in the `conv1d_w1()` layer which only receives data from two input nodes). +* Weights and biases are sent from the host at run-time as async RTPs and are stored in local tile memory. Larger ML networks with millions or billions of weights require streaming solutions based on memory tiles or DDR; such a complex solution is excessive for the small Radio-ML Modulation Classifier problem considered here where all weights may be stored easily within the array. +* Perfect functional bit-match against the Python model is not achieved. The main contributors to this are the dense layers; more details are discussed in the corresponding sections. A closer match can be achieved by building Python models aligning with the implementation then training those to extract updated weights/biases. + +### Key Design Concepts + +* Storage requirements for I/O data for some layers may exceed the available 64KB in the local tile memory. Therefore, splitting of the consumed input or produced output data into chunks is required. This has a direct impact on the nature of processing. +* If the input and output data fit into the memory tile but do not fit into the local tile memory, processing must be split into `NSPLIT` chunks such that local tile storage does not exceed 64 KB. Both input and output buffers must be split by the same factor in the local tile. Processing may then be scheduled for the layer as a multi-rate solution with a `repetition_count=1` on the memory tile and a `repetition_count=NSPLIT` on the kernel. For the Radio-ML design, this concept is used in `conv1d_w3-w7` layers as well as `max_pool1d_w4-w6`. To motivate this, consider `conv1d_w3` in more details. The block has (64,512) bfloat16 samples on the I/Os. Assuming ping-pong buffering and zero insertion, the input requires storage size of at least **64 nodes x (512 samples + 3 pre-pad zeros + 3 post-pad zeros ) x 2 ping-pong x 2 bytes/sample = 129.5 KB**, which is 2.03x larger than local tile. This motivates the need for splitting the processing over at least NSPLIT>2 chunks. For `conv1d_w3`, choose NSPLIT=8 to fit both I/Os into local tile. The following diagram illustrates this concept. + + ![figure](images/conv1d_w3_split_IO.png) +* The multi-rate solution with buffer splitting outlined above does not work if one of the buffers, input or output, does not require splitting. In this case, the multi-rate scheduling applies only to the buffer that is split. The buffer that is not split must use a `repetition_count=1`. But AIE kernel multi-rate scheduling forces both input and output scheduling to use the same factor. Instead, this can be solved using the asynchronous buffer mechanism on the buffer that requires splitting. + + Consider the case with output splitting. The kernel can be implemented using `output_async_buffer`, enabling the split of the output_buffer by `NSPLIT` factor. At the beginning of kernel execution, the locks for ping side of the output buffer are acquired. Once 1/NSPLIT of the output data are produced, the kernel releases the lock on the ping side and acquires it on the pong, then continues processing etc. For more information on asynchronous buffer ports, refer to [Asynchronous Buffer Port Access (UG1603)](https://docs.amd.com/r/en-US/ug1079-ai-engine-kernel-coding/Asynchronous-Buffer-Port-Access). For the Radio-ML design, this concept is used in `conv1d_w1` layer. To motivate this, consider `conv1d_w1` in more details. The block has (2,1024) bfloat16 samples on the input and (64,1024) on the output. The input requires ~8.04 KB of storage (accounting for zero-insertion and ping-pong storage) while the output requires 256 KB. Therefore, it requires **NSPLIT = 128 KB x 2 / 64 KB = 4**. The following diagram illustrates the dataflow. + + ![figure](images/conv1d_w1_split_output.png) +* For layers with compute, for example `conv1d_w1-w13`, the I/O data is a 2D matrix represented as (nodes,samples). + * Splitting the output: + * Splitting the output processing over the samples dimension requires the weights to be read multiple times. This is highlighted in the following figure: ![figure](images/split_output_samples.png) + * Splitting the output processing over the nodes dimension requires the input samples to be read multiple times. ![figure](images/split_output_nodes.png) + * For `conv1d_w1`, the output was split in the nodes dimension since the input samples could easily fit in the local tile and re-reading comes for "free." It could have been also possible to split the output in the nodes dimension, since the weights also fit in the local tile. + * For conv1d_w3-w7 layers, outputs were split in the samples dimension since the weights fit in the local tile memory (while the input does not) and re-reading comes for "free." + * Splitting the input: + * Splitting the input over the samples dimension requires explicit state history handling. This is highlighted in the following figure: + ![figure](images/split_input_samples.png) + * Splitting the input over the nodes dimension requires the storage of partial results. ![figure](images/split_input_nodes.png) + * The latter requires additional storage and results in an implementation that does not software pipeline efficiently. For the former, state history samples can either be stored in local tile or re-sent from the memory tile as needed. Re-sending the samples from the memory tile results in slight bandwidth expansion, but this is not an issue since conv1d_w3-w7 layers are not bandwidth-bound. + * Therefore, the choice for conv1d_w3-w7 is to split the input data in the samples dimension and use the memory tiles to send samples with overlap to model state history. conv1d_w1 input (as well as conv1d_w9-w13) does not need to be split since the local tile storage is sufficient to store all input samples. + * One Graph invocation of `radioml_top` is one inference based on 1024 complex I/Q incoming samples. This translates into the following per layer invocation. + + |Layer|Input Tensor Shape|Output Tensor Shape|Input storage req. local tile (KB)|Output storage req. local tile (KB)|Kernel invocation|Memory Tile invocation|Note| + |---|---|---|---|---|---|---|---| + |conv1d_w1|(2,1024)|(64,1024)|8|256|1|1|Split output nodes by NSPLIT=8, handeled inside kernel using async_output_buffer| + |max_pool1d_w2|(64,1024)|(64,512)|256|128|8|1|---| + |conv1d_w3|(64,512)|(64,512)|176|128|8|1|Split I/O over samples dimension| + |max_pool1d_w4|(64,512)|(64,256)|128|64|4|NA|---| + |conv1d_w5|(64,256)|(64,256)|88|64|4|1|Same note as conv1d_w3| + |max_pool1d_w6|(64,256)|(64,128)|64|32|2|NA|---| + |conv1d_w7|(64,128)|(64,128)|44|32|2|1|Same note as conv1d_w3| + |max_pool1d_w8|(64,128)|(64,64)|32|16|1|NA|---| + |conv1d_w9|(64,64)|(64,64)|17.5|16|1|1|NA| + |max_pool1d_w10|(64,64)|(64,32)|16|8|1|NA|---| + |conv1d_w11|(64,32)|(64,32)|9.5|8|1|1|NA| + |max_pool1d_w12|(64,32)|(64,16)|8|4|1|NA|---| + |conv1d_w13|(64,16)|(64,16)|5.5|4|1|1|NA| + |max_pool1d_w14|(64,16)|(64,8)|4|2|1|NA|---| + |dense_w16|(512)|(128)|2|0.5|1|NA|---| + |dense_w17|(128)|(128)|0.5|0.5|1|NA|---| + |dense_w18|(128)|(24)|0.5|0.1|1|NA|---| + +### Radio-ML ConvNet: AI Engine Graph View + +The overall AI Engine graph of the Radio-ML ConvNet Modulation Classifier is shown in the following diagram. + +![figure](images/radio-ml-aie-graph.png) + +### Radio-ML ConvNet: AI Engine Floorplan View + +The floorplan view of the Radio-ML ConvNet Modulation Classifier is shown in the following diagram. + +Placement constraints were added place the compute tiles in the top row of tiles and the weight delivery tiles in the lower row of tiles. The design uses memory tiles for layer I/O ordering and zero padding as outlined below. + +![figure](images/radio-ml-aie-array.png) + +### Radio-ML ConvNet: AI Engine Resource Utilization + +The resource utilization of the design is given in the following figure. The design fits into a 4 x 6 grid of tiles and utilizes eight memory tiles for shared buffers. + +![figure](images/radio-ml-aie-resources.png) + +### Radio-ML ConvNet: Throughput + +From the following figure, you can calculate what the throughput is based on AI Engine simulations. Eight inferences are ran in 532.8us, which translate to ~15,000 inferences per second. + +![figure](images/radio-ml-throughput.png) + +### Radio-ML ConvNet: Latency + +The latency of the Radio-ML ConvNet Modulation Classifier is approximately 466us based on AI Engine simulations. + +![figure](images/radio-ml-latency.png) + +## Individual Layer Designs + +### Layer Design Details: `conv1d_w1()` + +The following figure summarizes the key aspects of the design of the `conv1d_w1()` layer. The Jupyter Notebook used for validation is [gen_vectors.ipynb](aie/conv1d_w1/gen_vectors.ipynb). + +* An input memory tile is used to pre/post zero pad the input tensor to satisfy model requirements that use `padding="same"`. The layer of interest uses `kerne_size=7` which requires the incoming 1024 I/Q samples to be pre-padded with three zeros and post-padded with three zeros. +To guarantee kernel input size is a multiple of 16 bytes, it was chosen to pre-pad with 4 zeros and post-pad with 4 zeros. +* Incoming (samples,nodes) dimension becomes flipped on the output due to nature of compute. This will be recovered in max_pool1d_w2 layer. +* The layer input data fits in the local tile memory, but the output is expanded to 64x1024 bfloat16 samples corresponding to 256KB (assuming double buffering), which is larger than the local tile memory of 64KB. Splitting the output data impacts the nature of processing, as described earlier in [Key Design Concepts](#key-design-concepts). +* For this reason, the kernel was implemented using an `output_async_buffer`, enabling the split of the output_buffer by NSPLIT=4. +* Because this layer has only two input nodes, the `mac_elem_64()` intrinsic is used which drops the maximum achievable hardware utilization to 25%. +* The inner loop has KERNEL_SIZE=7 iterations and is fully unrolled. The next inner loop achieves II=57 with 7x2 MAC operations. +* The overall kernel structure employs an outer loop over the nodes dimension, an inner loop over samples dimension and the most inner loop over kernel_size dimension. This is a good fit for the chosen intrinsic. +* Notice how the tiling parameters of the memory tile are used to pre/post-pad the input samples dimension with 4 zeros. + +![figure](images/design-details-layer1.png) + +### Layer Design Details: `max_pool1d_w2()` + +The following figure summarizes the key aspects of the design of the `max_pool1d_w2()` layer. The Jupyter Notebook used for validation is [gen_vectors.ipynb](aie/max_pool1d_w2/gen_vectors.ipynb). + +* The `max_pool1d_w2` I/O storage requirements exceed the available 64KB in the local tile. Splitting the I/O data processing impacts the nature of processing, as described earlier in [Key Design Concepts](#key-design-concepts). +* For this reason, `max_pool1d_w2` is set up as a multi-rate solution with a `repetition_count=1` on the memory tile and a `repetition_count=4` on the compute kernel. This reduces the storage requirements in the local tile, which would otherwise exceed the available 64KB. +* Max pooling decimates the input samples dimension by a factor of 2 by applying a `max()` operation across two consecutive samples. Successive samples are strided by 2, so they are non-overlapping. This compute workload may be vectorized efficiently using the `aie::max()` function of the AIE API. +* 2D Matrix Transpose achieved leveraging the kernel `aie::interleave_zip` + Memory Tiles performing a partial transpose. Full 2D Transpose using Memory Tiles is not possible since the data is 16-bits and storage is aligned to 32-bit boundary. For more information, refer to [2D Matrix Transpose Using Tiling Parameters (UG1603)](https://docs.amd.com/r/en-US/ug1603-ai-engine-ml-kernel-graph/2D-Matrix-Transpose-Using-Tiling-Parameters) +* The layer is coded as an outer loop over the nodes dimension and an inner loop over the samples dimension. Vectorization and software pipelining of the inner loop creates 64 output samples with an II=8 (bandwidth-bound). + +![figure](images/design-details-layer2.png) + +![figure](images/key-operations-layer2.png) + +### Layer Design Details: `conv1d_w3()` + +The following figure summarizes the key aspects of the design of the `conv1d_w3()` layer. The Jupyter Notebook used for validation is [gen_vectors.ipynb](aie/conv1d_template/gen_vectors.ipynb). + +* The design approach described here is common for the remaining conv1d layers. This is achieved by building a templatized kernel where the samples dimension can be varied as needed from a maximum of 512 down to 16. +* The `conv1d_w3` is set up as a multi-rate solution with a `repetition_count=1` on the memory tile and a `repetition_count=8` on the compute kernel. This reduces the storage requirements of the kernel in the local tile. +* There are (7x64x64) bfloat16 weights that need to be stored, which have a total storage requirement of 56KB (assuming single_buffer). The weights are initialized from the host at run-time during initialization. +* The required storage for I/O buffers for conv1d_w3 (512,64) = 256KB (assuming double-buffering). This is larger than the available storage in local tile. The kernel splits I/O processing over NSPLIT chunks, with the kernel invocated NSPLIT times per graph iteration. This is accomplished by setting up `conv1d_w3` as a multi-rate solution with a `repetition_count=1` on the memory tile and a `repetition_count=8` on the compute kernel, hence reducing the storage requirements of the kernel in the local tile. +* Splitting the I/O data impacts the nature of processing, as described earlier in [Key Design Concepts](#key-design-concepts). The input and output data processing is split in the samples dimension. +* The input memory tile writes samples in linear order, consuming the input tensors of shape `{512,64}` in order from the rightmost dimension first (as in the Numpy convention). Samples are extracted from the input memory tile in a tiled fashion. Within each tile, access reads `dim=0` first, followed by `dim=1`, hence defining the `buffer_dimension` as `{64,512}`. The `tiling_dimension` is defined as `{8,22}`, since 22 input samples are needed to produce `{8,16}` valid output samples. The input tile traverses down the nodes then right across the samples, with a stride of 16, providing 6 samples overlap for state history. The Keras/TF model uses `padding="same"`, which pre/post-pads the input samples such that the output dimension is the same as the input. The memory tile achieves this functionality via `offset` = `{0,-3}`. +* The weights `{7,64,64}` corresponding to `{KERNEL_SIZE,inputs,outputs}` require 56KB of storage (assuming single_buffer) which is < 64KB. Since the weights do not need to be updated often, they can be initialized from host as `async_rtp` and stored in local tile. Weights arrive from host in order to be consumed as `{1,8,8}`, traveling `dim=0` followed by `dim=1` then `dim=2`. The sampels within the patch arrive in order from the rightmost dimension first (as in the Numpy convention). +* The incoming `{8,22}` patch gets captured into 6 x 32-lane registers, where the inner dimension of the patch gets access first, followed by the outer dimension. Each register stores the samples in row-based fashion, so `{4,8}` corresponds to four samples and eight nodes. Four `aie::accum` registers are operating concurrently, each producing 4 of the 16 output samples across 8 output nodes. The kernel achieves an `II=43` for the inner unrolled loop which contains 28 `mac_4x8_8x8()` instructions which corresponds to a vector load = 60%. +* The 4x`{4,8}` row-based output registers gets written into `{8,16}` memory tile patch, writing into inner-dimension first. The patch travels down the nodes then right across the samples. + +![figure](images/design-details-layer3.png) + +![figure](images/input-handling-layer3.png) + +![figure](images/weights-handling-layer3.png) + +![figure](images/compute-handling-layer3.png) + +![figure](images/output-handling-layer3.png) + +### Layer Design Details: `max_pool1d_w4()` + +* The design approach described here is common for the remaining max_pool1d layers. This is achieved by building a templatized kernel where the samples dimension can be varied as needed from a maximum of 512 down to 16. +* The `max_pool1d_w4` I/O storage requirements exceed the available 64KB in the local tile. Splitting the I/O data processing impacts the nature of processing, as described earlier in [Key Design Concepts](#key-design-concepts). +* For this reason, `max_pool1d_w4` is set up as a multi-rate solution with a `repetition_count=2` on the compute kernel. This reduces the storage requirements of the kernel in the local tile. +* Max pooling decimates the input samples dimension by a factor of 2 by applying a `max()` operation across two consecutive samples. Successive samples are strided by 2, so they are non-overlapping. This compute workload may be vectorized efficiently using the `aie::max()` function of the AIE API. +* The layer is coded as a loop capturing 2 consecutive samples from 64 nodes and using `aie::max` API to perform a lane-by-lane `max` function to extract the maximum of the 2 samples across the 64 nodes. Vectorization and software pipelining of the loop creates 64 output samples with an II=4 (bandwidth-bound). + +![figure](images/design-details-layer4.png) + +### Layer Approach: `flatten()` + +![figure](images/flatten-layer.png) + +### Layer Design Approach: `dense()` + +![figure](images/design-approach-dense.png) + +### Layer Design Details: `dense_w16()` + +The following figure summarizes the key aspects of the design of the `dense_w16()` layer. The Jupyter Notebook used for validation is [gen_vectors.ipynb](aie/dense_w16/gen_vectors.ipynb). This tile includes two functions, the `dense_w16()` layer and a final `selu()` computation. The layer uses the `mac_elem_64()` intrinsic to compute outputs leveraging method b. described above. + +![figure](images/design-details-dense1.png) + +### Layer Design Details: `dense_w17()` + +The following figure summarizes the key aspects of the design of the `dense_w17()` layer. The Jupyter Notebook used for validation is [gen_vectors.ipynb](aie/dense_w17/gen_vectors.ipynb). This tile includes two functions, the `dense_w17()` layer and a final `selu()` computation. The layer uses the `mac_elem_64()` intrinsic to compute outputs leveraging method b. described above. + +![figure](images/design-details-dense2.png) + +### Layer Design Details: `dense_w18()` + +The following figure summarizes the key aspects of the design of the `dense_w18()` layer. The Jupyter Notebook used for validation is [gen_vectors.ipynb](aie/dense_w18/gen_vectors.ipynb). This tile includes two functions, the `dense_w18()` layer and a final `softmax()` computation. The `softmax()` activation function is computed using the approach outlined in the [Softmax Function Vitis Tutorial](../../AIE-ML/Design_Tutorials/05-Softmax-Function/). The layer uses the `mac_elem_64()` intrinsic to compute outputs leveraging method a. described above. + +![figure](images/design-details-dense3.png) + +## Design Resources + +The following figure summarizes the AI Engine and PL resources required to implement the design in the VE3858 device on the VEK385 eval board. The design is using 17 AI Engine tiles for compute, placed in a 4x6 arrangement. Minimal PL resources are used since this is an AI Engine only design with data transfer happening from/to DDR over NoC. + +![figure](images/hardware-build.png) + +## Build and Run Design + +### Setup and Initialization + +IMPORTANT: Before beginning the tutorial, ensure you have: +* Installed AMD Vitis™ 2025.2 software and set `PLATFORM_REPO_PATHS` to the value `/base_platforms`. +* Created directory `/yocto_artifacts` and set environment variable YOCTO_ARTIFACTS to that path. +* From [Embedded Development Framework (EDF) downloads page](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-design-tools.html) package 25.11: + * Downloaded amd-cortexa78-mali-common_meta-edf-app-sdk, run the script and set path output to `/yocto_artifacts/amd-cortexa78-mali-common_meta-edf-app-sdk/sdk`. + * Downloaded VEK385 OSPI Image and move into `/yocto_artifacts/`. + * Downloaded amd-cortexa78-mali-common_edf-linux-disk-image (SD wic), unzip and move into `/yocto_artifacts/`. + * Downloaded amd-cortexa78-mali-common_vek385_qemu_prebuilt, unzip and move `amd-cortexa78-mali-common_vek385_qemu_prebuilt` into `/yocto_artifacts/`. + +### Hardware Emulation + +The Radio-ML ConvNet Modulation Classifier design can be built for for hardware emulation using the Makefile as follows: + +``` +[shell]% cd +[shell]% make all TARGET=hw_emu +[shell]% make run_emu -C vitis TARGET=hw_emu +``` + +This takes about 90 minutes to run. The build process generates a folder `package` containing all the files required for hardware emulation. Hardware emulation is then launched and run producing outputs shown below. An optional `-g` can be applied to the `launch_hw_emu.sh` command to launch Vivado waveform GUI to observe the top-level AXI signal ports in the design. This is done by editing [vitis/Makefile](vitis/Makefile) `run_emu` target. + +![figure](images/hw-emu.png) + +### Hardware + +You can build this design for the VEK385 board using the Makefile as follows: + +``` +[shell]% cd +[shell]% make all TARGET=hw +``` + +The build process generates all the design specific files needed to run the design on hardware in the `package` folder. + +1. Write the EDF boot firmware (OSPI) to the primary boot device following instructions [here](https://xilinx-wiki.atlassian.net/wiki/spaces/A/pages/3258155011/AMD+EDF+Getting+started+-+Discovery+and+Evaluation+AMD+Versal+device+portfolio#Writing-the-EDF-boot-firmware-to-the-primary-boot-device-%2F-media-using-System-Controller-(SC)). OSPI image can be found in `/yocto_artifacts/edf-ospi-versal-2ve-2vm-vek385-sdt-seg-20251116021631.bin`. +2. Write `/yocto_artifacts/edf-linux-disk-image-amd-cortexa78-mali-common.rootfs-20251116015456.wic` to sd_card using your favorite SD imaging tool (Balena Etcher and Win32DiskImager seem to work well). +3. Put the sd_card in to the board, boot it and log in. (default username is amd-edf and you will be promted to set a password) +4. Determine the IP address eth0 on the board with `ip addr show eth0`. +5. cd `/package; scp * amd-edf@:~/` +6. Run the design: `sudo ./embedded_exec.sh` + +The following is displayed on the terminal. + +![figure](images/hardware-run.png) + +## Summary + +This tutorial has presented the design of a Radio-ML ConvNet Modulation Classifier in AIE-ML v2. The solution has 258,648 parameters and requires ~20 tiles. It achieves a throughput of ~15K inferences per second with a latency of ~466 us. + +## References + +[1]: "Over-the-Air Deep Learning Based Radio Signal Classification, T. J. O’Shea, T. Roy and T. C. Clancy" +[[1]] T. J. O’Shea, T. Roy and T. C. Clancy, "[Over-the-Air Deep Learning Based Radio Signal Classification](https://ieeexplore.ieee.org/document/8267032)" in IEEE Journal of Selected Topics in Signal Processing, vol. 12, no. 1, pp. 168-179, Feb. 2018 + +[2]: +[[2]]: DeepSig Dataset 2018.01A: https://www.kaggle.com/datasets/pinxau1000/radioml2018 + +[3]: "Confusion Matrix" + +[[3]] Wikipedia, "[Confusion Matrix](https://en.wikipedia.org/wiki/Confusion_matrix)" + +## Support + +GitHub issues are used for tracking requests and bugs. For questions, go to [support.xilinx.com](http://support.xilinx.com/). + +## License + +

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diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/Makefile b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/Makefile new file mode 100755 index 0000000000..a899fb8d35 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/Makefile @@ -0,0 +1,68 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +MY_APP := conv1d_w3_app +MY_SOURCES := ${MY_APP}.cpp conv1d_graph_template.h conv1d_template.h conv1d_template.cpp + +PART ?= xc2ve3858-ssva2112-2MP-e-S + +AIE_OUTPUT := libadf.a + +AIE_FLAGS := --part=${PART} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} --include=../utility + +.PHONY: help clean x86com x86sim sim profile throughput + +help:: + @echo "Makefile Usage:" + @echo " make all" + @echo " Command to generate everything for this design" + @echo "" + @echo " make compile" + @echo " Run AIE compiler and build the design" + @echo "" + @echo " make profile" + @echo " Run AIE simulator with profiling and generate outputs suitable for Vitis Analyzer" + @echo "" + @echo " make analyze" + @echo " Run Vitis Analyzer to inspect results" + @echo "" + @echo " make throughput" + @echo " Evaluate the achieved throughput at the output" + @echo "" + @echo " make clean" + @echo " Command to remove all the generated files." + +all: ${AIE_OUTPUT} + +x86all: clean x86com x86sim + +${AIE_OUTPUT}: ${MY_SOURCES} + v++ --compile --config aie.cfg --mode aie --target=hw ${AIE_FLAGS} 2>&1 | tee log + +x86com: + v++ --compile --config aie.cfg --mode aie --target=x86sim ${AIE_FLAGS} 2>&1 | tee log + +sim: + aiesimulator 2>&1 | tee -a log + +x86sim: + x86simulator 2>&1 | tee -a log + +profile: + aiesimulator --online -wdb -text --profile 2>&1 | tee -a log + +trace: + aiesimulator --hang-detect-time=5000 --online -wdb -text 2>&1 | tee -a log + +clean: + rm -rf .Xil Work libadf.a + rm -rf aiesimulator_output* aiesimulator*.log + rm -rf x86simulator_output* + rm -rf log log* + rm -rf *.xpe *.elf *.db *.soln Map_* xnw* *.lp *.log .xil .Xil *.lp *.db *.log *.exe *.vcd *.json + rm -rf vitis_analyzer* pl_sample_counts* pl_sample_count_* + rm -rf temp ISS_RPC_SERVER_PORT .crashReporter .AIE_SIM_CMD_LINE_OPTIONS + rm -rf system*.* trdata.aiesim function_wdb_dir .wsdata _ide vfs_work .ipynb_checkpoints diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/aie.cfg b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/aie.cfg new file mode 100755 index 0000000000..83dee9bb25 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/aie.cfg @@ -0,0 +1,13 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +[aie] + +kernel-linting=true +xlopt=1 +verbose=true +pl-freq=625 +Xmapper=BufferOptLevel9 \ No newline at end of file diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/conv1d_graph_template.h b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/conv1d_graph_template.h new file mode 100755 index 0000000000..31d95be12d --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/conv1d_graph_template.h @@ -0,0 +1,105 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#pragma once + +#include +#include "conv1d_template.h" +#include "next_pow_2_constexpr.h" +#include "ceil_constexpr.h" + +using namespace adf; + +// ------------------------------------------------------------ +// Top Level Graph +// ------------------------------------------------------------ + +// NSAMP is number of samples from each node, assumed to be a multiple of 8 and 16 <= NSAMP <= 512 +// NNODES is number nodes, assumed to be equal to 64. +// KERNEL_SIZE is the number of weights per node, assumed to be 7 + +template +class conv1d_graph_template : public graph { +public: + // Declare Kernels + kernel kk; + + // Declare IOs + port data_i; + port weights; + port biases; + port data_o; + + static constexpr unsigned NWEIGHTS = NNODES*NNODES*KERNEL_SIZE; // Number of weights, dependent on NNODES and KERNEL_SIZE + static constexpr unsigned NBIASES = NNODES; // Number of biases, dependent on NNODES + static constexpr int NZERO_PAD = (KERNEL_SIZE-1)/2; // pre/post pad input buffer so output has same NSAMP as input. KERNEL_SIZE assumed to be odd. + + static constexpr double BUFFER_SIZE_MULTIPLE = NSAMP*NNODES*22/16*2*2*2.0/65536; // Ratio of IO buffer size to local tile memory + // 22/16 -> Bandwidth and kernel input buffer grows by a factor of 22/16 due to nature of processing. + // *2 -> 2 bytes per sample + // *2 -> ping-pong + // *2 -> Margin to ensure input buffer uses only two banks (same applies for output buffer) + // 65536 -> Local tile memory (64KB) + static constexpr unsigned NSPLIT = (BUFFER_SIZE_MULTIPLE>1) ? + next_pow_2_constexpr(BUFFER_SIZE_MULTIPLE) : + ceil_constexpr(BUFFER_SIZE_MULTIPLE); + // Process incoming samples in NSPLIT chunks so IO buffers fit in local tile memory. + // Return type of ceil in c++17 is not constexpr + + // Declare memory tiles + shared_buffer MT_input; + shared_buffer MT_output; + + conv1d_graph_template( void ) + { + // Tiling parameters for inputs + tiling_parameters bdw_input = { .buffer_dimension = {NNODES*NSAMP}, + .tiling_dimension = {NNODES*NSAMP}, + .offset = {0} }; + tiling_parameters bdr_input = { .buffer_dimension = {NNODES ,NSAMP}, + .tiling_dimension = {8,22}, + .offset = {0,-NZERO_PAD}, + .tile_traversal = {{.dimension=0, .stride=8,.wrap=NNODES/8}, + {.dimension=1, .stride=16,.wrap=NSAMP/16}} + }; + MT_input = shared_buffer::create({NSAMP*NNODES}, 1, 1); + write_access(MT_input.in[0]) = tiling(bdw_input); + read_access(MT_input.out[0]) = tiling(bdr_input); + repetition_count(MT_input) = 1; + + // Tiling parameters for outputs + tiling_parameters bdw_output = { .buffer_dimension = {NNODES,NSAMP}, + .tiling_dimension = {8,16}, + .offset = {0,0}, + .tile_traversal = {{.dimension=0, .stride=8, .wrap=NNODES/8}, + {.dimension=1, .stride=16, .wrap=NSAMP/16}} + }; + tiling_parameters bdr_output = { .buffer_dimension = {NNODES*NSAMP}, + .tiling_dimension = {NNODES*NSAMP}, + .offset = {0} }; + MT_output = shared_buffer::create({NNODES*NSAMP}, 1, 1); + write_access(MT_output.in[0]) = tiling(bdw_output); + read_access(MT_output.out[0]) = tiling(bdr_output); + repetition_count(MT_output) = 1; + + kk = kernel::create_object>(); + source(kk) = "conv1d_template.cpp"; + runtime(kk) = 0.9; + repetition_count(kk) = NSPLIT; + + connect<> ( data_i, MT_input.in[0] ); + connect<> ( MT_input.out[0], kk.in[0] ); dimensions(kk.in[0]) = {NNODES*NSAMP/NSPLIT*22/16}; + connect ( weights, async(kk.in[1]) ); + connect ( biases, async(kk.in[2]) ); + connect<> ( kk.out[0], MT_output.in[0] ); + connect<> ( MT_output.out[0], data_o ); dimensions(kk.out[0]) = {NNODES*NSAMP/NSPLIT}; + + single_buffer(kk.in[1]); + single_buffer(kk.in[2]); + + } +}; + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/conv1d_template.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/conv1d_template.cpp new file mode 100755 index 0000000000..452a2484f7 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/conv1d_template.cpp @@ -0,0 +1,152 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#include +#include + +#include "conv1d_template.h" + + +// ------------------------------------------------------------ +// Constructor +// ------------------------------------------------------------ + +template +conv1d_template::conv1d_template(void) +{ + aie::set_rounding(aie::rounding_mode::symmetric_inf); + aie::set_saturation(aie::saturation_mode::saturate); +} + +// ------------------------------------------------------------ +// Run +// ------------------------------------------------------------ + +template +void conv1d_template::run( input_buffer& __restrict data_i, + const TT_DATA (&weights)[NWEIGHTS], + const TT_DATA (&biases)[NNODES], + output_buffer& __restrict data_o) +{ + auto p_data_o = aie::begin_restrict_vector<32>(data_o); + + aie::vector data_reg0; + aie::vector data_reg1; + aie::vector data_reg2; + aie::vector data_reg3; + aie::vector data_patch_reg0; + aie::vector data_patch_reg1; + aie::vector data_patch_reg2; + aie::vector data_patch_reg3; + aie::vector data_patch_reg4; + aie::vector data_patch_reg5; + aie::accum acc_reg0; + aie::accum acc_reg1; + aie::accum acc_reg2; + aie::accum acc_reg3; + aie::vector weights_reg; + aie::vector bias_reg; + aie::accum bias_acc; + + + auto p_biases = aie::begin_restrict_vector<8>(biases); + unsigned index_offset; + auto p_weights = aie::begin_restrict_vector<64>(weights); + + // Loop over some samples and output nodes: + for ( unsigned iter=0,ii=0; iter < NSAMP/16/NSPLIT*NNODES/8; iter++) + { + index_offset=1408*ii; // 1408=8*22*8 + auto p_data0 = aie::begin_restrict_vector<32>(data_i.data()+index_offset ); // Input nodes 0-7, 16-23, 32-39, 48-55 + auto p_data1 = aie::begin_restrict_vector<32>(data_i.data()+index_offset+176-16 ); // Input nodes 8-15, 24-31, 40-47, 56-63 + // 176=8*22. Subtracting 16 allows doing an aligned read. We add this 16 offset later when doing shuffle_down_fill + + acc_reg0 = aie::zeros(); + acc_reg1 = aie::zeros(); + acc_reg2 = aie::zeros(); + acc_reg3 = aie::zeros(); + // Loop over input nodes 0-7, 16-23, 32-39, 48-55 + for ( unsigned kk=0; kk < NNODES/8/2; kk++) + chess_loop_range(NNODES/8/2,) + chess_prepare_for_pipelining + { + data_patch_reg0 = *p_data0++; + data_patch_reg1 = *p_data0++; + data_patch_reg2 = *p_data0++; + data_patch_reg3 = *p_data0++; + data_patch_reg4 = *p_data0++; + data_patch_reg5 = *p_data0++; + // weight0 + COMPUTE_PATTERN(data_patch_reg0,data_patch_reg1,data_patch_reg2,data_patch_reg3,data_patch_reg4,0) + // weight1 + COMPUTE_PATTERN(data_patch_reg0,data_patch_reg1,data_patch_reg2,data_patch_reg3,data_patch_reg4,8) + // weight2 + COMPUTE_PATTERN(data_patch_reg0,data_patch_reg1,data_patch_reg2,data_patch_reg3,data_patch_reg4,16) + // weight3 + COMPUTE_PATTERN(data_patch_reg0,data_patch_reg1,data_patch_reg2,data_patch_reg3,data_patch_reg4,24) + // weight4 + COMPUTE_PATTERN(data_patch_reg0,data_patch_reg1,data_patch_reg2,data_patch_reg3,data_patch_reg4,32) + // weight5 + COMPUTE_PATTERN(data_patch_reg1,data_patch_reg2,data_patch_reg3,data_patch_reg4,data_patch_reg5,8) + // weight6 + COMPUTE_PATTERN(data_patch_reg1,data_patch_reg2,data_patch_reg3,data_patch_reg4,data_patch_reg5,16) + p_weights+=KERNEL_SIZE; + p_data0 += 5; + } + + p_weights -= (NNODES/8-1)*KERNEL_SIZE; + + // Loop over odd input nodes 8-15, 24-31, 40-47, 56-63 + for ( unsigned kk=0; kk < NNODES/8/2; kk++) + chess_loop_range(NNODES/8/2,) + chess_prepare_for_pipelining + { + data_patch_reg0 = *p_data1++; + data_patch_reg1 = *p_data1++; + data_patch_reg2 = *p_data1++; + data_patch_reg3 = *p_data1++; + data_patch_reg4 = *p_data1++; + data_patch_reg5 = *p_data1++; + // weight0 + COMPUTE_PATTERN(data_patch_reg0,data_patch_reg1,data_patch_reg2,data_patch_reg3,data_patch_reg4,16) + // weight1 + COMPUTE_PATTERN(data_patch_reg0,data_patch_reg1,data_patch_reg2,data_patch_reg3,data_patch_reg4,24) + // weight2 + COMPUTE_PATTERN(data_patch_reg0,data_patch_reg1,data_patch_reg2,data_patch_reg3,data_patch_reg4,32) + // weight3 + COMPUTE_PATTERN(data_patch_reg1,data_patch_reg2,data_patch_reg3,data_patch_reg4,data_patch_reg5,8) + // weight4 + COMPUTE_PATTERN(data_patch_reg1,data_patch_reg2,data_patch_reg3,data_patch_reg4,data_patch_reg5,16) + // weight5 + COMPUTE_PATTERN(data_patch_reg1,data_patch_reg2,data_patch_reg3,data_patch_reg4,data_patch_reg5,24) + // weight6 + COMPUTE_PATTERN(data_patch_reg1,data_patch_reg2,data_patch_reg3,data_patch_reg4,data_patch_reg5,32) + p_weights+=KERNEL_SIZE; + p_data1 += 5; + } + p_weights -= KERNEL_SIZE; + bias_reg = aie::concat(*p_biases,*p_biases,*p_biases,*p_biases);p_biases++; + bias_acc.from_vector(bias_reg); + + acc_reg0 = aie::add(acc_reg0,bias_acc); + *p_data_o++ = aie::max(acc_reg0.to_vector(),TT_DATA(0)); + + acc_reg1 = aie::add(acc_reg1,bias_acc); + *p_data_o++ = aie::max(acc_reg1.to_vector(),TT_DATA(0)); + + acc_reg2 = aie::add(acc_reg2,bias_acc); + *p_data_o++ = aie::max(acc_reg2.to_vector(),TT_DATA(0)); + + acc_reg3 = aie::add(acc_reg3,bias_acc); + *p_data_o++ = aie::max(acc_reg3.to_vector(),TT_DATA(0)); + if ( ((iter+1)%(NNODES/8))==0 ) + { + ii++; + p_weights = aie::begin_restrict_vector<64>(weights); + p_biases = aie::begin_restrict_vector<8>(biases); + } + } +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/conv1d_template.h b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/conv1d_template.h new file mode 100755 index 0000000000..d80077202a --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/conv1d_template.h @@ -0,0 +1,49 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#pragma once + +#include +#include + +using namespace adf; + +template +class conv1d_template { +public: + typedef bfloat16 TT_DATA; +private: + +public: + // Constructor: + conv1d_template( void ); + + // Run: + void run( input_buffer& __restrict data_i, + const TT_DATA (&weights)[NWEIGHTS], + const TT_DATA (&biases)[NNODES], + output_buffer& __restrict data_o); + + static void registerKernelClass( void ) + { + REGISTER_FUNCTION( conv1d_template::run ); + } +}; + +// ------------------------------------------------------------ +// Compute Patterns +// ------------------------------------------------------------ + +#define COMPUTE_PATTERN(DATA0,DATA1,DATA2,DATA3,DATA4,OFFSET) \ + weights_reg = *p_weights++; \ + data_reg0 = aie::shuffle_down_fill(DATA0,DATA1,OFFSET); \ + acc_reg0 = mac_4x8_8x8(data_reg0,weights_reg,acc_reg0); \ + data_reg1 = aie::shuffle_down_fill(DATA1,DATA2,OFFSET); \ + acc_reg1 = mac_4x8_8x8(data_reg1,weights_reg,acc_reg1); \ + data_reg2 = aie::shuffle_down_fill(DATA2,DATA3,OFFSET); \ + acc_reg2 = mac_4x8_8x8(data_reg2,weights_reg,acc_reg2); \ + data_reg3 = aie::shuffle_down_fill(DATA3,DATA4,OFFSET); \ + acc_reg3 = mac_4x8_8x8(data_reg3,weights_reg,acc_reg3); diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/conv1d_w11_app.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/conv1d_w11_app.cpp new file mode 100644 index 0000000000..ff81c8d1da --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/conv1d_w11_app.cpp @@ -0,0 +1,57 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#include +#include +#include "conv1d_graph_template.h" +#include "read_file.h" + +class dut_graph : public graph { + conv1d_graph_template<32,64,7> dut; // + // NSAMP is number of samples from each node + // NNODES is number nodes + // KERNEL_SIZE is the number of weights per node +public: + input_plio data_i; + port weights; + port biases; + output_plio data_o; + + dut_graph( void ) + { + data_i = input_plio::create("PLIO_i_0",plio_64_bits,"data/data_i.txt"); + connect(data_i.out[0],dut.data_i); + + connect<>(weights,dut.weights); + connect<>(biases,dut.biases); + + data_o = output_plio::create("PLIO_o_0",plio_64_bits,"data/data_o.txt"); + connect(dut.data_o,data_o.in[0]); + } +}; + +// Instantiate AIE graph: +dut_graph aie_dut; + +bfloat16 weights_array[conv1d_graph_template<32,64,7>::NWEIGHTS]; +bfloat16 biases_array[conv1d_graph_template<32,64,7>::NBIASES]; + +// Initialize and run the graph: +int main(void) +{ + aie_dut.init(); + + // Read layer RTPs + read_file::NWEIGHTS>("data/weights-rtp.txt",weights_array); + read_file::NBIASES> ("data/biases-rtp.txt", biases_array); + + aie_dut.update(aie_dut.weights,weights_array,conv1d_graph_template<32,64,7>::NWEIGHTS); + aie_dut.update(aie_dut.biases,biases_array,conv1d_graph_template<32,64,7>::NBIASES); + aie_dut.run(4); + aie_dut.end(); + + return 0; +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/conv1d_w13_app.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/conv1d_w13_app.cpp new file mode 100644 index 0000000000..0b14302644 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/conv1d_w13_app.cpp @@ -0,0 +1,57 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#include +#include +#include "conv1d_graph_template.h" +#include "read_file.h" + +class dut_graph : public graph { + conv1d_graph_template<16,64,7> dut; // + // NSAMP is number of samples from each node + // NNODES is number nodes + // KERNEL_SIZE is the number of weights per node +public: + input_plio data_i; + port weights; + port biases; + output_plio data_o; + + dut_graph( void ) + { + data_i = input_plio::create("PLIO_i_0",plio_64_bits,"data/data_i.txt"); + connect(data_i.out[0],dut.data_i); + + connect<>(weights,dut.weights); + connect<>(biases,dut.biases); + + data_o = output_plio::create("PLIO_o_0",plio_64_bits,"data/data_o.txt"); + connect(dut.data_o,data_o.in[0]); + } +}; + +// Instantiate AIE graph: +dut_graph aie_dut; + +bfloat16 weights_array[conv1d_graph_template<16,64,7>::NWEIGHTS]; +bfloat16 biases_array[conv1d_graph_template<16,64,7>::NBIASES]; + +// Initialize and run the graph: +int main(void) +{ + aie_dut.init(); + + // Read layer RTPs + read_file::NWEIGHTS>("data/weights-rtp.txt",weights_array); + read_file::NBIASES> ("data/biases-rtp.txt", biases_array); + + aie_dut.update(aie_dut.weights,weights_array,conv1d_graph_template<16,64,7>::NWEIGHTS); + aie_dut.update(aie_dut.biases,biases_array,conv1d_graph_template<16,64,7>::NBIASES); + aie_dut.run(4); + aie_dut.end(); + + return 0; +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/conv1d_w3_app.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/conv1d_w3_app.cpp new file mode 100755 index 0000000000..f2206e0061 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/conv1d_w3_app.cpp @@ -0,0 +1,57 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#include +#include +#include "conv1d_graph_template.h" +#include "read_file.h" + +class dut_graph : public graph { + conv1d_graph_template<512,64,7> dut; // + // NSAMP is number of samples from each node + // NNODES is number nodes + // KERNEL_SIZE is the number of weights per node +public: + input_plio data_i; + port weights; + port biases; + output_plio data_o; + + dut_graph( void ) + { + data_i = input_plio::create("PLIO_i_0",plio_64_bits,"data/data_i.txt"); + connect(data_i.out[0],dut.data_i); + + connect<>(weights,dut.weights); + connect<>(biases,dut.biases); + + data_o = output_plio::create("PLIO_o_0",plio_64_bits,"data/data_o.txt"); + connect(dut.data_o,data_o.in[0]); + } +}; + +// Instantiate AIE graph: +dut_graph aie_dut; + +bfloat16 weights_array[conv1d_graph_template<512,64,7>::NWEIGHTS]; +bfloat16 biases_array[conv1d_graph_template<512,64,7>::NBIASES]; + +// Initialize and run the graph: +int main(void) +{ + aie_dut.init(); + + // Read layer RTPs + read_file::NWEIGHTS>("data/weights-rtp.txt",weights_array); + read_file::NBIASES> ("data/biases-rtp.txt", biases_array); + + aie_dut.update(aie_dut.weights,weights_array,conv1d_graph_template<512,64,7>::NWEIGHTS); + aie_dut.update(aie_dut.biases,biases_array,conv1d_graph_template<512,64,7>::NBIASES); + aie_dut.run(4); + aie_dut.end(); + + return 0; +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/conv1d_w9_app.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/conv1d_w9_app.cpp new file mode 100644 index 0000000000..5dda701d7b --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/conv1d_w9_app.cpp @@ -0,0 +1,57 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#include +#include +#include "conv1d_graph_template.h" +#include "read_file.h" + +class dut_graph : public graph { + conv1d_graph_template<64,64,7> dut; // + // NSAMP is number of samples from each node + // NNODES is number nodes + // KERNEL_SIZE is the number of weights per node +public: + input_plio data_i; + port weights; + port biases; + output_plio data_o; + + dut_graph( void ) + { + data_i = input_plio::create("PLIO_i_0",plio_64_bits,"data/data_i.txt"); + connect(data_i.out[0],dut.data_i); + + connect<>(weights,dut.weights); + connect<>(biases,dut.biases); + + data_o = output_plio::create("PLIO_o_0",plio_64_bits,"data/data_o.txt"); + connect(dut.data_o,data_o.in[0]); + } +}; + +// Instantiate AIE graph: +dut_graph aie_dut; + +bfloat16 weights_array[conv1d_graph_template<64,64,7>::NWEIGHTS]; +bfloat16 biases_array[conv1d_graph_template<64,64,7>::NBIASES]; + +// Initialize and run the graph: +int main(void) +{ + aie_dut.init(); + + // Read layer RTPs + read_file::NWEIGHTS>("data/weights-rtp.txt",weights_array); + read_file::NBIASES> ("data/biases-rtp.txt", biases_array); + + aie_dut.update(aie_dut.weights,weights_array,conv1d_graph_template<64,64,7>::NWEIGHTS); + aie_dut.update(aie_dut.biases,biases_array,conv1d_graph_template<64,64,7>::NBIASES); + aie_dut.run(4); + aie_dut.end(); + + return 0; +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/data/biases-rtp.txt b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/data/biases-rtp.txt new file mode 100755 index 0000000000..acc3b425de --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/data/biases-rtp.txt @@ -0,0 +1,64 @@ +0.050537109375 +0.047607421875 +0.050048828125 +-0.173828125000 +-0.055175781250 +0.457031250000 +-0.235351562500 +0.016967773438 +-0.161132812500 +-0.024414062500 +-0.425781250000 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a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/gen_vectors.ipynb b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/gen_vectors.ipynb new file mode 100755 index 0000000000..9c42d143e6 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/gen_vectors.ipynb @@ -0,0 +1,557 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "bcdf2452-4c3b-4ce0-b019-cbe980967a1c", + "metadata": {}, + "source": [ + "# Testbench for `conv1d_w3()`" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "946f566a-c3f6-446f-aeb6-cb0055910900", + "metadata": {}, + "outputs": [], + "source": [ + "#\n", + "# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved.\n", + "# SPDX-License-Identifier: MIT\n", + "#\n", + "# Author: Faisal El-Shabani" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "934e0796-0306-4ce9-9a92-598027c75f38", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-08-22 07:48:05.472467: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-08-22 07:48:05.476422: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-08-22 07:48:05.485129: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", + "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n", + "E0000 00:00:1755870485.499031 2889419 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", + "E0000 00:00:1755870485.503346 2889419 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", + "W0000 00:00:1755870485.515298 2889419 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755870485.515310 2889419 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755870485.515313 2889419 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755870485.515316 2889419 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "2025-08-22 07:48:05.519729: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", + "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n" + ] + } + ], + "source": [ + "from tensorflow import keras\n", + "from tensorflow.keras.layers import Conv1D, MaxPooling1D\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.model_selection import train_test_split\n", + "import h5py as h5\n", + "import numpy as np\n", + "import os.path\n", + "import vfs\n", + "import varray as va\n", + "\n", + "NITERATIONS = 4 # Number of AI Engine graph iterations" + ] + }, + { + "cell_type": "markdown", + "id": "5bdc7e83-3fd0-4fd0-99b5-7938816f0df2", + "metadata": {}, + "source": [ + "## Layer Definition" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "0c57f98d-1999-4b61-a129-e3dd1bd92677", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-08-22 07:48:10.562951: E external/local_xla/xla/stream_executor/cuda/cuda_platform.cc:51] failed call to cuInit: INTERNAL: CUDA error: Failed call to cuInit: UNKNOWN ERROR (303)\n" + ] + } + ], + "source": [ + "inputs = keras.Input(shape=(1024,2),name=\"input\")\n", + "x1 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w1\",activation='relu')(inputs)\n", + "outputs = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w2\")(x1)\n", + "model_stim = keras.Model(inputs=inputs,outputs=outputs)\n", + "model_stim.compile(optimizer=\"rmsprop\",\n", + " loss=\"sparse_categorical_crossentropy\",\n", + " metrics=[\"accuracy\"])\n", + "w1_weights = np.loadtxt('../conv1d_w1/w1_weights_trained.txt')\n", + "w1_weights = (w1_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w1_weights = np.reshape(w1_weights,(7,2,64))\n", + "w1_bias = np.loadtxt('../conv1d_w1/w1_bias_trained.txt')\n", + "w1_bias = (w1_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "model_stim.set_weights((w1_weights,w1_bias))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "cd15a0ca-2889-4d90-bd0f-2e76c63c6c19", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
Model: \"functional\"\n",
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+       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
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+       "│ input (InputLayer)              │ (None, 1024, 2)        │             0 │\n",
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+       "│ conv1D_w1 (Conv1D)              │ (None, 1024, 64)       │           960 │\n",
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+       "│ max_pool1d_w2 (MaxPooling1D)    │ (None, 512, 64)        │             0 │\n",
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Model: \"functional_1\"\n",
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┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ input_layer (InputLayer)        │ (None, 512, 64)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w3 (Conv1D)              │ (None, 512, 64)        │        28,736 │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
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\n" + ], + "text/plain": [ + "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n", + "┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\n", + "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n", + "│ input_layer (\u001b[38;5;33mInputLayer\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w3 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "└─────────────────────────────────┴────────────────────────┴───────────────┘\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Total params: 28,736 (112.25 KB)\n",
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 Trainable params: 28,736 (112.25 KB)\n",
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+       "
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"file_handle = h5.File(data_file,'r')\n", + "myData = file_handle['X'][:] #1024x2 samples \n", + "myMods = file_handle['Y'][:] #mods \n", + "mySNRs = file_handle['Z'][:] #snrs \n", + "file_handle.close()\n", + "X_train ,X_predict ,Y_train ,Y_test, Z_train, Z_test =train_test_split(myData, myMods, mySNRs, test_size=0.2, random_state=0)\n", + "X_predict = X_predict[:NITERATIONS]\n", + "X_predict = (X_predict.astype(\"bfloat16\")).astype(\"float32\")\n", + "X_inputs = model_stim.predict(X_predict,batch_size=1024)\n", + "X_inputs = (X_inputs.astype(\"bfloat16\")).astype(\"float32\")" + ] + }, + { + "cell_type": "markdown", + "id": "53bf2899-8424-4f34-b305-dea322001c7c", + "metadata": {}, + "source": [ + "## Compute Golden Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "532b9d20-6698-420d-842a-b5c2ee89c114", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n" + ] + } + ], + "source": [ + "predict = model.predict(X_inputs, batch_size=1024)\n", + "predict = (predict.astype(\"bfloat16\")).astype(\"float32\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "b588f848-eb35-409a-94c0-9b9bf986383f", + "metadata": {}, + "source": [ + "## Store Layer Inputs" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "84a1f04f-7eca-4694-906f-245a9001fd25", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 512, 64)\n", + "(4, 512, 64)\n" + ] + } + ], + "source": [ + "# Create directory if it doesn't exist\n", + "data_i = X_inputs\n", + "if not os.path.exists('data'):\n", + " os.makedirs('data')\n", + "np.savetxt('data/data_i.txt',np.reshape(data_i,(-1,4)),fmt='%.12f %.12f %.12f %.12f')\n", + "print(X_inputs.shape)\n", + "print(data_i.shape)\n" + ] + }, + { + "cell_type": "markdown", + "id": "33ae9119-15e3-49ce-9ef8-ffab0c9ec411", + "metadata": {}, + "source": [ + "## Store Layer Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "de799f89-ecbe-4480-9dcf-3bb4e5402546", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 512, 64)\n" + ] + } + ], + "source": [ + "data_o = predict\n", + "\n", + "np.savetxt('data/data_o.txt',np.reshape(data_o,(-1,4)),fmt='%.12f %.12f %.12f %.12f')\n", + "print(data_o.shape)" + ] + }, + { + "cell_type": "markdown", + "id": "b1ad8cde", + "metadata": {}, + "source": [ + "## Store Model weights and biases" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "9b35d7ca", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(7, 64, 64)\n", + "(64,)\n", + "(28672, 1)\n", + "(64, 1)\n" + ] + } + ], + "source": [ + "print(w3_weights.shape)\n", + "print(w3_bias.shape)\n", + "weights = np.empty((7*64*64));\n", + "counter=0\n", + "for x in range(0,64,8):\n", + " for y in range(0,64,8):\n", + " for z in range(0,7):\n", + " weights[counter*64:(counter+1)*64] = np.reshape(w3_weights[z,y:y+8,x:x+8],(-1))\n", + " counter+=1\n", + "weights = np.reshape(weights,(-1,1))\n", + "np.savetxt('data/weights-rtp.txt',weights,fmt='%.12f')\n", + "print(weights.shape)\n", + "\n", + "biases = np.reshape(w3_bias,(-1,1))\n", + "np.savetxt('data/biases-rtp.txt',biases,fmt='%.12f')\n", + "print(biases.shape)" + ] + }, + { + "cell_type": "markdown", + "id": "06a8af86", + "metadata": {}, + "source": [ + "## Run Vitis Functional Simulation" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "9986c78f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Compiling AIE Graph\n", + "Compilation directory: /group/fndprod/faisale/repo/internal/designs/radio-ml/aie/conv1d_template/vfs_work/conv1d_w3_app_b07b918c\n", + "Compilation command: v++ -c --mode aie --config vfs_work/conv1d_w3_app_b07b918c/conv1d_w3_app.cfg --work_dir vfs_work/conv1d_w3_app_b07b918c/Work --output vfs_work/conv1d_w3_app_b07b918c/libadf.a --target x86sim\n", + "Writing log to: /group/fndprod/faisale/repo/internal/designs/radio-ml/aie/conv1d_template/vfs_work/conv1d_w3_app_b07b918c/Work/logs/aie_x86sim.log\n", + "Please wait ...\n", + "\n", + "Compilation finished successfully.\n", + "Loaded AIEGraph\n" + ] + } + ], + "source": [ + "conv1d_w3_graph = vfs.aieGraph(\n", + " input_file='conv1d_w3_app.cpp',\n", + " part=\"xc2ve3858-ssva2112-2MP-e-S\",\n", + " include_paths=['./','../utility'])\n", + "act_o = conv1d_w3_graph.run(va.array(np.reshape(data_i,(-1,1)),dtype=va.bfloat16),va.array(weights,dtype=va.bfloat16),va.array(biases,dtype=va.bfloat16))\n", + "act_o = np.array(act_o)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "0db86f84", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "data_o_reshaped = np.reshape(data_o,(-1))\n", + "err = data_o_reshaped-act_o\n", + "plt.plot(err)\n", + "plt.title(\"Error\")\n", + "plt.show()\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "my-venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/gen_vectors_w11.ipynb b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/gen_vectors_w11.ipynb new file mode 100644 index 0000000000..e84336e70f --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/gen_vectors_w11.ipynb @@ -0,0 +1,656 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "bcdf2452-4c3b-4ce0-b019-cbe980967a1c", + "metadata": {}, + "source": [ + "# Testbench for `conv1d_w13()`" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "946f566a-c3f6-446f-aeb6-cb0055910900", + "metadata": {}, + "outputs": [], + "source": [ + "#\n", + "# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved.\n", + "# SPDX-License-Identifier: MIT\n", + "#\n", + "# Author: Faisal El-Shabani" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "934e0796-0306-4ce9-9a92-598027c75f38", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-08-15 08:14:18.291322: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-08-15 08:14:18.296489: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-08-15 08:14:18.306534: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", + "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n", + "E0000 00:00:1755267258.321269 244896 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", + "E0000 00:00:1755267258.325677 244896 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", + "W0000 00:00:1755267258.340455 244896 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755267258.340471 244896 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755267258.340475 244896 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755267258.340478 244896 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "2025-08-15 08:14:18.345112: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", + "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n" + ] + } + ], + "source": [ + "from tensorflow import keras\n", + "from tensorflow.keras.layers import Conv1D, MaxPooling1D\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.model_selection import train_test_split\n", + "import h5py as h5\n", + "import numpy as np\n", + "import os.path\n", + "import vfs\n", + "import varray as va\n", + "\n", + "NITERATIONS = 4 # Number of AI Engine graph iterations" + ] + }, + { + "cell_type": "markdown", + "id": "5bdc7e83-3fd0-4fd0-99b5-7938816f0df2", + "metadata": {}, + "source": [ + "## Layer Definition" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "0c57f98d-1999-4b61-a129-e3dd1bd92677", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-08-15 08:14:22.378208: E external/local_xla/xla/stream_executor/cuda/cuda_platform.cc:51] failed call to cuInit: INTERNAL: CUDA error: Failed call to cuInit: UNKNOWN ERROR (303)\n" + ] + } + ], + "source": [ + "inputs = keras.Input(shape=(1024,2),name=\"input\")\n", + "x1 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w1\",activation='relu')(inputs)\n", + "x2 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w2\")(x1)\n", + "x3 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w3\",activation='relu')(x2)\n", + "x4 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w4\")(x3)\n", + "x5 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w5\",activation='relu')(x4)\n", + "x6 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w6\")(x5)\n", + "x7 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w7\",activation='relu')(x6)\n", + "x8 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w8\")(x7)\n", + "x9 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w9\",activation='relu')(x8)\n", + "outputs = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w10\")(x9)\n", + "\n", + "model_stim = keras.Model(inputs=inputs,outputs=outputs)\n", + "model_stim.compile(optimizer=\"rmsprop\",\n", + " loss=\"sparse_categorical_crossentropy\",\n", + " metrics=[\"accuracy\"])\n", + "w1_weights = np.loadtxt('../conv1d_w1/w1_weights_trained.txt')\n", + "w1_weights = (w1_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w1_weights = np.reshape(w1_weights,(7,2,64))\n", + "w1_bias = np.loadtxt('../conv1d_w1/w1_bias_trained.txt')\n", + "w1_bias = (w1_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w3_weights = np.loadtxt('../conv1d_template/w3_weights_trained.txt')\n", + "w3_weights = (w3_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w3_weights = np.reshape(w3_weights,(7,64,64))\n", + "w3_bias = np.loadtxt('../conv1d_template/w3_bias_trained.txt')\n", + "w3_bias = (w3_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w5_weights = np.loadtxt('../conv1d_template/w5_weights_trained.txt')\n", + "w5_weights = (w5_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w5_weights = np.reshape(w5_weights,(7,64,64))\n", + "w5_bias = np.loadtxt('../conv1d_template/w5_bias_trained.txt')\n", + "w5_bias = (w5_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w7_weights = np.loadtxt('../conv1d_template/w7_weights_trained.txt')\n", + "w7_weights = (w7_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w7_weights = np.reshape(w7_weights,(7,64,64))\n", + "w7_bias = np.loadtxt('../conv1d_template/w7_bias_trained.txt')\n", + "w7_bias = (w7_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w9_weights = np.loadtxt('../conv1d_template/w9_weights_trained.txt')\n", + "w9_weights = (w9_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w9_weights = np.reshape(w9_weights,(7,64,64))\n", + "w9_bias = np.loadtxt('../conv1d_template/w9_bias_trained.txt')\n", + "w9_bias = (w9_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "model_stim.get_layer(\"conv1D_w1\").set_weights((w1_weights,w1_bias))\n", + "model_stim.get_layer(\"conv1D_w3\").set_weights((w3_weights,w3_bias))\n", + "model_stim.get_layer(\"conv1D_w5\").set_weights((w5_weights,w5_bias))\n", + "model_stim.get_layer(\"conv1D_w7\").set_weights((w7_weights,w7_bias))\n", + "model_stim.get_layer(\"conv1D_w9\").set_weights((w9_weights,w9_bias))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "cd15a0ca-2889-4d90-bd0f-2e76c63c6c19", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
Model: \"functional\"\n",
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┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ input (InputLayer)              │ (None, 1024, 2)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w1 (Conv1D)              │ (None, 1024, 64)       │           960 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w2 (MaxPooling1D)    │ (None, 512, 64)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w3 (Conv1D)              │ (None, 512, 64)        │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w4 (MaxPooling1D)    │ (None, 256, 64)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w5 (Conv1D)              │ (None, 256, 64)        │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w6 (MaxPooling1D)    │ (None, 128, 64)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w7 (Conv1D)              │ (None, 128, 64)        │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w8 (MaxPooling1D)    │ (None, 64, 64)         │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w9 (Conv1D)              │ (None, 64, 64)         │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w10 (MaxPooling1D)   │ (None, 32, 64)         │             0 │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
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Model: \"functional_1\"\n",
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┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ input_layer (InputLayer)        │ (None, 32, 64)         │             0 │\n",
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+       "│ conv1D_w11 (Conv1D)             │ (None, 32, 64)         │        28,736 │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
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"file_handle = h5.File(data_file,'r')\n", + "myData = file_handle['X'][:] #1024x2 samples \n", + "myMods = file_handle['Y'][:] #mods \n", + "mySNRs = file_handle['Z'][:] #snrs \n", + "file_handle.close()\n", + "X_train ,X_predict ,Y_train ,Y_test, Z_train, Z_test =train_test_split(myData, myMods, mySNRs, test_size=0.2, random_state=0)\n", + "X_predict = X_predict[:NITERATIONS]\n", + "X_predict = (X_predict.astype(\"bfloat16\")).astype(\"float32\")\n", + "X_inputs = model_stim.predict(X_predict,batch_size=1024)\n", + "X_inputs = (X_inputs.astype(\"bfloat16\")).astype(\"float32\")" + ] + }, + { + "cell_type": "markdown", + "id": "53bf2899-8424-4f34-b305-dea322001c7c", + "metadata": {}, + "source": [ + "## Compute Golden Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "532b9d20-6698-420d-842a-b5c2ee89c114", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n" + ] + } + ], + "source": [ + "predict = model.predict(X_inputs, batch_size=1024)\n", + "predict = (predict.astype(\"bfloat16\")).astype(\"float32\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "b588f848-eb35-409a-94c0-9b9bf986383f", + "metadata": {}, + "source": [ + "## Store Layer Inputs" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "84a1f04f-7eca-4694-906f-245a9001fd25", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 32, 64)\n", + "(4, 32, 64)\n" + ] + } + ], + "source": [ + "# Create directory if it doesn't exist\n", + "data_i = X_inputs\n", + "if not os.path.exists('data'):\n", + " os.makedirs('data')\n", + "np.savetxt('data/data_i.txt',np.reshape(data_i,(-1,4)),fmt='%.12f %.12f %.12f %.12f')\n", + "print(X_inputs.shape)\n", + "print(data_i.shape)\n" + ] + }, + { + "cell_type": "markdown", + "id": "33ae9119-15e3-49ce-9ef8-ffab0c9ec411", + "metadata": {}, + "source": [ + "## Store Layer Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "de799f89-ecbe-4480-9dcf-3bb4e5402546", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 32, 64)\n" + ] + } + ], + "source": [ + "data_o = predict\n", + "\n", + "np.savetxt('data/data_o.txt',np.reshape(data_o,(-1,4)),fmt='%.12f %.12f %.12f %.12f')\n", + "print(data_o.shape)" + ] + }, + { + "cell_type": "markdown", + "id": "b1ad8cde", + "metadata": {}, + "source": [ + "## Store Model weights and biases" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "9b35d7ca", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(7, 64, 64)\n", + "(64,)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(28672, 1)\n", + "(64, 1)\n" + ] + } + ], + "source": [ + "print(w11_weights.shape)\n", + "print(w11_bias.shape)\n", + "weights = np.empty((7*64*64));\n", + "counter=0\n", + "for x in range(0,64,8):\n", + " for y in range(0,64,8):\n", + " for z in range(0,7):\n", + " weights[counter*64:(counter+1)*64] = np.reshape(w11_weights[z,y:y+8,x:x+8],(-1))\n", + " counter+=1\n", + "weights = np.reshape(weights,(-1,1))\n", + "np.savetxt('data/weights-rtp.txt',weights,fmt='%.12f')\n", + "print(weights.shape)\n", + "\n", + "biases = np.reshape(w11_bias,(-1,1))\n", + "np.savetxt('data/biases-rtp.txt',biases,fmt='%.12f')\n", + "print(biases.shape)" + ] + }, + { + "cell_type": "markdown", + "id": "06a8af86", + "metadata": {}, + "source": [ + "## Run Vitis Functional Simulation" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "9986c78f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Compiling AIE Graph\n", + "Compilation directory: /group/fndprod/faisale/repo/internal/designs/radio-ml/aie/conv1d_template/vfs_work/conv1d_w11_app_d60af4d9\n", + "Compilation command: v++ -c --mode aie --config vfs_work/conv1d_w11_app_d60af4d9/conv1d_w11_app.cfg --work_dir vfs_work/conv1d_w11_app_d60af4d9/Work --output vfs_work/conv1d_w11_app_d60af4d9/libadf.a --target x86sim\n", + "Writing log to: /group/fndprod/faisale/repo/internal/designs/radio-ml/aie/conv1d_template/vfs_work/conv1d_w11_app_d60af4d9/Work/logs/aie_x86sim.log\n", + "Please wait ...\n", + "\n", + "Compilation finished successfully.\n", + "Loaded AIEGraph\n" + ] + } + ], + "source": [ + "conv1d_w11_graph = vfs.aieGraph(\n", + " input_file='conv1d_w11_app.cpp',\n", + " part=\"xc2ve3858-ssva2112-2MP-e-S\",\n", + " include_paths=['./','../utility'])\n", + "act_o = conv1d_w11_graph.run(va.array(np.reshape(data_i,(-1,1)),dtype=va.bfloat16),va.array(weights,dtype=va.bfloat16),va.array(biases,dtype=va.bfloat16))\n", + "act_o = np.array(act_o)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "0db86f84", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The history saving thread hit an unexpected error (OperationalError('database is locked')).History will not be written to the database.\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "PASS: Max relative error 0.000000% is within tolerance 2.0%\n" + ] + } + ], + "source": [ + "data_o_reshaped = np.reshape(data_o,(-1))\n", + "err = data_o_reshaped-act_o\n", + "plt.plot(err)\n", + "plt.title(\"Error\")\n", + "plt.show()\n", + "\n", + "err_nonzero = err[data_o_reshaped!=0]\n", + "data_o_nonzero = data_o_reshaped[data_o_reshaped!=0]\n", + "relative_error_perc = np.abs(err_nonzero/data_o_nonzero * 100).max()\n", + "tolerance_perc = 2.0 # 2 percent\n", + "if (relative_error_perc < tolerance_perc):\n", + " print(f\"PASS: Max relative error {relative_error_perc:.6f}% is within tolerance {tolerance_perc}%\")\n", + "else:\n", + " print(f\"FAIL: Max relative error {relative_error_perc:.6f}% exceeds tolerance {tolerance_perc}%\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "my-venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/gen_vectors_w13.ipynb b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/gen_vectors_w13.ipynb new file mode 100644 index 0000000000..241d909134 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_template/gen_vectors_w13.ipynb @@ -0,0 +1,667 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "bcdf2452-4c3b-4ce0-b019-cbe980967a1c", + "metadata": {}, + "source": [ + "# Testbench for `conv1d_w13()`" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "946f566a-c3f6-446f-aeb6-cb0055910900", + "metadata": {}, + "outputs": [], + "source": [ + "#\n", + "# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved.\n", + "# SPDX-License-Identifier: MIT\n", + "#\n", + "# Author: Faisal El-Shabani" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "934e0796-0306-4ce9-9a92-598027c75f38", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-08-15 08:14:22.926482: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-08-15 08:14:22.931276: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-08-15 08:14:22.940493: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", + "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n", + "E0000 00:00:1755267262.954980 3240203 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", + "E0000 00:00:1755267262.959101 3240203 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", + "W0000 00:00:1755267262.971654 3240203 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755267262.971678 3240203 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755267262.971682 3240203 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755267262.971684 3240203 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "2025-08-15 08:14:22.975944: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", + "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n" + ] + } + ], + "source": [ + "from tensorflow import keras\n", + "from tensorflow.keras.layers import Conv1D, MaxPooling1D\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.model_selection import train_test_split\n", + "import h5py as h5\n", + "import numpy as np\n", + "import os.path\n", + "import vfs\n", + "import varray as va\n", + "\n", + "NITERATIONS = 4 # Number of AI Engine graph iterations" + ] + }, + { + "cell_type": "markdown", + "id": "5bdc7e83-3fd0-4fd0-99b5-7938816f0df2", + "metadata": {}, + "source": [ + "## Layer Definition" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "0c57f98d-1999-4b61-a129-e3dd1bd92677", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-08-15 08:14:27.442605: E external/local_xla/xla/stream_executor/cuda/cuda_platform.cc:51] failed call to cuInit: INTERNAL: CUDA error: Failed call to cuInit: UNKNOWN ERROR (303)\n" + ] + } + ], + "source": [ + "inputs = keras.Input(shape=(1024,2),name=\"input\")\n", + "x1 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w1\",activation='relu')(inputs)\n", + "x2 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w2\")(x1)\n", + "x3 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w3\",activation='relu')(x2)\n", + "x4 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w4\")(x3)\n", + "x5 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w5\",activation='relu')(x4)\n", + "x6 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w6\")(x5)\n", + "x7 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w7\",activation='relu')(x6)\n", + "x8 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w8\")(x7)\n", + "x9 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w9\",activation='relu')(x8)\n", + "x10 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w10\")(x9)\n", + "x11 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w11\",activation='relu')(x10)\n", + "outputs = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w12\")(x11)\n", + "\n", + "model_stim = keras.Model(inputs=inputs,outputs=outputs)\n", + "model_stim.compile(optimizer=\"rmsprop\",\n", + " loss=\"sparse_categorical_crossentropy\",\n", + " metrics=[\"accuracy\"])\n", + "w1_weights = np.loadtxt('../conv1d_w1/w1_weights_trained.txt')\n", + "w1_weights = (w1_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w1_weights = np.reshape(w1_weights,(7,2,64))\n", + "w1_bias = np.loadtxt('../conv1d_w1/w1_bias_trained.txt')\n", + "w1_bias = (w1_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w3_weights = np.loadtxt('../conv1d_template/w3_weights_trained.txt')\n", + "w3_weights = (w3_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w3_weights = np.reshape(w3_weights,(7,64,64))\n", + "w3_bias = np.loadtxt('../conv1d_template/w3_bias_trained.txt')\n", + "w3_bias = (w3_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w5_weights = np.loadtxt('../conv1d_template/w5_weights_trained.txt')\n", + "w5_weights = (w5_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w5_weights = np.reshape(w5_weights,(7,64,64))\n", + "w5_bias = np.loadtxt('../conv1d_template/w5_bias_trained.txt')\n", + "w5_bias = (w5_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w7_weights = np.loadtxt('../conv1d_template/w7_weights_trained.txt')\n", + "w7_weights = (w7_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w7_weights = np.reshape(w7_weights,(7,64,64))\n", + "w7_bias = np.loadtxt('../conv1d_template/w7_bias_trained.txt')\n", + "w7_bias = (w7_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w9_weights = np.loadtxt('../conv1d_template/w9_weights_trained.txt')\n", + "w9_weights = (w9_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w9_weights = np.reshape(w9_weights,(7,64,64))\n", + "w9_bias = np.loadtxt('../conv1d_template/w9_bias_trained.txt')\n", + "w9_bias = (w9_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w11_weights = np.loadtxt('../conv1d_template/w11_weights_trained.txt')\n", + "w11_weights = (w11_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w11_weights = np.reshape(w11_weights,(7,64,64))\n", + "w11_bias = np.loadtxt('../conv1d_template/w11_bias_trained.txt')\n", + "w11_bias = (w11_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "model_stim.get_layer(\"conv1D_w1\").set_weights((w1_weights,w1_bias))\n", + "model_stim.get_layer(\"conv1D_w3\").set_weights((w3_weights,w3_bias))\n", + "model_stim.get_layer(\"conv1D_w5\").set_weights((w5_weights,w5_bias))\n", + "model_stim.get_layer(\"conv1D_w7\").set_weights((w7_weights,w7_bias))\n", + "model_stim.get_layer(\"conv1D_w9\").set_weights((w9_weights,w9_bias))\n", + "model_stim.get_layer(\"conv1D_w11\").set_weights((w11_weights,w11_bias))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "cd15a0ca-2889-4d90-bd0f-2e76c63c6c19", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
Model: \"functional\"\n",
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┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ input (InputLayer)              │ (None, 1024, 2)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w1 (Conv1D)              │ (None, 1024, 64)       │           960 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w2 (MaxPooling1D)    │ (None, 512, 64)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w3 (Conv1D)              │ (None, 512, 64)        │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w4 (MaxPooling1D)    │ (None, 256, 64)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w5 (Conv1D)              │ (None, 256, 64)        │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w6 (MaxPooling1D)    │ (None, 128, 64)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w7 (Conv1D)              │ (None, 128, 64)        │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w8 (MaxPooling1D)    │ (None, 64, 64)         │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w9 (Conv1D)              │ (None, 64, 64)         │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w10 (MaxPooling1D)   │ (None, 32, 64)         │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w11 (Conv1D)             │ (None, 32, 64)         │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w12 (MaxPooling1D)   │ (None, 16, 64)         │             0 │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
+       "
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Model: \"functional_1\"\n",
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\n" + ], + "text/plain": [ + "\u001b[1mModel: \"functional_1\"\u001b[0m\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ input_layer (InputLayer)        │ (None, 16, 64)         │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w13 (Conv1D)             │ (None, 16, 64)         │        28,736 │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
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 Non-trainable params: 0 (0.00 B)\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "model.summary()" + ] + }, + { + "cell_type": "markdown", + "id": "0905bc81-af38-4280-ae38-072b9530e565", + "metadata": {}, + "source": [ + "### Read training and test data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "841caa23-3f4f-455a-b21b-06a3b7cece28", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 150ms/step\n" + ] + } + ], + "source": [ + "if not(\"RADIOML_DATA\" in os.environ):\n", + " print(\"Please set environment variable RADIOML_DATA to point to dataset found in https://www.kaggle.com/datasets/pinxau1000/radioml2018\")\n", + "data_file = os.environ[\"RADIOML_DATA\"] + 'GOLD_XYZ_OSC.0001_1024.hdf5'\n", + "file_handle = h5.File(data_file,'r')\n", + "myData = file_handle['X'][:] #1024x2 samples \n", + "myMods = file_handle['Y'][:] #mods \n", + "mySNRs = file_handle['Z'][:] #snrs \n", + "file_handle.close()\n", + "X_train ,X_predict ,Y_train ,Y_test, Z_train, Z_test =train_test_split(myData, myMods, mySNRs, test_size=0.2, random_state=0)\n", + "X_predict = X_predict[:NITERATIONS]\n", + "X_predict = (X_predict.astype(\"bfloat16\")).astype(\"float32\")\n", + "X_inputs = model_stim.predict(X_predict,batch_size=1024)\n", + "X_inputs = (X_inputs.astype(\"bfloat16\")).astype(\"float32\")" + ] + }, + { + "cell_type": "markdown", + "id": "53bf2899-8424-4f34-b305-dea322001c7c", + "metadata": {}, + "source": [ + "## Compute Golden Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "532b9d20-6698-420d-842a-b5c2ee89c114", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 83ms/step\n" + ] + } + ], + "source": [ + "predict = model.predict(X_inputs, batch_size=1024)\n", + "predict = (predict.astype(\"bfloat16\")).astype(\"float32\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "b588f848-eb35-409a-94c0-9b9bf986383f", + "metadata": {}, + "source": [ + "## Store Layer Inputs" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "84a1f04f-7eca-4694-906f-245a9001fd25", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 16, 64)\n", + "(4, 16, 64)\n" + ] + } + ], + "source": [ + "# Create directory if it doesn't exist\n", + "data_i = X_inputs\n", + "if not os.path.exists('data'):\n", + " os.makedirs('data')\n", + "np.savetxt('data/data_i.txt',np.reshape(data_i,(-1,4)),fmt='%.12f %.12f %.12f %.12f')\n", + "print(X_inputs.shape)\n", + "print(data_i.shape)\n" + ] + }, + { + "cell_type": "markdown", + "id": "33ae9119-15e3-49ce-9ef8-ffab0c9ec411", + "metadata": {}, + "source": [ + "## Store Layer Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "de799f89-ecbe-4480-9dcf-3bb4e5402546", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 16, 64)\n" + ] + } + ], + "source": [ + "data_o = predict\n", + "\n", + "np.savetxt('data/data_o.txt',np.reshape(data_o,(-1,4)),fmt='%.12f %.12f %.12f %.12f')\n", + "print(data_o.shape)" + ] + }, + { + "cell_type": "markdown", + "id": "b1ad8cde", + "metadata": {}, + "source": [ + "## Store Model weights and biases" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "9b35d7ca", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(7, 64, 64)\n", + "(64,)\n", + "(28672, 1)\n", + "(64, 1)\n" + ] + } + ], + "source": [ + "print(w13_weights.shape)\n", + "print(w13_bias.shape)\n", + "weights = np.empty((7*64*64));\n", + "counter=0\n", + "for x in range(0,64,8):\n", + " for y in range(0,64,8):\n", + " for z in range(0,7):\n", + " weights[counter*64:(counter+1)*64] = np.reshape(w13_weights[z,y:y+8,x:x+8],(-1))\n", + " counter+=1\n", + "weights = np.reshape(weights,(-1,1))\n", + "np.savetxt('data/weights-rtp.txt',weights,fmt='%.12f')\n", + "print(weights.shape)\n", + "\n", + "biases = np.reshape(w13_bias,(-1,1))\n", + "np.savetxt('data/biases-rtp.txt',biases,fmt='%.12f')\n", + "print(biases.shape)" + ] + }, + { + "cell_type": "markdown", + "id": "06a8af86", + "metadata": {}, + "source": [ + "## Run Vitis Functional Simulation" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "9986c78f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Compiling AIE Graph\n", + "Compilation directory: /group/fndprod/faisale/repo/internal/designs/radio-ml/aie/conv1d_template/vfs_work/conv1d_w13_app_9247dd08\n", + "Compilation command: v++ -c --mode aie --config vfs_work/conv1d_w13_app_9247dd08/conv1d_w13_app.cfg --work_dir vfs_work/conv1d_w13_app_9247dd08/Work --output vfs_work/conv1d_w13_app_9247dd08/libadf.a --target x86sim\n", + "Writing log to: /group/fndprod/faisale/repo/internal/designs/radio-ml/aie/conv1d_template/vfs_work/conv1d_w13_app_9247dd08/Work/logs/aie_x86sim.log\n", + "Please wait ...\n", + "\n", + "Compilation finished successfully.\n", + "Loaded AIEGraph\n" + ] + } + ], + "source": [ + "conv1d_w13_graph = vfs.aieGraph(\n", + " input_file='conv1d_w13_app.cpp',\n", + " part=\"xc2ve3858-ssva2112-2MP-e-S\",\n", + " include_paths=['./','../utility'])\n", + "act_o = conv1d_w13_graph.run(va.array(np.reshape(data_i,(-1,1)),dtype=va.bfloat16),va.array(weights,dtype=va.bfloat16),va.array(biases,dtype=va.bfloat16))\n", + "act_o = np.array(act_o)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "e472a95b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The history saving thread hit an unexpected error (OperationalError('database is locked')).History will not be written to the database.\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "PASS: Max relative error 0.000000% is within tolerance 2.0%\n" + ] + } + ], + "source": [ + "data_o_reshaped = np.reshape(data_o,(-1))\n", + "err = data_o_reshaped-act_o\n", + "plt.plot(err)\n", + "plt.title(\"Error\")\n", + "plt.show()\n", + "\n", + "err_nonzero = err[data_o_reshaped!=0]\n", + "data_o_nonzero = data_o_reshaped[data_o_reshaped!=0]\n", + "relative_error_perc = np.abs(err_nonzero/data_o_nonzero * 100).max()\n", + "tolerance_perc = 2.0 # 2 percent\n", + "if (relative_error_perc < tolerance_perc):\n", + " print(f\"PASS: Max relative error {relative_error_perc:.6f}% is within tolerance {tolerance_perc}%\")\n", + "else:\n", + " print(f\"FAIL: Max relative error {relative_error_perc:.6f}% exceeds tolerance {tolerance_perc}%\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "my-venv", + "language": "python", + "name": "python3" 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All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +MY_APP := conv1d_w1_app +MY_SOURCES := ${MY_APP}.cpp conv1d_w1_graph.h conv1d_w1.h conv1d_w1.cpp + +PART ?= xc2ve3858-ssva2112-2MP-e-S + +AIE_OUTPUT := libadf.a + +AIE_FLAGS := --part=${PART} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} --include=../utility + +.PHONY: help clean x86com x86sim sim profile throughput + +help:: + @echo "Makefile Usage:" + @echo " make all" + @echo " Command to generate everything for this design" + @echo "" + @echo " make compile" + @echo " Run AIE compiler and build the design" + @echo "" + @echo " make profile" + @echo " Run AIE simulator with profiling and generate outputs suitable for Vitis Analyzer" + @echo "" + @echo " make analyze" + @echo " Run Vitis Analyzer to inspect results" + @echo "" + @echo " make throughput" + @echo " Evaluate the achieved throughput at the output" + @echo "" + @echo " make clean" + @echo " Command to remove all the generated files." + +all: ${AIE_OUTPUT} + +x86all: clean x86com x86sim + +${AIE_OUTPUT}: ${MY_SOURCES} + v++ --compile --config aie.cfg --mode aie --target=hw ${AIE_FLAGS} 2>&1 | tee log + +x86com: + v++ --compile --config aie.cfg --mode aie --target=x86sim ${AIE_FLAGS} 2>&1 | tee log + +sim: + aiesimulator 2>&1 | tee -a log + +x86sim: + x86simulator 2>&1 | tee -a log + +profile: + aiesimulator --online -wdb -text --profile 2>&1 | tee -a log + +trace: + aiesimulator --hang-detect-time=5000 --online -wdb -text 2>&1 | tee -a log + +clean: + rm -rf .Xil Work libadf.a + rm -rf aiesimulator_output* aiesimulator*.log + rm -rf x86simulator_output* + rm -rf log log* + rm -rf *.xpe *.elf *.db *.soln Map_* xnw* *.lp *.log .xil .Xil *.lp *.db *.log *.exe *.vcd *.json + rm -rf vitis_analyzer* pl_sample_counts* pl_sample_count_* + rm -rf temp ISS_RPC_SERVER_PORT .crashReporter .AIE_SIM_CMD_LINE_OPTIONS + rm -rf system*.* trdata.aiesim function_wdb_dir .wsdata _ide vfs_work .ipynb_checkpoints _ide + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/aie.cfg b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/aie.cfg new file mode 100755 index 0000000000..78861f6449 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/aie.cfg @@ -0,0 +1,14 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +[aie] + +kernel-linting=true +xlopt=1 +verbose=true +pl-freq=625 +Xmapper=BufferOptLevel9 +Xchess="main:backend.mist2.maxfoldk=80" \ No newline at end of file diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/conv1_model.m b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/conv1_model.m new file mode 100644 index 0000000000..a1d74a07b8 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/conv1_model.m @@ -0,0 +1,54 @@ +% +% Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +% SPDX-License-Identifier: MIT +% +% Author: Faisal El-Shabani +%% +formatSpec = '%f'; +fileID = fopen('data/data_iq.txt','r'); +data_iq = fscanf(fileID,formatSpec); +NITER = length(data_iq)/2048; +data_iq = reshape(data_iq,2,1024,NITER); +data_iq = double(varray.bfloat16(data_iq)); +fclose(fileID); + +I_in = zeros(1024,NITER); +Q_in = zeros(1024,NITER); +for i=1:NITER + I_in( :,i ) = reshape(data_iq(1,:,i),1,[]); + Q_in( :,i ) = reshape(data_iq(2,:,i),1,[]); +end + +conv1_golden_output = zeros(1024,64,NITER); +fileID = fopen("./data/data_o.txt",'r'); +conv1_golden_output = reshape(fscanf(fileID,formatSpec),size(conv1_golden_output)); +fclose(fileID); + + +fileID = fopen('w1_weights_trained.txt','r'); +weights = fscanf(fileID,formatSpec); +weights = reshape(weights,64,2,7); +weights = double(varray.bfloat16(weights)); +fclose(fileID); +fileID = fopen('w1_bias_trained.txt','r'); +biases = fscanf(fileID,formatSpec); +biases = double(varray.bfloat16(biases)); +fclose(fileID); +%% +conv1_actual_output = zeros(1024,64,NITER); +tmp = zeros(64,1024); +for j=1:NITER + for i=1:64 + conv_I = conv(I_in(:,j),flip(squeeze(weights(i,1,:)).'),'same'); + conv_Q = conv(Q_in(:,j),flip(squeeze(weights(i,2,:)).'),'same'); + + tmp(i,:) = max(conv_I + conv_Q + biases(i),0); + + end + conv1_actual_output(:,:,j) = tmp.'; +end +conv1_actual_output = double(varray.bfloat16(conv1_actual_output)); + +figure(1);plot(reshape(conv1_actual_output,1,[]));hold on;plot(reshape(conv1_golden_output,1,[]));hold off;legend('Actual','Golden');grid on; +figure(2);plot(reshape(conv1_actual_output,1,[])-reshape(conv1_golden_output,1,[]));grid on;title('error'); +max(abs(reshape(conv1_actual_output,1,[])-reshape(conv1_golden_output,1,[]))) \ No newline at end of file diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/conv1d_w1.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/conv1d_w1.cpp new file mode 100755 index 0000000000..9045b98158 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/conv1d_w1.cpp @@ -0,0 +1,82 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#include +#include + +#include "conv1d_w1.h" + + +// ------------------------------------------------------------ +// Constructor +// ------------------------------------------------------------ + +template +conv1d_w1::conv1d_w1(void) +{ + aie::set_rounding(aie::rounding_mode::symmetric_inf); + aie::set_saturation(aie::saturation_mode::saturate); +} + +// ------------------------------------------------------------ +// Run +// ------------------------------------------------------------ + +template +void conv1d_w1::run( input_buffer& __restrict data_iq, + const TT_DATA (&weights)[NWEIGHTS], + const TT_DATA (&biases)[NNODES], + output_async_buffer& __restrict data_o) +{ + auto p_data_iq = aie::begin_restrict_vector<64>(data_iq); + + aie::accum acc; + aie::vector data_iq_0; + aie::vector data_iq_1; + aie::vector data_reg; + aie::vector weights_reg; + + auto p_data_o = aie::begin_restrict_vector<64>(data_o); + + // Loop over nodes + for ( unsigned n=0; n < NNODES; n++) + { + if ( (n%(NNODES/NSPLIT))==0 ) + { + data_o.acquire(); + p_data_o = aie::begin_restrict_vector<64>(data_o); + } + // Loop over samples + for ( unsigned jj=0; jj < NSAMP/128; jj++) + chess_loop_range(NSAMP/128,) + chess_prepare_for_pipelining + { + data_iq_0 = *p_data_iq++; + data_iq_1 = *p_data_iq++; + auto [data_i_0,data_q_0] = aie::interleave_unzip(data_iq_0,data_iq_1,1); + data_iq_0 = *p_data_iq++; + data_iq_1 = *p_data_iq++; + auto [data_i_1,data_q_1] = aie::interleave_unzip(data_iq_0,data_iq_1,1); + p_data_iq-=2; + acc = aie::zeros(); + for ( unsigned kk=0; kk < KERNEL_SIZE; kk++) + chess_unroll_loop(*) + { + data_reg = aie::shuffle_down_fill(data_i_0,data_i_1,kk+1); // Add +1 to kk since we pre-pad 4 0s, but python model only uses 3 0s. + weights_reg = aie::broadcast(weights[kk*NNODES*2+n]); + acc = mac_elem_64(data_reg,weights_reg,acc); + + data_reg = aie::shuffle_down_fill(data_q_0,data_q_1,kk+1); // Add +1 to kk since we pre-pad 4 0s, but python model only uses 3 0s. + weights_reg = aie::broadcast(weights[kk*NNODES*2+n+NNODES]); + acc = mac_elem_64(data_reg,weights_reg,acc); + } + acc = aie::add(acc,biases[n]); + *p_data_o++ = aie::max(acc.to_vector(),TT_DATA(0)); + } + p_data_iq -= NSAMP/64; + if ( ((n+1)%(NNODES/NSPLIT))==0 ) data_o.release(); + } +} \ No newline at end of file diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/conv1d_w1.h b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/conv1d_w1.h new file mode 100755 index 0000000000..bfe165fe43 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/conv1d_w1.h @@ -0,0 +1,35 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#pragma once + +#include +#include + +using namespace adf; + +template +class conv1d_w1 { +public: + typedef bfloat16 TT_DATA; +private: + +public: + // Constructor: + conv1d_w1( void ); + + // Run: + void run( input_buffer& __restrict data_iq, + const TT_DATA (&weights)[NWEIGHTS], + const TT_DATA (&biases)[NNODES], + output_async_buffer& __restrict data_o); + + static void registerKernelClass( void ) + { + REGISTER_FUNCTION( conv1d_w1::run ); + } +}; + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/conv1d_w1_app.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/conv1d_w1_app.cpp new file mode 100755 index 0000000000..95835aed76 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/conv1d_w1_app.cpp @@ -0,0 +1,55 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#include +#include +#include "conv1d_w1_graph.h" +#include "read_file.h" + +class dut_graph : public graph { +public: + conv1d_w1_graph dut; + input_plio data_iq; + port weights; + port biases; + output_plio data_o; + + dut_graph( void ) + { + data_iq = input_plio::create("PLIO_iq_0",plio_64_bits,"data/data_iq.txt"); + connect<>(data_iq.out[0],dut.data_iq); + + connect<>(weights,dut.weights); + connect<>(biases,dut.biases); + + data_o = output_plio::create("PLIO_o_0",plio_64_bits,"data/data_o.txt"); + connect<>(dut.data_o,data_o.in[0]); + } +}; + +// Instantiate AIE graph: +dut_graph aie_dut; + +bfloat16 weights_array[896]; +bfloat16 biases_array[64]; + +// Initialize and run the graph: +int main(void) +{ + aie_dut.init(); + + // Read layer RTPs + read_file("data/weights-rtp.txt",weights_array); + read_file ("data/biases-rtp.txt", biases_array); + + aie_dut.update(aie_dut.weights,weights_array,896); + aie_dut.update(aie_dut.biases,biases_array,64); + + aie_dut.run(4); + aie_dut.end(); + + return 0; +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/conv1d_w1_graph.h b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/conv1d_w1_graph.h new file mode 100755 index 0000000000..98c48eae2c --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/conv1d_w1_graph.h @@ -0,0 +1,80 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#pragma once + +#include +#include "conv1d_w1.h" + +using namespace adf; + +// ------------------------------------------------------------ +// Top Level Graph +// ------------------------------------------------------------ + +class conv1d_w1_graph : public graph { +public: + // Declare Kernels + kernel kk; + + // Declare IOs + port data_iq; + port weights; + port biases; + port data_o; + shared_buffer MT; + + static constexpr unsigned NSAMP = 2048; // 1024 I/Q samples + static constexpr unsigned NNODES = 64; // 64 nodes + static constexpr unsigned NBIASES = NNODES; // 64 nodes + static constexpr unsigned KERNEL_SIZE = 7; // Matches KERNEL_SIZE in Python + static constexpr unsigned NWEIGHTS = KERNEL_SIZE*2*NNODES; // KERNEL_SIZE=7, I/Q paths, 64 nodes + + static constexpr double BUFFER_SIZE_MULTIPLE = NSAMP/2*NNODES*2*2*2.0/65536; // Ratio of output buffer size to local tile memory + // *2 -> 2 bytes per sample + // *2 -> ping-pong + // *2 -> Margin to ensure input buffer uses only two banks (same applies for output buffer) + // 65536 -> Local tile memory (64KB) + static constexpr unsigned NSPLIT = BUFFER_SIZE_MULTIPLE; // Process incoming samples in NSPLIT chunks so output buffers fit in local tile memory. + + conv1d_w1_graph( void ) + { + + tiling_parameters bdw = { .buffer_dimension = {NSAMP}, + .tiling_dimension = {NSAMP}, + .offset = {0} }; + // These tiling parameters pre-pads I/Q paths with 4 complex 0s and post-pads with 4 complex 0s, as opposed to minimum required of 3 and 3. + // This is done to ensure the kernel input buffer size is a multiple of 16 bytes. + tiling_parameters bdr = { .buffer_dimension = {NSAMP}, + .tiling_dimension = {NSAMP+4*2*2}, + .offset = {-4*2}, + .tile_traversal = {{.dimension=0, .stride=NSAMP+4*2*2,.wrap=1}} + }; + + MT = shared_buffer::create({NSAMP}, 1, 1); + write_access(MT.in[0]) = tiling(bdw); + read_access(MT.out[0]) = tiling(bdr); + repetition_count(MT) = 1; + + kk = kernel::create_object>(); + source(kk) = "conv1d_w1.cpp"; + runtime(kk) = 0.9; + repetition_count(kk) = 1; + stack_size(kk) = 2048; + + single_buffer(kk.in[1]); + single_buffer(kk.in[2]); + + // Connect inputs: + connect<> ( data_iq, MT.in[0] ); + connect<> ( MT.out[0], kk.in[0] ); dimensions(kk.in[0]) = {NSAMP+4*2*2}; + connect ( weights, async(kk.in[1]) ); + connect ( biases, async(kk.in[2]) ); + connect<> ( kk.out[0], data_o ); dimensions(kk.out[0]) = {NSAMP/2*NNODES/NSPLIT}; + + } +}; + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/data/biases-rtp.txt b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/data/biases-rtp.txt new file mode 100644 index 0000000000..779cd9c0c1 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/data/biases-rtp.txt @@ -0,0 +1,64 @@ +-0.132812500000 +-0.166992187500 +-0.103027343750 +-0.257812500000 +-0.132812500000 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a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/gen_vectors.ipynb b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/gen_vectors.ipynb new file mode 100755 index 0000000000..3e269fc764 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/conv1d_w1/gen_vectors.ipynb @@ -0,0 +1,428 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "bcdf2452-4c3b-4ce0-b019-cbe980967a1c", + "metadata": {}, + "source": [ + "# Testbench for `conv1d_w1()`" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "946f566a-c3f6-446f-aeb6-cb0055910900", + "metadata": {}, + "outputs": [], + "source": [ + "#\n", + "# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved.\n", + "# SPDX-License-Identifier: MIT\n", + "#\n", + "# Author: Faisal El-Shabani" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "934e0796-0306-4ce9-9a92-598027c75f38", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-09-03 12:27:57.423569: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-09-03 12:27:57.428078: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-09-03 12:27:57.437626: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", + "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n", + "E0000 00:00:1756924077.452971 2366580 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", + "E0000 00:00:1756924077.457569 2366580 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", + "W0000 00:00:1756924077.471135 2366580 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1756924077.471153 2366580 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1756924077.471156 2366580 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1756924077.471159 2366580 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "2025-09-03 12:27:57.475557: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", + "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n" + ] + } + ], + "source": [ + "from tensorflow import keras\n", + "from tensorflow.keras.layers import Conv1D\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.model_selection import train_test_split\n", + "import h5py as h5\n", + "import numpy as np\n", + "import os.path\n", + "import vfs\n", + "import varray as va\n", + "\n", + "NITERATIONS = 4 # Number of AI Engine graph iterations" + ] + }, + { + "cell_type": "markdown", + "id": "5bdc7e83-3fd0-4fd0-99b5-7938816f0df2", + "metadata": {}, + "source": [ + "## Layer Definition" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "0c57f98d-1999-4b61-a129-e3dd1bd92677", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-09-03 12:28:01.528909: E external/local_xla/xla/stream_executor/cuda/cuda_platform.cc:51] failed call to cuInit: INTERNAL: CUDA error: Failed call to cuInit: UNKNOWN ERROR (303)\n" + ] + } + ], + "source": [ + "inputs = keras.Input(shape=(1024,2),name=\"input\")\n", + "outputs = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w1\",activation='relu')(inputs)\n", + "model = keras.Model(inputs=inputs,outputs=outputs)\n", + "model.compile(optimizer=\"rmsprop\",\n", + " loss=\"sparse_categorical_crossentropy\",\n", + " metrics=[\"accuracy\"])\n", + "w_weights = np.loadtxt('w1_weights_trained.txt')\n", + "w_weights = (w_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w_weights = np.reshape(w_weights,(7,2,64))\n", + "w_bias = np.loadtxt('w1_bias_trained.txt')\n", + "w_bias = (w_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "model.set_weights((w_weights,w_bias))" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "cd15a0ca-2889-4d90-bd0f-2e76c63c6c19", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
Model: \"functional\"\n",
+       "
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+       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ input (InputLayer)              │ (None, 1024, 2)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w1 (Conv1D)              │ (None, 1024, 64)       │           960 │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
+       "
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 Total params: 960 (3.75 KB)\n",
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 Trainable params: 960 (3.75 KB)\n",
+       "
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 Non-trainable params: 0 (0.00 B)\n",
+       "
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"file_handle.close()\n", + "X_train ,X_predict ,Y_train ,Y_test, Z_train, Z_test =train_test_split(myData, myMods, mySNRs, test_size=0.2, random_state=0)\n", + "X_predict = X_predict[:NITERATIONS]\n", + "X_predict = (X_predict.astype(\"bfloat16\")).astype(\"float32\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "53bf2899-8424-4f34-b305-dea322001c7c", + "metadata": {}, + "source": [ + "## Compute Golden Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "532b9d20-6698-420d-842a-b5c2ee89c114", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 73ms/step\n" + ] + } + ], + "source": [ + "predict = model.predict(X_predict, batch_size=1024)\n", + "predict = predict.astype(\"bfloat16\").astype(\"float32\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "b588f848-eb35-409a-94c0-9b9bf986383f", + "metadata": {}, + "source": [ + "## Store Layer Inputs" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "84a1f04f-7eca-4694-906f-245a9001fd25", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 1024, 2)\n", + "(8192, 1)\n" + ] + } + ], + "source": [ + "# Create directory if it doesn't exist\n", + "if not os.path.exists('data'):\n", + " os.makedirs('data')\n", + "data_iq = np.reshape(X_predict,(-1,1))\n", + "np.savetxt('data/data_iq.txt',np.reshape(data_iq,(-1,4)),fmt='%.12f %.12f %.12f %.12f')\n", + "print(X_predict.shape)\n", + "print(data_iq.shape)" + ] + }, + { + "cell_type": "markdown", + "id": "33ae9119-15e3-49ce-9ef8-ffab0c9ec411", + "metadata": {}, + "source": [ + "## Store Layer Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "de799f89-ecbe-4480-9dcf-3bb4e5402546", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(262144,)\n" + ] + } + ], + "source": [ + "data_o = np.array([],dtype='float32')\n", + "for i in range(NITERATIONS):\n", + " data_o = np.concat((data_o,np.reshape(np.transpose(predict[i,:,:]),(-1))))\n", + "np.savetxt('data/data_o.txt',np.reshape(data_o,(-1,4)),fmt='%.12f %.12f %.12f %.12f')\n", + "print(data_o.shape)" + ] + }, + { + "cell_type": "markdown", + "id": "b08e73ab", + "metadata": {}, + "source": [ + "## Store Model weights and biases" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "1ee293d3", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(7, 2, 64)\n", + "(64,)\n", + "(896, 1)\n", + "(64, 1)\n" + ] + } + ], + "source": [ + "print(w_weights.shape)\n", + "print(w_bias.shape)\n", + "weights = np.reshape(w_weights,(-1,1))\n", + "biases = np.reshape(w_bias,(-1,1))\n", + "np.savetxt('data/weights-rtp.txt',weights,fmt='%.12f')\n", + "np.savetxt('data/biases-rtp.txt',biases,fmt='%.12f')\n", + "print(weights.shape)\n", + "print(biases.shape)\n" + ] + }, + { + "cell_type": "markdown", + "id": "06a8af86", + "metadata": {}, + "source": [ + "## Run Vitis Functional Simulation" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "9986c78f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Compiling AIE Graph\n", + "Compilation directory: /group/fndprod/faisale/repo/internal/designs/radio-ml/aie/conv1d_w1/vfs_work/conv1d_w1_app_f436b85d\n", + "Compilation command: v++ -c --mode aie --config vfs_work/conv1d_w1_app_f436b85d/conv1d_w1_app.cfg --work_dir vfs_work/conv1d_w1_app_f436b85d/Work --output vfs_work/conv1d_w1_app_f436b85d/libadf.a --target x86sim\n", + "Writing log to: /group/fndprod/faisale/repo/internal/designs/radio-ml/aie/conv1d_w1/vfs_work/conv1d_w1_app_f436b85d/Work/logs/aie_x86sim.log\n", + "Please wait ...\n", + "\n", + "Compilation finished successfully.\n", + "Loaded AIEGraph\n" + ] + } + ], + "source": [ + "conv1d_w1_graph = vfs.aieGraph(\n", + " input_file='conv1d_w1_app.cpp',\n", + " part=\"xc2ve3858-ssva2112-2MP-e-S\",\n", + " include_paths=['./','../utility'])\n", + "act_o = conv1d_w1_graph.run(va.array(data_iq, dtype=va.bfloat16),va.array(weights, dtype=va.bfloat16),va.array(biases, dtype=va.bfloat16))\n", + "act_o = np.array(act_o)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "66a9c0d5", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +MY_APP := dense_w16_app +MY_SOURCES := ${MY_APP}.cpp dense_w16_graph.h dense_w16.h dense_w16.cpp + +PART ?= xc2ve3858-ssva2112-2MP-e-S + +AIE_OUTPUT := libadf.a + +AIE_FLAGS := --part=${PART} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} --include=../utility + +.PHONY: help clean x86com x86sim sim profile throughput + +help:: + @echo "Makefile Usage:" + @echo " make all" + @echo " Command to generate everything for this design" + @echo "" + @echo " make compile" + @echo " Run AIE compiler and build the design" + @echo "" + @echo " make profile" + @echo " Run AIE simulator with profiling and generate outputs suitable for Vitis Analyzer" + @echo "" + @echo " make analyze" + @echo " Run Vitis Analyzer to inspect results" + @echo "" + @echo " make throughput" + @echo " Evaluate the achieved throughput at the output" + @echo "" + @echo " make clean" + @echo " Command to remove all the generated files." + +all: ${AIE_OUTPUT} + +x86all: clean x86com x86sim + +${AIE_OUTPUT}: ${MY_SOURCES} + v++ --compile --config aie.cfg --mode aie --target=hw ${AIE_FLAGS} 2>&1 | tee log + +x86com: + v++ --compile --config aie.cfg --mode aie --target=x86sim ${AIE_FLAGS} 2>&1 | tee log + +sim: + aiesimulator 2>&1 | tee -a log + +x86sim: + x86simulator 2>&1 | tee -a log + +profile: + aiesimulator --online -wdb -text --profile 2>&1 | tee -a log + +trace: + aiesimulator --hang-detect-time=5000 --online -wdb -text 2>&1 | tee -a log + +clean: + rm -rf .Xil Work libadf.a + rm -rf aiesimulator_output* aiesimulator*.log + rm -rf x86simulator_output* + rm -rf log log* + rm -rf *.xpe *.elf *.db *.soln Map_* xnw* *.lp *.log .xil .Xil *.lp *.db *.log *.exe *.vcd *.json + rm -rf vitis_analyzer* pl_sample_counts* pl_sample_count_* + rm -rf temp ISS_RPC_SERVER_PORT .crashReporter .AIE_SIM_CMD_LINE_OPTIONS + rm -rf system*.* trdata.aiesim function_wdb_dir .wsdata _ide vfs_work .ipynb_checkpoints _ide + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/aie.cfg b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/aie.cfg new file mode 100644 index 0000000000..bd3d1e8a37 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/aie.cfg @@ -0,0 +1,13 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +[aie] + +kernel-linting=true +xlopt=1 +verbose=true +pl-freq=625 +Xmapper=BufferOptLevel0 \ No newline at end of file diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/data/biases-rtp.txt b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/data/biases-rtp.txt new file mode 100644 index 0000000000..974efedc32 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/data/biases-rtp.txt @@ -0,0 +1,128 @@ +0.151367187500 +0.104980468750 +0.099609375000 +0.083984375000 +0.031738281250 +0.106933593750 +0.017333984375 +0.030517578125 +-0.016845703125 +0.011535644531 +0.155273437500 +0.183593750000 +0.024658203125 +0.116210937500 +0.095214843750 +0.065429687500 +-0.037597656250 +0.132812500000 +-0.105957031250 +0.147460937500 +0.099609375000 +0.066406250000 +0.240234375000 +0.100097656250 +0.037109375000 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All rights reserved. +% SPDX-License-Identifier: MIT +% +% Author: Faisal El-Shabani +%% +formatSpec = '%f'; +fileID = fopen('data/data_i.txt','r'); +data_i = fscanf(fileID,formatSpec); +fclose(fileID); +NITER = length(data_i)/512; +data_i = reshape(data_i,512,NITER); + +dense1_golden_output = zeros(128,NITER); +fileID = fopen('data/data_o.txt','r'); +dense1_golden_output = reshape(fscanf(fileID,formatSpec),size(dense1_golden_output)); +fclose(fileID); + + +fileID = fopen('w16_weights_trained.txt','r'); +weights = fscanf(fileID,formatSpec); +fclose(fileID); +weights = reshape(weights,128,512); +fileID = fopen('w16_bias_trained.txt','r'); +biases = fscanf(fileID,formatSpec); +fclose(fileID); +%% +dense1_actual_output = zeros(128,NITER); +for j=1:NITER + dense1_actual_output(:,j) = selu(weights*data_i(:,j) +biases); +end +figure(1);plot(dense1_actual_output(:));hold on;plot(dense1_golden_output(:));hold off;legend('Actual','Golden');grid on; +figure(2);plot(reshape(dense1_actual_output,1,[])-reshape(dense1_golden_output,1,[]));grid on;title('error'); +error = max(abs(reshape(dense1_actual_output,1,[])-reshape(dense1_golden_output,1,[]))) + +function [sig_o] = selu(sig_i) + idx_p = find(sig_i > 0); + idx_n = find(sig_i <= 0); + sig_o = zeros(size(sig_i)); + sig_o(idx_p) = 1.05070098*sig_i(idx_p); + sig_o(idx_n) = 1.05070098*1.67326324*(exp(sig_i(idx_n))-1); + sig_o = varray.bfloat16(sig_o); +end \ No newline at end of file diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/dense_w16.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/dense_w16.cpp new file mode 100644 index 0000000000..fce9eb6166 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/dense_w16.cpp @@ -0,0 +1,114 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#include +#include +#include +#include "dense_w16.h" + + +// ------------------------------------------------------------ +// Constructor +// ------------------------------------------------------------ + +template +dense_w16::dense_w16(void) +{ + aie::set_rounding(aie::rounding_mode::symmetric_inf); + aie::set_saturation(aie::saturation_mode::saturate); +} + +// ------------------------------------------------------------ +// SeLu +// ------------------------------------------------------------ + +template +aie::vector::TT_DATA,64> dense_w16::SeLu( aie::vector data_i ) +{ + aie::accum accB; + accB.from_vector(aie::broadcast(exp_B)); + + // Compute 'pos': + auto pos = aie::mul(data_i,Cpos).to_vector(); + + // Compute 'neg' -- first part is exp(x) approximation + auto data_t = (aie::mac(accB,data_i,exp_S)).to_vector(); + // Integer values should be in the range [0,16256], find outliers and set to zero: + aie::vector exp_i = aie::to_fixed(data_t,0); + aie::mask<64> msk_neg = aie::lt(exp_i,int16(0)); + aie::vector exp_bnd = aie::select(exp_i, aie::zeros(), msk_neg); + aie::mask<64> msk_pos = aie::gt(exp_bnd, int16(16256)); + exp_bnd = aie::select(exp_bnd, aie::zeros(), msk_pos); + auto neg_tmp = exp_bnd.cast_to(); + + // Compute 'neg' -- second part is remaining math + auto neg = (aie::mul(aie::sub(neg_tmp,TT_DATA(1.0f)),Cneg)).to_vector(); + + // Select between 'pos' and 'neg': + return aie::select(pos,neg,aie::le(data_i,aie::broadcast(0.0f))); +} +// ------------------------------------------------------------ +// Run +// ------------------------------------------------------------ + +template +void dense_w16::run( input_buffer& __restrict data_i, + const TT_DATA (&weights_0)[NWEIGHTS/2], + const TT_DATA (&weights_1)[NWEIGHTS/2], + const TT_DATA (&biases)[NBIASES], + output_buffer& __restrict data_o) +{ + auto p_data_i = aie::begin_vector_circular<64>(data_i); + auto p_data_o = aie::begin_restrict_vector<64>(data_o); + auto p_weights_0 = aie::begin_restrict_vector<64>(weights_0); + auto p_weights_1 = aie::begin_restrict_vector<64>(weights_1); + auto p_biases = aie::begin_restrict_vector<64>(biases); + + aie::vector data_reg0,data_reg1,data_reg2; + aie::vector weights_reg0,weights_reg1; + aie::accum acc_reg0,acc_reg1; + aie::accum bias_acc0,bias_acc1; + + acc_reg0 = aie::zeros(); + acc_reg1 = aie::zeros(); + for ( unsigned iter=0; iter < NSAMP/64; iter++) + { + data_reg0 = *p_data_i++; + data_reg1 = *p_data_i; + // Loop over samples + // Had to break into two loops due to CR-1242134 + for ( unsigned n=0; n < 32; n++) + chess_loop_range(32,) + chess_prepare_for_pipelining + { + data_reg2 = aie::shuffle_down_fill(data_reg0,data_reg1,n); + + weights_reg0 = *p_weights_0++; + acc_reg0 = mac_elem_64(data_reg2,weights_reg0,acc_reg0); + weights_reg1 = *p_weights_1++; + acc_reg1 = mac_elem_64(data_reg2,weights_reg1,acc_reg1); + } + for ( unsigned n=0; n < 32; n++) + chess_loop_range(32,) + chess_prepare_for_pipelining + { + data_reg2 = aie::shuffle_down_fill(data_reg0,data_reg1,n+32); + + weights_reg0 = *p_weights_0++; + acc_reg0 = mac_elem_64(data_reg2,weights_reg0,acc_reg0); + weights_reg1 = *p_weights_1++; + acc_reg1 = mac_elem_64(data_reg2,weights_reg1,acc_reg1); + } + } + + bias_acc0.from_vector(*p_biases++); + acc_reg0 = aie::add(acc_reg0,bias_acc0); + *p_data_o++ = SeLu(acc_reg0.to_vector()); + + bias_acc1.from_vector(*p_biases++); + acc_reg1 = aie::add(acc_reg1,bias_acc1); + *p_data_o++ = SeLu(acc_reg1.to_vector()); +} \ No newline at end of file diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/dense_w16.h b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/dense_w16.h new file mode 100644 index 0000000000..3d0811cff6 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/dense_w16.h @@ -0,0 +1,46 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#pragma once + +#include +#include + +using namespace adf; + +template +class dense_w16 { +public: + typedef bfloat16 TT_DATA; + + // SeLu Parameters + const TT_DATA exp_S = 185.0f; + const float exp_B = 16256.0f; + const TT_DATA Cpos = 1.0507f; + const TT_DATA Cneg = 1.7581f; + +private: + +public: + // SeLu + aie::vector SeLu( aie::vector data_i); + + // Constructor: + dense_w16( void ); + + // Run: + void run( input_buffer& __restrict data_i, + const TT_DATA (&weights_0)[NWEIGHTS/2], + const TT_DATA (&weights_1)[NWEIGHTS/2], + const TT_DATA (&biases)[NBIASES], + output_buffer& __restrict data_o); + + static void registerKernelClass( void ) + { + REGISTER_FUNCTION( dense_w16::run ); + } +}; + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/dense_w16_app.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/dense_w16_app.cpp new file mode 100644 index 0000000000..c0c23e4461 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/dense_w16_app.cpp @@ -0,0 +1,61 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#include +#include +#include "dense_w16_graph.h" +#include "read_file.h" + +class dut_graph : public graph { +public: + dense_w16_graph dut; + input_plio data_i; + output_plio data_o; + port weights_0; + port weights_1; + port biases; + + dut_graph( void ) + { + data_i = input_plio::create("PLIO_i_0",plio_64_bits,"data/data_i.txt"); + connect<>(data_i.out[0],dut.data_i); + + connect<>(weights_0,dut.weights_0); + connect<>(weights_1,dut.weights_1); + connect<>(biases,dut.biases); + + data_o = output_plio::create("PLIO_o_0",plio_64_bits,"data/data_o.txt"); + connect<>(dut.data_o,data_o.in[0]); + } +}; + +// Instantiate AIE graph: +dut_graph aie_dut; + +bfloat16 weights0_array[65536/2]; +bfloat16 weights1_array[65536/2]; +bfloat16 biases_array[128]; + + +// Initialize and run the graph: +int main(void) +{ + aie_dut.init(); + + // Read layer RTPs + read_file("data/weights_0-rtp.txt",weights0_array); + read_file("data/weights_1-rtp.txt",weights1_array); + read_file ("data/biases-rtp.txt", biases_array); + + aie_dut.update(aie_dut.weights_0,weights0_array,65536/2); + aie_dut.update(aie_dut.weights_1,weights1_array,65536/2); + aie_dut.update(aie_dut.biases,biases_array,128); + + aie_dut.run(4); + aie_dut.end(); + + return 0; +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/dense_w16_graph.h b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/dense_w16_graph.h new file mode 100644 index 0000000000..2002446ced --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/dense_w16_graph.h @@ -0,0 +1,57 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#pragma once + +#include +#include "dense_w16.h" + +using namespace adf; + +// ------------------------------------------------------------ +// Top Level Graph +// ------------------------------------------------------------ + +class dense_w16_graph : public graph { +public: + // Declare Kernels + kernel kk; + + // Declare IOs + port data_i; + port data_o; + + port weights_0; + port weights_1; + port biases; + + static constexpr unsigned NSAMP = 512; + static constexpr unsigned NNODES = 128; + static constexpr unsigned NWEIGHTS = NSAMP*NNODES; + static constexpr unsigned NBIASES = NNODES; + + dense_w16_graph( void ) + { + + kk = kernel::create_object>(); + source(kk) = "dense_w16.cpp"; + runtime(kk) = 0.9; + repetition_count(kk) = 1; + + single_buffer(kk.in[1]); + single_buffer(kk.in[2]); + single_buffer(kk.in[3]); + + // Connect inputs: + connect<> ( data_i, kk.in[0] ); dimensions(kk.in[0]) = {NSAMP}; + connect ( weights_0, async(kk.in[1]) ); + connect ( weights_1, async(kk.in[2]) ); + connect ( biases, async(kk.in[3]) ); + connect<> ( kk.out[0], data_o ); dimensions(kk.out[0]) = {NNODES}; + + } +}; + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/gen_vectors.ipynb b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/gen_vectors.ipynb new file mode 100644 index 0000000000..b5b6c574af --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/gen_vectors.ipynb @@ -0,0 +1,673 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "bcdf2452-4c3b-4ce0-b019-cbe980967a1c", + "metadata": {}, + "source": [ + "# Testbench for `dense_w16()`" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "946f566a-c3f6-446f-aeb6-cb0055910900", + "metadata": {}, + "outputs": [], + "source": [ + "#\n", + "# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved.\n", + "# SPDX-License-Identifier: MIT\n", + "#\n", + "# Author: Faisal El-Shabani" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "934e0796-0306-4ce9-9a92-598027c75f38", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-08-22 07:48:44.939997: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-08-22 07:48:44.944854: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-08-22 07:48:44.954938: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", + "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n", + "E0000 00:00:1755870524.969739 3985025 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", + "E0000 00:00:1755870524.974036 3985025 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", + "W0000 00:00:1755870524.988866 3985025 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755870524.988880 3985025 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755870524.988883 3985025 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755870524.988886 3985025 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "2025-08-22 07:48:44.993744: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", + "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n" + ] + } + ], + "source": [ + "from tensorflow import keras\n", + "from tensorflow.keras.layers import Conv1D, MaxPooling1D, Flatten, Dense\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.model_selection import train_test_split\n", + "import h5py as h5\n", + "import numpy as np\n", + "import os.path\n", + "import vfs\n", + "import varray as va\n", + "\n", + "NITERATIONS = 4 # Number of AI Engine graph iterations" + ] + }, + { + "cell_type": "markdown", + "id": "5bdc7e83-3fd0-4fd0-99b5-7938816f0df2", + "metadata": {}, + "source": [ + "## Layer Definition" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "0c57f98d-1999-4b61-a129-e3dd1bd92677", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-08-22 07:48:51.364215: E external/local_xla/xla/stream_executor/cuda/cuda_platform.cc:51] failed call to cuInit: INTERNAL: CUDA error: Failed call to cuInit: UNKNOWN ERROR (303)\n" + ] + } + ], + "source": [ + "inputs = keras.Input(shape=(1024,2),name=\"input\")\n", + "x1 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w1\",activation='relu')(inputs)\n", + "x2 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w2\")(x1)\n", + "x3 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w3\",activation='relu')(x2)\n", + "x4 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w4\")(x3)\n", + "x5 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w5\",activation='relu')(x4)\n", + "x6 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w6\")(x5)\n", + "x7 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w7\",activation='relu')(x6)\n", + "x8 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w8\")(x7)\n", + "x9 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w9\",activation='relu')(x8)\n", + "x10 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w10\")(x9)\n", + "x11 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w11\",activation='relu')(x10)\n", + "x12 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w12\")(x11)\n", + "x13 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w13\",activation='relu')(x12)\n", + "x14 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"MaxPool1D_w14\")(x13)\n", + "outputs = Flatten(name=\"flatten_w15\")(x14)\n", + "model_stim = keras.Model(inputs=inputs,outputs=outputs)\n", + "model_stim.compile(optimizer=\"rmsprop\",\n", + " loss=\"sparse_categorical_crossentropy\",\n", + " metrics=[\"accuracy\"])\n", + "w1_weights = np.loadtxt('../conv1d_w1/w1_weights_trained.txt')\n", + "w1_weights = (w1_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w1_weights = np.reshape(w1_weights,(7,2,64))\n", + "w1_bias = np.loadtxt('../conv1d_w1/w1_bias_trained.txt')\n", + "w1_bias = (w1_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w3_weights = np.loadtxt('../conv1d_template/w3_weights_trained.txt')\n", + "w3_weights = (w3_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w3_weights = np.reshape(w3_weights,(7,64,64))\n", + "w3_bias = np.loadtxt('../conv1d_template/w3_bias_trained.txt')\n", + "w3_bias = (w3_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w5_weights = np.loadtxt('../conv1d_template/w5_weights_trained.txt')\n", + "w5_weights = (w5_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w5_weights = np.reshape(w5_weights,(7,64,64))\n", + "w5_bias = np.loadtxt('../conv1d_template/w5_bias_trained.txt')\n", + "w5_bias = (w5_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w7_weights = np.loadtxt('../conv1d_template/w7_weights_trained.txt')\n", + "w7_weights = (w7_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w7_weights = np.reshape(w7_weights,(7,64,64))\n", + "w7_bias = np.loadtxt('../conv1d_template/w7_bias_trained.txt')\n", + "w7_bias = (w7_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w9_weights = np.loadtxt('../conv1d_template/w9_weights_trained.txt')\n", + "w9_weights = (w9_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w9_weights = np.reshape(w9_weights,(7,64,64))\n", + "w9_bias = np.loadtxt('../conv1d_template/w9_bias_trained.txt')\n", + "w9_bias = (w9_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w11_weights = np.loadtxt('../conv1d_template/w11_weights_trained.txt')\n", + "w11_weights = (w11_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w11_weights = np.reshape(w11_weights,(7,64,64))\n", + "w11_bias = np.loadtxt('../conv1d_template/w11_bias_trained.txt')\n", + "w11_bias = (w11_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w13_weights = np.loadtxt('../conv1d_template/w13_weights_trained.txt')\n", + "w13_weights = (w13_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w13_weights = np.reshape(w13_weights,(7,64,64))\n", + "w13_bias = np.loadtxt('../conv1d_template/w13_bias_trained.txt')\n", + "w13_bias = (w13_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "model_stim.get_layer(\"conv1D_w1\").set_weights((w1_weights,w1_bias))\n", + "model_stim.get_layer(\"conv1D_w3\").set_weights((w3_weights,w3_bias))\n", + "model_stim.get_layer(\"conv1D_w5\").set_weights((w5_weights,w5_bias))\n", + "model_stim.get_layer(\"conv1D_w7\").set_weights((w7_weights,w7_bias))\n", + "model_stim.get_layer(\"conv1D_w9\").set_weights((w9_weights,w9_bias))\n", + "model_stim.get_layer(\"conv1D_w11\").set_weights((w11_weights,w11_bias))\n", + "model_stim.get_layer(\"conv1D_w13\").set_weights((w13_weights,w13_bias))" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "cd15a0ca-2889-4d90-bd0f-2e76c63c6c19", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
Model: \"functional\"\n",
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+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
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Model: \"functional_1\"\n",
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┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ input_layer (InputLayer)        │ (None, 512)            │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_w16 (Dense)               │ (None, 128)            │        65,664 │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
+       "
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+       "
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+       "
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+       "
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"file_handle = h5.File(data_file,'r')\n", + "myData = file_handle['X'][:] #1024x2 samples \n", + "myMods = file_handle['Y'][:] #mods \n", + "mySNRs = file_handle['Z'][:] #snrs \n", + "file_handle.close()\n", + "X_train ,X_predict ,Y_train ,Y_test, Z_train, Z_test =train_test_split(myData, myMods, mySNRs, test_size=0.2, random_state=0)\n", + "X_predict = X_predict[:NITERATIONS]\n", + "X_predict = (X_predict.astype(\"bfloat16\")).astype(\"float32\")\n", + "X_inputs = model_stim.predict(X_predict,batch_size=1024)\n", + "X_inputs = (X_inputs.astype(\"bfloat16\")).astype(\"float32\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "53bf2899-8424-4f34-b305-dea322001c7c", + "metadata": {}, + "source": [ + "## Compute Golden Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "532b9d20-6698-420d-842a-b5c2ee89c114", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 39ms/step\n" + ] + } + ], + "source": [ + "predict = model.predict(X_inputs,1024)\n", + "predict = (predict.astype(\"bfloat16\")).astype(\"float32\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "b588f848-eb35-409a-94c0-9b9bf986383f", + "metadata": {}, + "source": [ + "## Store Layer Inputs" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "84a1f04f-7eca-4694-906f-245a9001fd25", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 512)\n", + "(4, 512)\n" + ] + } + ], + "source": [ + "# Create directory if it doesn't exist\n", + "data_i = X_inputs\n", + "if not os.path.exists('data'):\n", + " os.makedirs('data')\n", + "np.savetxt('data/data_i.txt',np.reshape(data_i,(-1,4)),fmt='%.12f %.12f %.12f %.12f')\n", + "print(X_inputs.shape)\n", + "print(data_i.shape)\n" + ] + }, + { + "cell_type": "markdown", + "id": "33ae9119-15e3-49ce-9ef8-ffab0c9ec411", + "metadata": {}, + "source": [ + "## Store Layer Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "de799f89-ecbe-4480-9dcf-3bb4e5402546", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 128)\n" + ] + } + ], + "source": [ + "data_o = predict\n", + "\n", + "np.savetxt('data/data_o.txt',np.reshape(data_o,(-1,4)),fmt='%.12f %.12f %.12f %.12f')\n", + "print(data_o.shape)" + ] + }, + { + "cell_type": "markdown", + "id": "a078889b", + "metadata": {}, + "source": [ + "## Store Model weights and biases" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "61671230", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(512, 128)\n", + "(32768,)\n", + "(32768,)\n", + "(128, 1)\n" + ] + } + ], + "source": [ + "print(w_weights.shape)\n", + "\n", + "# Munge weights to make compute more efficient\n", + "tmp = np.transpose(w_weights[:,:64])\n", + "weights_0 = []\n", + "for i in range(tmp.shape[1]):\n", + " weights_0 = np.concat((weights_0,np.diag(np.roll(tmp,-i,axis=1))))\n", + "np.savetxt('data/weights_0-rtp.txt',weights_0,fmt='%.12f')\n", + "print(weights_0.shape)\n", + "\n", + "tmp = np.transpose(w_weights[:,64:])\n", + "weights_1 = []\n", + "for i in range(tmp.shape[1]):\n", + " weights_1 = np.concat((weights_1,np.diag(np.roll(tmp,-i,axis=1))))\n", + "np.savetxt('data/weights_1-rtp.txt',weights_1,fmt='%.12f')\n", + "print(weights_1.shape)\n", + "\n", + "biases = np.reshape(w_bias,(-1,1))\n", + "np.savetxt('data/biases-rtp.txt',biases,fmt='%.12f')\n", + "print(biases.shape)\n" + ] + }, + { + "cell_type": "markdown", + "id": "06a8af86", + "metadata": {}, + "source": [ + "## Run Vitis Functional Simulation" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "9986c78f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Compiling AIE Graph\n", + "Compilation directory: /group/fndprod/faisale/repo/internal/designs/radio-ml/aie/dense_w16/vfs_work/dense_w16_app_17c64d52\n", + "Compilation command: v++ -c --mode aie --config vfs_work/dense_w16_app_17c64d52/dense_w16_app.cfg --work_dir vfs_work/dense_w16_app_17c64d52/Work --output vfs_work/dense_w16_app_17c64d52/libadf.a --target x86sim\n", + "Writing log to: /group/fndprod/faisale/repo/internal/designs/radio-ml/aie/dense_w16/vfs_work/dense_w16_app_17c64d52/Work/logs/aie_x86sim.log\n", + "Please wait ...\n", + "\n", + "Compilation finished successfully.\n", + "Loaded AIEGraph\n" + ] + } + ], + "source": [ + "dense_w16_graph = vfs.aieGraph(\n", + " input_file='dense_w16_app.cpp',\n", + " part=\"xc2ve3858-ssva2112-2MP-e-S\",\n", + " include_paths=['./','../utility'])\n", + "act_o = dense_w16_graph.run(va.array(np.reshape(data_i,(1,-1)),dtype=va.bfloat16),va.array(weights_0,dtype=va.bfloat16),va.array(weights_1,dtype=va.bfloat16),va.array(biases,dtype=va.bfloat16))\n", + "act_o = np.array(act_o)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "66a9c0d5", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "data_o_reshaped = np.reshape(data_o,(-1))\n", + "err = data_o_reshaped-act_o\n", + "plt.plot(err)\n", + "plt.title(\"Error\")\n", + "plt.show()\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "my-venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/w16_bias_trained.txt b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w16/w16_bias_trained.txt new file mode 100644 index 0000000000..974efedc32 --- /dev/null +++ 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All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +MY_APP := dense_w17_app +MY_SOURCES := ${MY_APP}.cpp dense_w17_graph.h dense_w17.h dense_w17.cpp + +PART ?= xc2ve3858-ssva2112-2MP-e-S + +AIE_OUTPUT := libadf.a + +AIE_FLAGS := --part=${PART} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} --include=../utility + +.PHONY: help clean x86com x86sim sim profile throughput + +help:: + @echo "Makefile Usage:" + @echo " make all" + @echo " Command to generate everything for this design" + @echo "" + @echo " make compile" + @echo " Run AIE compiler and build the design" + @echo "" + @echo " make profile" + @echo " Run AIE simulator with profiling and generate outputs suitable for Vitis Analyzer" + @echo "" + @echo " make analyze" + @echo " Run Vitis Analyzer to inspect results" + @echo "" + @echo " make throughput" + @echo " Evaluate the achieved throughput at the output" + @echo "" + @echo " make clean" + @echo " Command to remove all the generated files." + +all: ${AIE_OUTPUT} + +x86all: clean x86com x86sim + +${AIE_OUTPUT}: ${MY_SOURCES} + v++ --compile --config aie.cfg --mode aie --target=hw ${AIE_FLAGS} 2>&1 | tee log + +x86com: + v++ --compile --config aie.cfg --mode aie --target=x86sim ${AIE_FLAGS} 2>&1 | tee log + +sim: + aiesimulator 2>&1 | tee -a log + +x86sim: + x86simulator 2>&1 | tee -a log + +profile: + aiesimulator --online -wdb -text --profile 2>&1 | tee -a log + +trace: + aiesimulator --hang-detect-time=5000 --online -wdb -text 2>&1 | tee -a log + +clean: + rm -rf .Xil Work libadf.a + rm -rf aiesimulator_output* aiesimulator*.log + rm -rf x86simulator_output* + rm -rf log log* + rm -rf *.xpe *.elf *.db *.soln Map_* xnw* *.lp *.log .xil .Xil *.lp *.db *.log *.exe *.vcd *.json + rm -rf vitis_analyzer* pl_sample_counts* pl_sample_count_* + rm -rf temp ISS_RPC_SERVER_PORT .crashReporter .AIE_SIM_CMD_LINE_OPTIONS + rm -rf system*.* trdata.aiesim function_wdb_dir .wsdata _ide vfs_work .ipynb_checkpoints _ide + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/aie.cfg b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/aie.cfg new file mode 100644 index 0000000000..bd3d1e8a37 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/aie.cfg @@ -0,0 +1,13 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +[aie] + +kernel-linting=true +xlopt=1 +verbose=true +pl-freq=625 +Xmapper=BufferOptLevel0 \ No newline at end of file diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/data/biases-rtp.txt b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/data/biases-rtp.txt new file mode 100644 index 0000000000..85bd94cd82 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/data/biases-rtp.txt @@ -0,0 +1,128 @@ +0.191406250000 +-0.120605468750 +0.080078125000 +0.184570312500 +0.100585937500 +-0.007141113281 +-0.083007812500 +0.211914062500 +0.051269531250 +-0.077636718750 +-0.129882812500 +-0.025268554688 +0.042236328125 +-0.005828857422 +-0.036621093750 +-0.079101562500 +0.196289062500 +-0.053955078125 +0.188476562500 +-0.029174804688 +-0.120605468750 +0.039306640625 +-0.062011718750 +-0.005065917969 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+0.103027343750 +0.023681640625 +-0.044189453125 +-0.007690429688 +0.123046875000 +-0.048828125000 +0.033447265625 +-0.098632812500 +0.164062500000 +0.135742187500 +-0.110351562500 +-0.012329101562 +-0.009704589844 +0.090820312500 +0.048583984375 +-0.098632812500 +0.110351562500 +0.097167968750 +-0.064941406250 +0.145507812500 +-0.025146484375 +-0.078613281250 +0.034667968750 +-0.153320312500 +0.005828857422 +0.105468750000 +0.021606445312 +-0.015991210938 +-0.146484375000 +0.029174804688 +-0.023681640625 diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/dense2_model.m b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/dense2_model.m new file mode 100644 index 0000000000..8cb617586b --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/dense2_model.m @@ -0,0 +1,43 @@ +% +% Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +% SPDX-License-Identifier: MIT +% +% Author: Faisal El-Shabani +%% +formatSpec = '%f'; +fileID = fopen('data/data_i.txt','r'); +data_i = fscanf(fileID,formatSpec); +fclose(fileID); +NITER = length(data_i)/128; +data_i = reshape(data_i,128,NITER); + +dense2_golden_output = zeros(128,NITER); +fileID = fopen('data/data_o.txt','r'); +dense2_golden_output = reshape(fscanf(fileID,formatSpec),size(dense2_golden_output)); +fclose(fileID); + + +fileID = fopen('w17_weights_trained.txt','r'); +weights = fscanf(fileID,formatSpec); +fclose(fileID); +weights = reshape(weights,128,128); +fileID = fopen('w17_bias_trained.txt','r'); +biases = fscanf(fileID,formatSpec); +fclose(fileID); +%% +dense2_actual_output = zeros(128,NITER); +for j=1:NITER + dense2_actual_output(:,j) = selu(weights*data_i(:,j)+biases); +end +figure(1);plot(dense2_actual_output(:));hold on;plot(dense2_golden_output(:));hold off;legend('Actual','Golden');grid on; +figure(2);plot(reshape(dense2_actual_output,1,[])-reshape(dense2_golden_output,1,[]));grid on;title('error'); +error = max(abs(reshape(dense2_actual_output,1,[])-reshape(dense2_golden_output,1,[]))) + +function [sig_o] = selu(sig_i) + idx_p = find(sig_i > 0); + idx_n = find(sig_i <= 0); + sig_o = zeros(size(sig_i)); + sig_o(idx_p) = 1.05070098*sig_i(idx_p); + sig_o(idx_n) = 1.05070098*1.67326324*(exp(sig_i(idx_n))-1); + sig_o = varray.bfloat16(sig_o); +end \ No newline at end of file diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/dense_w17.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/dense_w17.cpp new file mode 100644 index 0000000000..f1e21cac83 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/dense_w17.cpp @@ -0,0 +1,111 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#include +#include +#include +#include "dense_w17.h" + + +// ------------------------------------------------------------ +// Constructor +// ------------------------------------------------------------ + +template +dense_w17::dense_w17(void) +{ + aie::set_rounding(aie::rounding_mode::symmetric_inf); + aie::set_saturation(aie::saturation_mode::saturate); +} + +// ------------------------------------------------------------ +// SeLu +// ------------------------------------------------------------ + +template +aie::vector::TT_DATA,64> dense_w17::SeLu( aie::vector data ) +{ + aie::accum accB; + accB.from_vector(aie::broadcast(exp_B)); + + // Compute 'pos': + auto pos = aie::mul(data,Cpos).to_vector(); + + // Compute 'neg' -- first part is exp(x) approximation + auto data_t = (aie::mac(accB,data,exp_S)).to_vector(); + // Integer values should be in the range [0,16256], find outliers and set to zero: + aie::vector exp_i = aie::to_fixed(data_t,0); + aie::mask<64> msk_neg = aie::lt(exp_i,int16(0)); + aie::vector exp_bnd = aie::select(exp_i, aie::zeros(), msk_neg); + aie::mask<64> msk_pos = aie::gt(exp_bnd, int16(16256)); + exp_bnd = aie::select(exp_bnd, aie::zeros(), msk_pos); + auto neg_tmp = exp_bnd.cast_to(); + + // Compute 'neg' -- second part is remaining math + auto neg = (aie::mul(aie::sub(neg_tmp,TT_DATA(1.0f)),Cneg)).to_vector(); + + // Select between 'pos' and 'neg': + return aie::select(pos,neg,aie::le(data,aie::broadcast(0.0f))); +} +// ------------------------------------------------------------ +// Run +// ------------------------------------------------------------ + +template +void dense_w17::run( input_buffer& __restrict data_i, + const TT_DATA (&weights)[NWEIGHTS], + const TT_DATA (&biases)[NNODES], + output_buffer& __restrict data_o) +{ + auto p_data_i = aie::begin_vector_circular<64>(data_i); + auto p_data_o = aie::begin_restrict_vector<64>(data_o); + auto p_weights = aie::begin_restrict_vector<64>(weights); + auto p_biases = aie::begin_restrict_vector<64>(biases); + + aie::vector data_reg0,data_reg1,data_reg2; + aie::vector weights_reg0,weights_reg1; + aie::accum acc_reg0,acc_reg1; + aie::accum bias_acc0,bias_acc1; + + acc_reg0 = aie::zeros(); + acc_reg1 = aie::zeros(); + for ( unsigned iter=0; iter < NNODES/64; iter++) + { + data_reg0 = *p_data_i++; + data_reg1 = *p_data_i; + // Loop over samples + // Had to break into two loops due to CR-1242134 + for ( unsigned n=0; n < 32; n++) + chess_loop_range(32,) + chess_prepare_for_pipelining + { + data_reg2 = aie::shuffle_down_fill(data_reg0,data_reg1,n); + + weights_reg0 = *p_weights++; + acc_reg0 = mac_elem_64(data_reg2,weights_reg0,acc_reg0); + weights_reg1 = *p_weights++; + acc_reg1 = mac_elem_64(data_reg2,weights_reg1,acc_reg1); + } + for ( unsigned n=0; n < 32; n++) + chess_loop_range(32,) + chess_prepare_for_pipelining + { + data_reg2 = aie::shuffle_down_fill(data_reg0,data_reg1,n+32); + + weights_reg0 = *p_weights++; + acc_reg0 = mac_elem_64(data_reg2,weights_reg0,acc_reg0); + weights_reg1 = *p_weights++; + acc_reg1 = mac_elem_64(data_reg2,weights_reg1,acc_reg1); + } + } + bias_acc0.from_vector(*p_biases++); + acc_reg0 = aie::add(acc_reg0,bias_acc0); + *p_data_o++ = SeLu(acc_reg0.to_vector()); + + bias_acc1.from_vector(*p_biases++); + acc_reg1 = aie::add(acc_reg1,bias_acc1); + *p_data_o++ = SeLu(acc_reg1.to_vector()); +} \ No newline at end of file diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/dense_w17.h b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/dense_w17.h new file mode 100644 index 0000000000..9c1fc18e11 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/dense_w17.h @@ -0,0 +1,45 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#pragma once + +#include +#include + +using namespace adf; + +template +class dense_w17 { +public: + typedef bfloat16 TT_DATA; + + // SeLu Parameters + const TT_DATA exp_S = 185.0f; + const float exp_B = 16256.0f; + const TT_DATA Cpos = 1.0507f; + const TT_DATA Cneg = 1.7581f; + +private: + +public: + // SeLu + aie::vector SeLu( aie::vector data); + + // Constructor: + dense_w17( void ); + + // Run: + void run( input_buffer& __restrict data_i, + const TT_DATA (&weights)[NWEIGHTS], + const TT_DATA (&biases)[NNODES], + output_buffer& __restrict data_o); + + static void registerKernelClass( void ) + { + REGISTER_FUNCTION( dense_w17::run ); + } +}; + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/dense_w17_app.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/dense_w17_app.cpp new file mode 100644 index 0000000000..d5a3e8589d --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/dense_w17_app.cpp @@ -0,0 +1,56 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#include +#include +#include "dense_w17_graph.h" +#include "read_file.h" + +class dut_graph : public graph { +public: + dense_w17_graph dut; + input_plio data_i; + output_plio data_o; + port weights; + port biases; + + dut_graph( void ) + { + data_i = input_plio::create("PLIO_i_0",plio_64_bits,"data/data_i.txt"); + connect<>(data_i.out[0],dut.data_i); + + connect<>(weights,dut.weights); + connect<>(biases,dut.biases); + + data_o = output_plio::create("PLIO_o_0",plio_64_bits,"data/data_o.txt"); + connect<>(dut.data_o,data_o.in[0]); + } +}; + +// Instantiate AIE graph: +dut_graph aie_dut; + +bfloat16 weights_array[16384]; +bfloat16 biases_array[128]; + + +// Initialize and run the graph: +int main(void) +{ + aie_dut.init(); + + // Read layer RTPs + read_file("data/weights-rtp.txt",weights_array); + read_file ("data/biases-rtp.txt", biases_array); + + aie_dut.update(aie_dut.weights,weights_array,16384); + aie_dut.update(aie_dut.biases,biases_array,128); + + aie_dut.run(4); + aie_dut.end(); + + return 0; +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/dense_w17_graph.h b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/dense_w17_graph.h new file mode 100644 index 0000000000..e59b696d33 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/dense_w17_graph.h @@ -0,0 +1,53 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#pragma once + +#include +#include "dense_w17.h" + +using namespace adf; + +// ------------------------------------------------------------ +// Top Level Graph +// ------------------------------------------------------------ + +class dense_w17_graph : public graph { +public: + // Declare Kernels + kernel kk; + + // Declare IOs + port data_i; + port data_o; + + port weights; + port biases; + + static constexpr unsigned NNODES = 128; + static constexpr unsigned NWEIGHTS = NNODES*NNODES; + static constexpr unsigned NBIASES = NNODES; + + dense_w17_graph( void ) + { + + kk = kernel::create_object>(); + source(kk) = "dense_w17.cpp"; + runtime(kk) = 0.9; + repetition_count(kk) = 1; + + single_buffer(kk.in[1]); + single_buffer(kk.in[2]); + + // Connect inputs: + connect<> ( data_i, kk.in[0] ); dimensions(kk.in[0]) = {NNODES}; + connect ( weights, async(kk.in[1]) ); + connect ( biases, async(kk.in[2]) ); + connect<> ( kk.out[0], data_o ); dimensions(kk.out[0]) = {NNODES}; + + } +}; + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/gen_vectors.ipynb b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/gen_vectors.ipynb new file mode 100644 index 0000000000..75fbe413c3 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/gen_vectors.ipynb @@ -0,0 +1,685 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "bcdf2452-4c3b-4ce0-b019-cbe980967a1c", + "metadata": {}, + "source": [ + "# Testbench for `dense_w17()`" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "946f566a-c3f6-446f-aeb6-cb0055910900", + "metadata": {}, + "outputs": [], + "source": [ + "#\n", + "# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved.\n", + "# SPDX-License-Identifier: MIT\n", + "#\n", + "# Author: Faisal El-Shabani" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "934e0796-0306-4ce9-9a92-598027c75f38", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-08-22 07:48:55.062934: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-08-22 07:48:55.067862: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-08-22 07:48:55.077801: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", + "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n", + "E0000 00:00:1755870535.092797 3973800 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", + "E0000 00:00:1755870535.097132 3973800 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", + "W0000 00:00:1755870535.111789 3973800 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755870535.111802 3973800 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755870535.111805 3973800 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755870535.111808 3973800 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "2025-08-22 07:48:55.116400: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", + "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n" + ] + } + ], + "source": [ + "from tensorflow import keras\n", + "from tensorflow.keras.layers import Conv1D, MaxPooling1D, Flatten, Dense\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.model_selection import train_test_split\n", + "import h5py as h5\n", + "import numpy as np\n", + "import os.path\n", + "import vfs\n", + "import varray as va\n", + "\n", + "NITERATIONS = 4 # Number of AI Engine graph iterations" + ] + }, + { + "cell_type": "markdown", + "id": "5bdc7e83-3fd0-4fd0-99b5-7938816f0df2", + "metadata": {}, + "source": [ + "## Layer Definition" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "0c57f98d-1999-4b61-a129-e3dd1bd92677", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-08-22 07:49:03.863576: E external/local_xla/xla/stream_executor/cuda/cuda_platform.cc:51] failed call to cuInit: INTERNAL: CUDA error: Failed call to cuInit: UNKNOWN ERROR (303)\n" + ] + } + ], + "source": [ + "inputs = keras.Input(shape=(1024,2),name=\"input\")\n", + "x1 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w1\",activation='relu')(inputs)\n", + "x2 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w2\")(x1)\n", + "x3 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w3\",activation='relu')(x2)\n", + "x4 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w4\")(x3)\n", + "x5 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w5\",activation='relu')(x4)\n", + "x6 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w6\")(x5)\n", + "x7 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w7\",activation='relu')(x6)\n", + "x8 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w8\")(x7)\n", + "x9 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w9\",activation='relu')(x8)\n", + "x10 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w10\")(x9)\n", + "x11 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w11\",activation='relu')(x10)\n", + "x12 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w12\")(x11)\n", + "x13 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w13\",activation='relu')(x12)\n", + "x14 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"MaxPool1D_w14\")(x13)\n", + "x15 = Flatten(name=\"flatten_w15\")(x14)\n", + "outputs = Dense(128, activation=\"relu\",name=\"dense_w16\")(x15)\n", + "model_stim = keras.Model(inputs=inputs,outputs=outputs)\n", + "model_stim.compile(optimizer=\"rmsprop\",\n", + " loss=\"sparse_categorical_crossentropy\",\n", + " metrics=[\"accuracy\"])\n", + "w1_weights = np.loadtxt('../conv1d_w1/w1_weights_trained.txt')\n", + "w1_weights = (w1_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w1_weights = np.reshape(w1_weights,(7,2,64))\n", + "w1_bias = np.loadtxt('../conv1d_w1/w1_bias_trained.txt')\n", + "w1_bias = (w1_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w3_weights = np.loadtxt('../conv1d_template/w3_weights_trained.txt')\n", + "w3_weights = (w3_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w3_weights = np.reshape(w3_weights,(7,64,64))\n", + "w3_bias = np.loadtxt('../conv1d_template/w3_bias_trained.txt')\n", + "w3_bias = (w3_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w5_weights = np.loadtxt('../conv1d_template/w5_weights_trained.txt')\n", + "w5_weights = (w5_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w5_weights = np.reshape(w5_weights,(7,64,64))\n", + "w5_bias = np.loadtxt('../conv1d_template/w5_bias_trained.txt')\n", + "w5_bias = (w5_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w7_weights = np.loadtxt('../conv1d_template/w7_weights_trained.txt')\n", + "w7_weights = (w7_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w7_weights = np.reshape(w7_weights,(7,64,64))\n", + "w7_bias = np.loadtxt('../conv1d_template/w7_bias_trained.txt')\n", + "w7_bias = (w7_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w9_weights = np.loadtxt('../conv1d_template/w9_weights_trained.txt')\n", + "w9_weights = (w9_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w9_weights = np.reshape(w9_weights,(7,64,64))\n", + "w9_bias = np.loadtxt('../conv1d_template/w9_bias_trained.txt')\n", + "w9_bias = (w9_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w11_weights = np.loadtxt('../conv1d_template/w11_weights_trained.txt')\n", + "w11_weights = (w11_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w11_weights = np.reshape(w11_weights,(7,64,64))\n", + "w11_bias = np.loadtxt('../conv1d_template/w11_bias_trained.txt')\n", + "w11_bias = (w11_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w13_weights = np.loadtxt('../conv1d_template/w13_weights_trained.txt')\n", + "w13_weights = (w13_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w13_weights = np.reshape(w13_weights,(7,64,64))\n", + "w13_bias = np.loadtxt('../conv1d_template/w13_bias_trained.txt')\n", + "w13_bias = (w13_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w16_weights = np.loadtxt('../dense_w16/w16_weights_trained.txt')\n", + "w16_weights = (w16_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w16_weights = np.reshape(w16_weights,(512,128))\n", + "w16_bias = np.loadtxt('../dense_w16/w16_bias_trained.txt')\n", + "w16_bias = (w16_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "model_stim.get_layer(\"conv1D_w1\").set_weights((w1_weights,w1_bias))\n", + "model_stim.get_layer(\"conv1D_w3\").set_weights((w3_weights,w3_bias))\n", + "model_stim.get_layer(\"conv1D_w5\").set_weights((w5_weights,w5_bias))\n", + "model_stim.get_layer(\"conv1D_w7\").set_weights((w7_weights,w7_bias))\n", + "model_stim.get_layer(\"conv1D_w9\").set_weights((w9_weights,w9_bias))\n", + "model_stim.get_layer(\"conv1D_w11\").set_weights((w11_weights,w11_bias))\n", + "model_stim.get_layer(\"conv1D_w13\").set_weights((w13_weights,w13_bias))\n", + "model_stim.get_layer(\"dense_w16\").set_weights((w16_weights,w16_bias))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "cd15a0ca-2889-4d90-bd0f-2e76c63c6c19", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ input (InputLayer)              │ (None, 1024, 2)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w1 (Conv1D)              │ (None, 1024, 64)       │           960 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w2 (MaxPooling1D)    │ (None, 512, 64)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w3 (Conv1D)              │ (None, 512, 64)        │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w4 (MaxPooling1D)    │ (None, 256, 64)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w5 (Conv1D)              │ (None, 256, 64)        │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w6 (MaxPooling1D)    │ (None, 128, 64)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w7 (Conv1D)              │ (None, 128, 64)        │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w8 (MaxPooling1D)    │ (None, 64, 64)         │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w9 (Conv1D)              │ (None, 64, 64)         │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w10 (MaxPooling1D)   │ (None, 32, 64)         │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w11 (Conv1D)             │ (None, 32, 64)         │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w12 (MaxPooling1D)   │ (None, 16, 64)         │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w13 (Conv1D)             │ (None, 16, 64)         │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ MaxPool1D_w14 (MaxPooling1D)    │ (None, 8, 64)          │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ flatten_w15 (Flatten)           │ (None, 512)            │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_w16 (Dense)               │ (None, 128)            │        65,664 │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
+       "
\n" + ], + "text/plain": [ + "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n", + "┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\n", + "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n", + "│ input (\u001b[38;5;33mInputLayer\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1024\u001b[0m, \u001b[38;5;34m2\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w1 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1024\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m960\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w2 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w3 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w4 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w5 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w6 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w7 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w8 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w9 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w10 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w11 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w12 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w13 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ MaxPool1D_w14 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ flatten_w15 (\u001b[38;5;33mFlatten\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dense_w16 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m65,664\u001b[0m │\n", + "└─────────────────────────────────┴────────────────────────┴───────────────┘\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Total params: 239,040 (933.75 KB)\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m239,040\u001b[0m (933.75 KB)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Trainable params: 239,040 (933.75 KB)\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m239,040\u001b[0m (933.75 KB)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Non-trainable params: 0 (0.00 B)\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "model_stim.summary()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "53441463", + "metadata": {}, + "outputs": [], + "source": [ + "inputs = keras.Input(shape=([128]),name=\"input_layer\")\n", + "outputs = Dense(128, activation=\"selu\",name=\"dense_w17\")(inputs)\n", + "model = keras.Model(inputs=inputs,outputs=outputs)\n", + "model.compile(optimizer=\"rmsprop\",\n", + " loss=\"sparse_categorical_crossentropy\",\n", + " metrics=[\"accuracy\"])\n", + "w_weights = np.loadtxt('w17_weights_trained.txt')\n", + "w_weights = (w_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w_weights = np.reshape(w_weights,(128,128))\n", + "w_bias = np.loadtxt('w17_bias_trained.txt')\n", + "w_bias = (w_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "model.set_weights((w_weights,w_bias))" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "1f5d4822", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
Model: \"functional_1\"\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1mModel: \"functional_1\"\u001b[0m\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ input_layer (InputLayer)        │ (None, 128)            │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_w17 (Dense)               │ (None, 128)            │        16,512 │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
+       "
\n" + ], + "text/plain": [ + "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n", + "┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\n", + "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n", + "│ input_layer (\u001b[38;5;33mInputLayer\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dense_w17 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m16,512\u001b[0m │\n", + "└─────────────────────────────────┴────────────────────────┴───────────────┘\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Total params: 16,512 (64.50 KB)\n",
+       "
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 Trainable params: 16,512 (64.50 KB)\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m16,512\u001b[0m (64.50 KB)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Non-trainable params: 0 (0.00 B)\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "model.summary()" + ] + }, + { + "cell_type": "markdown", + "id": "0905bc81-af38-4280-ae38-072b9530e565", + "metadata": {}, + "source": [ + "### Read training and test data" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "841caa23-3f4f-455a-b21b-06a3b7cece28", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 159ms/step\n" + ] + } + ], + "source": [ + "if not(\"RADIOML_DATA\" in os.environ):\n", + " print(\"Please set environment variable RADIOML_DATA to point to dataset found in https://www.kaggle.com/datasets/pinxau1000/radioml2018\")\n", + "data_file = os.environ[\"RADIOML_DATA\"] + 'GOLD_XYZ_OSC.0001_1024.hdf5'\n", + "file_handle = h5.File(data_file,'r')\n", + "myData = file_handle['X'][:] #1024x2 samples \n", + "myMods = file_handle['Y'][:] #mods \n", + "mySNRs = file_handle['Z'][:] #snrs \n", + "file_handle.close()\n", + "X_train ,X_predict ,Y_train ,Y_test, Z_train, Z_test =train_test_split(myData, myMods, mySNRs, test_size=0.2, random_state=0)\n", + "X_predict = X_predict[:NITERATIONS]\n", + "X_predict = (X_predict.astype(\"bfloat16\")).astype(\"float32\")\n", + "X_inputs = model_stim.predict(X_predict,batch_size=1024)\n", + "X_inputs = (X_inputs.astype(\"bfloat16\")).astype(\"float32\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "53bf2899-8424-4f34-b305-dea322001c7c", + "metadata": {}, + "source": [ + "## Compute Golden Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "532b9d20-6698-420d-842a-b5c2ee89c114", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 36ms/step\n" + ] + } + ], + "source": [ + "predict = model.predict(X_inputs, batch_size=1024)\n", + "predict = (predict.astype(\"bfloat16\")).astype(\"float32\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "b588f848-eb35-409a-94c0-9b9bf986383f", + "metadata": {}, + "source": [ + "## Store Layer Inputs" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "84a1f04f-7eca-4694-906f-245a9001fd25", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 128)\n", + "(4, 128)\n" + ] + } + ], + "source": [ + "# Create directory if it doesn't exist\n", + "data_i = X_inputs\n", + "if not os.path.exists('data'):\n", + " os.makedirs('data')\n", + "np.savetxt('data/data_i.txt',np.reshape(data_i,(-1,4)),fmt='%.12f %.12f %.12f %.12f')\n", + "print(X_inputs.shape)\n", + "print(data_i.shape)\n" + ] + }, + { + "cell_type": "markdown", + "id": "33ae9119-15e3-49ce-9ef8-ffab0c9ec411", + "metadata": {}, + "source": [ + "## Store Layer Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "de799f89-ecbe-4480-9dcf-3bb4e5402546", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 128)\n" + ] + } + ], + "source": [ + "data_o = predict\n", + "\n", + "np.savetxt('data/data_o.txt',np.reshape(data_o,(-1,4)),fmt='%.12f %.12f %.12f %.12f')\n", + "print(data_o.shape)" + ] + }, + { + "cell_type": "markdown", + "id": "a078889b", + "metadata": {}, + "source": [ + "## Store Model weights and biases" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "61671230", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(128, 128)\n", + "(16384,)\n", + "(128, 1)\n" + ] + } + ], + "source": [ + "print(w_weights.shape)\n", + "\n", + "# Munge weights to make compute more efficient\n", + "tmp1 = np.transpose(w_weights[:,:64])\n", + "tmp2 = np.transpose(w_weights[:,64:])\n", + "weights = []\n", + "for i in range(tmp1.shape[1]):\n", + " weights = np.concat((weights,np.diag(np.roll(tmp1,-i,axis=1))))\n", + " weights = np.concat((weights,np.diag(np.roll(tmp2,-i,axis=1))))\n", + "np.savetxt('data/weights-rtp.txt',weights,fmt='%.12f')\n", + "print(weights.shape)\n", + "\n", + "biases = np.reshape(w_bias,(-1,1))\n", + "np.savetxt('data/biases-rtp.txt',biases,fmt='%.12f')\n", + "print(biases.shape)\n" + ] + }, + { + "cell_type": "markdown", + "id": "06a8af86", + "metadata": {}, + "source": [ + "## Run Vitis Functional Simulation" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "9986c78f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Compiling AIE Graph\n", + "Compilation directory: /group/fndprod/faisale/repo/internal/designs/radio-ml/aie/dense_w17/vfs_work/dense_w17_app_d8585a9a\n", + "Compilation command: v++ -c --mode aie --config vfs_work/dense_w17_app_d8585a9a/dense_w17_app.cfg --work_dir vfs_work/dense_w17_app_d8585a9a/Work --output vfs_work/dense_w17_app_d8585a9a/libadf.a --target x86sim\n", + "Writing log to: /group/fndprod/faisale/repo/internal/designs/radio-ml/aie/dense_w17/vfs_work/dense_w17_app_d8585a9a/Work/logs/aie_x86sim.log\n", + "Please wait ...\n", + "\n", + "Compilation finished successfully.\n", + "Loaded AIEGraph\n" + ] + } + ], + "source": [ + "dense_w17_graph = vfs.aieGraph(\n", + " input_file='dense_w17_app.cpp',\n", + " part=\"xc2ve3858-ssva2112-2MP-e-S\",\n", + " include_paths=['./','../utility'])\n", + "act_o = dense_w17_graph.run(va.array(np.reshape(data_i,(1,-1)),dtype=va.bfloat16),va.array(weights,dtype=va.bfloat16),va.array(biases,dtype=va.bfloat16))\n", + "act_o = np.array(act_o)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "66a9c0d5", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The history saving thread hit an unexpected error (OperationalError('database is locked')).History will not be written to the database.\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "data_o_reshaped = np.reshape(data_o,(-1))\n", + "err = data_o_reshaped-act_o\n", + "plt.plot(err)\n", + "plt.title(\"Error\")\n", + "plt.show()\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "my-venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/w17_bias_trained.txt b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17/w17_bias_trained.txt new file mode 100644 index 0000000000..85bd94cd82 --- /dev/null +++ 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+-0.172851562500 +-0.084472656250 diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/Makefile b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/Makefile new file mode 100755 index 0000000000..3ecdaf1c46 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/Makefile @@ -0,0 +1,83 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Chandra Sekar Balakrishnan + +AIE_SIM_ONLY := false + +SIM_FIFO := false + +MY_APP := dense_w17_app +MY_SOURCES := ${MY_APP}.cpp dense_w17_graph.h dense_w17.h dense_w17.cpp + +PART ?= xc2ve3858-ssva2112-2MP-e-S + +CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing + +AIE_OUTPUT := libadf.a + +AIE_FLAGS := --part=${PART} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} --include=../utility + +ifeq (${SIM_FIFO}, true) + AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} +endif +ifeq (${AIE_SIM_ONLY},true) + AIE_FLAGS := ${AIE_FLAGS} --aie.Xpreproc="-DAIE_SIM_ONLY" +endif + + +.PHONY: help clean x86com x86sim sim profile throughput + +help:: + @echo "Makefile Usage:" + @echo " make all" + @echo " Command to generate everything for this design" + @echo "" + @echo " make compile" + @echo " Run AIE compiler and build the design" + @echo "" + @echo " make profile" + @echo " Run AIE simulator with profiling and generate outputs suitable for Vitis Analyzer" + @echo "" + @echo " make analyze" + @echo " Run Vitis Analyzer to inspect results" + @echo "" + @echo " make throughput" + @echo " Evaluate the achieved throughput at the output" + @echo "" + @echo " make clean" + @echo " Command to remove all the generated files." + +all: ${AIE_OUTPUT} + +x86all: clean x86com x86sim + +${AIE_OUTPUT}: ${MY_SOURCES} + v++ --compile --config aie.cfg --mode aie --target=hw ${AIE_FLAGS} 2>&1 | tee log + +x86com: + v++ --compile --config aie.cfg --mode aie --target=x86sim ${AIE_FLAGS} 2>&1 | tee log + +sim: + aiesimulator 2>&1 | tee -a log + +x86sim: + x86simulator 2>&1 | tee -a log + +profile: + aiesimulator --online -wdb -text --profile 2>&1 | tee -a log + +trace: + aiesimulator --hang-detect-time=5000 --online -wdb -text 2>&1 | tee -a log + +clean: + rm -rf .Xil Work libadf.a + rm -rf aiesimulator_output* aiesimulator*.log + rm -rf x86simulator_output* + rm -rf log log* + rm -rf *.xpe *.elf *.db *.soln Map_* xnw* *.lp *.log .xil .Xil *.lp *.db *.log *.exe *.vcd *.json + rm -rf vitis_analyzer* pl_sample_counts* pl_sample_count_* + rm -rf temp ISS_RPC_SERVER_PORT .crashReporter .AIE_SIM_CMD_LINE_OPTIONS + rm -rf system*.* trdata.aiesim function_wdb_dir .wsdata _ide vfs_work .ipynb_checkpoints _ide + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/aie.cfg b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/aie.cfg new file mode 100755 index 0000000000..f0a6bcf2b9 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/aie.cfg @@ -0,0 +1,13 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Chandra Sekar Balakrishnan + +[aie] + +kernel-linting=true +xlopt=1 +verbose=true +pl-freq=625 +Xmapper=BufferOptLevel9 \ No newline at end of file diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/data/biases-rtp.txt b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/data/biases-rtp.txt new file mode 100644 index 0000000000..85bd94cd82 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/data/biases-rtp.txt @@ -0,0 +1,128 @@ +0.191406250000 +-0.120605468750 +0.080078125000 +0.184570312500 +0.100585937500 +-0.007141113281 +-0.083007812500 +0.211914062500 +0.051269531250 +-0.077636718750 +-0.129882812500 +-0.025268554688 +0.042236328125 +-0.005828857422 +-0.036621093750 +-0.079101562500 +0.196289062500 +-0.053955078125 +0.188476562500 +-0.029174804688 +-0.120605468750 +0.039306640625 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b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/dense2_model.m new file mode 100644 index 0000000000..8cb617586b --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/dense2_model.m @@ -0,0 +1,43 @@ +% +% Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +% SPDX-License-Identifier: MIT +% +% Author: Faisal El-Shabani +%% +formatSpec = '%f'; +fileID = fopen('data/data_i.txt','r'); +data_i = fscanf(fileID,formatSpec); +fclose(fileID); +NITER = length(data_i)/128; +data_i = reshape(data_i,128,NITER); + +dense2_golden_output = zeros(128,NITER); +fileID = fopen('data/data_o.txt','r'); +dense2_golden_output = reshape(fscanf(fileID,formatSpec),size(dense2_golden_output)); +fclose(fileID); + + +fileID = fopen('w17_weights_trained.txt','r'); +weights = fscanf(fileID,formatSpec); +fclose(fileID); +weights = reshape(weights,128,128); +fileID = fopen('w17_bias_trained.txt','r'); +biases = fscanf(fileID,formatSpec); +fclose(fileID); +%% +dense2_actual_output = zeros(128,NITER); +for j=1:NITER + dense2_actual_output(:,j) = selu(weights*data_i(:,j)+biases); +end +figure(1);plot(dense2_actual_output(:));hold on;plot(dense2_golden_output(:));hold off;legend('Actual','Golden');grid on; +figure(2);plot(reshape(dense2_actual_output,1,[])-reshape(dense2_golden_output,1,[]));grid on;title('error'); +error = max(abs(reshape(dense2_actual_output,1,[])-reshape(dense2_golden_output,1,[]))) + +function [sig_o] = selu(sig_i) + idx_p = find(sig_i > 0); + idx_n = find(sig_i <= 0); + sig_o = zeros(size(sig_i)); + sig_o(idx_p) = 1.05070098*sig_i(idx_p); + sig_o(idx_n) = 1.05070098*1.67326324*(exp(sig_i(idx_n))-1); + sig_o = varray.bfloat16(sig_o); +end \ No newline at end of file diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/dense_w17.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/dense_w17.cpp new file mode 100755 index 0000000000..8d4dc5a5d3 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/dense_w17.cpp @@ -0,0 +1,127 @@ + + +// +// Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Chandra Sekar Balakrishnan + +#include +#include +#include +#include "dense_w17.h" + + +// ------------------------------------------------------------ +// Constructor +// ------------------------------------------------------------ + +template +dense_w17::dense_w17(void) +{ + aie::set_rounding(aie::rounding_mode::symmetric_inf); + aie::set_saturation(aie::saturation_mode::saturate); +} +// ------------------------------------------------------------ +// SeLu +// ------------------------------------------------------------ + +template +aie::vector::TT_DATA,64> dense_w17::SeLu( aie::vector data ) +{ + aie::accum accB; + accB.from_vector(aie::broadcast(exp_B)); + + // Compute 'pos': + auto pos = aie::mul(data,Cpos).to_vector(); + + // Compute 'neg' -- first part is exp(x) approximation + auto data_t = (aie::mac(accB,data,exp_S)).to_vector(); + // Integer values should be in the range [0,16256], find outliers and set to zero: + aie::vector exp_i = aie::to_fixed(data_t,0); + aie::mask<64> msk_neg = aie::lt(exp_i,int16(0)); + aie::vector exp_bnd = aie::select(exp_i, aie::zeros(), msk_neg); + aie::mask<64> msk_pos = aie::gt(exp_bnd, int16(16256)); + exp_bnd = aie::select(exp_bnd, aie::zeros(), msk_pos); + auto neg_tmp = exp_bnd.cast_to(); + + // Compute 'neg' -- second part is remaining math + auto neg = (aie::mul(aie::sub(neg_tmp,TT_DATA(1.0f)),Cneg)).to_vector(); + + // Select between 'pos' and 'neg': + return aie::select(pos,neg,aie::le(data,aie::broadcast(0.0f))); +} + +// ------------------------------------------------------------ +// Run +// ------------------------------------------------------------ + +template +void dense_w17::run( input_buffer& __restrict data_i, + const TT_DATA (&weights)[NWEIGHTS], + const TT_DATA (&biases)[NBIASES], + output_buffer& __restrict data_o) +{ + + aie::vector v_reg0 = aie::zeros(); + aie::vector v_reg1 = aie::zeros(); + aie::vector bias_reg = aie::zeros(); + + aie::accum acc_reg0, acc_reg1; + + auto p_data_o = aie::begin_restrict_vector<64>(data_o); + + auto p_biases = aie::begin_restrict_vector<64>(biases); + // auto p_biases = aie::begin_restrict_vector<16>(biases); + + auto p_weights = aie::begin_restrict_vector<64>(weights); + + auto p_data = aie::begin_restrict_vector<64>(data_i); + auto data_0 = *p_data++; + auto data_1 = *p_data; + + // Total of 128 nodes + // First - 64 nodes ouptut + for ( unsigned n=0; n < 64; n++) + chess_loop_range(64,) + chess_prepare_for_pipelining + { + // First 64 samples computation - node (n) For example - Node 0 in first loop + acc_reg0 = mul_elem_64(data_0, *p_weights++); + + acc_reg0 = mac_elem_64(data_1, *p_weights++, acc_reg0); // Next 64 samples - First node0 computation done (128 samples processed for Node0) in loop 0 + + v_reg0.set(aie::reduce_add(acc_reg0.to_vector()),n); + + } + + // Last - 64 nodes output + for ( unsigned n=0; n < 64; n++) + chess_loop_range(64,) + chess_prepare_for_pipelining + { + acc_reg1 = mul_elem_64(data_0, *p_weights++); + + acc_reg1 = mac_elem_64(data_1, *p_weights++, acc_reg1); + + v_reg1.set(aie::reduce_add(acc_reg1.to_vector()),n); + } + + bias_reg = *p_biases++; + + // First - 64 nodes + // Add accumulated data with bias + auto add_bias0 = aie::add(v_reg0,bias_reg); + + // Call SELU function - First 64 nodes donw with SELU + *p_data_o++ = SeLu(add_bias0); + + bias_reg = *p_biases; + // Last - 64 nodes + // Add accumulated data with bias + auto add_bias1 = aie::add(v_reg1,bias_reg); + + // Call SELU function - - Last 64 nodes donw with SELU + *p_data_o++ = SeLu(add_bias1); + +} \ No newline at end of file diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/dense_w17.h b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/dense_w17.h new file mode 100755 index 0000000000..a602e08e12 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/dense_w17.h @@ -0,0 +1,45 @@ +// +// Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Chandra Sekar Balakrishnan + +#pragma once + +#include +#include + +using namespace adf; + +template +class dense_w17 { +public: + typedef bfloat16 TT_DATA; + + // SeLu Parameters + const TT_DATA exp_S = 185.0f; + const float exp_B = 16256.0f; + const TT_DATA Cpos = 1.0507f; + const TT_DATA Cneg = 1.7581f; + +private: + +public: + // SeLu + aie::vector SeLu( aie::vector data); + + // Constructor: + dense_w17( void ); + + // Run: + void run( input_buffer& __restrict data_i, + const TT_DATA (&weights)[NWEIGHTS], + const TT_DATA (&biases)[NBIASES], + output_buffer& __restrict data_o); + + static void registerKernelClass( void ) + { + REGISTER_FUNCTION( dense_w17::run ); + } +}; + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/dense_w17_app.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/dense_w17_app.cpp new file mode 100755 index 0000000000..dfaf30132a --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/dense_w17_app.cpp @@ -0,0 +1,58 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Chandra Sekar Balakrishnan + +#include +#include +#include "dense_w17_graph.h" +#include "read_file.h" + +class dut_graph : public graph { +public: + dense_w17_graph dut; + input_plio data_i; + output_plio data_o; + port weights; + port biases; + + dut_graph( void ) + { + data_i = input_plio::create("PLIO_iq_0",plio_64_bits,"data/data_i.txt"); + //weights = input_plio::create("PLIO_weights_1",plio_64_bits,"data/weights.txt"); + //biases = input_plio::create("PLIO_biases_2",plio_64_bits,"data/biases.txt"); + + connect<>(data_i.out[0],dut.data_i); + + connect<>(weights,dut.weights); + connect<>(biases,dut.biases); + + data_o = output_plio::create("PLIO_o_0",plio_64_bits,"data/data_o.txt"); + connect<>(dut.data_o,data_o.in[0]); + } +}; + +// Instantiate AIE graph: +dut_graph aie_dut; + +bfloat16 weights_array[16384]; +bfloat16 biases_array[128]; + +// Initialize and run the graph: +int main(void) +{ + aie_dut.init(); + + // Read layer RTPs + read_file("data/weights-rtp.txt",weights_array); + read_file ("data/biases-rtp.txt", biases_array); + + aie_dut.update(aie_dut.weights,weights_array,16384); + aie_dut.update(aie_dut.biases,biases_array,128); + + aie_dut.run(4); + aie_dut.end(); + + return 0; +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/dense_w17_graph.h b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/dense_w17_graph.h new file mode 100755 index 0000000000..2f5f5d4fbc --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/dense_w17_graph.h @@ -0,0 +1,56 @@ +// +// Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Chandra Sekar Balakrishnan + +#pragma once + +#include +#include "dense_w17.h" + +using namespace adf; + +// ------------------------------------------------------------ +// Top Level Graph +// ------------------------------------------------------------ + +class dense_w17_graph : public graph { +public: + // Declare Kernels + kernel kk; + + // Declare IOs + port data_i; + port data_o; + + port weights; + port biases; + + static constexpr unsigned NSAMP = 128; // 128 I/Q samples + static constexpr unsigned NNODES = 128; // 128 nodes + static constexpr unsigned NBIASES = NNODES; // 128 nodes + static constexpr unsigned NWEIGHTS = NSAMP*NNODES; // KERNEL_SIZE*2*NNODES; // KERNEL_SIZE=7, I/Q paths, 64 nodes + + dense_w17_graph( void ) + { + + kk = kernel::create_object>(); + source(kk) = "dense_w17.cpp"; + runtime(kk) = 0.9; + repetition_count(kk) = 1; + + single_buffer(kk.in[1]); + single_buffer(kk.in[2]); + + // Connect inputs: + connect<> ( data_i, kk.in[0] ); dimensions(kk.in[0]) = {NNODES}; + connect ( weights, async(kk.in[1]) ); + connect ( biases, async(kk.in[2]) ); + + // Connect outputs: + connect<> ( kk.out[0], data_o ); dimensions(kk.out[0]) = {NNODES}; + + } +}; + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/gen_vectors.ipynb b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/gen_vectors.ipynb new file mode 100755 index 0000000000..88c2b5fb5a --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/gen_vectors.ipynb @@ -0,0 +1,681 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "bcdf2452-4c3b-4ce0-b019-cbe980967a1c", + "metadata": {}, + "source": [ + "# Testbench for `dense2()`" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "946f566a-c3f6-446f-aeb6-cb0055910900", + "metadata": {}, + "outputs": [], + "source": [ + "#\n", + "# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved.\n", + "# SPDX-License-Identifier: MIT\n", + "#\n", + "# Author: Chandra Sekar Balakrishnan" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "934e0796-0306-4ce9-9a92-598027c75f38", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-09-22 13:23:04.484684: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-09-22 13:23:04.488956: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-09-22 13:23:04.498253: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", + "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n", + "E0000 00:00:1758568984.512953 2362566 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", + "E0000 00:00:1758568984.517112 2362566 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", + "W0000 00:00:1758568984.530208 2362566 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1758568984.530220 2362566 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1758568984.530223 2362566 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1758568984.530225 2362566 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "2025-09-22 13:23:04.534336: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", + "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n" + ] + } + ], + "source": [ + "from tensorflow import keras\n", + "from tensorflow.keras.layers import Conv1D, MaxPooling1D, Flatten, Dense\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.model_selection import train_test_split\n", + "import h5py as h5\n", + "import numpy as np\n", + "# import os.path\n", + "import os\n", + "import vfs\n", + "import varray as va\n", + "\n", + "NITERATIONS = 4 # Number of AI Engine graph iterations" + ] + }, + { + "cell_type": "markdown", + "id": "5bdc7e83-3fd0-4fd0-99b5-7938816f0df2", + "metadata": {}, + "source": [ + "## Layer Definition" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "0c57f98d-1999-4b61-a129-e3dd1bd92677", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-09-22 13:23:09.213047: E external/local_xla/xla/stream_executor/cuda/cuda_platform.cc:51] failed call to cuInit: INTERNAL: CUDA error: Failed call to cuInit: UNKNOWN ERROR (303)\n" + ] + } + ], + "source": [ + "inputs = keras.Input(shape=(1024,2),name=\"input\")\n", + "x1 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w1\",activation='relu')(inputs)\n", + "x2 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w2\")(x1)\n", + "x3 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w3\",activation='relu')(x2)\n", + "x4 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w4\")(x3)\n", + "x5 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w5\",activation='relu')(x4)\n", + "x6 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w6\")(x5)\n", + "x7 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w7\",activation='relu')(x6)\n", + "x8 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w8\")(x7)\n", + "x9 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w9\",activation='relu')(x8)\n", + "x10 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w10\")(x9)\n", + "x11 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w11\",activation='relu')(x10)\n", + "x12 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w12\")(x11)\n", + "x13 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w13\",activation='relu')(x12)\n", + "x14 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"MaxPool1D_w14\")(x13)\n", + "x15 = Flatten(name=\"flatten_w15\")(x14) # 512 nodes\n", + "outputs = Dense(128, activation=\"selu\",name=\"dense_w16\")(x15) # Dense1\n", + "\n", + "model_stim = keras.Model(inputs=inputs,outputs=outputs)\n", + "model_stim.compile(optimizer=\"rmsprop\",\n", + " loss=\"sparse_categorical_crossentropy\",\n", + " metrics=[\"accuracy\"])\n", + "\n", + "\n", + "w1_weights = np.loadtxt('../conv1d_w1/w1_weights_trained.txt')\n", + "w1_weights = (w1_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w1_weights = np.reshape(w1_weights,(7,2,64))\n", + "w1_bias = np.loadtxt('../conv1d_w1/w1_bias_trained.txt')\n", + "w1_bias = (w1_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w3_weights = np.loadtxt('../conv1d_template/w3_weights_trained.txt')\n", + "w3_weights = (w3_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w3_weights = np.reshape(w3_weights,(7,64,64))\n", + "w3_bias = np.loadtxt('../conv1d_template/w3_bias_trained.txt')\n", + "w3_bias = (w3_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w5_weights = np.loadtxt('../conv1d_template/w5_weights_trained.txt')\n", + "w5_weights = (w5_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w5_weights = np.reshape(w5_weights,(7,64,64))\n", + "w5_bias = np.loadtxt('../conv1d_template/w5_bias_trained.txt')\n", + "w5_bias = (w5_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w7_weights = np.loadtxt('../conv1d_template/w7_weights_trained.txt')\n", + "w7_weights = (w7_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w7_weights = np.reshape(w7_weights,(7,64,64))\n", + "w7_bias = np.loadtxt('../conv1d_template/w7_bias_trained.txt')\n", + "w7_bias = (w7_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w9_weights = np.loadtxt('../conv1d_template/w9_weights_trained.txt')\n", + "w9_weights = (w9_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w9_weights = np.reshape(w9_weights,(7,64,64))\n", + "w9_bias = np.loadtxt('../conv1d_template/w9_bias_trained.txt')\n", + "w9_bias = (w9_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w11_weights = np.loadtxt('../conv1d_template/w11_weights_trained.txt')\n", + "w11_weights = (w11_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w11_weights = np.reshape(w11_weights,(7,64,64))\n", + "w11_bias = np.loadtxt('../conv1d_template/w11_bias_trained.txt')\n", + "w11_bias = (w11_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w13_weights = np.loadtxt('../conv1d_template/w13_weights_trained.txt')\n", + "w13_weights = (w13_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w13_weights = np.reshape(w13_weights,(7,64,64))\n", + "w13_bias = np.loadtxt('../conv1d_template/w13_bias_trained.txt')\n", + "w13_bias = (w13_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "# Dense1\n", + "w16_weights = np.loadtxt('../dense_w16/w16_weights_trained.txt')\n", + "w16_weights = (w16_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w16_weights = np.reshape(w16_weights,(512,128))\n", + "w16_bias = np.loadtxt('../dense_w16/w16_bias_trained.txt') \n", + "w16_bias = (w16_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "model_stim.get_layer(\"conv1D_w1\").set_weights((w1_weights,w1_bias))\n", + "model_stim.get_layer(\"conv1D_w3\").set_weights((w3_weights,w3_bias))\n", + "model_stim.get_layer(\"conv1D_w5\").set_weights((w5_weights,w5_bias))\n", + "model_stim.get_layer(\"conv1D_w7\").set_weights((w7_weights,w7_bias))\n", + "model_stim.get_layer(\"conv1D_w9\").set_weights((w9_weights,w9_bias))\n", + "model_stim.get_layer(\"conv1D_w11\").set_weights((w11_weights,w11_bias))\n", + "model_stim.get_layer(\"conv1D_w13\").set_weights((w13_weights,w13_bias))\n", + "model_stim.get_layer(\"dense_w16\").set_weights((w16_weights,w16_bias))\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "cd15a0ca-2889-4d90-bd0f-2e76c63c6c19", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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+       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
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Model: \"functional_1\"\n",
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┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ input_layer (InputLayer)        │ (None, 128)            │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_w17 (Dense)               │ (None, 128)            │        16,512 │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
+       "
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+       "
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+       "
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"file_handle = h5.File(data_file,'r')\n", + "myData = file_handle['X'][:] #1024x2 samples \n", + "myMods = file_handle['Y'][:] #mods \n", + "mySNRs = file_handle['Z'][:] #snrs \n", + "file_handle.close()\n", + "myData -= myData.mean()\n", + "myData /= myData.std()\n", + "X_train ,X_predict ,Y_train ,Y_test, Z_train, Z_test =train_test_split(myData, myMods, mySNRs, test_size=0.2, random_state=0)\n", + "X_predict = X_predict[:NITERATIONS]\n", + "X_predict = (X_predict.astype(\"bfloat16\")).astype(\"float32\")\n", + "X_inputs = model_stim.predict(X_predict,batch_size=1024)\n", + "X_inputs = (X_inputs.astype(\"bfloat16\")).astype(\"float32\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "53bf2899-8424-4f34-b305-dea322001c7c", + "metadata": {}, + "source": [ + "## Compute Golden Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "532b9d20-6698-420d-842a-b5c2ee89c114", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n" + ] + } + ], + "source": [ + "predict = model.predict(X_inputs, batch_size=1024)\n", + "predict = (predict.astype(\"bfloat16\")).astype(\"float32\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "b588f848-eb35-409a-94c0-9b9bf986383f", + "metadata": {}, + "source": [ + "## Store Layer Inputs" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "84a1f04f-7eca-4694-906f-245a9001fd25", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 128)\n", + "(4, 128)\n" + ] + } + ], + "source": [ + "# Create directory if it doesn't exist\n", + "data_i = X_inputs\n", + "if not os.path.exists('data'):\n", + " os.makedirs('data')\n", + "np.savetxt('data/data_i.txt',np.reshape(data_i,(-1,4)),fmt='%.12f %.12f %.12f %.12f')\n", + "print(X_inputs.shape)\n", + "print(data_i.shape)\n" + ] + }, + { + "cell_type": "markdown", + "id": "33ae9119-15e3-49ce-9ef8-ffab0c9ec411", + "metadata": {}, + "source": [ + "## Store Layer Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "de799f89-ecbe-4480-9dcf-3bb4e5402546", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 128)\n" + ] + } + ], + "source": [ + "data_o = predict\n", + "\n", + "np.savetxt('data/data_o.txt',np.reshape(data_o,(-1,4)),fmt='%.12f %.12f %.12f %0.12f')\n", + "print(data_o.shape)" + ] + }, + { + "cell_type": "markdown", + "id": "a078889b", + "metadata": {}, + "source": [ + "## Store Model weights and biases" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "71ff2c18", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(128, 128)\n", + "(128,)\n" + ] + } + ], + "source": [ + "# For transpose\n", + "w_weights= np.transpose(w_weights)\n", + "\n", + "print(w_weights.shape)\n", + "in_weights = np.vstack([np.reshape(w_weights,(-1,1))])\n", + "\n", + "np.savetxt('data/weights-rtp.txt',in_weights,fmt='%.12f')\n", + "\n", + "# Create bias\n", + "print(w_bias.shape)\n", + "in_biases = np.vstack([np.reshape(w_bias,(-1,1))])\n", + "np.savetxt('data/biases-rtp.txt',in_biases,fmt='%.12f')" + ] + }, + { + "cell_type": "markdown", + "id": "06a8af86", + "metadata": {}, + "source": [ + "## Run Vitis Functional Simulation" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "9986c78f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Compiling AIE Graph\n", + "Compilation directory: /group/fndprod/faisale/repo/internal/designs/radio-ml/aie/dense_w17_methodA\n", + "Compilation command: v++ -c --mode aie --config vfs_work/dense_w17_app_d8585a9a/dense_w17_app.cfg --work_dir vfs_work/dense_w17_app_d8585a9a/Work --output vfs_work/dense_w17_app_d8585a9a/libadf.a --target x86sim\n", + "Writing log to: /group/fndprod/faisale/repo/internal/designs/radio-ml/aie/dense_w17_methodA/vfs_work/dense_w17_app_d8585a9a/Work/logs/aie_x86sim.log\n", + "Please wait ...\n", + "\n", + "Compilation finished successfully.\n" + ] + } + ], + "source": [ + "dense_w17_graph = vfs.aieGraph(\n", + " input_file='dense_w17_app.cpp',\n", + " part=\"xc2ve3858-ssva2112-2MP-e-S\",\n", + " include_paths=['./','../utility'])\n", + "act_o = dense_w17_graph.run(va.array(np.reshape(data_i,(1,-1)),dtype=va.bfloat16), va.array(in_weights,dtype=va.bfloat16), va.array(in_biases,dtype=va.bfloat16))\n", + "act_o = np.array(act_o)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "66a9c0d5", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "data_o_reshaped = np.reshape(data_o,(-1))\n", + "err = data_o_reshaped-act_o\n", + "plt.plot(err)\n", + "plt.title(\"Error\")\n", + "plt.show()\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "my-venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/w17_bias_trained.txt b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w17_methodA/w17_bias_trained.txt new file mode 100644 index 0000000000..85bd94cd82 --- /dev/null +++ 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+-0.172851562500 +-0.084472656250 diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/Makefile b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/Makefile new file mode 100644 index 0000000000..2d520d60cf --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/Makefile @@ -0,0 +1,69 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +MY_APP := dense_w18_app +MY_SOURCES := ${MY_APP}.cpp dense_w18_graph.h dense_w18.h dense_w18.cpp + +PART ?= xc2ve3858-ssva2112-2MP-e-S + +AIE_OUTPUT := libadf.a + +AIE_FLAGS := --part=${PART} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} --include=../utility + +.PHONY: help clean x86com x86sim sim profile throughput + +help:: + @echo "Makefile Usage:" + @echo " make all" + @echo " Command to generate everything for this design" + @echo "" + @echo " make compile" + @echo " Run AIE compiler and build the design" + @echo "" + @echo " make profile" + @echo " Run AIE simulator with profiling and generate outputs suitable for Vitis Analyzer" + @echo "" + @echo " make analyze" + @echo " Run Vitis Analyzer to inspect results" + @echo "" + @echo " make throughput" + @echo " Evaluate the achieved throughput at the output" + @echo "" + @echo " make clean" + @echo " Command to remove all the generated files." + +all: ${AIE_OUTPUT} + +x86all: clean x86com x86sim + +${AIE_OUTPUT}: ${MY_SOURCES} + v++ --compile --config aie.cfg --mode aie --target=hw ${AIE_FLAGS} 2>&1 | tee log + +x86com: + v++ --compile --config aie.cfg --mode aie --target=x86sim ${AIE_FLAGS} 2>&1 | tee log + +sim: + aiesimulator 2>&1 | tee -a log + +x86sim: + x86simulator 2>&1 | tee -a log + +profile: + aiesimulator --online -wdb -text --profile 2>&1 | tee -a log + +trace: + aiesimulator --hang-detect-time=5000 --online -wdb -text 2>&1 | tee -a log + +clean: + rm -rf .Xil Work libadf.a + rm -rf aiesimulator_output* aiesimulator*.log + rm -rf x86simulator_output* + rm -rf log log* + rm -rf *.xpe *.elf *.db *.soln Map_* xnw* *.lp *.log .xil .Xil *.lp *.db *.log *.exe *.vcd *.json + rm -rf vitis_analyzer* pl_sample_counts* pl_sample_count_* + rm -rf temp ISS_RPC_SERVER_PORT .crashReporter .AIE_SIM_CMD_LINE_OPTIONS + rm -rf system*.* trdata.aiesim function_wdb_dir .wsdata _ide vfs_work .ipynb_checkpoints _ide + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/aie.cfg b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/aie.cfg new file mode 100644 index 0000000000..90679ce91a --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/aie.cfg @@ -0,0 +1,14 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +[aie] + +kernel-linting=true +xlopt=1 +verbose=true +pl-freq=625 +Xmapper=BufferOptLevel0 +Xchess="main:backend.mist2.maxfoldk=110" diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/data/biases-rtp.txt b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/data/biases-rtp.txt new file mode 100644 index 0000000000..cd97398382 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/data/biases-rtp.txt @@ -0,0 +1,24 @@ +-0.093261718750 +-0.080078125000 +-0.275390625000 +-0.129882812500 +-0.089843750000 +-0.065429687500 +0.079589843750 +0.028076171875 +-0.018066406250 +-0.114746093750 +0.071777343750 +0.123046875000 +-0.020385742188 +0.108886718750 +0.113769531250 +0.174804687500 +0.068847656250 +-0.163085937500 +-0.141601562500 +-0.166015625000 +-0.140625000000 +-0.118652343750 +-0.199218750000 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b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/dense3_model.m @@ -0,0 +1,44 @@ +% +% Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +% SPDX-License-Identifier: MIT +% +% Author: Faisal El-Shabani +%% +formatSpec = '%f'; +fileID = fopen('data/data_i.txt','r'); +data_i = fscanf(fileID,formatSpec); +fclose(fileID); +NITER = length(data_i)/128; +data_i = reshape(data_i,128,NITER); + +dense3_golden_output = zeros(24,NITER); +fileID = fopen('data/data_o.txt','r'); +dense3_golden_output = reshape(fscanf(fileID,formatSpec),size(dense3_golden_output)); +fclose(fileID); + + +fileID = fopen('w18_weights_trained.txt','r'); +weights = fscanf(fileID,formatSpec); +weights = reshape(weights,24,128); +weights = double(varray.bfloat16(weights)); +fclose(fileID); +fileID = fopen('w18_bias_trained.txt','r'); +biases = fscanf(fileID,formatSpec); +biases = double(varray.bfloat16(biases)); +fclose(fileID); +%% +dense3_actual_output = zeros(24,NITER); +for j=1:NITER + dense3_actual_output(:,j) = softmax(weights*data_i(:,j)+biases); +end +dense3_actual_output = double(varray.bfloat16(dense3_actual_output)); + +figure(1);plot(dense3_actual_output(:));hold on;plot(dense3_golden_output(:));hold off;legend('Actual','Golden');grid on; +figure(2);plot(reshape(dense3_actual_output,1,[])-reshape(dense3_golden_output,1,[]));grid on;title('error'); +error = max(abs(reshape(dense3_actual_output,1,[])-reshape(dense3_golden_output,1,[]))) + +function [sig_o] = softmax(sig_i) + exp_x = exp(sig_i - max(sig_i)); + sig_o = exp_x / sum(exp_x); + sig_o = varray.bfloat16(sig_o); +end \ No newline at end of file diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/dense_w18.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/dense_w18.cpp new file mode 100644 index 0000000000..479749c209 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/dense_w18.cpp @@ -0,0 +1,112 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#include +#include +#include +#include "dense_w18.h" + + +// ------------------------------------------------------------ +// Constructor +// ------------------------------------------------------------ + +template +dense_w18::dense_w18(void) +{ + aie::set_rounding(aie::rounding_mode::symmetric_inf); + aie::set_saturation(aie::saturation_mode::saturate); +} + +// ------------------------------------------------------------ +// softmax +// ------------------------------------------------------------ + +template +void dense_w18::softmax( aie::vector vecA, output_buffer& data_o ) +{ + auto itw = aie::begin_vector<8>(data_o); + aie::vector vecB; + aie::vector vecC; + aie::vector vecD; + aie::vector vecE; + + // Find maximum value: + TT_DATA max_val = aie::reduce_max(vecA); + + // Subtract max value from all values: + aie::accum accM; + aie::accum accA; + accM.from_vector(aie::broadcast(max_val)); + accA.from_vector(vecA); + vecB = (aie::sub(accA,accM)).to_vector(); + + // Start computation of exponentials of all input values: + aie::accum accB; + accB.from_vector(aie::broadcast(exp_B)); + accA = aie::mac(accB,vecB,exp_S); + vecC = accA.to_vector(); + + // Integer values should be in the range [0,16256], find outliers and set to zero: + aie::vector exp_i = aie::to_fixed(vecC,0); + aie::mask<32> msk_neg = aie::lt(exp_i,int16(0)); + aie::vector exp_bnd = aie::select(exp_i, aie::zeros(), msk_neg); + aie::mask<32> msk_pos = aie::gt(exp_bnd, int16(16256)); + exp_bnd = aie::select(exp_bnd, aie::zeros(), msk_pos); + + // Accumulate all vectors to determine scale factor: + vecD = exp_bnd.cast_to(); + TT_DATA scale_factor = aie::inv(aie::reduce_add(vecD)); + vecE = aie::mul(vecD,scale_factor); + // Write result: + *itw++ = vecE.extract<8>(0); + *itw++ = vecE.extract<8>(1); + *itw++ = vecE.extract<8>(2); +} +// ------------------------------------------------------------ +// Run +// ------------------------------------------------------------ + +template +void dense_w18::run( input_buffer& __restrict data_i, + const TT_DATA (&weights)[NWEIGHTS], + const TT_DATA (&biases)[NNODES], + output_buffer& __restrict data_o) +{ + auto p_data_i = aie::begin_vector_circular<64>(data_i); + auto p_weights = aie::begin_restrict_vector<64>(weights); + auto p_biases = aie::begin_restrict_vector<8>(biases); + auto p_data_o = aie::begin_restrict_vector<8>(data_o); + + aie::vector v_reg0 = aie::zeros(); + aie::vector bias_reg = aie::zeros();; + aie::accum acc_reg0,acc_reg1,acc_reg2,acc_reg3; + + for ( unsigned iter=0; iter < NNODES; iter+=4) + chess_loop_range(NNODES,) + chess_prepare_for_pipelining + { + acc_reg0 = mul_elem_64(*p_data_i++,*p_weights++); + acc_reg0 = mac_elem_64(*p_data_i++,*p_weights++,acc_reg0); + v_reg0.set(aie::reduce_add(acc_reg0.to_vector()),iter); + + acc_reg1 = mul_elem_64(*p_data_i++,*p_weights++); + acc_reg1 = mac_elem_64(*p_data_i++,*p_weights++,acc_reg1); + v_reg0.set(aie::reduce_add(acc_reg1.to_vector()),iter+1); + + acc_reg2 = mul_elem_64(*p_data_i++,*p_weights++); + acc_reg2 = mac_elem_64(*p_data_i++,*p_weights++,acc_reg2); + v_reg0.set(aie::reduce_add(acc_reg2.to_vector()),iter+2); + + acc_reg3 = mul_elem_64(*p_data_i++,*p_weights++); + acc_reg3 = mac_elem_64(*p_data_i++,*p_weights++,acc_reg3); + v_reg0.set(aie::reduce_add(acc_reg3.to_vector()),iter+3); + } + bias_reg.insert<8>(0,*p_biases++); + bias_reg.insert<8>(1,*p_biases++); + bias_reg.insert<8>(2,*p_biases++); + softmax(aie::add(v_reg0,bias_reg),data_o); +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/dense_w18.h b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/dense_w18.h new file mode 100644 index 0000000000..1d09e41bf9 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/dense_w18.h @@ -0,0 +1,44 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#pragma once + +#include +#include + +using namespace adf; + +template +class dense_w18 { +public: + typedef bfloat16 TT_DATA; + + // softmax Parameters + const TT_DATA exp_S = 185.0f; + const float exp_B = 16256.0f; + +private: + +public: + + // softmax + void softmax( aie::vector vecA, output_buffer& data_o); + + // Constructor: + dense_w18( void ); + + // Run: + void run( input_buffer& __restrict data_i, + const TT_DATA (&weights)[NWEIGHTS], + const TT_DATA (&biases)[NNODES], + output_buffer& __restrict data_o); + + static void registerKernelClass( void ) + { + REGISTER_FUNCTION( dense_w18::run ); + } +}; + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/dense_w18_app.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/dense_w18_app.cpp new file mode 100644 index 0000000000..5429ea675d --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/dense_w18_app.cpp @@ -0,0 +1,56 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#include +#include +#include "dense_w18_graph.h" +#include "read_file.h" + +class dut_graph : public graph { +public: + dense_w18_graph dut; + input_plio data_i; + output_plio data_o; + port weights; + port biases; + + dut_graph( void ) + { + data_i = input_plio::create("PLIO_i_0",plio_64_bits,"data/data_i.txt"); + connect<>(data_i.out[0],dut.data_i); + + connect<>(weights,dut.weights); + connect<>(biases,dut.biases); + + data_o = output_plio::create("PLIO_o_0",plio_64_bits,"data/data_o.txt"); + connect<>(dut.data_o,data_o.in[0]); + } +}; + +// Instantiate AIE graph: +dut_graph aie_dut; + +bfloat16 weights_array[3072]; +bfloat16 biases_array[24]; + + +// Initialize and run the graph: +int main(void) +{ + aie_dut.init(); + + // Read layer RTPs + read_file("data/weights-rtp.txt",weights_array); + read_file ("data/biases-rtp.txt", biases_array); + + aie_dut.update(aie_dut.weights,weights_array,3072); + aie_dut.update(aie_dut.biases,biases_array,24); + + aie_dut.run(4); + aie_dut.end(); + + return 0; +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/dense_w18_graph.h b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/dense_w18_graph.h new file mode 100644 index 0000000000..1d6ea739a1 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/dense_w18_graph.h @@ -0,0 +1,53 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#pragma once + +#include +#include "dense_w18.h" + +using namespace adf; + +// ------------------------------------------------------------ +// Top Level Graph +// ------------------------------------------------------------ + +class dense_w18_graph : public graph { +public: + // Declare Kernels + kernel kk; + + // Declare IOs + port data_i; + port data_o; + + port weights; + port biases; + + static constexpr unsigned NSAMP = 128; + static constexpr unsigned NNODES = 24; + static constexpr unsigned NWEIGHTS = NSAMP*NNODES; + static constexpr unsigned NBIASES = NNODES; + + dense_w18_graph( void ) + { + + kk = kernel::create_object>(); + source(kk) = "dense_w18.cpp"; + runtime(kk) = 0.9; + repetition_count(kk) = 1; + + single_buffer(kk.in[1]); + single_buffer(kk.in[2]); + + // Connect inputs: + connect<> ( data_i, kk.in[0] ); dimensions(kk.in[0]) = {NSAMP}; + connect ( weights, async(kk.in[1]) ); + connect ( biases, async(kk.in[2]) ); + connect<> ( kk.out[0], data_o ); dimensions(kk.out[0]) = {NNODES}; + + } +}; diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/gen_vectors.ipynb b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/gen_vectors.ipynb new file mode 100644 index 0000000000..471e699aee --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/gen_vectors.ipynb @@ -0,0 +1,691 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "bcdf2452-4c3b-4ce0-b019-cbe980967a1c", + "metadata": {}, + "source": [ + "# Testbench for `dense_w18()`" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "946f566a-c3f6-446f-aeb6-cb0055910900", + "metadata": {}, + "outputs": [], + "source": [ + "#\n", + "# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved.\n", + "# SPDX-License-Identifier: MIT\n", + "#\n", + "# Author: Faisal El-Shabani" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "934e0796-0306-4ce9-9a92-598027c75f38", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-08-22 07:49:07.971160: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-08-22 07:49:07.974937: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-08-22 07:49:07.983648: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", + "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n", + "E0000 00:00:1755870547.997366 3974680 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", + "E0000 00:00:1755870548.001731 3974680 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", + "W0000 00:00:1755870548.014144 3974680 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755870548.014158 3974680 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755870548.014161 3974680 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755870548.014163 3974680 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "2025-08-22 07:49:08.018310: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", + "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n" + ] + } + ], + "source": [ + "from tensorflow import keras\n", + "from tensorflow.keras.layers import Conv1D, MaxPooling1D, Flatten, Dense\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.model_selection import train_test_split\n", + "import h5py as h5\n", + "import numpy as np\n", + "import os.path\n", + "import vfs\n", + "import varray as va\n", + "\n", + "NITERATIONS = 4 # Number of AI Engine graph iterations" + ] + }, + { + "cell_type": "markdown", + "id": "5bdc7e83-3fd0-4fd0-99b5-7938816f0df2", + "metadata": {}, + "source": [ + "## Layer Definition" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "0c57f98d-1999-4b61-a129-e3dd1bd92677", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-08-22 07:49:24.377831: E external/local_xla/xla/stream_executor/cuda/cuda_platform.cc:51] failed call to cuInit: INTERNAL: CUDA error: Failed call to cuInit: UNKNOWN ERROR (303)\n" + ] + } + ], + "source": [ + "inputs = keras.Input(shape=(1024,2),name=\"input\")\n", + "x1 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w1\",activation='relu')(inputs)\n", + "x2 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w2\")(x1)\n", + "x3 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w3\",activation='relu')(x2)\n", + "x4 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w4\")(x3)\n", + "x5 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w5\",activation='relu')(x4)\n", + "x6 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w6\")(x5)\n", + "x7 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w7\",activation='relu')(x6)\n", + "x8 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w8\")(x7)\n", + "x9 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w9\",activation='relu')(x8)\n", + "x10 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w10\")(x9)\n", + "x11 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w11\",activation='relu')(x10)\n", + "x12 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w12\")(x11)\n", + "x13 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w13\",activation='relu')(x12)\n", + "x14 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"MaxPool1D_w14\")(x13)\n", + "x15 = Flatten(name=\"flatten_w15\")(x14)\n", + "x16 = Dense(128, activation=\"relu\",name=\"dense_w16\")(x15)\n", + "outputs = Dense(128, activation=\"relu\",name=\"dense_w17\")(x16)\n", + "model_stim = keras.Model(inputs=inputs,outputs=outputs)\n", + "model_stim.compile(optimizer=\"rmsprop\",\n", + " loss=\"sparse_categorical_crossentropy\",\n", + " metrics=[\"accuracy\"])\n", + "w1_weights = np.loadtxt('../conv1d_w1/w1_weights_trained.txt')\n", + "w1_weights = (w1_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w1_weights = np.reshape(w1_weights,(7,2,64))\n", + "w1_bias = np.loadtxt('../conv1d_w1/w1_bias_trained.txt')\n", + "w1_bias = (w1_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w3_weights = np.loadtxt('../conv1d_template/w3_weights_trained.txt')\n", + "w3_weights = (w3_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w3_weights = np.reshape(w3_weights,(7,64,64))\n", + "w3_bias = np.loadtxt('../conv1d_template/w3_bias_trained.txt')\n", + "w3_bias = (w3_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w5_weights = np.loadtxt('../conv1d_template/w5_weights_trained.txt')\n", + "w5_weights = (w5_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w5_weights = np.reshape(w5_weights,(7,64,64))\n", + "w5_bias = np.loadtxt('../conv1d_template/w5_bias_trained.txt')\n", + "w5_bias = (w5_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w7_weights = np.loadtxt('../conv1d_template/w7_weights_trained.txt')\n", + "w7_weights = (w7_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w7_weights = np.reshape(w7_weights,(7,64,64))\n", + "w7_bias = np.loadtxt('../conv1d_template/w7_bias_trained.txt')\n", + "w7_bias = (w7_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w9_weights = np.loadtxt('../conv1d_template/w9_weights_trained.txt')\n", + "w9_weights = (w9_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w9_weights = np.reshape(w9_weights,(7,64,64))\n", + "w9_bias = np.loadtxt('../conv1d_template/w9_bias_trained.txt')\n", + "w9_bias = (w9_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w11_weights = np.loadtxt('../conv1d_template/w11_weights_trained.txt')\n", + "w11_weights = (w11_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w11_weights = np.reshape(w11_weights,(7,64,64))\n", + "w11_bias = np.loadtxt('../conv1d_template/w11_bias_trained.txt')\n", + "w11_bias = (w11_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w13_weights = np.loadtxt('../conv1d_template/w13_weights_trained.txt')\n", + "w13_weights = (w13_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w13_weights = np.reshape(w13_weights,(7,64,64))\n", + "w13_bias = np.loadtxt('../conv1d_template/w13_bias_trained.txt')\n", + "w13_bias = (w13_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w16_weights = np.loadtxt('../dense_w16/w16_weights_trained.txt')\n", + "w16_weights = (w16_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w16_weights = np.reshape(w16_weights,(512,128))\n", + "w16_bias = np.loadtxt('../dense_w16/w16_bias_trained.txt')\n", + "w16_bias = (w16_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w17_weights = np.loadtxt('../dense_w17/w17_weights_trained.txt')\n", + "w17_weights = (w17_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w17_weights = np.reshape(w17_weights,(128,128))\n", + "w17_bias = np.loadtxt('../dense_w17/w17_bias_trained.txt')\n", + "w17_bias = (w17_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "model_stim.get_layer(\"conv1D_w1\").set_weights((w1_weights,w1_bias))\n", + "model_stim.get_layer(\"conv1D_w3\").set_weights((w3_weights,w3_bias))\n", + "model_stim.get_layer(\"conv1D_w5\").set_weights((w5_weights,w5_bias))\n", + "model_stim.get_layer(\"conv1D_w7\").set_weights((w7_weights,w7_bias))\n", + "model_stim.get_layer(\"conv1D_w9\").set_weights((w9_weights,w9_bias))\n", + "model_stim.get_layer(\"conv1D_w11\").set_weights((w11_weights,w11_bias))\n", + "model_stim.get_layer(\"conv1D_w13\").set_weights((w13_weights,w13_bias))\n", + "model_stim.get_layer(\"dense_w16\").set_weights((w16_weights,w16_bias))\n", + "model_stim.get_layer(\"dense_w17\").set_weights((w17_weights,w17_bias))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "cd15a0ca-2889-4d90-bd0f-2e76c63c6c19", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
Model: \"functional\"\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1mModel: \"functional\"\u001b[0m\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ input (InputLayer)              │ (None, 1024, 2)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w1 (Conv1D)              │ (None, 1024, 64)       │           960 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w2 (MaxPooling1D)    │ (None, 512, 64)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w3 (Conv1D)              │ (None, 512, 64)        │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w4 (MaxPooling1D)    │ (None, 256, 64)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w5 (Conv1D)              │ (None, 256, 64)        │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w6 (MaxPooling1D)    │ (None, 128, 64)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w7 (Conv1D)              │ (None, 128, 64)        │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w8 (MaxPooling1D)    │ (None, 64, 64)         │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w9 (Conv1D)              │ (None, 64, 64)         │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w10 (MaxPooling1D)   │ (None, 32, 64)         │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w11 (Conv1D)             │ (None, 32, 64)         │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w12 (MaxPooling1D)   │ (None, 16, 64)         │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w13 (Conv1D)             │ (None, 16, 64)         │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ MaxPool1D_w14 (MaxPooling1D)    │ (None, 8, 64)          │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ flatten_w15 (Flatten)           │ (None, 512)            │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_w16 (Dense)               │ (None, 128)            │        65,664 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_w17 (Dense)               │ (None, 128)            │        16,512 │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
+       "
\n" + ], + "text/plain": [ + "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n", + "┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\n", + "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n", + "│ input (\u001b[38;5;33mInputLayer\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1024\u001b[0m, \u001b[38;5;34m2\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w1 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1024\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m960\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w2 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w3 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w4 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w5 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w6 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w7 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w8 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w9 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w10 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w11 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w12 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w13 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ MaxPool1D_w14 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ flatten_w15 (\u001b[38;5;33mFlatten\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dense_w16 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m65,664\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dense_w17 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m16,512\u001b[0m │\n", + "└─────────────────────────────────┴────────────────────────┴───────────────┘\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Total params: 255,552 (998.25 KB)\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m255,552\u001b[0m (998.25 KB)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Trainable params: 255,552 (998.25 KB)\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m255,552\u001b[0m (998.25 KB)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Non-trainable params: 0 (0.00 B)\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "model_stim.summary()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "53441463", + "metadata": {}, + "outputs": [], + "source": [ + "inputs = keras.Input(shape=([128]),name=\"input_layer\")\n", + "outputs = Dense(24, activation=\"softmax\",name=\"dense_w18\")(inputs)\n", + "model = keras.Model(inputs=inputs,outputs=outputs)\n", + "model.compile(optimizer=\"rmsprop\",\n", + " loss=\"sparse_categorical_crossentropy\",\n", + " metrics=[\"accuracy\"])\n", + "w_weights = np.loadtxt('w18_weights_trained.txt')\n", + "w_weights = (w_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w_weights = np.reshape(w_weights,(128,24))\n", + "w_bias = np.loadtxt('w18_bias_trained.txt')\n", + "w_bias = (w_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "model.set_weights((w_weights,w_bias))" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "1f5d4822", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
Model: \"functional_1\"\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1mModel: \"functional_1\"\u001b[0m\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ input_layer (InputLayer)        │ (None, 128)            │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_w18 (Dense)               │ (None, 24)             │         3,096 │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
+       "
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"file_handle = h5.File(data_file,'r')\n", + "myData = file_handle['X'][:] #1024x2 samples \n", + "myMods = file_handle['Y'][:] #mods \n", + "mySNRs = file_handle['Z'][:] #snrs \n", + "file_handle.close()\n", + "X_train ,X_predict ,Y_train ,Y_test, Z_train, Z_test =train_test_split(myData, myMods, mySNRs, test_size=0.2, random_state=0)\n", + "X_predict = X_predict[:NITERATIONS]\n", + "X_predict = (X_predict.astype(\"bfloat16\")).astype(\"float32\")\n", + "X_inputs = model_stim.predict(X_predict,batch_size=1024)\n", + "X_inputs = (X_inputs.astype(\"bfloat16\")).astype(\"float32\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "53bf2899-8424-4f34-b305-dea322001c7c", + "metadata": {}, + "source": [ + "## Compute Golden Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "532b9d20-6698-420d-842a-b5c2ee89c114", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 38ms/step\n" + ] + } + ], + "source": [ + "predict = model.predict(X_inputs, batch_size=1024)\n", + "predict = (predict.astype(\"bfloat16\")).astype(\"float32\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "b588f848-eb35-409a-94c0-9b9bf986383f", + "metadata": {}, + "source": [ + "## Store Layer Inputs" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "84a1f04f-7eca-4694-906f-245a9001fd25", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 128)\n", + "(4, 128)\n" + ] + } + ], + "source": [ + "# Create directory if it doesn't exist\n", + "data_i = X_inputs\n", + "if not os.path.exists('data'):\n", + " os.makedirs('data')\n", + "np.savetxt('data/data_i.txt',np.reshape(data_i,(-1,4)),fmt='%.12f %.12f %.12f %.12f')\n", + "print(X_inputs.shape)\n", + "print(data_i.shape)\n" + ] + }, + { + "cell_type": "markdown", + "id": "33ae9119-15e3-49ce-9ef8-ffab0c9ec411", + "metadata": {}, + "source": [ + "## Store Layer Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "de799f89-ecbe-4480-9dcf-3bb4e5402546", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 24)\n" + ] + } + ], + "source": [ + "data_o = predict\n", + "\n", + "np.savetxt('data/data_o.txt',np.reshape(data_o,(-1,4)),fmt='%.12f %.12f %.12f %.12f')\n", + "print(data_o.shape)" + ] + }, + { + "cell_type": "markdown", + "id": "a078889b", + "metadata": {}, + "source": [ + "## Store Model weights and biases" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "61671230", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(128, 24)\n", + "(3072, 1)\n", + "(24, 1)\n" + ] + } + ], + "source": [ + "print(w_weights.shape)\n", + "\n", + "weights = np.reshape(np.transpose(w_weights),(-1,1))\n", + "np.savetxt('data/weights-rtp.txt',weights,fmt='%.12f')\n", + "print(weights.shape)\n", + "\n", + "biases = np.reshape(w_bias,(-1,1))\n", + "np.savetxt('data/biases-rtp.txt',biases,fmt='%.12f')\n", + "print(biases.shape)\n" + ] + }, + { + "cell_type": "markdown", + "id": "06a8af86", + "metadata": {}, + "source": [ + "## Run Vitis Functional Simulation" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "9986c78f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Compiling AIE Graph\n", + "Compilation directory: /group/fndprod/faisale/repo/internal/designs/radio-ml/aie/dense_w18/vfs_work/dense_w18_app_11549624\n", + "Compilation command: v++ -c --mode aie --config vfs_work/dense_w18_app_11549624/dense_w18_app.cfg --work_dir vfs_work/dense_w18_app_11549624/Work --output vfs_work/dense_w18_app_11549624/libadf.a --target x86sim\n", + "Writing log to: /group/fndprod/faisale/repo/internal/designs/radio-ml/aie/dense_w18/vfs_work/dense_w18_app_11549624/Work/logs/aie_x86sim.log\n", + "Please wait ...\n", + "\n", + "Compilation finished successfully.\n", + "Loaded AIEGraph\n" + ] + } + ], + "source": [ + "dense_w18_graph = vfs.aieGraph(\n", + " input_file='dense_w18_app.cpp',\n", + " part=\"xc2ve3858-ssva2112-2MP-e-S\",\n", + " include_paths=['./','../utility'])\n", + "act_o = dense_w18_graph.run(va.array(np.reshape(data_i,(1,-1)),dtype=va.bfloat16),va.array(weights,dtype=va.bfloat16),va.array(biases,dtype=va.bfloat16))\n", + "act_o = np.array(act_o)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "66a9c0d5", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The history saving thread hit an unexpected error (OperationalError('database is locked')).History will not be written to the database.\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "data_o_reshaped = np.reshape(data_o,(-1))\n", + "err = data_o_reshaped-act_o\n", + "plt.plot(err)\n", + "plt.title(\"Error\")\n", + "plt.show()\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "my-venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/w18_bias_trained.txt b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/dense_w18/w18_bias_trained.txt new file mode 100644 index 0000000000..cd97398382 --- /dev/null +++ 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All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +MY_APP := max_pool1d_w4_app +MY_SOURCES := ${MY_APP}.cpp max_pool1d_graph_template.h max_pool1d_template.h max_pool1d_template.cpp + +PART ?= xc2ve3858-ssva2112-2MP-e-S + +AIE_OUTPUT := libadf.a + +AIE_FLAGS := --part=${PART} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} --include=../utility + +.PHONY: help clean x86com x86sim sim profile throughput + +help:: + @echo "Makefile Usage:" + @echo " make all" + @echo " Command to generate everything for this design" + @echo "" + @echo " make compile" + @echo " Run AIE compiler and build the design" + @echo "" + @echo " make profile" + @echo " Run AIE simulator with profiling and generate outputs suitable for Vitis Analyzer" + @echo "" + @echo " make analyze" + @echo " Run Vitis Analyzer to inspect results" + @echo "" + @echo " make throughput" + @echo " Evaluate the achieved throughput at the output" + @echo "" + @echo " make clean" + @echo " Command to remove all the generated files." + +all: ${AIE_OUTPUT} + +x86all: clean x86com x86sim + +${AIE_OUTPUT}: ${MY_SOURCES} + v++ --compile --config aie.cfg --mode aie --target=hw ${AIE_FLAGS} 2>&1 | tee log + +x86com: + v++ --compile --config aie.cfg --mode aie --target=x86sim ${AIE_FLAGS} 2>&1 | tee log + +sim: + aiesimulator 2>&1 | tee -a log + +x86sim: + x86simulator 2>&1 | tee -a log + +profile: + aiesimulator --online -wdb -text --profile 2>&1 | tee -a log + +trace: + aiesimulator --hang-detect-time=5000 --online -wdb -text 2>&1 | tee -a log + +clean: + rm -rf .Xil Work libadf.a + rm -rf aiesimulator_output* aiesimulator*.log + rm -rf x86simulator_output* + rm -rf log log* + rm -rf *.xpe *.elf *.db *.soln Map_* xnw* *.lp *.log .xil .Xil *.lp *.db *.log *.exe *.vcd *.json + rm -rf vitis_analyzer* pl_sample_counts* pl_sample_count_* + rm -rf temp ISS_RPC_SERVER_PORT .crashReporter .AIE_SIM_CMD_LINE_OPTIONS + rm -rf system*.* trdata.aiesim function_wdb_dir .wsdata _ide vfs_work .ipynb_checkpoints sig_o_sim.txt _ide + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_template/aie.cfg b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_template/aie.cfg new file mode 100755 index 0000000000..83dee9bb25 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_template/aie.cfg @@ -0,0 +1,13 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +[aie] + +kernel-linting=true +xlopt=1 +verbose=true +pl-freq=625 +Xmapper=BufferOptLevel9 \ No newline at end of file diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_template/data/data_i.txt b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_template/data/data_i.txt new file mode 100755 index 0000000000..260472eaf5 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_template/data/data_i.txt @@ -0,0 +1,32768 @@ +0.0000000000 0.0000000000 0.0000000000 0.0000000000 +0.0000000000 0.3085937500 0.0000000000 0.0000000000 +0.0000000000 0.0000000000 0.0000000000 0.0000000000 +0.0000000000 0.0000000000 0.0000000000 0.0000000000 +0.0000000000 0.0000000000 0.0000000000 0.0000000000 +0.0000000000 0.0000000000 0.0000000000 0.0000000000 +0.0000000000 0.0000000000 0.0000000000 0.0319824219 +0.0000000000 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for `max_pool1d_w4()`" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "946f566a-c3f6-446f-aeb6-cb0055910900", + "metadata": {}, + "outputs": [], + "source": [ + "#\n", + "# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved.\n", + "# SPDX-License-Identifier: MIT\n", + "#\n", + "# Author: Faisal El-Shabani" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "934e0796-0306-4ce9-9a92-598027c75f38", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-08-22 07:49:24.063571: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-08-22 07:49:24.067766: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-08-22 07:49:24.077178: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", + "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n", + "E0000 00:00:1755870564.091840 3975565 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", + "E0000 00:00:1755870564.096489 3975565 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", + "W0000 00:00:1755870564.109728 3975565 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755870564.109740 3975565 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755870564.109744 3975565 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755870564.109746 3975565 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "2025-08-22 07:49:24.114255: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", + "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n" + ] + } + ], + "source": [ + "from tensorflow import keras\n", + "from tensorflow.keras.layers import Conv1D, MaxPooling1D\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.model_selection import train_test_split\n", + "import h5py as h5\n", + "import numpy as np\n", + "import os.path\n", + "import vfs\n", + "import varray as va\n", + "\n", + "NITERATIONS = 4 # Number of AI Engine graph iterations" + ] + }, + { + "cell_type": "markdown", + "id": "5bdc7e83-3fd0-4fd0-99b5-7938816f0df2", + "metadata": {}, + "source": [ + "## Layer Definition" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "0c57f98d-1999-4b61-a129-e3dd1bd92677", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-08-22 07:49:32.554452: E external/local_xla/xla/stream_executor/cuda/cuda_platform.cc:51] failed call to cuInit: INTERNAL: CUDA error: Failed call to cuInit: UNKNOWN ERROR (303)\n" + ] + } + ], + "source": [ + "inputs = keras.Input(shape=(1024,2),name=\"input\")\n", + "x1 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1d_w1\",activation='relu')(inputs)\n", + "x2 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w2\")(x1)\n", + "outputs = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1d_w3\",activation='relu')(x2)\n", + "model_stim = keras.Model(inputs=inputs,outputs=outputs)\n", + "w1_weights = np.loadtxt('../conv1d_w1/w1_weights_trained.txt')\n", + "w1_weights = (w1_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w1_bias = np.loadtxt('../conv1d_w1/w1_bias_trained.txt')\n", + "w1_bias = (w1_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "w1_weights = np.reshape(w1_weights,(7,2,64))\n", + "w3_weights = np.loadtxt('../conv1d_template/w3_weights_trained.txt')\n", + "w3_weights = (w3_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w3_bias = np.loadtxt('../conv1d_template/w3_bias_trained.txt')\n", + "w3_bias = (w3_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "w3_weights = np.reshape(w3_weights,(7,64,64))\n", + "model_stim.get_layer(\"conv1d_w3\").set_weights((w3_weights,w3_bias))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "cd15a0ca-2889-4d90-bd0f-2e76c63c6c19", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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+       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
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+       "│ input (InputLayer)              │ (None, 1024, 2)        │             0 │\n",
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Model: \"functional_1\"\n",
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┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ input_layer (InputLayer)        │ (None, 512, 64)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w4 (MaxPooling1D)    │ (None, 256, 64)        │             0 │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
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+       "
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"file_handle = h5.File(data_file,'r')\n", + "myData = file_handle['X'][:] #1024x2 samples \n", + "myMods = file_handle['Y'][:] #mods \n", + "mySNRs = file_handle['Z'][:] #snrs \n", + "file_handle.close()\n", + "X_train ,X_predict ,Y_train ,Y_test, Z_train, Z_test =train_test_split(myData, myMods, mySNRs, test_size=0.2, random_state=0)\n", + "X_predict = X_predict[:NITERATIONS]\n", + "X_predict = (X_predict.astype(\"bfloat16\")).astype(\"float32\")\n", + "X_inputs = model_stim.predict(X_predict,batch_size=1024)\n", + "X_inputs = (X_inputs.astype(\"bfloat16\")).astype(\"float32\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "53bf2899-8424-4f34-b305-dea322001c7c", + "metadata": {}, + "source": [ + "## Compute Golden Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "532b9d20-6698-420d-842a-b5c2ee89c114", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 37ms/step\n" + ] + } + ], + "source": [ + "predict = model.predict(X_inputs, batch_size=1024)\n", + "predict = (predict.astype(\"bfloat16\")).astype(\"float32\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "b588f848-eb35-409a-94c0-9b9bf986383f", + "metadata": {}, + "source": [ + "## Store Layer Inputs" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "84a1f04f-7eca-4694-906f-245a9001fd25", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 512, 64)\n", + "(4, 512, 64)\n" + ] + } + ], + "source": [ + "# Create directory if it doesn't exist\n", + "data_i = X_inputs\n", + "if not os.path.exists('data'):\n", + " os.makedirs('data')\n", + "np.savetxt('data/data_i.txt',np.reshape(data_i,(-1,4)),fmt='%.12f %.12f %.12f %.12f')\n", + "print(X_inputs.shape)\n", + "print(data_i.shape)\n" + ] + }, + { + "cell_type": "markdown", + "id": "33ae9119-15e3-49ce-9ef8-ffab0c9ec411", + "metadata": {}, + "source": [ + "## Store Layer Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "de799f89-ecbe-4480-9dcf-3bb4e5402546", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 256, 64)\n" + ] + } + ], + "source": [ + "data_o = predict\n", + "\n", + "np.savetxt('data/data_o.txt',np.reshape(data_o,(-1,4)),fmt='%.12f %.12f %.12f %.12f')\n", + "print(data_o.shape)" + ] + }, + { + "cell_type": "markdown", + "id": "06a8af86", + "metadata": {}, + "source": [ + "## Run Vitis Functional Simulation" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "9986c78f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Compiling AIE Graph\n", + "Compilation directory: /group/fndprod/faisale/repo/internal/designs/radio-ml/aie/max_pool1d_template/vfs_work/max_pool1d_w4_app_8ac1a6e3\n", + "Compilation command: v++ -c --mode aie --config vfs_work/max_pool1d_w4_app_8ac1a6e3/max_pool1d_w4_app.cfg --work_dir vfs_work/max_pool1d_w4_app_8ac1a6e3/Work --output vfs_work/max_pool1d_w4_app_8ac1a6e3/libadf.a --target x86sim\n", + "Writing log to: /group/fndprod/faisale/repo/internal/designs/radio-ml/aie/max_pool1d_template/vfs_work/max_pool1d_w4_app_8ac1a6e3/Work/logs/aie_x86sim.log\n", + "Please wait ...\n", + "\n", + "Compilation finished successfully.\n", + "Loaded AIEGraph\n" + ] + } + ], + "source": [ + "max_pool1d_w4_graph = vfs.aieGraph(\n", + " input_file='max_pool1d_w4_app.cpp',\n", + " part=\"xc2ve3858-ssva2112-2MP-e-S\",\n", + " include_paths=['./','../utility'])\n", + "act_o = max_pool1d_w4_graph.run(va.array(np.reshape(data_i,(1,-1)),dtype=va.bfloat16))\n", + "act_o = np.array(act_o)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "66a9c0d5", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "data_o_reshaped = np.reshape(data_o,(-1))\n", + "err = data_o_reshaped-act_o\n", + "plt.plot(err)\n", + "plt.title(\"Error\")\n", + "plt.show()\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "my-venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_template/max_pool1d_graph_template.h b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_template/max_pool1d_graph_template.h new file mode 100755 index 0000000000..eb50c06200 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_template/max_pool1d_graph_template.h @@ -0,0 +1,48 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#pragma once + +#include +#include "max_pool1d_template.h" +#include "ceil_constexpr.h" + +using namespace adf; + +// ------------------------------------------------------------ +// Top Level Graph +// ------------------------------------------------------------ + +template +class max_pool1d_graph_template : public graph { +public: + // Declare Kernels + kernel kk; + + // Declare IOs + port data_i; + port data_o; + + static constexpr double BUFFER_SIZE_MULTIPLE = NSAMP*NNODES*2*2*2.0/65536; // Ratio of output buffer size to local tile memory + // *2 -> 2 bytes per sample + // *2 -> ping-pong + // *2 -> Margin to ensure input buffer uses only two banks (same applies for output buffer) + // 65536 -> Local tile memory (64KB) + static constexpr unsigned NSPLIT = ceil_constexpr(BUFFER_SIZE_MULTIPLE); // Process incoming samples in NSPLIT chunks so IO buffers fit in local tile memory. Return type of ceil in c++17 is not constexpr. + + max_pool1d_graph_template( void ) + { + kk = kernel::create_object>(); + source(kk) = "max_pool1d_template.cpp"; + runtime(kk) = 0.9; + repetition_count(kk) = NSPLIT; + + // Connect inputs: + connect<> ( data_i, kk.in[0] ); dimensions(kk.in[0]) = {NSAMP/NSPLIT *NNODES}; + connect<> ( kk.out[0], data_o ); dimensions(kk.out[0]) = {NSAMP/NSPLIT/2*NNODES}; + } +}; + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_template/max_pool1d_template.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_template/max_pool1d_template.cpp new file mode 100755 index 0000000000..1841579d47 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_template/max_pool1d_template.cpp @@ -0,0 +1,50 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#include +#include + +#include "max_pool1d_template.h" + +// ------------------------------------------------------------ +// Constructor +// ------------------------------------------------------------ + +template +max_pool1d_template::max_pool1d_template() +{ + aie::set_rounding(aie::rounding_mode::symmetric_inf); + aie::set_saturation(aie::saturation_mode::saturate); +} + +// ------------------------------------------------------------ +// Run +// ------------------------------------------------------------ + +template +void max_pool1d_template::run( input_buffer& __restrict data_i, + output_buffer& __restrict data_o) +{ + + aie::vector data_i_0; + aie::vector data_i_1; + + // Loop over some samples: + //for ( unsigned n=0; n < NSPLIT; n++) + //{ + auto p_data_i = aie::begin_vector<64>(data_i); + auto p_data_o = aie::begin_vector<64>(data_o); + // Loop over some nodes and samples + for ( unsigned ii=0; ii < NNODES*NSAMP/64/2/NSPLIT; ii++) + chess_loop_range(NNODES*NSAMP/64/2/NSPLIT,) + chess_prepare_for_pipelining + { + data_i_0 = *p_data_i++; + data_i_1 = *p_data_i++; + *p_data_o++ = aie::max(data_i_0,data_i_1); + } + //} +} \ No newline at end of file diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_template/max_pool1d_template.h b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_template/max_pool1d_template.h new file mode 100755 index 0000000000..b949b211c2 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_template/max_pool1d_template.h @@ -0,0 +1,33 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#pragma once + +#include +#include + +using namespace adf; + +template +class max_pool1d_template { +public: + typedef bfloat16 TT_DATA; +private: + +public: + // Constructor: + max_pool1d_template( void ); + + // Run: + void run( input_buffer& __restrict data_i, + output_buffer& __restrict data_o); + + static void registerKernelClass( void ) + { + REGISTER_FUNCTION( max_pool1d_template::run ); + } +}; + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_template/max_pool1d_w4_app.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_template/max_pool1d_w4_app.cpp new file mode 100755 index 0000000000..70e1aac68a --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_template/max_pool1d_w4_app.cpp @@ -0,0 +1,36 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#include "max_pool1d_graph_template.h" + +class dut_graph : public graph { + max_pool1d_graph_template<512,64> dut; // NSAMP=512, NNODES=64 +public: + input_plio data_i; + output_plio data_o; + + dut_graph( void ) + { + data_i = input_plio::create("PLIO_i_0",plio_64_bits,"data/data_i.txt"); + connect<>(data_i.out[0],dut.data_i); + + data_o = output_plio::create("PLIO_o_0",plio_64_bits,"data/data_o.txt"); + connect<>(dut.data_o,data_o.in[0]); + } +}; + +// Instantiate AIE graph: +dut_graph aie_dut; + +// Initialize and run the graph: +int main(void) +{ + aie_dut.init(); + aie_dut.run(4); + aie_dut.end(); + + return 0; +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_template/max_pool1d_w4_gmio_app.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_template/max_pool1d_w4_gmio_app.cpp new file mode 100755 index 0000000000..44dd6419e0 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_template/max_pool1d_w4_gmio_app.cpp @@ -0,0 +1,86 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#include +#include +#include "max_pool1d_graph_template.h" +#include "read_file.h" + +class dut_graph : public graph { + max_pool1d_graph_template<512,64> dut; // NSAMP=512, NNODES=64 +public: + input_gmio data_i; + output_gmio data_o; + + dut_graph( void ) + { + /* Setup the GMIO to connect the AIE to global memory */ + // logical name of the gmio, burst length 64, 128 or 256 bytes), required bandwidth in MB/s + data_i = input_gmio::create("gmioIn",256,5000); + connect<>(data_i.out[0],dut.data_i); + + data_o = output_gmio::create("gmioOut",256,2500); + connect<>(dut.data_o,data_o.in[0]); + } +}; + +// Instantiate AIE graph: +dut_graph aie_dut; + +static constexpr unsigned ITERATIONS = 4; +static constexpr unsigned SAMPLES_PER_ITERATION = 512*64; +static constexpr unsigned BYTES_PER_SAMPLE = 2; +static constexpr unsigned SIG_I_BYTES = SAMPLES_PER_ITERATION * BYTES_PER_SAMPLE * ITERATIONS; +static constexpr unsigned SIG_O_BYTES = SAMPLES_PER_ITERATION/2 * BYTES_PER_SAMPLE * ITERATIONS; + +bfloat16 data_i_array[SAMPLES_PER_ITERATION*ITERATIONS]; + +// Initialize and run the graph: +int main(void) +{ + std::ofstream output_File("sig_o_sim.txt"); + + + aie_dut.init(); + + // Read input data + read_file("data/data_i.txt",data_i_array); + + bfloat16* sig_i_array=(bfloat16*)GMIO::malloc(SIG_I_BYTES); + bfloat16* sig_o_array=(bfloat16*)GMIO::malloc(SIG_O_BYTES); + + /* Copy the samples to the buffer */ + memcpy(sig_i_array, data_i_array, SIG_I_BYTES); + + aie_dut.data_i.gm2aie_nb(sig_i_array, SIG_I_BYTES); + + aie_dut.run(ITERATIONS); + + aie_dut.data_o.aie2gm_nb(sig_o_array, SIG_O_BYTES); + aie_dut.data_o.wait(); + + /* Post-processing */ + int count=0; + for(int i=0; i&1 | tee log + +x86com: + v++ --compile --config aie.cfg --mode aie --target=x86sim ${AIE_FLAGS} 2>&1 | tee log + +sim: + aiesimulator 2>&1 | tee -a log + +x86sim: + x86simulator 2>&1 | tee -a log + +profile: + aiesimulator --online -wdb -text --profile 2>&1 | tee -a log + +trace: + aiesimulator --hang-detect-time=5000 --online -wdb -text 2>&1 | tee -a log + +clean: + rm -rf .Xil Work libadf.a + rm -rf aiesimulator_output* aiesimulator*.log + rm -rf x86simulator_output* + rm -rf log log* + rm -rf *.xpe *.elf *.db *.soln Map_* xnw* *.lp *.log .xil .Xil *.lp *.db *.log *.exe *.vcd *.json + rm -rf vitis_analyzer* pl_sample_counts* pl_sample_count_* + rm -rf temp ISS_RPC_SERVER_PORT .crashReporter .AIE_SIM_CMD_LINE_OPTIONS + rm -rf system*.* trdata.aiesim function_wdb_dir .wsdata _ide vfs_work .ipynb_checkpoints + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_w2/aie.cfg b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_w2/aie.cfg new file mode 100755 index 0000000000..bfd3f4aee8 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_w2/aie.cfg @@ -0,0 +1,13 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +[aie] + +kernel-linting=true +xlopt=1 +verbose=true +pl-freq=625 +Xmapper=BufferOptLevel9 diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_w2/data/data_i.txt b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_w2/data/data_i.txt new file mode 100644 index 0000000000..63a83bae64 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_w2/data/data_i.txt @@ -0,0 +1,65536 @@ +0.000000000000 0.000000000000 0.000000000000 0.000000000000 +0.000000000000 0.000000000000 0.000000000000 0.000000000000 +0.000000000000 0.000000000000 0.000000000000 0.000000000000 +0.000000000000 0.000000000000 0.000000000000 0.000000000000 +0.000000000000 0.000000000000 0.000000000000 0.042724609375 +0.060302734375 0.116210937500 0.177734375000 0.225585937500 +0.135742187500 0.177734375000 0.104003906250 0.056884765625 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"cell_type": "code", + "execution_count": 19, + "id": "946f566a-c3f6-446f-aeb6-cb0055910900", + "metadata": {}, + "outputs": [], + "source": [ + "#\n", + "# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved.\n", + "# SPDX-License-Identifier: MIT\n", + "#\n", + "# Author: Faisal El-Shabani" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "934e0796-0306-4ce9-9a92-598027c75f38", + "metadata": {}, + "outputs": [], + "source": [ + "from tensorflow import keras\n", + "from tensorflow.keras.layers import Conv1D, MaxPooling1D\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.model_selection import train_test_split\n", + "import h5py as h5\n", + "import numpy as np\n", + "import os.path\n", + "import vfs\n", + "import varray as va\n", + "\n", + "NITERATIONS = 4 # Number of AI Engine graph iterations" + ] + }, + { + "cell_type": "markdown", + "id": "5bdc7e83-3fd0-4fd0-99b5-7938816f0df2", + "metadata": {}, + "source": [ + "## Layer Definition" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "0c57f98d-1999-4b61-a129-e3dd1bd92677", + "metadata": {}, + "outputs": [], + "source": [ + "inputs = keras.Input(shape=(1024,2),name=\"input\")\n", + "outputs = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1d_w1\",activation='relu')(inputs)\n", + "model_stim = keras.Model(inputs=inputs,outputs=outputs)\n", + "w_weights = np.loadtxt('../conv1d_w1/w1_weights_trained.txt')\n", + "w_weights = (w_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w_bias = np.loadtxt('../conv1d_w1/w1_bias_trained.txt')\n", + "w_bias = (w_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "w_weights = np.reshape(w_weights,(7,2,64))\n", + "model_stim.set_weights((w_weights,w_bias))" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "cd15a0ca-2889-4d90-bd0f-2e76c63c6c19", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
Model: \"functional_2\"\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1mModel: \"functional_2\"\u001b[0m\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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+       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ input (InputLayer)              │ (None, 1024, 2)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1d_w1 (Conv1D)              │ (None, 1024, 64)       │           960 │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
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+       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
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"file_handle = h5.File(data_file,'r')\n", + "myData = file_handle['X'][:] #1024x2 samples \n", + "myMods = file_handle['Y'][:] #mods \n", + "mySNRs = file_handle['Z'][:] #snrs \n", + "file_handle.close()\n", + "X_train ,X_predict ,Y_train ,Y_test, Z_train, Z_test =train_test_split(myData, myMods, mySNRs, test_size=0.2, random_state=0)\n", + "X_predict = X_predict[:NITERATIONS]\n", + "X_predict = (X_predict.astype(\"bfloat16\")).astype(\"float32\")\n", + "X_inputs = model_stim.predict(X_predict,batch_size=1024)\n", + "X_inputs = (X_inputs.astype(\"bfloat16\")).astype(\"float32\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "53bf2899-8424-4f34-b305-dea322001c7c", + "metadata": {}, + "source": [ + "## Compute Golden Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "532b9d20-6698-420d-842a-b5c2ee89c114", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n" + ] + } + ], + "source": [ + "predict = model.predict(X_inputs, batch_size=1024)\n", + "predict = (predict.astype(\"bfloat16\")).astype(\"float32\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "b588f848-eb35-409a-94c0-9b9bf986383f", + "metadata": {}, + "source": [ + "## Store Layer Inputs" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "84a1f04f-7eca-4694-906f-245a9001fd25", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 1024, 64)\n", + "(4, 64, 1024)\n" + ] + } + ], + "source": [ + "# Create directory if it doesn't exist\n", + "data_i = np.transpose(X_inputs,axes=(0,2,1))\n", + "if not os.path.exists('data'):\n", + " os.makedirs('data')\n", + "np.savetxt('data/data_i.txt',np.reshape(data_i,(-1,4)),fmt='%.12f %.12f %.12f %.12f')\n", + "print(X_inputs.shape)\n", + "print(data_i.shape)\n" + ] + }, + { + "cell_type": "markdown", + "id": "33ae9119-15e3-49ce-9ef8-ffab0c9ec411", + "metadata": {}, + "source": [ + "## Store Layer Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "de799f89-ecbe-4480-9dcf-3bb4e5402546", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 512, 64)\n" + ] + } + ], + "source": [ + "data_o = predict\n", + "\n", + "np.savetxt('data/data_o.txt',np.reshape(data_o,(-1,4)),fmt='%.12f %.12f %.12f %.12f')\n", + "print(data_o.shape)" + ] + }, + { + "cell_type": "markdown", + "id": "06a8af86", + "metadata": {}, + "source": [ + "## Run Vitis Functional Simulation" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "9986c78f", + "metadata": {}, + "outputs": [], + "source": [ + "max_pool1d_w2_graph = vfs.aieGraph(\n", + " input_file='max_pool1d_w2_app.cpp',\n", + " part=\"xc2ve3858-ssva2112-2MP-e-S\",\n", + " include_paths=['./'])\n", + "act_o = max_pool1d_w2_graph.run(va.array(np.reshape(data_i,(1,-1)),dtype=va.bfloat16))\n", + "act_o = np.array(act_o)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "66a9c0d5", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "data_o_reshaped = np.reshape(data_o,(-1))\n", + "err = data_o_reshaped-act_o\n", + "plt.plot(err)\n", + "plt.title(\"Error\")\n", + "plt.show()\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "my-venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_w2/max_pool1d_w2.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_w2/max_pool1d_w2.cpp new file mode 100755 index 0000000000..2380df5188 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_w2/max_pool1d_w2.cpp @@ -0,0 +1,65 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#include +#include +#include + +#include "max_pool1d_w2.h" + +// ------------------------------------------------------------ +// Constructor +// ------------------------------------------------------------ + +max_pool1d_w2::max_pool1d_w2(void) +{ + aie::set_rounding(aie::rounding_mode::symmetric_inf); + aie::set_saturation(aie::saturation_mode::saturate); +} + +// ------------------------------------------------------------ +// Run +// ------------------------------------------------------------ + +void max_pool1d_w2::run( input_buffer& __restrict data_i, + output_buffer& __restrict data_o) +{ + + aie::vector data_i_0; + aie::vector data_i_1; + aie::vector data_i_2; + aie::vector data_i_3; + + aie::vector data_o_0; + aie::vector data_o_1; + + auto p_data_i_0 = aie::begin_vector<32>(data_i); // Works on even rows + auto p_data_i_1 = aie::begin_vector<32>(data_i.data()+NSAMP); // Works on odd rows + auto p_data_o = aie::begin_vector<64>(data_o); + // Loop over nodes + for ( unsigned ii=0; ii < NNODES/NSPLIT/2; ii++) + { + // Loop over samples + for ( unsigned jj=0; jj < NSAMP/64; jj++) + chess_prepare_for_pipelining + { + data_i_0 = *p_data_i_0++; + data_i_1 = *p_data_i_0++; + auto [v1, v2] = aie::interleave_unzip(data_i_0,data_i_1,1); + data_o_0 = aie::max(v1,v2); + + data_i_2 = *p_data_i_1++; + data_i_3 = *p_data_i_1++; + auto [v3, v4] = aie::interleave_unzip(data_i_2,data_i_3,1); + data_o_1 = aie::max(v3,v4); + + auto rv = aie::interleave_zip(data_o_0,data_o_1,1); + *p_data_o++ = aie::concat(rv.first,rv.second); + } + p_data_i_0+=NSAMP/32; + p_data_i_1+=NSAMP/32; + } +} \ No newline at end of file diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_w2/max_pool1d_w2.h b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_w2/max_pool1d_w2.h new file mode 100755 index 0000000000..94487b64e2 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_w2/max_pool1d_w2.h @@ -0,0 +1,42 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#pragma once + +#include +#include + +using namespace adf; + +class max_pool1d_w2 { +public: + typedef bfloat16 TT_DATA; + static constexpr unsigned NSAMP = 1024; // 1024 from each node + static constexpr unsigned NNODES = 64; // 64 nodes + static constexpr double BUFFER_SIZE_MULTIPLE = NSAMP*NNODES*2*2*2.0/65536; // Ratio of IO buffer size to local tile memory + // 22/16 -> Bandwidth and kernel input buffer grows by a factor of 22/16 due to nature of processing. + // *2 -> 2 bytes per sample + // *2 -> ping-pong + // *2 -> Margin to ensure input buffer uses only two banks (same applies for output buffer) + // 65536 -> Local tile memory (64KB) + static constexpr unsigned NSPLIT = BUFFER_SIZE_MULTIPLE; // Process incoming samples in NSPLIT chunks so IO buffers fit in local tile memory. + +private: + +public: + // Constructor: + max_pool1d_w2( void ); + + // Run: + void run( input_buffer& __restrict data_i, + output_buffer& __restrict data_o); + + static void registerKernelClass( void ) + { + REGISTER_FUNCTION( max_pool1d_w2::run ); + } +}; + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_w2/max_pool1d_w2_app.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_w2/max_pool1d_w2_app.cpp new file mode 100755 index 0000000000..7a9fd0de52 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_w2/max_pool1d_w2_app.cpp @@ -0,0 +1,36 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#include "max_pool1d_w2_graph.h" + +class dut_graph : public graph { + max_pool1d_w2_graph dut; +public: + input_plio data_i; + output_plio data_o; + + dut_graph( void ) + { + data_i = input_plio::create("PLIO_i_0",plio_64_bits,"data/data_i.txt"); + connect<>(data_i.out[0],dut.data_i); + + data_o = output_plio::create("PLIO_o_0",plio_64_bits,"data/data_o.txt"); + connect<>(dut.data_o,data_o.in[0]); + } +}; + +// Instantiate AIE graph: +dut_graph aie_dut; + +// Initialize and run the graph: +int main(void) +{ + aie_dut.init(); + aie_dut.run(4); + aie_dut.end(); + + return 0; +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_w2/max_pool1d_w2_graph.h b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_w2/max_pool1d_w2_graph.h new file mode 100755 index 0000000000..1874bf01f0 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/max_pool1d_w2/max_pool1d_w2_graph.h @@ -0,0 +1,56 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#pragma once + +#include +#include "max_pool1d_w2.h" + +using namespace adf; + +// ------------------------------------------------------------ +// Top Level Graph +// ------------------------------------------------------------ + +class max_pool1d_w2_graph : public graph { +public: + // Declare Kernels + kernel kk; + + port data_i; + port data_o; + shared_buffer MT_output; + + max_pool1d_w2_graph( void ) + { + // Tiling parameters for outputs + tiling_parameters bdw_output = { .buffer_dimension = {max_pool1d_w2::NNODES,max_pool1d_w2::NSAMP/2}, + .tiling_dimension = {2,32}, + .offset = {0,0}, + .tile_traversal = {{.dimension=1, .stride=32,.wrap=max_pool1d_w2::NSAMP/2/32}, + {.dimension=0, .stride=2, .wrap=max_pool1d_w2::NNODES/2}} + }; + tiling_parameters bdr_output = { .buffer_dimension = {max_pool1d_w2::NNODES*max_pool1d_w2::NSAMP/2}, + .tiling_dimension = {max_pool1d_w2::NNODES*max_pool1d_w2::NSAMP/2}, + .offset = {0} }; + MT_output = shared_buffer::create({max_pool1d_w2::NNODES*max_pool1d_w2::NSAMP/2}, 1, 1); + write_access(MT_output.in[0]) = tiling(bdw_output); + read_access(MT_output.out[0]) = tiling(bdr_output); + repetition_count(MT_output) = 1; + + kk = kernel::create_object(); + source(kk) = "max_pool1d_w2.cpp"; + runtime(kk) = 0.9; + repetition_count(kk) = max_pool1d_w2::NSPLIT; + + // Connect inputs: + connect<> ( data_i, kk.in[0] ); dimensions(kk.in[0]) = {max_pool1d_w2::NSAMP /max_pool1d_w2::NSPLIT*max_pool1d_w2::NNODES}; + connect<> ( kk.out[0], MT_output.in[0] ); + connect<> ( MT_output.out[0], data_o ); dimensions(kk.out[0]) = {max_pool1d_w2::NSAMP/2/max_pool1d_w2::NSPLIT*max_pool1d_w2::NNODES}; + + } +}; + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/radioml_top/Makefile b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/radioml_top/Makefile new file mode 100755 index 0000000000..d2d68b1d0d --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/radioml_top/Makefile @@ -0,0 +1,84 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +USE_JSON := true + +MY_APP := radioml_top_app +MY_SOURCES := ${MY_APP}.cpp radioml_top_graph.h ../conv1d_w1/conv1d_w1.h ../conv1d_w1/conv1d_w1.cpp ../conv1d_w1/conv1d_w1_graph.h ../max_pool1d_w2/max_pool1d_w2.h ../max_pool1d_w2/max_pool1d_w2.cpp ../max_pool1d_w2/max_pool1d_w2_graph.h ../conv1d_template/conv1d_template.cpp ../conv1d_template/conv1d_template.h ../conv1d_template/conv1d_graph_template.h ../max_pool1d_template/max_pool1d_template.cpp ../max_pool1d_template/max_pool1d_template.h ../max_pool1d_template/max_pool1d_graph_template.h ../dense_w16/dense_w16_graph.h ../dense_w16/dense_w16.h ../dense_w16/dense_w16.cpp ../dense_w17/dense_w17_graph.h ../dense_w17/dense_w17.h ../dense_w17/dense_w17.cpp ../dense_w18/dense_w18_graph.h ../dense_w18/dense_w18.h ../dense_w18/dense_w18.cpp + +PART ?= xc2ve3858-ssva2112-2MP-e-S + +INCLUDES := --include=../conv1d_w1 \ + --include=../max_pool1d_w2 \ + --include=../conv1d_template \ + --include=../max_pool1d_template \ + --include=../dense_w16 \ + --include=../dense_w17 \ + --include=../dense_w18 \ + --include=../utility + +AIE_OUTPUT := libadf.a + +AIE_FLAGS := --part=${PART} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ${INCLUDES} + +ifeq (${USE_JSON},true) + AIE_FLAGS := ${AIE_FLAGS} --aie.constraints=${MY_APP}_aie_routed.aiecst +endif + +.PHONY: help clean x86com x86sim sim profile throughput + +help:: + @echo "Makefile Usage:" + @echo " make all" + @echo " Command to generate everything for this design" + @echo "" + @echo " make compile" + @echo " Run AIE compiler and build the design" + @echo "" + @echo " make profile" + @echo " Run AIE simulator with profiling and generate outputs suitable for Vitis Analyzer" + @echo "" + @echo " make analyze" + @echo " Run Vitis Analyzer to inspect results" + @echo "" + @echo " make throughput" + @echo " Evaluate the achieved throughput at the output" + @echo "" + @echo " make clean" + @echo " Command to remove all the generated files." + +all: ${AIE_OUTPUT} + +x86all: clean x86com x86sim + +${AIE_OUTPUT}: ${MY_SOURCES} + v++ --compile --config aie.cfg --mode aie --target=hw ${AIE_FLAGS} 2>&1 | tee log + +x86com: + v++ --compile --config aie.cfg --mode aie --target=x86sim ${AIE_FLAGS} 2>&1 | tee log + +sim: + aiesimulator 2>&1 | tee -a log + +x86sim: + x86simulator 2>&1 | tee -a log + +profile: + aiesimulator --online -wdb -text --profile 2>&1 | tee -a log + +trace: + aiesimulator --hang-detect-time=5000 --online -wdb -text 2>&1 | tee -a log + +clean: + rm -rf .Xil Work libadf.a + rm -rf aiesimulator_output* aiesimulator*.log + rm -rf x86simulator_output* + rm -rf log log* + rm -rf *.xpe *.elf *.db *.soln Map_* xnw* *.lp *.log .xil .Xil *.lp *.db *.log *.exe *.vcd *.json + rm -rf vitis_analyzer* pl_sample_counts* pl_sample_count_* + rm -rf temp ISS_RPC_SERVER_PORT .crashReporter .AIE_SIM_CMD_LINE_OPTIONS + rm -rf system*.* trdata.aiesim function_wdb_dir .wsdata _ide vfs_work .ipynb_checkpoints data_o_sim.txt + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/radioml_top/aie.cfg b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/radioml_top/aie.cfg new file mode 100755 index 0000000000..9770be027f --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/radioml_top/aie.cfg @@ -0,0 +1,13 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. 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"bcdf2452-4c3b-4ce0-b019-cbe980967a1c", + "metadata": {}, + "source": [ + "# Testbench for `radioml_top()`" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "946f566a-c3f6-446f-aeb6-cb0055910900", + "metadata": {}, + "outputs": [], + "source": [ + "#\n", + "# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved.\n", + "# SPDX-License-Identifier: MIT\n", + "#\n", + "# Author: Faisal El-Shabani" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "934e0796-0306-4ce9-9a92-598027c75f38", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-09-11 18:31:53.245190: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-09-11 18:31:53.249482: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-09-11 18:31:53.258766: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", + "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n", + "E0000 00:00:1757637113.273665 445476 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", + "E0000 00:00:1757637113.277968 445476 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", + "W0000 00:00:1757637113.291130 445476 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1757637113.291145 445476 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1757637113.291148 445476 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1757637113.291150 445476 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "2025-09-11 18:31:53.295306: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", + "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n" + ] + } + ], + "source": [ + "from tensorflow import keras\n", + "from tensorflow.keras.layers import Conv1D, MaxPooling1D, Flatten, Dense\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.model_selection import train_test_split\n", + "import h5py as h5\n", + "import numpy as np\n", + "import os.path\n", + "import json\n", + "import vfs\n", + "import varray as va\n", + "\n", + "NITERATIONS = 8 # Number of AI Engine graph iterations" + ] + }, + { + "cell_type": "markdown", + "id": "5bdc7e83-3fd0-4fd0-99b5-7938816f0df2", + "metadata": {}, + "source": [ + "## Layer Definition" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "0c57f98d-1999-4b61-a129-e3dd1bd92677", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-09-11 18:31:58.168410: E external/local_xla/xla/stream_executor/cuda/cuda_platform.cc:51] failed call to cuInit: INTERNAL: CUDA error: Failed call to cuInit: UNKNOWN ERROR (303)\n" + ] + } + ], + "source": [ + "inputs = keras.Input(shape=(1024,2),name=\"input\")\n", + "x1 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w1\",activation='relu')(inputs)\n", + "x2 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w2\")(x1)\n", + "x3 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w3\",activation='relu')(x2)\n", + "x4 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w4\")(x3)\n", + "x5 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w5\",activation='relu')(x4)\n", + "x6 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w6\")(x5)\n", + "x7 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w7\",activation='relu')(x6)\n", + "x8 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w8\")(x7)\n", + "x9 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w9\",activation='relu')(x8)\n", + "x10 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w10\")(x9)\n", + "x11 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w11\",activation='relu')(x10)\n", + "x12 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w12\")(x11)\n", + "x13 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w13\",activation='relu')(x12)\n", + "x14 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w14\")(x13)\n", + "x15 = Flatten(name=\"flatten_w15\")(x14)\n", + "x16 = Dense(128, activation=\"selu\",name=\"dense_w16\")(x15)\n", + "x17 = Dense(128, activation=\"selu\",name=\"dense_w17\")(x16)\n", + "outputs = Dense(24, activation=\"softmax\",name=\"dense_w18\")(x17)\n", + "\n", + "model_stim = keras.Model(inputs=inputs,outputs=outputs)\n", + "model_stim.compile(optimizer=\"rmsprop\",\n", + " loss=\"sparse_categorical_crossentropy\",\n", + " metrics=[\"accuracy\"])\n", + "w1_weights = np.loadtxt('../conv1d_w1/w1_weights_trained.txt')\n", + "w1_weights = (w1_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w1_weights = np.reshape(w1_weights,(7,2,64))\n", + "w1_bias = np.loadtxt('../conv1d_w1/w1_bias_trained.txt')\n", + "w1_bias = (w1_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w3_weights = np.loadtxt('../conv1d_template/w3_weights_trained.txt')\n", + "w3_weights = (w3_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w3_weights = np.reshape(w3_weights,(7,64,64))\n", + "w3_bias = np.loadtxt('../conv1d_template/w3_bias_trained.txt')\n", + "w3_bias = (w3_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w5_weights = np.loadtxt('../conv1d_template/w5_weights_trained.txt')\n", + "w5_weights = (w5_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w5_weights = np.reshape(w5_weights,(7,64,64))\n", + "w5_bias = np.loadtxt('../conv1d_template/w5_bias_trained.txt')\n", + "w5_bias = (w5_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w7_weights = np.loadtxt('../conv1d_template/w7_weights_trained.txt')\n", + "w7_weights = (w7_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w7_weights = np.reshape(w7_weights,(7,64,64))\n", + "w7_bias = np.loadtxt('../conv1d_template/w7_bias_trained.txt')\n", + "w7_bias = (w7_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w9_weights = np.loadtxt('../conv1d_template/w9_weights_trained.txt')\n", + "w9_weights = (w9_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w9_weights = np.reshape(w9_weights,(7,64,64))\n", + "w9_bias = np.loadtxt('../conv1d_template/w9_bias_trained.txt')\n", + "w9_bias = (w9_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w11_weights = np.loadtxt('../conv1d_template/w11_weights_trained.txt')\n", + "w11_weights = (w11_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w11_weights = np.reshape(w11_weights,(7,64,64))\n", + "w11_bias = np.loadtxt('../conv1d_template/w11_bias_trained.txt')\n", + "w11_bias = (w11_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w13_weights = np.loadtxt('../conv1d_template/w13_weights_trained.txt')\n", + "w13_weights = (w13_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w13_weights = np.reshape(w13_weights,(7,64,64))\n", + "w13_bias = np.loadtxt('../conv1d_template/w13_bias_trained.txt')\n", + "w13_bias = (w13_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w16_weights = np.loadtxt('../dense_w16/w16_weights_trained.txt')\n", + "w16_weights = (w16_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w16_weights = np.reshape(w16_weights,(512,128))\n", + "w16_bias = np.loadtxt('../dense_w16/w16_bias_trained.txt')\n", + "w16_bias = (w16_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w17_weights = np.loadtxt('../dense_w17/w17_weights_trained.txt')\n", + "w17_weights = (w17_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w17_weights = np.reshape(w17_weights,(128,128))\n", + "w17_bias = np.loadtxt('../dense_w17/w17_bias_trained.txt')\n", + "w17_bias = (w17_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "w18_weights = np.loadtxt('../dense_w18/w18_weights_trained.txt')\n", + "w18_weights = (w18_weights.astype(\"bfloat16\")).astype(\"float32\")\n", + "w18_weights = np.reshape(w18_weights,(128,24))\n", + "w18_bias = np.loadtxt('../dense_w18/w18_bias_trained.txt')\n", + "w18_bias = (w18_bias.astype(\"bfloat16\")).astype(\"float32\")\n", + "\n", + "model_stim.get_layer(\"conv1D_w1\").set_weights((w1_weights,w1_bias))\n", + "model_stim.get_layer(\"conv1D_w3\").set_weights((w3_weights,w3_bias))\n", + "model_stim.get_layer(\"conv1D_w5\").set_weights((w5_weights,w5_bias))\n", + "model_stim.get_layer(\"conv1D_w7\").set_weights((w7_weights,w7_bias))\n", + "model_stim.get_layer(\"conv1D_w9\").set_weights((w9_weights,w9_bias))\n", + "model_stim.get_layer(\"conv1D_w11\").set_weights((w11_weights,w11_bias))\n", + "model_stim.get_layer(\"conv1D_w13\").set_weights((w13_weights,w13_bias))\n", + "model_stim.get_layer(\"dense_w16\").set_weights((w16_weights,w16_bias))\n", + "model_stim.get_layer(\"dense_w17\").set_weights((w17_weights,w17_bias))\n", + "model_stim.get_layer(\"dense_w18\").set_weights((w18_weights,w18_bias))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "cd15a0ca-2889-4d90-bd0f-2e76c63c6c19", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
Model: \"functional\"\n",
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+       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
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+       "│ input (InputLayer)              │ (None, 1024, 2)        │             0 │\n",
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(\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w3 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w4 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w5 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w6 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w7 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w8 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w9 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w10 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w11 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w12 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w13 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w14 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ flatten_w15 (\u001b[38;5;33mFlatten\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dense_w16 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m65,664\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dense_w17 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m16,512\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dense_w18 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m24\u001b[0m) │ \u001b[38;5;34m3,096\u001b[0m │\n", + "└─────────────────────────────────┴────────────────────────┴───────────────┘\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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"file_handle.close()\n", + "modulation_classes = json.load(open(os.environ[\"RADIOML_DATA\"] + \"classes-fixed.json\", 'r'))\n", + "myDataReshaped = myData.reshape(24,26,4096,1024,2) #(modulation,SNR,frame,I,Q)\n", + "myModsReshaped = myMods.reshape(24,26,4096,24) #(modulation,SNR,frame,modulation_onehot)\n", + "X_predict = myDataReshaped[:NITERATIONS,25,0,:,:]\n", + "X_predict = (X_predict.astype(\"bfloat16\")).astype(\"float32\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "53bf2899-8424-4f34-b305-dea322001c7c", + "metadata": {}, + "source": [ + "## Compute Golden Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "532b9d20-6698-420d-842a-b5c2ee89c114", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 162ms/step\n" + ] + } + ], + "source": [ + "predict = model_stim.predict(X_predict,batch_size=1024)\n", + "predict = (predict.astype(\"bfloat16\")).astype(\"float32\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "b588f848-eb35-409a-94c0-9b9bf986383f", + "metadata": {}, + "source": [ + "## Store Layer Inputs" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "84a1f04f-7eca-4694-906f-245a9001fd25", + "metadata": {}, + "outputs": [], + "source": [ + "# Create directory if it doesn't exist\n", + "if not os.path.exists('data'):\n", + " os.makedirs('data')\n", + "data_iq = np.reshape(X_predict,(-1,1))\n", + "np.savetxt('data/data_iq.txt',np.reshape(data_iq,(-1,4)),fmt='%.12f %.12f %.12f %.12f')\n" + ] + }, + { + "cell_type": "markdown", + "id": "33ae9119-15e3-49ce-9ef8-ffab0c9ec411", + "metadata": {}, + "source": [ + "## Store Layer Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "de799f89-ecbe-4480-9dcf-3bb4e5402546", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(8, 24)\n" + ] + } + ], + "source": [ + "data_o = np.vstack(predict)\n", + "\n", + "np.savetxt('data/data_o.txt',np.reshape(data_o,(-1,4)),fmt='%.12f %.12f %.12f %.12f')\n", + "print(data_o.shape)\n" + ] + }, + { + "cell_type": "markdown", + "id": "9dd2e257", + "metadata": {}, + "source": [ + "## Store Model weights and biases" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "c099a8a4", + "metadata": {}, + "outputs": [], + "source": [ + "w1_weights = np.reshape(w1_weights,(-1,1))\n", + "w1_bias = np.reshape(w1_bias,(-1,1))\n", + "np.savetxt('data/w1_weights-rtp.txt',w1_weights,fmt='%.12f')\n", + "np.savetxt('data/w1_biases-rtp.txt',w1_bias,fmt='%.12f')\n", + "\n", + "weights = np.empty((7*64*64),dtype='bfloat16')\n", + "counter=0\n", + "for x in range(0,64,8):\n", + " for y in range(0,64,8):\n", + " for z in range(0,7):\n", + " weights[counter*64:(counter+1)*64] = np.reshape(w3_weights[z,y:y+8,x:x+8],(-1))\n", + " counter+=1\n", + "w3_weights = np.reshape(weights,(-1,1))\n", + "np.savetxt('data/w3_weights-rtp.txt',w3_weights,fmt='%.12f')\n", + "w3_bias = np.vstack([np.reshape(w3_bias,(-1,1))])\n", + "np.savetxt('data/w3_biases-rtp.txt',w3_bias,fmt='%.12f')\n", + "\n", + "weights = np.empty((7*64*64),dtype='bfloat16')\n", + "counter=0\n", + "for x in range(0,64,8):\n", + " for y in range(0,64,8):\n", + " for z in range(0,7):\n", + " weights[counter*64:(counter+1)*64] = np.reshape(w5_weights[z,y:y+8,x:x+8],(-1))\n", + " counter+=1\n", + "w5_weights = np.reshape(weights,(-1,1))\n", + "np.savetxt('data/w5_weights-rtp.txt',w5_weights,fmt='%.12f')\n", + "w5_bias = np.vstack([np.reshape(w5_bias,(-1,1))])\n", + "np.savetxt('data/w5_biases-rtp.txt',w5_bias,fmt='%.12f')\n", + "\n", + "weights = np.empty((7*64*64),dtype='bfloat16')\n", + "counter=0\n", + "for x in range(0,64,8):\n", + " for y in range(0,64,8):\n", + " for z in range(0,7):\n", + " weights[counter*64:(counter+1)*64] = np.reshape(w7_weights[z,y:y+8,x:x+8],(-1))\n", + " counter+=1\n", + "w7_weights = np.reshape(weights,(-1,1))\n", + "np.savetxt('data/w7_weights-rtp.txt',w7_weights,fmt='%.12f')\n", + "w7_bias = np.vstack([np.reshape(w7_bias,(-1,1))])\n", + "np.savetxt('data/w7_biases-rtp.txt',w7_bias,fmt='%.12f')\n", + "\n", + "weights = np.empty((7*64*64),dtype='bfloat16')\n", + "counter=0\n", + "for x in range(0,64,8):\n", + " for y in range(0,64,8):\n", + " for z in range(0,7):\n", + " weights[counter*64:(counter+1)*64] = np.reshape(w9_weights[z,y:y+8,x:x+8],(-1))\n", + " counter+=1\n", + "w9_weights = np.reshape(weights,(-1,1))\n", + "np.savetxt('data/w9_weights-rtp.txt',w9_weights,fmt='%.12f')\n", + "w9_bias = np.vstack([np.reshape(w9_bias,(-1,1))])\n", + "np.savetxt('data/w9_biases-rtp.txt',w9_bias,fmt='%.12f')\n", + "\n", + "weights = np.empty((7*64*64),dtype='bfloat16')\n", + "counter=0\n", + "for x in range(0,64,8):\n", + " for y in range(0,64,8):\n", + " for z in range(0,7):\n", + " weights[counter*64:(counter+1)*64] = np.reshape(w11_weights[z,y:y+8,x:x+8],(-1))\n", + " counter+=1\n", + "w11_weights = np.reshape(weights,(-1,1))\n", + "np.savetxt('data/w11_weights-rtp.txt',w11_weights,fmt='%.12f')\n", + "w11_bias = np.vstack([np.reshape(w11_bias,(-1,1))])\n", + "np.savetxt('data/w11_biases-rtp.txt',w11_bias,fmt='%.12f')\n", + "\n", + "weights = np.empty((7*64*64),dtype='bfloat16')\n", + "counter=0\n", + "for x in range(0,64,8):\n", + " for y in range(0,64,8):\n", + " for z in range(0,7):\n", + " weights[counter*64:(counter+1)*64] = np.reshape(w13_weights[z,y:y+8,x:x+8],(-1))\n", + " counter+=1\n", + "w13_weights = np.reshape(weights,(-1,1))\n", + "np.savetxt('data/w13_weights-rtp.txt',w13_weights,fmt='%.12f')\n", + "w13_bias = np.vstack([np.reshape(w13_bias,(-1,1))])\n", + "np.savetxt('data/w13_biases-rtp.txt',w13_bias,fmt='%.12f')\n", + "\n", + "# dense_w16: Munge weights to make compute more efficient\n", + "tmp = np.transpose(w16_weights[:,:64])\n", + "w16_0_weights = np.array([],dtype='bfloat16')\n", + "for i in range(tmp.shape[1]):\n", + " w16_0_weights = np.concat((w16_0_weights,np.diag(np.roll(tmp,-i,axis=1))))\n", + "np.savetxt('data/w16_0_weights-rtp.txt',w16_0_weights,fmt='%.12f')\n", + "tmp = np.transpose(w16_weights[:,64:])\n", + "w16_1_weights = np.array([],dtype='bfloat16')\n", + "for i in range(tmp.shape[1]):\n", + " w16_1_weights = np.concat((w16_1_weights,np.diag(np.roll(tmp,-i,axis=1))))\n", + "np.savetxt('data/w16_1_weights-rtp.txt',w16_1_weights,fmt='%.12f')\n", + "w16_bias = np.reshape(w16_bias,(-1,1))\n", + "np.savetxt('data/w16_biases-rtp.txt',w16_bias,fmt='%.12f')\n", + "\n", + "# dense_w17: Munge weights to make compute more efficient\n", + "tmp1 = np.transpose(w17_weights[:,:64])\n", + "tmp2 = np.transpose(w17_weights[:,64:])\n", + "weights = np.array([],dtype='bfloat16')\n", + "for i in range(tmp1.shape[1]):\n", + " weights = np.concat((weights,np.diag(np.roll(tmp1,-i,axis=1))))\n", + " weights = np.concat((weights,np.diag(np.roll(tmp2,-i,axis=1))))\n", + "w17_weights = weights\n", + "np.savetxt('data/w17_weights-rtp.txt',w17_weights,fmt='%.12f')\n", + "w17_bias = np.reshape(w17_bias,(-1,1))\n", + "np.savetxt('data/w17_biases-rtp.txt',w17_bias,fmt='%.12f')\n", + "\n", + "# dense_w18: \n", + "w18_weights = np.reshape(np.transpose(w18_weights),(-1,1))\n", + "np.savetxt('data/w18_weights-rtp.txt',w18_weights,fmt='%.12f')\n", + "w18_bias = np.reshape(w18_bias,(-1,1))\n", + "np.savetxt('data/w18_biases-rtp.txt',w18_bias,fmt='%.12f')\n" + ] + }, + { + "cell_type": "markdown", + "id": "e464a910", + "metadata": {}, + "source": [ + "### Store modulation_classes for host program" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "67904073", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['OOK', '4ASK', '8ASK', 'BPSK', 'QPSK', '8PSK', '16PSK', '32PSK', '16APSK', '32APSK', '64APSK', '128APSK', '16QAM', '32QAM', '64QAM', '128QAM', '256QAM', 'AM-SSB-WC', 'AM-SSB-SC', 'AM-DSB-WC', 'AM-DSB-SC', 'FM', 'GMSK', 'OQPSK']\n" + ] + } + ], + "source": [ + "print(modulation_classes)\n", + "np.savetxt('data/modulation_classes.txt',modulation_classes,fmt='%s')\n" + ] + }, + { + "cell_type": "markdown", + "id": "06a8af86", + "metadata": {}, + "source": [ + "## Run Vitis Functional Simulation" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "9986c78f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Compiling AIE Graph\n", + "Compilation directory: /group/fndprod/faisale/repo/internal/designs/radio-ml/aie/radioml_top\n", + "Compilation command: v++ -c --mode aie --config vfs_work/radioml_top_app_06d6bfe7/radioml_top_app.cfg --work_dir vfs_work/radioml_top_app_06d6bfe7/Work --output vfs_work/radioml_top_app_06d6bfe7/libadf.a --target x86sim\n", + "Writing log to: /group/fndprod/faisale/repo/internal/designs/radio-ml/aie/radioml_top/vfs_work/radioml_top_app_06d6bfe7/Work/logs/aie_x86sim.log\n", + "Please wait ...\n", + "\n", + "Compilation finished successfully.\n" + ] + } + ], + "source": [ + "radioml_top_graph = vfs.aieGraph(\n", + " input_file='radioml_top_app.cpp',\n", + " part=\"xc2ve3858-ssva2112-2MP-e-S\",\n", + " include_paths=['./','../conv1d_w1','../max_pool1d_w2','../conv1d_template','../max_pool1d_template','../dense_w16','../dense_w17','../dense_w18','../utility'])\n", + "act_o = radioml_top_graph.run(va.array(data_iq,dtype=va.bfloat16),\n", + " va.array(w1_weights,dtype=va.bfloat16),va.array(w1_bias,dtype=va.bfloat16),\n", + " va.array(w3_weights,dtype=va.bfloat16),va.array(w3_bias,dtype=va.bfloat16),\n", + " va.array(w5_weights,dtype=va.bfloat16),va.array(w5_bias,dtype=va.bfloat16),\n", + " va.array(w7_weights,dtype=va.bfloat16),va.array(w7_bias,dtype=va.bfloat16),\n", + " va.array(w9_weights,dtype=va.bfloat16),va.array(w9_bias,dtype=va.bfloat16),\n", + " va.array(w11_weights,dtype=va.bfloat16),va.array(w11_bias,dtype=va.bfloat16),\n", + " va.array(w13_weights,dtype=va.bfloat16),va.array(w13_bias,dtype=va.bfloat16),\n", + " va.array(w16_0_weights,dtype=va.bfloat16),va.array(w16_1_weights,dtype=va.bfloat16),va.array(w16_bias,dtype=va.bfloat16),\n", + " va.array(w17_weights,dtype=va.bfloat16),va.array(w17_bias,dtype=va.bfloat16),\n", + " va.array(w18_weights,dtype=va.bfloat16),va.array(w18_bias,dtype=va.bfloat16)\n", + " )\n", + "act_o = np.array(act_o,dtype='bfloat16')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "66a9c0d5", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "data_o_reshaped = np.reshape(data_o,(-1))\n", + "err = data_o_reshaped-act_o\n", + "plt.plot(err)\n", + "plt.title(\"Error\")\n", + "plt.show()\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "my-venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/radioml_top/radioml_top_app.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/radioml_top/radioml_top_app.cpp new file mode 100755 index 0000000000..1fc4260057 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/radioml_top/radioml_top_app.cpp @@ -0,0 +1,222 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#include +#include +#include "radioml_top_graph.h" +#include "read_file.h" + +class dut_graph : public graph { +public: + radioml_top_graph dut; + input_gmio data_iq; + output_gmio data_o; + port weights_w1; + port biases_w1; + port weights_w3; + port biases_w3; + port weights_w5; + port biases_w5; + port weights_w7; + port biases_w7; + port weights_w9; + port biases_w9; + port weights_w11; + port biases_w11; + port weights_w13; + port biases_w13; + port weights_0_w16; + port weights_1_w16; + port biases_w16; + port weights_w17; + port biases_w17; + port weights_w18; + port biases_w18; + + dut_graph( void ) + { + /* Setup the GMIO to connect the AIE to global memory */ + // logical name of the gmio, burst length 64, 128 or 256 bytes), required bandwidth in MB/s + data_iq = input_gmio::create("gmioIn",256,100); // Based on input bandwidth when simulating conv1d_w1 standalone + connect<>(data_iq.out[0],dut.data_iq); + data_o = output_gmio::create("gmioOut",256,10); // Based on ratio of # input samples of conv1d_w1 to # output samples of dense_w18 + connect<>(dut.data_o,data_o.in[0]); + + // layer_w1 RTPs + connect<>(weights_w1,dut.weights_w1); + connect<>(biases_w1,dut.biases_w1); + + // layer_w3 RTPs + connect<>(weights_w3,dut.weights_w3); + connect<>(biases_w3,dut.biases_w3); + + // layer_w5 RTPs + connect<>(weights_w5,dut.weights_w5); + connect<>(biases_w5,dut.biases_w5); + + // layer_w7 RTPs + connect<>(weights_w7,dut.weights_w7); + connect<>(biases_w7,dut.biases_w7); + + // layer_w9 RTPs + connect<>(weights_w9,dut.weights_w9); + connect<>(biases_w9,dut.biases_w9); + + // layer_w11 RTPs + connect<>(weights_w11,dut.weights_w11); + connect<>(biases_w11,dut.biases_w11); + + // layer_w13 RTPs + connect<>(weights_w13,dut.weights_w13); + connect<>(biases_w13,dut.biases_w13); + + // layer_w16 RTPs + connect<>(weights_0_w16,dut.weights_0_w16); + connect<>(weights_1_w16,dut.weights_1_w16); + connect<>(biases_w16,dut.biases_w16); + + // layer_w17 RTPs + connect<>(weights_w17,dut.weights_w17); + connect<>(biases_w17,dut.biases_w17); + + // layer_w18 RTPs + connect<>(weights_w18,dut.weights_w18); + connect<>(biases_w18,dut.biases_w18); + } +}; + +// Instantiate AIE graph: +dut_graph aie_dut; + +static constexpr unsigned ITERATIONS = 8; +static constexpr unsigned NSAMP_I = 1024*2; +static constexpr unsigned NSAMP_O = 24; +static constexpr unsigned BYTES_PER_SAMPLE = 2; +static constexpr unsigned SIG_I_BYTES = NSAMP_I * BYTES_PER_SAMPLE * ITERATIONS; +static constexpr unsigned SIG_O_BYTES = NSAMP_O * BYTES_PER_SAMPLE * ITERATIONS; + +bfloat16 data_iq_array[NSAMP_I*ITERATIONS]; +bfloat16 weights_w1_array[aie_dut.dut.layer_w1.NWEIGHTS]; +bfloat16 biases_w1_array[aie_dut.dut.layer_w1.NBIASES]; +bfloat16 weights_w3_array[aie_dut.dut.layer_w3.NWEIGHTS]; +bfloat16 biases_w3_array[aie_dut.dut.layer_w3.NBIASES]; +bfloat16 weights_w5_array[aie_dut.dut.layer_w5.NWEIGHTS]; +bfloat16 biases_w5_array[aie_dut.dut.layer_w5.NBIASES]; +bfloat16 weights_w7_array[aie_dut.dut.layer_w7.NWEIGHTS]; +bfloat16 biases_w7_array[aie_dut.dut.layer_w7.NBIASES]; +bfloat16 weights_w9_array[aie_dut.dut.layer_w9.NWEIGHTS]; +bfloat16 biases_w9_array[aie_dut.dut.layer_w9.NBIASES]; +bfloat16 weights_w11_array[aie_dut.dut.layer_w11.NWEIGHTS]; +bfloat16 biases_w11_array[aie_dut.dut.layer_w11.NBIASES]; +bfloat16 weights_w13_array[aie_dut.dut.layer_w13.NWEIGHTS]; +bfloat16 biases_w13_array[aie_dut.dut.layer_w13.NBIASES]; +bfloat16 weights_0_w16_array[aie_dut.dut.layer_w16.NWEIGHTS/2]; +bfloat16 weights_1_w16_array[aie_dut.dut.layer_w16.NWEIGHTS/2]; +bfloat16 biases_w16_array[aie_dut.dut.layer_w16.NBIASES]; +bfloat16 weights_w17_array[aie_dut.dut.layer_w17.NWEIGHTS]; +bfloat16 biases_w17_array[aie_dut.dut.layer_w17.NBIASES]; +bfloat16 weights_w18_array[aie_dut.dut.layer_w18.NWEIGHTS]; +bfloat16 biases_w18_array[aie_dut.dut.layer_w18.NBIASES]; + +#if defined(__AIESIM__) || defined(__X86SIM__) +// Initialize and run the graph: +int main(void) +{ + std::ofstream output_File("data_o_sim.txt"); + + aie_dut.init(); + + // Read input data + read_file("data/data_iq.txt",data_iq_array); + // Read layer_w1 RTPs + read_file("data/w1_weights-rtp.txt",weights_w1_array); + read_file ("data/w1_biases-rtp.txt", biases_w1_array); + // Read layer_w3 RTPs + read_file("data/w3_weights-rtp.txt",weights_w3_array); + read_file ("data/w3_biases-rtp.txt", biases_w3_array); + // Read layer_w5 RTPs + read_file("data/w5_weights-rtp.txt",weights_w5_array); + read_file ("data/w5_biases-rtp.txt", biases_w5_array); + // Read layer_w7 RTPs + read_file("data/w7_weights-rtp.txt",weights_w7_array); + read_file ("data/w7_biases-rtp.txt", biases_w7_array); + // Read layer_w9 RTPs + read_file("data/w9_weights-rtp.txt",weights_w9_array); + read_file ("data/w9_biases-rtp.txt", biases_w9_array); + // Read layer_w11 RTPs + read_file("data/w11_weights-rtp.txt",weights_w11_array); + read_file ("data/w11_biases-rtp.txt", biases_w11_array); + // Read layer_w13 RTPs + read_file("data/w13_weights-rtp.txt",weights_w13_array); + read_file ("data/w13_biases-rtp.txt", biases_w13_array); + // Read layer_w16 RTPs + read_file("data/w16_0_weights-rtp.txt",weights_0_w16_array); + read_file("data/w16_1_weights-rtp.txt",weights_1_w16_array); + read_file ("data/w16_biases-rtp.txt", biases_w16_array); + // Read layer_w17 RTPs + read_file("data/w17_weights-rtp.txt",weights_w17_array); + read_file ("data/w17_biases-rtp.txt", biases_w17_array); + // Read layer_w18 RTPs + read_file("data/w18_weights-rtp.txt",weights_w18_array); + read_file ("data/w18_biases-rtp.txt", biases_w18_array); + + aie_dut.update(aie_dut.weights_w1,weights_w1_array,aie_dut.dut.layer_w1.NWEIGHTS); + aie_dut.update(aie_dut.biases_w1,biases_w1_array,aie_dut.dut.layer_w1.NBIASES); + aie_dut.update(aie_dut.weights_w3,weights_w3_array,aie_dut.dut.layer_w3.NWEIGHTS); + aie_dut.update(aie_dut.biases_w3,biases_w3_array,aie_dut.dut.layer_w3.NBIASES); + aie_dut.update(aie_dut.weights_w5,weights_w5_array,aie_dut.dut.layer_w5.NWEIGHTS); + aie_dut.update(aie_dut.biases_w5,biases_w5_array,aie_dut.dut.layer_w5.NBIASES); + aie_dut.update(aie_dut.weights_w7,weights_w7_array,aie_dut.dut.layer_w7.NWEIGHTS); + aie_dut.update(aie_dut.biases_w7,biases_w7_array,aie_dut.dut.layer_w7.NBIASES); + aie_dut.update(aie_dut.weights_w9,weights_w9_array,aie_dut.dut.layer_w9.NWEIGHTS); + aie_dut.update(aie_dut.biases_w9,biases_w9_array,aie_dut.dut.layer_w9.NBIASES); + aie_dut.update(aie_dut.weights_w11,weights_w11_array,aie_dut.dut.layer_w11.NWEIGHTS); + aie_dut.update(aie_dut.biases_w11,biases_w11_array,aie_dut.dut.layer_w11.NBIASES); + aie_dut.update(aie_dut.weights_w13,weights_w13_array,aie_dut.dut.layer_w13.NWEIGHTS); + aie_dut.update(aie_dut.biases_w13,biases_w13_array,aie_dut.dut.layer_w13.NBIASES); + aie_dut.update(aie_dut.weights_0_w16,weights_0_w16_array,aie_dut.dut.layer_w16.NWEIGHTS/2); + aie_dut.update(aie_dut.weights_1_w16,weights_1_w16_array,aie_dut.dut.layer_w16.NWEIGHTS/2); + aie_dut.update(aie_dut.biases_w16,biases_w16_array,aie_dut.dut.layer_w16.NBIASES); + aie_dut.update(aie_dut.weights_w17,weights_w17_array,aie_dut.dut.layer_w17.NWEIGHTS); + aie_dut.update(aie_dut.biases_w17,biases_w17_array,aie_dut.dut.layer_w17.NBIASES); + aie_dut.update(aie_dut.weights_w18,weights_w18_array,aie_dut.dut.layer_w18.NWEIGHTS); + aie_dut.update(aie_dut.biases_w18,biases_w18_array,aie_dut.dut.layer_w18.NBIASES); + + bfloat16* sig_iq_array=(bfloat16*)GMIO::malloc(SIG_I_BYTES); + bfloat16* sig_o_array =(bfloat16*)GMIO::malloc(SIG_O_BYTES); + + /* Copy the input samples to the buffer */ + memcpy(sig_iq_array, data_iq_array, SIG_I_BYTES); + aie_dut.data_iq.gm2aie_nb(sig_iq_array, SIG_I_BYTES); + + aie_dut.run(ITERATIONS); + + aie_dut.data_o.aie2gm_nb(sig_o_array, SIG_O_BYTES); + aie_dut.data_o.wait(); + + /* Post-processing */ + int count=0; + for(int i=0; i +#include "conv1d_w1_graph.h" +#include "max_pool1d_w2_graph.h" +#include "conv1d_graph_template.h" +#include "max_pool1d_graph_template.h" +#include "dense_w16_graph.h" +#include "dense_w17_graph.h" +#include "dense_w18_graph.h" + +using namespace adf; + +// ------------------------------------------------------------ +// Top Level Graph +// ------------------------------------------------------------ + +class radioml_top_graph : public graph { +public: + port data_iq; + port weights_w1; + port biases_w1; + port weights_w3; + port biases_w3; + port weights_w5; + port biases_w5; + port weights_w7; + port biases_w7; + port weights_w9; + port biases_w9; + port weights_w11; + port biases_w11; + port weights_w13; + port biases_w13; + port weights_0_w16; + port weights_1_w16; + port biases_w16; + port weights_w17; + port biases_w17; + port weights_w18; + port biases_w18; + port data_o; + + // Graphs: + conv1d_w1_graph layer_w1; + max_pool1d_w2_graph layer_w2; + conv1d_graph_template<512,64,7> layer_w3; + max_pool1d_graph_template<512,64> layer_w4; + conv1d_graph_template<256,64,7> layer_w5; + max_pool1d_graph_template<256,64> layer_w6; + conv1d_graph_template<128,64,7> layer_w7; + max_pool1d_graph_template<128,64> layer_w8; + conv1d_graph_template<64,64,7> layer_w9; + max_pool1d_graph_template<64,64> layer_w10; + conv1d_graph_template<32,64,7> layer_w11; + max_pool1d_graph_template<32,64> layer_w12; + conv1d_graph_template<16,64,7> layer_w13; + max_pool1d_graph_template<16,64> layer_w14; + dense_w16_graph layer_w16; + dense_w17_graph layer_w17; + dense_w18_graph layer_w18; + + radioml_top_graph( void ) + { + // Connect IOs: + connect<> ( data_iq, layer_w1.data_iq ); + connect<> ( weights_w1, layer_w1.weights ); + connect<> ( biases_w1, layer_w1.biases ); + connect<> ( layer_w1.data_o, layer_w2.data_i ); + + connect<> ( layer_w2.data_o, layer_w3.data_i ); + connect<> ( weights_w3, layer_w3.weights ); + connect<> ( biases_w3, layer_w3.biases ); + connect<> ( layer_w3.data_o, layer_w4.data_i ); + + connect<> ( layer_w4.data_o, layer_w5.data_i ); + connect<> ( weights_w5, layer_w5.weights ); + connect<> ( biases_w5, layer_w5.biases ); + connect<> ( layer_w5.data_o, layer_w6.data_i ); + + connect<> ( layer_w6.data_o, layer_w7.data_i ); + connect<> ( weights_w7, layer_w7.weights ); + connect<> ( biases_w7, layer_w7.biases ); + connect<> ( layer_w7.data_o, layer_w8.data_i ); + + connect<> ( layer_w8.data_o, layer_w9.data_i ); + connect<> ( weights_w9, layer_w9.weights ); + connect<> ( biases_w9, layer_w9.biases ); + connect<> ( layer_w9.data_o, layer_w10.data_i ); + + connect<> ( layer_w10.data_o, layer_w11.data_i ); + connect<> ( weights_w11, layer_w11.weights ); + connect<> ( biases_w11, layer_w11.biases ); + connect<> ( layer_w11.data_o, layer_w12.data_i ); + + connect<> ( layer_w12.data_o, layer_w13.data_i ); + connect<> ( weights_w13, layer_w13.weights ); + connect<> ( biases_w13, layer_w13.biases ); + connect<> ( layer_w13.data_o, layer_w14.data_i ); + + connect<> ( layer_w14.data_o, layer_w16.data_i ); + connect<> ( weights_0_w16, layer_w16.weights_0 ); + connect<> ( weights_1_w16, layer_w16.weights_1 ); + connect<> ( biases_w16, layer_w16.biases ); + + connect<> ( layer_w16.data_o, layer_w17.data_i ); + connect<> ( weights_w17, layer_w17.weights ); + connect<> ( biases_w17, layer_w17.biases ); + + connect<> ( layer_w17.data_o, layer_w18.data_i ); + connect<> ( weights_w18, layer_w18.weights ); + connect<> ( biases_w18, layer_w18.biases ); + + connect<> ( layer_w18.data_o, data_o ); + + location(*this) = area_group({{aie_tile, 6, 0, 10, 3}}); + } +}; + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/Makefile b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/Makefile new file mode 100755 index 0000000000..266941919c --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/Makefile @@ -0,0 +1,69 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +MY_APP := selu_app +MY_SOURCES := ${MY_APP}.cpp selu_graph.h selu.h selu.cpp + +PART ?= xc2ve3858-ssva2112-2MP-e-S + +AIE_OUTPUT := libadf.a + +AIE_FLAGS := --part=${PART} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} --include=../utility + +.PHONY: help clean x86com x86sim sim profile throughput + +help:: + @echo "Makefile Usage:" + @echo " make all" + @echo " Command to generate everything for this design" + @echo "" + @echo " make compile" + @echo " Run AIE compiler and build the design" + @echo "" + @echo " make profile" + @echo " Run AIE simulator with profiling and generate outputs suitable for Vitis Analyzer" + @echo "" + @echo " make analyze" + @echo " Run Vitis Analyzer to inspect results" + @echo "" + @echo " make throughput" + @echo " Evaluate the achieved throughput at the output" + @echo "" + @echo " make clean" + @echo " Command to remove all the generated files." + +all: ${AIE_OUTPUT} + +x86all: clean x86com x86sim + +${AIE_OUTPUT}: ${MY_SOURCES} + v++ --compile --config aie.cfg --mode aie --target=hw ${AIE_FLAGS} 2>&1 | tee log + +x86com: + v++ --compile --config aie.cfg --mode aie --target=x86sim ${AIE_FLAGS} 2>&1 | tee log + +sim: + aiesimulator 2>&1 | tee -a log + +x86sim: + x86simulator 2>&1 | tee -a log + +profile: + aiesimulator --online -wdb -text --profile 2>&1 | tee -a log + +trace: + aiesimulator --hang-detect-time=5000 --online -wdb -text 2>&1 | tee -a log + +clean: + rm -rf .Xil Work libadf.a + rm -rf aiesimulator_output* aiesimulator*.log + rm -rf x86simulator_output* + rm -rf log log* + rm -rf *.xpe *.elf *.db *.soln Map_* xnw* *.lp *.log .xil .Xil *.lp *.db *.log *.exe *.vcd *.json + rm -rf vitis_analyzer* pl_sample_counts* pl_sample_count_* + rm -rf temp ISS_RPC_SERVER_PORT .crashReporter .AIE_SIM_CMD_LINE_OPTIONS + rm -rf system*.* trdata.aiesim function_wdb_dir .wsdata _ide vfs_work .ipynb_checkpoints _ide + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/aie.cfg b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/aie.cfg new file mode 100755 index 0000000000..80c82e5ffd --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/aie.cfg @@ -0,0 +1,15 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +[aie] + +kernel-linting=true +xlopt=1 +verbose=true +pl-freq=625 +Xmapper=BufferOptLevel9 +#stacksize=2048 +#Xchess="main:backend.mist2.maxfoldk=80" \ No newline at end of file diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/check_sim_output.m b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/check_sim_output.m new file mode 100644 index 0000000000..529b65f806 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/check_sim_output.m @@ -0,0 +1,23 @@ +% +% Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +% SPDX-License-Identifier: MIT +% +% Author: Faisal El-Shabani + +function check_sim_output() + %% Read golden output + fileID = fopen('data/sig_o.txt','r'); + formatSpec = '%f %f %f %f'; + [sig_g] = fscanf(fileID,formatSpec).'; + fclose(fileID); + sig_g = [sig_g(1:4:end);sig_g(2:4:end);sig_g(3:4:end);sig_g(4:4:end)]; + sig_g = sig_g(:).'; + + fileID = fopen('x86simulator_output/data/sig_o.txt','r'); + formatSpec = '%f %f %f %f'; + [sig_o_sim] = fscanf(fileID,formatSpec).'; + fclose(fileID); + sig_o_sim = [sig_o_sim(1:4:end);sig_o_sim(2:4:end);sig_o_sim(3:4:end);sig_o_sim(4:4:end)]; + sig_o_sim = sig_o_sim(:).'; + fprintf('Max error = %f\n',max(abs(sig_g-sig_o_sim))); +end \ No newline at end of file diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/data/sig_i.txt b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/data/sig_i.txt new file mode 100644 index 0000000000..fa34c48c15 --- /dev/null +++ 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b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/gen_vectors.m @@ -0,0 +1,67 @@ +% +% Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +% SPDX-License-Identifier: MIT +% +% Author: Mark Rollins + +clear all; +close all; + +% ------------------------------------------------------------ +% Create stimulus for AI Engine +% ------------------------------------------------------------ + +Niter = 8; +NSAMP = 1024; + +sig_i = reshape(repmat(transpose(linspace(-16,+16,NSAMP)),[1,Niter]),1,[]); +sig_i = double(varray.bfloat16(sig_i)); +sig_o = selu(sig_i); +sig_o = double(varray.bfloat16(sig_o)); + +[~,~,~] = rmdir('data','s'); +[~,~,~] = mkdir('data'); + +fid = fopen('data/sig_i.txt','w'); +for ii = 1 : 4 : numel(sig_i) + fprintf(fid,'%.7e %.7e %.7e %.7e\n',sig_i(ii),sig_i(ii+1),sig_i(ii+2),sig_i(ii+3)); +end +fclose(fid); + +fid = fopen('data/sig_o.txt','w'); +for ii = 1 : 4 : numel(sig_o) + fprintf(fid,'%.7e %.7e %.7e %.7e\n',sig_o(ii),sig_o(ii+1),sig_o(ii+2),sig_o(ii+3)); +end +fclose(fid); + +% ------------------------------------------------------------ +% Vitis Functional Simulation +% ------------------------------------------------------------ + +vfs_model = vfs.aieGraph(input_file="selu_app.cpp",... + include_paths = { '.' },... + part="xc2ve3858-ssva2112-2MP-e-S"); + +vfs_i = varray.bfloat16(sig_i); +vfs_o = vfs_model.run(vfs_i); +vfs_o = reshape(vfs_o,1,numel(vfs_o)); +err_o = sig_o - double(vfs_o); + +figure; +subplot(2,1,1); plot(sig_o,'b.-'); hold on; plot(double(vfs_o),'r.--'); hold off;legend('golden','actual'); +subplot(2,2,3); plot(err_o,'k.-');title('error'); + + +% ------------------------------------------------------------ +% Function SELU +% ------------------------------------------------------------ + +function [sig_o] = selu(sig_i) + idx_p = find(sig_i > 0); + idx_n = find(sig_i <= 0); + sig_o = zeros(size(sig_i)); + scale = 1.05070098; + alpha = 1.67326324; + sig_o(idx_p) = scale*sig_i(idx_p); + sig_o(idx_n) = scale*alpha*(exp(sig_i(idx_n))-1); +end diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/selu.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/selu.cpp new file mode 100644 index 0000000000..fe02d25099 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/selu.cpp @@ -0,0 +1,87 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Mark Rollins + +#include +#include + +#include "selu.h" + + +// ------------------------------------------------------------ +// Constructor +// ------------------------------------------------------------ + +template +selu::selu(void) +{ + aie::set_rounding(aie::rounding_mode::symmetric_inf); + aie::set_saturation(aie::saturation_mode::saturate); +} + +// ------------------------------------------------------------ +// Run +// ------------------------------------------------------------ + +template +void selu::run( input_buffer& sig_i, output_buffer& sig_o ) +{ + auto itr = aie::begin_restrict_vector<32>(sig_i); + auto itw = aie::begin_restrict_vector<32>(sig_o); + auto itp = aie::begin_restrict_vector<32>(SCRATCH_POS); + auto itn = aie::begin_restrict_vector<32>(SCRATCH_NEG); + + aie::accum accB; + accB.from_vector(aie::broadcast(exp_B)); + + // Compute 'pos': + for (unsigned ii=0; ii < NSAMP/32; ii++) + chess_prepare_for_pipelining + { + *itp++ = aie::mul(*itr++,Cpos); + } + chess_separator(); + + // Compute 'neg' -- first part is exp(x) approximation + itr = aie::begin_restrict_vector<32>(sig_i); + for (unsigned ii=0; ii < NSAMP/32; ii++) + chess_prepare_for_pipelining + { + auto data_i = *itr++; + auto data_t = (aie::mac(accB,data_i,exp_S)).to_vector(); + // Integer values should be in the range [0,16256], find outliers and set to zero: + aie::vector exp_i = aie::to_fixed(data_t,0); + aie::mask<32> msk_neg = aie::lt(exp_i,int16(0)); + aie::vector exp_bnd = aie::select(exp_i, aie::zeros(), msk_neg); + aie::mask<32> msk_pos = aie::gt(exp_bnd, int16(16256)); + exp_bnd = aie::select(exp_bnd, aie::zeros(), msk_pos); + *itn++ = exp_bnd.cast_to(); + } + chess_separator(); + + // Compute 'neg' -- second part is remaining math + itr = aie::begin_restrict_vector<32>(SCRATCH_NEG); + itn = aie::begin_restrict_vector<32>(SCRATCH_NEG); + for (unsigned ii=0; ii < NSAMP/32; ii++) + chess_prepare_for_pipelining + { + auto data_i = *itr++; + *itn++ = (aie::mul(aie::sub(data_i,bfloat16(1.0f)),Cneg)).to_vector(); + } + chess_separator(); + + // Select between 'pos' and 'neg': + itr = aie::begin_restrict_vector<32>(sig_i); + itp = aie::begin_restrict_vector<32>(SCRATCH_POS); + itn = aie::begin_restrict_vector<32>(SCRATCH_NEG); + for (unsigned ii=0; ii < NSAMP/32; ii++) + chess_prepare_for_pipelining + { + auto data_i = *itr++; + auto data_p = *itp++; + auto data_n = *itn++; + *itw++ = aie::select(data_p,data_n,aie::le(data_i,aie::broadcast(0.0f))); + } +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/selu.h b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/selu.h new file mode 100644 index 0000000000..0216b92f92 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/selu.h @@ -0,0 +1,37 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Mark Rollins + +#pragma once + +#include +#include + +using namespace adf; + +template +class selu { +public: + + const bfloat16 exp_S = 185.0f; + const float exp_B = 16256.0f; + const bfloat16 Cpos = 1.0507f; + const bfloat16 Cneg = 1.7581f; + + alignas(64) bfloat16 SCRATCH_POS[NSAMP]; + alignas(64) bfloat16 SCRATCH_NEG[NSAMP]; + + // Constructor: + selu( void ); + + // Run: + void run( input_buffer& sig_i, output_buffer& sig_o); + + static void registerKernelClass( void ) + { + REGISTER_FUNCTION( selu::run ); + } +}; + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/selu_app.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/selu_app.cpp new file mode 100644 index 0000000000..4d52ab8744 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/selu_app.cpp @@ -0,0 +1,38 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Mark Rollins + +#include +#include +#include "selu_graph.h" + +class dut_graph : public graph { +public: + static constexpr unsigned NSAMP = 1024; + selu_graph dut; + input_plio sig_i; + output_plio sig_o; + + dut_graph( void ) + { + sig_i = input_plio::create("PLIO_i_0",plio_64_bits,"data/sig_i.txt"); + sig_o = output_plio::create("PLIO_o_0",plio_64_bits,"data/sig_o.txt"); + connect<>(sig_i.out[0],dut.sig_i); + connect<>(dut.sig_o,sig_o.in[0]); + } +}; + +// Instantiate AIE graph: +dut_graph aie_dut; + +// Initialize and run the graph: +int main(void) +{ + aie_dut.init(); + aie_dut.run(8); + aie_dut.end(); + + return 0; +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/selu_graph.h b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/selu_graph.h new file mode 100644 index 0000000000..ffed45ccd3 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/selu/selu_graph.h @@ -0,0 +1,37 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Mark Rollins + +#pragma once + +#include +#include "selu.h" + +using namespace adf; + +// ------------------------------------------------------------ +// Top Level Graph +// ------------------------------------------------------------ + +template +class selu_graph : public graph { +public: + // Declare Kernels + kernel kk; + + // Declare IOs + port sig_i; + port sig_o; + + selu_graph( void ) + { + kk = kernel::create_object>(); + source(kk) = "selu.cpp"; + runtime(kk) = 0.9; + connect<>( sig_i, kk.in[0] ); dimensions(kk.in[0]) = { NSAMP }; + connect<>( kk.out[0], sig_o ); dimensions(kk.out[0]) = { NSAMP }; + } +}; + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/utility/ceil_constexpr.h b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/utility/ceil_constexpr.h new file mode 100755 index 0000000000..08c4e4b180 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/utility/ceil_constexpr.h @@ -0,0 +1,17 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani +#ifndef CEIL_CONSTEXPR_H +#define CEIL_CONSTEXPR_H +constexpr int ceil_constexpr(double x) { + if (x == static_cast(x)) { + return x; + } else if (x > 0) { + return static_cast(x) + 1; + } else { + return static_cast(x); + } +} +#endif diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/utility/next_pow_2_constexpr.h b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/utility/next_pow_2_constexpr.h new file mode 100755 index 0000000000..9fcb68672d --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/utility/next_pow_2_constexpr.h @@ -0,0 +1,14 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani +#ifndef NEXT_POW_2_CONSTEXPR_H +#define NEXT_POW_2_CONSTEXPR_H +constexpr int next_pow_2_constexpr(double x) { + int power = 1; + while(power < x) + power*=2; + return power; +} +#endif diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/utility/read_file.h b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/utility/read_file.h new file mode 100755 index 0000000000..25f47f7625 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/aie/utility/read_file.h @@ -0,0 +1,26 @@ +// +// Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani +#ifndef READ_FILE_H +#define READ_FILE_H +template +void read_file(std::string file_name, T *data_array) { + std::ifstream ss_i; + ss_i.open(file_name,std::ifstream::in); + if ( ss_i.is_open() == 0 ) { + std::cout << "ERROR: failed to open " << file_name << std::endl; + } + else { + std::cout << "PASSED: Successfully read input file " << file_name << std::endl; + } + for (unsigned ss=0; ss < N; ss++) { + float val; + ss_i >> val; + T buff = (T) val; + data_array[ss] = buff; + } + ss_i.close(); +} +#endif diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/create_venv.sh b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/create_venv.sh new file mode 100755 index 0000000000..fa68207d6b --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/create_venv.sh @@ -0,0 +1,52 @@ +#!/bin/bash +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + + +echo "Container File Notices" +echo "" +echo "NOTICE - BY INVOKING THIS SCRIPT AND USING THE SOFTWARE INSTALLED BY THE SCRIPT, YOU AGREE ON BEHALF OF YOURSELF AND YOUR EMPLOYER (IF APPLICABLE) TO BE BOUND TO THE LICENSE AGREEMENTS APPLICABLE TO THE PACKAGES IDENTIFIED BELOW THAT YOU INSTALL BY RUNNING THE SCRIPT. YOU UNDERSTAND THAT THE INSTALLATION OF THE PACKAGES LISTED BELOW MAY ALSO RESULT IN THE INSTALLATION ON YOUR SYSTEM OF ADDITIONAL PACKAGES NOT LISTED BELOW IN ORDER TO OPERATE (EACH, A ‘DEPENDENCY’). ADVANCED MICRO DEVICES, INC., ON BEHALF OF ITSELF AND ITS SUBSIDIARIES AND AFFILIATES, DOES NOT GRANT TO YOU ANY RIGHTS OR LICENSES TO ANY SUCH DEPENDENCY. THE SCRIPT ITSELF IS LICENSED TO YOU SUBJECT TO THE FOLLOWING TERMS: " +echo "" +echo "Copyright © 2025 Advanced Micro Devices, Inc. All Rights Reserved. " +echo "" +echo "This file is licensed under the following license terms (MIT): " +echo "" +echo "Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:" +echo "The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software." +echo "" +echo "THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE." +echo "" +echo "This file pulls in the following packages subject to the licenses identified below:" +echo "| Package | Licenses | URL |" +echo "|----------------------------------------|------------------------------------------|--------------------------------------------------|" +echo "| jupyter | BSD | https://pypi.org/project/jupyter/ |" +echo "| tensorflow | Apache 2.0 | https://pypi.org/project/tensorflow/ |" +echo "| matplotlib | OSI approved python software foundation | https://pypi.org/project/matplotlib/ |" +echo "| pydot | OSI approved MIT | https://pypi.org/project/pydot/ |" +echo "| bfloat16 | Apache software | https://pypi.org/project/bfloat16/ |" +echo "| scikit-learn | BSD-3-Clause | https://pypi.org/project/scikit-learn/ |" +echo "" + +echo "Do you want to continue? (yes/no)" +read response + +if [[ "$response" == "yes" ]]; then + echo "Installing Python Libraries" + python3 -m venv my-venv + source my-venv/bin/activate + pip install --upgrade pip + pip install jupyter + pip install tensorflow + pip install matplotlib + pip install pydot + pip install bfloat16 + pip install scikit-learn + pip list +fi + +if [[ "$response" == "no" ]]; then + echo "Permission not granted to proceed" +fi diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/description.json b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/description.json new file mode 100755 index 0000000000..25a63b33de --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/description.json @@ -0,0 +1,52 @@ +{ + "name": "Design_Tutorials-01-Radio-ML", + "description": "01-Radio-ML", + "gui": "false", + "flow": "versal", + + "platform_allowlist": [ "vek385_base_reva"], + "platform_blocklist": [], + + "testinfo": { + "test_name": "AIE-MLv2_D_01-Radio-ML", + "jobs": [ + { + "index": 0, + "dependency": [], + "env": "", + "cmd": "", + "max_memory_MB": 65536, + "max_time_min": { + "vitis_hw_build": 300, + "vitis_hw_emu": 120, + "vitis_hw_run": 30 + } + } + ], + "targets": [ + "vitis_hw_emu", + "vitis_hw_build", + "vitis_hw_run" + ], + "category": "canary", + "make_options": [ + "EMU_CMD=\\\"./launch_hw_emu.sh -qemu-config ../vitis/${QEMU_COMBINED}/combined.qemuboot.conf -login \\\"amd-edf\\\" -password \\\"amd-edf\\\" -run-app \\\"mount /dev/sda2 /media; cd /media; ./embedded_exec.sh\\\"\\\"", + "EMBEDDED_PACKAGE_OUT=./package", + "EMBEDDED_EXEC_SCRIPT=./embedded_exec.sh" + ], + "custom_build_target": { + "all": "all" + }, + "custom_board_target": "run_test", + "configuration": "segmented", + "compilation": "edf", + "tasks": { + "board" : { + "pre_exec" : ["./env_setup_yocto_edf.sh"] + }, + "build": { + "pre_exec": ["./env_setup_yocto_edf.sh"] + } + } + } +} diff --git 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differ diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/ps_apps/Makefile b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/ps_apps/Makefile new file mode 100755 index 0000000000..515a1a1b87 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/ps_apps/Makefile @@ -0,0 +1,58 @@ +# +# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +ECHO := @echo + +APP_NAME := host +APP_EXE := ${APP_NAME}.exe +APP_SRC := ${APP_NAME}.cpp +APP_SRC_DEP := ./* +APP_SRC_CTRL := ./../aie/radioml_top/Work/ps/c_rts/aie_control_xrt.cpp + +GCC := ${XILINX_VITIS}/gnu/aarch64/lin/aarch64-linux/bin/aarch64-linux-gnu-g++ + +GCC_INCLUDES := -I${SYSROOT}/usr/include \ + -I${SYSROOT}/usr/include/xrt \ + -I${SYSROOT}/usr/include/xaiengine \ + -I${XILINX_VITIS}/aietools/include \ + -I../aie/radioml_top \ + -I../aie/conv1d_w1 \ + -I../aie/max_pool1d_w2 \ + -I../aie/conv1d_template \ + -I../aie/max_pool1d_template \ + -I../aie/dense_w16 \ + -I../aie/dense_w17 \ + -I../aie/dense_w18 \ + -I../aie/utility + +GCC_C_FLAGS := -O -Wall -std=c++17 -DXAIE_DEBUG \ + -pthread \ + --sysroot=${SYSROOT} + +GCC_L_FLAGS := -L${SYSROOT}/usr/lib \ + -L${XILINX_VITIS}/aietools/lib/aarch64.o \ + -L${XILINX_VITIS}/aietools/lib/lnx64.o \ + -ladf_api_xrt -lxaiengine -lxrt_core -lxrt_coreutil \ + --sysroot=${SYSROOT} + +.PHONY: clean help all + +help:: + $(ECHO) "Makefile Usage:" + $(ECHO) " make all" + $(ECHO) " Command to generate the aie_dly_test ps_app used in this design" + $(ECHO) "" + $(ECHO) " make clean" + $(ECHO) " Command to remove all the generated files." + + +all: ${APP_EXE} + +$(APP_EXE): $(APP_SRC) $(APP_SRC_CTRL) ${SYSROOT} + ${GCC} ${GCC_C_FLAGS} $(APP_SRC) $(APP_SRC_CTRL) ${GCC_INCLUDES} $(GCC_L_FLAGS) -o $(APP_EXE) + +clean: + rm -rf *.o ${APP_EXE} \ No newline at end of file diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/ps_apps/host.cpp b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/ps_apps/host.cpp new file mode 100755 index 0000000000..2887d11e34 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/ps_apps/host.cpp @@ -0,0 +1,267 @@ +// +// Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +// +// Author: Faisal El-Shabani + +#include +#include +#include +#include +#include +#include + +#include +#include +#include +#include +#include +#include + +#include + +#include "read_file.h" + +static const char* STR_PASSED = "PASSED: "; +static const char* STR_USAGE = "USAGE: "; + +// ------------------------------------------------------------ +// Run Parameters +// ------------------------------------------------------------ + +static constexpr int32_t NUM_ITER = 8; +static constexpr unsigned NUM_SAMPLES_I = 1024*2; // 1024 I/Q samples +static constexpr unsigned NUM_SAMPLES_O = 24; +static constexpr unsigned BYTES_PER_SAMPLE = 2; +static constexpr unsigned SIG_I_BYTES = NUM_SAMPLES_I * BYTES_PER_SAMPLE * NUM_ITER; +static constexpr unsigned SIG_O_BYTES = NUM_SAMPLES_O * BYTES_PER_SAMPLE * NUM_ITER; + +// ------------------------------------------------------------ +// Main +// ------------------------------------------------------------ + +int main(int argc, char* argv[]) +{ + //TARGET_DEVICE macro needs to be passed from gcc command line + if (argc != 2) { + std::cout << STR_USAGE << argv[0] <<" " << std::endl; + return 1; + } + + // ------------------------------------------------------------ + // Load XCLBIN + // ------------------------------------------------------------ + + char* xclbinFilename = argv[1]; + unsigned dev_index = 0; + auto my_device = xrt::device(dev_index); + std::cout << STR_PASSED << "auto my_device = xrt::device(" << dev_index << ")" << std::endl; + + auto xclbin_uuid = my_device.load_xclbin(xclbinFilename); + std::cout << STR_PASSED << "auto xclbin_uuid = my_device.load_xclbin(" << xclbinFilename << ")" << std::endl; + + // ------------------------------------------------------------ + // Declare GMIO buffers and RTP arrays + // ------------------------------------------------------------ + + // Declare GMIO buffers: + auto sig_iq = xrt::aie::bo(my_device,SIG_I_BYTES,xrt::bo::flags::normal,1); + auto sig_o = xrt::aie::bo(my_device,SIG_O_BYTES,xrt::bo::flags::normal,1); + std::cout << STR_PASSED << "Create GMIO buffer objects" << std::endl; + + // Malloc GMIO buffers: + bfloat16* data_iq = sig_iq.map(); + bfloat16* data_o = sig_o.map(); + + // Declare arrays for RTPs + bfloat16 weights_w1[896]; + bfloat16 biases_w1[64]; + bfloat16 weights_w3[28672]; + bfloat16 biases_w3[64]; + bfloat16 weights_w5[28672]; + bfloat16 biases_w5[64]; + bfloat16 weights_w7[28672]; + bfloat16 biases_w7[64]; + bfloat16 weights_w9[28672]; + bfloat16 biases_w9[64]; + bfloat16 weights_w11[28672]; + bfloat16 biases_w11[64]; + bfloat16 weights_w13[28672]; + bfloat16 biases_w13[64]; + bfloat16 weights_0_w16[65536/2]; + bfloat16 weights_1_w16[65536/2]; + bfloat16 biases_w16[128]; + bfloat16 weights_w17[16384]; + bfloat16 biases_w17[128]; + bfloat16 weights_w18[3072]; + bfloat16 biases_w18[24]; + + // Declare array for golden output + bfloat16 golden_o[NUM_SAMPLES_O*NUM_ITER]; + + // Declare array of strings for modulation_classes + std::string modulation_classes[24]; + + // ------------------------------------------------------------ + // Read input/RTPs files + // ------------------------------------------------------------ + read_file("data_iq.txt",data_iq); + read_file ("w1_weights-rtp.txt",weights_w1); + read_file ("w1_biases-rtp.txt", biases_w1); + read_file("w3_weights-rtp.txt",weights_w3); + read_file ("w3_biases-rtp.txt", biases_w3); + read_file("w5_weights-rtp.txt",weights_w5); + read_file ("w5_biases-rtp.txt", biases_w5); + read_file("w7_weights-rtp.txt",weights_w7); + read_file ("w7_biases-rtp.txt", biases_w7); + read_file("w9_weights-rtp.txt",weights_w9); + read_file ("w9_biases-rtp.txt", biases_w9); + read_file("w11_weights-rtp.txt",weights_w11); + read_file ("w11_biases-rtp.txt", biases_w11); + read_file("w13_weights-rtp.txt",weights_w13); + read_file ("w13_biases-rtp.txt", biases_w13); + read_file("w16_0_weights-rtp.txt",weights_0_w16); + read_file("w16_1_weights-rtp.txt",weights_1_w16); + read_file ("w16_biases-rtp.txt", biases_w16); + read_file ("w17_weights-rtp.txt",weights_w17); + read_file ("w17_biases-rtp.txt", biases_w17); + read_file ("w18_weights-rtp.txt",weights_w18); + read_file ("w18_biases-rtp.txt", biases_w18); + read_file ("data_o.txt", golden_o); + std::cout << STR_PASSED << "Read all IO/RTP files" << std::endl; + + // Read modulation_classes + std::ifstream inputFile; + inputFile.open("modulation_classes.txt"); + if (!inputFile.is_open()) { + std::cerr << "Error opening file!" << std::endl; + return 1; + } + std::string line; + int iter = 0; + while (std::getline(inputFile, line)) { + modulation_classes[iter] = line; + iter++; + } + std::cout << STR_PASSED << "Read modulation_classes.txt file" << std::endl; + + // ------------------------------------------------------------ + // Load and Run AIE graph + // ------------------------------------------------------------ + + auto my_graph = xrt::graph(my_device, xclbin_uuid, "aie_dut"); + std::cout << STR_PASSED << "auto my_graph = xrt::graph(my_device, xclbin_uuid, \"aie_dut\")" << std::endl; + + my_graph.reset(); + std::cout << STR_PASSED << "my_graph.reset()" << std::endl; + + // Transfer RTP's only once: + my_graph.update("aie_dut.dut.layer_w1.kk.in[1]",weights_w1); + my_graph.update("aie_dut.dut.layer_w1.kk.in[2]",biases_w1); + my_graph.update("aie_dut.dut.layer_w3.kk.in[1]",weights_w3); + my_graph.update("aie_dut.dut.layer_w3.kk.in[2]",biases_w3); + my_graph.update("aie_dut.dut.layer_w5.kk.in[1]",weights_w5); + my_graph.update("aie_dut.dut.layer_w5.kk.in[2]",biases_w5); + my_graph.update("aie_dut.dut.layer_w7.kk.in[1]",weights_w7); + my_graph.update("aie_dut.dut.layer_w7.kk.in[2]",biases_w7); + my_graph.update("aie_dut.dut.layer_w9.kk.in[1]",weights_w9); + my_graph.update("aie_dut.dut.layer_w9.kk.in[2]",biases_w9); + my_graph.update("aie_dut.dut.layer_w11.kk.in[1]",weights_w11); + my_graph.update("aie_dut.dut.layer_w11.kk.in[2]",biases_w11); + my_graph.update("aie_dut.dut.layer_w13.kk.in[1]",weights_w13); + my_graph.update("aie_dut.dut.layer_w13.kk.in[2]",biases_w13); + my_graph.update("aie_dut.dut.layer_w16.kk.in[1]",weights_0_w16); + my_graph.update("aie_dut.dut.layer_w16.kk.in[2]",weights_1_w16); + my_graph.update("aie_dut.dut.layer_w16.kk.in[3]",biases_w16); + my_graph.update("aie_dut.dut.layer_w17.kk.in[1]",weights_w17); + my_graph.update("aie_dut.dut.layer_w17.kk.in[2]",biases_w17); + my_graph.update("aie_dut.dut.layer_w18.kk.in[1]",weights_w18); + my_graph.update("aie_dut.dut.layer_w18.kk.in[2]",biases_w18); + std::cout << STR_PASSED << "Transferred design RTP's to AIE graphs" << std::endl; + + // Start data transfer + sig_iq.async("aie_dut.data_iq",XCL_BO_SYNC_BO_GMIO_TO_AIE,SIG_I_BYTES,0); + + // Start throughput profiling + xrt::aie::profiling handle(my_device); + std::cout << STR_PASSED << "xrt::aie::profiling handle(my_device);" << std::endl; + handle.start(xrt::aie::profiling::profiling_option::io_stream_start_to_bytes_transferred_cycles,"aie_dut.data_o","",SIG_O_BYTES); + + my_graph.run(NUM_ITER); + std::cout << STR_PASSED << "my_graph.run( NUM_ITER=" << NUM_ITER << " )" << std::endl; + auto sig_o_handle=sig_o.async("aie_dut.data_o",XCL_BO_SYNC_BO_AIE_TO_GMIO,SIG_O_BYTES,0); + sig_o_handle.wait(); + + std::cout << "Graph completed execution" << std::endl; + + my_graph.end(); + + // ------------------------------------------------------------ + // Measure Inference Throughput + // ------------------------------------------------------------ + + long long cycle_count = handle.read(); + handle.stop(); + double throughput = (double) NUM_ITER / ((cycle_count) * 0.8 * 1e-6); + + // ------------------------------------------------------------ + // Regression Test + // ------------------------------------------------------------ + + bool flag = 0; + double tolerance = 0.05; // Minor functional mismatch expected + for(unsigned int i=0;i tolerance ); + flag |= this_flag; + if(this_flag){ + std::cout<<"ERROR:data_o["<golden_max){ + golden_max = golden_o[j+i*NUM_SAMPLES_O]; + golden_max_index = j; + } + if (data_o[j+i*NUM_SAMPLES_O]>model_max){ + model_max = data_o[j+i*NUM_SAMPLES_O]; + model_max_index = j; + } + } + golden_classification = modulation_classes[golden_max_index]; + implementation_classification = modulation_classes[model_max_index]; + std::cout << "Inference # = " << i << " golden_classification = " << golden_classification << " implementation_classification = " << implementation_classification << std::endl; + } + + std::cout << "==============================" << std::endl; + std::cout << "Cycle count: " << cycle_count << std::endl; + std::cout << "Approx Inference Throughput: " << throughput << " KHz" << std::endl; + std::cout << "==============================" << std::endl; + + if ( flag == 0 ) + std::cout << std::endl << "--- PASSED ---" << std::endl; + else + std::cout << std::endl << "*** FAILED ***" << std::endl; + + return(flag); + +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/radio-ml-model.ipynb b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/radio-ml-model.ipynb new file mode 100644 index 0000000000..e99a0b0c4b --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/radio-ml-model.ipynb @@ -0,0 +1,850 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "16fe840d-a400-4238-8e36-42d1b6776997", + "metadata": {}, + "source": [ + "# Radio ML Model" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "5e30bef2-d9ca-4fda-9b0e-81bad9e1fc16", + "metadata": {}, + "outputs": [], + "source": [ + "#\n", + "# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved.\n", + "# SPDX-License-Identifier: MIT\n", + "#\n", + "# Author: Faisal El Shabani" + ] + }, + { + "cell_type": "markdown", + "id": "e69905dc", + "metadata": {}, + "source": [ + "### Import Libraries" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "94c6070a-3496-4de5-ae0f-9eab29328418", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-08-14 14:52:47.469835: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-08-14 14:52:47.474612: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", + "2025-08-14 14:52:47.484371: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", + "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n", + "E0000 00:00:1755204767.499277 3196037 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", + "E0000 00:00:1755204767.503564 3196037 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", + "W0000 00:00:1755204767.518799 3196037 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755204767.518814 3196037 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755204767.518817 3196037 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "W0000 00:00:1755204767.518819 3196037 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n", + "2025-08-14 14:52:47.523797: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", + "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n" + ] + } + ], + "source": [ + "from tensorflow import keras\n", + "from tensorflow.keras.layers import Dense, Flatten, Conv1D, MaxPooling1D\n", + "import matplotlib.pyplot as plt\n", + "from tensorflow.keras import mixed_precision\n", + "from sklearn.model_selection import train_test_split\n", + "import h5py as h5\n", + "import numpy as np\n", + "from numpy import argwhere\n", + "import os\n", + "import json\n", + "import statistics\n", + "import shutil" + ] + }, + { + "cell_type": "markdown", + "id": "553c8544", + "metadata": {}, + "source": [ + "### Read training and test data" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "d8e55ec3", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(2555904, 1024, 2)\n", + "(2555904, 24)\n", + "(2555904, 1)\n" + ] + } + ], + "source": [ + "if not(\"RADIOML_DATA\" in os.environ):\n", + " print(\"Please set environment variable RADIOML_DATA to point to dataset found in https://www.kaggle.com/datasets/pinxau1000/radioml2018\")\n", + "data_file = os.environ[\"RADIOML_DATA\"] + 'GOLD_XYZ_OSC.0001_1024.hdf5'\n", + "file_handle = h5.File(data_file,'r')\n", + "\n", + "myData = file_handle['X'][:] #1024x2 samples \n", + "myMods = file_handle['Y'][:] #mods \n", + "mySNRs = file_handle['Z'][:] #snrs \n", + "\n", + "modulation_classes = json.load(open(os.environ[\"RADIOML_DATA\"] + \"classes-fixed.json\", 'r'))\n", + "\n", + "print(np.shape(myData))\n", + "print(np.shape(myMods))\n", + "print(np.shape(mySNRs))\n", + "file_handle.close()" + ] + }, + { + "cell_type": "markdown", + "id": "4f81d85c", + "metadata": {}, + "source": [ + "### Examine RF input samples, 30 dB SNR case" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "285ec823", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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tTLsz6Cbo3qf/K5fL4rvf/W5kWwDiHe94h9i+fbvYtm2buPnmm8VLXvISAUB84QtfEEIENrDjjz9eABD77befOOWUU8SZZ54pHn300dTPNvfdpYV2xmnUVq688kqxfft2sX79evGDH/xArFq1SlSrVbFhwwYhRGDron706KOPFh/84AfFT3/6UzE9PR3b//HHHy9WrlwpRkdHxVOe8pRYH2owuChyvz300EPFy172MrF9+3axfft2cfvtt4uTTz5ZABDvf//71XZkpV2xYoU46aSTxH//93+Le++9N/aZZGuke+2ZZ57Z8+9psPBIs8TedtttAoBYtWqV2G+//cTXvvY1cd5554ljjz1WWJYlLrvsMrUttZ1zzjlHbN++XWzatElceuml4rDDDhOWZSkr4ZYtW8Q+++wjAIijjjpKvPe97xXnn3++GB8fjx3X6aefLjzPEwcccIBYs2aNeOCBB3p6Hgz2Ht7znveofs22bfHGN74xFq2j4y/+4i/E2NiY2L17t3qOLLGf/OQnxfbt28WWLVvEtddeK/7sz/5MABA/+clPhBBCzMzMiCc+8Ymqf3vrW98qvv3tb8diKIQILbGHHnqoGBsbEzfeeGNXv/tiw5Ih7NavXy8AiFNPPTVzu7e85S0CgFi3bl1L29MgjwaDlUpFjI6OiltvvbVr38Ggf7Bjxw6xcuVK8d///d/quSTCbseOHcLzPPHVr35VPbdz587Yc4TLL79cvOxlLxOe56lO9IgjjojlCFAbBCA++tGPdvnbGSxmfP/73xcvf/nLxdlnny1+8pOfiLe//e3Csizxv//7v2ob0+4Mug2695155pniiiuuEFdccYX4v//7P/GKV7xCuK6rBmRCiERir1KpiH/8x3+MEMFzc3Pi05/+tDjqqKMi277pTW+KDAbNfXdpotVx3caNG1OJ5UMPPVRcfvnlkffdf//94tRTTxXLly9X242MjMRywo4//nhRLpcFAHHCCSeIubm5rn9Xg8WJIvdbItb4P8dxxN/8zd+ImZkZtV2z2RRf/epXxTOf+czItieccIKaYwgRki6VSkW4rit++ctf7tXvbLAwSCPsrrvuOtVWbrrpJvX85OSkWL16dWRhltqO/m+fffYR5557bmS/mzZtEu9973vFfvvtp7YrlUriU5/6lPB9X213+umnC9u2hed54qlPfWouoWPQP7j33nvFFVdcIb73ve+JV7/61eKkk04SW7ZsSd2ecj2/9rWvRZ4nwk7/NzY2Jj73uc9Fth0fHxcf+tCHIv2mbdvijDPOiNxbibCrVCpizZo1iXmzg4QlQ9j1WmFHQYg0GPze974nVq1aJfbZZx9x3333delbGPQL3vve94rHPe5xkaD+JMLuzDPPVMGuDz74oPr3/Oc/XzznOc9J3f/09LS47rrrxN/93d8Jx3HEihUrIisQAMR73vMeceKJJwoA4otf/GL3v6TBosMFF1wgqtWqWL9+feT5t771rWJoaEgFoJt2Z9BtpIX5N5tN8fSnP10ccMABqj+ke+sVV1whrrzySnHzzTcnFjzh2LRpk7jgggvEcccdJwCIt7zlLbHPNvfdpYVWxmmWZYn5+fkYsXzNNdeIe+65J7MoTqPREHfccYf47Gc/q8g7HqhN9/bPfe5zAoA46aSTjLp4CaDo/fbQQw8Vz372s1V/97vf/S6y4JCEHTt2iEsuuUS88pWvFADE85//fPUakS5f+cpXxBFHHCGGhobEDTfc0PXvZ7C4kEbY0fOHH3547D1ve9vbhOd5ol6vCyHCtvP//t//E1dccYW4+uqrxR133KFeT4Lv++L+++8XX/nKV8SBBx4oAIhvfvOb6nUqOnHBBRcI27bFc57znNz7uUF/4qUvfak45phjIoQt4Qc/+IGwLEu84x3viL1GhN273/1uccUVV4irrrpK3HrrrbmLW+vWrRPf/va3xZOe9KSYepkIux//+MeiUqmIxz/+8YlKvEHBkiHshBDigAMOSOzQOA477DBx4IEHtrW9ENFJy8033yxGRkbEwQcfLB577LHOv4BBX+CBBx4Qtm2Lr3zlK2Lt2rXq37Of/WzxhCc8Qaxdu1bs3LlTCCHEc5/73MRVB/pXpMISdVrcdgYEVRhnZ2fF8ccfLyzLEuecc07PvrPB4sALXvAC8dznPjf2/EUXXRSZZJp2Z9BtpBF2QgjxwQ9+UABhNUVqJ+2gVquJxz/+8ZFJiLnvLl2sWbOm0Djt4IMPFkJkt9MioAnvW9/6VvUcX4z78Ic/LACIt73tbYmTGoPBQdH7bVKV2FZA0QCkIOGVPh9++GFxwAEHiGXLlok//elPbX+GweJHGmG3ceNGAUAcd9xxsff8y7/8ixKhCJFeJbYoHn74YWHbtnjRi16knuNVYr/2ta8JIKj2zgULBoOBb3zjGwJAbEH017/+tSiVSuI1r3lNIvmbViW2KHbt2iWWL18uDjvsMPUcrxL7s5/9TLiuK44++uhE2/YgYEklgb/mNa/B2rVrccMNNyS+fv3112PdunUqqLrV7XUce+yx+OlPf4pt27bhpS99KbZv396dL2KwqLFx40b4vo8PfOADOPzww9W/m2++GQ888AAOP/xwfOpTn8LatWvxu9/9DmeccQYuvPDCyL8f/vCHKJVKOP/883M/j6rhbN68OfZapVLBz372M/zZn/0Z3vWud+Hiiy/u+vc1WDzYunUrms1m7Pl6vQ4gCKk27c5gb4OKRkxNTXW8L8/z8PSnPx31eh07duyIvW7uu0sLJ554YqFx2l/91V915fOy+j0A+NznPod3vvOd+M53voN//ud/7spnGixOFLnfdgNZbe6II47Ar371K9i2jZe//OV48MEHu/KZBv2DNWvWYP/998fGjRtjr23atAmVSgWjo6Nd+awjjjgCK1asSO3/3ve+9+HTn/40fv3rX+PUU0+F7/td+VyDxYHZ2VkAQXExws0334yTTjoJz3rWs/CjH/0Irut2/XNXrFiBI488MrXdnXjiiTjnnHNw++234zWveY06zkHCkiLsPvShD6FareI973kPdu7cGXlt165deO9734uhoSF86EMfamv7JLzkJS/BBRdcgIceegiveMUrVBl4g8HFU5/6VFx88cWxf095ylNwyCGH4OKLL8Y73vEOVZHzwx/+MN74xjdG/r3pTW/C8ccfH6naedVVVyV+3i9/+UsAwBOf+MTE18fGxnD55ZfjcY97HE455ZTU/Rj0P57whCfgj3/8Ix544IHI8xdccAFs28bTn/500+4M9irq9Tp+/etfo1Qq4UlPelLh9z344IN47LHHYs+Pj4/jxhtvxIoVK7DPPvskvtfcd5cO/vmf/xlDQ0OZ47SxsTGcccYZLe33+uuvV8QLR16/BwDf+MY38MY3vhFf/OIX8elPf7qlzzXoHxS53xbFli1bcM8998Ser9VquOqqq2DbNh73uMclvvdpT3saLr30UkxNTeGlL31pInFjMNj467/+a6xfvx5XXHGFem7Hjh245JJLcMIJJ8C2W5vu33zzzZieno49f8stt2Dnzp2Z/d/HPvYx/MM//AMuvPBCU7m4T7Ft27bYc/V6Heeeey6q1Sqe/OQnAwDuvfdevPrVr8Zhhx2GX/ziF6hWqx197u233564EPvoo4/innvuyWx3f/M3f4MvfelLuOGGG/CGN7wh8f7dz+g+DbqI8fjHPx7f+9738Ja3vAVPe9rT8I53vAOHH3441q1bh29/+9vYsWMHLrjgAlWKutXt03DSSSfhm9/8Jt7+9rfjta99LS6//HJUKpW98ZUNFgCrV6/G61//+tjzX/rSlwBAvfamN70JRx99NA4++ODE/bz2ta/F+9//ftx222145jOfide97nU4/PDDceKJJ+LII4/E9PQ0rrzySvz85z/HMcccgxNPPDH1mPbZZx9cccUVeN7znofXv/71uOqqq3Dsscd2+lUNFhk+9KEP4bLLLsMLXvACnHHGGVi1ahV+8Ytf4LLLLsM73/lOrFmzBuedd55pdwY9w2WXXYb77rsPQDDoO//88/Hggw/iIx/5CMbGxgrv5/bbb8eb3/xmvPKVr8QLXvACrFy5Ehs3bsT3vvc9bNq0CV/60pfgOE7q+819d2ngcY97HM4991yccsopieO03bt34wc/+AEOP/zwlvb7uc99Drfeeiv+8i//UhEvt912G84991ysXLkSf//3f5/6Xtu2cd5552HPnj34t3/7N6xcuRJ/+7d/28nXNFiEKHK/LYoNGzbg2GOPxQknnICXvOQl2H///bFt2zZccMEFuP322/H3f//3WL16der7n/Oc5+Ciiy7CiSeeiJe+9KW4/vrrsWrVqm58TYMFxle/+lWMj49j06ZNAICf//zn2LBhAwDg/e9/P5YtW4Z//dd/xY9+9CO84Q1vwD/+4z9i2bJl+PrXv456vY7PfvazLX/m97//fZx33nk46aST8Od//ucolUq49957cc4556BSqeCjH/1o5vu/8IUvYPfu3fjWt76FlStX4nOf+1zrX9xgwfCe97wHExMTeOELX4gDDzwQW7ZswXnnnYf77rsPX/jCFzAyMoLJyUm8/OUvx+7du/GhD30Il156aWQfRx55JJ7znOe09LlXXHEFPv7xj+O1r30tjjvuOIyMjOCRRx7BOeecg/n5eXziE5/IfP8HPvAB7Nq1C5/85Cdx2mmn4bzzzmuZrF60WGhP7kLgjjvuEKeccoo44IADhOd5Yv/99xennHKKuPPOOzvePisf5b//+78FgFSPt8Fgg+fc3HrrrQKA+Ld/+7fU7alS8T/8wz8IIYKA45NPPlkceeSRolqtikqlIp785CeLj33sY2JiYiLyXqRkRN17771i9erVYuXKlSpPymCwcPPNN4tXvvKVYv/99xee54knPOEJ4jOf+Yyo1+um3Rn0DEnVNyuVijj66KPFWWedFcnzSmsnHFu3bhX/+Z//KY4//nhxwAEHCNd1xYoVK8QJJ5wgfvzjHyd+trnvLl3ceeed4s1vfrPYf//9hW3bqv3dfffdke2KZtj99re/FX/3d38nnvrUp4ply5YJz/PEIYccIt761rfGMj6TCkoJIcTU1JQ47rjjhG3b4rzzzuv8SxosOmTdbwlFMuwmJibEl7/8ZfHyl79cHHTQQcLzPDE6Oiqe85zniG9+85uR/jMrh+yHP/yhsG1bHHPMMbH7s0F/IqnKMP1bu3at2u7hhx8WJ510khgbGxPValWccMIJ4pZbbonsq2iG3R133CE+9KEPiWc+85li5cqVwnVdccABB4i/+qu/ErfddltkW55hx9FoNMTrX/96AUD8x3/8R/snwGCv44ILLhB/8Rd/Ifbbbz819vqLv/gLcckll6ht0iq/0r/TTz89tm1eht0jjzwi/t//+3/iuOOOE/vuu69wXVfss88+4tWvfrW4+uqrI9vyDDsd73//+wUA8d73vrezE7GIYAkhRG8pQQMDAwMDAwMDA4O9g3PPPRdvfetbceqpp+Lcc89d6MMxMDAwMDAwMGgLS8oSa2BgYGBgYGBgMNg47bTTsHnzZnzkIx/BQQcd1JYtzMDAwMDAwMBgoWEUdgYGBgYGBgYGBgYGBgYGBgYGBosIA5LEZ2BgYGBgYGBgYGBgYGBgYGBgMBgwhJ2BgYGBgYGBgYGBgYGBgYGBgcEigiHsDAwMDAwMDAwMDAwMDAwMDAwMFhEMYWdgYGBgYGBgYGBgYGBgYGBgYLCIUKhKrO/72LRpE0ZHR2FZVq+PyWCRQwiByclJrFmzBrbdO87XtDsDjr3V7gDT9gyiMH2ewULAtDuDhYBpdwYLATPGM1gomD7PYCHQSrsrRNht2rQJBx98cFcOzmBwsH79ehx00EE9279pdwZJ6HW7A0zbM0iG6fMMFgKm3RksBEy7M1gImDGewULB9HkGC4Ei7a4QYTc6Oqp2ODY21vmRGfQ1JiYmcPDBB6t20SuYdmfAsbfaHWDankEUps8zWAiYdmewEDDtzmAhYMZ4BgsF0+cZLARaaXeFCDuSbY6NjZkGZqDQazmvaXcGSdgbMnLT9gySYPo8g4WAaXcGCwHT7gwWAmaMZ7BQMH2ewUKgSLszRScMDAwMDAwMDAwMDAwMDAwMDAwWEQxhZ2BgYGBgYGBgYGBgYGBgYGBgsIhgCDsDAwMDAwMDAwMDAwMDAwMDA4NFBEPYGRgYGBgYGBgYGBgYGBgYGBgYLCIYws7AwMDAwMDAwMDAwMDAwMDAwGARwRB2BgYGBgYGBgYGBgYGBgYGBgYGiwiGsDMwMDAwMDAwMDAwMDAwMDAwMFhEMISdgYGBgYGBgYGBgYGBgYGBgYHBIoIh7AwMDAwMDAwMDAwMDAwMDAwMDBYRDGFnYGBgYGBgYGBgYGBgYGBgYGCwiGAIOwMDAwMDAwMDAwMDAwMDAwMDg0UEQ9gZGBgYGBgYGBgYGBgYGBgYGBgsIhjCzgDYdi9w09cB31/oIxkMNOvAzWcDW+5c6CMxWEx4+Grg1u8t9FEYGLSPjbcCV34S2PHgQh+JwWLBw9cAt353oY/CwMBgEeGR7VM4+7qHMVNrLPShGPQxLvnTRlxz37aFPgwDg/YwNwH85vPAPZd0vCu3C4dj0M8QAvjaccHfo/sDT3n9gh7OQOBXHwVuORvY98nA39640EdjsFjw/ZOCxzVHAwc8Y0EPpWX4TcB2FvooDBYaP3orsOcxYO11wLuuWuijMVgM+P7rg8dVjwMOe/6CHoqBgcHiwL//4h5cc/923LJ2F751+jELfTgGfYjL79qMD/7gTwCAhz/7Kji2tbAHZGDQKu74IXDNp4O/P7wWGFrZ9q6Mwm4QsWst8ON3AH88L3/bbfeEf+/Z0LtjWkq45ezgkZ9bg6WN+lz49/hjC3cc7WDDrcB/HAxc9/mFPhKDhcYe2XY33rqwx2GwOCBE+PejZnHKwMAgwDX3bwcAXHmvUUcZtIffPLBD/b17praAR2Jg0CYmt4R/T+9I364ADGE3iPj9t4C7fgxc8rdRoiAJk5vDv5vzvT0uA4Olimk2aM27JhcbznkZUJ8Grv70Qh+JgYHBYkJ9Jvx7fN2CHYaBgcHiQb0ZjdfZM1uP/P+2x3bjsjs3Y92O6b15WAZ9hsm5sN3snDKEnUEfYm5P+Pf8REe7MoQdADRqwO51C30U3cPcOPt7T+pmAID5yfDvmV09OZwlB4tZB/3mwh2HweLB1Pbw7+k+W3H2TQaNAYCmaQcGGvj4oTaTvl2PIYTA5j2zC/b5BgYGITaNR69FnZg7/+bH8L7zbsMv79oMA4M0jM9wws4ISgz6EJykM4RdF/DjtwFffgaw4Q8LfSTdASfpWiLsdvbmeJYaeNZX3vk3WBrgJN3U1oU7DgODdhEZbIioHdJgaWKOtYnGwk2ofnzrBjznP67Gmdc8tGDHYNB/uGvjHmzYvXBE86Bi90xUUffYrug5JiJmebW0147JoP8wPhuq6nZMG4WdQR8iorCbTN+uAAxhN7sbuO8Xwd93X7ywx9ItzI6HfxvCbu/CbwJNdmMxqkUDAJjmCrvOcgwMDBYE+upgo8+s3QbdB28T9YUjPr534zoAwOd/dT+afgEi+Y4fAef9VTRfxmBJYdP4LF7zvzfg+Z+7BsIsPnQVE5oFVs8fo9eXVb29dkwG/Yfd02E72jFpFHYGfQhD2HUROx4M/y6PLtxxdBMtEXZT4d+GXOoctano/2fNOTVA1C5W7yPrVjM68EbDrHIuWcxNZP/fYOmBE3YLSOCuHimrv8eLhJNf9C7gwV8D5/91D4/KYDHj/i3h5GnTHrP40E1MzkXjEzjxAoTKqeVDhrAzSAfPPpyaN5EcBn2IiOPRWGI7Ax9wDoryhWfYzecRdnyFvI+IhMUKnUHXCTyDpQk+mV1A61jL0Nsz71sMlhb0xR9j9zeYWxzjh93MLtVSNcHNf8rdpOkL3LVxDxpakL5Bf4Pb7W5fP75wB5KEqW3AN08ALn7fQh9JW5iYy1bYkSXWKOwM0lBv+hGSbqZm8sAN+hB8jGQUdh1iEC2h7VpiF9DSMjDQL8h+qwhq0Btwkq7RR8R4TDE6viCHYbAIoLeFDgcfBgMA3gYWUGG3jdmldmlqnk7x/gtuw2v+9wacec3DXd2vwcJiy56wzWybWGTjtKv/Hdh4K3D7+X1ZuEy3xOqq1z3GEmuQA52gm6v333VgYIAaGyOZohMdIkLYDYDCzvejDSSPsOOTMKOw6xwxws6QoAboY4WdRtIYxejShU7INPuoHRv0BrxNLNC9TgiBHayCYEsKuxzUGj5+eWeQc/eHR028xSBhKyPpFp3djsfT8PzbPgFZYkfKLgBgFytCMVdvYr4RqFWNJdYgDbMaYaf/v2X4PvCHc4Atd3W2HwODVlDv3hjJEHaDluGmT6r0CbeOiMLOEHYdoxYtX2+C2Q0AREm6frrOdAI6qz2PPwZsvae3x2OwcNCJZtO3GfCMywVSk883fNSbYdGA3XnVBFtQLHFSxyg8Bgu7WDuZml9kvy1XsvdhVXmyxB6ycghAVGFH6jrHthShZ2CgY1brb2c67X/v+Snwi38Avv68zvZjYFAUQkQXtjvMADeEHZ+Q6mRLP0InA/JUEItghXygoE9q+4mcMegd+lVhV9MVoxnt+UtPA856jqm8OKjQf3tTgMQgMhhdGMJOt07tylPY6YsQGRVCN42HbX7nlGnvixFCCNz0yM4IuVoEnBCYmmfE89xEZpvYK+DxPFPbFu442gQp7A5eWQUQVb3y/DrLsvb+wRn0BWZqUdVrxwq7TX8M/17o69tgaaDLrhRD2A1a0QU9HyuPHOCv+/V4VUiD1qBfoEaFYgD0cYadRuKn9Se839h4a++Ox2DhYBR2Bjo4adut8VOLkyldiTE1l2NvjKmG08dIm1n10O1TfbTQsoTwnd+uw8ln34S//8GfWnofJwBUm3nwCuA/DwZu+GIXj7ANcMKuDxfA6NyuWR4QduMsV9Lk1xkUga5onq13aFt3w0riA+GmM1j86DIfYAi7QbOE6raUvAZiFGHdRex8mkmtAfpXYRcjaVL6B14JqQ8zdwwKILZaaBRHSx68Dfh1oNnhpOoP5wCfPRDY8IfCb5nVlBi51QRjldzTnRXbJsM2PznXMLbYRYgvXvEAAODGR1orGscVPCrD7tr/CB6v+lR3FMTTO4B7ftbauNr3o4RdH1bjJhJ9zbKAsJucb6AuqyyTPdYQdgZZ0PvxjhV2s7vDv3ev7WxfBgZFEJs/GUtsZ4hUORsAsqoThR1gCLtOETv/5nwaQLOe91Gb0EmaNAKaK5V3r+vZ4RgsIIzCzkCHbvHo5H4nRJAxVJ8Grvvvwm/TJ3a6lSqGWGGodMJuYja6r1aLE/zPFQ/gtHNuwZY95lrZG5icK+4Qma377H3yd+Xk7fhjnR/QZR8GfvQ3wIVvLf6e+QlAsDbdh1E1RGzvt6wCcr2SFdYo7AyKIFZ0gl2vbYErVacHoMCkweJHqxFlOTCEHZ90NGudrxAvNFpV2OkNqA8HB4sKRmFnkISIJbaPFHZFJ+ScsDN2g8FEq4tBBoMPPUKjk/vdxKbw7+HVhd+mE3bTeUoMvR1nKOyIXCC0ovKoN318+aoHcd0D2/GZX95b+H0GxTHfaEZI1A27ixPGXJk5XWsEhPGuR8INJjZ2foAPXhE8PnB5oJwrghih3H9jciLshkuOIuYox46uKVMh1iALpNIsOQFNoSupWwYfl/bhNbU3UGt0SIoaRGEUdl1GUctXv8Ao7BYWMc+6OZ8G0Cyxs/0TehvrH1P6E26JNUTOYKJoWzBYOtDbQCcryG3mCesk2kyeCk4fNLdC2LVgiX14+5T6e/ukWbjrBTaNR8/r5j0ttJu6lmE3uztq8Z7c3NnBCRG9PsbXFXtfbUr7f/+RC3Ruq56DFUMlAGH1ZqOwMygC6tdXDgftp5W+NxGcpDPz3Bh+cMtjeOrHf4WL/7hhoQ9lcKDP/43CrkPoOTz9fiG3nGFnCKauwijsDJLA24XwAb9PlLxFCX0+2TZ9yGDCFNQxQLAKf+Y1D+G6B7bHFXadFK2aZ0TFTHHLkj6Ry82w0wfNPVLY3bc5VErtMBVme4JtWmXYybyCIwy8nczV/Xhxh04VdtPbo21t233F3qe3xwzL9mIFXZOVkoMVQ6SwC64lssYuN4SdQQZmNMIut1/PAx+7GoVdBEIIfOSiO1Fr+vi/m7oQBWAQoMuL3G5H7x4ExDKa+nyyqXdEuQo7OZC0vSA0ug9X8xYVqD1ZdkDMGPLCAEjuZ5w+GLAWzS0zCrvBh1HYGQD45M/vxnk3P4YDl1fx28frCrsOCLsaswLOFC8gEM+wy7PEFj/mibn2FXYbx8N7v04sGXQH4xqhOtECYcfJ1/lGM66om9za0bFFLN4AMLkpeTsdMUts/40hZ2uBtS6isJOWWHpcLp83MEgC9bWkxOzYrtkwhF0aeIyEQ6GTBp1D77s7HDMbhd2gWUJbJSBp+8pY8Ggq/3UGUtRVlsv/93l7MugO+jWwP5Zxmaaw48V7+uS7GbQG+u1tuc5XRN6/t6zf634L/PzvzYLTXsANDwXqt43js/Hxgt+Jwo71IdPFCTvKNlollRjTeVlH+jFnjHk6Udhxkm7CVJjtCfTfp2jRiXrTR8MP+6b5hg9MaQRdp9VZ9ffrCj6Gb13/CE4++8Ygj28ALLFz3BI7HCXsSGG3YrgPFiwNFgzzOmHX9CE6GU9EFHZmXsZBdnUgqOhs0CV0MzIEhrBLsMT2380xAuqISiPBYxaj6/vhAJu272SF3IARoMui/zdY2tDbQb9cZ0WJRr56aZRXgwn6XVXflvM7P3gF8F9HAHf9pPPPvu37wNefD2z6Y/w1vwl891XArd8Bbv1u559lkAm+Au/Xu6iw45bYDJuqDt06lUuqxQbR6YTdhCSERssBSd2Kwm6LpqrbOW0WQ7uNCY2wmyqosNNVmPMNP67q5DEP7UB//0R6Jt6nL70XNz2yCxfc/Fj0OgD6ck6iMuy4JXbaKOwMimNeKupGK0HfKwQiJHvL4PFEfXhN9RJ0TQLA9kkzfu8aaF5UGpX/N0UnOsOgWWLp+1RXRP+fBM72lmWDMgq7zqAmtaRYNKsVBohPZDtRouxNUHt2yvL/aYQd6zf6vQ81SEarixG/+wowuwv48duTKyTueAi48K3AjgfzP/vqTwNb7gTOflH8ta13hX/P7s7fl0FnYI6Zhp7R2kk2J1cWtTChookdEXbTeQqBmMIuuS8WQigF1/7LKgBaU9htmYhOfHKLYRi0DFJrEYpm2Olqx6Yv0JyWVSRH9pMbdVthl0zYzTBF6NaJufA6sJzgsc/IhXrTR1MSK5WIwi6aYbfCEHYGGQgJu1CJ2ZEttmEUdmnYxRaTdk7Po9E01WK7An2R2yjsOoTOePb7hUzHX0QFwSdchrDrDuiclo3F2IBBJ+j6hcjVbzhpRVT4jcgo7AYTMYVdTt9mM8vT7K74619/HnD3xcDPP5j/2VPpdrJI1tTceP6+DDrCHCOtml1V2DFLrF8v3EfSJI6sU7kquIKW2Nl6E/VmQDwowq4FhZ2eW9dxaLpBDESoDpUCcquoJZbaDI9r8mdkH7X80OBxrkOFHb2f+supbYmbrdsREnLbp+ZDwo6Iwz6zxPJrpOLZsSqxSmFnik4YZGC+EbQjUtgBHRB2zXp0ManPrqlegy98CAFMz5t7VVeg+ABS2BnCrjPQRJMIln63MNKAucj3URMuC/Cq0fcbtAdD2BkkIVZNsU/aheofyTKfctz8+X7vQw2S0eq9kitM9Mmq3wzfP76+tePwtcEkt7Jl5EQZdAc84yZG2HWiHNazuwoWbKpJNcCYJADqTaEUPokoaImdmA2+p2NbKh+vqMKu6Qtsk9YistPmZusZtAwqOnHQimD8WlRhR+qdkXJIBvgzUp274rDgsVsKuxWHB48p6l9enGTznrnQEjuyT/DYZwo7IvQtCyg5IWG3a6aG+UZTEddGYWeQhfl6cI0Olx1FrNfbVX7pQpw+u6Z6jV1aXMOUuVd1B4qPMYRddyBP4K6GtHx1KFlccPh6A8ki7ORrbiW0vPULkbBYoQg7kwlowKCTDH1jiZXtmTIu0yxvDUPY9RRrrwMufBuwa+3CHQPdG0o55C2Bh7hPa4TdDFPcVZdl70cfbM9oar2ZHcmfadB1+L4IgvElhK6ybPF+98j2Kbz8f67DxX/cEM+tK+h2INXFGLNOkTojEQUtsaTeGqu4qJZay7DbOT2Ppi9gW8DBK4eC9xqFXdexRxF2wTkuGphObabsOig5chpEhNoKqbCb7xZhd5jcf4LKGFEL98RsPSQThlYHj33m+plX59aGZVkqw258pq6UPLYVVU4ZGOigdlTxwmt0vl2FXYyw669rqteY0Qg6E9/QJSjCTo6ZRTM+F2wBS56wE5Kw214nwqpPJtJpUJOq4ej/s7Z1S4Dj5W9vkI9WJ7UGSwN9a4mV7VdZ5lP6R6Ow6y2u/CRw90XAN45fuGOg3740FP1/EoSIkmdT26Ovc5JtModk09V5Ovk3zfalk3kGXcVMvRkp/Cv0FeMWM+w+dvFduH/rJP7hh7e3rYIghR0nAObqGRO7ggo7IoOWVT1UvcByWdTWunVP8BmrR8oYq7otvdegOPZIeyVZlucLEqqk1Cm7NsquRthxS2xS9mZRUNEJIuzqM4mRElx5OTnXCK+D6vLgsc9EBHRuPUmyULbkrulapOCEbVvJOzAwQLjoUnZtlOQ1WmtXYaertevFixotBegLUVOGsOsOdD4G6Ehlt7QJO9+HJSfSU5CW0H7PX1KTKtlA/AaQVgqbB8o7pej7DdqDfv4NYWcAhO3Co+uyT64zXWGXaok1GXY9xcY/BI+dqj46Af32niTsstpwYy7aVrJItult2QS2rkzRCTxuiTUr5z2FXoXTiln9W+vXHtrObLB639Kiwq7iOfCcgATQiwpEj7FYhh0n7MqeHfmsPFCF2P3GKhgidZ4h7LoO+o32Gw0Iu0yiloEm/iXXRlmSsRYp4pYfIrcSnU3syeI9tgawNFKQYYblRe2ZrbeeFbrIQLmPpIqiarATc3XsnCLCzuTXGWRjnqlgiVRvO8OOE+X7PTUk0Q0AxBeTzOJSl0Bj5NIocMSLgSe8AhDtLwItbU0ym2ROCcpw66+bYww6YUTPuQl5EfRdnVJI2PULkbBYoc6/UdgZSAgRSKGBICuyPt0/xDi133KOJZZ/n8Zc8J0ts4LeFegLLvOToeJxbyK2GJHRhnWyRZ+oTmuKu/o04KRYY/WAaD1biu/bZNP0FPrKu+XTGKIcjKdaHD/wCVizPgeHv9giYVdybVRcB/VmI9s6VTjDTlpiq55SCxXNUNrKCDsi+0yGXfcxrqr4Bg6ZuSwrNINqM06osLOInBveB0EpZBH0Pe32tUQSeENAdUWwsDC7Gxg7ILIZbxdT8w349dlASaFykPtrAazOyFAgJOeEANbuCM6xya8zyANl2JVdW5G/7RN2clwwdiDwvt924/AGCvoCl1HYdQm0EO1VgdN+2vHulrbCjg3cJhdaYTexCfjqscCXj+7M1iMHn023Gj6XNoimybfjGktst9CKJdlgaYATG0XUSYsJ1B/Scae1Z95vCr9/CMl+gF75NKmwQmMe2PFgb4+jFcJOzyOb1woKcFUckF21TSdu9OIE/P+GsOspYtlwPluIAFq2+nNX3NxsezlDIfliKbVUtsKuNUvsWNVrWeFBhN3+y8oYatFOa1AMvi8UqbrvGCnsChJ2ZNt0LUWo2kTYlUfC+10nCjvqi7xqQNgBiTl2uvKyOS/fRwo7v9GZNXcvg8hyIrk9x8aYtKuHhJ1R2Blkg+41pW5YYlX8U6UbhzZw0PsgPdPOoE0oUVR3+rulTdixgdqMkBfyQq1mPXItsON+YPda4NHftb8fOYn64rUb2XPZlR13zgE/uX1b5P0GbaKVnCeDpQFOzrU5sV0wxBSjaRl22vMmx6572LMx+v+JTfFtLvsX4KvPAh66snfH0YolNkayTUb/ry9K6QRfZF8aCaeTf/y9jbm+mtz2G3Tlmk2LfnmEfgqmmR3Q1xdLCxJ2XNFDxFomcaMshpItLGCJJattywq70QqGy8YS2wtMzjdAxYBbtsRGFHYObPhwmqSIGw4XJbIWEvJA90CvClRXBn8nWGJ15WWjphF2QF+p7MIMu5CNXzUSKCAf3Bb03cuNws4gB9wSW+rUEqvin0y7S0I8w87cq7oCGiMbwq4LkDfUOeGhRu7ghSJYeC7P9vva348cfM6BdUxp5ID8rtummxin8YBRhHUGU3TCQEdEYUcLA33SLnyNgE61xHYWPm+QgbE1wBu+Hf5fz3Br1IBbvxP8fd0XenccreRz6sqUGMmmEXhZSpY88k/ft1HZ9Qz6hMkSRNjJfq0F5fB8oxlRTPh1rQ/Rg8LTjokRdhWvQDVBZfPPLqTDCTtlySpI2G2ZCL7LfssqqJYChZ2xxHYXpK6reLYq7FFYYdeIkrxDYAtMpeHwftdJX0KWWLcSKuwS3DMz2uTYr8n3ccKuj3JhQwI9NLjvOxoQdvdsCuIMVg0b4sQgG4qw8+zOCbtmd4mTQcOsttBhqsR2CdTubEPYdQ55MmtwUYM8oQt1Y+SZPjseaH8/csA8Dw81IW+YaRMrOaluwEF9oQnLQYEpOmGgg5NXZFXvF0usKpaRk/EZC3Lvk+/XDxhaCTztjcBRrwn+rxee2HE/+09KgaFuQFfYZalEdWWKbmPNUsnpyCX/tNdN4YmeQSfCQsKudUX5tEZUxCrOFvwd55VaykGlkCW22KLaBFfYtWqJ3SMtsWMVVWG2KJlkUAwTc8HvM1rx1O8+3/Ah0oqsMfBKpgFhJ9ue5QBuOSwOldUv5X4Is8QOkcIuTtjpRK4gopoy7IC+Gkcqwo4p7KiK7w5ZdOKAZcaaaJANqvjMM+wyF2KyoCyx5W4c2sBhTqq/V0sl7PSAEHa+Lxb2vttloniJE3bBRVznhN1C3Rg5Ybf70fb3IxtIlITLnmQH3z+H3DMoBqVIkpMB4Yc5PwZLE0TYWXZY/KXfLLE0gUmbkOuV7PqFkOwnkOJibiL6PM+0G3+sd5+viI42LLF5JFsmYddChh3QWe6UQSbmtcGv47NQZaAlZa1ecVapdG05bmmj6ERoiS1QdKKcQ9hJQmisEirsCltiJ8OiE6QOaXuyaZAIInxHyq4i7IBi57mm7HaBemfIYtXQLSvs4zoh7BpcYZduiY1lG6piFZWgmAvQuZCgWQdu/2Fnc4uCqGkZdkBI2IX/r8LAIAuJlti2M+yMJTYLZImlbMlBuFfNN5p487duwp//+xXYOL5Ai7jGEpuC2XFg/e9bew8jt+aJ3FoohR23OU1sTN8uD0TCCRcNIuFyKjvW4aIucsg9g2LQV+/5cwZLE1wWTdLoNLJDCGD7A4uH0GvXEmsUdt0HKS7mdcJuc/i3XkG1W/B9Vum4DUtsHsnWUYadTtgZhV2vEFPYQS86Ufy6j1WiaxRTvukICQKLKa0yFsl8XQVfwBLbwoRxrt7E+IysXjpWablghUExkApkuOyg4oZTmSKKCm6j9hwbw6Swozahik50YomdDfeVZYnVCDuLE32kCGpzDHnL2l04+7qHUbvnF8DF7wa+/PSgyngPUWsGCscIYTcWJeyMwq4gNt8OPHbTQh/FgmA+QqoH/bqxxPYGRNgtHyDC7voHduCmR3ZhutbEtfdvy39DL2AssQmozQBnHw98+y9aK9jgxwmrmC1jb4FXzZvY1P6EPaKayyHhyBIrjCW2a9CLTgCGsFvq4KsstMKXdp395nPAmccAfzhn7xxbHpTCLidUXv8+JsOu+6hIwi5LYVeb6k0fzglmRXRk/MY0WS2NhsfFoU8aiyjs6Nrh+2rU2CIJfZbJsOsVohMmAZcssW1Y/XXCziLSn4jpgmOxeiTDThJ2WQq7pm7jLVJ0QirsGvl2Syo4UXaDbLWO85cMEkHtZ7jkwnVsuLLkcJHCE1wF5jlWmGFH4zYijTuyxBJhVwGGqEpsXGFH5LIjj99uMsKO+rw25iUbds/gTd+4EZ/95X14+IF7whe2dxC5UwB1pnglPG7fkcg2a5YbhV0ufB/4xguBc14ObL8/f/sBQ6RKrNNphh1V6zQKuyRQQaRl1eD8ZC549QnW7w7Hgbeui/e7ewWKKO5OuxsMwu6xG4Hd64K/W6mSRwoz4Shyy9etXXsLfBIimsDUlvRtsyAHo/UiuXSyEytknzUoBj3nCTAk6FIHTRBtF3DkdZY0sRUCuPY/gr+v72HxgFYQI+zSLLFGYddzpCrstHuFTuh1A/y+UMQSSxPdkX2CxzRVnCuVFllKFpr4juwn98XIPq7kG16dvy+DjsBX3m2el9hG9eup+Wj7sX29GERBhV0zVGIoS2ymwq5Y7l5S0Yn5Agq7rbLgxP7LKrAsq7WCFb6fXAXaIAZS2I3IKryF8gsllMLOseE6NoaVJVYuRnRadEKIsGiKWw0VdrPjsU2JBCY7mk3EtVdlCrvWCbuNu0OlcWNqR/iCnoHaZfB8QMJT1oQFNFYOl7DPqMkSywXPO7zrooU7jgWAEAJ1qdQsuTZKbkBmN9qtAG8Iu0zEFHYFq20vZtB9GADu3dJbVXEqVLszCrsQPP9t/S3F36cssWGGXbM+l/WO3kG38expzxYrmMKuoYpOpBF2vOiGIey6Ah5uai9wLqLB4gBX2Kk2kTCx5X3AikN7f1xFUNgSq2fYGYVd15GmsOPqbACYG+/+Z0cqHRexxMqJLpFsaUUn0l5P2tfwPvFtaT9OCaguj25v0HXwlXcP7Br3WlfY6UUn7Fj11tYssbzoROaEQ+/TUotOBN+PF52oF1B4bJ8MJgr7yADvcpFjIvzqX4EvPgl4sIWF5yUKpbBThF0BslaC5x6WHFYllpR1ROa2q9blC1heNcwfTSDLiDxcPhSQCQ6RcxGFXetjSF7Mwp5jCpNeLOgwhHbjsOjEyuESnnxAcP962ZP36+nnDwx4TNKe9Qt3HAsAIuuAgPh1bTv2fEtoGMIuC5RNO1YZHEssKd0B4JHtU2j6PSzIlgaaBxnCjoETdlvuCFa3Nt4GbLsv+31+mGEXEnYLZImlgcHwvsFjmx20aISEnVLNpQ2i2fc3ltguwG8GRSaA4Mag7I+GsFvS4DkGTkaGHbfLLBbSobAl1hSd6DnSFHZ6bl1PCDv5+1o2U31kWWLlYIlUb4256PZEuhEJl7VQRvfGEXlv5Go9UvKVhrsX0G6QCj6Qd8AG9W1k2OlKKJv6DCoGUfB35OSLIm0yq8TmW2JrDV+pDsaqbksquZ3TwXFTxb2WFHY3fz14vPLj+dsucRDhS4Rd2SWFXf555iowz7EwZHU5w67BFt+8KlCmgkEJhJ1svyuGPFjw4Qpa9K10pLCbZEVdnAhh11uFXVLRCQA4753PxpdPPhr/+qon9fTzFzv8osTB1Nbwb31RbsDBi/sEKtiA/G0ahV1PQPem0UrQlw5CRfMte8Ix5XzDjyiO9xqo3ZkMOwa+EjG3B7jpLOCbLwa+/bLsgNUEhZm/UIQdWXv2eWLwuGdDW7vx2XfKrxLLCDthCLuOwc+dw8gZc06XNtQqi5utuuSE3dT2+Ot7G0KExFueJVZ/frEUzRgkpCns9AlYgu2qY/ABbxbprLaX99GhVeFzNXYvJqKNXs+akNLkl8i/WhJhN8L6W7NA0ivQZHys4sLlCjuVYVf8utdX8RVR0aYl1nOskLQpUnSC7NgJVdzJDgsAoxVPqYWKVIndIRV2q0eDyWFbRSeswRia9xKkIBspB795K+eZV4n1uMKO7nOebBuNNh03pJa3nKBfqqQTdnQdLB8qoQyuZK6EfVo7CjumYC3XxtkH9lZhp6yMGmG3YriE1x19IJZVl2bw/+RcHSd97bd46id+hdvXj+e/gc9rp3ekbzeA4P2s51gqn7JthZ1yPhnCTge3HxNh16rC7v4tk4su9258Njo+fWj7Athiu1zsZDBGBXpn9qt/DR7n9wA7H05/HyOsaiI4oaLdG3QnaNTCge7qxwePbVaKJYVdUEiiuCU23NZMdtoGP3dGYWdAiCjsiBhPmNhywm56e5BntJDgk29SHohm8nHpE3WjsOs+chV2lvb/LoKH53LSWaQMoHm1bOoHSRknREi6EWGXNSGlz6ZtIwq7yfjnmAWSnoEG5WNVD25EYScJjhbOvT4pcKiARYuEHVdLlaXCLrvoRHHCbrTiwrEtlJziVQq3TwXHrRR2kkjKndBw+6Xt5H7OUoduiW2luEedVTKNVomV6k4ioNutOE3qUFLIKcJuInb/rMl2sWLIQwWszbvVUDXchsJumhV1KdfHwxd6bYklhZ07GNPLbuH8mx/DHx8bx0ytiS9eUaDwB3eOLTGFHS3C2BaCgjKS/G10StgZhV0MXPkdWmKLk2/X3LcNL//SdfjYxXd1/dg6AfV/a2RF6oe2ZcSu9ArGEpuAmYzVBypGkYSIJZaqxC4AucKDs1d3prDjVWIbeTZX+v4iVOMJQy61D36euf3RnNOlDSKvbKawSyK0uJVRNLNzvfYGIrllrKpb0rHTpNdt3RpnUBB5hN3YmuCx3UlmFvhKIR98JJAdAKKZMariomzP9ZkwOmBopdx/lsJOU+vVJkOikFtiO7CPGRQDEWGjFQ8u5G9vOaxfa0VhF7YdB03YRABStd+CltgGI18qrSjsiGRMOGZecAIAvFYUdlPBca+iDLuiRBIvNpHlDDEAEC86oQi7ZvGiE55jo+TaGNKLTtD9rt0FfL06IBF2ELH7Oh3LCq6wowJVbvs2/0lG2JWa7J7Qc4VdWNDDIMQV94QW11vW7kIjry/hFYoHhLDbPjmPv/7GjTj/5scyt+OEOgB4tik60Svw+1I7Crtv3fAIAODHt25Q1WYXA+j+8IyDlwNYIMLOWGITQIObA58Vf2332vT3kcJMuGhYwUBPLMREk1ZWbRdYeXjwd7sho4ywyy0kwS2xC10ldxCgcp4cwLaD3xNIn9QaLA3wVZYsmzRX2AELn2PH+428qseq8mL6JNigQ5Aldp4RVkKERO/o/sFjoxeEXYIlFkhXUjaZwoQyyUgZpxRyVlgoImtCSp9dleSe8ENSkiY15RETQbAXQAP5kbITEna2G97rRPF7HWWNjZRdlLgVkNpLgd9RCIGGzIRyHUsp7JJyzO7ZNIHfPLAdgtTNGTbeibngs0lxoKrEFpjI7JyiohPB5LCw8osXJDCEXS6mNYUdTe5rjXwVDpElrrTbDSOFsKvP4rcP7cDffPtmXPKnFlwvOkHgsQISmgK6xiyxFYuse9Xo+/MWfX//LeCXH4pcM1xh5/mMeOyxwq7OLOoGAepNH3dtCn/32XoTD2zNIRD4+G9+oi1b9GLDV656EDev3YWPXnxnZpZfvRElfR1ZdKLRbuEAnUA3UOD3pREi7NqsErt2x3T+RnsJpMB++kHLASwUYdfddtd9wm5i094nKGjF6kmvib82uSX9fYywKpXKkef2Kqhj9oaBZQcFf7dZJZYGn3U4qFOV2NTKjvG8uwVRGA4KfO3itHMUjgZLAzRBtF2W/5VjiQWiK6wLAX6MnLBLVNjlT4INOgQp7IQfVavRuR6RhF0vFXa2F10tTJtIKoWdFyqmyL5Kx14aCW2JWRNSRditCJ+jfcxzS2w5ur1B10GD++GyC9eS4zzHCxaogLYUdmMVN1pxVlli81VFfALn2aHCTifWZmtNvOGs3+H0c27B3Lzcb8biwoSusHOoSmERhV2yJTa36AQn6XpxDQ8YYpbYFop7hKpMC55jo6ossZKwc8MMuzPOvw3XP7gDn/z5PcUPTh8LAok5do2mD2rCEUssKeuK2Pwfuxm49J+AW84GHrtJPT3Fik6UBLuW6r0dV4RVYgdDD9INrN0xjbm6j5Gyi2cdGtzHHtqeQyDo6s4eFwvZG7ibkZb3bkknjhXpK9sQkb+5qsQ00IKgIexi4BmwVapo3oIldu32sD8Zn1kcY69G01djgGccHPS7D22bgkiLcOkVFGHndmV33e1R1/8+KEl/7utC0m5vnCCa2B7yHODP3wYccDTwnDOC57JWk5Ql1g0Ju4XIXlK2nqGQsJvd1daE3Uq0xGZXdlxwS/CgQGfTs8gZg6UDNXhnZEfSALymKeoWi8KOE41AMYWdIam7D68aLgLQfY0G8ZYDDEvLaE8IOyLg9LaQthhE25fDSTAp64hsKzOSLUthp/KgKsGiFhCSG5EqsaX8fRl0BBrcD5dcprBzgvYHtJS7ye21HtgEQdkRCxB2LNPIdSxUPKoUGp1wbJ2YU1VflYtCLS6kZ9gRYUe21iKh52SJ1avE5qoWDGHXEqioAhWdoMl9vUiGHaky7cASO5xmia3PYPdM0BZ2TbcwNk4KGyfCjllSObm4fKgUEnb0+cqlkTGG3HF/+DcTKEzV6D0CZbBrqcdj/LQqsUsZj0hS44h9hnHoqqCNrd+VM77Tx389tjLvDWxmlTuzvn9NU2lSldhWi07snq5hz0zdWGIzUGNqxoqXvOCVBiEEdrB+kfrKhcY0s+Y+7cBlsC1gYq6BTXv2co2CpIWbDtDdHvXBXwWP664H1v4GmNkFfO044Ly/6urHxMAH7Sd+CXjPb0JraUYnR+RULaKwWwByRSnshoKb+vA+wf8vfBuw9rqWdmXJBlKPVIlNy7ALvmuDqfFMhl0HaDJVCcAGW4ujEzNYIESKTmRk2Okr3zqBt7fBj9uy0slG3wcgB1JqEmzafNdhWfEcOyLsKstCMqsXk31l6y5JgoYUVS1YYmuaJbY0ElZty1TYscmvvq/EKrGm7fUKpHyoeNwS67VliaVJwVjVjebhOcXdDnVGELqOpYg1nbDbOR0SFrbQFheSMuxmkhV2TV+gmWHLmqk1MCMnC6ukJbZMk6BchR1T3Ph1E6WRA6oSO1xqR2EXWmI9xwqrxOoKu3q7GXYJBAH13UwpVWf23RVDXphhR5/vFCDseNG9qTAnbV5eA2XUYYO12R4X1uNFYAwCPLozuE8dtmoYB68Mxkj5hN1gKewaTR9bJ8LvtCWDPNFJX1dZYosvCG2bnMMJX7gWr/jydWHUk6kSG4Mi7Fxb3T+LEnbTtWbEUrt7kSjsKA7AcyyMVjwcLXPsLr8rw3HZC/A5VBfQ3R518x3h32uvA274IrD9PuDBXwOTW9Pf1yk4YUcop5dRJzSooipcVMrBINFaiIkmJ+wA4OBnB48P/gr4/l9mV7rVoAi7SJXY7Ay7OsuwWzKTndnd2XbpdsAVSUBY6W0pDbzX/x64+tPtD3QHETTYth1mk064JnWiZaGLTugVjtLIxoh1lhR2C6gq3XYv8PMPAg/8euGOoVegHDtdYVdZFp77XhJ2qm/LKaiTVHSiXYUdJ//S9mWKTuwV0GR8qKRn2OXEbyQgtMR68Li9toXfkSvsPDtdIUA2VYARdm6GJVZm2C0bCtq5y/K4smyxO+XnlF07LIagstX8bEuOnltnVHaZ0DPsChf3QKjUcW29Siwp7MgS2+ZvoC/eAomW2HlWIGPZkBdm2NHnZynyCbwgASfs5HmoQruOeqxApnNrik6EWLczmOMdtmoIB68I5nmPLTGF3dbJefC1jq2T6e1Qb0OuLDqRtVii48I/bMDumTo275nD7Ky8jo3CLoZ5Ro6W3WSFehp2TUXHf4vFEqvfG1539IEAggxFurfvFSQprTtAd3vUXYxYWns98PC14f83/6mrH6Xg+9FVdkJFUyIkoFEPLaGKsBMLMNFU7L8cqD7pteFrfh2455Ji+/F92HKFu1Kp5JNwZJ8VLhxvCeX/7FoLfPHJwP88Nfi7W9AJjiKDrUHDeW8Ervs88Mt/XugjWTzw2cRWqYAS+hl9grZYLLF57ZlPeNUkeAHb/NWfBm79LnB+j5XdC4FMhZ1c8OlFu+GkM5CvZuMKE8okS8qda1thNx3dZ0RhtwTuYQsEIsiqnLBzmMKuhcWpUGHnwaUMO9tj1ub835HIM9sCbNtCxSP7qaawYxMLpwBhR5bYMRnCTQoPIHvSuFPag1YNl2BZwSSTZ3llWrr0saoh7DIRWmKp6ETxSr6k1HEdC67Dq8TK/oWU4trCY+EMrSxLLCPsuLpluOSyDLtK9P1Z91OusJveHtt3Fdp11GOFncmwi2PznuBaPnBFFfsvC37b7RmEFYCBy7DbPB7tz7ZmKOx0laarMkSLE3YbdoefNzdPhF13iJNBAr9eqWhTUYUdV64Di8cSq/JNpfr6zc8+BI/bdwR7Zuu46NYNe+9A/MVM2PEbx8Y/AFvvDP+/7d6ufpRCYxbKjhVR2GlKhAQ060Fjq7MMO2sh8sa4ggAAnv4m4NVfAEYPCP6/p2ADYzf14aEqGvTzpnwnwTL8yuUllD21+XYZ1l4HttyZv31RNHUVSgE7QytYe33vrqNugSpW/vH7+dtuuRN46KqeHs6igGBZT3bGAFwnWhaTJRZIJ2mSCLuF7Ed2rwv/3tshs72GPumjx+rySGXDriOmsMshaIg0c0vhfVkn2cqjrWXYOUxhp1tiuVpvKdzDFgg0uK9GLLHcIt2Cwk5mui2renAgJwiOW7wyJuITu1AhEJ1wUOVWQISfRddLgQw7rrBrZEwaKeh/tBIO0MuMuMgM89YV1b2o9jwgEEKEllhSMrZg5+JFJ0qOhaEUhZ3QfgMiCXORZInV1dEISbWyY2O47KIiLbGC7qNFlKszKYQdXauW1rf2eEHDZNjFsXUi+A32G6uobMsdUzmEnX4f73F1316D+lTC9ozvrzLs3KDfbafoBD+/NSo01CVr4iAhyRLb9EWhc63neuq/8UJhVsZSDFO+qWPjDc8M6gP8ft3u1Pd1Hcp1t9gIu2Y9nKyTHZWD3Ui6ClWYwQpXxYDEgFcdzbq8OVouHC84ofZCKEMa2s3dsoBj3gkc/y/B/ycKVoxlN+LhahUNkU0Y+Y3QEluRhJ3tLwF1Aq/GObure/vVJ7VFVkeL4p6fAd97DfD9kwaDhBAC+L83Av/3l8AdP1roo+kteLvIUibFik4sdJVYbXWokCV2kVWJXehKu92GUthJlRpX2Lkd2riy4DMFFJC/GJFIssnfQmXYFbSxJllik/Zlik70HIkKO9sLiQXRQtGJSJVYti+luixuiSVyQCnsNGJsXE4kIsUtiijsiLCzmSU2I0dpaj5430glrArHiYsssi9uiTWxEmmYqTXVMIgmZaWWLLFSYSctsUphRypl+Si03yAs5JCDRMKOFlvG1VNc3TJUclCWltgmLT4oVXvG5/LxLGtDC6Wwq2sFAwYZ/3fTo/jSlQ/kVp+k7LaAsAvaxO6ZerYalAg7qrLe55ZYUj0RJubS23SdFUIAwv633oIllisYa7UEi7oBgPB6LTFLLFBs4UMn6GYLWml7DTp2isgAguITAHDXpr2oVKV+e9Ep7ChHwbKBJ50Yf52r77oJuSopSkP400bWofHVrJTOtCmJMt92Ycsbq70QllhdYUegirF7ihJ24cUzVK2iqRR2yRdRU1qCm7BRqS6gwnBvgw2YIvkfnUInOLqZYXf7D4LHyc3A1LbO99cLtJJbNrUNmJIZgnf9pDfHs1hAv7/lZBMdpLCjiouLRWGXa4nlk2Cqtr2A/QhXEPS5jSSGsjZ4p74sYontRZVYUlsWVA9HSDZS2FFlV25jLWB/5O1Q7UvPsDNFJ/YG6kxh51hyQG+77Vli6wmWWMdjqsv8xUNubQTAqsRGJxtUCMJJqkablGE3GzxHCjvLstSkMYt0m5STULJpAoBjW5Du2EyyL1J0Alj4SIRFDMoosq2gLQIhMVrMEhsq7IIMO90Sm5wHOj1flLBLmKjlWGLLro2qJV0vVguWWH6MrA3Rvit7PcNuaVhiZ2tN/H8/vQtfuvJB3L0pnUybbzSVEmn/sQpWDJXgyL4ks/Iw/a6j+wWPfa6wI8KO+tTJDDVWXVuIcajoTwuWWK6wa+rjFwMFpfJlCjugGGGn94dztcVC2MmCO+z7POmAYOz86M6ZbKV7N7FoLbGkoBtaBTzzNLlSWg1VYj1W2O2qeXj9mb/F79dJxRTdeP16qgRcyIu4aXlwSwtI2Mkb6FTTVtWEAABja4LHyU3F9iO/jy8sDFdKaCBbTu/LwXXTcuGVSGG3BCY7fEVyphcKO3nelf2xC22Kqyx3PND5/noBToQC2UrAnQ+Gf08UbN/9CmWJtbNJBRqgDa8OHhdaHdaqJdZ2F0duIyfpBo2wyyw60UtLLLM/AgUIO547Rxl2pIqTxF15pJjCjqv1sqrEmqITPQcpHKolB54k2YTjhosMbRSdGGUKO2G3aokNiwcAYFXuogPyWamMiirs0hcXdIUdADXJzqpUSJNSrrADgoIYQI7CTifoeqyE6mfwjCI9K7CIwq6hK+z0KrGyL7UacwCrsKqrhFKRWCU2m7CzLAujbrD/ui3fVyRWhbcbZqsOLbHBsQhI1rjXCrvG0ig68eC2ycS/dVDBG8+xsHzIg21bWDkc/L6ZOXaklB8hwq6/xzJE7hwgM/yywv910tcr0Pfq4ISd0OOKDBR4H2Tblrpui5BaUzIigH6nxaaw44rBlcMlpfrdObWXnIRJ94EO0EXCTirohlYDhzwb+MBtwPt+Cxx0jHy9R4SdHMzP+MHA6rcPyePwmD02ZQIj5AqusF04pLBbkAy74DiufGAcJ3zhN3hMVhRCdWXwODtezAZJRSTgYqjsKYWdyLHEWrYLR9pQLPiDX9V0djz8u6uEHbP1AKwiaBfIi92sOMbOhzrfXy+gqxV1iw8Hr3y8e91g2HzT4DMlCnXciRl2sp+i636hJ2ytVom13SCDKmmbbqA2A9z90/xrdpAJO6Wwk9cW9WURwq6HRSeKqocjllg5CY5Vdh3NV9j5zZDw5hVnY0UnhlsiegzaA1mVqp6jsuCExRR2ogWFndzXaMVT9lphe6wPyR+L8SwyIF9hp5R8ALPExo95QsuwCz4jn3SjSeloOToxdJ18dV686JDJsEsDZckNs/NcakFhp4hex0IJdZSoSjH1VbJtWKIZIXlnWs2w4wSBXnwHLKtLHvuYIwk7SyPsssaQvJ3U4go7qhIrKsuDFwooVzvBvPadBhX3bQnHt/duTh/r7pYquhVDYSGaFbL6dGbmV10j7PreEhtcO2uWB+OULEusfl20WnSi1vAj9wChxxUZKOhFYtSiVz2/H6UIiH1kLuOiIezqoWqQYFkWVg0XzI/sBvxmGBGy6DLsaAJBCoDlhwCrjgzVIr2yxMqJQU1WRL1zg5ygOSUgZ0XJJ0Wa5cH1ghukg+beJw/oOwgPTV/gFlIJkoReNIupbRRh52C45CiFnUi52fuyE7McF45U2PH9DCwiCrsuWmJjtrHWVQeJmN0dJR66eczdBCdCgWyyhNt65yeiv8mggX5/bolNrBIrr/HqCrnNAl+HMVVVShXORIVdDxY+bv46cOHpwDdPCElQHfW5aH8/cIRdWpXY5aFiqBeWJ1/v2/IUdrzohE6ysUIReao43tZ4AYt5TWFXZvZaY4ntGUjhMMQVdrYbqIeBlhb7iFgZrbhwLaawa0GlW9cssVxhx3OlaCKhiEFYYXvRSMamLzCp2bf4Z2SpPOh9IxphV0SdZwi74lAKu3KooCDCrtZClVjPsaOWUU1hByCs3Aqg1ixK2JHCmCvstMUWhAQu2a1HnOB985bsF50CLo0cS2xZFrJoluS9o+cKOyoYMNiE3baJ8DzuyFDK7Z4J2g+p6oCwKM1khspM/U4DqrALSLXk60nPQfQK9L1Jn6VgFHapmNfyAlupFEsLJ5TLOLvYLLFetA9aPRoc514h7Pj4ZdFZYmlVn1dqBeIh2d2G7NRqCE7I7Rv2QIhgwCXyLELyhArbheOVYs/vNchJCZGO91AeglcNB69FOmt5Uw8Udi6akrBrpkyeSSZssww/fjwDC27d7Ga7TFUkdUhe6GS3bj1dLNCVPVnHOaN9p0Em7HiVWCeF9AKYwk4SdotFYacXUdH7Ez/h+/VCYbfx1uBx91pgOiXHUV+FXqzXSruIWWLH5fPLi1VcbRepVWJzCLuIKk5OJlWhCFbZNU31wa+TTIUdz8MzlthegRQOUYWdwyyxrRB2wb6GSm5I/lmt9SFKYacsscFx+CLMKQNChZ1SSzleahueYKqXCGFn56s8qEpszBJL6jxfBBEQZz4buOpT0TfHLLEp49bGPPCzDwD3XZp6HIOO6QRitJ0qsa5toewH57kGVhSKLfhHCLsC+waQYomVfRcj1ThxCADDdlMeS5uW2Oa8mr/ECbvRcJseihJ4iP0ggyvEspRyu2eC15YPhX3JqOwfslRmah5Kopc+V9jRNbvvaEVleqbZYvVKw06B/FCOmHXdKOxSkV5pvYglNjivVPm4yHv2BpIssUB4nDsm9wLH4S9mwk4OoHfMu0oCDCA6WO/FTULeGOcl2bVjah7n3vgonvaJX2OyKS/OlIkvEVbCdpXCDkBvJptZUCrB4Ed9aLu8oVsWm6AVIOyYJTZQ2AU/L1lfdQgaXDsOvNICEpZ7G1yt2M1KnLEMu+LWnkzoirrFSm7p15muuOPQScisbfsditBi6pFMS+zy4HGhiYdUwq6Iwq4HfQi3gk9uSd5GVyIvdA5gt6Er7Oi6qS5narUeDEZ4Gwby1cNJlli9UER5JJvABqJEnlOK7ksIrUpszr4MOgYN7iusSmy7llgedl2xg7/9FlW6KouMFHZsRZ0TN8oSayUcs07YyUnkUMmJ2PpIBdXMqFQ4laKwU1UOmz5w9aeB7fcB138hSnBS/59ng7zpLOC27wE/eHPqcRTGdf8N/Obzi7eQVQqma6Swi1fjLWKbC5WZNioiOO+zYDE6lqVUdlS5FQBqRUPvFWHHJmoJCjtuzQWAITv4zecUYZdzP23W432w3D9ZU8uykEXdGw236eHYIswfG+wqsZzYzyTsprMUdlmEnWxDRNj1edEJUh+PVV0VGTCRct500pcWSxoFq8ROa9WcLX1uZqCgV1ovt7DwMa0RdovGEsvGFhzKEju9lxV2i84SKydG1z06g9ed+dtQGqkUd6I3En9545lH2Bl+/Gd3AwCmiLBLy7BjE03PYxVaF0xhF/yom8fZ8SZUlsrfj4tqKVTYpVliuUzYc13UhRPZz8CCD1a6WYlTtaecqpqtIkbYjXe2v14hZunJOLf6dxo0JRSHssTaYT5T0mSU2iWRMouNsEsjGyOEnbyltDBxLwQhormHaYSdThoPmq0syxLbS4VZmt0/7XeOFJ3QVHE0YS2N5qupuFLFsqILgI358PO5wm7Q718LCD6Rcu1goO9bdlvxD3xlv2yTWo9n2OXfN2useAAQHaDz1f6w6AS38RLJ6Ecs9qrgRCU6yCZSJSsjjSxCQ6UUhV1TRItGbbs3/JvulzTmSxs3bL0r9fNbxu++Alzz6cU7pkhBaImNK+xqBcLSefZhySfCrhLdSObYcYVdvbDCLskSK/vuWtwSSwpRIuxmBSn9chZ9k8ZYtSkIIRQhPuoFj3WXEXY9LMyjq6MGFVwdlq2wC9rP8qGwLRChn2qJ9f3wNx8iwm4wLLHDZVd9/5kUC6VeJVZZYgvY3YFQ6UywqJhkl5ROg4S6tuhVSinclASlsBtdZJbYerxKLBCQxUC8ffQE6v5tdY0o7roldkaU8diuGfzmge2oN3185/dbw216oXYgkkq4GCpFT8qcoAlMtsIOtqOqxALoTlXPVqBIx6AxbRqfDfNXWiLsZEl44aDs2vAlYeenWWIpw852UfZs1EFkwoBPePgkvpsT+l5l2Okh+/2isMsk7PrE5tsNqOBRJ530EiIcRJOqdqGrXeqrkqmWWE7Y0QSjeDWvQpjbEz1nUwUJuzRbWb+CVBoxS+yyHivs0iyxaYQdU5ikFZ0oj0QraScp8OkaoO04+ccC1iMKu4UoHLVEwFfjPSv4W1h2fntIQI3lFCUr7FqwxMqBuWVZidZImhiSjde33OggmhHPpHqhwT0hYmtNAZGE+lg0kn83ycbEvFo6jUWI2Em7jrt1/+cKVbqu+gSJlthWFHasurDXDM77DMrRjaTCLpphV/C+5icQdrTYMD+p+rqGlsFIFV3niLDLU1vW5f3OsoGhVXL/U5FzMOYGbbLuDIXv6+FiYE0jWwYVE7PFLLHjZIll9vqxChF2KfcqPtYZ3id4HBBL7EjZRUX2j2kEjyJ9pUqz1aITRCQRYWOpWBpjidVB9zO16CULNxUpOqEr7PRiTwsFpbDzovdhul8UrvbdCXy2aG11R23cdYXdjFyluvHhHfjq1Q/hk7+4DzNC3gi7aT8ksAy7Yw9fGXlpjm7ABRR2Jc9FU8iTutcVdmHRCQCYrjXDbANF2I0X2I+UvsNFybEh7GzCjiY2tuOi7IZFKgbeEssHK72wxHY7w47UaCP7B4+LdTU8prDLyGAjEnJ0TfC4WL9TN8DthE7KZJRPzhaNwi447umGhRf/97XYOCnbccwSyzLsrC6R1DpmNdKaT3o59DaX1Qb7EUTmzk8GpCgRd9XlvVWYtZJhJwQrUuEFSjog6Gt9P5phx0mTJLKnqfWpyhLLCDtvSJLhXYogMEgFJ9lKpLCDGxAGQFtFJ0qujbLM7vItN6q6zIlRURlgdjggDqvccYVd8HeVlHx8cQGItJnpBPUWoNlaU0CWoIo2UVDvbTSByU3hCzwagu6fNOZLa8ecsOtkYaQxF1Wo9hGmVJXY8DwXUUASwuy4UGE3rSvsEgi7IvsGwBYsEqrECl8tZoaW2KDNVqV9dcbXXBp5CjtvKPgHAPXZCLE44kqFnV0KKyP3MB+3rlWdHFRwddx4BmEXLgDEM+xSFXb8Hs4tsXu7IGIXMcUqO1dl/ziTW3SCLLH5cQQcpHTeXxa4sIU2fjFQaGgFPlqzxFLRiYBrqTX9wr+Rws6Huz5OT7PE7lXCLinHtEN0nbCblSTZjY/sxKV3bgYATBNx1guFHasS+4ZnHqQ6AgCYkxbT1JsTV5i5NhqkMNvrGXbRohMAsHmPHLzpgd1ZYBl2JdcOBr9gSkIdTEFTdu3w8wddYcdVNz2xxPYow27lEcHjYlWjtaKwI1vc8kOCxz6X+2ciUiU2RWHHzx1N2BacsAuO+48bJrF2xzTu3iJ/z0xLbOtZVoUwo6lK0tpLTGE3YIQdt8TOTwBgSuyeVomlvNMChB0nbbjCDgj6hKQMOyD5vstXKYGQ/JufDMcTtP+sCswGXQFX2JVIFcctsS1c90RWlJgl1rd0Ii17f3oGGBCSZbTaL4RQE8PlVZnryyt2A1HCjvLRNFury22tKVDEoKawo4mnNb0jes1QdpwQ4eKhssSmjMMEm0gxe2XLYMUP+o2wSyJVnRYm9Q1GlHnN0B0UgSsJOyvsl4oXnUhS2A2DClnQuVeTZXnsVCBimgi7PHs4kbxelZFxs5HjHLKDc9WwvN5mzNIhLcGiE1kVT5Paam6GHf99SDnp1/t6PBMq7BylQJ5LtcRGSV+14NFilVgikkhZbTLs4tDvoXT/bMkSOxL2nS0VnvjDOcD/PhP4+QfC52ozwDmvBC79p+L70aCqxGqEHV2De8cS232SuGs9qiCFnbzpPbB1Cg9tm5LPyRtJDy2x8/Bw+OphfPO0Z+ETJz4ZH3r5E0NLbI7CzrIdeI6F+kIpzEhhB0+tvGyiHDu1alago1YKOxmWLBuKSLvZy8GwZXsou0vIEssntM35llQBmUjLsOuUsCNyYkyq0YqQtwuBmMIuxY7o+4ywOzh4XKwkZDeQWCVWaxM8XJ/sSYuEsJttBDfykNDPssT2SGGnZx6mTVRbIY37EaTSaNbCyb5bDcg6qrgqmt3r0whKMVeEsNOqY3nVUIE1Pxmt7MrDeJPuu02m1AOiCjuu1Ms7JoOugCsfyBLro3VLbNMXilgJMuyC9zW5wg7IXTzVq2wCXCEgK26yVf8VFTt+zICmsNNsrQ9fDfzP0/D8+o3q2NNAk5WqprAjMsme3hx9w/T24LFZC4m4vAy7yAd2YJOjPtQbDrNH+wRq8s9IVa8AoUpQuU22pSyxU0JX2AX/ryK8Dxe2xCapKywrVnii7kcny2X5WYqwy1uEoDGWW1XHi/qcIuwc20KVE3YFXR+1ho8P/uCP+N+rHszcLu29wOBbYnV13HSKaodIjdEIYZdjiaX2YzlykU4SvX1ceCIsyOMpUiitSAFfzAGKLZYkfdYqWeiDCiR1K/x/kKBs+VoObCGFnVzcWjUS9nNpuYSJuPSfg8c7fhiKZx79LfDY74DffwvY8Ifi+2IgO69eJZauO70oSU+wmBV29blg8DyNCh6/b3S1jmyyPSEayBIrPAyVHDz/8avx1ucdjuVDXlhpKVVhF6oGPMcOLaF7ecAvmEqQzt2mcXnMUpZfKGtNU9gJi4pOpHwfSSTYbqAwbFJz6PZkb7FBP5fdIpLTMuw6JYCJ3BqVlthuqgK7iaKB/7UpKGUQkZDzi5SE7Ab8JMJOI8Xp3DlltbK/4Kupsh+katOhZT6rSiz1oV3uQ3RL7HwKYdeKLbsfQRM+ANjzWPBIVYVdNjDoNtkbs8Rm/M56dSxeLGKKWZlLusIuifwjS6z83CRLLO3bZNj1FEKIMO/GseDZLMOuRSs8txZ6ro2SRQo7J5/EjewnOIbDGmuB77wKuOpTsQkHz0laXnHY5yTbsWdqWj7a908C9jyGk+d+EDt2HbMphB1NOB09+oEIO76woDJMU747v7Y7ybXq0/w6ILnoRCsqnCZrx24jOPdTohxmRwOJRSeKK+wSqsQCYf8tydKwynHQPkoieN9Uk1waRS2xFTZumI2o3Eqy0ErdKhWupP2T2zbgkj9twheueCBzOx2+H/YRntOd3KbFCp2YSCMqJhPyFkOFXYFiS7YdKuv72IkSXrNOaIlNy7DTLLHUloraLakfXj7kwbIARxF2xhKrgxfgAZIjJdLAcwmJXC2e89mMZrttui145EWVNvy+2L40hBl2msKutBcVdro7pAvoHmE3S6t1Vbzg8fuo5w9cXg2zIXqgsONkF795L6sywi5V6UMKOw+ubS+Ywq5ZDzPsHr9vcEMPFXbhTTgXsoHUhRtcfEphl22JteyA4FNVYgd5wtNsxG07rahw6nPpuTGtBrMXhU7Y+fXO2uj8VLTiZrdQtEosTTJsD6iuzN52EEC/f5YllgZobjkkXhZa6SqPm6pNp0YGcCu41SPCTi+8kkbY6UTVoBWdsJ2QoBpfHzySIsdhlq5uFyxpJcOOP6dnzxFhZ9lR5V3avnSFHU14G7Ph5EW3xO7tSIslAl5sIVDYsf6hRSt8hLBzLJQlYRdX2GWPRWiy8aLpy4OV+eu/gGWOdF3IQTtNCj3HwgjxFbCDyUIC0agUdmUncq+vioD8zyo6oQi7UnRoTZZHq6ZNuCnDju6dlhMo3oD0/p8v5HSksNMI7z5CUtEJVdgjR4UTIZ5tWxF206IcJQQow85qJ8MuwRILRAtPsGOl9lESQb892dBzkNOIHdnPu+Wowo7lUpWlpbeB4pbYmx8JFe2tWNw4WTrIGXZCiJg6bHZuFvjBW4Abz4w8PyVJuZFKKwo7rf3QPb5PC0/Um74iu0fKYYHItLZV11SaToH8UI55liVacR24yhJrCDsdeo4mXbdzOYsT842meu9w2VXvK1xJe2Jj9P6+Q6p5t9wZPrdnQ7F9JRwbkJBhV9mbGXZa/nIX0LUetTkf3PTcyghOe86hWD1SxqrhEt75gsPDbIgeEHaK7ILXBmEnLaGOg5JrtZ5h1yVVkC9VIA3bw+H7BIO1Dbs1wq6Qwi60xJZcZolNUdhZ8vvbTrB9cykUneATeBqsFyWLZncD//Nk4IK/Tn5dV4PkDbaKQhF2B4TPdXItfecVwP/+ObDtvs6OS0dRhR19n/JoVDEzqIhYYlMsLnTu3PJeCYYuBE1hpwj9IlViu51hRwPV4X3l/9MIuwFX2AHhavu4VNhVlgePfGDQ6DLZq+dxZBF2SeXsaaI6Kav7lkYlYWJlTyJjGXYsD48swaQQ6tYCiUEidJLNk4vjQYZda+p8rlTybBslbom1HSgLWM5YhOw8o344kd3HCcZlNBkkwq7qOaAaBT6NdRLa8QzPsJsPCTZbTvoyFXa1lKITkkyyFcks2yxFQZBqPlLtuIDCrhPXSh8r7KZZgD2BLF1ZhKr+uudYsGWG3Swq0SqU8j5MuXJAOwo7jbCLWWK1cH0/eN9kU2ufaS4Z6ucjyvzZSNYkHX+NW2JzriuuksmqgKqDn7+BtcRuuRONG7+u1JhU8dVdey1w3y+AX300cn6nEhV2wd8TeZZY+r0qfaKwm96R2La4XXi47KqMz7QqsXWtEEKRCt0cc6zoQMWzmSXWZNjp0As3lQsSb9QHA8BwyVGEXWGF3e510f/vkGreCGG3vti+NNBinb5osCBFJ7pow+5ehp2cGLmlKg5bPYzrPvwiXPOhF+GIfUbyibMOUJ8P9jkPL2JDWFb1wtLoKfYgS1PYNdImpEm45ZvAfxwI3HVR+wcP+rigg7PdIIcPAB7eLgdTdBMuQipxSyzLsEu9OZMl1vEW1BK8V8HbQnVF8FjUYnrfpUGW1oO/Tq7W1IoKpRUQOTG0snWSUcfWu2WHKID1N3V2XDqIHCGFQKrCTn6fytjSIOzkJLYubOyek+0mVnRCtkuHZZF1m3RpFbLdEpGfmnEpt9s4UcdFf9ocea5roDajLNRLVGEHhP3W7rXy/8uDR8sK286CKuwSrAB0nRNhx0mCLIJCjxlwSuHfpNaLFZ0Y4AWnBYQ+GfeoUATslpW1alXftmDblrLEqkXDgotdpIga9cOJ7EoruJfoltihkqsKZaj4j4R2PDUfbs8nyMNiKvKZOnxfqM/ULbFKKVIbD55YfmjwSPunghPeUD6pwhdyOlFhU4YdFXLpI3B7HSFU2GVPGLkCz3VsOHKcMo1ydLKZWCW2YAVEvd8iKMKOik5E1S2uH/Tbe+p6P9uawk5l9DkWPNBCfqnwdcUn47tnircxfu5dewAtsb4PfP358H79EbzY/hMAYBVVyKyx87T5dvUnnctRprAba8USC0SLTS1W7HgI+PyRwA9Pjb1E12vJteE5dm6GXS2t6EQbCruq5zDCzijsdMQUdtzaess3ge++JpEoJhK24tlwHTt8XwbRJ4TARnIP0oIrYccDwTyQlHZA2wo7vcowgRZ4eP/WMyxmSyzdOJxScJMbKrkYq3hYNVzCPLKJs07QqAWDF98uKdksEBB2Nfrc1GpbQYOzXQcuLzqRp4gSAvilDEvU5M/tgBRwrlvC42SG3cPbp+D7ginsihedaEiFncghjIiwtGMZfgOsUCDS2CkDpaHoc3ngA2U9BB+I27e6VbWQbtLlZYzgapOw46sa3b4eiRwZIptrynklG095lBVVGWRLbPD7n/f7jXjZV4Lg8thkrMEG3qra5yJR2AmyxKb0j4yw++NGudDQ7T6EroE8wo7aXHlZ9P+DBLq+yNZOdhmAtZ0uk71KPUx9W4EMO76ySBPVKVLYMcIuSxmnE4U8D4+r9SL76cGCk+8DN58dmYilYs8G4KJ3Axtv7f5xLCDq2mTckUUnIpbYFjPsaEBd4vZaoLB1j8izsWZYRXqlHfRB80phFxzTUMlBSebu+UQwJrRjpbArO5GJyqg/iRLqqZbLOVZVT68SSxNOh/qxFYfJNxFhJ/up0lD+d+djwU7u4XqV5T7CtJ4ziOIqnIYfbcd2gwrmVaJkX1KGXaeWWFqokO2goSmJHCLsGjpxnaew8xIz7FzbRokIO8sNjyfnuuKKqPGZ9hR2ziASdpv/qP7c1xpHybFVGxSzrJL9zocABCR+Ut4ikXfzDT+Z4Ghqk/1+UNj94dvB4wOXx17SC2/kZtg1QoUofyyaYTenig4E5KDKsOsieTIoaDByHwjPda3pBzzHuuuB3/1v7H26ctRzg/dnFav46tUP4Xn/eTV+cMtjYczNsIxQ2/EAsO1eqHxzIMx4bRHhgmCU4qqqCvJ7gePQr+EuoGuEndUgwi5aaWms4oXVWnswAW3WyEoWvTGOVTylCGmmkF2WqpIaKNIaRS2hfLJIVS7zkDGw8uXnuZ6HQ1cOoeTamKv7uH/rJOoOrZoVIDTkTZ2qxNpONgFnRRR2lrK+LQmFnVsJrYdF1Sg0QQQC/70OnuUFdFFhl0RwtalI4203iXTsBHSdkeInL8OuPBZOvgdZYSevs+1TjbCPgYhel80Ewq7bKqlWoTLspEQ+rX8kJZ5wArUNe65raFVhp9rgABJ2w6uDRyLsSHEHsAlZtxV2RMIV6Nv0aAAgJOwmNsn/JxB2WVVi+aCH1AaTcl9EOKjJbQ8GY3f+CLjsQ8A3Xpi/7ZWfCKqeffOE7h/HAkIF9dsWLCtUxQUVV2W7KGiF1xUUKg/PIiVlsXsnkTMjzXAiuwKSsKMMO5Ur5yiFneqnEqpaR+yW2gR5DDOpRQ24vauiVadTCqoaEXZSYVefARo13PuYHFt4Q+waLpBh14maVCniq+3vY4EwnUCCFM254pN+x7ZgybHHtG6JlWOtilVTREPnlljZd0krc92PTiydZvCb7KkXJK6bTJnPFHa88ENJSEssvMIq5Kk2CTu9jxg4MFVQCXVUPFuR8xHCjtoUq0bJyWX+d6LKTm8/FHsx/hhw3l8BN53VwZdIQKMG3H9ZGLPRDjLIRP16zc2w0xZ06NouWiWWMswqnoOytwQz7IQAfvdV4JHf5G6q+go7mmEX6esSMs/137SIwo6K2HzkojvDQnKHHBc8jq8H1t8S/L1M8iptEtT6Qgih4oWLOoXzSNtF0sJ1h+gaYWfLG4dbit78h8uOUtj5PZg8+XKCJuxy5PlqyWGEXcrkhRFWrmMXz7Dj5EKRAdOv/w34z0Mle5x0GKSwC47j6IOWAwBe+eXr8ZXfSEloEbJTZU5FFXZpRScsViXWc1iG3SCHdpMKzKsw62HByS2FvAPhxJPD11ZxupFhJ4SW+SYJu3YVdr0k7GjwSARCGmFXZ3k96vsMMGHnhzYs1ccA0b4jUWHXBuly49eA6z7f5oFqYP0JwC2xOmHXlNv1UKWr5zjmZdhRG1xolWIvMLQqeCTSfmTf8DVF9nZbYadZSopk2PGBCv0e1IdyhV1WP+kn7WtZdF8qw66H969Hf1t824nN4d9J0Ql9Chrg0uTJtcJ+rdX8wLjCLvh/oy2FncBwc1w9t8wK+gaaDIaWWAeeVAU2CmTYDZUcQKvqOmzNpk4ayd5Vdm3YmrpIZTHV5QRk2UHqtY1btuB/fvmn4Pu41WxVlV40q5PrPI1U6gMo1VKJKezsYiqcCGFnWWrsMSMq0UmcFyrsaFLaetGJlCqxqugEm1gKoeZR4zVdAZqmsKNxQylczOUKO8dWltgavMJjUk40jbdgia1rap2BAxvTjmEGQ6WwgAI4YSe3o3bqOVYkAN91bPW+xMIT+rU5ul/wePM3gkieyz8SzfpqE//0o9tx2jm3oP7LfwEuOBk4703t74yTK5pIZkrLnMyzxOoZdtSeilSABpjCznMw5ArYst9fMoTdg1cAv/4YcO5rczfVr1ki7Pwa42soa5VhWt5XqQ8uyUWqwn0kzT9XP0GODwVw98XBc4c9P3icn0wv8piBWjOq0CTwbNmeq+zSKoV3gO4Rdn7UEksYLruYlxl2lDfXTQgpCRfaSSm7Nmo5hF1YdCGoqhoqSHLUIZxcSJs4cvzuK8FE8ndfTX5d3owdN/gOz3/8avXS2j2ysRYhO1nmVMmxYeUovGyyBDtukOG3lDLs2iFG+G+dJNVVk8suZtjVZwEh20B5JFSTLEaFHQ1SaRU57bxSW/aqS8oS2wSrRA1EB808w67gZDWG+hzwq38Frv50NAeiXbDjBvItsU048CksvutFJ2S7JXJKNJPPD51HsokOJGG3Ovr/kf3Dv2mA3ytLrG73L5phR4Tdrkei/+f7TFTYJaj11L5IYbgyup9e3L/4PT+PhCP1FBDm7A0Amn50EOzKSVCQYdda0Ym6tDyVHJ38az3Drow6XBH+5mNCU9hR0QmWYefHMuzC457mZJC2wj+CuVTLZVrQNQA4kkzySGE3tErdJ6+/8yFUEfRbDYcRdklknN6fdaKk7VPCrukLNSFPyrDLy5mjdmxbCIhVufg5o2fYSYtpFTX1OR0r7LQqsWF+lBUZL+2syTaUZ4lVxCArVlWfC7PxbAuuVNjNCy9fvSnBM57SSJUk6GqdgQNbKB+zplEtOYp4c+YSFHbMNqgrDom8SrSF6oTv2IFyv6zITIoApCgm5+r4yW0bcN0D2zFx3zXBk9vvbT/Ch88tSD0lEZ6H4FyRKjHNEkukD5Gc1J6EKGaL5VVChzk1sFSKTmwvXlBQz9FUi2hz7DdMEIjMqvtqcE4TlXlZIEvs0KqAtAOADVJhR4Sd8NsqrKTbfAmcNKd7SM+gx7l0AV3rVR05cChVooRd2bWD6kQAGr0g7GTHZmmEnWVZEHIA36wn35wsRlhFM9zyFHasAeWFgPLOj3IIdKgsueB43/mCw3HqcYcAQGsFOyjDTgQKOyvHVmIJatReUCWXim4McoZdxBLbovWQk2RJv0dsUttCEZPUz2Sf4w2FBR3aVaTxtju9o/3jSkJhwk52/t4Qs8QOMGEnySufK9CAdIUdDapFs7XVpWkW4koVlzqBrrATKf0JqyYb9iE9ssQOMzVZ0jVI55GUDINYgIAUdoRRRtj1yk6th6hnKT+aWj8IhBZllXPJvkNWHl6Swo7sQQTK9Otl0Qne1vL6Xr74MEDKYZqMxxV2TtuWWI9CxaVlqSHkAFuRuPmW2BFE+wEiv8KiE1Ix5zmKZGxkFJ0g5cBQ2YktyA5jNrWogT7J5KAKfF5djhcry1U7np/ciSErOOa6XcnOGdPvqZ20dXqv21+E3QxTfw1HMuykbS7nnqm3YxoTzSBFYWfVMCKLBBRX2OVViZ2KHKtr25ECSRMNN2hnRS2xbjm0Njdmw8qPjg1PBMcStcRmX1fcEpuVSRU7HPm5zhJQ2I1iRhY1CM6pwypKU79P6rmRSnzSXlUqsyIKuwPi2yS5fFrA5j0h+e832DG0u8iUkfGt5/jlWWJ1hRRvT3nXd7DfYJuK52CIn/ou2hMXNTghnyNISasSW6mx3zBh4XtOFfYIti/z7LsiIFK3uhJY/fjoawcdE7b9Nmyx1E+XNIWdZYVK154r7HTHXRfQPcJOruJ45ShhZ1kWhLQeNmq9IOxkpVcn3iHS5/ppVWLl4NLSqqT6jZxBEB+Qz+UQduOPhn9zGxAHEXZSYTdUcvHp1z8N/9+rn4TZFgg7vxkqYjxWJdZKIeBsZYn1pCVWNodBnOQSeKllpUYpOLnlpFKSIkxNajVbT0cKO/k5TjnYrypC0ua1xCcg3Va10bkli1qews6tsMIf0wNlH4tAWUadKGGXmGFXiaqJWrH3TTHV57Z72jhQDZrCLuwfkgm7Jhxmq++2wk4SzRRQCySr5+h8kXKz29bQxYBlB0b/P7o3FXa6lTCDZEtSxRE4YVekSqyTQP6p/2uEHURbNopM8Pt8njI5Yg0anIUInk8FAB6RbBFLbHtFJ1xewAJgGXbZ/Z/vCwxZ0X6AigSERSdCS6yqRiv0DDtWdIKHaWtVpoesdIVdqBqMD6uV3ahBFdKXhSrguQlU5THX7Uo28az3eZ0UnehThR0pOywrSo6SijEv56oZI+ykGkqUo++VCrsyahiWBENh8irXEktFJ8KsObIRNoWFBpyAOM67riJFJ3iV2HC/pLCbE24hhV29GS2E0MrENi3sfWDAFmDGrBkMMYWd3Ygv1CRZtwn0vtlaQptSjgv5e40dGN9mcnP8uRawaTzs24brTE3VLhHI73UzuyIvTc2xPhWMrExT2DWi9weu2CySYzfHFHZDLtt+qVhi+fxQ+y1imzaj/SEp5cp1bvGOzzcVYecWU9jFfmsaJ1WWAfs9NXy+NAqsPJLdH9sh7KKqQQ6yxc43ek3YLVaFne+rm0KpPBR/XRJnqkBEF0H5bLrCLvhcys5LHtQowspxgyqxUh3SzJvstGKJ5dbJlG25NZfjoBVDYcGOAgN/Kl4RFJ2wwnMikm/2RFg6jgfXtsOMqkG2xPKBFA1wig56I8qJhN9DZ9S7YoklNVo1+tiu1Y+ID6BY5eFWoAg7OShNO0ZliR0KiRW/MZjkCqARX1ZIfEUssfJcOV50FbAV8pyvjOol09tBWtGJmMIuzLALv1uPqsRWxtjEJIG0JjKRiOBBXHxYeUT0/3ww343czCSkZtgl2XnYogghporjCrsMFYkeMwAkkH+SsIsQ3V2+h0UmI60QdoNT9CSeYcctsTlE/Z4NwC8/rMKraw2dsAv7EACFYwEChZ1O2EUVdjPMuuPZGjGYpbArubGxwQjmUieMtWbwPi9BYUcThzIp7KrL1YTEnt8TqgItprBLuoZjlthOFHZECvSX6oQsmkOeE7EZEpGcp8BpaoUeVIYdKlF1CMuwGyq1mmGXkl9EYyMqOsEnlpIcDlw1FvbM1POLr0SKTjCFHdtv1BKbf3/gFWKB1hR2EQJyEMHuA8swjarnKEugxVXtlGEniarRBIVdRVVKzciBpd9rnyfGt+lQYbdFKuyGMIchwea0Exva2yG/12lz3WmtomjxDDt5f+AKuwKE3TxX2HEX7FIh7LjbZjabsONqXP5o88WqLMJO/pZ0zacRdno7F7wy+lGvDl844vig3yPCLs/FmIDwO8X7IVIELl1LLOuoytU4YSfkBKvZi8Gr7NjshEFHqLBLJgI4YVdiRSfyCbsWLLH8O6cwxWTNdTVrwkErqqpgRxEyoymVgU1ZdMIqqrDzXJRcTiQMMGGn1B+l0ApSlCiq5yjs9MllNybPvEAD0FlBAiDaXhtdvh5pkFEqqLDzqiH5krV9v0NEc5OaScS4sieVo4P8VtoOv0l3w4qnWWJTi9IwhZ2acHczw04vvKKI9gRCmK5laoODSAKvODz823KiirN28w/zoOfSFSk6kZRhR4go7LL2RRl2GeRfTGGH7hOW/D6eMwCO3OcHyBKrK+xcrlajcy+ayUrp808GbvkG8KPTAcQH1B4VnSDlW8F7py8EhjTCriyIsJNFJ4jgKTnh52RYYmliMVx2YhOVYWsOzRQleK2RHHQNkN1IoNyQY8fKcnXdurU9SiU4Z7H+PzHDTrfEdlJ0go2F+ggzWnYSgc573oS+wTLsAIQKO1SUsgeAUthVUFOTvMLCXT/l3OpFJ5QlNlTY1axgjLdjej6/P+dFJ9hCFr++XD9oI4HCLv/+oE9k51uY2FJRgL4tOrHhVuA7rwIuek/y66w/GLLmUfFspfK0+TmVc8RJjajiUAq7JNKKqV+FEPj3Kx7DulUvCJ475LnBY4eRNjumgrazytLmpe1mW3MBgBbJMaX61IIKO1VFXN5rWBGfIoUnSGFXcW1UnGB7AQsYVOWnDq6qK6iwUypwIuya7PdMmO/ONUJSFGAKu5RFjTmNyBM0NvKGgeWHAK/+InDIc4Dn/2PwPEUrdaCwS7oX0/H23hKrOe66gO60XjZxqlTihJ0lV6pELyyxKv8t3iFa8mYp8iyxtgvXDotO5Fpi+SC8MZetJuGTyjTCTr7fcaPfYdVIKcidQPp34CDCrgEHnm2rc2IlDXqFgIPgc92lVHSC20BUldiCSrM8S2xahl0naiNObgFqENm2coOTzb1W2KXlaHHVIBGQwOASdn5UPaKuMz7AU+2yHCUeWsk/5AO4vKBW3wfu/ml2pTEi4qTyOLV/kP+vwwnD3LvZh9RnQwKwPJptC18KllivEmb5PVmrAtYzhZ22WpiVYecnkGx6Bs8QLzpRoIAFV+uN7Kfta2V8m7T2V5tpz3rPFzfy+qkBVdgR0eEqVRy3xLJBqUgYsG+9M/JYb0bJP0faa8nlUDRrq9EUGNYssSVliSWFXbCPaskNj1kkE3bzjaY6tiSF3TDmVE6XjrTcHCA4ZyOYhS3HXFxh59YnlSV2FuVsUsUUnUgl7FyVYScgMq5xX7B2LITKJp4R5WSFnVVXk7yiVSpTLbFa0YkGn1jK37ZhB2OinVM11j7TMuzYuIHdF7k11RVE2DmFFnR0q9hcC9axmHqx31CfDiqCb/5T8uts7ldGHSWXEXY+uxblXEEpyypxQUkmacUUmg9sncK3b1iLv9z4Fkz/5bnACySh0UYYPwcpiXWFcm7MUxr4nEjrN6djGXbBY5rCTldgW5allN2Fik6wKrEVRyrBre4RJ3sD4zO14opeHfw+kaewowIN8pol4s0prLCj92UX5pnXf2uaT5Mb5ph3AG+/HDjoz+Xz7ee1q8q3doLCziXCrtcKO82V0gV0ibALLs6msFAul2Mv20TY9WJCrvLf4oMOS2bCiZRJGynMLNeFY1uhkiRXYaeRNVmTwhYUdlQllrC8WlKVbosMzCjDzrcc2HZoibWS1C5sUO04Ljx3qRB2LF+pVbVaRGGXZMdLybDrRO1S0yyxnSrsOEnXK4VdK5ZYy2qdOO03yOvJj1Vb5Rl2zEJjWWzC2gLhxNvnfM5g7tr/AC48Hfjx23OPuwEblpVy3Gy7pnDSt+kEpK6z7KDNZCrsyBIrb/bCH8wiOu++Fnje3wMv+mj0+YJER8uIEXZZltgEko1XTgWA5ez/mVViEya+yw8J/y6Nhuq9PKJ7+/3A5w4DLv9I/LU8RPrNnH6K3xsGOMOOSLamYFVigezrrRTcG/TKdK6ufCtcJdbHsDbhLPlSrdaIZ9jFFXbR/mqGVcccLjmxe+QwZpE2h1KTzERLrIUxUB6tVENJws6rTypL7IzIqRKuP9eRJbY/Cbs5ZYmNToT45CwtZxAI255tWcG1LMfCM6gkZthVUFPkShGyINiwWNGJGq9mKPuVpiTsdkzNh+rjtP6cPsctR+6LDWUptOD4lGFXKnRd6RPulhR2GRPlvkDegjjrzyuooeTYKEsCwPFrse3C7DaNLPr1/4dPbXo3RjGTTFqxyf7G8WBfuzCGP1afxwq1dUbYUVbnsFa0px1FE4DoOYsRdsH3GSWFXSnoI1MJuwSFFLWpGIm1+Q7goncDk2EkDJHOFc9GiWIQrP6xw+6Ymscxn7kSbzzrd+3tgJ//nEVDVdmZFHZE2OkKO20RZFazxJZyik7ErPVUxNGLi7yCHXZO2CUr7PZW0YmE4msdoqsKu3mU1MngsLImWJ2imaGwk+SGlUJ2KUuo7cGyLPjygs5X2GkdZdb34q/NJ3eEtiLsojf3imdD2ERm5E/cKcNOkBVWKeySbgjhAMByPXiMsBxswo4NpFRFxW5ZYnuZYUeW2A6vJf6+bivsfJ2wy7PEyu/SapZgv0H2MxR0nphhp9uTsnKM0tBKJct7fho8ZlWTVRl2DlYMldKL0jBirycKO26HtaxshZ2yxA7Hn8va//j6zo9zb2LZgcBLPwns84To83srw87KUtglkGz89wCAFYeFf2cdc1IOCCfsVh4WtAlA2l2s9OO64UvBwtfNX4+/loeMyUgMkcHy4BB28Qw7Ir+s6O+Tde2PBEVjIlZAAK5UnsWrxOYQdiKusPOEHI/WqUpsnLBrpijspqUar+zaAZmo3SOHrSIKuzhZ4dk2llvMDmtZytpdaU6gahFhV8ouDKBfIx0VnehvS2wlprArFkwfIZ7ZfXIWZa1KLCPs5GcVyc8KPiSPsCOFHVVotFUf47uksGOW2CJFJ2g8VZ9jxJkNRyq/Zn0n224toU+sWwln14n4voM6hykkR5LCTs55I4SdnCOSii1WdOJ3/4sDa4/gTc41qj1HwO6hj+4M7yH3bZkIi7rlLcrmgD53ROs/2yLshMhUoetVYisFLbGccEm1vH/jBcAdPwSu/ET4FUhh5zooOxRJ0z8Kuxse3IF6U+D2DXvaU9nx859zj9ALNBDx5nHCDiK2nzAnMKrMS1PYRQkyAUtl2A0nbq+IvCIuhfkp4A/fUS6jRhFL7JItOiF/yHl4arUhAtkJphFnufve9Kd0G4ufrE4DAMcjsit50Ef2BCL7Goqwy5ng6Q0oa/sCA31SwLle9DtYloVKNRg0WM35XCuPoO8pG4iyxCYVnWADANtxgyqxchDrd1udsZjAB6mtKLsateigKbHohJZhl2dnKALdEut1kbBrzHa3MmtS0Ymk/TeYwg5gxOmAEnZpxRv4ZFSvCqYmrC1ci5GiKDmEHf9d0j6DEXHLqh7qIoWAZsRemGHXRbk55S5SpkUWaU3XWiuE3f+9Efjy04H7L+vsOBcDepVh10zr2zJy5/SBCtlih1ZHybys6IAkhR0vsjF2UHR7J2OCm6DCL4zIZCSj7/X9aH8/QJZYvbqmA1bAIWKJ1X5H3r9YUeKDJgmhJZYUdsUWu5q+CBV2clHLa6YUnfAcOLJQRj2FsKNtaWKpfmtJrpVRT1Vv1TJW9R3bwjJL9smkCJUKu0pjCkNSYTclyjmZjrrCrgPLv37P6ROQxXnI0wi7iMIu/f5DGYSObSliZc4qw4cd/W2VJbaGipyMFlfY5VSJrU0Bvq8+z7FDhR2pvDaOzxWwxLKiE6QOa3BLLODwKrEFxhU6YdeKdSwr7L0vQGPSPHcIgnbBLbEuJ+zknFAP5gcQOff7W7uTlT5ssr9+V/iZe2brTGHXWT7qjPxcXaHcFmGXY9UnpeGwVBqSJXa+4SdeU0nxAqHlnbVHfg5YgUeusKvIRZp+ssQOscWI9bvaWPTj5z/nHkELUJ5WJdbxtfmYpjaPVYnNKTrB+5UKarDk+EHNbXUowq5AO//lPwO/+HvgZx+AECKmGuQIM+x6bInVHXddQJcVdp5abYhATrDsdibkP3s/cPbxwK3fTXzZSlGnBZ8riQA/ucGGRSdkdl1RhZ3+PbK+VwHCjo7DTSAdq1XWmHMmYUS0CdkxEYlpJ1li2WCQLLH1opbgfgafeLrF1YuxTiMxP0uTwKqBdycZdppsuJsKO6C7qjbdEsuf44jl8g26JTYktACgJhIICn2A77RB9kYUdjmrr5xQSyucI8LjHqt66UVpWHGKnivsgByFXT26DX8ucd9TwPqbgvNx9ac7P9aFRkGio2WkWmILKuwA4JQfAAf+OfAizZJaqEos25fjAif8G7Dvk4Fnv1vbV8Z147I20UpOj9+MDnqz+kx9LDBARSfCQbBW2VXoCjudsGPnRP4uDW2SQIRdmC1XsEpskxF2w6uDfZIlVk4oZlnV17iSL9qOaVsiaNQ9SRaIKKMGP4W0IZKklGCJ9RwLy5BM2FX9KWWJnUMl59rSz20nltiU63SRY44VEeHwCivsmFJUXp/zVtA3RNQszBJbbjnDLqFSNsDGRkF2nlL7MUusJ3PAH9o2Gf42wk+ueMGLTjCFHV1fFTtsLzO+V0i5H7PEtqGwc/rWEkvnMIUkYfeBMuooOU5oiRXxTGJqq5G8RVbUYZU1kaywY/OU8dnwMyc4YVefbqEKShxkiR3qhsIuJmLRLLG1aPGNKiMwkwjLsOhE3BIbIdUnt4R/y2ur6QvVF5ddByVbqqr7SGE3xSo1P7K9jTFERGGXPa/SF8/onNN9VKGeTNhR26b3pSkCOWFH97vgg9IssfL5JHGMjtsvCB7vv1T99kCy0nfvWWIXeYZdTbhqtSHyIR4Rdm1MyO/4YfB47X8mvpxWsAEAXI8sscmEjEOEnXyvIuzyVi31QVIW4cNZ6ZwsPV1hBwBDvOpuDuFJBTiEHCQoS2wiYRc+57hB0Y1m0aIb/YwkS2wRoki/ISWx/kpZogdnd0FhV9LUaO0Sbfr7upljp+yIjLBLOrfK5tul77TYoYgvKelXhF1S0QldYdcKYdeCwo4TenPjydswIm5Z1UM9qbot+38TtvpuohcZdjTZycywo0koz4LK6J+33RP+Pbm5u4rThUDPqsRSIQm96ETBDDsAWHM08K6rgWPfFX2+kCVWG2y/8J+Bv70ROPKE6PPKQpZwXLy9TGyMv56G2GQkKwJD68MGSGGnT8ZJYdcQdmiRBuLnnp8TeY9s6Go9S1fYFcywEwJlS17fsvgIZe8ohV1dTkxLjrLxhsUtotbuea3yna6wq1gZCjstKJ3Ddey4wk6SgMP+FKryO8yKUnY+pH4+lnDRCd0SyzmiLGKN5pOBJTa4Z85bwT0lQvSRwq7VDDshWH+pnVu3El4r85PRIg3Sfl2pBkrR36/bjX/9Kbs/JSouWdGJBIVd1Qrby5xwWCZeliW2qf2/FYWdJPX7tegELfT5jWQVIvsN9KITnmDnVJ5fPecLADAVZq2txGRuht3EbPiZk3ON0BILdJRjpyyxMsPOJ8dR2gJuFnSCM8cSy3kC/fsLIViVz/CipqIIkWuUj12lwo6334pno6wy7PqHsJuYDa/b3TNtCGhascRqlZ3p/pVP2IWFPYCQsEvrLzhBRopyuJV0BZpS2LWgMHRKEQVmksIurzhG17BoLbFygF6HG+2Y6EPkhNzuxBqYMki25KpGkiXWyvlcW67q2nJwSISdyCOs9AsgU2HHLYgJ2/m+Oo4khV2EsMtRglGGnSUbSLbCLnzOdjx4Tlh0YqAtsUr9kZMVo0OfeCVaYnUVSk7+SBHwiqpA51Vi9euomzl2SflhSW0+prDrYcblYoC81nyZr5WYFalPntrJIuNtMmsgJwQwuzv8f9qKKrPyjlXcQgo72kZ0sw9pRWHH1V1Frm+e4TezM7pi24/Ya1ViiyjsCg5Uithri6qAaPCXRFjyamlM5ZCLVlTJelsboAy7ppY7F6riLJkfKKGPNxJW+/WMGVo8jVlV8zLsfIEy5DZVSdj5RNhFi05USw5cfsz8c2RfR+9Ryg66P3KFXQqpn1kl1rawHFORfZHCbkSEltig6EQrltguFJ3gldr7ALOq6ER0rmFZlpqgZSnsGhGFXfCbzNvVyGsAokUnWsmw47+J3m9ZViSDLGIzl4unw0PDWD0S3LsuuTO0+SX26XzcwBV2pDBiCrvZBq8Sm35/jivs2ig60beWWKbCTlrM5oSdVUfJCck4N0FhN8vs+ApT29SfVWs+OceNVVqfnAv3OzFXj5K+XSDsSKFcG5aRFWnjQSGAuy8OijfpyFnUUtVyJWFn25ZSOunfnyukeAEfalMRBdfsOPuQ4FrhVsd+VdhNzIXtbK4dYimySJY9v1X3YqoSqwg7ffExOpZRZDRZwolQTVksiSjsZGZrqroOCOeReWMobWGr3mDtJ+FenFcco2vwWxy7FkB3CDs/JOySFHakHLM7IS7SCDuf7KTxVUKqHGunWWK1DDvfLqqw01VKGQN4ftyJIcLhOfFK8e9QrZTC1eC81VTNM23b8vtnZNg1RBCu7NiWsrMNtsKOTehbKXag/3ZZgdCxohMdqI1qXVaj6QRdtxR2fjO0Wbrl7HxAurkT+TjoCjtGaAEpGXb0t6sRdi0p7LTqlGntrj4bbb+phF143GNVLyQaY0UnQmJPEXZJiwTtggaldAMvorCz3WLnUCfopvqcsGununARtETYkTqgKMmWUQkxyRKbhawMuxlG2LWyOBBTV2f0mb2MHFhgpKnilGI4rU3wcyKvZX1i70Aj7LJ+R+2YKpBtXSrXHHlPm41ZYh24ORl285pqIKawQz2VtEmycRE8hxWd0CyxI5hBVU6aZ1BmBV0KKOy6UnSivyyxs4yA1UGTxiwlXIQkk0r0mk2W2LjCzrV8VJ1m+N48FTbve5PUi+RAqE2qa8q1LTU2s0tD+PLJfwaALe4ByfcxtaDhRhR2jaacTEuFXU04qAkUWsTSJ7LzLVjHQotvnyrsaGwBZEduSAzZDTnnFfDAXmtEFXZUFTV4MlwsrSKNsAvHMZOMvJmYbURJ3w4iFygLkopOzFf2kftMIUgeuRa48K3AmcfGX9PPlda+qEosEXYAlJVYJ4Q5IVdKKjrhF1PYeY4Fx7ZQsvqPsOMkbSvXnwLnChrzuG/LRKoFNCw6Ec2wK4lillhFWMtxQVrfO5+ksEsrOAGEc948Sywt6ANAs4Y64y+SqlWXXEn87jWF3SLLsBOyE2vASSw64ZAlticKO2mJTbCT2h4RdklWGx+2tHQohZ2cFOQq7FoJ/s3LsOOEnZdA2Hk2amRFy5lkqAw7+X1sWfY+K8OuCUc16pCwHGTCjlXVInKkUNEJXVVZoKJhOzlkOpQarQsZdkL0TmEXGaQyMjTp2khV2A3O5DYCQQo7qhJbQGHXqSWW71OHboHNIeyawsZoxWXKwGbidlxh11KxjDzQoDRWKTmhvUSKyhRQ2LHVbgBR5WE/wslXULSFlgi7Fq0AWarAVkmFrAw7bvVppa/JyeeJvlZgYadP0dQy7Ihka1Bl3jSiKZL/Nwc0GwkFLKRV1W+tSqwfIeyWB2/1Sd0SLToxVHIYMagfc9BmiawoZ2TYpU5IlCU2PklwEzPsgn0uwzSGpOJgWpRiNt3oF844t62izy2xiYRdkgpHQyJh5wTjq0ZChh0ADFvBb/GMxh3Av68OKhKmgfc9SX1gksLOsSLjouc9bjWu/Mfjw8U9IJvAtVmVWOGjKecwFUgiGqXgnBTIOCXSmjICW7LENhkB2Y+wrGwXi/YbDFl1lD0bQcIvL+SlZdhxhR1bJB/CvCr+EP2c8B46oSvsgDDHjpMVLYKIQqqyPVcKFMqpiqZHfxf+HZsPaf0Qm2f4vohZYoH0LDF+7XKFFN0rIgsmXGEnr2VS2KliCDZVM+8fwo7boNvKWmO/z62PbMErvnQ9Pn3pPcmbaoViiCQti+w575wWH0EkfT1lQYsrBYeKKOyUk6YFwg5AQy7Meo4Fy0og7Pa2wm6xWWIb9eBibcBOLDqhFHZJSq8scGY15Us7quhEAmEnlTuRMFACr5Iq3yvIEptDsIhYDlhWpg17za/HQ0LZcZQSCLuhkosa5HfLK44g96UssXKS46AZXxVkuVo0yFHff5AtsXyQSiqwIoPeIgo7vTpi1qS2KPS8t06qxDbrAA0qysvk/ruksIvYQErZZGhq0YkBJex8WuGTK4SJhB1Ve/Oij+0WnQDSz6e+Kps26GNE3GiZE3a6wo6IPSckI7upsKNrgHIcs5RzSZbYrHalK+q4CqsfUSBUvC2ovo3Uw1mkQosDlcyiEy0G92Zl6/F20Eq/p6uQs/reWEGqwVn8qscy7PRCEfI3yrLEAoECSMu6ileJLdb/NXyBCmXYySrSlt+ABT9WdKJacuOfE8uwC7Yt65ZYqhJr1VWVUR31jCqxnm1jGSns5L5IYedZTaxE0AdP+6X08wh02RKr3XP6BKElNiG3OimYXkOTq9pI8WkH46rIZNMtw5fEbtUOzvOH/W8GbeUXf59+gLzvSSTsSGE3pSnsomO9g1ZUIWCjSeRy3oIGIxgt2b+VSWEHNyA6Crg+aCI7WpGVPFsgDOqabb4vkTXG1u53Fase2C6hX5fBtZWYYadVmp1LLDoR3kO5wk79TWPnDmJkpuXnLnNlwR1vuTy+FIKEjxt3PKgdr07Yhf/nhGQRhR21P9uKFi8Jr222PV98bswBftjvExcRWmL7R/U5Oc+yJ9upZsruufes3wEA+NHvNyRvqkj2aNGJOGEX/Y3nVduWFloVR5BiiWXtQBWdSKsQC4TquzwVqTZ/8eeC7d2UHE1vqRN29Top7FzFanNQ8QenVcKOZ86krAKGFVbjJ0URdllh1gAcqhJrE2GVM0is6wPQggo7IN6x8eNIUAlWPCdU2OUVnYhl2GVUbvNpddyGIxs2VZcdbIUd85W3olZTv5ul/Z9B/paPjdfwyi9fjx//cbPcthOFnZ5h1wFhx98jJwtdU4Dw72hnnFsh4iRkln12EKBZYhOtpVwZBmTbBNOQ19ekbZdGXrDqtiNllxXLSMuws9Nz7jqBUthptvCk/pBPYApZYrdG/9/vCrtuFLpJgi7vzwzGb9EK0AvyL2lfvH9pZXEgRjhlKexayLftM+gZdnZMFZdCliao03VLbLgvPcMuux+JZNjRPQ1ACQ3M1ptoNH01MB/yQoVdQx2zlmFHllgi7Oj3k/uuoJZKBmVZYh3bwnJdYVcahpCf78mKu1N+nsJOu647WRjR7zl9gpCATS7uAWQr7Oj3sxlJVpcKu0ixCsvCHIJzMySJr6ZgfVrOQhcsO5rtSFDqqKloxVrqn6jYhedgn9FyehQFEFXYuWXQ+NSShVdCws4LroMCi8iUYUdqqHqRQhsSejZlXyIr7F4n7Ow6yq4d9kEE4QN+MznDrs4VdnOqKE7S5wjbjdgj1d9dyH2mYxuThN2MsyzcZ1IO2a6H2d+PRF/LUNhRfp1theQOEPaxepGTtOI9yhKbprADgPqMIgCJEPRIVd1HCrt5RtK1rLDz/ch9gtqmQPZ9S7fEejESWlPYaepRJ2exJLFKbBFLbIsKu+ZcsAiTpHQHwu+3ZItO1CWB1YCTeJK8UpuEXcROOpeYHUGEnZUw6HAziy7EFXawitmJmrqNMGtQnjeAZ8fhJkxwhkoOaqKowo7ORbTohP45/P/cEkvVZZeMwk6pwAqQVvQ70upohiX2U798EPdunsCZv3lUPt/BoDqtSmw7VlZ+c6eOsmuEndyP7QaD1DTVXGMeSuW3VBR2ZIkVWQq7LhSdyKnUlfp82qCPEXEjFS+j6ERI7IXb9EJhJ9usIuKSVK5sAlPEEkvFB1YeGTzqA8B+Q8Hsr5bRVoZdq5bYbhB2GYQl7+dbye7MmIzEPyPHKtTHiGXYqYmQvOatlGs/YcwTUTkhHKPVSE1UtEost8RWxtTzJQSfsYdV26uWHEUM1qARz4KKTkQne6odyft+GXX4OVViE4tOOFa8SqxlQZSXRbab4gq7rKITtMjVyXXOK4z2EbhiUoeXk6MEQP1+LrPE1pUlNnyfEAJz0t1StYNzRVmDAFRmVvwDcvoslT/GM+zs+EImgAOXV9OV7UA0w86yQiKHFHZkiRWeprDLsMRKAmVYnt80xUwS9D6iL6HOYQGFHVIUdgDQmFfqqIh9m81rq6hlZtjVhQPelBXp0eGYuc4WMkad4LOmHNYXJd0fuftAJ6v1OSO7702xghPcokiqw3lNQUYqV70fTbS760U36rMsW01T2In+Iey4+muu0eJYWrvfliRpnxa92dCiLpQ1Fum/KcCsx5olNi3jNZJh14olNo+U1hV280GfnrZoQIRd1qJOGoQQ+K/L78MFtzyWv/FiJewateCHbFpuomeYiim4aOQHtkZ2zBqe8BMH4Q7SLbGOl/G5jMQj66hwiins/JjCLqPTjIUEJyvs6sKBl6BOHCoVV9iFllhphY0o7NJVMSFhF3x+3vfvayhiieestVB0glZHM4pO7JjRVnQ6yrBLUaO1MxGkjs+thGRlt35rnXBKyxnjpNISqxLbhAXbQlhEJkLY6QVLMkipNBRV2OmDsTTyl5H6I9wSqw/OEhV23Sw6oalMlSIzp/BLEcKObvYrDgseuaq7H9FO9mERpBbU6bUltt08vCSyIxrEXBgxwi6rSuzgWmLjGXbSEqur4rKKTgBAs8aCrqN5eKHCrlg7Dgg7ItVCws6T48Jd08FvZ1uBooOIwbjCLsUSm0DYpSvs0tVF0aITy9XzPjtmAJjwK0xhlzChoHNLtr2OCDu6prs3odgbmEmpEgvk5ygBTGFnhZbYhrSTcnKq4QulsKtIRci+4NXVWSYmBy98lAQqOqFXidWjQoCowi4vww5Q7cKSfRQRSTW4wQS1JYWdLJJVpDKuRENT6/QlsrKztN+gjCDDjpSMEfK7WQuLTkQUduF+q1YNc/Pp972aRjLNN3wIIToeM88wknBIVhKetEbDDZKC/nkGrE6UFVDYcTsskK6wU9ECmlI5sahBzC2SpLCjDLv+UX1y9VeiJfaP/wd86enA1oRcOm18QsRbU4ig7TAIIWKLZ6HCTh/nR9vprG6JTbIsM8yzvjVU2GUQdhmRNkIIXPiH9bhn0wQwH83g9uUiTFofpCyxbSjsbntsHF+79mH860V35isfW124LoDuEHZy4uRbyQdGCrtgoxYGGAWUIFmWWJdbTIX24/icsJNEXUE7kd9KsHQscyRZYdeAk7gqFVhiSWFXkLBrVWHnRAeveRl+fY1mwoS+yORNKewkYefX4ySwbFPUjhKJmVYRIysKkBBpoO/gljvbTxJ0wint3NI1zKt4DrrCjl1rw2U3zHmLWGJTFHatqF1jZEEaYRfPlEoEI+KiRSfS+xK1Tatq6izUNUtsVttt1RJLg9DlBwePA6Ow6zZhpw0+umljzTrmbtpr282w09tPpsJucItO6Bl2ysZKqjg697EMu/g50Sf2VDxsnoi0ggWbmr5AmTLsvKoiLobs4PffMRW8NlQKFpPtWIZdWpVYWniIEnYVq5ausMuwxLp2QtEJAE2msJsQQ5jzrWJkOE3YO1kYUddWn2XYyeqWyVVis3OUAJZh54QKu4YTqLe5/bPRFJgTwb2mihrKqIXEDJBRrClnoqYUdlPRIg16/AmAsUpGdXb+nBpLBe/VLbHz8ILrN6t/lKCJLBEsrShR9GzKvkTWeFTrj8qYR8V1FCkiuMWvGarnIhl22v1DJBGDzXDspWO+4Xc8ZqbjcmwLVdl/zooSK7iRcEycoJ7XyOqMDLspmbs3rBN2HhF2WoZdSvEeyiSLWLT1fLP6TExh51pUaKhPFXZJxNAlfweMPwpc/i/x12KEXaiwI7UjgZPxtNhBykalGqVxd4ollojRPEtsvRE+r6rEesOJ2wYHlF5c7oaHduBDP74Dr/rK9QkKO7LEJvdBZTd/UScNG3aH18VdG1P6f0Lewk0b6Eqv2pRFJ0QKYVfihF0rK876wDhhoEwrszYphhhc/pz+uTQZFbZqqMIuNtkRUmGnVj8yOs1m3gCeEXZJjPBQycG8UthlD/4tugkrwo59/5QMuybLsPOXQtEJpRQptXbT0xV2/Dn1f7maKRKqgbaiLOVQgzjdDtjGhFwp7KpoS8GVBV/rnNJWAPWqt3zbAcp74hCswMtI2WXKyy5aYn0/3J+T064LZ9glK+xihD7rw8j2a/VCYRezxKZPYM65cSMmGqSSSWnjzUZ4fY2uCR7r08nb9gvayT4sgrQMO30hLGnbPGQVimi56EQG2cGvh14p7GJqssFZ/Ipl2Ik08ksn7PRz0oiG7SNceA3Jv4LxJFxh51ZU/znqBcdGCjsid2y9Smys6ESKJVbe9zMVdinZSwBQspoYtWQ/ywm7UqiwGxfDwWTVyiBVmuy7pm1TFD2YUOwNKNVSRpXYIkUnHNtWE/5mgsKu7vuYlwq7MuoYg3Zv0EkLQl7/F8mw4wo7Nj6TGKtmFHuKfBaNu4J7vy3HUp4gwq6kKezS78/zeoZdC4SdnofVl8gq3BSzxDZQ9uyQFHHLavwlGvPJbVUjw0RiNVpS2AV9yVglvEbn6s18hd01nwW+8+rUsd2MJL2HSg48ISvawstWF3KCOmaJTRemJFWIBcIqrmlVYvWFD2pTTa7gKqKws+R9qk8VdplVmpPcMbollinldk9HfyeuhiOC1LIseI6FkqyMnRSfJIRQx0VkdGLGYMpnKUtslsLOTV+YX7cj7Isbc1q/LOcLaYRdJwq7h7eHn3Xv5pT+n7BoLbGyhLifcoOKKOxaIQjyCDshlC3DTaiw6pY4YZU8yeQKM6ugwo4uiGnIzi3jO83N6d9BJ+xYtdaEVanAEltMYUeEHVliS66jqlyl5k6J0BIbKuwGmLBTxIgXEnZF2qSusEt6nyZjj4Sctktg6DaJrijsSp0Rf0nQV+vTyNCEVeTMirKDAHaNRxR2vE9qaIRdq9ZGfpPOylkE0knUlONuwMFIpsIu/H62XCywulolViN5s4pOyHN61vWP4p5t8numXSs1Nugc3V8+1+eEXa8UdjwbECiYYVeUsOuiJTat6IQWxNxSXxNb7Ms4t0Wqifcp9HwqRX6RKs5KIV4TzklDkX92ZF81ssQWrhLro0wZdizqYcQLjnXXdNBHDBFhJ6iyrROQJXrRCW6JFSJUCzJLbFo+GqkiIsqQqW3AjgdRabK+htlgG1749x4M5xcGUJbYavo2RdGDCcXewExSkL8EtadChJ0FRtjJohNssllv+MoSW/LnwwxCQqrCLke5mJRh5yRbYkcrHuoo0B7oN5Tvtf2gfyMypibcgIwslGEni7TIDDtfIFVVqkO31/UlMqvQB+dtDsEYpGTVUXLCohPCCd0rtfnwHhO1xEbvPU5zNn5+Zb9H/eFoxVP97lw9R2EnBPCbzwGP3gA8+OvEr0jX0FDJQUlWA50VXkjO6IRdsxFdzIwRdsniBQCYrqVYYlMUdmnRAqF6NssSG8+wU4RdPynsIpbYjLG0W44/p7UJrgrOVNgx/qHkhCR0EmEXKSBRogy7hIzBlM8Kq8RmEXbppDTPL90zESXORI0y7HKKTrSRYccVduMzOWNsTUDVDXSFsPOJsCuisOvEEquzybxgQ4IltsQtsak2rpAoI4WdlXeMsjOaEsHNUWQUAIjlwaVk3KQp7Cqeg7rIv8nKDwseZANxbTuUVKdm2MUtsV1XZywmRCxzLVQnpd+N8kf4vgisTfHH4LU2J9A6waUIuzb2x1Vc3bbExlZ6U1RzCYPSLOnzIECwogzDPAuOT2xjCrtiljCFRhJhl1Z0Il+5HBw3ZV/YGC3nW2IbcODJhRNLNNtXleqggaJS2KW0Xb+pFF91uJhrZliJgNDi4VZC1Uu/E3Y9y7DTru9uZth11RKbsuimXwudEHZZ53aAi040tdw5pbDTq8TGLLH6uK3OqklG1XrKEls0w06wCYnHFHZucAw7SWHnEWEnCwDBTsz0CtUZdvSzZZ9atWpopk5INGWIEMD3TgS+dhz22XBFcDzWisgAvh5R2I0EEzV13QjEcuy6qbCj+0+fZdjNMrJBB7WnLEtsI1FhJ4tOsPPd8ENLrCvmMQaNxEjLsMvr/yIZdky1mlB0YqziokkK1qRxecwSKwv8yX7Hk2R2aInNn0vQOeDnt56SS6VDz6bsS2QuIAVtbxbB9eehAdu2MOzIfsUOi9lxsUYlpUosIAtP6KSMT0V4HPl+GxXZrwQKu4xA/j0b2H+SSYuQsHMVqTsjuMJOI8J0Nel8SoYdtV3Wvqbmg8+KZ9ilFZ1ILt5DTrBohp12TdZmwuI/8ny5lGEn+qdNcjJJPz+R34bPowhau+UVjPV2xvtJTnCVXDtU5lF/xfbLSURql26OJbaRlGGXRdipWKX4GGqKVU7eM6WRx7JNJAmggM4UdmTvBhApaJWIxZphR6RUaoad64YXSysD2NggW+tEOGGXoLDz+HOxoHRSj9hhdlzBCnuWUthV5K7Tv5PI8Pbzz2rCTsx9GCq52RkWDLac8Nhy4Oy5dtSWmfi5YZVYqKIbA0zY8cGUWqUqorBjOTlWSltWxIWsrhVR2LV5TlupkJmHnhJ2mqpGqebSFHbcEtsCcdqPYAq0Ic8JlZcJGXZ3bpnFK798PXbMypte0WuR/47UVlItscUUdqIZEnFD5YyJAyP2SqWM3NB2UdPaTNqNnJ3PBpxQmZDWxmmVuDwanjM9TLnf0CrRWwS+D1XZuReEXda+RIuDHvX9c0ijlgg7VqgIyFHYaQPRAbLE1nUba1qGXazoRPw6jZAmyMqwy7PE+mGVWLeqFuFGnKglVinsWAB5VGEXzbAruXb0dy6HC3WWn9yf1BpadcMdDwLb7wP8Bo68+f8DAGyzVkfeU3fD/e4BEXZsHKiTn3RMSmHXSYZdf1tikwg7Gstn5RM1RbxKrC8jR3jOUr3pqyqxdnOuBYVdwQy7+cnodZCwmDlW9QpaYqMZdnaTFHbMEuv7EFl2awki0yOEXcG8p4EoOpE1NpbnbZYUdvL8jjjB8z4bW8/PB79nybGj+eTaPLaERqQIRPDZ8neT/WG15CjSb67RzFbYbb8//FtXwklwS6zrS4Wd74X3Lb3ohN7W0yyxCfe96TRLrMcISIZQqawTdsFjI4uwq3PCjiyxwefX+4mw4wo7vUrs1Nbw78QYkei1zS2x+rnmqnleMNRzGGFH/RW7HqgPdm1LkfN56mZ6vuo5BS2x6fPCCUacNWva63IMrxctIXRSJZYrFPMJu0WaYefnEXaOzSZPrWTY5VRjZQ3TSciw81wnJApTbVwhYWUVWH0K3hR8hxnZaTeyCJ9Yuevk71CHm1J0wi5cbZQGvZYkdTzbSs7LAtRAkGfYFVl963vwAU4rRBH9blkFG0gtKdtcdwi7LlpiqS0WDeRvBboSJi/Djl6PbDuYCjvqa2zbRtmzky2x8nf4yCX34d7NE7h7izxPRX9nOndORvtU2xYkL9hiQsmxYbvJCxpCEdVOlLDrVo6dIq1zik6w/9fhoqaI0TzCbizMFRoYhV0X+3D+e6sMu6zcuTYJu6Rjbtlem0JY6vfoDFV8DCq/tAAJR98hjzTvQ5AayNEy7NQYK80Sm5Dr19DsoyrDrsUqsY2mCBUEbjm0xLrB/neyohNA6J5owgmICY1kpMli2XWin82yax0/+TeNTTQ33BLbZitWRd/jhYTduNAssey4Yv+nscsStsRWMqrEplUqBKAUkg4j7AQRdlxh1xSKmHGa893PsKuxDDvLComcSNEJN3vupFf6le3ClaSyssTChRCAn3aNMhA5x89vlmKRYyCKTmQpvuX5pnZBZNCQVNg17bgllogphbpO2NXjtkfqj/zgN6h6jLCr+9kZdpzQmd0dfx1RS2wiYacTYTpBl1Z0gu6RfpywGylHrwelsNMtsTlFJxIVdhVZvKc+G1aZle939UJDfYBMSywnU+fG42/W2i3l/CftS2VOatxDoLCL5rfycTRVruV9hJujbqbPGi47rVli/XpMaT7JFHb69WTJNuGl2PJL8jjbUtgxwm48l7BbpBl2QmXYJWc2lFwrWVWSh7ysJbYv10uwxDp2+uoUq4CoBqBOdFCXBkfeDKeFVNjVM75TbOKgE3ZhllyS57rsOkqxlXfuVNA7EXaFFHZ264RlP4MPpsgS25zPt+/xjLE0W2qWwq6dCbTfDK8BXV0kmq0TIlwp0nNLbAoZmlV0YoAmtxHIyajteCg5dnL1YPk70OB8tknZk0Uz7EhlUs7PZqTfhG7EaQo7bnV1LNiyX9HtrqTEa8JBOULYdakfIRItVnglWeEKBOcxd5EoUWHX54RdLzLs+L5o/93MsCtkie1QrdcNS2wR1Zyvbzs4lli9UIQFTbmgCpGkqMIIzVpMrRdX2BVrx74Q4cSCLaaNeMH+tk8Gv3tVU9g1YQfkTFqGnadZYr0hCGkvs1MIOzXRpJX9yS2xbXTCbnr4YPX3A+KgYB8Rwk5X3hBh12GGnRB9Sdg1faEmWkOl+HGHltgshV3wGBR6IMJuKPa+QGEXtCe7MYflusIuZ6ErX2E3FSpcMjLsVLRK4uKIli0q30ukMhF38yJ4PXU+wEBkZ9m1QaKbWN7TH84B7vhR6nuTxAd9gwIZduSucqXCbpgUdmxsTYRdrDiKRoZ5aKh+J/ycqMKu4jkq8y2wxGYo7Pj+cwi7aslVbWRaeCHhFlOuaWNEfZykLLGUdxa2r8ncKrFFFXYJlks6rqFV6rhrPNYAUDn3NeEUzmJcaPDrLdaX8X4n6ffV5pouI+ziltjkvMCKI+BY8nOVwi5uieVkdF7RCSLsqiUnrBLLqyrrcJgISxtHTcyG35GKgIYfFJyfNJVvJxl2rVliFylhl1dtKqKwa2UikauwCxtfKUFhV3IzlH0JRSdUR50TmE7WU1pl8TMUdlYKUaj/P8iSi/8cZddOz47SP0sEr5Ml1rWtjAy7MFA+9v0HmrBjdoWsKsI68hR2fhNkGwtLsVvwC/52iYhkFVDgfgvHrCPJEtutib1uA1EknK5sScqw66xE/aIHFYNxHEmiJ1hL5W8ZEnYZuTVJUAo79tum9Uv0G1BuW1rRiSb1Jy4sy4JIU36wxY8SjyHoVuEJXWGXRkiS0ltYQUYVZX+mKuzkKnF5NNx3vxN23a7+DGgKuyKW2FYru3az6ETKccXGEu0o7OTgMtMSqwc1D44lNjXDTllis8ca4f8bal+Oo1limxr5l6uw81Gmanas7xtzg/1vngj6NspPsth4K8sSW+aWWNsFbBu+E6qtkhDLXpreHtvmHhwe+f/OVc8MX/MPDSYRFpvgx84ly+tLer0o+G+yWAm72XHgnksix8onnEmW2GJFJ5iqhBR28nrlyrx6U2BOEl2oz2K5rZMYbRJ2lAlVm4wWaUhYzBwqOekOG066ahl2rrTEusoSG7yeOh9goAm3a1tKKReZhE9tB37xD8BF7wJ2Ppz43rTA975AakZuGA0xLbMNyXJMCruGHS6Y1qVVL1YcRRuXlayGUiyFnxXsb04qjqueE62qSuPrpLFbAcJuVlpihz0brixQMuNnVInV46jS3G4ZCrsYYecyxSA//LQqsXZClVhSm9FYtlljCjtp1bTC+KuiWYwLDa7+ih0zP/cZFYYJEcJOs16r4k/a9UqZjAASi06EhF3YtkNCNfkcK6u956JqFVHYsdoH2nhtcj5sX4Jeo0UsqpDdgyqxk0xhN9GvGXa+bCDCSl5R97jSrYWJRG0+p9OgwZew4brxzy7xyXHCoBEIBm7U0CypsLNzSAxHRC2xWRl2RNjRCldWoYKkykplbonNOXe2JOwsaV3znGIKO7UaZhdTGPY1Ihl2zJaZN4FThEiKOo2dsyZT1oUWhDYmbrwzpmPNWHXIBR/c9doSq0gjXWGXUCW2leIf/Qg5sXUcF+XI4gUn7IL2Ra9N0M9SWGHHCOWsKqpA2Jary+X/06rEEtEo+0UnWT0XVdiVErdpG82Gauc3rZ/D0z/xK/zP1evka8mWWOov8zPsiLDTLLF9MqhLBFmjumqJTZjcdzXDLmNRo1v22lgxiBb6vZhqLuPcLiWFXazoBLWJlEIJ6v9hlVgvprCT2xRdPOSvs3vziBfsaNN4cE8Zq5D6L3g+v+gEs8RKQtl3pKomLcNOTTTl+ZjaFjyufmLwfmHhd/5TI++Z8vbFDxovwk3OM/En8TjUmwKCK1NjCjtSE3aYYZdEwi82XPVJ4EenBeSQBGVvWVaooOEIK0nmF52wkyyxjJhq+D7mQeOYWSyzgrGLyBuv5CrsAsJOzDNLbKToRDg2CjKsU/rapN/QJYVd0EZdZYnVFXbp/Z+yyTmh6yeS9zSzM/z7/su09w5A0Ym0sTE739O+JEaJsLMlKWR56rcgwi5m3dbuCR4a8aITKsNOEnYlh2W+5VSJreUTdtOSuBn1ws+dbLqhQi6h+moE+phRLzqRUCV2tKITdskKO8qRzFXYCcEsscvlcc1jXls4cUQ4Pm2HpNnbEEJE1F88VxNAtN9J+v11S6yVbq9V16tmYR+KEHZJCru4JVapm1MWS0hVHyjsyOXTnsKOCpkAgEXnQ9qiLSq4k9IHUbvoVGGXT9gtcoWdn3JgrmOpyVOsamoG5mZ1wk5n9YN9NaVlS0fZTc9/8+Wg2xfhKpLFLV8ZIGJsRpDCLv07Efk1Szf+lBXTiNKPoeTYaEgLXdbnBMdFWVkhYZemzqPcwQYcdbFaBYOe+xr8InIYg583sVLqtHLyDZ39XWeEXZMIu3aIMboZudVQvcBt520r7HphiU1T2KVViU0qOjGYCjuyqtuOp12TvP2QdUUO9kSL7SbRsp1miZW/AQ1yUpUClInpRh714wqtszYqkcrcXRgc1UPF2y/uG8fEXAN/2CifixXwiaoUa0WLTlTG2MBBpBOY/YBuK2cB9ltbvcmwyyJn2rbX5hB2rdzjdNVcpsJOUxoMkMJOt7uRor9GuXNpgfYxe3ItNrGnPjJU2BVbUHI4eeaEixUjskosESJj1Wi7aMBOzLBTlljXjqmXlMLOT+4vayp7SVPYvfBD2PGSL+Af6u/DJn9F5D31po+PNN6NT459KozSEBZUdce0c9mxwq4PCLs/nBM83vY99dRcTdqqPCcSkk6gMXQ9Q2FHtjjP8mNFvTjRV28KZYlFfQ7LJWHXGNo3eC5tvJLXZ5HFjBU4ckUj/E3YQnLVc5joQL+OEqIKSGEnopbYmhV8j0aWvZZ264cqObo+I0UneAECLUMrol7sV6T1Pez8k1iDCNGqrFTdsErqt6jX5Gu6ElRzpGVl2M01mcLOo8w3prBLIo25Oi7FPUGW2DE3/NypphuSxXrRCdqPyorTc0nTVehErgxrFvZIJh9DTcugI9C1Ters4PoT0eNq1kLCT7PENkR/EHYNX0QSmmKKNd7vJI1t27LEago7SUALWGGbyLHEuklq3MhnhX13lQpFJVW5JVhWqphjnn0Pq0mEnay4rgi75D7Ia7PoRKPpR87fjH7N6shxnraDrhJ2Ii3DjuU2NXW/cQYaWvUPoXc+qmCDEysBHXyuE64oaZ1vsxESVo5DCjtJ2GUNgvwmbNlJ0OqbnzGotLWqQml2kTojzjjKXljtMEvJB4SEHSnsHNsKKztqN2i/Gfzf5xl+pLATS4GwcwISjC6mPLKIZ4S1orCjv9upmJmkRuPH3CrZpgKKS+io2mwSYhl2OUUnIpbYjMHHAICuJ9dxpeqX+iR5zvymah90rbdcpCfJsp3WX9BvTpUP0wgIUuy2pLBz4YuUyWY7oIGj5eDBHVJBl2Z1ZVVtgQIKuzlmiXWrUJPkfrbFFiQ6WkISAVdIFVe0UEQvLLG6qqsDhV2GeiAGRajEbSR9iQveDHz9+cCWu6L2PfCiE1qV2NwMu0ZsX9TXzPuBwqBohl3EDcHua8NO9H6r1B1+OO5p+H6MeFYKO55hJ9sUKavSFHapltiRfTD/tLfgEv/5MSJJ5fqwiU/Eqhs7lxqp0zZhl0D2LDZQLhXDTD34vjGboYQqOlFAYaeqCwNAeTjyGu1jToQKu7EYYZetTE+3xAaEndWswZM5kJFCJmwxs1IKF+xFrDo7+w21DDsqJOBIQqlhSRIprQgfQ5gvaTPVDDufnLCbj1ZV17Mp+xKpllhG2Imowq5qy7koV9jJbPNYW6V7kWwHJSRZYoP3zrEMu5Dg4hl2OYRdypiaLLGjXvi5sw07JNzSMuzIehpT2JGynMgdpkZMtcSmKOyUUjl63mieSlWeI9+NyJrGPGpybuup6IYw/qloteOFhE4qxkjGXIVd9B7hRopOaPbjFEtsVRJ2vl1iWe8Jllj2G4UVurMtscNlp5glln0HfS7DP8Om66kctAFS2KWpfOn+HFMu5mB6PtpOY5WddSxahZ3sXESBKrGZBRpiu412No26TroxO2nCj+M6FlOzJBNWvEosFZ2wswgr1mkXybCzZYc+K5IVdkQc8uPg4CrBZr2gJVY2EC/y/bXPZRVNvVYIy36HvvpZlCxqsosvh7DjhUwyA4PzoK3+KrSrjlNFJ/h36LYlVi86oWdHLbEMOzbQtR1H9oXaNalVNw0eW7RS8wy7PEtswZwt6gcc2S/YXGGXkGEH20HJtcNV/G5k2LFr4OEdwd9k74mTMGmW2JRzyItO2GywWptK3r4f0AuVdCJh18UMu0yFXbuEXZ4ltoW+s5UqsXS9qm37nLDbfh+w5U6gNhVmW6ncOQrz1i2xOsmk271qzHYnxx4sU7fBCasca7elxp520Pbl5EIn7MYqmsJOaJ+jZdiVHCf8LWX7FDQBSis60YwqO0IF7zJl/dWJJDoPvIBCYNVNIcSVJbaLGXYpUTYLDr5AL6/fMCw/JX5H5VxlZdhJaxbZsmDBllbSeobCbpksOpGvsCtG2AHAMILvSJlzgBXJbhoquWoMWdcdNvza0BR2HllifSLsgueL5GE32LXpJU1uOWFXi1YPbTA7bd8ibbEgYe5HCl8i7BoICbuGnBfGCbvogmlA2CX3maQ4Lns2s/IJpqRP+B0TrhsdZIkdkf3kvPCC/eZl2Knc4xSFHS1UcYWdtBGOpBJ2yX1ibpVY9d0sZtucV21VWeaZqrofFHb6McYsppF5Zz1eMNGP3iMKKew0sVBVVT1OFnfMNeIZdtRXpPW9RA5WS26xohNAmNmuzc9rSYRdJUrYpVWJdZMWIQpAP3e1hp9dPbtVd0gBdElhF7UO6AhsYLITa0Fh52sKu7r2XtpXI8US6zoWq8iokX3KEsqrxBawxLLBOpFwWTZfItFUFkaq0s9OtMS6toUmkZ25GXbBcTtusL1jW6lyel+RnWGGH1SV3C6FxS9G6IOpouQXH7wnWWLlfn3YELCxcpgsCF0oOqHLhtvNn4so7HpUJZYG/2mkUZbCLo1g6mewvsR2A4VdQ++TEgi7hsghm3TQ4KUVhV1CmGwEysobHIvrOskVbtVv78J1bPgFgq0LQ2UMDWHHVDTnL25ZiVpi8zPsiLCTq7ODUCm2lwo7fn9f7Bl2eaRRK5ZhvUpsEUss9W/tVPNeTGC/TbxKrHQHKEtsAeseAPh1tq8oud8U0qpaUGHnEGFH7V6+L5LBg7gl1leWWD3DTlpiIwo7Sdg50Um6DppoKYUdEf+lEUVg+AKRSoW1ZpjrQ0gqhqGgMhKpffloK3pA9dl2GLexmOD7UeJBqqHnJNGQVHACABw7wcKpgSaUFRFWSw9tUqxKrB9WiUVjFqMI7gu1qiTs0oo15fVZjquy5kas4BgcIuy8IYBZfaueo8aQtVpyBEQkqkDulyyxpNxryjbcKKCw45UjQ4sxa2Pz6Qq7wSg6kW+JJcKOFL4VWfimZpXU707ilEqaJVaSTJ6VQNg1SWEnCTvXCdtow892yPDxS6rCThJ20hI7DzcgQdIIOyLoVHGH+Wi/k7GoNaUUdtHzEFEM8o+SbUh3zcUy7FSxgQqbb9TjhJ8fznXbyS3b29CPMaZY03/TlOJrqmI0fJXhGis6oS2cEYYSqh7nZdi5SXmXCd9jyGNVYvMUdk7yPJKTmqoIFGXY+dkZdm6Be0QSaGzA+7ZMW2zSuLlDdFVhl8Ykeo6FmrzpNHJsnZHdNnSCLvreJrNiJf04nh3az5qNZKKsyayotrSS2lkTTTaApJu5SMuWEyLIpkCYYdfUbgI++w5JllhenTFPnagssfICyyo6kZRh55A6Y6AtsXrWWkF1Fx+8ZyjsmlJlurxKIb8dkBdkB4wRdvT5LRJcinTshSVWVy6mnNckm+9AK+zC391xXJSSVK8J+YeJOXdZoLbAMxbT2pw2YEwkd4QIFbtyfyUnZQFA/i0cN8jcTFE1twXZXhpOmOujsuliqqlQPQOEeYCFqsQCg0HYFSQ6WkKSxTWNGItsX5Rky7LEtrhKmVZdNMGWWRgtWWJpsMxWjvtZZceIowYPyEe4sBdT2OnxDwkEnk7+0e/cpEp+BYlnmjALuifKx6pG2I1qRScauUUneIadtMTKhSUvxxLrOXageqB+pDQcLoqCWbogJ9+IFlCoR7L1UohnXkGvHSWzRkYuOszuhsqnAlRfrRR2KZZYZeHMmJgrhZ2QhFtpWM0f+PsamsJujAi7ymq5QZsZdoDKsYsp7LxKZDPHtlThsro+/lcLsOw31BR2RGg3ZIZdPSUih6POcuhChV2KJVZTo4d9xCIkgYsixxIrbC82BqFK1TW46vdoNFIssdRuymSJzciwk5bYshsq7OpNP51UBKJkW8q9h2yqQ04YxVJr+PlFJ6or2fdgxJG+qAWh2lh+0YlkC6g+p3d19ayKKWK2zYSiE2Bz3X5U2NWbIoiJIMRcS3o+L90jQoXdCikgiZGj+sKZREVW1m1ayfPd5Ay77KITYZVYoGxpLp80qLmhbokNP0MtoMmFdzvHElvkHpEEaqcjZVfdz3UCNILFa4kNO7IkWBZTibVA2OnKNV2dRxbZegphFxS7IMIu+rm+yjuyQWMpmpjaWQMgdqNThF3aoJKXo5eZBzrpSHbahkhW2AFQxTxyi04grrAje5p+jKElmH//4PtkWoL7HR0r7FIssVR4RQ6ulg/Jm3Yn5IUit7psiXXc7Bt+OxA6EZqXYZdUdGIAM+zY764UdnqGnbzhNuFAkP1F3yYPDTZ4ScvxIsQUdkmEXXgzoww7l1e4jahL5UKB7cK1Laaw6wJhJye9dTuBsEuoPgm0kAPIq8QCg2GJVURHry2xXVTFZZGM3SpgkVD4oDB0CzmbjKRuyxck+jlighFHTT3vRmgKu7Q2ESNL6/GVfaaCaDZFYWs3ZXSpe6JS2EUnDboltgk7mPhZ0b6qFqkSSxESZImNBvrrCKvE2sF76dhLw5G4E24Z4rl3kbwwK42wi+YTRZ5rBT2YTHQVmtWS1NBkS0qzxBYpOhFm2IWEXVJxhUbTD6NsGrMYFcG9aJ4Udu1WiQXUYtkw5mBZgN1MGBcRVCZaSuEcPu+S/Y4niLCTLiQ7aLuJCnkNXGFHVrnIJDwjw05Vfx5ghZ2wHdTUYmBwfiuSgJhHOP6iuV6EsBMi7A9JYZeYYUeWWEbYuUzBlLWgEbHEpijs5HU0LBc2avAkYZdSdEJZYpcn71sfU7JjS82woyIaeq5aM5mwUwq7ZpLCLpwTEbmsognYYlA/KOySFGqR6y9PYaepsF00sXwombBrpNiPKcOuYZfCezH7nFlF2HGFXUJfkfC9xhx2vLkZdslzQ05qqogKaYm1JYFXSumDYkrNguBjgyH5vTNz7JSQbbERdgVW6xpSeeTrsu4M6CSTnuFGBF6T2Vo5uMJMV9iRwkwgrDblSqLLRsaPwLLfci1XvIGTwk5X+jWzM+yCA5JVyrImGawYBll7XdtSVmSd7FPf3wq/v+UuBUtsQSWYjiYbHNENnZPA6qYQ7HdZVf7enSjs+tESm6dczCw6MYAKO0b+O44XzXjTLLEUDA10qLDLsiuyzwsVQwltgL2XFjK8iMKuGd/WDiyxvciwm7fCCWpq0YlWLbFMARM8jkSf70c4OWRtO0iqdlUow66oKq6bltiU60appcrJr2chph5Aet/rt7BtP4ARRyrDjqrKU4adH982goQMO04KwPdhybFLQynsChJ2yhIr72fyfaOl6Hb7jVHmW3ifjijZ5HeJKOz4/RJQ96mSSO5PQmWIFe1DvKjCLlLYgKkWIxPSVEtsM3pMSdsUQas5k3sbeh9MhJ2yxCYfd5hzla+wq1C139JQmDHI3ldr+mGUTW0aw5D3oso+wXOdEHZSXTVqzQbj/rSxHqDaaKOW1qexzyEVqLLEBm3Vp8qlRYpO8Aw7ThIR+G+jLW7Vm8mKnb5CTpVYYblhjq6cA5QRbFsTbmiJJYUdJ5f5PuW4o5yYYScVdirDLhSl1Bp+9vg9YolNHlMrpSop7IQTWP5Si07Itl4eDdt1EmHH73t+HfONpmoTOmFXkYTaXErRCWp7hFBh50e/m1uOKOxqusKOFadstTLoQkAtKDD1WqTyalFLLPUFVhNj0o6s20D1au0Esng3LS+8HrhYSVliw/el5bTq32uZK8UtWl5nIpTVOfoduSqTKjUrhR3ld6Yq7LKJxTTwuAy6pmdq0X5UCIHd0/J4FmuGnaoq6qTfoMgq2JIlVlMJ6IQdt8QmISCsUgg7ssRa4SmwlcIu3xLbQJgtIdIG/wn2Wb1whlL6WW5imXogsJrxY07+rPCYydrLJ89N7VyGVtzw+zuq6MYgE3a6wi4noF+9j9kPEi2xIfEKMIWd6IC8qMsbb6oltlWFXS8tsSnnNY2wc9l3Uplrg62ws2wnkuepW2LrjLDLJZt0qJs0U9ilqax0xVBicC3rT5ygTXsRu2s9ti0p7DoiqXXIlV5VZRta0Ql+3K1WiaVBKF1fg2CJ7UmGHQ08kjLsummJzSD/igbjJwwuI/tOqGKXiyT1QKp6lT6HK6D6+H7KqpXGMuxiCrtw2wgSM+yCAbdjW5HtmypbrqAlVo09oxl2I9ra8T6jRNSG455GAjEYybBLscSmKewiVWKJyHArgONGFXYRFVc4YYqomdIIOzpXHSvsmGNgMUJX+EjCjiZIqVVidRVOApIy7MLqstHfRllip7apBfE5ZYntRGEXxDAMYza4BjIIO3IuNWJFJxKEEoqwC/ossof5SmFXIMOO2eQS857496YcWDokem9fK+xSxtdNIuwcpvIP+oISSGHnxQg7rkKKzDOo6IRVj5FWqj9illhF2OVlfOZVEQWzxNpk5dUUdjHCTv7frYZjd67kU2PK6EIVFZwAgGGNZE9T2MWyQCUcXe2ZqLCbZ1Vmo229KfrDEhtWDg/bTUQZmGuJ1cY6AMYqyfbjyH2YoWKzOUnCvWg+o0qsntOqPkv2ISNy33MoR/I6E+EkK+w48UqVmmnB3cnNsAut1UKf92SA2mnZtVWGqq6w++jFd+LP/v0KXHHP1p6o2LtD2BUI1yPCTrSQu0UKuzkh88A0si/MoUs+IY6dYYmVg2ifvdeiDLtMS2w4KfQ8InvSJsbh83OqomwyceinkI7BAUlLRmZ2DsvKkkq5YPIc7FcnP6lEvM8q+9pL0RKrqtDkECPcHpNEdrF2AYQZdo1uKOz6qkpsXoZdRpXYZgJx1O9gk3XXcTRLbFRhRwTT6pESI5sKthtld2ZkbJ7CLsG+EB43V9gFxxIl7HiGHak+XFnoppsZdgF5NoNgIrJmWUXlocaOg5SKcDBcctKts2rfWp7iIBB2ezvDTjTTyd6uWGJbVAKlZtjRILaN6q1J6oFUhR1TYlsJ10q/IaHohBrca5NKVbwg144cZth5jhV5vQknmPTn9WESanWd7iHy9y/b0YmJOmYqbgE7OAamCmz6QhETgSVWI0QyMuyavgDNUUquHVPv8gkRD/Bvsrwwl2frpJGfKp+oFH+uFSx6S6wWSyDjC+ZIAemlTMYSrK06KEOwrBR2w4nFFRq+jzmyxE5uARAUmpt3pBJbr5RJSOovdVCGnTUXkGKcENFgKUtsivWNz7u8qArUpqITjl4lNr3NcJtcYt4TH9PpGXbNsD33LXKqxAo7rrArQSriREhw+EkZdhGFXYYlVl73c/Jn4oRdboYdv7elEHbKWs4Iu3qkSqzWtokw8SrhYlRShh1vv34Dk6xCrE4KpWbYcfU1A12jsSqxTrTQWozwYyKbfiDs1IICazfR6y/PEhuPTRj1kgtCpBWJKasMOzeRsJvLsMQCWpEaek5+9qgd/G6zqMS2iSFlfh4pOkH3SNmnUq5tmi0/cpwtFJ6YZ0RwVZLPnLDbNjGHC25ZDwC4+r6t0bFgl9Alwi44QVbGgREx5OcUTohAdgIziuzSCTuSbSbfGC3LUkSY/l6lMGMKO0cSdk4WYcVUHJ6XQ3qQ6kpYKvMgLUvPz1AQkCUtU2HHjsGRnZdjW0rhFbfExj/XLkJY9jtSM+wKWmKdFLKLBZsCocKuSGZIKvrKEls0w45IEjb5VQPOjGyofoW8lhrChuPYGuklvysRdrKtrB4pxyvJ5oFPLlvNsOPPEdjv4DBLbBJhpxTWtqPZZrunsKN7wEErh0IyE4gOSOX3rcHFypFSunVWvVdX2JEltp8z7FokeosgKYuDT0bTcra6UnSiwOQ3sq80K6G26twKoakGwMy+kWeJdQpch/0ApqTUM+xCS6xWdEIfrOsTCL8Rtdey9tMg21KWTVpCCBGO1egeItuSxc75AcviasdQyUeW2GZkEhAUnYgSIhYF+idYYvl7PSdO2FlWaHmNZNgxRVJEQaLIzxTCznY7I4QXPWGXbImdT6hOyBHJAUwBKRzLvOiEHVfY1ZsCUzSplOPDPRhG3cpxBBRZZJD3mpECCjtdsRV+kYTfkGzbIIVdcNytKOy4TS5UdaUQBnVd+ZJssesr5GTY+ZYby7Cj8z0vHPV+ijuqcnKZxiKWrX7rUoYldrbBM+w4YZcxfo8QdsltlIiGilzYqMEJSBY3R2HnDbFtEiyxjhe5n0/MBedgrBK/FipKYZdiic2tEptgiW3Oxwm/vsuwY1Wa/3/2/jxcuuS8CwR/EXFOZt7l22pXVUmyFtuSV4xsGWOwWWzAuKGBpofVTcPAGKZ76GkGeDD9TAM2vU13AwPNtBnAZunBgDcwBgNtxoBtFluybEm2ZGsv1V5fVX3LXTLzLDF/RLxvvBEn4uTJe2+pbl7N+zz11HfvzeUscWL5xW/RKvodgCEIu0ESCwDXKTunkECbStgJsGtQZ8diApil3FsCZF2GYccpscodr1TNFKuK+9/0swDAeLCcN8f8uF2S5cvjHBsn0goMO0cIAIBTIYl9+k5gnD5zZ5nvn89ZF8qwU6OS2DxLbqwsdVoFwM76n8fYaeyd1yaSUP+zfC8xzMyYhx37JBlUHrBTJYCPGR9VkOam4Q/EsBsB7Cwz7MY97KhMPWTYDb6X/RgkYEmS2B1mBGyqVGJlJjLsegGIZCWxHpghDztv8tlSgt5ZgCiatKbGnGcF27Ipsa8Vw67gS5ebmEo/nl1OVMyVkGBVWmNe6SEY1wWgCQAePJyJ0IktAbsIKNjA/B0F7Hz/aBWMl8RWRhy7BIQ4dKKG0RrdhCS6yeUnise9ayNvvLUfdrfT42Z/UYMHDuabQydSVsP/n2GXrxyDXk5CSj5bW3vYXYC8thRWkBgxbwVoyvPXG66vnKRNZIld6lJhgZ962IXQCeWkJSUAKQU8+zaW4ojX98R805uvXddb1DRZpwWbCYD1f/dbvhjveOwa/sQ3vEMcS/CwayNgsGM5LEDBEQlQTaETGN57uRCspSSWNgGQT9HrhMw4sJnGPOz8z8pM9vnL1muwmLjQSvtgP48g6aCUYsmqciEJSdHfZj0BdoeBYRcBdj3uIZ573bP7WCvf1mw3vskwojgiOeQBlq5dcHs5GL5W0xy+0KdlALv5QBI73cOujVifQyAzmtMlC2kOndhphl2BiMFrJjNg2NW+Tzi1AeAgRVQELmdYYTVaZryF7yKGHQF2hk30160MncjcR/m71DbE14mXxC443baGtUBX3GiX8lNSz2QksZHCo8G9U/f51/eGz0KJYdcIhqesQUpsVhLbBC/RRBLb7AjDTgYyhX5phGGXrl0zkthDsuIcSGLzDDsKUYklscLDjqwjRLq5BMhyzDVOiVXEsJsA2GXskvreRv07zwG8zQAFUaUeiPyRBT/ZTbUS57yXkcQ+dycc48dfOtp+s3lCXchozSEFIwMUM+zOkM62tDNAgYMS+DMpsGEE7OoL6bT0XgmUUeiEQe86uZy+mqWPFarZDDiJd3Nzx98Iv7t0l4z87+wow27DwlMcl1tg+x1hpfjapAw724bBh0r7Tm80dGPXqyTd3Miwkx52OUksgQWu07q1LyZICmebVOcSVYELSom9aElsyrArMBdz5zQA7DYkB+1SsfTeBePUMpSBJbHuGq0Ew67JSU9HvycD2BWl+iQj24NrnLY4OW2hedI+MzrLnqMNC6VN7GF3gaETRx6we/LWHjpo9FZBK5sH7GBwY68O17AUZnLVPexKY9i2NSaJlX8fvP4iJLHbsvU2mPUzYLdF3ymlDaZ2xzmJYXeB0vDXq8RkPZXE0kYtyVgrwVaLKtrxvwsZYOFCJ8K9aIn5Vm2e83TWsncUjzfi/v+Od78Jv+Pdb4rfxH5GHhisJGDnFjNa+cVhArwoP05VmQ3NJgLsVHazrdIKK6DoYVdJdtgmDzvtAbtutfXc4p//7PP4gvY+ngQuL2DXpICd66uZ5VCUxI4bnwNAz5LYwBqqMwvjtrO4a2MA7S4OAssccP1Iuu6Zkg7oEw2vqxP3PFHaqgfyoiIPxXQ8l3NSKpJte8aX8nMLAmKaXswrCuODfDZnOcZixGpvHaM2AUpzIYC7UnfWwE0A73/qJbx11eJwHgMWfcbDrvY+Wqe94TG4HwudMDNee8zQDHzc6LtOM5LYdSSJzQWGpUzMdcQOt9bixAOEcy+JJTVCq+eudUt/OiCAc/VefjNeWrIIMDEw7MqA3brr0fcWWsfPoASDgAzDjuexcehE5CUKiE3z3QqdqLW758umj487HRPTNRZvTgaGHXm6DiWxeYYdjasN6uxYROE/kSRWAmGZ60wy2X24vvxkG4adwG9ilqRFRXhFwrCrSww78fsxr9O0WGpdaW6bxxKwuxuemZfur4D5ZWXY2c2S2I5YYlsw7JgW7G9s+t4QnDAC2Pkd4oGHm6A3Uyk58G1gp3TQqPwkUZVeKw2OkQfOepb1jtzUTbv64rvcAjs8OCwJThYNufPXfmJgPhslsZsSSuX7pOda8ncCCW5ySuw5Fm2pxxbVmSWxtAB5LVNiU4ZdSRIrZEqyQ9vlRMVckSQWBpVRmEWhE7EklmQWt/ZnZw+d2MbDrhLeHwW/lh6aFzMyxEe+njZslKlRGelhd3GS2HudO87Hby4AKDFhHoLma1S4tqjyr+HXdmGiQ8/X5/xy4Jf/34C3/srzH/frVa+FvDzHxrlIwK4UYGGtACi2lNdOkcRO9cuUjMFNzC/Jyir56e1SCRAuCp2QPmxQSVBCQSLNDLsuSqKUAJ+lMIgJ7MSut+wdRWDaxrlS5GHXR+dHi+ZZpV0AmPSthZTEDj+7E0CFUnmJY1hwxj5pgGczSdCjmLgrnq2x4JdC/fSn7+D/9Lffiz/6994bPucyVoFht8owO2RNCZ0IDLvgYcfJgWIx2PQ97mPfpRn6umOv8cYagHGG3RizYnETAHAdxwnD7nDwUvKwSwkLkeqDqk4ZdoLRBWBtBZBm8+CFfDapTa5HJXnh5/YKSGJ//kX37K5WS7zvqVfDH3jNJBh2vo8gmfxJLzzscgw7KR31fdxcTZDE1tLDzpbnbfI7qJI5+KrteeibM8OOADs/L08BO9mfVZm1Q0RoCFYQ9049YLdXlsTSMVGt24KH3SAllhh284ggEICV2Gt1VzzsJOidTTRNx8TB8xjWedR3Hc7c/4dsxnxIDLWLBgUPu3ZoTaC1AmF2OUlsy1YEXhJrpwB2w9CJiM0uyUUesKMQilLwjTzOsY2dtGSCPKWUS0nsC/eW0WvttvPgCXUhvSpJKNUIw85S6MSYD1tSigE76pxSWetmOWmn8oNdz4k/QhJaTwDsSBJrDWazDSENPenAgyQ2PQ4rBoFS2SlsKJFSKhFkOr8Bwy7jYVdRSi56DHxorkqlC8Ac+JarTf5vXWgXgEiJPQ94kfN7o2NIv39KZYMzXiuGXSF0IvUNA9wurx7ZMdzlYoadcrKnKpO06u8BLQQcYLetJFYEimz0sNvAFgWiSQ5N2uNj9+3ZWtH/Vwmod3GhE3db1+Yfue4mlNlACWFBcG1eBdAz9+zJSSy1xbf/auBX/9fA5/2a8x/361URkHbRcvepktizAnbpglS0n2097Aa70MTEkqbYE9unPJ9NbPcIULkCklgxWaeFkklAtg7aTdDVkH0b/UybOLaLpKCyrwH8ImKCh10rATtasG28P2EDpeliYIwYAMzMSBhM9B012kEKXpqgy+OeGOcIxJCLmTiRUzBMSuxMmpcpPekapfWJ2w4YYlbCzgB2rr9ebvCwq3IL3KSoHc86KYn1YIi8N52FhcbKBJbdS/YGWiuuWRawm3BtFzcAADfUsWMWMcNuCNgFAChl2NHCPCOJ9QwZ5cdEWkOse7HkK7QbyfDJMhYHkjwJ2OXljLtU92g/Ez1eOR5uCPYwLg0WYOYPsXpO+2CFYDsf7JBLia3mPD4YdMWUWK8odZJY8rBrN4VOjAM6lBALhLAMAiAbJeSuckNLSmJNZm6fZdg1kxh2ACI7grKHXSLPznnYtWvBsIvtWzro3WDYZUJfIqCxNLehEkA+Kb4OKnfN0vPv+jw4Su1iVQLsOHQiDQYZ9qOAY3VSv7Lw3qHHUwC7zFpXXosKoq17djIFUY1tGpSOc6wCYGeyktg7J/I+WCiaI41ZI2xZFwPYkYddNSKJneLDNngT+QK4G6uS9xLYNcZOI0AqBQpzQFkVSfPGF7stKlQ+JVYXwb3AUmGZWNKZBuBwgiR2bGLG4KCJkGWWxBYYdpEkVgKWV5FlZ22GYTdREttvADno+vsO8nBeQSsIP69zSGJnKWB3RnAr2t17rRh2BNgJhh0N/NZePAh52UsY3hqtPcMuaRPEsPOTplsHtWDhTZXECvnWRg+7TKLsYNAPx039ySwXmCF26ZWpYLRG/xqETtxp3XE+eDBDbVQA46JJY1j4H8yrsLDKtSm5g5xJ5tvZmjKGbVs5AE4pgJgnRWP8c3rYyfYzGfzb4KMmNwqm9jVZEG4CGH4ej7HLUlIS20mQTQJ2JmbYpcydjIddCFvQ/Hf225UediNtuO8talVi2BXmL6Jf6yJWYDtcKKaSWJawtQNAqOtSwE6wP3wNJF2I/YqiUApxXNZa/Jd/76fxh7/rfbByw/EM7YuGYgbsRnynX9c6J8Mux/Cg4kUqSWJnB+y51kaSWPfvU3Odf/cSbqK1GN8Um7JhwQy7E8+wu++PJcOwK0licww7BuxiSaw1XhKLCYCdYN3MmNVVkMQmPzcCgN7VurvyGxPo8PKRnOPTetMMQicIJDjtjBiDxiSxYR1RoYtTYvsegLuOwcNOx/diakosMLhfBDLMK82JmjSfaowAUSQw225i2GXmlH2Du8ywG2IDldHc50nmF/fDyTM+7mEX1nHh/RmG3RYSyNerZHBL1pMzfW4HktgwbtE6Ikhi4/NvBMNbFvnCrYUnoxxTKShkL9k4qTL9KBD3x7VnNp/YGTZWRqkVBTxJhp1fUxr00OhHfTS/XP8CnlQvRvYUm0pKYkPoRPj+IwGEV/K4LtDD7kIZdnpkgOo1DTrTFxEEhLE5YTI4EmtsDOzqfdjFgNlGoRMlwKowmFl++DXqmQfsSgw7lsNpnlDa5BzoekwJnSh65Ynj7WCih4+uTTrY88/ie6PQkF2W8ZRKLiRYujkxdIJlYRLskpJYL8fzAN3ezGBeGeH5dR5JbAnc2vIecUf+WkpiE6kxEI6zW4d7cFEy38teLMFyz+WsEpJYvi7kf0jszFkAxrZl2JnZBA+7DWxRIGHYZSSx9Bmin9SmQmVUACQLkputyj8DrzTunG7s1dirh5IUdyxBEns4r5ilmN0kIsDOzPFDP/sC/vsf+vBQlrKLNcXWYdsqSbymGONPqU2fI1+zqUwBsGEPO9GXbp3AXG3upyQb8QwMqEtXMnRCLsbFOQXwq3C+aWpd3wUWgQD/COh3YRCbwahWhk4MPOzG708InQh+m5Gvnjxumn/5DdqZagaAUBSiAQj2R7B+yIFJkpkXZJlxeu1L91f4/vc9gx/4mWeDBzJ52IlzmlLEArj0DDulnYk4gVHkYSdYDrnKyY7TYsCOGXYHzLjoLZg9SYv7VRV85V6yNxxDb1Ky9ci13bsJALiujt0xE0CZ8bBTugDYjXjYzdFAo+c1g/WARiMZdoU+rIlCJ3IplQnDTgAGzJzdZYYdPbro8fKx9OvzczlVDUInjPfhPOoDkE73ay8riZ3z6yr00cJfkiVOBMOOAKh1J9tfMrexdtj3JYAdBVwczCv+W6sShh0Qb2pKSWyWYUdtsYrmnxw6kUmJBYCFB+Xk3Csw5OI2NEyJFdYu4jupj0g97Fq7Gx520l4hSgammiiJ7ZXhufi+vzyD0ImChJ1CVNZFhl2e6ZwLVgKATrA1yYrg2M5dWNVYZdbnkV+sZNiJwJ4ZmjLD7tn34e/o/xp/d/Zn0Wyh+IxDJ9w1ORaS2PvL8G8DiTVcVknsCMPO6u0BAqIULr0kVqWg2wSwixl2BSmqFf53dSUubAFgaRuSXRnUJIktMuzCRLS0S2Zz/kBJadrhHZuYMfNPRw3VbpLiikUYefK5P+zwIqNUuQXg1gy7Kg9yJLKeRW2wqPX5/LzWJQ+784ZOvBaS2GSRLhYqPMGTUfGfNQy7QMenHesmZan5AXeNGjOjcTg3LK0+F6iwiWGnC205Om7D/UlWEisBO+0ksRfLsCNJrDunG3s19mdVuD6ZXd7WmsTDLnMN/QTU1nv4o9/9M/j2f/UxfOsP/tz5j/f1Lm3AzLeLfrZTaj8zqkZ8tqbURQJ2RXmt/1l6Z05Nio087DaAJDkm9i6PpYI1Fy3GxT3vyQ9uk++aHxNs34Lm80YAdqQGaHo7yYvRedh56R+nxG4Y14SHXSyJ7dkbh8GGPgZEtEh17JKFRtcnC58Rhl0abEB/ixIBRTt7+k5YOHetGGfPAth5xou57IDd1/8Z4E8+DXzdn3I/U0psQYpFNYVhx5LPLjDsJMBEgBWByvdnj/DfXrI3Yg+xM3vYeUksjh0ATpLYUYZd3mc2uoe+f9PK4hCSRe7a4TKSxA6fq663gYVppG/aGMNuuJhOGTu7VHeXGxh2GIZOEGB30uoBCztqq5wSWwvAro0lseJ5Zkms8LBbt31of7ZDZF8k+wLebInbDUli92rDc6bGA3atFT6tEpglwK6SDLuCJFamxJIkNsOwc+flnpHYwy4viaVndMCwM/NIdVRiSncwTk58yYuTlo2KbRKoBvOkdLwlXKTi9ScBdqXQiVTCTuPqyhZCJwr9cLTpJCpm2Lm2dIr55pTWzPo8lsT6c1cmWnPO0JRl+T/1twAAT6rbqJ/+d+PfL0puFu1nJLH3l+E5ixl2lw6wcwenRwA73nVop08uCAg8Jepk6mHHstbyBSl555EUtRcX0xjDmu/SQrlvg0/SRoYd+aVYI0C3kjR35KYW3pscGIAhw64vMOzo2KwMnZD3b5cXGaXKLQAZwZ+YElvyf0tYUotaY14ZwTY6C8OulBJ7VkmsXEy+1qETklrvry2djwSVqK4sYCekpX7HrEvBuI4AuwrzWmNRGRE6MRF0kezJjR52UySxgkns+5Naq6HEWzxTqqphLtzDzi2qKFHq2qLG3qzAsEslsRhhdXuJR2cWnPT0nk++cv7jvQw1lrp6lioBcJuAtrMERUggpD/DpGdT8IGZhYXMtpLYSOZaaNtyA+5KSGIDQB+xyCJJrB6wwqJKJLHSi6syml/fsyS2j+934fo5wI6kncOU2GyJDZRIeioYdsHDLm7HxLCbox1IaQbpmBMZdtJDKPq7OI9PvxI2uroo1CT2aJpSZAJfEQNgJCjuUlQiiZrOsJsgiRUMu1xyIH3G3b2QNPxR+4R7vxkZY7fwsOOUWAqdyHjYqRLwn9tIEe3tuhKyYv/sucsXSwVlyQV9ZVR+AT7CsBuwVHew7qw8+I4Ot7OAnR4w7LQH7I77Yb9PbBz5u1gS28cpsaJvJYB1ZlJJrPzM4ToEAFAfDH+HIOPbnwXAjmylmr4PBAHJsJPe08IvbnAM0fyzC6ETGQ87IEjb5fmvC21owJ6VmyIihENKF93vwlx2Fxh2LInVSdAIVQm4T35uBcPuoHLnvU7OvyRhp+CGtc1vDNHGSdoP5zalgLg/rny/e4L56MaKe3E5dGJmNGrlcQy5lgEwQ1dOqn7xw+F1L/z0+PeLonY1rzUDdqcRYOeuT6VV2BADLiNg5yWxkqGVVH8GU3lirq2UG4QGYFcmOGH4vd6wdSDT8Aw76WEXLTbzk6C2DQ//rN4UOhE6eM27ZMlklo5j5KaqKQw7YaYsOzoG7FIPu24oJ67N5knyTlcE2PnzZgR/Q7vsN4Bd4vpr5QfY6pwMu02S2G0Sl4FYCnnRIQ8kf6R2rJQY2IlhJ3bp0rqyklh3XXrrPOyc/1oiK+0C/XyvNljMzJklsQ1M2EXPgQp9HxbUo5JYd9ydFQw7k2PYhe8wpkJthF/nBXrYnWKOa/MKRivs1SbvYScksQdCEjvmYbdCGLM+cft4J1LENtYE/6+tqgjYFdrZlAVr9Dli/JYyagZ+VPiuqZ81BiKOJezlKvKw24JhdyVSYsP5dkUPuzR0Ip3jxJJYORepTQidIGauC53YbM/RjUpiS/en52NuZEqs8LArMuyqCQw7BuxorBOAXSYQgb7TiJTYJpIXd3j61bBw7mn+qPUZJbFewgfxOZe5kgWbTOrLvjxl4WSK71WBYUegE92b29c+n//2Mfu492s8pyRWeNjV2gqG3cHgpbTZbwdrmIyHnZnxnP4GPGCnNIx/TZuAwWlFTBgdEuIbyeIa8bC7CpLY+/TYo48CGuh6dxh62DFg1xoG02j9GktixT2TDDtpx5HYDQCeYVeJ/jGynMl4yQFxIrooYgXtzysB2Pn20dkhYBd5T+9FfnGD8zKxFcQ9D2LkUmKBIKlcTgidGHrYiU0RIUOmP6eS2A4Gqx0A7HKhE5En3JjXL8D3oofhTeuF8TL/gSQ2z7CjcXVpK+Q87ALTOcZesqm2QBTSZDrXl5/aCQy7aggOU/+8NzNh/DdVtOacoSn7aL76iXC8dz46/v2iSBI7M5qfacmwo7b++M29sCEGXD7AzjDDrgzY2TPs+ms/qWi8YapO38ug0wjDruCdx4NfBFjpjQtlZtjZSqTE5nfbrQTsqvwigTztxnz4JklihU5fIsvMMEyluBlj8KrSQop3FQG7DOpdSjNNq8ss+DL+WS0MFrWBUq6zDQED5/Gwu2BJ7GuSEpuZpNJihb5X+mCkdWUZdgHgZ4Zd2iaEJHZRm5hht6Uk9tt/9Cn8mR/8+eh38fGI301KiQ2hE2OS2N4qGOMANWbhXURwjU+JPbVzllXsz8yGlFjjFnRsw5CTxLpnaykAu6azeOqV4+Frd62mhBRtU7zIKHnYJffZDseW0SqxqbZl6o0dkwQRtwU0twHsMguyC2Gavl4VpaiK3XiSlloXPtJKkGlD6IScixmREkubi20nJbEoXuu2t5gpsQkFTPYYdB52Nj6/dKGYACK6CouB1COtzLALTPNxhp0SYFMsLyaWCiDmrWdkcDIL4LJLYqlShl1hoUg1SJLMFPsGtgKwE3NmYnBQe/j4Y98AfP234S+85dsBKHd/JkliNzPstLI4VEtgddf9fn5j8FLNycfpJkTGw04pnl/dUh4ErBaopBfWSLuR160yKqQpthmGHW0ki7lDI1m4z74P+O7/FPjg9w6+5zIXyVAr1eFkLcej4EccGHYrwFpoD17d7wIjySh3LSLALvP8VqpPALt4MwSIGXaRJBaI26C8pzTPTtoo+W7t1yaAkORh1/XhmaP5ulwbVYs8YSDnoXxWhh0z5FIPuwQMkom7GXyhThh2DUzcji9pybEkm3o9sPvIq+daEXY5U3GfRhUCLuJrTQw7B9hlGHb+HkWBKkA8hmXOCQBMGzbh03CKQWVCJ2js3auNGMf8/acxWhUksc0pcP85/nH+6haAXRMYdgdzd01OM5LYx64vYqmuurjNiwsC7NyNNGPxtWfY9SfmWm+IYZdIYqcw7FR+sCPAKk6J3SznItPfVhlUXkKqkW90nYiTNiQ3LTD9xhY35A1YZPIB/BB30FFDtb6TSz3sgiRWMgwvmB1z2Uqc0zd9x0/im/76vxcL/20YdjnD+7AQoMlkbc6ZmNmECWVUZw2d+IxIYiVgRwN7wrD7rALsgo+l0conrXoQnSWxPiXWOobd3sxs/xz6e/v0/Q4vnvi+Kwf2yesbMS3zjKQOhuVC2dCJyDvTeW6cK2glrXWQxN7wgN1eBNjlJLEVZkZzv5l6nwIAGr/Lh3n06xfvbwDud6EunGGXTIr4ey5KErsJsNsiZUsVNpy2CY5IK/Kw29C2I2DwKkliu5g9w/Mndz1SkCmqgYedYNhpPfisdgtJbNhh9/dUF+ZZVAw06iTZtovS+dyLaBHqX0Medqodhk6k3l0ywdBXTq7Z8OJMC7+imAUld/FVLxYCZ2hfxFAjMGFyMMzrVcmG6krIkrIvn+Bh1w8Ydoe8wQqEBSHLOysDfPUfxrMHXwCAGE5jktgJ/Va9QOc3lK6rY2DpATsfRiFLlySxBf9r64G0m/CAnZklgSbldiOZdJVWIT2Xft+1YUNm7tNzfVuX/ne11sA//ZPAz34/8D2/L7Y6uOR1Ihl2MgxCbGLy/AMW6Na8Nr3fBg846psiNihLYgVghw7Ltg8G/P76WihYv9E78BMsedXSv6Wn15gkNmmrTSckscQSjrynMww7awuAXbvZw44AO8GwWxdk72WG3Tw758kx7HZBEhuSw0OKbtSf8XhKDMr8eNvZii2aSDra2/izWg6YyUtilxmJd99bvkeLhOls5BgmSgZpKGFzs9nDbrguzDHsKJiTXj9Dm5fE3n06+rE+fm74mkLRRs68MgxUEvi9bnsemx65Pn/NNsQuBrADSWJHALszMOwICOx8wxww7PrNctISwy43qE6RxBJg1yvD51ti2JF8tkN47YAlR+cwwhKkhNliuIX4nAZVHDpBDLvSJFpcu8qo7b2zdqmEX+CPfvRl/OhHbuPjr/rrsJWHXTl0ooHhTmyWYyRtUyWA66zglvSZkLKwi5hM5Sap6e5ISeILXA2D9lwJk/PaOIZdk7YJlrNWWMxcWMnWPnDE8LRmXIYtn+sx4JYnp4Z3zbLtWUyGaGLZbXvsYyUGd5JV7NUGjc0AdiyJ9bYA/txUvx62cfrcPh6zXroKgN1nysOuBI5dOGB3BoZdyUftLGEQvQD7Sp+ffo82F38fXo+KPN4Ee0akXwNIGHbjHnbE9tcK0FFKrGDYKVVuX76chx3dVwqdmOZh10LHKbGCYcfphNxmZtHxz5AB7LZi2IVFYycNxgugSgTYWQkIb9/P0sJYw4bPucxVYNiVJLFabU6JHTDs/HykSth5qb8TMXy6jZLYaYu1pnaA1w17H1jec79cZBh2FIaXbtjnGHYAbOUBO2bYzYO0lcEeZNtNK2TvDsRMQiekDJISbUl1JME+o4D7z4bX3p++MH6967h116pCh5PVcDxqZegEAKzu8z+PWs3X16DHotauj6PKeGFXcJshDHIk495crCcA4UOWm7vlguVGJbG0nhWS6VQSS/N32uxiht0qPl76XuGhHFJix0MnlpGHXeJBRx9N4DFdJ7kpQio02wEIrGV3HIFxthOAHbGudSF0gi0m/NiSjnV2yLCrlLi+QhYbPCcTNqOXeJ9mPOykfHkgiS0wnNscYGfP5mFHnzUzGjOVAHaCBZ/10Tx5GQAY56iXL09e/xLDblZpx05FAL9l4MTD1+Yw6jIDdlNCJ6YEJxQ+tyfALhmwgg/byEXhwSkviZVhD1Xkv5Q/Tk6mRQXjB9LIYFBU1wTWW1Vg2HFa7Yj57zSGXWDz1WKAsKVJrx0ChRfOjrlslWFV3l3TLtUI+NWHQaAIcgg2JVGx6/OAF10bPv+iElVzgzlwMeBsbpKayo0/Kxl2AdAy3kSWnzG67lISW7nX0M7YwLemVP6zGkjvtjJgZ6HwTd/5Hjx9LwYNh8cddnYrXQbsWp8mG/ch5wRf+56BtVO74EnffjF0QtgVVMKGABg+f34CcK9zn0O7sVcCsCuxJs9aErCKvicDXll7TsAuIw3ahmG3kfV3BmbSNjLECFC5Sgy7NvZpE/0DgIG8NCpeYLh+nzYPeVffxuMyL/w3eADGgN1s83usDZ6i8Ay7jCSWjyv1COPd+2aw0JDhEe4kRhh2YjFDi3QjFmcudCNcm9MmtB8l5ebnYNgFBsBuMexIilWSxE5i2FmLCm0gAHgFQ5TSC3CiZJjPCYbk2HxlYv9HgN2j9jZ4fkmsNVGGQejCc5WsHayfXz2gPJBU7wVp6yaGXeLjGL0PiM+XAjI8iBfJaZUCjl4Kr33+A4Pvuqx13LhzN+jyDDsr5h8AsLrH/zzqKl5TVuhiOaz4jEgS659FBkKYxEH+daTYScCbHCAnNxm4L4zv84mUxJIlk3+tk8QmgF3qPc0Mu3X8/+R7m2bNaaIlD7scw45A+VkCuIwz7MLn1+icwoKkiNJ7cAcAO8n0pucvZtj5a8Uehfm5Tms1A1PSU01egwGr3Jdhhp0ZAPwSXE374crkN0x6OXcQvtQbAVTuZ8M5SvBvod2/mbQlGHbZpGoP2H3avBEAnPfk8s74MfiiNjqvNPZ9kMwJA3bu+A5mBtfmlQh1uoyAne9wzIiHnfL076w8acPnggG7PEtuTBJrVcmwdTio1lowzAqTIPKw61JJbAalbQWIs4lhN3Zjtd4M2LFUFyZm2PmHrRR2AVPw8NvlRUapqL0gnPOrq2RHPFeyzZYkVYLhSJP22iiROrzl9Yxo6PtYNh3+7A/+HL7rJ546u/8c33MBOgIXwwDx5/fySYu//55PuwGGd8f9tW3HALsLDsG4LCVMzivtdqwHLFYZOjEzZ2NmMmC3gWEnAMQf/chtfOyVdfT+8DrapQup07XJMJBFCm6tlfOwO08ysixqL3AMu8OFu26LUuiESImtjYo3kNJ25SehR537nC943C2UroQkdkyudZaSMh5ZOaaG9C+b7GGnkU0uPBPDboMs8yzMJH5vvRkkiYDBC2Savl4l/IiYcWQ092tk+dBFQQnuGjz18onzZmKGnRtziGFXJUw2y4Cd2BwDiu04Hzox8h5xH1qSRwlWYMMSyGTT1gwXA2dj2A0XXxIEzYMqXcKwIynr2UIniCXANi6XHrAjed40hp2RoFqh2s5iH6KfnzngKTVMp0UnbYAbCaiOMTkn9lvr2jHUHuledL+oFkC9GLyuvHZI2if92m/wPqw8kFQfxNLWMQ87ZvckICUz7MRz5a8btfUIsGvusv8sAODOU4PvuozVdj1O/alW6BMPu8DO7WCC3Y1nR/bWzY9ojpQH7GQ4QwLYkY8d2RWlDDvpYUefASSSWPKpror9J/UnezMTSAz+u6LQiZKVjUk24uXcSofQiXvHSz7uG0VJrHvtqh0CSqnsfZgSK0InBAGhQhszxiSANeJteVmqY5lq2MTJetiVGHZiTs4MO0EqkiBZK75LFjHscpJYaqe1UQPZacQSFxWNj6yaWWxm2GUlsYGVvmeo/cabanPV5INvPGD3snkI96wnwhy9OH4MvoIkVmN/HktiCbC7tqixN6vC9U7nzOes8wN2NkyazBjDrjTojBRJYqmjSKWndsLAaAu7DOkkEfAMOw+wEACWFvnmdaqKzzczKafPsDBQ/sYNB93NO53Gp9GaFLCMPiaw+aKHiFNik/fStSx6+O2wjKdUoiOjeoXmbd3IQn1g1F8OnehsYCTNKnN2hh1HqiugmuN//uc/j7/2Y5/At3zfB9CwL+N5QicKKVNnLd+uf+ADL+GPf8/78d/9kw8NqfOTGHZXrN0JSazRzienS0Hcjhh2FeaVMxemNqr6dhplW4SehOCYsr8OsfCKHo6CQVNxe9bDY08YdrW5QIbdOoDWp5jh0Bu9ziqNdQ6UFCmxtdFsJZA9P98W77WuD/+8R93i4/bRFQDsLprZVZJ45RJZ5b/PFBZxXsBuE8MuluxMKjlGl5JQB6+txmVzu1IqPMsRw45YcQVJ7AefuYuv+R9/BL/vb/xkAHH9Qs/aLnyO/2wAcegEsBHwbPs+Ezox0vbF/LGnZFvRXtpUEtuJNgOMSmK7dOEzwrBrxHtbweorgSoSsNOQ7essDDt/7TGc/13KquI5xKrgb8Uvn8Cw63qLfZDMr+bvSOVnDOAyw1wsns+bEgtgXXmGXfe8+4VPjk0r+F8XNt0Thl1v3PzqQQLsZvuTGXZtwrCrBww7wepLmFaRJPb4+fiD7z2TPbfLVsu25zWQgQPxVwnzrfFzoJ5CrbwkdoUagOK/V+iwSEz5I6KIvw/kL8bBC4m/+EwodgBxL3Jz5iitNb8JTv3JwdyI++kBu1542BFpgENGfF9WJeuf1GbFf9a9E/e+R67PA9stqYUH5QgE6oU0eMCwSxOgaV0hvZjhGHZ1xjewRcWs2ctcMggix8re7GFHm+1hPa/6dgj4is9N5aOENZyMAHY5lnOVgqq+OhlGw6qZ2Zk87CQrfaHd5zLOU0mGXVkSe6Rv4CXr7QcmAnYcOlFp5/8IIYlduet1bVFhfybDMC4bYCcaCwFLuVJnkcT6k9a+oxh4xXUkJx2TxBJQNsHDTgBWbQGwYyBPGZbERp8nX8vgXjAiVQMfigkMuwmS2K6VDK+cJDb/UEcedjnJ21UqAS5Q3V7SBHsEtIoYdnV+siaAkBnviJ0DvKDdyXofUArv+dSr/Kdn7/t7d2ZJ7AxF09qzlm9PH3/FDdJ/7cc+MeJh5waaf/KB5/D/+KcfxstHq88CSawDs5RSIjHbtwmSxFqXEjszwucOmAb2Ch+8qQw7er18f/o6YqsBrn8YyG0jYE/BaCkDP+fkyD8DjZrDQjNgN690/riTlNhYEptci4Rh96YH3G7b0fIK9HubjPe3rWRSH74nI9V63QG7Cb56FyKJ3QDYnZEBdemKPIBF6IQRvnMdh05IeWmP/+3ffQoA8G8+9vKAYQdm2MXgJ81VmAGwAfDsrQydSCWxI8wnkJ9RfMwDSWzqEeb/X6t2sNBoxSLC/SLDsMsk6DHzQC7OEiBRJtFpAj/PyOAkwGtnGHaiDbRdz9drUQidyAV7pNVZiwPl5ySzYDdSJ+yQVB4aJdCOSmKnyY1XFTHsvNdbxr8OAIf5DdcO+X659/Orh5hhtx+kahs87FKJXCoTjm1VYqZV5FNFnnxU957FLtTpukNniSHnzvlkFQN2ZFfCrB4viSWZbDOVYcf9ifuewLCLySTEsKtTD7scINeJDYxCujBLYmcVHw9ZIzWdUMY0CcOu2sCw07XzHvXt8b4H7B67PmSNUqUMOynXHHrYxQzYnIcd4MI+IrBv5zzsxCZOLnWV7ucmDzsbh9cNJNUY9nFUZBdwIlKPA2BXtiWIgpOic8pLYjcz7IZtPIRfacw9YBcYdsHDboxhd2xu4GVcj363qeRm0X5NALcL4CCG3eHCqaTMawTYnf/TBBA2mhJLwQkjLLGorIXxHab2g+oAsMuw5AYfo/OSWGtzgFUA7PoCYEdMtV5XqCOGXQawI4ad0oJhF58DA4kjgzstPM0IYEfH21kdI8uFBYbKLIaY/aOGr78SJSjtVMHDboxhJxehwkw82tkKQMhM7E6eWR5Ig+RsH23X40PPhQnQM/c6vDn9/inF0jY/sJqZO+8LZNh1EmgqetjtY932+C/+7vvQdBYv3l/hf7qykljJsPNtQRrk9n0kZ51XzqRYpUb8m6jVXQCMRz3skmegGDJD99Ma7k8ce67sYVfrC/aw8wP7SrsJ3wEDdoXQCeHjVxuNee3YhrXqhu3Ky21PMYdWwBO33GT0aHXOY74MpUfu/1lKstOi7xkB2eTfp1TOe+wiPew6Mc5uC2huA/Zlpbc73KbIUkOcg/Sws8ywi+Wl0vvJ9p3bGiKGnX9vYNjFgB1P4jdc67azmLH0ZIokNnxOn4ZO5CSxAw+7sBgoedjx3CvDsKsybAlmOGgdy4nERuuxkOVtYth9+Pl7+MGfeQ5/8Fe8jTc4ZK3Zw+618di58BKyPimbKzPsMp5PSXW9xSFJYknWiaH/UpswfWrJ8LkASezJ7EEAwONrB27nEmIBwNR+w77UpyXrrs4kHnazAz4HJwMfk8TGMuBB6IScQybXIFqUU+ot1d3dYNidrjueG9Gi+3jd4tbBjM+T2P29mQEtmGHHgJ1n2BnVMxOHKzOW1CyJ9dc48fSkti7vobWWSTA5lYGTxM7i3/liSWwdGHa0To5SYmmDPVXGlBh2nNQdA3aPjgF2Hngn9tLYMz7qYUdAYd+iQhd7spH6aUc87FiW7jfA5e8AhPu9wcOusbHF16ya4XjdxQy7RAJPpf29PekNrDae2mGBvmdfwtymCfUXpfExlsRu42EnJLEiqGmhiJ1PDDs3RtdFhp0jvpxU13HXOu/SqR52Ib1Yc0os4ABwKYl1DLvXZkPs/KO1mGCPMeyYJTZ18io/d5YPneBJ40hgA3m0qWTxojKLgUqwQ0qAHUlie2WCGaw4lui1Iv2MGYYDHz46jvI5kDegIa+8DL24awO7ROrR2cNuAsPQaIXVZwPDzoYH+X5DE+wJDDvaQRoxe20poRLn9AQUg+Rzd5eR0eerLOM9R+gEcMGAXdjForLV3HX03VAS+wsv3OcF0kdeuA88drUlsb33sAMAaMn8aoQktuZJipKT8L4BUJ70hNcAjZ3GsCPZLLfPAcMu3E8pjxlI5gmQtO51jqV8QR52fmBfKXfu1xY5ht1QDtLAoK60T+St3IS4IIk9xQw392fssXI1ALuLlsQOxwoAeXmo/Pd5vefOxbBLJoKRVPVs/pBbh05cheRrf769mD9VRkf9GjAEmY5EahpfE2YEkAdODOyfxcNuhlQSO3LNEw+7WBIbQifqRKrLwISfh9XoNnvYSTa7L5MBk1ohFYpCDcTzEBh2YRMbash8AIBf9xd+FIADGf7Ub/jCwSWgBXH0OZe5xOZovJgfZ9iNAXZt3wcPOx84AQRAYN26966ZfaKjz3bg9MgGY2mDI6nj2UMAgIdaLx89fDT7usq3O1UgLAwYdp4J9QA8aDY7CMyXhL2ZVsqwi9okkKg04o3rIO9WIYjBzNx7dkQSe9p0PH9yyZo2SNKT9UMqiW28X/ra/71GO2QhZcYSSvA83cCwI8DOWte+q9wm98j9oYoksb5PJEJJ1sMu9Z4eMOySPtif19HpZsBu4ee7FLghwaRBcmnKnqV1BW2K6NoxyVQXs/PE2my9A5LYwNbW2U2eqR52rTWRhQ2Nt+tJDDvXjtao0VgDHsX6ln1EF5lNE7Z9SIA43tBSClg75cyJPauHXbg+C9MDrQDsZOhEjmHn+6WVOU9d1zMAAQAASURBVMA9+L7/9M74MdBbfRud+bVFbRSazvUPlBJLktjXimF3AZLY0FjqMcBuW0ms+FwzzzPsciyx4Rf7TqsE9omU1NooZqeUJLEc3qAMqpk4XzvsCCyDexqKgiMKTDc1wqCJgNCSPEQwvKIYcTq/dAHjj1cyeaIF+VUDToAsqDSNYZfuIOUkscFDTAJ2Z/ewI/noPl64t4z+dH7ALvH7GQMrp5ZgZFFxkhYz7Pw5VXv4uWcDY/CjLx4FmegVZdi11vBgFoFx3Zrb0Ro1TzQ2bQYMSshBmxRUi14X2ikArImpVgD0uyh0opwSS6y2Siv0Zw1aScsP7KcesDuYSQ+7IcOONiVa62TFs2qEbegBu6Wd4dZ+jcO5B+yugiT2ooGi0jg7yrBTgb00pT5THnbCY2dSn9y7RRt/9iawT4KbV0ESyx644Vo5hp2XokhJrGDY3TkN/QnP05jx4X5mcCthlARJ7Ph96iJJbMzuyLOLw+d00A68UOF+BmYDMezS8VKkxNoUsEsWPukiFokHGh1HxKaQssWhh50RSX+b2td7hYWGLFp07KIkdinSI6M5rqhJKbE9sM+S2ADYhdCJPvo/J6bKzx7z3J3Ybx15wI7r2mPZ1xm2xEktgfIMu9a49dIDkJJYAtY3MOyKHnZJ6ISukQLqEdhHDLtH3un+f+/ZaV68r3OdNl20PjDoA2Du+w9i0FkCrjwIwIBdr/m9xZTY0dAJv270x0EstLoKbX7d9XlZtmwTZjhHAoIkdk9KYqOUWJLEpimx5GFH3oWJJDYB7I4ZsAu2AGmlDDsCk2aVHvjelRl28WaNC53IA3Y7IYkVoQpZiX+Sul4G7OKQOFpbNBmGd5oSq4hEYGusbRzgQeBqThI7APjpe/zPc93yeH+K+WYPu2rYz0oW8Mz7P3apz6xqBqxBAIENqw9C6MTklNjYP5WebQfYuXtwfVFhr67Yl3LTps22daGAXTUSOkGyzjEftvhzww2q5m5QNShMwkcmHQRIDdJpMx5uSinBsMsDB5YoxKpCbSr01Jgzg58VbDzl/e4GPhS+8Y758MXhFiXAztN+0x3TwgKDjyNiGIbzH6TqXoVKPCgA4M56CsMu2THNySFEqiZ72FWCbbTt9VwHwO65uzFg9zLFWG0DbvWdMP+OFyAXmRIrAz1OewLsyAuDzGv38NQrIVDgeN3htC8wvXa9hCSWF3MRYNfwxIMksUBgJMvPGC2WxFZ8D2zufUnwyiZJbCtCJ2JJbDy5pBRcE/lgnpdhF0A1QEpi8x52lhl2FWZGl73uxGefwrHrSD527yoAdtuGKmyqTYCdXEieBWSTr3/NALsMS27KppT8HCMAu8wGHawNvz9jKMClK2Loiw1MIySxvWTFCcYl+T4pCTJVSehEkhJL3zWQxBbuU9tbzLwkhheRY20/YgWq2M/LBqnQAHRLJLFz1aJLFn4DD7scwy41TUdsoB2llIp5GzFvBoDdiCwzZ/LeCUP3ihcUlxywy0hiS+w6IGHBFartexxQ6ISQxA487NpYEksMyabbJImddm2PqgfiXxw+kn1dVQsLjeh78ky+rjqIXzc7EGmvMXszrVQiV+lkkR+FGsRjaxRKQ4DdQ5/vX7Oa7BX1etbJuo1sXSp0AUijjVUG7GKGXatm0d9rdJF0DkA8pvm2bQaAHW2GxJJYCUI1rWBKdpkxU4ZOJG2UAMj9jCS27a3zzQaGgB39nsPkSBKbKHf8cZ0s3bz2sRtjHnY+dMKDQJwCbYbPeLShAQxtBwQAGjPspIfd5QeNOY295GFHzy2FgKTPsQ3AsrSnyYZOJBJ4KtURw65iAJo+h9ReAzAaob9Igbje/3yowzz8FLOzMewEm32u6FmZyLBbHwEAmuoAd7dm2Pnxx4PMtB5xklhi2NWXnGHHnZgZoLSyiFUyGbATnVA9d0iymUgJl0VA2DCdNQ/2EeDVF/x/+o4ANoO6Gvdr6gW1WZv8Lhkz7MYAuykMO/bLi8/HFhYNJAmW31sJs/sSw3Cni+WAQhLbJrvpueIBKe4UcjtbLQx3jDLtc3tJbADsnveA3a1914ZeXSaTpykVBWf487jIFMMcYEfsrUHoxD6efvVEvhun3RVldkaSWD/xr+oA9HdBEruyQRI7q0yQbm/BsGtQoS2BcOKzSBK7KXSig+HBXPYP/NmSiUcMO4SF+7mKfOY8YMeS2NpkgUbbhmtQV4olsdnz85+9wgzXFjV/9tHqCrS/bRhkU0ouAqLvyWwGXShgdwZQQWWOKT2ubRiI8jWbQDh5vWXoxC73aSSJTRl2tNEIYthJ8Ktn37VKgky8QeQlsTruJ0LoRCqJzd+nrsuEToxKYmk+JoExAp17tF1eqhvG/dD+uybuTyKwwr1g8J5xhp2OEwFF2MeaZayyfZnBcy4XP9m1ilio6Z3xsPP31fZYrd01n2cWilSDJMlMdb0NDDsCIcR7OSU2Sf6NGD6TJLHj1/buLGHUHeYZdkSE0APCArWx+Hua+jB+Xb0fy+FGJbExaD2rEpAkCp2ga9AO30uS2IOHgQMPRO6ALHZeaXzuYzf5Z4MeS3puaO5EAAa1TR+w0TLDzvj3ZkIn5CZAyrBLvoeAQwK1Kq3YDanMsBMBEDmvbYD9RfelJJZSYrs+AEEsiU1TYhOGXTo/SAC7R66NSGL99UkZdvOMP9rAn7JNJLEU4oEultMK9c8uMOy6TEpsk5XEjnvYra0KawEhiY1DJ0oMOymJTQE7D6pm7pExSX/hi8a8fRWvU6Z72AmGnUi2nWs/9iUednM0kTUYF8nXq8Mze9jR+p7A+JN1x1Y61+bVa+phdwEMOwIqqkE0sCwzITgh/ly/g2sVZgTYIQXsCDwrM/tYfpZ8LzHMVHJB+42hE/5zVOU978qLapLPSg+7FLCkn/WIJLYSSWOlySsx7PoEsFObGHbie2uRalpiGO50iZ0HqhXJNqdIYqmdjaTEtjakatZGB4no1pLY4BtBktgvfNyliDFgtw2DRg7qqST2IhggnlkiE3j52lJbEuf09Kun0dtPugnA6S6W2N2jwddJ7wWQJCSxNAjOKiGnnsQECv5to0CfMOB1r5/OsMsC0OL8au9hd+aglbQ8I/N4S4YdgeZzoxmYHFwLYtjZOa4tKmbYLZt+JyZ1o/WZ8rC7KFYcIPqijB/emRh2+bnC1h522wB2sr1PSZTdhUpCJ4x2Sdd0TjHDLox1JOPUGYYdvZfZaJys6z+rSya7JQ87azEbpMTGIEJUDAyKxakKc4HWv6cuMezkPCyZL7SCFeF+sYqPC9JfbchwMFrxxogM8OhFvxwz7IZt8eXjcEw5vIrksIAAUi+7h5149lcrd35jDLscKJpW11vBsBOS2IQdwp6GBJhIuVcBDAEwuQ98ZfY4b0YBAG69Ofu6us5v9g+UH76a+lr8upmUxIpjz0pik5RYTUBfMueUHmk0p5DPADHsFteB64+7f+9A8MS73vwA/sH/5Wv554hhJ4AQ90eSxCYMOw/oVeiGskG5CeDbx5Bhl0hifftTSsWgS04h05XvD9WxBxcO5xVSu5+mkwy7k/j/nBJbYthRH+zO+XQLht0q8bCbZbAE7lpzoRMAn2+FLsYixLxwl0InjFb5EB1qQxs97HSk8CLWobwGAysH/oMnEaDCupPgZzeaElvLTSdRdPyHvt89UXvD88pVxiqJ+mUjJbF+TLcRw64siW2qgwDYbelhR2s0CpQ5XXeszHmtU2LPDdiFRZLOUxDpi1gSOnHyKhagi7kIXRCTHYoeTkG3qPxCYBB2IaUr8muZYbdBEqsdMDMWKkAsvZhhl2e6jd3YqtJhEb7Jw04lnyN2kHPfGzHshJytbXdYxlOqZOdKKwQvrAmSWGsqfNsP/hx+6EO3o89z/8542FX67JJYZqPt4dUT99mf85AbSO/SoW6TAhlJu0aAx7NWhmG36ksMuz2W+bLZfzvevne2xORLesFFPnMZSWxttpRTCzko7aqpvhn6xgg/DyAknpVCJxxzjhh2KqSzcuhEeKaMdjuCF5YS61lwJ74dEag2q3Tw3itIYo1WmNebJbFLz7A7XIR+8HjXgycumtnVFRaguYCHs7Di5GefWxIbJI5RZYMjpnjYbcOw2+K1u1KC6QWUfedSDzt6hiKQyUtKSVVQJ5JYUgPwgowXnAUPu1zoxBjIx98jQEbRTruWjov6r4QlJ8C3rs0z7AyDfUNJbJVhS8hEwIoX4wH8lEoPvcHD7s5JOOdXT4bzmTzD7pIDdoKhuF57wC7D7OCX0wJ3RPrW9hZ7udCJhGEnE3wBybDrB/5tUcm+ZqRaq/AyrodfPPGu7OtIEmtsByvH87R9+mqqBLCrDxIwuCwbb1NWYcqYiTzSktAJufj3/rOYHQI3nnT/3gGGHYAIxDYRYOdBJbJvYUmsY9h1PoRiZQNgN5DE5hh2fk3I32MJhCC1RWjvkazRZMZ5vj+CSZ6sE4gNdDCv+PW0Dow97IZWNu6AKXTC/77gYdd3LYxWeOLmHkpFoA+BQAzYZUD5CLyyNmyakJegvx41AjjlbCqCDcwubMZ24hkcbEBYG+YTnBKb32xf98LCpmt5vI0ksUkfFw4iMOxWUaBUK1JiM5JYGsMSSwI6/mvKb5Sr/fi8SpVhkfLGgFGYE2Dn5/m9JpZlKXTCSWK7WkhiJzDsemEnQSqo/RlJYjv2vnaS2IpZs2NWZ2epcwN2bRPMzrMmf762ZdhJtsR8XmCY0aR8hJ1GYQ+pd1xJikqAV1cArKxYkMSL00zohNiF1gXjWGb6jfj/zXLpjOl3Cb+86PMLkmAGTiPATrG/W4lhuNMlky+1woOH8wBATGDYnXYaf/3HPoFv+ycf8e+RA2UAQmoGXS4gdGJ2gDt+8v3GW66TO2mTBcWUog5P6TBJ35DCt1UlQBAAnNo0dCJ4YdCC4h2PucnlUZMsdK5KiclCkJkkKadicAz+h1t6wVF/aU1kmjzw2kruU5MBvtLXUb9eRwy7oYddrd1/7KHXbdnm0/Lt5ahz7eiQGXZmKM2V52AqKKUwM9M87K4vHDucYurv77qP3WcqdCInP30tPOy2YQFtCp2IgLQtPeyUzifj5l6rzcX2r69XUeiEH99YZkLgVyYltu879nuppCqiCvJGQMhwSF7LbL1kM3XEw24rSaz/Xv4euRAB0NE5cuhEyqw3of9rSwy7siQ2mxIrEu8iBl4unVcCdsoMmKK84E/+TSVTVglITS1ULl0JwLPxgF0unZBqCsOu7y0O1NDDLmKhQTLs3GdGHnZjm50TNy06a/HfN7/DMane9qsi8FBWXQXCQiSNKwCDA4bd4kYMBo942LFEjmXASZvNhk60w/fSXG+2HwC7u5/Ont+lKx36+Qo9yzXpPFckiU0YdgzYeUaSUSOhEwMPOztg2AVJbPiMWoLKueATyYDMsJOstQnDzq8/jfSwo5TY0/j/JIklgIw+N22HxBxUHd784H4WfKNKGXapsb8sGcBgW+HrnWHYVSl7G25DnHwpL3OxI4RWQ4mpfGYTxjqXH+caK4kBJUnsOMNubb1sVcyrlpwSmwNV/RiWbJj0BcBubGMFQGSJwOt3MdbOtDv+zsvRKbm5Vu1QEmttCIiRktgJDDvJSqRnkBh2x8LD7pAlsTHoflF1bsCOgK0W1QaGHQF20xZxTROkW3OZxiomYiEldkwSS4BV6h2XB/tIEmsLk0QrOtzNkljyldN8HAOGnSWmW/kcaqPL0jU6bvawi8/HFgZn+l5tQoPSWgUPvysJ2IWBcH9mcDAzIcm0b7Ogq3sD+TT6XagcCCAYdsHD7hxsIyEfpcS9Jz1gd6YkX0GV/3P//Ofxa//8vxafcwEL+2SSAQRmFO/E+V3XxixYMvW2R9yE+WiKl+Aulm9TLm01AF/RPSTATnrY5RJZR79HSGLFPRi0EQaW/eJkgyS2swFozDKKBbBXGTfBoNf05wWM/DNw4mVDxIIrhknwbrF7ph0wWmjjEcOOGHzufTsP2G0j+ZxSpXH2IiWxn7GU2C2Zb/IYlBpn58nfbSu9vayVkcQC4H7NZhh2crNTjzDsUvCP3t8OPOwKc57ehjQ2AgNHgZQYAI7YRgA6v2icpWEYYo7Y+PlC38SAXSekre4XQ4ZdLkFPMpriYAC/cSz6LQbZKIE5aYsSkJP/Dr+TklgCSc/vivOaljYAPDNkEsNus4dd21vsM8MueNhFLDRIACpm2PUXJIlte4sf7L8Kf+lL/yHwO/5u8XUkia1UF0v6eA0T98ur6jD6GfsPCDnvuIcdm9CTJJYAIpoby3adPGuRJFb4FeP6E+7fOyCJ5RJyVQpESCWxigCTZcywW3p7lxptBrATDDjRPgx6Zpmx3UAiiQUQyxpzPorSwy4jiV02PcvlDwRgR31c0/UBsCuFTlBfS5sWaSI2e/P1eNvDSVtMiua71F+NM+wCvtA3ErBLPOyUSIkVbbzbkZRYOZYMNiDkWLjBw66RDLtepsRKSWxgeIf39/w9a9Tunog+YzXKsKP+Ip8SewDXL5xqYtht8rATfZtvb1K2T5YYvOaQDLuUQLY+BuDe29WHuAvfNkm+P1LymtF1lJJYYq1eX1SYVxoVhWHgkgF2rZBzjQF2TOtOjVML1bGBuMFikWfYMfg1MjCW0mlV4b3EsCuFTgS/lcoz7GhCmxm4xc6xMXnAkhh3aszDboP01n1/y98li+TCqRRZFb6XPfyumjQRiNhAB/MKe7MqSGKBMsvO31saiBkEgA3toQuAySxi2J0RsCNJgWCjPXg4w+G8CmDFNp/pB/JeVfiL/9+P4udfuI976/hv5yrBXqRiwI4+v3HndGzd86wVmC5/zB52V6zdiTYnPezWEnDKSmIlO3PDNREJwA0qLEqM5Oh4NkliBcNOeDIOwGLh3ZiGThT70Knlgd4lXN+5XweJSN7DzveBvq+dV0YAkvnQiaV1klgAInhihwEW4OKlmJs87C4kJTazsXQWea0EySL5WI5htw1gFxtq5yWxaejEuKRzJyq5L/WAFSd8v/y/JVAfS2KpvRCTLWFBsCyLJLHjDOM2J4nlCb4dvo89j034HimJ9X1akWGHYCxf9rBTXraUHBcKHnbCYDxK2CMpsu/TZkYPfXGStshMoOTfVGvPLjmcVwykdhe8oHhNivy1KHRikoddeSHY9RaHIAaYZNh5YDBh2IWU2IyH3Yj0elMfSOyS08UjsT9iUjWvnXpeLEffnXzPOpXE7j3A5xCli2b6sEa0RyBI5ZgJk5PE0mahZOuIDefAsHu6eI6Xrgh0Ur1gvrnzXPm5KgN2nrVj/YbEqWfgGfRYDCSxYjyR6qaM9Jbm0hKgriVTMgca0+ebSkhmw32WcxuZEkuWTW1nAxDEgF2SxsoMOwLs8h52Bt1GwI5UDdSuVyOAnRH4QrsmwE4JywIZOjFUIbUwkRz0shbbK+Q87OQzu8HDbt0LK62+yafEJpsS7svCXHmNKgmq6TgcZSD3Fp/TJf0v/Uz97pIBu4kMO3FcMtk29bAjpt0MGYadT4iF0rDVPu5ZD0Av7w6tg5KSzGbqE6Uk9r7wsFNKYd94YPCyAXaUltXacUmsLgBWpWrXQWq7mOUXoCxrHZXEbmK2JYw0tQGw4g7ROAkpA1w5hl0A0cjDTyfBGeStNxY6EbFtit567nP6hGFXCt3QhfMPgOUVA06ACDzZqw32ah0YdsBA5sLlr+2yJ1ZShsHEAEfFAEcka9zWgF/sapE3za19xwY6D8OuFe1jnfqRnaeEVxtJF0/I64MZdm535X7vnucbezVu+uTb46vKsMtIYmujhRdcy/dmhZoXIxE7bBOw0MWTkv2FMPkt+FuwJLbIsBPHnWEGMtM4ksSqiHXcnxeoECy4g5mB9gPwvNIC8AzHrXraXXZ/m0WvK3vYUXul/+98UiwDRRcN2CVjFKd8Slbc6+1hJ14r5eBZwG4LD7sCSBIV9fHKxGy8XR5LE+AoDYroI7YazYXCdTUy3IDsOUgSm6TEMkOPJbHjHqtd3w8lsbLdFTYrIlag2ODsBx52w/ZHgJ1NFAidkLZGx1uFBUfKlrDWRmEVMQuKNj3cZ80qjQUdKh1z0hYjSWyb+J0hLHT2RIpdd/4lwGtf/t62DYVOlPsWap+9Bcuw0uqsSIkVgF3NktjYw056uAJIUmLPx7ADMFxYJkWkgwopwy7PfF6aBLDbfyD4J25g2EUsOYTr2aQMHyMAJ/LPZm+phGG3ax52QMywS5hvxLCj+0KSWAKyTv1jmGfYUX+VA+xi6S3ZE8n2HnvYZUInRkJBgODPy/OpZA3d9H2QvjapJJY87NLQiUT+Lxh2b30oL/OmShl2K2Y5T2TYVXNwdG4UOpGwpOH6ul0InZCJ4wOGnexv6nGG3dpKhl0AMdcCfMpKYsVm1Bo1mjaM7ZsksWFTKj0n9/8DBuwOonMtVgTY0cZAGGuJYU/rGGLYzVTL6wUuek5n11BXOnjY2S78rVAy6II+d59TYlsG7Gjzf4/EZZcOsGsDEDC4QKIM0bqnMuyEh91iXqO3wwcwsMRGJLHsHZcAVhS6YOIL2pMEpDTJZu87AyMkj10OsONUMiMkwXmmXwqcyYpM6ktSXUqJTRZKzLArSGLTa8cm0lcydILScwzmtcHezCQMuwJYRPRgm4Ac4m+SYcehE+fysHMdW1/tsYfdzf0a1xZVHFgwtUiyq8L9JgDyIkMnWmvw6HU3cTlqqdfyA4BnDd7r3LNwc3+G6wsKnbiiHnYEfFnJsEsAeD9AupTYIIntbLKgLZVMUEKFgz0J2KUsk3CfYo+3MrCXk8TaBKhuUDHDLnjYnbMP8c/ACrMoFGJembz3Xicmw/CgZzEl1k34TjHnzyaG3e5LYi8YKCoCdhngq8TG21QXHTpRPK56dME6qBSAHJO5pud+hUInCIwceNhl/OD6jIxTAqWl0Al6P4MDG65f1wPzUkosMGz/ElCFn4RrDZJcdsxmi4M1YsDOA5jJ5l4jwZdcIjuGgQhysVIJNkUjJLHkA1obhYXxklgCOpO2KGWw1sasAD5fAHu1EQy7HQDsKIykmcKwC3/rMqyJvrewNqQVYp4D7Cystby4p99rJQDVUUnssN3kSjJpRosBkC5mTjIDNO5rT2c34/fvPxD78430YS2fs4r+H0InBJtqwLDLeNhJht29Z3eHbeyvUS4lluYeKcOOgKwTP5c1yHnYCVak9LfMSG+7jCQ2TondIInNeNxFgRPiuxgU76SHHYVOJIBdkWEXA3YGHd7ycALYffB7gb/3TQyQEHswlcTmZO/yOenW/pgkM9UIDzsznDu3OyKJJXBOqw0edgzYph52Hlju4k1/llNLhh1LYsX1bmOG3SrxsDv1dkbznCQ2wyJ33+N+JsBuRQy7TR52Sg2k310f+qiZ8usUwi38+pbCKKKi53R+DZVRWGIW1sMbgicY2BRtkBiGR6uWnytaQ+xXr834emEMu00HRgy7Ct1G+iEA9K0IszAibVMyKgossfh7PWCXDk6F9/YbJbE0uaycwbpfVPcZgItlqtrAmDDoyvMnxp0eCZ2I0xnzxxXYfPlFVRq6QQw7nQz2vdoAWO5yiYFwVmns1RUAhY46hCLDjgA7ksRWg78xIGaDJHZmzpMS68CtlZqz58SNvRrXFvXZvOeos5OhEN0Zjy1XgpH1yDUHGN3vEoad33W907rrfWOvxnVKieXQiSvW7iIGGgG5KgbKhPyf/Q+rjPx0w3cAbtd3MTPlVGlxPA8ezsqhDEI6GwPQCRhH/jWeQaiFJNaet135dnNqZ2GCCSTpr5JhF8vQ3PNXYti5tri0MxzMYobd7gN2Z9wkKJVkBUTfMwbYbSuJfQ0YdqXP2gbQHDDsiDGdmfinrzXjY/ZOVBI6kabEkgxWethZ0R6MEoCniq/d4LPYw85f2w0edl3XlUMncu9LgJSQRhsDjYPFnpgjlSSxkYddAbBL2RJSDuQksZLBFc9Da6Mxp8tHc7yBh138vKc/E6BSG2HWvUOSWFpr1COAnZTN5dgbdM0Dwy4ACpKFJt9LoFV0fyZJYsev7VSGnQRAsh52Sf/YWo1TK5gp8xsx8DbCMG6EPxSQyIABARJWA5ZhlDArQZ7DR93rbQfcf378XC9L8TXvh8w3P7/RdSJJ9JLRY3+JanTYmyVtNZdW7l+79EAI9Y9tBrCLPOxyKbBy0zKTIhsFToi/0fqz7fqMJJbAsSQl1vbu+5J5V+OPu0KHt6QMu+/5fcCHfgD4998OIATIECi6TmTosiQY36cyXXcSAByzMWVJu40lhd5OYHW9ziVTUOuBJDYD+BYksY0V/Xu/IXRC9kEdWfS49XHqYUeS2JyH3aC/SM5p37p598oc+NdNAFCTpNjAsFPsxUpsVFIIEpAXlU+IxfzQb54pnBIbeUPwBH2nbJf7tfuul+6HuQA9V3teEnvpGHYUTtBhfFJt6nxwRKk68blVxFQSi1Nip41JYg152E3zjuPJUAkMEcm0Rkhiu5GdNsmwk7+Xx0GS2VzFkthSGEY+dIJDN5IFRul7bWaX/MqUYA3NK80IeaeG0dG591E6VA/tjJ+BcD8EI5Qe6roK4MX2gF1suL9XGyxqg8N5FUCIrVJiyUQ03O+T7gJBMvbdMHjgwB3zUScYdtYyw+6Vxg00N/drXCdW05VNiSXz0ZhhFzFmZehEHQC7XJ+XLQLNrMKsrrGoTPm9ghH34OEsyKKLHnY6JMYZkSJN/YP0uqMJlRou3M9UBKphhmsCsCulvxJgR5s0MbCXMPEo+Rkz7gcOr4qH3YWnxBZkrheaEjv2Wdt42BUAu0581jZhEIUEvFEPuymv3ZVigDLxsEtCJ1ohL40Au4wkVrOHXTw20uZpN2DY5fuRvmuhlX8th07IzbT8QgbpIoh257v0HIdtuStIYiPwhdqMTGTHMBAhAuyEJLbpenEtGz6mANgRwy6VxMZzvDR4omXATqP21621G8Ciy1B+Dt/7DdV5ZjFPJReeOX+k3m+WM8OukBIr2YkpeHVRklgGeUe8v93nENurjxl2Up4afa7FnhLjndaxHG5K6ISYqwCCCSMDBkw8D5VAQySJ1Qa4/rj7+dVPjJ/rZSnBahwy37xHW72I3+IBPLJ3MeiGoIbc/FKKn3ODfvA9LIkVn8Epse2G0AkpuRVr3+N1yrCjOZP7eS0ZdoPQCfKwkzLFlWgT7njuLl07WFQWDx6I10qizv0X/LnFDDtq3zkPO4kpcehPgWE3YG+LZ/Gys+w6ybAbhE5kNh4LgN2qj4lOHDqR8bCLGXY+3MGPdU3qYcehE2XZcgSK3nkKb/vId+BJ9RIOrCeimIkedsCAzSyl9+RhR2vijiWxOYadl73Or3H/xoDdhuAJZh6LdnngB+QX77nrNTOan/eFB+yaywbYEVC1Kb62koDVBICAGGvkjZTzc2IQbkQSG7zjpklRiWFXlsQG42Ip/8oz7AJgZ+r8QiJ4yU1MiS2ANLbLL240y1ASwJKYfamHHWnBrxrTCRAsMA/Y+Q5nKsNu1YdrS0g+3w8JXAhGUluS5G0qP+E56t1zc8t7vR3MTZD5ncHDjpmaEPH0F+hh18EIXzpi2K08aOeu/8trdww3BcPuygJ2AsikBdkAcBI7WjJ0YnJKLJmxosKi1h6oKsimBSPu1v5sgoedSLfVudCJ4fn1CSvnzNWE0ImUYUfAs80AdiTznxktQjXE+ZEnC5wklrwoCBQ82nmG3RkA/bHaKIk9J8hW/Kxp0rLs55SOKzJLv2APOw6kygMqO1kJuBk87GJJbCc87JAD7LRhoIw2MWr+LPEayNCJcSakzTHZxCK46GHH4Rbx9xIjeGyxR4sYlTLsJDMpkxALDAMROgEKGa2yskWaQ84qjbn23ncDhh1JYuP2LD3t5PnWJqTY7QTDjoDcNvj5lSqSzWXkVsywywB2koXWCOYHM+ykh90FpcQC2zLsNrOZu97ie7tf5n74kt8encOmlNg0dCI6ZwBZjzQ/zkepuqmM8tEvcv9/7v3j53pZKmLY+WvehTm+VoJh58v6cyWGXaV67KVtdcDCDqmWQw+7MF+kCsCr8LCT/WB0f4b3+WjlzoXABvpbxLBjSeypA9nYw45SYsV5tytEMlwAL3sTv1tzDaVE2z56MfzbHxvNd1cJwy7nU6lUYCEzw86IYyEPOyVCJ9INN/Edl7WKvqaAOJ8Raw8aD7rYw46sHuT5Mys28rDz6wk/1q0LHnYDuTeC7UMExH3HN+BLP/Q/409VfxPXeydLPaluuq+aBNjF7VwyeSuP49B6gCWxOes1Cp2YX+Oxdqn34r8Vaj0iiX3xvmuL0raHGXb23BBbVBfAsCOp3QaGXVWYSJc+lxtNzLDrxc4m7dTqEcCOvnfAsEPew80mk7e0JNCnRUpszsMuTOANKtmxiIUUedqZkXOQKbGbvPX6ZPAmht3Aw6/gYcfnfyUBu8AamleGO5yWGXYbUmL78Lh0KRAgGHY5CeHW8jQf0HCvIzaaT8qcidAJO01e7o6PWFzhHBiwuwg2pbi2zLCTgB3tuAK4vXa/lx5295oL9NO7TCUkqFkPuyaARytUPFFxktiJbYc8ZOBYmI5hV3ivAJavR/LqEYadH8y1VmFDg/rHXrZ79zp7UQw7P1EcSGIrw0CjJb8Na6EJsPObQ+4aZhb9NNmDC/pgSexVYdhdNFBUBOwy0lsGX7Zl2GWOOeMhtrGUmNKUpLpn8bAjNsmU0AkG9y6Y6fh6VMJy4wkrpcSSjFWkxGYZdloy7NzfDQN4sdqBFycbmKK2zUtPi3JF+h4ZOiHOcZvQibS/jBl2ecAu+BH53XcBCkmDcSmJlSmxtGsfGHbxonsTw04ajNeaZHe7wLBz15zWGvUIw84IgCAntyIQ70ANPezYQ7C3EQul5gAGsRjNGf5Tbe1ht2EZVvSwy/fLbW/xbc034a89+MeA3/iXonPb7GGXl8RyW+W2XQ2eM/aW0ogZdgDw+Je5/z/9k+PnellKeNitEiCNLHUisAiA9vLqY9EkrsVdQAy4AAEYjNJoSdLoJbGZlNi2s3nLhZzkVvx9KImlNbT3sOttkJna3t3vVH6qnVTSvX8dsy4B3PEMu2uzpG+586nw7+OXAARZ5TLxsCuB8iYF7KQkVqTEDhPIA7jUXPKk2J77BRU/t0A0H6F59nKVzN3Jw66PPewisBcu9CgC2akShl0qiaXnISeJZYCfGbktcO9pAMDXm5/C9f4OAOCkvhWf11gVJLGVUahJEuvPk+b7owy72SGvVZZqP/5boXJMRNrof8Ez7K5Jn219aQE7YtiND07VlpLYILU1sfRUTNJKSaeySum0mySxJcBKCRAOAHo/ecpKSKWHXYlhxx525XOQHn5dOw7YpYM3hWqkkljy/0vBzsAw3OFFRqkkw67W2PML9YYm4W2B3cUedqLTV8kOqwBNasGkapFZ1E4pD+TcZ8DO/X9/ZmKa7VSAi1iCgmEXQicugNUmgCACF+8xYLdkOSzMHK+eus7MefJ5Kr4tAEe7Xv4566WHXaWCFFXs7KxlSmxkA7DhHnPgSYVFZYoeb+6zwgA3GmBCk1Nrot03q5P+Ucg3qsQM/dwedoJhdy0C7ELKLrNsxPNFQUMS2IvalV9MOJ8fxTtlv/nLnsB3/qdfgW/6qjef77hf79ogJdy6MrvU7udYLum+86yS2DG23jaAnWBYlY5rGwZiegxqBERP2YX0/13ehFDx+JWmxEKCX5n2EEliFc1FSHqaD53gSbze0P/5VOgeKm4jJWZeci+ZyUc+fORhl56jDDIoAHZRgECamugr9SMK0ie3GZJL8mTWX6V4EUAM5o0edgmAxwbjWqMCyXIvdkHxmhRLYjcz7LRWLJ3LsTcoiOIAQw87ybBrxf2kMD0CAyWgOs6wu2APO2Wxbjf3j11vcQfX8O+u/zqWikdy65HxYSCJ9W3WkvdXxPCJ58D0PC2UuCbE1nrL17r//+z3AX/7twDf/wcvt5+dYDWmoRMU2CUToAFAz9zi/0jcosMUtGKmd7wB5Bh26feQh11oR9F9zDHsJHiWAWaPB6ETsYdd0/UBZAXcOiRlSyoVWHbtUBJ7b+3a0H46bEufMH/vab7b9RZt14fQicIzTs+KXYuUWCoGttvASiS7BVOH/nUKSPQ6VhsBdgWGq67w8y+5eewHn34l/gAaDzo3f3e/a4UkNh5/ADEWA9yeyCqqSUMnRiSxAwlvkgz9luXPAQBOPcNumoddGjoRxjHysF1P8rBz7D7Mr/Nxnk4E7AI7PVynw7k7Lroeh3KN4jfEGjs+BmxbFyaJ7TdKYkXS6xRJLH9uFaUTtuK9zLAbCWxghh3ygJ1OUmItD8SFxWYCEuaYf+Ik3P9VhUoeo0xR80CaNulWTCh3/rEsYFCF0AmS2qoEsKSJdHr+VxuwCztkThJLqHzeSDp9nzSQbFOgg4GQKoROVJJhdzZJ7KuNux+3IoadBH8nLgY56Ta897SbCAhN+vwATJF8955k2BFgN9vHnVP3fTf3HUClFcrhB7te3C40Mywihp0A7KQkdlbprA1AtmSidq0Thl1Klw+vjfwQk+e9z3nTAUNgRTDxaBBkhl13TsDIPwOrRBI7kx6ABLJLaazvS+eVDkCwbONtAAKBsFP29keu4Ve+4xG87eHAutjJ2iZUYUqVPOwuCmSTn/2ayWslYLeFTUFREpsD7EoedhcEnL4elVxL9p0jhl3Gw47OVym34OXPSRh2KQtCSbYeIBiKhetHgWfK+0ENjjllF8cS2C75OYBjIx52Ou93O4lhlyxmAuMtMPLdcQnwMwqdIIZdCtiRJDZl2BUksZVCrYhhtzuSWGLYjQF2gGCTZUMnehh0weNtdi28z4QFPQEHEkyL7t8FSGI7YZ4+WjL0JALs8sBwDghkZpYEG0clsZ5hJxaobd/HgFDC8CKfp30tng0KKnjju4GH3+n+/bF/AfzMdwF/9VcBJwnYcFmKwB+V8ZaDwawyMbsLgJk78Pflk/AcHlRJG+S2kSaq9jhlJl/CsMumxAqWp2yDOQ870Q+WUmKJuOGYe3XYmGpOhSR2T55s+L6kvyMPu7303H2QHgBgfd+fW2jbq7bnPqsE2DHDrh1j2LVh81g8i7nQhctYnXh+A8M19bCr8bGX3Xq1Qof7S9EG2MNOCZVOIxh2fk0ShR5lGHa+ja7S0AkC7DKy5UFK7KufjP5OuMOSGHZnkMTS/dMidILWj5TizmFUsjh0IkhiT9V2kljJsCMSDVXMsPOM0cuWEmunMuyMKrM5MiUZdpUOXmBdI9hpDLqNMezcRU0ZdsQ4Sz3cgpyrIIlNJDI9AXYjA7fVGpURyY05hl1dPgcprWybUuhEfpKgNwCWg8COzyZJrE9w4iCGDQw7yWwb+MjlQifM+QG7Ox6wI6+3/ZmJJ9mTGXZDSezyNZLEErh4n2WuqzBY1we4exIAO6UUDuZVmRG26yWATBrMIk9KD2R2VnlvRS+JLQTt5L8jBIrMa+PBvgKLiJlzOk4cTl4X+l8d+1uYmPlBbUemyV5Y6ASnxM4jfwitFaxfONuE4QqEgKOyJNYz7BACXa5UXXjoRLLIoLpQwC4DspzFw27KcW0CgmTJVLbSZw+O17enDSmnO1GJbDVln9ksw87NrQ5nVSKJ9Qw7WCj0YVGVSmLZW258TLDMBEjaR+m6J20zAIN+LkehE7zYG7Y/2tBUA4adCBAoMOxSP7AuAVaMZIAQw86GhQItAizNKQahEwnDbiCJFd5IBNjtROhEzLAYk8QCw3APWV1vsQ+xMRsx7MKCntqG9A+LPezGJLHEoioTCYDtGXYA0Mj5f4lh1w3DLCQYbEsejwjPHp2r3KxrOxtvogxSYj3DDsLTjNYXSgH/4V8GHv1i4PO/Edh/yLFvfvhPjZ/761URwy4G0ii0LmKiATAL15aePwrP4UE6dKVsdSHjJB836g/zgF3Gi1D2jxLE3SSJ7Xvuq9nDru/dvaJza0+HklggsAulh50/lzsrD9iZ5Plbnwz+Lc9t2XQbJbEEtFg+JmmF4P5do0Nd0TgVrjd9ZtovXraSbO3Q55AkPTzznW8fBh0+8IwITaANnD7xsKtiea0ELnMpsb2fY6+72J+WAOz5lJTYe89mz3E5d4Bdzmd0UFUM2DHDziiYhGFH5JtZ1sMukEaIQXyypSRWAps39+L+nRh3ADiFvblgBvuWM+Fh0a5XvwGwI1bJHO1WDLtOVah0QIo7EQxgCj5ssqgjMiXAKmHnWT0+ySYPOzbCTRLG4g8TDDvPEqzQC1ZWzxPaakQSW2nFAFE2jRaAKrARiAmYetjR9Ui98waSt6tUQubnUmK9NGYjw85PSAS9dRAIQJJYKz3s1HTQJS1PQ7/TzgC0uL7njnUgiZ36ub6jX0bnsIU0bFP5tt5ZETrRExC6DIP1bB93Tl2fccN3eAezCuvV1WTY2d65BMUedmLzwu/srBGSTd1rdAD4NwGqXWifi9pJWDurnc1IwcOuIUmsDQC9XDZYBmBNvEBSySRRvI4mF1YboMt897bFktg6opu7w3CDOC+cJfOaJm6FNFl6tpZ2hr3asOTpytQ2DLIpJRaGz99d4j2fegVf/baHcCvrYVdg422qnN/bRYJ/G7x9ipWezyhgF0s7r0bohAeoSpJYHUCOVIp8MK9g1kPADnA77Sn4N2DYbQA8de/Ga2a98R8K7CebfA9LYhOG3UjoBH1XCtjFDDs/jygy7PrhexBAkjZaILljmBmNGeGIExl2KYDXClkPA3YXzAB4TSqRxJbYN1RVumgU1fUWB/CMIV1FkjrpD9YkwBWQAIElMNnayd6bDPJuAdi1TZJ2nvkeltQJ1qk8j04ZNypm5vhSNp2+LwLsovCeBLAjOVrCQMOT7wL+0I+5fz/9HuBH/lvga/545oQvQYlk3lSqyh52IrAEAGoG7BqA7N6SdVcA1OINoJz0NnjYCUks97c23z9ym8gDdhw6MaviTc6KwBn/zFQLNzdtlsKPMMewWw0A6jtL73GWAnbCx5rmYForFw7W9Vi1PTOZZgVQnlUchAPINia8HoebLmbnGHZ5D7sgqX7JMzkr9Hjpvli7Wsmwkx52ceiE9I+LU2I9MObH0aaNWblLT8TIbXQPJLy59FUzw6q+AeBoS4YdeWWK62PpWUk97DJzLsEUJeDthBh2xL4rVMPtMvSHZP1ERWt0AJh5+4qLlsSeH7AT0tXRL9JxcMKmJZLlzzVRuINMY2V22gjDjtJpK3RuMPWDWACs0t1ZYk7lF5sqmfTRbmdWQio6i4oTFpvw0AnWnxqRxCqleJLWl1hgxOZLADiT87CzFtoDhQPAkk3ld1jGUyohT5zXQRK7YoZdKSU2gBxUQ4adADhySZ92y0HCD2532wpAyx5eB/MK7u5pdw+3ZdiJpNtB4ud5SgA3xLBbWZG+y7sbB7h/172WAicO5gbN/bw0c9fL9p0H7IK0NAKS/EBBP9NExcmpzyCJrXTsnZjeW8GIO1xUxdfZLkxOo903U8VgnAydoEnSBpby5PLPwBIzHMySjYiqdseRMlyt5s2PiGkYMew8YCcSYq9UvUahE50y+N1//d/joy8e4ave+iC+6y05wO68INtFSGITVnPfAxAg0FaAXSphyvjjUQ1CJzLXZ9eKziVl2PFm5JBhR+DewdzA3BevE23CoA+71QzYEcMu9bDL3ycrNnWzx1zYrAiS2Ph7yIe4MjpuM1MAO5Y36rA5kDBS08VMumtfSY87AuVYEqswN24O0RdCJ1LPulLoRG00bxR3F2yK/ZpUsolcWsxTmZSVIqrrbQicmB1EUmrpIdhkJFDR/StJYmWbm+phZzYBdqEdtdISZ8TDTh4vEDPlGPDNzElToFJ+RiSJlYBQspAOgF15TYMnvxz4pu8r//31riyQlqhoBDsTABb7hwAaAI5gUatu2Hd16XgSQCYKXmDArnfXPi+J7YEq0wazktghw+5gbqLfk3UUs5uJYbe8E/p6Cdgxw24oib1PanOdtC9aAwCRPHZeBcCO+rAiw44AuybjYUdsRdVlNl1qBlsuPWBnAyA1YKwJxuDtE3duBh3unQ77hVWLBLATYC9CkIxSyabBgGHXJYCd+8y8h11iR+ABu5f334oHTz7ufvfwO5goNM3DLs+wq/SQYdeMSWKbkHZM7eOYkPX1Jg+7IcPuRsKwe/gwtMWZ3xBb9xdLBrgASay7MGk6aVqVWKRGu0TFz40nY6RNlgwzlsSOedhJQE4MpqWUVGaQFHd1Y/kGMezyklgB2AkfPu60xXuqEdARCIBo1xYWGWSumXrY+fOLUnLFdUiZff1FLbYvY/EOmYlSYhlYKibw0kBdsaHxOmXuiNdw6MRZPezaNb/+FS+JJYYRAQwlKWOx/HGeCsBuG4n6aFkrrq3GtUUFoxVWoEF9GUlimZa/CCBkAFYKoOmOFi0COxt72K2pzXmG3QoVZkYz2yti4W0E7DwY6yWxzn6gAEoIYPX6InjY2VQSKwDoaDBPDftFkAsvPC4KqBBec4eLpJ9mSVLsYef8ZUJwR5MDJBmwq7E/v4qA3UVLYt19fP8zR/joi669/tuPv4zbJzEjIPr3hXrYnRP8k58pmV5TNioGHnYjbTsFGEtMr10qCopIPewSuahMiaVNzcN5BQMBigmf44hhl0hiOZGSr1++HRNoNmDYmcIcLmHyNQMPO/f3mdHDNkMfUZTESoZdXhKZLmZosZIy7GToBDigIzDseCMn8QxMFz9FSawJkthuJxh27jraniSx44ugzQw7AuyuRX+rBMMulwoYMSRLktio3Wxi2FHoyHQPuyYC7PLSa7ngp5KgYF+aGwCD81YqAQ1yDDsOnfCBASSJTVJUd6o4DEJKYsMcd14PAbu9/ev877KHcDqeCMAuSYld2bCOoJLBKNl+TrYJDkgK/UAkiRXjEtmI8GYJpScf3w6fXRUYdgIktNbi/tq3oUTVFjHshDyWGITLpsOK2tAGDztLHnayjfnxokIrxqlwvYlIcekBOzGWDPoyAUASMGrQ485JUO1RrXqx/uwaviaUksvPeppSTapJAuy2SYktMOyeuf6Lw4se+YLRPnpQST/Tin6zIjYhYUuYANhVC25Hxzh76MSs0hGR4OFrErCjZ/iyedhRUtdGSawIjiixxESlzL0+k5Ja+ZuSJp3K0rX4W847Lk2J3eT/k4ROkIddlmFHdGhVodYaQxmlOJ4R0BEIQNpGSWxyPgRYRpJg+b1J6MSFG5ZfphJgxbzSDH5xcmoJLBIMJqLBDszshc/dXDLs7ETQRZYY2F5Ze8BuQR52BBRveZ+EFBIAHjiYDQHks5bYqXXBBwb7tQmgJhASomb7uL/0u3z+XA5mlQBAr1a7swxoBabazGisSIa9vAfASWLlxGy+DcMukq+qxDsxv6BwoRO1ALRKE0sDJRYUtAGgkj6skZJYVV4QTC5reYA9tXMcJsCa9jurKmHYrRHMhWciTTaSxApvvP0R79DLVNZavHy0grUTJjgXzrBz1/Z9z8STmk/f9de0kMb6vqdexe/9zp/A3/jxT2SP+8c+cht/9Lt/Bh954X6eFSU2vP7+ez6N3/CXfgzf9RNPDT7n1eM1fsv/68fxJX/6n+EnP/nK8LPkMxBJYqd42OUXWOMedhNeuytFktiBh13CVhO+a5EkVolrIgCMCp0InfDzuAHzbfz6EWjWq2TuVAJKGbDzAJAFesFmo03Kyqj4OwXQyAy7PmHYEfgm35sANrxI6RKGXZLI2XbCD5AksZVGTSmxqYedv95t4geUMsxkAigx7HZCEkv3k1NixzdZTHKdZQ0YdqKkP1hugTZJErsFYBck0RvugVI8nneS7FD0sBsy9yRTbmwTuUlAZPlvB9gRw0d42NFmNafE+me+2n3AzqAL4S0UBkHhYIkk9vAwAMBFhUMKsvr/V8oBdtZa/p515+6TBEYillSun8sxICNJLDHsqphh54+DNzHo2Th6wf1f6fh+Rgy78J2nTYeV9+2iTQEuybDrVnyec+EtFzzs8s84tUVFgF0k0w3gZ5oSK0Mn1u2EOdTrWNRP61EPO4Njf9krdLhLDDtxT1ed3LjvBgzDNtNPuO+IAbtGjEd917KkNgfYDRiBHrC7O3sU39b8Lnz02ruBr/rPAgt6ioddwrDrbThuY/2837c5Ot8qlaIDEcOO+lxm2G2QxPLYmbC7pSxWAna1Z5euLtjD7sIYdnZTSqwArLpCcEL0ub7hMVDFDLMwYE0JnahqsfsqO6hCSmy6a5lWGtbAUtXsjnvYwY0Ydv3w4TJj9HH5PQWwM/XW4+P1x6lziyoAJpHi2qsM2NkAnswrzR3Okhb1JUlsH8A4Mppcp/5iUhoYyRrPwLCjjkUZ3PGJSynDbjL7iooSdnyHdnO/vrhkVnEMPSXwzkwApQBOA+vrA975v8YMO1Oe4Ox4ScBOetjxtfE7O42tol1FF5gwse0wWOw+o5bMsoIsrPOJsgPGHB03teu0X08M+9lrFJoXnMr/3+Zkg1Ora/h5XaKOUmIBQPv+UtvW9bN9uAY0MZmZQviGkNru7YAk1lqLP/4978e7/uwP4/d8508O0h8B4L2fegX/wz/9MF64t9yOQTalfJt5/3Nuwv32R9xC5RkC7DKsuF4Z/IG/9V78yM+/hD/9j34OP/Azsfnwh5+/h9/znT+B73nv0/jmv/3ewNDPfNa9tcV/9f0fwAeeuYtv+b4P4Kc/fSf6rD//w7+An3rqDu4tW/zf/8EHNzDsqu1CObbysCP5p39uLzr84/WoJBjCJKw46h9aKYn1GzgHcxE6oQSzEYBGHya/qYcdTeI3eNgRWN9PCUORxyzmi47NRpuugc1WAl7ou1RyTBHDrsB8KnrYUSKnXOwkYNxMhE507GEXzwFShl2TLIYawZ7aKUksMexIEjsxJTYXOtFKhh2xiHzJBX1OAhUBVwnr46MvHjn20hkYdhs97AChsMn5lcXf02Y+VynF4CNLYkcYdtnz7vpY0skLaWp/xKwiJGGXATvpYZcw7Cx52MWA73z/MIC+pflXes/4ezr01vuLsYed+6yFaO+VBF1ysmyZ4pvpB+/5zfLre3X4vdKoWRLrnxkCIwmwm12Lk7gjhl34zjsnDc9bdTr/o3UN/+yDJ7y0ctV0vDYoPePcpomhJwE7HQI8GIQSANeueNhRN16NetjVDNgZ1eMOAXbimp92MTgfUmIpEGEIzgNg4or1z7dMiW3EhkFOEjsAGJd33LGYQ/z17hvx//m8vwC84Uu2ZNjFgJ20nzibJHbBz+mRJcBuA8OuHTKuAeDJW6H9RYAdSBJ72QA7v9NoNwxOtVEh6XUCw45203igyjDZ2IduBOyKQhUihh0lKaVyivyEjIqAMWLYcapsZnEUQLQUsKOFRHi46g27hrSL3BclsTGQyMdAkliITipi2CX3jdPJdth3p1SSYVcbXqwv+w3AlZAH3vCBCoPABuFzF4dOePBiG3kgm7zu42jt3nfdg1vUSbaph96mIsDOA0P7MxPYR+eVxIr2ZLVBZdznR4DdqQPsGhNMYg+EL9+FHcslKysALWZSVIJhtyKGXTXwKmlHpCtRCTB2ZnQcdlJgALTeOFkVvHion037dUWemP4+kRF4Y6uLlcS2YXK3woyZpVRa9vl9k5fEViVJrGfYYea8XC55/dAHn8d3v/dpAMC//oWX8B0/9sno7//sZ5/Hb/sr/w7/67/8GH7Pd/xEADAuyjvNt5mPvOSu22//ijcCAF6kNLwIZHO/e+m4xe2jsAHy13/sE9FH/pV/9XFesH789jGeuzfcxArfexqBD3/lX32M/71sOnz/+57hnz/8/H026w4MO+krtaWHXZrqN8bOK8pndxmw8wy7PmXY0WYkgSMhdCKWxPpkU20CkAm3EE7BP9o85QXVpvvUx+bYXKbwvoTJ545bMuxKklgB2Pn5oi6EThgt3pscV82LGWLYxQumSO5G8uI+gIhFhh1tCiWLn5RhJv3J6L5EAVaXtZI5+SZJ7IDlIcqlxJYYdmFB33TDxSxJmrvORpLY9z31Kr7uz/0r/Cff8RNxv7CBxJDzmisVExempMQWmHsMZI5s9qYybSCAd00nGHZGJMAyw87LGVXsabaTNRIG0XpLnRTwVbMD9rUqWtZISTEgZJx+c7LpBbGAvMKGDDsH6udCJ8Y97O6euL/f3KsjZlyVsK/42bj/vPt/cq4MxiYpsXdPGz5ulbYvKYkFGEBZ+LXvsu2xpgTSooed/32WYReuZZ1h2O2Khx0z7FI5OiAYrhWOPYhUYtgtOxUpvFLAMif7d3/wmI4HZdcRYBfa2iKDWZC8n8cez7A70a79hER0asdTPOziNQpvdCjFoS5Lb/VE68gqB9i1gmHnz/m+9ZLY9TjDrmGGXdxXP3I9rGcfvxHaYmDYXTYPu4521McBO6UUWhp02s2LcvJUYsCO/i8QXpp06LGE1YIklsC+9L1qwySRpLQDht1I6ITSXhJrk/PnnRQDs8FItx/zyoMEB9PQiQzDTkgYo+sDXA0ZT6kE22lugiT2lDq1DQy7FhUz7AZSO06SFZI8af5/FsButo8jvyNGfm/z6qwedgFQPJhXWFTm4iSx4tyMl3a7SYZCV/kO0e/UNdp1asQEA5zMNwArVy0l1l0bq4K0tDYaK+sns14S23j/OaqtGHY0kbQOrIrCTkY87OaVYeArnVyxh2XSr7P9AJ2X8HXhgf8i+hAPqvVwbMQUWNOSOd2tRftOJLHk0Sc3ifzztcIMezsgif01X/Aovvlr3oovfNx55Py1H/04s+zWbY9v/Uc/xxO6Dz9/Hx96wfcfFwV++3t93LoNg1/zBY8BAF46oY2n4WYQgXnf8EWPYWY03v/0Xbz/6TsAgLsnDf7JB54DAHzBG9w5feqO73u74YL0k6+6e/c73v0mAMAPf+gFvHLsfvcvPvQi7i9bPH5jgXd/zgMAgGUXvz98pnIA0zZAWrooViPP5CB04gqMpQkIF1Ji4+uSZ9gZnmdZZRxDw3+ezqXE+r5lIInd4GE3ZNiVJLF+s1Uy7KSUV0pipSG/APis3zjVYww7weqQlXrY8XvI4F94qKXhJnWl2MiaATtui+RhlwB2qSQ2YtgRyHexC4rXpJL7OTUlNsew63qLQ5X3sKvFgp6unWT68OfaWI5Imynv/dSrEWsJG6SuvPDcFDoB5C1xCkzOHMMOEOyXkTlpMyKn7aSHna4G94W+d06L5TQldpeKvOVUh7a3DoyUHnYZhh1mhxykVp5/5TeAKvK8arpojgakgJ27F+tWMuyGm1wOsBveZ2Ji3dyvo/YT0md9nzH3zwYz7JJzlaynAsNucO5SEit+lgy79USGHUtiqyHDrkJIRJXXY1cYdnJcSDd58h52ErAL93pZYNhx6EQmCdt9WcywazoB2LEtQfDblkV9BclWCbA71a790BhYj/TRVNQWuK359XkUytETw86zBwmws5m5r/Cwo+8/sh543pQS29K1itvllzxxg//95gf3+d8EwK+6SwbYgZkY4x5sQGAlTWHYMcODgCqWnvoGay3THqsR/7fKGHQ2eXit5Qs6TIklz5YCYJfIcDmkITOpVDyBdww7enhaYsn1Qk62AbDj61AAO2nBnTLmCJAsediZgoedumJpnQCiAbeuFIdOnG5k2BE7zeDaooZWGHp/CZ876WE32YdMVhPip+9Lk1gEhl3Re6xUgoW1VxvMa7096FcqcW4UnsLS3Yq8MF4EAKw8YHcoJI57tQnSRdtfHDPoEpQE7KgiSawf0JaYDRh23VQWpWTYEWBX8k7kNFUTMexU3zhTJz5u6tfz/YP2AyKFA7UwYQHOi81zTIz8btjSzgAo9jsMhyHkNl0TPaM5wC7a6GAPu9lOpMRWRuNbfv078Q/+s6/GY9cXePl4jR/6gNv5/p73Po1n7pzi4WtzBrQ++JyffFyYh11YQLz9kUM8eWsPe7UJCVgZVtztU9fuv+6dj+IbvtgBfH/n3zv/uX/4M89g1fZ4x2PX8Ae+5i0AgOfvD1nn9FkvHLn//9Z3PYEveuI6ms7iB37aseq+76fcYvk3/+In8M43uEUGT5JSSexZgLQBI2IKw44ki1dBEkvzISEXBQQ4KXznktAJKYm1nGwafIZSSeyAYbdBUqzZPzll2BWktIn0lo+bJPyCzRaAFxNJwZhhl3rYdQIkKQApKZDUSFae+LuUxCrhnWM4KCKRZxc87AaSWMGeCgy7XZDExgEPm+bKqfRYVjvCsKPxd9327HMVM+ykJDZYxxjRPk5XfuNhQlBOuwXDjuYPYe3Qh/F1wLDro+OlouvWjWw6EEtOGtFH7Csp6UyeM/Z5osXyTktiad3kzmnZhnNnFn+dgFj1wklNgfJmeJoS66/hgXFtYdmE+W8Pp5aIwkMkMynXz8mE6mScW7UdTrxi5+b+LIxh2mBWJUwuZtg9538eYdiJ/u7eshHKkJHQCYDXOdLDjiSxRYadIcAuyBu5/DM5U3mGXZCEXm4PuygFVYtnDxB4i8Fx6zd60ON0PVQTLNsYOOZ7TAy7kocm4TOVZNj5/scTphYbAFVuR2w/M+dzAsImRc5nFAD+nz/8EXzxn/5n+OAzd4X8ep0cd4Zhp0YYdsLDjo7zPkti72WPg9/qjzNNKP+mr3oz/sjXfx5++I98beT1TZLY5WWTxNLDukkSC4SJRgl0yn0uedsQ044WiHIxqEcksVUu7EG+N5WQskdJHjSg3WPepVVlyaMSO+6S9cKLR7EQ2jRo0/XNSW8BwaAbhE6UJbGNNcOHlRfbO7zIKBV7ULhFPe1cnXQbGHZioF7UGnPJTusb30n6SXgkiQ0sqa1Sd/3Ok6332SQ2Zdg1aejFphKgDp1DVi54lpIMOwbs/I6MiRl21HHT+QDA3kw8oxdxPJeowsZDDMYFSazfgbKzaFcxZthtADBF4EntJbHlHd4gt5hXOg67kd9T8LCj11P/mEuTpQXxQBKxTYkkVwADr7lZXYeNmG7NzwGBlkCctNvLZ9tPIk4x3wlJLFVtNH7XVzpQ7m/+209i3fb4yz/yUQDAH/zat+HXfuGjAIAPvegnJhcM2HXW4M0PHkBrhSdv7eU3Iwiw8wmyX/LkDfxODyT+wM88i3vLBt/1E58GAPy2r3gjvuyNtwAAzx+1mc9yY9adpfv/5z56Df/RL34SAPC9P/UMbh+t8K9+4SUAwG/+sifxuY86wO6UADsaEwsypO0YdgafvH0cTIRHPOysNvjgM3expCF3l/uzhDUXGHYe/Mp42Gn/2sNZBe3HxT7xXTOqG0hijWTrAWLBOe5hZ1PpXQmQFYoH+monPw2sP8CzWApyQzLiTgG72MMu/940DKFLZDa0GG0jebH7rJnRmKlUEpv3sKP+r02YJOzDUwUPu9ZuBote96JN9H6ah50ZYW/01uJQ+f5xRBKbMxmPAFchR6Q5GgA894r3QpqyHioAa7nqU3XSiFdeiWHHkuvUMiDz3phhJzwBJRidMGCpXc/Jw26nJbHBWw5w1gvS/3de6RC8AHB7eMT7WLWl+Tlfv9g2YeFfvmy7wJiF5vk+VS2BjrHQiYyHHbGwtAKuyZRYHRh2Aw+7+55hl0piI4ZdkECfrNuyb3e6vvLzsIVIiSXgKbVA4a8dMOwkYOeOKZ8Sazgldp2kZ1+2ilJQUz9OaoOq4uts0OGUZNtCSbfqlbgX3QCwbDPBOu7D/X3y13MtGXZeEpsLnACkh50/Xn/PV8o9F8TK2+Rh9+d/+Bewanv8V//ggxlJbOg3iTiw8oBdYNiNAXYLPs771jM010cRYWHw1oLf36I2+MO/+nPZ15mKwrZW3SUD7Gzq8TJSueCITZ/L3m0FsAvIsOREVdLPKd1xR8b/zsQTpbSYYZcCiZkJvBI7upUOxxEGXeqYM8BZUpyWW1hk0OJYpZNEz7DTsLwAkkyzwWRhA2C50xUBpEESuybwpMSwE6ETe7UD7aKQBDFgUlIn4DrCfqqsUZbvWHqz4D7k2twdI9HH19t62CVSSHcOFyTZEgAweTESwLI2sRfGqU/lkYypRSUYdsD5GX+XqKzYxaSKADtfp5hHu4rzbTzsErAqksSm3nSiLc8qHfd/8rozwy5vGUCbEbYjD1ORJsspsefoQygh1gO8KcNOsufkpJF8/AAfOmFzklg32VvuiCRW1m9/95tQG4X3PXUH/9H/+m/wzJ1TPHQ4x+/6yjfhXW++Ba2AF8hb7qJY0swe1njTAw6Af/zmXmhjUaBRkAJUWuFzHjrAu9/yAN7+yCFO1h3+9D/8WXzouXuYVRq/+cuewBsf2Me80qNsvQ4GT9zcw/VFjf/wFz2B2ih84Jm7+DNeCvylT97A2x85xOd5wO6kLTPsTtddYI1OAuzc+Xz85RV+xf/0L/E//O8fHZ5z8tpn7zX4D/7Sj+G//O4PRr/fyWIQzqsZ0tAJAtkE8KX8IndvZlD7iatNfNcM+oFsSZHx+QCwy18/ZtiVQifS9h8pHqQXVMymiRh2CcPY0gZoMka1EnwpzIkHDLsuBlYqPTwm2lyujebURQ6dSALS6HOJ/VCSyNZaMTjZ7kLoBM9JA3g5VgH4zIROdBaH8As3kv35mgmmT0iJDd+lxf2zYhH57J3gt3r7nmcRbcWw23wPKHm9nwDY9QXm3iQPu1zohASSJRg9YNiRpxYx7HZfEjvXxHwLgF1DHnay/DV4m1+4d6XN1gHb229IGve603UMDKbG/lFwQM6rkzenqgFgd+fEHeONvdq1ZSmJHXjYeQDi+EX/c/ysxB524XOOV91GdQdXhmFHwNNeCRDybVp35GEXZIjSD3AgidVhXnjZJbG96BcGfZlQ5dH8ywWjJJuTusK6s9HGfSoJzgXruC/zgF01lMQSdlEC7EwK/Pp7TOudoYfdONvx9v3VSOiEgib2qI3XxRoZpVYb2gz1hfd630f1bZmwg3iza0pVfnw9vWweduoMDLsSSyyqZMLUc5JXLEEEAFOPMOyMCkyVLpnAAzHDBIDSeU8nfn2SEmsnSWIrGB2Oo2vj42hhhjrypALDrnRc7vc6kWFkQzcEUDhA10uGzVehhIddbRR3Ogye0AOdFi9YKyxqN1ivGSxoIqCjQcUPtVJKeCJu72HXev83oxUP3HTMrfz+KSUAjfmFM+wCAEzticDQlfYDqqccH2k38EeS2FkC2O0yIyUpBuwEU21mNFY2fk6XiBl29TYJw0KOPTMa1YiHHU34Ox86EfV/8roXGLv0em1bwNognRXnx8nb5wmu8c/i0s6g1DCRalbp+BmMWIZ+F1YptmqwOYbdjkhiZT18bY4/8MvfCgD4wDOOnfmHf/XbsaidXP/zHr12tmTqUvU9iD3cweDNHrB74tae2IwYylhbGLzpgX3URkMpxczA7/MBEf/Bl7wBN/dnMFrhrQ8f5if54rM+71G3gHjgYIZv/OI3AAD+kU+e/e2ewUevOWUPu9QsXONLv/Wf4zv+7aeH31U8f/eaX3jJTTw/fnuEveh/99Srrq198tXM4nrXKgHoBww7kspkGHa10ZgbYtjFigSDPgAVJImV4J/47tJ4wME3Oh8cVjR815VIvgzHTYBdZVRoOxMZdhEzid67ISWWALY6kcRaGxb8NK+bVUISSyBbsiCnY6A5QrowlQs0skhpL0Bk85qXoTm5l8RuZNj5eXZGbtX1FtcIsFtcj/4Wh06Q39/Qyw0AOjH2HK/D871akyR287iyTUqsTT2sZdue6GHHflgjzH0J6lLReTedjcHo1MOOQidAkrpdZth5C5qMVJU97DJ1i0PpNoBWdO34e+C/RwB2dsiwi30ucww7EfiRrD0IsLu5H6f7SrkoAygpo67oYbeKvvN03ZXnHykhwjO56BxXbc+S3VRRwV9LgN2IJLbOhk7ULAm97IAdP79GDf04eS5TsWVOHIwSLHjWbR8RRuoElM0FzLgvc/dJ+YBAmRIbALuCZDk9XmLYec9uun/Bm2/8Xtw9bQTDzm/Q2aEklhh28ToyaW8kya4WfBxHvZDtjyTFMnt9w2YRFY2vy8vqYZeGHWRfmu4SjRQtBJlZRv/PMezGPOyEJLbLvjdhkFBIQwFg4bAK34gGQKL8LJF+ppRiliAzDAXQsRGwU+PgikqARKooVCMB7HIMO62vMmAXFoC1cec+q7T3yQIzb0rvo2CARer/ljDs5EPN92MbwM4n1rQm+L0Re4kmCo38/inlj3HtU2LnlR4GZ5y1onbsjo+AkKXei156pNxEQEpi57VBDx0GlysE2AWmWsqwiyezp3YepS7FgSWbPOwCWDWvNGZykyIF7ISE1UliJcNuCJaoUuiE+zCgowlC+D1tLpyLpSuCIQ5mVeQPAXj2XMSwkyxD4VFFi3nJsPNg4Aoz7O+QJJbqj/6az8c3f+1b8TkP7uObv+at+N1f+Wb+2+c+ei1clwsB7MJnEAgHAE/c3Mu3McEOeMtDYZL/H3/5G1k28KYH9vEnvuEd/Le3P3KYN0IX/Qqx5wDgj/+6d+CtD7vP/uq3P4j/+F1PAnALkYevzYesZv//o0Zh3fZ4z1N+YjaFgeifvftry9dgcJxUfgwmht+FeYS+nqWGIBwAAWhJDzti2AVp5oySTRMPO4M+zHlIbku+wNazDErAmy/Ti8WprA2SWCgjJDmBGcgMuyjpNfXw9AuP5LPDrr8Ox5sy7BK2BC2cmGEn5oD0bClx3ckXhxfEBHjaOPWPFrupJFSyxohh1+xC6ATPyb0kdhPDbiwl1lpcU37hNr8R/U2asgdD9vBdcq7cqvBsE8gAAMsVeYhNYNh1YeG5qSwvmOM5fO67SumzDPaMMOxyrBv2vpOhE6YWQKEF+i6A1uRhZ3bfw25hvBdVEgbBm6u/9r91//8VfxIA8Jt+0RN49PocNw78vDdSLQTrHL52/v/8PW0fPCmhhxuVku2Y9bATgGDCJL/jE2IpyVZuYAS5vgdQFvGzUU6JXUffebxuy2NkOq/3czI6x2UTpJ0lwI42eZhhlw2d2OBhd8klsTIFteRh19pgmVOhEx52MYMzqCD60L+18XgxTIl1IJuqMx52HrspMSAH/qFtbG0TGHZlD7tjYTFQGSXA4ZjJa7TiTRzyilvaAmDXNeHa1Hs81q6tCl6U6zJgt86kho+V8UDiaXux4+u59UAsBR2RpVJ1qgLsNEksLQSp4Q3CHTLJlLmqjMIKZJjoYY6M5xaV2hA6MQDG6LhykthENtIlwRF96yx/WxjsbaDFM1OkyLDz4GByLaJAjsTTp4Me0vH5/HdYxlOqDEC6Vxus1sSwO82/LwFEnIedZNiFe5IGiAQJ4RaLZ+9hlwtomBkNpURHPJlhF1hYThJrcHSWQIxcCV80OneSGp6q/eild6zrHA+S0Ak6thn68wOIl6hyDLsodMLXKWZJGpjOgxi54sCFIIldFRiYVrSDWmsOCRm8llkiaf8oAbuGJbYSkNRJwuGZyoPnp5hlJ2/zWgJ2TaDL2ypiRfRmBljAdpJhF+S2+4WJx2UurRW+5RveiW/5hncO/vbWhw7wPgasLgAoSgG7B0kSu8DHR1lxGm98IDz7h/MK//gP/zJ84Om7+MLHb0T39M0P7GOVBf8CE/xzBPj3+M09/PP/69fgw8/fxzseuxYtLj/nwX20zybH5ds17XZuxUAUi7SN76VNRmLSXyTT8fUqCpmBW2ymvnPEpo0YdrAArGPYaQv0GPiuVegEw86rA8TmYttbzDZsHgaGXSqJLYxrAmSMJbEBsDNaeblYIl3zZf0Gh7F5D7s6ksSmDLtYLjRIiRVzscCwc8dcG4Vq4GFXYNiRz22yGIrMzAmwszvQ/2mSIbvz3JQSO+Zh1/V9kMQmDDsZOtFmTMaj+6PCtT8VC8zAsJviYbcFw44UNkmf5pKv43sYFrR5OWVRsgjBuhFjaAQaCMZSdI5dEwCAKxE64a4RSWJXbcfjaWeFJPYr/xDw9q8DHvxcAMAj1xf493/y64D/9yFwiuwGlPv8xMNOS2AwzKdT6WHFoJNk2InPZXlqRhIrE2IBSElsnUoU9x6Ir0ciHw9BALEk1jHsSv1vMh/xczLyq7u3bBhMK83LAsPOP2e1AOz83LRGKxLIw8YLnWPaL162kimoEVgO8DVsVcXX2SiL5bqBtZY3eKCHc5DUw66cEusZdllJrO+DN0iWu966dumvvwPs1sL+obypcvsozNUVMJDEyn6TNnFOvQ/9WoY8yPVMI9b29T4qLcC//UOgOR5NiuW+baIklohdp51G39tsou5Z6gIlsZsZdkE+Ol0SywMVecUllPDeKlSpn4CoWjDs+oTZBgB1YUGqCwALTXSImcfMtxHAjhawwYfPT7D88XR2AsOOJ6H5a8dS3WSiEIVqJIyDDmYQKc8A0y4vMkolFoAzBpYMlsR2KmnYqZO0DrBb1DoOfWD2moHRMWuRFjSqb0dNLaNae3aRB+yuCTaaUgrz6gwJr76zW0Mw7C5KEit2BFNJ7ImKGXZ3rFvESxCSdthaNc6o2MnKAXZSzukr9bCbVUqwKDc8iwlztBJhJyloRgxlqwy0VpjPquCHmPGwSxcecUhFi5BaJdoog/7nSYkNktiDDGA3M0YwRANo3sjdbwhD+owkdmnrornxrtbbHjkUDLsL2HQRbU8ZgzfccM/zEzf389Iqsdh48lb87M8rgy//nAcGAOybHtgfDbDooPH4zfizKqPxRU/cGPivPHlrP6QrsyQ2lv9txUAUY8YXPXFdLHbLHnYtNN75huvi+d3hzS8JxMOGeUoiGZUpsUDwqKt1kFPL12vJsEtSYgEPHJS86Oh4aI44YNjROJJcd+FhF+3wM2AnvY/ykljLktgRD7vCJnYqF0oZVnIOSG2Y5pCzSqNSQRnh/hi3L5IX8Xg6kMSGBRrNF3cjdMJfcz8n35QSW6UsD1FdD1xnht2YJLYMXAGBQAAAq3Uz/Pc2HnYb5v4A+F4PQicy31Ni2A0lsRnAjhamUUqsAJqlJDbZvAspsXHK5E7WwMOuF/MszV7S0Bp4+PMD2zV5f3SN5Tw78bDLMfk66CFgJ9s2q3fkvI3AMyGJ9c/6XZLEEsNO3MuBV9p+AtjtPxj/XAnlgpDEOobdBkks+c759S+tBW7fD5sgZYYdediRJFYy7NznVOjCHDAj+73Mkti+t7xMlCmxwcMutA1pZ6Bs71hgbFHjx2URMJOef9sPn3X3Andtlb+266wkdhPDzkYWU6Qoor+PedhROAoAx15OJLFdxLAjSaw/N6vC2rwbqmoABVTz4OfZ2QBGj0himZ0+lWHnAbsempOPL6IuALATFOkNtY0klh92AvkS6Sl9RptjiYkyWvEkO/WOa6yBSRBTzYyogtEx7ywnQOJYSqwpMOy6ILXcSLVkwLLEsPMStgHDTgJ2qaePGTRAvYFhuNMlgEqahOzNDJbkJ9aMM+yICj+vTczuYSPQjCegBLKnAhheErv0AQ0SsANcZxk6pYn3KfKwM2cD/UolrmstrisAHNt4of1K75gyh0KKKBl27oOuEmA3nFjXWrOnA9USszAJBDHspnrYicCFyoGmXWEXnftPfzwzGW4hrnsIsYkHZpNI7HnHX0hnz8QqTYvj4GdZUC32sAuTxrUInQCA3u8EqwiwI/befCclsWP11ocOxCTtYiWxj9045AnX4zcX3D5tAWR7IgHZSvXGB/bH5bVW44mb0wzMY6luPN411uBgZs7MsPvGL36c39vl+ihhNfH1X/AoP4OTNigva4nn37HikqCIjIcd4AC7eaV5wTtk2InQiSQlFvAsiA0MO5LETk+JFYu3nCRW9WHxUmLYGWLYxfc0YssV3psuigNg46VNUnIJvzAFMew0jEpk2cmCnFM6a3FPcscoQifWuxA6QZJY4ec3+vINDLtr8IDdwMPOy6Ra6WEnGXbi/gjpVSMUQ+utPOymy6yCh3XiYZdZd3HK5CB0wjPlRjzsckBlxIaRYLSc23ZNRhK7+x52c2K+rZsgPU9sb8beH49nGd/BBBhcJV55Oe9egFhPmbA8+ndOEnvq/sYedmJTInh6+jVKyrDbfyj+Ocuwm+Fk3W327yM/PM+wI7XNy8deiqnKLFoGfEgxEaXEetmlGo5TLnTi8nvYyT5bazW8L8JPnTfB4MZb6bNIm2dsRdG3g9CNIsPOr4P1zAGrMiWWNvwXhfsTpdqKOTdJVel8xjzsToXFwKrtg0dtAthVKmAspz19bx9b5fA5+T6/3gNUAoRSwMq6zLDLhRCNFeFEDUxI8L2AujDALmV25WrgQzfhc2mgorRY6ydpbUsT6WqUUl4LP6eWbqDoENPBkgAvU2TY0eTSH89I4lxgvXmgjlBvZtgFA/hNSVF2w+RVZya9gAPsOtpFJUPKEQ+7kIK2w6yAUmXu+7zSgmG32cNuZnQMdnUNg2aNAKyodA4w3VReEnuq3GAk2Wh0zCFBdEsPO2LY1SYL1JypxKKWrisx7F5RsRfG7Y4YdmGyxybZF3U8l6isYHVQ1VVGEmvnkcFwZXRg82y6HtK/zWgPwhVAiWQxGQO34rWF0IkoxKZr+buj0CFN7JBzTIw4ybXOBkMMU2LDREY+g5YAu8zg7cDAKwbYPXwQ5JtTrCc2lWgTjz9wyP9+7PqCWSZNM2RmdtB44tY0wO5ND+5zXyTBv7YNGyUpw65UT97aK6bCdzD4le94hP/ebrFx2EHjCx6/jluHe+X32sAu/OInbuDB6/vxcexiyTAZGRThn23FHnb94LW10YJhF7PCdC50Qmw2dlM87AgYKKbEJu8TbGcjwTMdjoklL8nCJ3ypmytUhdAJo3VREhsYdnnTbyUWEgS6Sw+7CgnDLpl7bgqdkAAhM+x2wcNOx6qXTYDdmNyq7S2uqfGU2HUnU2KFWiICVMWmkOgLzsKwS6Wr2UpD5woMUKAMBBIwXNrMk8eUC9uIU2LraE6DvhWS2KvDsCMPzuU6PO8dTLS5Ovb+OBAiI4n18yuSxJ4mXnmLNHRCyjqZeSRZfIJAw/2DayuvcujEUBJLbYP9Q/duxedzkAB2kmHHn1PhZCVDJwoedgSQtATYueMkKeRebYJn8YsfBr7n/+j+jwAumZGU2GzohKnjhN1LWr1QYVVaDe+LYPG3ArCrKHgiwU1k8EidhG7kEqHdHwiwkww7Ihu5z5/GsPP9rK7ReECN+tAxD7sU4FonABz3mwjP1rILLOCscoz86T3AGyVfT2LYFa5VoZSYN14ywM5dFDWBYdenu0SjLw7ac0Ay7DzV0C9GpAwve3xKCWabb8yiQxyELvjzKDHsOHSCgJhElhB9N01qyUw5SXoKiY1m8y7bJsCOjyve1aq0GjAKiB3QWjMACj87GHaaJ2d7MxPAk4kMu0Vt4tCHPvw93RmKgOypCzcPKBxbD9gt4mdrkTL8ppTwORtIYs/tYTe8rgSEvAQx8Fd7uLN2vz8QzCaW8HBHe3U87HILP+cxN0yJjRh2Wo0b3EffEfqzWeUksSX/O9vFC4qSNJoGnDR1ujIGrWRwsSwtvM6QDPw8fQib1c6xPx8uSgbHLVNi5TPICYNDevwSM/ZavCq1P6twcwxU2rYEO+1J4UlXGY3DPW9KLAA7ObZMBdkeu77gcZRN2wGs/SJpMc+zLHP1xK1MGIbonz/v0Wt8fZpmcz9jRUjLk7f28JAH4WguEZWQTL3pgX288SHH4FG2m26HcNlKjF8xw47sPtzfpbQUcDv+s0pj7pNNWUIoZEvDzzKgX7ViV7845yE7ltTcvuhhF+aUtfSTk0EYGWZGVFUsz6SKZIiF96YyoNwiIGVBEROuNsF3jvtfPs84dZbYD+liKPL+oZTYnWDYuWteY5ok1kiWR1IuJTYviZ2JBT2zT5L5MYOuiJ8LKu5TpoTwFaSruVIpYNeVgcGSNx6tk4qbeZAy7Xi+wp8rv1cpyKRSloXTs3EFQidmHkiTsmfygR5/f2b+JVVjBEj56zdTQ0lsL6W3vhhoiPpHCQqSPLUe9J9jktgoUKW3wN5NeAcxV6MMuyCJPWnGGHb+dRRg4b//wI/tL90nTztxbf/pnwA++D3AX/2VgLX8bJueADvJsAv9xDB0IswLm/byjsVyk8EISSwA520n7JkkYGcoeMLjFpbS2GlebqUk1sJam02Edi+IGXZNxLBz17MUOlExc04w7Oq9QV83tqmyLAJ2TfhsOJY+1SmlxHYWa1pbZRl27pwiYHEbSewU+wIgIvlIxuB56/yAHXfOEwC71Idu9MViJwdBesqT4i6AXZtMW2nxSoyDTjDbjEoBOz95Kyw2aQJFgN0Y802nHnYM2A1lvZtMCdkjsCQPSaS6VJVRA8YBSYM76IGH3SZJ8E4XtR0bANKtPOxIEhsx7AJokbJ7gCS1dyow5qm5x9YNijmG3dZgWyKbnNdmOoNrU9Guj7yufhB+wd4Mr3vgrZwAJGW+tFuztuMLtJ0sYrWKifXMaBwjlvidYhZNAmuREttvTIkdSmKLk6bE42JWkkYnKZB8XJWKX+9fF6XJch9yAQy7gofdfMCwE9dAPoMVMexyHnazCDi+KvXITSc5yYJK25YA45+8FQfIUBJeKwC7k6WXtZgKDx5Mk0QZrXDdf9ZyFe7T2i9+OXFvQj15a5/ll8zWE4D2mx7Yx4PX3Hl0EwBNkriRxPcB/96cBQYxDXur8YabC7zpIQEI7CpjXfRbLtk1ZS541YBIiaXX1kajIoZdAjIZJT5LsJDpd00vJLEF2wdm2KVzT2bmpR52ZMgtPOz6njdT6Jij8ytIYitbYtht42E3XDAxOOJVETSHnFeaFyh8LRP/5JY97PziJZEbBRBKcerveic87Nx1rBGuxViNLQb7do095e9dkoRJm43WhkVjOp/jdiOWThKwW5+JYTfhHtAaIunTtvOw84AksSozc/wx776mC4BBmnKKPoRO8HNZ7bIk1l1vAuzWEcNOb2yDyK3XcjLmBBhcNn0kvU0ZdjMBugSGnf9cK+/PbADYvXKcSmLDGlsCEc4/1AAHD4cvHjDsKCU2kcSu2jKDkxl2HiBJJLG3jyg1VqytPv4j7t/NCXD0IiqtoNAHhrNIibViMyh4kQobBAbkL+9Y3HUxYBfJ8DsbzWW6qA/qPTuTADs/BzfhXkivura3YsMoD9iZuZtHrloJ2JGH3bhkue36QICp5iJIQ0f/z/XRJwnAte5jIgf3b8KW4qQLktiUkSfPiQBeuhbWAnaCJJZDiCaGTsh5cwpAnqcugGGXl07ligG7CRPlNGE1pRj3TQBRNslJCbAioKwTUpu0sZIsQ+cAq773CWiCeTIiiVV+ICf2oU2SbkkaKw1si8XhBflrV0qJNXq4eO+7AFiWJMHZ89/1Eg8Rdd6L2mBJfmLFlNggeZ0ZnTDcghwvK4k9C8POS2Lv9+64ch5226fECg+7ygwBj/NU5rpSytOzvWDYPfR23PeA3cF8CNgFxtQVYtglsnjATZyJPUm1tHHohAPa/aCyqb+k9mcNS2JLPl02kdLE0tLwWtqISZnTMsTHMexosibkcGOg//Ft4OjF8fMBJnnYRe23p2tQYVaFPk35iaWOBm/hYXfFJLEA8MgNN9G6EO80MUFMQyRuZJh8p54hd7A3D7KWCUWst5VYGBEAtg1g94YbC26fJ8vYAsMl1+7hwevu+nQTAM2jU7eomM9cinMA7IbvvX8awMpr8wpvuBUkxDu7CZGw5ni+kKTEdomHnfYMO5KUdcQwlmy2dFGlgqduJxekRQ+7EsNus4ddJVlDIiWWJ+QlQIQ97KYw7IZzMSDnYZcBR2yQ6QJeEqtoIR9fy9TDjj1hRxh21Dc3/bmXAK99+etYTWXYEcsjI31TclGWSGLl59KiMWVUMOhqwYBpnmE3xcNuOsOO1ldBErvZwy4FAmmdVNzME++V16KWrK4ueS4Ew66h72USxy4Ddn5+5H0jm3XYSKKN+ynvj65xTirv7x8Ddm0cOpGmcVbSh00HsNSBdWK+pav4GKxlj7iHDufxsZkqWkNziqrs+649Fp+fTO4UKbHOw67A4KQ5GHnYeQINbZrS88BzsqPn4/e/+LMwWmEupJAydILadYVuuLEkPewuMcOuE0x8o1TCfOyjtaZDGGizqYsAO/KuY4WXkMQCrv20DM4nbbnJSWJjhl1JEhttShEBpsow7MY87BKAa2kLgJ3od1d+E6LpbRxGR9XGISWSqNTXvj2OMOzWBcZ1sYQy41IBdiQN0Hpz5xzYaGeRxMYDVidkihsZdknCEgFlXQ5gIQ835AC70AGFlNjwQKQVGHZ5SWxg+k2Q+5SSz+h4UJCwaY3eU5t7v7PQtcFrJ50s6MTg90qVSPzjcATJsGtKHnZEQw6BDdwp9E3E3EsneOZMHnYOrLjXueMaZ9htB9iRh10s6704SSwDdn7Q/XQrALtHvpAZdvKc9phhd0GMv8tU/RCwm1UaR4hBiOMkJTZi2G0KFpEedhWlxI7vctJAPpNeeaItpeE6ueNC3wmv0dDv0K7eAPTvGuDbfznwF38xcO/Z8XNqCVTL+8zNjA6MzFQSK/t0v5jXtg3PX0Ny25qZoFepHrnpFqI5UGnrEr6fKWB368CBzq0Avk49SHa4Ny0kgj/LA3ZruTDyn0t/m1KL2qDym053jl0/SovoDgZvfGAfD99wQFopwEnW8alrh/v+fB6+UfalO/Kvnc1qKKXwhgcEILCryddKCQZaN0h2pX6kEUw199rebR6olBXm/l+hEwEPYROBASuZErvBw25gx1J6n/CwC2beJUlsnmFM/UnKsCNmktGqKFdMDcSZkaQz4IifszkZrEVtNG8WB8Cu5GFH7IW8h537LM8c2gXAjqVu3UAmlqsxhp1Z3wMArNRiAHblALt0Qz8KtCCTe7FWYLbxBoadtZYXnpvUNYCQxFKbLrVPiAVtcuzctmzy3ImSLEyqCGhOgWwTxuCOJbGC5bWrxcw3D2xL24dJDLvM/CtHbvGvm/sE6Cgl1g5DJ6iNttLjkz5bbkpKhh0A2B4vewbbg4cEtgUAUd5vlpI/8Jbw/tSPMGLYBRn4yboNiq7UCoLaLktiY4Yd1TWyAErniC9+CJVW2INQSxQAu9kAsAsedpc7dMLbaCnXL8g+qRMedrTR0vOmQY/lWnjYkVesZNiJz2paK1Ji8wy72jPspCSW+p8USKbKethVcx7rqK+Lxt+kUgnpKlkXsver72fW1qDrXZ/adiJ0Igqao2PZi74fAHpi2K3GGHZnk8R21gwYg+epC/Swm8Kw80yzKaETbHpO4Q5V9H1S1rrxe5EHytpM6IIeC52QgB15vWnROSVFkyKVJsoSs46OZwLDTo1NXq3lSUNVp55TgWFHIGcAOzPnb64uw84KYIkmM4taeNgVGXYBDCCGXSSJFeBxCgBXxoTQj6nX1O8C3+nykthFbUJK2WSGXQB15rWOgysuSBIrU3IpJfZOUwG//18AX/+twC/5QzjKAHaLKwzYUT8mJbHzynnY8fkCuGsPol0rCYxtBBYSyXZtpG9l0uYSz7l5rbNsTZUw8ahkf+ISkj0TT7wuMOySidHdp4H7zwLr+8BP/e3xcyJQzc6ySa7zOh86QaAll/Q48QO49c/5qZ1n5ba7Xo95Say6AMCubdw1cwy7WBJ769D7uYl2Q5LW6/vbAXbEXIv88Pw4Td8zteYztyC5d+wAtFfvO+CuVxUePpzjEQbdNvczJPE93HMTvYeu07Ud9uXHnmG38N//xINXgGEHhBTViGHnrUFIEtvZCNwjhl2tUpCp4r8zoMBqirDhI4G00kZXVZLebfSwq+LEVj4/YVaeKjzoUvj5YVVk2GlIE3ZZNNciA3H2EMow7No+9EssL6bQCZpP8PVJPOwmMOw4xe7ykk1CGTKTbzencyIB1ZLSa8eiONUHg7/J+3B/6e5v6lUWfTZJ8FRon30BrE1LHtv5POwyDLsMEAwEJk0zkiLOwRHSV5GfyT4jiSV5pZDEjrD/dqb89ab+i+wZWs9s2uxhl2HY9Zm2QUEJ7GHXR/PplMlUS4ZdBNg18XgmQyfgxtJXThLATvSHWqvYPxQAfsNfBN78y4Df+0PD82PAbikCymYxww4IfXffBUuCJHQiXd/c2CsAdveehdEKC4i2L8+RADvVDdnb2kShMpe1aI+F+gTZNUhJOpEtSLVoVOfYmf5eEObBiru+i/qZddcH1lghdKJaeGsVGxjy1m+ilpQpxEDrreVNd9QLZg7SMaRsc1kpI+00kcTSNaI8AVoHNJ0DIfMpsXQse9H3A0BXkyR2zMNu2C+OFnvYXSxgd256ATGxVDWhcy6ld2VqkD6bMNm2Yad1qgIs2DOOwx6sGXjYGQLscgw7AbgYBhIFcJMUJ7ea2MOOgCPyGKKHa6wI9MstFCAWxqkkttIKS5GKV0MAhTAD2ZK60oBdB4UYWFvUeoKHXaC3kofdKhM60Xj2miwCOAza6Ys2L4m927p7cZhIYovJnmNFDDsrJbFbsvRKJSRnFTPs3DGfNh3w5Je7/wBm2B1kGHYXJtG9TFVg2AEKR9jDA3Dg7F0cRm3HaMX9gt10f0QC8MzohAWXX7QGhp3JtgPFzOmUYRdL7IN0NrxOcehE0ofceSr8+94z4+fELLgZrucksSaVpQfJtxxUtdwZ7lZAV/PYcooZA8tXqUiKeREs6Zfvn+BRuLHi4cN4l/2Ba27yIxmgJGm9tiVgR4mqbRRg0frv2Q6wW8xnwCoAdi/fO8EjAKrKMd8eueknaBP6zlMPQF7bd+dOYF+OgX/swb3F3I0nTz4QPOxOlivsTycKXq7SFdA3qNTQw45DJ2jirQxgewaZaCGaBiXEoRM9v7cyfiyRDLvCfFGXpHclNYIABiO2m5DE5ryPovL9SbqhG8lbebMj3TwVbAkrPIQEsMIpkMLwvUKHWRVCJ0guy4xGWhz4BRixH9LFUCtkSdQ3r3chdEIAYwM2SKbGGXZuUbbUwz5FKeWY212P+0vPJEnmc5H3kvDMorKldpNUai6/sVJ5+Fk87PzPzKrMSmKHHna1vJ5FSWwbpLhXgmHnniHqv5p1YGkDE7yscnL+HMjK0lvJsAvz6VJKrNvQEJ8jVAb8HTp896tHJ7B+T+WB/QCyumP17dhorNs+tM2H3g783n9cOD8/F5AScy+JtXI927fu8+WcngA7/7vrSajedVrvZAC7aqawIA/KOn6G1/57a7QZpnS1Uww76hOUcj52be8ZuRwC5oExwSo8XfdA7TEFYtgJ2wTZvzlJLIFQeYZdNQ/Xt4OBQejfSoAdDWVtb6Nk1q6JZfrVSDBQCnAtuxiwCwy7sC4HwOdE7SBOiaXQCTcJk35+20hitwXsOmgmqVxEnXu0polLKsXMVUh63XwCKqF8W2FuCoRFQjcB7ErDHoIkdhj2QICVyXrYCYadZ7IpZpPkADuCgolhF58/p8VO8bDznXOWNREx/3Iedv7h4LALeqiHtz9IYq8eYBceIsEEqw1W5GHXnObT/ASDjuSkkbGl0KunD3QdJXZuB9i92rh7eT0F7KSc9UwedhrzKmEJnqei6xpLYk/W8WfTzrXcVaNJcTb8YNcrkcUDfsGkgGMbVvD37P6AZp7aABQrSTGujWbj3/S9vBFigoddrh0ET8wxSWzD/bSUpdG5DvqQu58O/z55efyc2gDYZSWxkYddE1+DCLCr0RMjpV1FSdCNnk9ibOxaPe6BIm27c/tnvHjH9UXW78LLIsBOtjEOithCxgoAD7OvXHj2iYn/wPXtPosAs/teovrqkTuH2o/ZjzGg2QU2QaEotfa6R9seuRHeu2qTnWAP2O3P3WLmxv6Mx97nXy3LLS596eCnZpKFUORhJ15L4BeHTgwYdjbrMxQtSJM5X1q1l6WqAWBX8rALi7dKAi+CFZhLF5RF31Xb+JgikGSDJJZen5PZsGxRSFXpuPSAYRerO+gYeAMsadv0fUZZKC+v3QkPO3/NZ2gx28RsQgDVcotB07jncGkOB38DwvWnRdZgAzbHsBOAHQf9bPCw68U8c4ovEltTMGNpzMPOs1+TzXhmr5b8bQsgcgRSliSxfcPtS/dXAbAjhl0siaVrt1kSm2PY0QZDNXhdlUmJ7VCWxK4HDLug9IEyDjkR/c+r992859b+LPS7DL561vCITHFQxGoWMkJrnCS2TQE7IAbsSBLrCRK3DuI2zAy7Y+91fPCI+//952G0DpLYOt4U7Biw6wIRRfTFUWDHJS1mQYtnN7DBg4ckqXOsGG+dh51rR5wSW8XtUDI025wvW98zM65eBBZyyAFwz0PZw84z8SzQC8CuTc4rOqekUg87mRJrrQVPNWwgygCu3bZ9nyd+tDHDTvs1GAC0tbcumSCJHQR0lEqQfI6WF7eevQAPO1qwbe6c+w1Jp7KY4ZFKT5md5nc8MqDT4HsT7zhm2GWAsmqMYSd2bCsC4UZkGzTBMrTwJkksydK2AezoOuRYEwK0MannlNacmsdAHQF3GbCTQzdy57/jZRlY09yx7M2EJBY2z+4SDLpZ5QbROCW2LImtowCAidfU7wa83JCHXTygLSTYNtnDLrCw5nQOGe+yM5XonFJJ7LLp0fsetul6lziEGLDTWmFeJZ5kV6RCeE541pRy5yunDXdxgEUyCbQTU7VtH4NVUhLbp+/lSaOXxEppdMSwGwJxgNuF7YQHTs4SgUA+hWQwvvt0+Pfx7dFz4pTYkdCJCDQXz6h8BueVlLwHwK63CtVssVUwwq4UBTjMVIdnXj0512e9dM+9X2WYHCQPhe0YHGh8SuLNg+1YcQ/5oAz0Le4tG/d5vr/m75lYBJgdnbg29MqRu+czL1V9yDP2DDo8f6/gW+qLPPUoxfbGgfcwQ4/n7sTvPfHg3t4iMBFpjH3uCgB2Ufoe9w8xm4u9cxRJYhOGnTDqTwMsXEqsmMiXgDdfhtUdZwDsMt9T5YIwUkks+6k1vLkn/chcSmweTIkNxC1GQyfE1JzYisywS0Mn+tb596QedgVJLMn8AKC5vGSTUMIrbiNQgnGGXcUMu3yfQptm9/wiK12YRlKujIfda8WwUwOG3QQPuzR0wrezdcHDTgKcWRA5J4mVoRPkU3UlGHYE2Pn+q4kZdqWUzPD+zCZ9rm0kTL4YsDOD9h7dC+3kue7FTVi78L0RgJ0fA6Pk9uR4qL2k6dLZyjDsVr1x8slIEkuAnbgOCcNuXploPcCA3emr7v+PfoH7//3nYDSwACXExoAd+YrL51G2VwpduMwMu2gc8RVtYhHDbuBhR6ETMZGJCTz+Wa+rwDJsMuMPA1twDDsGtSgAbwPDTh53vybfuEXwtzSxh12XAU/TTeYVrQvbVWwlYEl26iWxvWPYhdAJKYn182CRKszHUPm56khKLPVtkzf4JWB3mRh2HDqxhSS2lHQqKyx0486HGCJB1rlZEsvSMpLEjrDz6DwqdEO2FRsJKhh/47bysEsYhoFht/kcaMDeyLCr40FSi5TYlkM3ykChucIMO5YiQ/PAt5ChE0DEwOESDLqZSdhpfWD3NDDcIVJVWvqJTXhwreWO4/ba3YuBJLaW/nPbSWKdh53BvDIXJ0GV3oA6ZtgBYcfkWHRcqdHsmZJvd6BURhILuI5fi4XTErOhkasZX7BS2TbInZlhx4BdwrBLUmtnUhpN173vue9KNwBmA0ksfZ4InRAsGsjJ3/Je+PfJJsAueNgdZDzsZkZHA3N6Dfh1KbC3IX32KpQEWZ96+XxA0e27jp2Who8AwA3POjPo8MK9pTP89WPMtjLWPc+KM+jx1MsnePbOKQMU24ROAMDengfsvKfcXb9YmXsgL4zxPT79SsG3FA6IWXsp1M1Dtzigdq6VxfN3YzCU2Hj78zCe0Bj7wp1dBuy8Tw764IvFDDv3t8Cw0/zamZDEBoZdYOsFNtswDKKRHnaFMY5Zbqkhui6MIyKNNg6d8IsblTmmlGEnv4vGvciPTBfZeRHDrrNC/hT6q2AqL0A87wdIz0MKfqLvILEp8tcqhU4Q6xEAlrvAsBNMtimm38FnbrgwrxoH2K0KDDvaNLt7QubqQ4sT/mwd1goE4NhUMloouVCd5GFn4vXPmIcd+UWZ5FqxJLAgiZUgopRvVxFgF7OyJAuWQzSuEMOOmG80rtGzN9nDTvZdIymxlfSwo9Rn6AFgHPwEbfR+t2mZWAQIMssrxx6wO5SAXQy+RsnZm4r6weVdPqcTapo5DztaYygTgDZhQSRZdtdTwO4RAuyeh1EKc+WPO5HENorATwnYheeR2YntbgF2ceiLO/eVb4e0qc+hE+xhlzDsfAAIrc/WrWR4i/sl1r+q3meAqk18L/c2pMQCgmFXL0AYaeph12TaWho6IYkcso8iUhHjGwMPOymJjRl20TFUfiwYkcQ220piheLnaHWJQieCdGqKJDb4HUz9XGZuEGBFDdKzxaYENhAgxkDdCMMuArwKhu0tTKCRsiQ2A9jZeNFrVVjoynOYwrAbk95GzL96eB8YsPSNyI4AlmYsdGPXixN0KmbWkLyVknSzPnbC6JMYdmuJ4osU2Vk6SariVM2N1S7Zk/D2ygN2KbhV5X3HRiuVxNYCqLF9DKxsWyLVinaxpPcGeRLQTsOs0gMPkL36AgHEy1S2ANhVBtbKtqIGu6lpSE35K2hwCIBdKWGWGXG+L55VkmnZRscMZBh2Og6pUJn+PwJ3ZL8oTV03MewiSexw8RO1367hzQ/J8qTzWzPDbsmA3QnmVxawk4vFZ14pT0Km1Ms+sCE3vhOTskKP5+4u8dzdJVtJbBs6IRfln37lBJ96+QRG0bOz3X069Aw3Coy459NiF7N58l0tnh5hIL560nCfzYxB8Ry/eDcG4QiwO5AJuf67SFq8kyVCJ9hDjAA79rDrB6+dVRoVhU54AMpKD7skcVZKVaXksMiwA7F7E2AgYRVwiSCJSOZHrMCsJDZh2Ek2n58rRGwpowZSM/5bxLATHkKSTUGSJZsAdpJhZ+O5J2DRiKRmAo9S6Rcz7GSqab8ZLHrdS4ZOnJNhN2vdptGqKgB2zLAjSWyeYdf1iJinNEeb9b4/mciwozTITaXF5p21GWmq/GyWtSYMO/KwK4ROSOZRlWH4dHIuQccjgCmW4vYJ02sXi+8tMexis/+N7TCnJssxbxNZ9bINLKk+A9jR3IaDE3QATAdSfKX43xS89JD0oU3A5bBZMoVhR0mz5Ce3xxvys6oa+GsG9t8syGnFPJ999ZBh2D38Dvf/9hQH9rgoiSVvz4hhJ84xkhNf0mLpaCY5XHrYsSRWBCZJhh172CVJwjPBLG9y/UTj5ynVAtCaAbvU1qnk/Rwx7JoMw26Ch90qAVQJnES3jl5v+rDuATxrsOvjDXo+r9jDDgg+dl212cOu2VoSS8ExGkerSySJNYl0dfzbhtKrUqVeSyqZvDE7bQsPOzvhvVXqCxB9UEjvYVPIhPkni2S1tOhNPan4eLZg2Okc6EOfYxUHXMiiHY/Oe+7QIt5mgEI9Jgne9fLnLReAbqdAoVGUejRkXDAgYil0QoJLLX8uAXqy6m0ZduuwgHzJM+yu5Rh22yaqtjFg5xht4nPPI4v1AGMLw52g1op3YU4TwO7afNjeFxKA2eVExaRU4mNJNa80/pv2dwEA3qu/iH8XvbeUdpiU5XvrGKBGK/anTOW0zPjzYEsUYMIMu/B9Aw+7JPBEs/l86Eu07INkfyUHxOWdcQDb74idljzsTJwS2/vFcyqJrY0Wktg1P1+ndl6k9e98ScDu9r2RF26uV+65CZzJbcgJoOPZO6d46pUTTkycNB+QxSyuDk+9cuI+iyTVWwJ2BJh1XYO7pw3ueWns3mIWf5ey+PQrZSDtqVdOeBys6/i9APDCndBXr9sejX8OD/cEqOMXVCm4t1Ml7g1PyG18n2kibSW4Z3RgqCBZYKg+I4kN6e1RCmJhbKpY3ZEy7EqSWFq8BYa9DA+YEjqhJWDnFwSDxM/EdoBKKRWxJXjBJPqrACQqkNyN0ms1/IYxA3bhfZ0A7PY4dCJe+DTsYRd+v9oFwE4w2aYAdsQsy8mtZqs7AIDj6lb2vSnLfRA6oYSUmiWxPQN2f6z/DvfC5Z3RYyzJVkulxXfJtMgcKJZj6QBBDlcKnZAS6iglltKN5QKYPezCM0pgg6Z5RPpc7lIlCcBtK1Niz+ph18V/k9/jx7rTtQydMEUPOwajjVyHCFCMyve3dz3DLgLsktTaOmXvjVV6b6s5K2kO5tXw/CX7j44vYtiFY+Y0+tM77v/XHwcWN90/29tCEhsz76lfrNEGdZx4TmY7xLCrMgw7aRPCz7AAfGVgCa05qzrePJeS2BAwI9oYqWDmzgeZ+tsmkdFPYdhZAdgVPewy4Gl6f5aCHBMx7Ch0QgXAru0KKbFthmFHcw0C7EYksfS924ZOtKhw5Dd/vu+nnsaP/PyL5/KVvjDAzqQ+ItlvG5F1pi8FLQQThl0qiZ0AdjFQlni45Rh2EZMgmSj2kQcaGf+OMOxIVlaRQWQKOpaBs7QUS1VzDLtgiJprUARMdgnDLiuJrUiadPUAO/YOFIACDYhr5e97k3gaWcusJGIwOXCJOoUVxjzsqrHEzlz5TsNWe2j8ZPoiGXbZlFjgfDJUIYmV50+7MCeN+3suIZZqcUUZdsSITaWl80rjn/bvxvt/0w/jj6o/BmDol0NBO3YTYCf6Qhp8U7/McDzxJsJchjf0Q8AuDbGpdSElVvT/0bnK709NXUcGSGbY2TxgFx13t2a7AwItqWaVxsoSs3vFO4iOYXf1AbtnXzkfUPTqkQOl6hxgJyaLz95Z4tOvnDALaFuQTS5cCLDjMWiDgXtadRUAmA89d49lrfuLxeDYnh3xlnOgYbLIEu996W4A+168v2RG/d48LGZo3H7pbpnJ9+ydU/ymv/zj+BPf+/5Np/b6lI5BOACCYZd42BEzxQNyFXvYeYadCvemSj7LpcSKRSOxRwoM8CCJnephF9omA2ddL2S83fCYBoBdHUIfaCNPLHAjD7vMMyABO1owRX5hOgBCNgESyfW0tfHc0x2DZNgFiZCswLALv1/vgiTWEMDeT1owjTHsFo1j7Szrm9n3pgBJycMuCp1QLa4lSZf41I+PHmMpGKJUBIwbdI4hNMnDbrh5DAj2Zgro+p+VSiR5vn1aAQoHq6LgYUftTV0lSSwFujRBRQJMkcRm5vy5MBruL933rNpwbztrBgAytf+ut84bWjLsRhh8lJie9bCjoMWR52ZQ6b2tAsNurzbDPlj669F7xdrlyVsBSPncRz37lQC7vVvAtTcAAG40LwXAro4Bu5UV14rDWcLGy1yAVZe1xjzsJMNu5fvtQeiEJQsK364SAlKQBdssw5s31ecuiIEAuzYB7ErqFBMBdiF0gnzMq9TDboRhR/dr1QsljWTY0bOJMAfpipLYIcOOGcdTGHbtcKweLQLsrMbRyoGpf+Tv/wx+73f+JFbnMI49P2BHwNoUD7sNO6ay2EMtMdCkBWI/Ajql1fPi1T3oDFjlGHZV3MBlsQccDA9ixILJSVVpwcFsg0QSSw1qCmCnE0lwVALNze3YdQnbphu5dmFi0OcTU3e4GFwYMOyANfnYpQw70QbWwsMuApe6MmBXG42+YPKbLZ8Qa70/g1JDg895GnqxqfrgbdDAYF7rmFkFnI9hJ6XiokOja0uS2FxCLFXE+LtKHnbEsBtIYl2buHfwFtzu3CByZoYd9SOZnduhh517LQFxUerrFIadDFHpmmxKuJJ9qOyv0gFxJJWJPewwywK8qfcehRD1Kk4znRnhYdcuA8MOc+x9Fkhin3v17JLYtutx10/061lm8SUmi0+9cpwHuKYW+4h5ht3L5/msACT++EdvswSwyrDknhsBNJ96+VgAkCb+P4CX7wUQ7vm7S2ZJRAEs/t+375WZfB976Qg//ek7eM+nXt10Zq9PCelfSImljVq/qWD95NvPKWbaMcpIEks79MT8jUInopRYyXyT49OwD6x57lnwsEvHNOFhJxe+kYw3lcQmoWZGq3izDjGTzSgpiR22W2m23WbYFJUZnn+letSV5gUKe5CJ+RuZ4gPBd22QEsvft2sMO88AQjvJ9HssJXbR3AEwAtglQMwgJTbDzJQMu6nFi+WJjA323VSdWzyOeNi1BYYdgdGrDQy7egD0Zdj6NN4LqS61NzXC/tuZYha233BowxwfmCKJpeuSD0AYfA+GoRMt9KA9yvl1I1ieLnRiDLDzKbESsEsAxDHW06DSPrdeMMNuf7YJsBtaY33ZGwPjlUFFksQubgLXHgMAXGtewr7yzLxZ4mFnM+sZ0RdTv7i8xEk7uWc36nPInol9TAMTVLadgYcdAPRd8LHs+izDGyvPsFs4hh2/3n8eraFLDDvJIrfCwy6V+o552BHDjpRlSwbsEoadx3NaT7ZxQRqFlFgGD4cedmuzH17f5ski6236axvuUweDo1WD20euzc6MxvW9s687zr1iqdjDaMJuylhwQlLBG8kDdcQwO0PCKgFiNvGws5mE2WrEw46976AxJ0ksm8EmnUDf844oswQLDLt+woKErkOeYRdMSvMMOy9b8ZHMIXxhE2DZDaR8O10cABDOaeHBsBVIEpt42IlJSgMXDT6rhMyua/h+NlnATnHCTi6YZFB+J4CSaw7n1SDJclFI9ixWcg5BEisZdueQoYpkIjmhJqAxlcSmIRqAGwDW28p8d6C4H0uecZrwrbsu7CglgyD5zKlN98YPTFbselptAIvBfWVJvX+uZ5XGacoAjdKw05RYlR0QJbBnooW29LBLwJGRHS0J2OUZdjFobkmepuNxKHpW2xA6cWLnOLiyDDsNqzSU7fHCnSNYa8+UhvvJl09446zKje8CsPv4S8d4+ForWHHbgmxB8vXUKyfYn1VDsGzyZ/mxEj1+5OdfxNcOQLdwbM+PMOw+9fIJvkIl5yPmGy8JwO7Zu0v23JOvIUDrdLnC0arNLuw/eduBeZ/z4HZpuJ+xEtJnXjCyJNYA5PPU9zB+TrUwfjFAxtBskh0+i8dKmRIrGGYY2JPEbbAiwK4uSWLHPOyG4RYGQqZbYNgZpbBGhQXCApnN9smPrCCJBRCdHy2MjRgzo0RAEdAxMxq9v5ZNhmHX+7mdViHJLgWsmHnl71dn1TQ2zetdW0pixxl2dwCUAbvUm2noYUd+bhKwa1FvC9jlEhpHSos2uo7CH4bfW5LEstycQNoCYJceE/0cJc7T2kkw7Oh7VZ+RZu5aCRsAAOjakBJbaTW4tqX3R/PzLMOOmHzuXqRJnwNJrABT285iLr3yciCu70OOl0sAMzwwISV2UuiESSWxCzGP1UCTJ6fA1KLNhPnjb/qyJ/ALL9zHFz1xw81V+j54Hi+uM2B32LyC6/Dj7vxGdAgxYEdz2fC99Cyv2surHuttWRIbMexoPJUMu0hO7TfGEgLSTFhO5BjeJYYdXVtaz5Q87Oh4u97CtoFhl0p9Rz3s/Lh4OK9w+2iNUwHYdTRmasU4EjHsms6xBrPrSJLnRgw7f25GzLvWR0D1wOCYsteqVDZgQY1PiX3pvsMVHr42P9NcnOrcDDtK6pgmiSVwazrDjhMHafHqf2+3kJOWveMygJXRgf6ZAAfETOughx52KRgjfqbFLDNgkuOwUzzsKJ1uhGEnvfWiQ/GDK0tw2/K1MyMMw52vzCScdrCWtKhPU2LFoKJMDa2VY/fY0IkEhl013JHVemDYOVoe1Gg9YJfze5vXBoNkz7ES57CGG7gqraCVCudxLoZdGCTkZI+AFg6dWI572G0FQu5I6ULoBLWTZdPzjtIiaTuWwPJNATC+DejMzmpJEqsnMOxaq+PdN/96koXICHhdlMSOMOxGJLE02DtJbJ5hR8EvfbcOu/8pMGpE6ES3YgbrCeajk46dLz9erNcNbh+dTWL+4efvCR/WzBglFjUfe+kYH3/pWPjOnQ1kMz504uMvHV0Iw+6Dz9wTnxOz9QHg5fvHRU+bvCRW83hKgRwA8PzdU+TkwFLKVgq4+LgH7N7y0HbJup+xEomJLLMjE2nRLrre8iYgBTuzh50HCWjnv1K9YOuFwIrIR0ne98yYQJJYNZDEZgzf5c8CGHRpn0LyS31wARCpjBL9id/h7xOmwogkViYxjoZOdD3Pzyr2sEtDJwTDzm8mVyb02WnoBAOEBEJAT1ucv97FoRPdRIaduLdJ7bd3AQCr2c3se1OAZJASK8FA4Svn2CDiWr7zN44eI/tHTfSwC9/Vuf6KgYhhGyt9NoE9qwJg1xTeRz9bCQjRopNsOwT7ReW81HatqE8g2R3P8fVm/zpAqMmmedjR2HGyikGXVF0gAQPn8ylUKbnr7j+fEtNv7mfWd9S2CMCYlBKbSmIXLPWbVzmGnZBJp4EVcM/st/z6d+I3fOnj/uQEI312CBw+CgA4aF7GofJrNA8qUXGYivw+kWpMz3YaanCZisYEqRIJieZjHnatW2eJAEAAqOSGg+0jhl02nIZSf8nDjpOl3a9p7Bizk+HPE5JY9rdMPOy63roQHVE0HztMGXaw6IjZrxW3H1JQtl2fpMRKD7sMYEfMRZjAvCOGYVJBEjvh2RfPfAeDo2UA7B66dj5fz3MDdjShjdJVC8XBCRMSSE1iagxmsnlm3TYedsywo/eWGWZO8pUHWCjVNUqJpeNKz0myVIh9QgAZvZYAtAmLG6LE564dsUtSSSIVefXRNQtA4SbA7uoAJwD4fkr5Ni3al+Rz1S6z7wEKvl+tSIlNEioBYthtA9i5gao1rgMZeKOAwK0tPjNi2Dn/OqUU5pVg2Z3HN07QsLMedmv391GG3eyqetiRj2WeYXd/Ge7NgGFnkklPqcSkhN+bbFK41/XCV9PLjEwGKBUbADnAjtuMALdlyEBV6eDzlJPEUr9TGBzR91AE2JVCJ8Qz2DeBym4zDDtOdG5XzLA7vcoedgj336gOP//82WSxH37u/jgAJ4Cx20cr/NxzAeA7K2BXoUdv3aT67H54AYABgj9QAN0EA852ePbOMGgIiEMncjKjO0enDHg8e2eZv1bivJ5+Jf89n2TA7nDCyb0OJZheQ4ZduC5tbxnMnGvP8klAJppcz0TwgQTSIh8lyRTJ2EmQJHawWVz0sBNMPgbGNkhiUw87JRjGno0/MAofkStGoRMp0Cc+w0l1fR+tLIxWvPmzpr5VKESIYVdpFbMURTGwSIcJc6n9nLhEP3Muhp212G9eAQCsZkMWBTCUxKY/Zz3sfEos91cA8I1/bvQYw2J54hJM9Gmxh12OYRcfK9Us9YSChfSxK8l02Re3LUsuJftOSXBmVyth2Mm1XzpPy78/Mz8fS4n1Y9S663l91sEMADt5Txvp89kHpU8E4vrPP/GA3a39nCSWNm+3kMSmDLt6wcy1eaUzgN06fNeUeS3ZpSjtQBYB2F0jhp2XbVJFfpwpUKgNM+zOY/r/WleOYVfJRHP2sPPtS4xdy7bncZnm6HVVR4m9ISnXct9fyz6VGXbu2tIajmT0NMdJvT1lsSS23exhBwxZdmvfjkiNwAw7AP16Fd5PzwlLYi3ariSJHQJ2kY/t3M+9CjY9NFZPAuxEX9jCedi95CWxDx++noCdtTxpqqrNk+qQqLr5gdEsifVAFYcunJ1hRzfY+u/Phi7oIGFMExZpl0Uy7CgRccB8yxm3m/Q4pjPsiKVnMgy7Tgwmqf8EEIBJGnQYuMwsqsY8/Ha9VIbtxEmm1g9kBYZdYw1mVfCvyHnYNTbvYbddSqxbvK2061hy4FYMtE1n2DXWwELzrvE8Cs84vyQ2BSyJGXU6wcNuXm3JGtyRUgWWEC0M6ZoAOQ+7iRYC/v4qMRFkVnHkoSLB5xl/Z2CLttHrOhmu46uSALQAt2W/YXShzROjzhsIFyWx4nPXepHd0ZYpsX27gi2wWpwkVqSSsSR2UTTOvRLFvk8dfu65u2f6iA8/f49lh1nQjBM/LYhdMid/rAxYMVq+T56p0F45zfIcDDv5/yBrVRGz4dMZ5tuy6fD8vQIIp4I8hLxJnrt7ymB4DNh5Q2/V4ZMv533sPvmy+/7PubQMu8D0Sn3nZCp91wXAbmYSwC5h2NVKTNKFJDZaNGoNSkrNjQkzeGbxQBJbGEdkuIWU5FCyeSSJDSCiLKMFK51YN6kEcSQQQAJyXUZmI1kuDH76a0mhJsHDTnFbpBRLo5XwokoYdpzUt5sMOzM1JbYk7VveQW3ddTpdPJR97yAlNmHYUcphZ2NJ7N7MoBZ9F+rF6DGWfOaKJfo0lxZZBoW7AlOOxtHTVvxejM+0gB9IYmkBngOx/b3pW/GsXQmGXbzeDGs/M4nlmZXlZyWrw3Wd7QIBILXtUEqJhOvUw67MsDtZuXEqlsQGMAuINxM2ViZ0gphRsyxgJ8DKDMNuUH4dhNmh6+cOHwEA7K9uFxl2bZ+RQwoWIYcYtP2A1XVZaszDrhMedrxpY8KGYJwS6/5eV2GMQN+Gjaq2D8mnEjOgTXR/bdnj3Y/fGj3mlR7tt6i/UAySLQbnJd+ftrc1S2K9nYgA7DrP2nNesUTa8mNgnzLsMqET1TB0ouuta2dAcU1S6huzJfrUFhWOVk0kiT1PnW/FIjojk06aMkXShVxAQ1okteWwhZSdx8EJWzDsCKhryf9u+F7JiGrbBnI4JMBLMvOCJDbZlchIYsNuiP9bF3eYY6V9J0fXRVbXuibaJZJEPm5i2CWAZQ7srOrxXe1dLgI+pLyLaNKntnZrg4GHnQe7fEIs4MCClZTFiB2x4e6kEuDF9NCJlfKAXRbc0miINTTJwy6cg3u/CZ/TXZwktrN5hh2Z0Y4x7OLUz6sD2JnI6ykUh06c+kWnGk6w6T2bADv+u5hEqRzLJLOJEDHmEqPeHGN3JhnIUhIrwMJKK/+aMIFA34cJ2uHDwL2ny6ET8nNne1nPh1p46fVtAM1t4htVy9CJbiVCJ/LMvStTQor5oefiScjdkwYfeOYuL0b3ZwYn6w5f+uTNaEH8oefu45eOgWaSqYbeMQJqAE3h9WNFAKP/PoXgAXtWht21mQJa//8eQ+ZB36JCh6dfHTLfPvz8fVgrAcjwXiXYF8/fXeLR6wsfOjH0sJNg10dfHLb3pnOefQDwlocuqYdd5PEWj2XaVFDK+Sy3QhI7I4YdSWL9AoNDJ0TwQQ5IY1mWqf0Ym5HEFkMnMotlIGLNUV/b9H0EhgRJbMHDTg8lsQOAZMR0P2LYZVhWvDjrQkosAXa04dhI6Zc2QNclDLsge5IVUmLd73vogWz2UpbYfDhXSuz95wEAd+wBUOUBtYEkthA60QmwpPLMzAPZVDb0WcRimpw6KPocJ4ktb6SUwEDq20/lYyG8IXlRmmz6DyWxsh9116Br3LxZow/2QFcIsLNtC1RuTjTJSmNs/pVhwCnbYVFrLJsefe8oIx10dlOxNhpN16Fpbfw9Ix52RJKJJbExezxK6N54ftp9D/V11TxO92SGIa11BZgofA+LRf51BKR4D7u99cu4hlvud/OEYdf1aFFhhm6gFoGuGYy31rGxZtXEZ+8zWDSWRCnN7Lcannti2CnBfl8JwK61ZE3hwdO+AfpgKeBCJzIgFCXzevYiMemWHTHsuo3tn3w+KZRJetjRhofsxweAXRo6ITYYKFzOmCCJ7Xx7ajuXvL7OMuwoAGPoYdf2NoC/GZseJ9t1/54E1ot5RwuNpunx3B33/a8zYBceODMhJTYER0z3sCNmXQDsPOjWlUG3tIYMuzI7rzIaK2KkDRh2ZDwabhqf05gklpNu4wX42HGkZZhhN1y8k7dea02WYm85JbaN/p+7duThV6keV41hRyCqyaTEHvc1YDBMifXXqoEJgF0KLhHDTryGKpZYTwfslso92Dlwa1ZtmRIrjg8Ik9BZpdGuLoDVJhh2cxk6kaTEUux71pev0jzIXBkptpCbpKETBJre8wy7RW2GwJShDY7xdkMmz1E6a3bCKPtrvwiSjLlkV7LJMHZd6ARJYt0g1FmFWjATjBYgtU0mbACw79kNJYad3w1bW4PFPD+uKKVg/UBtBWCXLhLmlfCw+yySxMpF7oeeC9Ljn3rqVfz+v/kevHI83N1+68MH+Ju/99144wP7ePH+Es/cOUVlEv+3zHcAwEz3OO0NDgmw2zasSCxIv+iJ6zg0HfCi/1smHGrKZ/2St9zE19tH8Q37DwMfRLLQDFKkT9weMt9+9lnHStyvALTpewMI9/y9Jb4UPnQiJ+EVYNBHMoDdU6+coOstFrXGo9fGWTmvWwnZTSqJJT+4prNuYsuSWPfnaiCJ9VIdybCTklgBWLnfVdGmGJXtWs/szDDscv5RyTGH7wmSWK3yQRjRR2dTYuMEvJxFAZX0I2q74eJMgk2pvJg2a9cy2dVfn0542AUGTrjG1tqwaKKQkF1h2JF/s7IMXo4VhXh0KfDgAbsX7C1eOKaVSr2GoROCvSj6kFmlsSePbQPD+KwMu5oYdiMedkGinYKPfgO1yzPs6JjSOSxLtmmuKYFo9rBr/PG1g7/tZOlkXcepj7qYkBm/PwNK5UBWMU87nNdYNiu+zkpXWUZptNnAbLVxSaxBj/2ZidtzAvCVpPTFqveAVcP/DoCdwcBHtBfzMzMFsPNjMkkVvSR2b3Ub15QfJ1OGXWdDwB+1VQEyS/B91U5j636mKydnryUbvCPAzv9dzC+WTVizE8NuFoGnQRLbCA/VyPbm/nPu/14Fw5ZRhO2i53VdqfIedvFYJ88v7afZw86vE9e9de2mW6P36wgpiSWF4tr78jGZZYMkNmIuUlvKrEnkxldqEZQt39YtFKxvj5/w6orzAnbna7Gis68v2sOOGHYkieWUVGJsTPd/s0nnGQCrvGSBGXZNvKixHdFNw/t0shPDJcAZZspQ5zw4h80Dm0kAS1m0u1XysGOG3SDsIg9YbhWSsCtlbbh2AtgIKbEUOpF42EmGnX9Y55XhTsF2K0gPuxSBj1Jit5DEnsINSnlwS8hHJzHsXPtYM8MuMAV58XERDDtoTiEChimx94lhlzmngcz4KlTEso2fcdrJv+sZdjnZJ29WTGTYSfN1ZTLPsOiTCNyrc21ARJKn/Ukk8fbgdosqAvYqrVj6xt8pvSH3H3T/L4VONNK/rgz8WF4srEOQUdKXziuNlRWAHYVO2Dn2PgskscYzu07XHV68v2Sw7pFrczxxcw8PX5vjxp4zZP74S8f4A3/rPThetfh3H3deT09c920q62EXfve93/yV+IH//KuxyDDStjleZTv84H/+y/B3f/9XhL9tu/Dzn3VzrvBX/5Mvx4N78eRWHnuFDj/z6TuDj/jJT7jz369yIBztals8f3eJddvj9tFqI2D3s8/eHQRcvPeTrwIAvujxG5HR9KUq0ZYCiyzIf41Y6NFzT5JYkgmvB5JY/34b5NTQFQcwMNjEc7e4D+wFE15P9rALC+Za7q4LfzAev0qhE1qJHXw/7qfm3V3+vUDMsGNJkpTEisAISxtsOmbYddDsCQSe2wmGXYYpI8E7aqcd9PTF+etZAoDY05uPdxPD7kV7kwHbtCQYU2k1YNxFMirJzDQae5UE7MbXJSW/uGKJNrpqxz3sGAxM2fFTJbGF0AnkxthEEjuTgF3KfN2lStZ1tPHQWjNtoy/nYTciiXWAXbyxP5/lxz26j21nBfi1HpXEVqqL/esApOE4WzHsgBgwqzZ52AmAmY5vbM1B6ouZZ517SWzdHuEheIuPxMOu7fuhWkSAmHKOvWwuZ7/HDDuxoRBJlZlh585FMuxOm47XHGTbUBsB2NkQqtS0gWEn12y494z7//UnAAB7vv9bepC/Qsdr5lJxICcz7OY8XaD1hDy/dAxKQyfWbQCme491uNCJmLTVdo61nlVqZUInIubiCGC3FoDdJEZ0HwB3anPkU3xeD7vzrVjEBZkSOkEXfZvQCcMMu/i927DTyLyXAbIR/zsJ2JE3HFWXAfqYYZdKVXNJi+zhF3tF2QmLG5qUmvR7xHG2MIPBFggItE2+NzepqL2H31y+7ipUBKCG680pseRhlzLsemKnVVkPOyU87NaocXDelFifjnTsAbsSuHUmDzsv6yUm16wyjtWmMI2pV6petj8piXXHnqbEHmaCNOaVwfIi/PQuU4n7rZNnjRYGd07cvUl38gEB2G3oL6k/0ZEk1oNZGQ+73irUVQBvB2xNwcgchE5oAfB5YC1NB5Y+oANJBAAsbvj350346RlcYj66m231DOgdw46T6ZLF+6I2MUWePOwwH/jDXKnyY8obrtX44D2LH//obfydn3gKrxyv8c43XMf3/qGvisDQ5+6e4jf+Lz+ODz9/H3/8e9/PaV6f9/ACeArZhaH83Rc8uu/u64hUa/x4xb3ou7hfO6MfHgbjnVwokS9Wj/c/fRertkPbWazbHvtzg3/9kdsAgL0KmfeGhfpzd5d44d4S1goQKhM6cWOhsTzp8b6nXsW73nwLd08bPHg4x7/5mPued7/lge3O8TNZAiyoUhYZy1h7lxJLHnZJ6AQl+A087GT/pDIJp7mFL4C2WfG2qZkVPOzSBSGn0eoIZJQsFAZQpoROJCmxJgU2Muwn6Z3XZBgOtZBcksdw6mHXWY2m7zHXhs+19c+L0YpBz0YshCSTjmTKLnRidxh2ALAwmxfaxZTYO08BAJ61DxXTWSUYc21RDVjvcShK6AeYYde6dUXOxkEWJ7luKYmtlJfEjnrYxfIzquBhJ34prHyyjBvxc5DEyv4tZtjtm27wt50ssYEEhHXX9pJYOf/K9As6zL0oYILme7NZfk0dSd43SmJD3xbJYeWx+eOpZZ84pSRgV2/ysBNgogQZS0WbuSSJnV93MvZ2ibdpzwJb3Izf0tkQoJZJiXVBexqrtmdw8bLVmIdd2wdm7aqLMYXgYUe4g2TYhXtB40vT9QxEzSoNfPD7gA//IPDcz7jXXndpvXssifVAG7qNgDX3aXzP52j7MD4BgNYKWgG9HfOwc8e9aoP9AEtiVUYS2/fo+g2hE8IKIethlyERSAA7lxEwKOGbeG1RYXW0xouXwcPOdg1ZAgfZ50ilwRFjRR0ksfJM+l4Cz6YMCsmkjwzK+8IOaGc1oIA28TOjQUky7BQvquNOzvatw0FEQEV4LTHsyrtkg+OqgvFuWiH1VmcnCgOG3RhgKRh2fducP0b4spQET8SAWRsFoxVOyZh+EDrhd9Gt4QmPk9mJe+Yf8jUq3BpIYhVHbG8jiT2yHrAr+L0Nkj3HikMx4l2mCKw5F8NOePiJz2eGXeP+fjTCsJtXGkcXkVh7mSrDsqUi6Q0z7Orhk0Z936gk1lrexJAsPpXzv2Mz4+A16Bh2wQJAA2LQNzyJo6or0Z49sJZ6N1YydIKOXSRGYebN9ckINi1i2Nl6fHKga6AH0K2FP2XKZDQidGIpPOwWnxWS2K988zX87x8Afv/feg8Ax6r9C7/tFw2Yi2+4sYdv/93vwm/7K/8W//j9z/Hvv/Cxg0mAXfAqLMsBpxwvf4bsK8/I1hse0xBIe/TA4CNHHb75b78X//ZjL7OsBwAeuTYXHnbD92ofWEEeeHsVXHuUr/VjzRc/doDv/jjwzf/bezGvNF64t8K73nwL73/6DgDgV73jke3O8TNZzEbMS2LDTrX0sPN/ph1/z7CjuUXFgJ3on7QRk2jSBokURFG9UD9URYZd2cOulnIYDzLGgF1eEltpkTqdetgN2HkZSayQq3LoRNavyLKcZsiwMwGA0zRXc99ZmwB6WuvOz2iVMOx2M3QCCNdirIoMuzufAgA8ZR/BrQKgdn2vzv6bD0Uu8tjDzgF2+x5Ytcog/+mhaBFopiwAgYjl2nQWJUA5kj4XQifWXe+YmbaLnj8CalIWCf2sxEKUK1lIz7VY00w9t8tYglyxPzOougDYTWPYZVi+ufWeeF0A7Ly0tATYCdAlDp3IpdAGJnkUOEHvAcLm1TahE8AAsIslsYkNkLQs4WMe2YhOATulnCzWP8MAmHVH5RJCk/VM4rsYALvLyrCL01SBRIbvr+cpM+x8v6A6D9gFuwPAM+xE6IT0sCOAtdYAvv8PBs85gBl2xKYjVq5Bv1ESThsFZNVjTY3eNtHf3DlqrEX4BQD0YiPrWoZhZ6WHXaJQdCmxduhhZ62QxIZgr9jDzrezjK92I6wrJqkgBMP+el3j9lGYq7yuKbFdG9In64yka/BlxBLbQhJL6bOBYZbsmk9h2Jl4AjcWuqCUQusZaX3KsKPQCeGpQ+BPek702k6y3hKGHcWfqw30effWwAhAsgNC/iVd6VrQ7zkFks4/swMsJJyUPHYlKmI7hfNWSmGvNixBpQU9l3/o10noRATY+Yd8beuMJPZsKbFHnWvvZfnoNh52gWEnmVzx55zjXotUUbn4oIlNyrC7VvDluxB57mUqKYnNAEkAcOfEnesiw7BLfTuzJVnO1ZBhlzM9bhFM12vhHUiT7gDsDRl2lWDYWQ+sNUk6cGWkJNZ/fxt223jQLAF2zLCbje9m0/kKSazKSI/5WW3XzGD9bJHEfuMXPhKxSb7tN30hPv+xa9m3vOvNt/CnfuMX8ut/31e/BU9cr6LPi0p6y/HEvMzennK87rNaMb7r7Rd+YoIaH9NwofS1b3fMtn/58y8NJvH/51/xtpBoL9+rwiLoEy8dswfeQR3/Xb7vV37uA1DKPe8v3HMT4/d+6lU0ncVbHzrAL37Tre3O8TNZ5PEWpajKoIiMJJZ91+KU2I4Zdv79NgZmw2I0kcQmYyelxa1sBZ22j8J7YpBRMPkEg7DeIInVOoQ3UZ82lMTmE6vla7q+zzKawiKi543WWUYSG66Pn6tSaq9IiaXPAWKfIGI99lYPgikuZYnrOFebj5cWuH2aBPnqJwEAn7aPFBl2NwVIl5unGOknJRh2c6OxIMBuwgZDSGjckmGHPg6dSFicEmtJz5Hmr6u2zzJXm7Qd+6LraUcYXMywow2OXQ6cACLA6WBeRTLySenyuY2G3PUTfpvX5pUPW/LA1zx/DWeShazF9+TCbrhv63CzJIkVAWTAGSWxe7ew8jLTeT3CsNNVOOZJKbEiiMn72HEdxIBd0/XBB5vXuvE5UvDEsrmcDDsC7N7afAT4wT8CnLwSJ5qTmquPSUAGPZaiX2g9oBcz7EJoz7qzzGS7dvpcDNbdfDOw7+ZFBM5RUI1R/cZ5s0nGwU7gDFVinQPEY5OUnx7471l3ArBjDzsdLM785zddjybHsOuaMPaL9O68h929wfk02wYEiQ3ix26E79MK0c9nqXOtWCidNLewyxWDTpsAO2s5cY2AOm6YzE7zN2vK7rvvINjniBlm+ff2zDBLfFNIUpbzsEMConUtJ7cWGXYk751wDpVciPYtoEPnS0aMXeF2krQiSGLL167WmqWJbdtix4fdUBv8xI5bj3w3iQE5ywMDO01rFQ+KfjdohaFJbCVTOCcwS2mgute7K58Ft4wIaJgCtDHoWA8YdqFzO48kNiwkZD+wlwJ2Gxh2ATy8IoCdTNGu4nOma/MqSWIzDLuIVWyt22VMS9z/2MMu6WsAAdgFht3MBLZmn8gISimxBIDZ9bFnEacMOxFkkXrYVRKwK0himwDYje1m98Y/s+2Kg4xyDLuQ6ihTYq+4JNZfhzdcq/C//M4vxt/4N5/Ab33XG/Fb3/Xk6Nu+6Ze8Gb/0bQ/ihbtL/NK3PwT863/s/pAD4JQaMjXOLIlNAbsy6DH5sxKv2NxC5ne9+w34iXWNDz9/D7/z3W/G/+HLn8SPffQ2Hj6c46ve9iDw4zmwLwA8v3D7GB9/yfX/+5UFVulr3b/feLPG//hbvxT/5APP4fMfu4Zv+KLH8Jd/5KOwFviWX//Oy+tfBzdPUHByvCD7DNeFWWOdDYAcS2IpKCGWxFZZSayJACv3+fmNKfKyaVBhkV67KR52crIu5nCbJLEm8rBbh88AhnLhjCRWsiWaxIjbfUZgudDGcEiJDewJCqwgMJU2iCutItlO21nMq1jmFuR9O8KwUy513KCbJInlNiSBB2uB278AAPiUfQRfUVivSFDjWibwKOdhZ9ChrhQW3sOuVxU2jSypCfvGEsDLSqRFpu1TArBpn0KbtQ6wq5CGuRQlsYMwFfGdSejEXLfOknKXAyeAmPk2M6hOziqJlRumOUAtvO7GXh18UAHszfNsnNDf9qGP6RqMetihx61UEptsLESeXlNKAnaLm1h7FuLM5AA7ybCb4GHHjCgBcNx8E/D0TwAAjtQhDusY/Gg6K+adMTmFjoc8KS87w+6/uP2twAsvArd/AZX5MwB8cro/r9OO1qJhLrJuQ8IwaePSxN7aX/t1Gxh21+5/JBzAG34R8HV/mtcaKWBX/f/Y++9o2Zb8LBD8YsfeOzOPuf75qleqeiojqaqkkgQlCUlISALhZBCNGmG6QbCQGmi6oZmGGdSgpofGLGC6YaBBw4wGo+7FahhhWkADEt4KhAwlW6Wyr149d90xmblNzB8Rv4hfxI7YJjPPvXlOvd9ab71zz0mzTewwX3wGzWDohMU7yAubYRUyxhxkY5MH2M0cEOc87HQbzwRseyeVZU2hEyEJhdtcMYad197LdEosbWSMksMCHsP+mevOM++Z64utg062AuyqaoUZTDrmiIEnG8MYATxfBQpbCCWhVtY5CrDzARPrf5dgAdR2EuSDIW3Ew46OK5TENlY+m2FmbrRdRFupjpH9jgmdCAE7BqW1Aww7YhJSaEafhx33n2qqKwKcAD54ElnUn52bwbHDsIsHSkiZo1UCmVDWqHKNIpISK6Z52BFg1xBgF/F7KxwIqNpqUH7hPPakBwyVckeSWOUmM3wXohM6sdTfEZX5FpKl+1yRdsfbXMLD7q5h2B1Gdq0yDvK1dXwSzJNfC86wi00YmXTZ3KeCpb5ahh0LUYmnxBJgd2Ze5wO1MhNoja2AY145A1pr/LoOwHEqD7BL9+/KAHZZvYRsluZ3C+8181yy0Iml/ezzIfbeZS/GoPjadz+Nr33306Pf+sITR3jhCSMRsD43iTEqy4EmAthtGBRhv3NTaS3QZY/EFprm5wMJfNev/0Lv7V//ec+5f0TZefrz51LhvGrw/T+p42yd311c8vQrv+BNHmD6536d/737WiTx0ymxJHV3gBr3VGoDGSf5rq07kljz/oQk1spkEomvBNitkeMwBdiFm1Bs8eZN1hljsgPYBXOqGGDX9bBLg9acLeGCB3yZEKDBk9Z8j2XY2Q1jBrQRw65xDDsOAtF38GOkuWqLTKfRKjXoufa4qxESUjVOctlTnmwV0HO6By8Cp6+gRo6fUM8nU2Kve5LYHsCVSWILNCiltIE7Y3y16djGh06Q/LbFwx4POw7AhowQmpuu6xagcZXNUVKS2Dxs154Hmw/YLbIGaKCZ9Je5OGA3zy2BpEE2CFjo9wcbluazvM8OXnfjoPQAu6ODOBvH9rctZ9jVvUzyOMPOB7M8xtGY2oRhxyWxyoSnxNbhZEeVs/nc7c+0P97NbuAoeEvVtF2VTkcSa0DrvQ2d0Nf+TqPnFPjwP4V8BzHRuh52hCnY9mlsrIhh54dONF4fQMDs4tQETXzW1wHf/Je847EpsbWzjRiaN1M7Il/pVrg+ypPERiTYPJTrcEb+rAooSBK7AsgrnXAcySSxrUJlx39z7y0xQHhgtu9hZ5ickTUJbY6NUZHqE3bP4bM33DP8/K2DxBvG11ZwX105JsaYgWc0w45NzmRhOpw8APusJGMKw26cnNYy7ALgIJYuS95Uobdc27gO3iLONnkoXEgMDwCy4IBd4OfSk3qrvzhk2JnXRxZD2nMtfv6XulibyvMueHJmJbEhw84PbKAqc2ZmT5LYKGCXTUuJNeDf64bxF2WjSTmNGdcrid0BSMYlsZxhZ57ds3UNpZRl2MWSbz3w8Kp42BGQqTLIoH8MfSAOI9eEh0gk2w67/9xHVOR9DDvXXwsh7KaHlbyYz6wiDLtcugWrMpLWWkkvaSruYccBuwGGXU0edv2gmjIGsqJZQpJfRrDrOi8yrOh4A0nsKGnLZa0Uy2hqDTHmODimFJMdTmXYZQDYwrAnaXP4s4LFaGycTQBBnerxv3vLLd3WPvSKblMHFrDjr52wWbOn1TKPt64kNrML/LrtMuyEmRetVCiJpZRYtnASEp2kwixYgNEx1W5M64BNqWvOjpm+pwlSYu2kPOFhJ1noBCXVdnyHegIBYimxXCZUMPZMGODBN8YqC9gZ5qJ5XnKZeYALsfg8ULF1n8P/ts9F6pExklhvIfjP/h/AH34z8Ke/AADw0fIFrFCmJbGMhXTUy7Bzhv+50AthksQm5+GsqiYAeYeKAS/rHoYdv5d5sNk2s5LYJvqMOElsd5MOQDyJXfpzhwUBqpdeEssZdrkXOrGxh10PoIa2xs2DwgIvAHBtEQfseNKn72EXY9jRZkSLa+FGeSiJ5Z5eY2rGUloXN/s97Ph38c281FyfKzKobr9gf3xZPNF9C2fYJSSxiz2XxMauvZecbs7rLCKJBYDahGlQyFMZeNjxPoDAsdn6rv77YfeaklXPmbmcOZpBwI5sAzIzJ685YOeFaXSZ0NZXTwq7RuFejSSJ1SmxZs5vPp/aX8fDjvvXCX+dAgQedhHAjlh/qTGjU6xvftNNBzi/7YnDxBvG11aAHU2aauSjBh7HkpsA2AUMuxzBgzjGK8cy23zAKsXOayzDLg6MKS6JpeMLWIOW9QbZAexoEW0X0xHpRFiesXIbfldXqstLhYAddWYRsFMI4c7/qqR1AvaeV6or354XEmcqIYltiZ0WAnbMG8vo3tcqx6wjJxDMw27EIGEAu1crA9gl/N42SomNhU6oHSwoeUgBO3/uYXdeNdZfJc6wY9fzEi9uvWJAZtjZhxJY2k3i5YP0KcDOyJ2VRMlAQJLqe6ETntTVfT/Foivq7yzDLu/stnspsWZwC9OBZazNE2AnZyx0ol8Su0LZv5ttALu8emh/JXKfYTfLnSRWVUvLCjzH/GpLYlM+XlNrELAj+Wnrf9dWQFs9aTOr93P4/yPeS6MBO77IMOPjC7f9xLE5HWokRXFU37+nRdYhEk0kdCJnya4tWgO6UgosbbCuGwLsjHl1RxIrgCzzACv9AQmGXUMMuwgDMwXG8mNm4Q7co89uPCQCwfIss0xwMsD2wDAOWkdYpjzxr45443BAzwZ4BGzElktiAw+7PBMQQnjSW8D5BBWZ8D4HmMCoeYzl/PxGeNiZ6/lk9QngH/x+rx18/9Ev1a9JrFc4wy4GzPgpsX7oBDHsxgB2sXvfW8wvr8/DrvEAu/icY123bu3jSWJToRNmcy8amhBIYkW67V+q8jzsJHICRJQc5327gST2xkHhET+ODxOAnZdwPeRh5/rujr1OKImVfp8xWAHDrj8llh0bH4dT6xcC7Ao2n3vuC+yPP5W9rfOWqmm7iqGgzdIzfbrezzVGqxRK+NeENrdqJoklUg3N82lThzAL8owtgnvBGXYWHCPA7uB253godOKUplBoBxmm1O+QRz8P9+R9ksdwM+X84vyNQAtCe4Cdn7p8viaiQQqw89cGkjNKKdxk9RBhOSb8RIadzPHz3+F8Fr/s7XfGvb+ntmPY1eSdNu5jXOjEwOSVdXLEynOhE/qG0kJ0jCTWAWU9EhlWtJs3jmFnWHMdDzvHsKM2Kqx8tvHOYYwkNs+1BNM7fvtd5j4k2IZucPa989Lnb5DnahX9+6UsjwXmT0j6GXYuJZZLYmc5Y7nZlNg4w26aJFZ/1quVkcQOhE6oMVLWiA8ffc4k4C9VTGqZxySxVWMDJzLRZZcB+npeOYaded5axrKlGsewY79L3R8GrvG2Fw2saBLPQOBD4wONfnvOMoGaFslWEuvf91xywM60eQPYffBejf/x739E/y4Ex6mIYYeBlFjDpsuNHBYAstKf5M6KDOfQ4He7PnUMO8yuuCR2R/LyIeCMMzW2Bew40BJbfIytUZLYkX1yz3s//82OYfD+t91yz1okdOIyb0L4DLvQz4rJWCMedklJLM2XWBAEEAAi7Pchk7xZ6/7EpqXzGvSwC9JoLcNODXrYZZkDCWnD2qbEMjDMO3ZWHEiLeYYVniQ2YNixBEB7fQTZGThJrD0WuAWQ55mmnIE+f80+F80Nxkhi6dzfs/4h/YvnvgD4hj8LfP2fwQ8sfiGANGA3LyTe89x1PH1tjm//ihc6f/fktiyBs5SZ9RocBdglklyTxVigVS/DzqyPBLoedkYN1CpEn5Eqwvj0jrH1F8j6Zx8cn19Bht3BbBOGHWO+UfWEdqCtcOOgdP0igOsHPsBA5ZhHinnY1R0Ajv8sRdu11wnALA8IHFPPfr77eXFDMzdBvmkjJLHAMGAXMOxee9vX41yV+Lv5L+i8xfOws2oR/5rQPPt0tZ/jcd0oPIF73u+OlV4TNq2yzyCt/8g2h/qemtQxBivw/QQbxrBrnTfbMg3Y0fqTgk5zRNpRUNRfkK80MezCPsnaUrD2RsdU5k6tVcVSYjMB58WvP//csCY7qrE6Dth5YyQBdhGG3eahEzmevj7H7/qad+DrP+9Z/IJ3PdX/vhG1lSaoqRzDbkxloxl2blCmsAVpqZ+BJHYKYEfpqE06JRYwA65ykyAqYqj5Hna0OxtKYp2HHUk2bECFmaSSNFbI4QGApJUlmk4nZ/38kh52ufc6ERt4WdGkOjz/S10ROSDVvJQ4Q7+HXVcSy5hG1sOuGzrhS2LHMOw0W+/llUmJjSaVCUsDHrUgr53fz4wBRV5K7DYedjZ0QnigJg+deGgGyMNZRMKEMADjikixPW+/QBIbTPpi0mfPazHVdho3gPNrn/WETlQBE1JlOdBEJLFK4igySDVkMVARwy73/R0zgXUYtGIYMa8tgf/wcA1tftrPsDsfSHJV0gfnapUhL/yFwizPcAo9ULfLh5Dm+b7yktggGX3jGpKm8kRW/tzujGG35ecAvQuZXiAtJfE1i+f3PnuIL3nhJn74Y/fw277y7cDfib328vdpNK/wQyccOGlBprZFo0jySpJYPdldEmCniIEXeNjRojGUycTSFuEm7tUkwI6zAjlTyoAhIuJhF2HYWUsAM6564Iv3DPSHFlQc6Av+zuXFDrDjDDsf0NQMu4J5k2ZY1a09Nifbzdhc6PIw7GiNUU5IiX1X9eP6F5/5NcDnfQsAoPm3/9J7Tay+97f+PFRNa5PcY5/dtAooOMNOWN/G1Ma5dz4ksxrtYefkt+seD7tOYjErzuonX8oYwy60waA2lUWZymHoBLnTXx3A7qjMLZDWIIt6G3bfH0hC+c9Ry4TGY9jVKut6zplySdoBw44HOwTnIdF2GXbBpljOgcAx9ZlfBTz9Hr2+OHoaq/rjAFKAHWfYSZ3+rtr0usNaqPhzvI98+R/Ht3zgG/Dk4c3OW+IMO/8cCbA7We0n471pFa4Jfw16rB4CEFruajdb9HmSJHZu+h5S9q29lFi3/qT136purNRTrtKAHa0/H67Na2NMzaDyALBrhCFbBeu+IYad59Vopd9r997Gv7dL40u4Vv5rUww7L33XetiddM5nzY5pVAXzzd/+VW8f974RtR1gNxB2EJY0aHmOgYeFJiZKWL8xWRiDcSigbZifwgjALly8DiwGSCI2jmHnM/+oSE7aMvahsKmPBJxRBz6CYSeFXhij6UxEBz3sgl1xC1wmWBNN4vwvdfEk02AHcZ5neEURwy54YK3/m/QBO5lhqUptu8RSWLspsc4TcJBloVyAxf1WH08MyAEYW3MMc8PzsOPnIB3Yvg2rLcmwI6pyg/vnui1xyQmvnfnp7VNZhp0YZNjFdm3LPNPgmug+87YSgHJfSmwD6U/os8IH7BhrL3xWAFgTWWGZpbm38MgzgXMLUpt+0UzAVqpw4PiQh91ASqwIBuAlSq99A1riv87068T56/Z6NPliPLvhMtYj87BjwCD/rm2ZcVt52NHnECgUWyiNkAzzxVbEwy5Hi+/5zV/EXr8Fk2+Pi+YwBMJBKegoSGi2ml1AcoadYfqYuc66EVBKWZBIiuDeECgY7ron2jF52VQi0s4GPexYGi2TxMpoSqzf/2SZAwnpGGru/TXwDPBFSMf7Dpxh2Nr5XBF62CnpWHHm+JQNnci8zyQQxvNMY8xv/rd9LlqIl2J4oU3X+Pnmo/oXT7/b/q0ZwWzTwR3xcSeWEpub0AkL2A1mxIL5F24gifUYdv53dRKLWfFNNdrE90InEtIvGbJqebuW/pxtLug1VwewO5zlyIXb8E/NYVPvtxWVrLpx6InjmQcM3ghTXU15mxrcwy76+Y4F2llLBMCCxzoeU7IAfvMP6PcLwTzssm4fHIKJstTzvNS6g+aGAWCX5wWWmEU3Geq2RUVrrabW41QAMh8Z65mzPWXYNUrhCP68+Lh9COCatx6n/pBIQDMz3lpJbIxhpxpr2XTKAEt5/rr+4eBW53iozdwn/HQEYCczAYnGbtbVBBoHfV3Mw84Cdpnw7TGIYWeugbc5Zu4tyZwrwkEsYEdszaAtcTZ/b+hEPD07WRPIZFNrJx52zUjczwZHGNCt54MB6B1AS/EPExOnmFtLAjf0DbbS2MSgTBMlFQJ2JMNlO2gZT2lRruERO40P3mHSLSzDbgRglzmmVue4BgG7YPCI7ZSxIu+U5qoy7PIAPOEMuypk2KVCJzIs4U9KVii8SRGgdydHM+yqM7uDcmJYQbH0UADWO3EUMy4hiZ0VjGG3hV+hYibWcQ+7GvfO9HVMTUJmBpwCsB3bb5/KA4n9Nhfu3seA2Vyy8IYBD7sqYLllweaA/gyW/sqBrbAtMdZeuNsOwIbVZDV5zRUIkw5Tktg1CpzTczMiJbZPtioC+esSZTQ2vcr1YJydfsr+TtIAfVUrYdY/uQbGCp8Vx/o3scHU4qIYdrGF5hhAk1+7KDsv6M9ji+jUay9R0QZmEYJsAJC5JOm6UR2GHUlia5NsSvMhSYCf8oGnTsJngqFIgQ9xSeyQhx1Po3XhARItSpobJEInfIZdxMNuQBbOgbSYyT9fjHfZiG48aUJJrFGN0Hm55F6fYVdkwl4HuhejJXCPsSxgN8bDLhMQaPHm9hP6F3fe6T5nqhS189nMqDxz8/kyz+yiOeUlzSsWONJbqdCJYO3QBwRmbBGsIgywlLm6ZczErHRsoJ9+FubWw+6KAHZQuLXIGJC2BWDXK4mt8eabB5DCPZvP3UxJYvX9WDet3z9a2WnKwy6UxPpjO994GV2ysEb+ay90Ihj36Njo3K0n2TSGHd/QCGtdK59hF9lwo/XUyZ562DWtwpHwAbvDVpM4WrZG02stYdWDJcnxzTjgMex46IRh2T5kgGW2uqd/WNzoHA+tSx4Qw04oHEf8tnnlmUDBVJSNYbyl+pUow45LYpuEh10AUJ8RCJmZ19YE2Jk1PYXdmfI87MiPMcKwo2MqN5DE7rq2BOwMCDImqRXw5Uo9LBoHBLrJIIFd9F7r/zYC7HLprGMZdjQJCnd1CbBj8i8uK2WJZ2QC3LLXhimxdDzjJLHCTrDCMAxl45Pj52MlsS2FXfSff5M4/0tdjF1UBJOkRSFxmvKwIxkh/ECJWZ5hGRher1VXEptnmWNZDrEsDLtOQeAMMxzN8o4PCZXzQ2wdkyRVqZRYyVhtWyzsFfdGY9eWwJZWAS8/0APwzQTNX3vY7YDtt0+l3AIrXCCEnnUxD7uCJ+em7g8B0cpngGZhqjZ/bfgM2EmfD3DEnhUAqLNuuy8Chl03JVbvcq2gd0gBDEpihzzs8nxmF7X02bO8+/paanBOrvXzdapmmM3jhs5XpnbOsBtibzeujZod98nlAXbbeNiFgF1MEhuRLIWVAl+4DNh7vQ8+Aeh4PF3Gsl5qoYwVMMmubhFVU+gEpcRak+xMM/DM82pVFvRZZp7UkcQmAE9FdixRhl1KEuvasvXPaXhK7LAkNhNgoROUEss8buy8VkSfGfp8ku/Y95niC9ImBKkYM64OGIhk8xJ62NFiyHrYSQcq0jx2tMn8YywaB4shdQ70uT+JezjAUj+rt95q/9ZOZbZFPhsw19XM/YsgdGIMw84CqJNDJ1o/dCJonw2/z5GiTb020oelmCQudCLynZbhpf9WWobdFQmdAHDrQFqSRTUWsIttqDMzevc9jMlXSssgrZHhM27HNxUdM8kxj7Qktru5pli76abE+sfjwOjNAPx+D7tgPB+yiqhTrKi0jF+PP+xz+bU333twCTzsQobdofGwQ8CwK6RjMlp2r3nNijbOpPDuBT3/J0t2bQikKlmIiCli052ylx/P+mEjmWUoGWBHjLdwDRTzsFvXjuXrSb/zCGBnzpUwIGLYqeC1ThKbYNg1rWPYrU484pX+/qmhE+PVn1NrK8CuMcDamB0lIADdegCCqnZMEBp4JAf72jo+eCSKjBmdJDa+e2o/3nq+pRh2nDXHmX8N+5Eksd3XWqDOvD4bcQ45W7yH6a02vTYpW/L9pKwUN+FhR4N5c1WkiYC9NzWyDmtoXkicK8aw4wMWyV5CSWyeYRVj2EU97EbKogxg15bHAEQv9Vh6qcED98ncx7XKPR+TkqfEbnGvFQeCGHuRyz5fvKc7zXGS2P0cTCcXB76Czv5mwDSMAVOanTkALHAPOw7YhZsUgL2unWcgCyaX7H7GGHYq89v9GoV3fjwl1vnikWw8d4nM9XkcbDbMvaXql8TOCumxXJcqzrBrg521BziMAqRXqnbF7Bqi9zO5xSAbb6h2xbALF6NRqeoI+b0H2HVlRnyDznv9lQudIA87X5oJQLPV2E54bRYKeeBh1yDDumnt3zuSWFpY8kk6kPSwI0/MKpYSa9tksJnFvosYxk2rLFgooRzjKaHgEEK4Deo+hl2i3RJAQwbZ9n3B33mAR3jda2SOBUOSWHN96P32Oprz96SSLTHBcu/497lICTBGEiszgWeEkXkdP+OBR3SuqY3QMZ+tP4cxM0WLQgrLsKtHWARR+54eOtHo9yY87KoeDzsA1sNKRTaRCagJmSQyZNh5klj/+ZxlV0wSC+C2x7DLcH0x4tyiHnY9lgkAoFrcPtB/ayGjHooAD4dQLpShWcMLdjBl+1s0XT/sQBJbRBhPU8pKYosIYGc34Er//0kPO0qJTTHsusdYNS3z5K6j47eTxO4n471RXYbdTOlr0WXYOcCONnWIPEGp7H5ib+MYdkuyUADEygB2s6PO8dA8mW9CXBto/h2GHRKSWGpvbMOotptfjmHnpcTWaQ+7s7XZ0MpofWFYmjZ0wl8H5JwtTYCdatz7TFUJb89k7S3DjoIVRnvY+aBb8nMZYEc3tfDAvtqyxEQCdOLVSUwcWIQo6+EWZ9jxmOJM+sdlf4wAdu44WvP/KZJYt3jvpLdGgERewjzUlpVI0uCUJJYkwfXVA+xaZB3wZM4ZdoAvi2VgFwcDZrnxsGO1RmGTuKg4M9Jb6MTKAHa1kfCl/OsA2NRkfozJYmDJLDiH0WBiT/GAlVDeQ6DdR1/X1zTNsOPy3CvCsGMSpnCwOp4XHgkpdl1Ggb2MPcnbNTHsBJRbtKYARO6Dwv6fksSqkGGH3HtdngnLyiGKvmXYqdJJYgE3mPKqiI1XYlGkn4FQlr6KeNgBQJ37E5EH6sBO3K5s7SrsYGi3cFcgG+AvcrbxAQnBythnjZLEpjzsEs9kT0DFZZb5Wy+1mCRWSLeAbFrnYRe8tkVmTMFpARlPie3IZBLyVlJhRNUd/F55HlIOUC2sZNSlxGaeJDbdlmvh++n4YFg/M5TAzXMmyfLZyc7jzrLKAmZjyyWx5vjalhh2caai72Hnqz9Ge1Y9xiK7jEH/a+iF1VME2F17xvtbsyXDjku2aYO8QI0yz+yieRrDbpoktsuwi3vYpYBAGh/biIddlWTY+SbyUUksMezo/kiW7nkZiz2/N+aZlxJ7IZJY89o/8Mu0fLss06gItZl10yY87NxnVsr1x6FvclcSu52nJUliSym7Y2Qo1w1CBDqVZNh1QR4qLyW2rf25j7nOLnRiPzfQmrbFIZbe7wiwIyWdgjDrWMeeK63QwQB2igN2TgVRmvUpnf+RbNwYXPrzZEC3tXnBLG4AHJf9fZaUDLCTtkdwXpimLFPUS4l1mwbUznVfS/0M87ALQGBiTSoCsakNpfwQuSSWn3ugsuMg4qgaIERtUzvxsEtJMcPKPVlr+oFpOBOETHTz3Mop2rqyLLFRklgLlBnAakASOuxh5zo+z1uPATL04DSiu4imzt9KY0fc2DwTlg0VestZht1IDzuh+q+dsky+y7vI6BSTDoYyhMNSM3VaI+eJAXZ1kMI5y2XHw26NvOOPl3spseMYdmsDMPSxgHygeBxgF0pifZBse0ls7NoSk+xnX9WdYNLDrnAMO3WJF7deGWC+VV0PO5kJXGOeIk8cdye4nrQ0dX+YLx0HlGVsI4EzIdl9EoFsjwDYWsUlsU2MYcdeJ3lfRYNX7UBj77mJyWJHhk6UMsOKMWxiDFcAUIFf3QMcXH2G3a6kmEMgnJcSOyCfHSo+TsWSXUd/TrBBEvusMdeHyzU5uv7p5mFngyT8tFIA4ImrVcsZdiZ0onVSsqpp7QKSGCshK9FLhgPctez49vZIYqN9XwsXlJFHfaByTxKbVmFYBhX56EUCHVIsU5pDcIadlxJrFxEtGpIXE8OOecVaBqIgJnPtfZYn90EAVJnngiSxlyF0ggC7YlTohMDTwiQfHscBu8097BwDsmVhJTMpLbBaj1hWeQDqqC92a4eqUcl+ecgbr7SAXYRhl2CS0MLaEh76GHZXRhLrruvNRWaB4izr2t70vn8wdILdv6bC5zyl5yoH8zTg6Zn1W+bRKgoIUn97UGh2sFeBD2LMU2xKxRl2wRjcAewS468NCvCvw2iGXVMF45T+PZEgTvfWww447jDs9DgTKukK6fzpqO+h11B/2QmdMAw7YqPdkIz8k/B1PpoV3ibE8QiGXcnCZ1LJ1bF7SZLYXPoqoNZu3KUlsXZMpTZDPoYEwJWBhx3//kwCufGMNNY5VFU9cXNlm7nrQG0J2BHDbixgN85YvqmIseMYdpIxzKp6bQMbxoBdMkxnHQisoAdChZ2JTVdlDLs8MjmEY5Yo1tCzgOlnpbEjItD1+RvEuQ52JUwDaROTRBV0nhTPnrp2jUic/2Uuyy7qMuy0r4FAJcyDzo0nvdAJ5v8WCZ1Yq3johO3shhZtBNhlumPp28nzJOJD94nJemeBrLfeoYcdMtmZFNw81Mf5oVcIsEsw7KTcCXi4V8XaXGxizhmUMcBuHMPOseFmEQ87770eaM28NYNQnoYznGMMu2AyvlY+UJ1nbkfOsnSZh51ChnNip4YhL4AF8c6HJLEBy3WpyqiHnSznWCl3rR+oTwdJ7I6YXTHfHe972NiSMEIfXRcdOhFlvvX0nQnZWdrDbkMm354XjV85gSVcCpxJxuZqUZNHXYQVVtUulMJJYn0vtjDd1AECwdhJPsd9Hnbs+30Zb+YveoVj2A152Onv9D1yPDDMtpmEnI0ksWt3DfnYwMMiaNOjyPxr2SDrePwpy7AjSawPfBJLIJcOVLTWJ5dIEmvZhj0lswxPW4bds97fLGC3iccmfFCD5k7kYUcMO2sz0lNNGwfHksVAZY9hF/S1Q59Lc4QmMq+ghXO4SWdDJ4g14zHEaO5gGHZXJSWWES1uzoUF7BY9QJpXMWZwLPk87KtGjHsl7yO5GT+x1RjItWr1aw9k5BkP+qqOHcHEWlV9HnaBXJeuzyDDzg/e8FhR4VsahYbjC5xBaJ73W4cl3nbnEE9fiwd6PO5q2rbjYVe25lqY++UBdpZhp6+HYmME0A2dCNenFrArDpJj1rVF7m1C3JgPedhxhl2R3CQpIvfShk5I4fVDbcCwy7PMXg/CVawvIWf31isWOuEDkuGmViopds2OaVRdoCR2q08kBtpYhh0tQAs0vYtyYnY1kNZrgvycZqjRVJUFnaYx7HyJjEgBdokJOT0MvDPPEx52Vi4hOGBntNy0W0P/HyPrFcICaW2C+Zd64DKSxBJASMBlErCU0e+51OX5cvkdzqEBBZZioenHawYimAXvGjmucbBLdiWxtcijhr2DSZ9UBrA7N4DdtR7ArswlapXphdHQotwwAUIGku8bt72HXayDIqknpRLFgCnAMOzU9seyV8UYEbFI8JaZmyYlsUoCAt0FKxVJtoOEYhmmarP/N0SnN0W2AjTpVoxVGt1V6khiC29HXzJJrGPYuZRYADhHiQXW/rNGxRh2fSmxoY/kEkVUEjsvJB7gAE/gAQDDsOv53CtRj8zDjstYt9xZvLDQicjidsz1SR1DyOCzr4+wsq4AYGcZdgHTCxCAEJ78sgo87JzvmvQ87LKOJDaQcoYpscEYp4yHXXSzOAbYefLmHKXU3181LZTIIKCZUh3ALqJaqAOPY9/DbpwkdmkWt4UU3iYXX5A6hh1dK+ejVXcYiLX9PP7/JvCwk1lmz402kzddoD/KqlQGiPGhE08Rwy4E7BQxODYE7BgQWqsMMwA5SWI3YNiNluaSh51o9QIyweKoB5h7jmHXXeOkvJosaSLqYUdzB308ThJ72QE7Izdsa9xZSLsBcVZPu1/eZvoQw86zgkjPT6gNrr30zKrLYgOwNoDdIjYkh5JYxh7dpIhhV0YBu4SHXRKwo5TYFMMukhLbtG6Du4mz9L/s7U/g+/+brxh3Qo+h6lbhMAHYOSUdAXbCthPqe3gAoH6Nfy+4hzkAXM+WQIOoHJbqiaMZPvTKKVolkAnl7CwSlWfChU7IMpnMLdnmFJUD7Pw1SiMKvXLwGHb658z4HJIvn5JM+tqs3BqjDAG7YK4xOwLOXu1KYm2/OFYSG9nY2FFt6WFndk/HMuwyYXfK2h5/tDZodPq9mUtJbSqWsDoesAulqCnWgGPYhUbH/gMDAFJKtGZXWbHBzzLsOLhXhMcxHrAD3K4YMRDdl3WPy6uATWCBuzx+7VIpuZe6uH9XIrFzKSJJsVwSG4BdYUpsnXd3bbissR3JsDsT+nOuR0dZ9/31WEYaASCq9Ixsyx2x2pRlnnYnGcSwo3riKA7YlYxNJtqqk9RzKYuDxJEJNPcUiU2wcy90IsWwMwzQwGPRS68OgIsKuQew2cRhYsPUjpEZO24V+NOskXtgYc7YwLYPMQvslSLAjoW8hJ9vU2JLHJT9z8ADOJr7OWZRuco8z/Cqum7//VB9GkhiE95fk2tot/DCPew2AFY7gF0fkNYXOpE4hlTC7BUNnXAMuxBkM6wflvZGDDspuqwwLVkiD7vG+zuCJDm7651qx8QCjjHs2JyrA9qa73JsEmU3VaVoXT/WwxYlhp1o/JTYnCWwpibrBAieGUlWyoi7blrm2xZh2AXMxDZg2Mlg8V17klgjn7pEDLs1XYuRoRNPg0InfMDOAVqbLX0Kxm4ihl0uWs0qIYbdCA87y3gcexwdhl18I8W7z5EiBnqUYZdIQ7S2RIh8JzFfzJrKSmJHqIb2vsx5CtXgqUN9vd7z/O1J7x32sMtcfzVyDM1TDDsCudj8bN3qz56HDDulOgBiHm6WTKimVfZ9szzmYReAZ3JgXLRBAQHDzrTFVsEmPtu3eKETVW8fvq/VtgpzYUDMA93WSuNhR/fLZ9j5zGNaizVKQgjTD7D5Ssiwu56b+xIJnKC6Y0gWY62dZJYxht3MEhPCPqkIx3q4PqiUviqpiXnY0c9GbUaAscwL90zVK5aCG4ROhAw/Ai1XgSSWHdOoGiBQbVNbAXbWBHFk6ARPOq1DWScrkmRx3TRfBDbV2oJOoySxyXTW+HET8KXChhmZwHvHxUBI8uGKhk6YgU9aWe+4DoUmlk0IdjbxwTv8XpqoyQE5sQX+rhRg5xLWwgnJISUHUfBExQE7Boh4Hna+JLZVAo3sAnYFS2LtA6kBACvNADrBsCR2lkvHjhtaDDI5Yhg64VhtWwQ99DLs/HNIMeyyTPhSy0u8wLU1IIn9H77h3fiM2wf4TV/61ujbS4+dmWg7CTacD9j5PiINMpuSCACZmfTRLjm10wp59LjD0IkVCm9XPvNCJ8x9ZAy741nupzIH1ZodsUEPuzzDA+UG4XvqMMmw44Ddp9TN3kCXK1E7C50YAuzYxHyboAj+Ps/DbhOGXeBD1mOWvpEkNgXCRUMnLv9Y2hgGWB6CbFZK5Rh2ThLrs/EIsKsN48Pu0gdtxgIiCQaZOygDlsXahxDd+xsk21JfqX313DEVndCJbv9jWX00NzAT+kwIDPk40iKF/HY68kNm/N5JiWWLMcuCCZhSFlwJ/IHqSOgEzdv3PSW2aZUDL9Xwc+Qz7BIedhtLYt39CZNrC9Omq1GS2KkMO1LnUOhEgmE34GHXlcSy0AkLIoYedoa1adlzXQ+7jiT2Atglj7xYP//+z9Dzhy975zM9b4i/11YkFKLz2lGSWNd3eeENUUmsfu0iD57xgHEM8D5jOuOWAieAUBJLc89AErslww5wbFkqHTrB5j0XKE28qKpbhRlMO1ncBOAYdoRHtJZhl7F752/q1MhQykyztxlgNwuCR26SJDbhXwc4kkU7GrADSjgwOMX6zcOxHk5+mhvmOc0H6Jwp+MZn2PltpCykC5iol0lJbMdDjwC7hCR2OmC3+3a3HWBX93unhaVlrfokOj5srNrasaGosoy9t6ldYEM+fFHIzykLJKEp5L1NLXYiTDZP/sXCIGjH0wuooJ0MtIBSNi1WjjgHwF2PTnptgLx3inaKQoZdgrauLMPuEkgTH34KePWnh1/HGHYh5Z9YPGckcY0w7CpIj04cetidYo4ych8LxgztAMBhmZ2Ah0oDfzyUIKzZFIZd5SSGHsMuz7CGv/jYpIiGLSKLlJBRlwLsAPgp0lchKZYtVmMSnC/5zDv4R7/7K/H7ftlnR9+es/5yiGG3hs+wKzy/UJ9lUgcsU+etaSYEbEHXMSoGOpOodZBQC3CWrumbmCz72RsLlxQbC50wv0ulvlLNcokHcIPwfRzFGXZFhlfhALtPqDufBgy7ER5tY2rIQJcZGm9ttrtzD7sQYOLMhhHXJ3UMG4VOXGLAzjLsAkksGV5z1lEiVIKCEqqkJNZ8R+bAPwAdU3t3ULT5kBgjUyxLAMgK/5hbYv1xSWwafK6t/5I5Bp74OSCJpY2S8youP6R+WTNWAj9A5caTENAkZoULnfDZMi7pznnYKZsSu9+AXcWkbnKMh50AnjEedioMnVDbhU7wUJDaSsXNtbUedv4Y9L/84w/i5/+xH8C//+hd+7tUImuyGMOuajb3sCtDwI4B2XXimBxgF+tHfUmsBRuuBMOOMZPMPc5HrtW8cZGApSZy/fhr+bjXQ4LxgnloLsYBO9Ymlub2LrLgueH9acc/dHp/sKpdO/IksTQnCBI9EfShXik1mBILdPstL3TC2/S7PHO9xgPsbgEA8sDDruXjbifB3czhDWAHwGuL82B+fD0nwK5HEmsZduPmlHmWuXAgWSY97NxY302JpXGYXkNBd8K0ce4Xmxd+X1PKzD0XNZfEBgy7pIfdifc6e0z5yDHjApmdWzLsCLAbK4l1qZRN1QPYBQ2TinYc62rlAiRGeCVkgSTWAlZDi5BwV1d1J+R55oCThr1eWbkwY7IEfnfEtBsj69WfRQy74NoNUDAJSKHzlgNgZ5s6/32rV38a+FOfD/zZLwHufbT/tWznocOwM4DdiSJJbDcltkKOGXtfmWdYKR+wi4ELGnTRvx8M8TBU3HuNPo5+hh0PJBgniV2pohM6UaUAu7PXge/73cDHf7D/swE2yege7/O3XSe5KCSuzdN9RSavGmDHQOINFgiFlzCc8rDjoSihhYC/I0ZAf8jGoz6UfEHtRkxKYt8JnSgQGrISs5javDKg8Ro5nro+Z2zWiCSWTdaigKGpLsPuKBo6ETLsPi0Au5RZ/9QakqZ6MtZtJbF84ZJgI0z9HP7/aBjEBh52MY9bzkq4oqEToZdaCLJVrUJlQaYuK2xdOwaeTKbEBiyPxPUTfQy72Pvs+wWQZYxhpzwQ0fbTPW1ZCX/x4MkQB54B+vxzI4kNwRFa1FQMEAoDPBpIJhn226I0/XAY3hHzsGsvCcNuVbuF+CiGXXWCA2Hax+HT3t8ss21TDzvGyrDJtSCGnRlfA8DuT/z9n8JHXjvDr/muf909jokedjmarTzsHMOuy5bxQF1WThJLC1E2T6PNPvM5bqE+Mpxhn8sbjyayx2MKh6Qnaux7+jzsxktiV42+d7Pw43h/alNiCeTfnGGXWRlm0P8mU2Ijaxc6D6AD2PF2HfZbledhVw1unuxjeYDdgQbsisZsagcWZB7DTlDohPOMtQQTNl8J572HmfmuwgezeL3ppiaQNENrEVPS87ArkpskMYZdFbDZ7Maa8DcGMsawkyHDLs8Chp0h4KRCJyzDLh46EYKIg7W3DDtido0OnRA2JayPYReTxAKwbJO2qS1bTo5KiTWAHQFVlmE2wpeHV6QzlcyjzJPENn4SFwDkQXKjpHNIeMmF1bDz5yXspDchibWAnX/+KSluUhK8b/Vjf12j4c0a+In/o/+1dne6a6RPktgTm1zJHtjWAXZdDzsG2Kl5lN2Te/LAIUmsBuzuN/pz+wA7DbZN9LCLMOxWxFDggyQA/J/fAfybPw989y8bBm7b9PP0GbddJ/nZz17rBWC8ZNN9B4vHlDVcz8Z71bDyEoZT95j50nk+chH/u4Z707FJuSx8HxqyOkgBdiqYRNWi6NxXF5BD3+1k2XeOShfYEgmdEAbcC/1LwiplhvuMYXcPR1HQfJZn+IS6Y//9MfUEjjoz2CtWYzzaxtSQgS4Hr+zO4qaAHZM/biOv7SwWephvfX3nkIcdl1nysdL7nh0xHR9j0fjVlbGmGXYhIFcjM6bgBhyzAWAB+MfTW4H0fbKbuinALpDSBpNo62HHfPdyNK4f65l017Z9UUqsUUpIgSEpd2kZdiSJDRcx7vxdgEfrAcINhFtkiDjDLpT7+B52PkOy2WCB/ihrXbd2HJRjALvTTwLQFgm1DMaqhoCFTRl2XErtA6r0/ypYVhGYQfec3q8/b5okdlsPu9JsaMXYMi4IowsiC8ElsV1rAZo7WClcftUAu4lsLS9Mwrw3abEQGUNHSWKVD3yFwQ4Azs0tm2UBKM/701ASuxHDTrfnWW5UGcmU2ACwi81PaMMW6GfYBcdZt8onMWxr0fEYquEedoZhVxDDLrAy0ExGB+Tz1zTI3OY125yc5Rl413dkAbv0XPuLX9Beeu7a9gN2OU+JzWeO9dsJnYgBdr6PJv2f0uCzljPs9M9F6beRUmbuGehh2En6bBs6caz/HzDsqP8eLYkdsMXYprYC7CziO/KBEEJYpJTLR8NSKYYdTTCqahLYRUwyx7AzwNXGgJ17Hw8VaBrXkFXwcOlj5Z147cInJjLs2hTDLnU+1mfCTFYGvPMoPGCQEfa466UfcT9/9F/1v9bu9HflibTr8KAxkwxPEutADg7IzXKJh3Cd3Cnm0QdaCMGu57jQiddqfRz9KbHOG2+Kh9284OfQkxL7E3/LvPfcv86xIql1pIPigN17nrve+TuvWSGtufRVY9htIsHR7N0B3wjGsONglZ9ObDYPCDxTPss0M/IVWgxZGWuiX29yf6eqzrosZ+qrqC8nhl2FAjcWZW/ohGjihsNhzfIMDxQD7NRhQhIr8b82vwD/6On/HH/54NfhJdy2rNorW7tidg162DGm2tYMO+Y7tpWHHX2/0kBHTKIw5voMLrASgB2ft+yK6fgYqw4N/0NWHAtwoFRCKbTtB4FDLTJUdYuqHZDEdjzsEkxIGpenMuzM72msVsrJxrz0uz6GXWCA7TPsIqAGK+p3z9e04RxIYlPyYta+Gki3yAjOU1oPO38x4nvY+aET1YapkI+qOHNGjOjP8tOXAAAvqVsd2Rz9cxPGO8CN0p2HHbHKSAa+Zh52XCrIyzH9pkliJUxK7ICH3RDDLrb4rntAxDwT7vnnz1xgp+G8q66CJHYLi4bMX+t5/+/zsIv5oAbl+tvWByYa8n1jgJ1JtZ2FoRPeBhNtYvgy+ilF7dzOv8IxcoqHnSUPiA47zmfY+RsNVd0yT24GYF4iwK6OMOzygGHXeAw7Gpv1tRDMNsGu9RggLITw5r6WYRcAo7yePJ7jW97/vCNHDXrYMcBOlknWb9Ejic1DprhZp/oedkYSW/Yx7FbMwy4uibXjHzHsVqEkNh7Gk6yhTe4taieS2CkPhJWP9nnYNW6hy8t5uFXI0C/r5GUZdiDAiiSxKcAqBdgZEI4BE1nmWDAN63yUTYnlDDs2iLU1pDmHsR52bcBaCY8rdR8ImHSSWAI7E99rGXZ77mH38gfcz3d/tv+1bOchBNbI2P6MjPAjktjQI6zMM9xVx/bfp2oRBQuACYxFA9i9WunjGJLEJsG2sJiHHZcMzvIMazvAMYZddQ4s77t/v/zj/Z9PgF1kkXL9oMAf+ab34Je+5xl8ayJcwR2PZJ5te972xhTR0yMg8ZgqZIZaDQyS5GGnpHdvdRiOD+hSmEQoiSVmo4AC2sbJ+VOAXTDwUWoirxCwayvdvlo5w9FM4swCdoGHXdsis1T3NE0f0EAcT4m9jyMveZe/boUS33fnN+K78/8EAD59QiceGWC3waLmoj4rTAmNfdaYyWfKiyQGInmhBjFJ7OXtz2z4AczENuU71/oBDlY6C+5hN1ISS5P4BBOD+og2slngvy/FsHNt5JxuM/dH65GmUTItSWJ9uWn/nNhJYuOhEzSHWPNrJVqvfVGABz8+YtgRoBReR4/lEFio7LuH3bpumR/r8HMkTzRg9yl1swM+0CJ/cw87B2oQ+EzsFgK0KiaJfeWhr1yg++7YbNMYdoVoUNVNsm9qrKw1Phe1klgVMEnhgJpQEquPM4uHThCQaO5Loa4SYLeF3UMMsEtuALG+asT38MAcK3/1POzctafNiDJk2PHvEQE4sgHjdlkRwy7wTQtZ7h1JbGT85QmxARNWCGGf3Y6HXav8TerLKIlVDLCb3wAASFqbUSgcHysDSayw61zp1FQBeMqD3A4swy4N2AHAH/rG9+DGodlAH/SwE17oRNLDrkcSGzLs6jB0QjCGXSCJLToedoaAEwRruHYUetjFQyf2QRK73ScSe2KkJBZwss6mSg+8KQ+7Vki9aV5XNrAhGzEwkOTLMtpGS2L9Y6R02VB6Sp1Ey1iDiuRlSYZdYyetYyWxdhFcJ44rAUAS88ky6yyzLxE6kUpm26dSCrj/cffv1z+sf5eSOjDz61nQcVDoxCn5anFKLHnYhSmxMsPrHLDDLA3YjWUsmpTYV9bjJLHjPeyMib/yGXallFhbSSwD0EM/QA6MRsp5QsYpwN/8c57HN/+c5/uPERNlvpehtmTYFcz/MO1hF5dsa4ZdANgRI0T4x+NtJDTV4EZMls9QKWmZBU1k0dyIHFCszbPUr4NZ7iSxIcOOySGyWT/DblFK/Jv2XbiLazhTBT7QvsWTfFPRJHJZtThd6eO58h52u/IhHe1hxxcbG06QoxKkDWQFoRypL711jIddeAxRD7uUJHZHwOljLOelRgy7VOiEC0qQImSFaUksedw5Sax/bzxDdQDJNF9avIxm2NH3+N44gGOhjGfYUap2xMNuoiS2Ezph5hjrukVVpBh2GWPY+YuxjoddKImVmX0eLktK7Jp7U41gqmYnWhIbY9ilFo9ji4Maa2LYEWBnU2LdOPypBz5g99rpCm8qD5IysWSxdljXNZDF2+eQh11pGXZd5j5Jv2L2HbkUKJrId1qGHV0DksJdBcCObYhPlVdm/lpP/3+Mh92wnI73t54ktu4CdmfEsAtDJyL91DaSWAI1rG9auGFCYCJ9nw2d6GHYJWTVUgg0UFEPu4qviS6Q6XRR1TQKM5Ak9gYAQJpxhjz0CUMp8sxtdBGYbnCR2gPsTPsyz+jhLAfMRsKCvivvn2t7nzPoYZe5tGhZpj3sIu2NNjKon3KAHakEiWEH23bK2YCHXQKw6yTS25TYgGFHktieADyvpsrnJ9R2n2gZZxMAO5seOIJh1wmdMGBfU9mBYQw7jdInczQmndUAVqn32uSjoGHaoIsQsKNziklima9ULtEoASkU0Kwd42/k4GYlsSFAY3fb4p28Y9gZgJAYdkXKl+gSLDLOXvM7+9V94PyupRF3ioEnMaPnRSFxriIyvZQktshwD0f236dYJDXuwgDNwww73VG8PkYSKyUzWB2SxOrOOWTY+QAZu5Z3P+y///Uh9uK08JRUTWIN7lO99kHg6EnngWBKM4H1AitkUowpH3SLX4+2XiODpox7oRMe2EeAnfl/0O176bytkxKk+vUyz3CGGa5DPycxSawK2MCUEqvkDIelTEtiGWAny/5JxEEp8VH1FL60/XM4WzdQyLAou30g/e68anDy6QLYhRPmTWto8mH93LgR+obeHR74F2FzjP4cdqzcm3NqGERqIyyYAOvXsgWRuFqAXdPxpQtlrM5Taa2EVjLpnVX3GchQNQrLpl8SS5PoDiAVjAfCMuwGPOwSDDveH5/Wyj+/yOt5NaEktmGsrQF7EgJDnDQzYNgRYMfATQnmWQY9hwk97IhZkQcMO7qOXshBYNdyGTzspswLLGCHmx220OSwh6D4InMdMuzM/+n3APBg6R/vaydrvOnmAQNQpwN2ep3RL4lNnR/N/zoJ8uy9cYadQN5E+mQDDmkyhGIMu6vmYTeRNSOEfjZ5enoM8AQCJt8ISSzf1ODS0gjDjtjDRZiuHDmfMFl6Sq0swy70TQsAu1ASG5vXkuoiIdPUcsguw65ulFPoNNWFeoldVDVKYS4Chp1NiTXzd/KwY6ETod2XJ4kNNhg5w25B3zXAsAPQHVMTlUvB2Lgl63Oz4HXd9kabBtQH2f7W3Fdp+hedyG0+Nzj2Wc4ZdsukJFYGthFJwK7xj2mwRgTHbFrbedhtQDm1wQk9klibLBgy2ayHW+VCJ0aAXSGzzQJ2iU5RJOQyKSZRawE7HjpBD5ffIRLI0lZuYZqPZdhldO3C4zJAYophRx52dM3Qf+3USK36Y60HL+r/Hz4BHNzxfxcrZn4dA9YOZxKnquthRyBbKImd5T7D7qRPEmvu29iU2BMcQAjguAdUmBWZv5vUV2YAXKHseNgRw05xSezDT/rvf/Bx9BW1v43N5ul4ip7U2n2tl38c+FNfAPzlb+r8iZ7TBrLjVTSmYqBbWI2RmkZTYhWbCML1uSrovzzg3mPYxfuTWZ45NiqA8+yo8xoVTBKEAU5EPsNBmaclsWZwXSuJxay/byf56+laQZnrFMbWA07+erKsLcPuDUnsyJokid0CZPM+a0s/vEmAXU/fmWKaZpFn0v4s3N+BDgPqMhb1QbIDshnwixvxWwZd13etalrrcZeF4J/Z2LQpqR1JrH/9yHx6PMPOb09Z5qRVtKjNJjLsSJ4zJSU2nPSH/yY28LpusbZAaQMfsMs6oRxK+ewoWowQY8HzNguu+SaMmkdZ66ZlUrcRG3kP9PzlUwHDTillgdJsY8DOtfV167Nb6P+cYfdw6fe/984r+37+eYPlAXZVsp0NedhZhp3q9mF1j/Qrl5nnSxU7rgINiqsaOrGJH1qnD5rCsOuRxJp7WNWtL/1ru9eeGHZFShLL5uzcP3NqWQ87ajshuNNJie0B4C3DLg4iddI9TflM3Dp9vfe4dEqsWfvMtec32T/QpkzNme3mOod2X42Kh04APmBnAy6mMOxU/1wm5WEX9rlhkjmQlsRWgYddycbqch5KYoXzv67OHGAXMOw6DL9kSqzP+huslJXKDmo7wM4i2BMAO2Je1OmBtw2QZPt7Btg50Gn4u3M+eLT1CEmsn3zEDsz8PQQSM++4vddyhh1LfawZYDdWEmsBzJRUNyVhIxTenI9jJ/ZPdtU+LzIInLv2LHD8tP7ZeJdEi0IngoRMKg0ikCSWAXYsWdPzfyskHrCEyp9Ub0o/0COpxA6wm+N4lvdOKkuZ+btJfWUZdkUnJXZtPkNxAP3kZf3/Zz9f/59LjyNF7S8Z4jKySjkhSGNf6qf+LgAFfOxfA3c/4v3JSlCRbbSj793jxPUgEG4N6QHRRR/DLtgIkYEklvoXlQTsGBsVwEoedl4Tetg5Q+Q5DmcS5zYl1h8cud/iYiAYImTTlTKLmnhfm+vzeOVkZRdsh1c+JXa851NvDU0+Yimxu/Cw2yp0gt3bmgHCHmA3op+Z4mGXOveUpPMSVWNTVAPfOXMNadxb1Y0fOsEN7cnDjqzXOpJYWoQEIFLSnoT6qASoH173RGAYAJxSU6OQkshx8SKQUNiUWAaSDLTbEAzpGHFLx8BbNwzcZIukFsKx4rKAYWfmNo6paCRSFiASVjZFG4mXwcPOzXVGPEcP9dzwJXXTAyP5eW4cOsFkVCsOqALWambVujZzEgB2Z2bDaDLTj7Xbpq67AAj9zZq2x+eitFhfW8DOtSvrqxd5b5EJJ7uLSGIBva7ILyFIkqxtN5A6LLOUh91EwM4CVq27zpwVxK79mWEPdxh2kWOJpXaOLWJGWUlsOEbadhGGTvSkxKYYdkHfZt/GJbEeqH152qIXOkGS2EZfD8eeY2NlANgJTxJL98JfBxywefVMmXXfQMCb/pyRDDvPw65M9nUx4LXupMSaDTxQSqz+bgsIApgFKbGLQrrzOXvd/aHDsAs8G2fEsPPXJKs6vZERrQsMO9kOsCOftkmSWCdrTX5s0sPOyayogeYpWSerrOAMu4p5uA1JYuNMtvBGOIadez2BXUr4E0RaRDcs2GDb0AmRkOrav5vfZ0YSPOiddxlkPKev6P8fPukAu4d9gJ1j2MUevINSstAJBtglUjjnuUSLDP9efi5O5s/ge5svTQJ2wgKgPdezqezi8kQtcP2gv13PipEedkpBWQ+70juHkoVOKM5EIcDuuS/Q/z97zQ/i6HyHPq8UY3VszXJpAcRLw7A7v+d+fulHvT81DCTeKCVWupTY1AYHAXaVyj22Rh7xsLOJrQFgVxbSM/WmwJyUJ+G88Bl2yxhgF7BKMwPYiaLEQZljmWLY1Y4NehDxo+MVBkxw9iiv47k+lk/c1Z+dCXwapMTuKJ100MOOL2q2nKhM9PJJlhBuoyzJsBtxfVLH0Bc60QHsxkv59rVonMlECNjpc5uZ8fRs3aA1/ZVm2Pkg07pusQwZdsF16xifW6+jVOjEVA87tmFFia18WLZAYnrhTH1bpjTzzUkJsxEMu6z333wOQceVM0msnmuKToouzTdpnAkX354EMwj6qPYcsPO9qUbMSR/EPez4wnDr0AkmiZWWYUcpse6zHwaSWLJk6APHosXbU7MGycGmSmIJsFu1FDrBQHUKrIi8V0qWEuuFTrifCy3WNq+5Ygy7gfTn/vc3XmJ2cgPIA5nS4x63IHBsR/YMs2t/UhkAvyOJ7Y7Vnc2SCUWgRjR0QikmiR3jYWcAu4RMMwb0NK1mz9Y8nGZbi47HUG3TdiSxQjWQaFigBGO201gUMuyQYZ5g2PHNasuwGwXYjcMFfIZd0eNhR5LYGMOOvFh9hh1JYmfCHUNZ+pt2B7McKMyahHACoAPYdew3SBJriDPdY5rIsNs3wE5sgCQSYBcGJ/By/m9xhp1iHnbZiJ2cgr+mra2HW8rDzkpIQ8CujS9kY6ETsQmiZImy7dotVPNipEFrys+FZGeJa0EeeVLV3sOWAuzEZQDszg1yfnCbAXafTL+eedjFtOhHM8awY75a1E47gJ0BB/7L4vfjf/2i78UDHNqFS6fG7EywTuIUC8sKSlUpMwey9O06t7XddQkZdnkmUIlI6MTJp/T/77zddXI97MWs7X+expYHQl6WBe7rH3I/n73q/UnZVNbNPOw4I7dNXA8C7NqsgGCBK7GU2FT6aymFf90HdslnOfOgA1DlMUms34cIm/y6wGFfSiwx7FQZ9aPjFQZMHCRAuGPzLJHR+42DcmNJ1KWpXQFFg5LYXTLsIp+1rbyWeSJODoNI7dD3hU4kwb09HksHisYZy7AJ2GoEMp2sajsX4qETjQGZqkZZBp4IgTFzTTssj8TYSQy7ZEpsGJwV82wy84CTNVugtsOAncoYGNFUaLjR/5CHXTD3CPswDtid0Uexa9la3znysCOA1IBGnZTY0MMus+dI1gjNBhK4R1nruvUX4n3VVHaR9pK61VnUU20M2DFWxirwsKN1xarNoMwilQA6qjOTEjudYZdBQb92DjZXC9U+A5JYGiOtz54nie1h2EmWEsv7Q49h1ziD/KsUOrHp2Mathfg4PMrDLj33sayjpkU0jdf8TjOe9a9s300VASA7jKMJtbLG/BEPO953d1JiN2DYRcMKiFkWAT8vEdtTtGyD0TDsAP3MO8COsc+ses6swRhgN0uETvC1pU2JTVxrr0bae+SZ8EInrExfhIBd9z6GiazU1tcWsDNBE0xyW+bhOkACpVm3npo1Wb4AgjWYDD0brYddKInd1MNu3wC7AaAoVsrKWoc97ELpVsMZdjRBGQF28de0dc0YdinPN7aDyspKaYMbYc8pIpHhLMGCedg1K7dQLUbu2tD1CL3QhlI66f7oHWH33pR3HjEmQ8Byr4qorge3gKOn9M8PP5V+PbGdVFw2dzBjvlpeSqxLN+KACE20l7WyEohhSewwYNdkM1TIexNi6btGMexY57PEzJNNCiF801oqy158QgOiAHB2N/0dVmK+3cBYyksYOsFB4rPXvD/Z8BzIjQAiLYmlRVW/JDaUr+rACn9Sbhl2QT9RyMxnMCTkNlSz3C0eAKApYoCd2Vwx352ZiUhWaA87K4mtAkmsYdido/S8NmIlM+GB6CmAjxh2VDcH2KtXoh6Zhx0H2bacqOzKw46/j6wnstxPEB8DaCY97PwJsD5mX6LoXnv5Pey88AOgs6i0gN2ytgw7oZyMk+ZAVdNiRTLPlCTWTKKVMuBDIjzFedilALuQYddtT7QoOONNQBk2TB/Djs/XmlXCw26cJHYWzBk4gNNw70B7LX1vurAtEmshNPT2PezMvN1c831Pia1CqVtfPXwJgMIaOV7HsQfSEdMD2IZhx0InlA+WZiRZUy4UJPSwcwy71vu8UWXutWXFsN9RjWbYNcSwc8dXteljKj0PO9a2KVwBGhTKSWJ35Rh220hiK3+OHn4G7+PGSGI5Ey4E7LLcAhMny9oC3bkInvGIJLaTmjmh1h2GXWQ+CTBJLJ1zn4ddvA3lYVgA3PN02SWxGfcSn11zP6KyfXzNGXbm2bN9EJyqJxU68fxtxzSzKbE7ZdixviKfMZl+6GHXDZ1Ie9iZDT2SxDJAMJe+5ZAniaW1bOmz64A+D7sT73V0TOFYnay9Zdip6Q+EZdj13HSbLBgw7BQ9jPVKJ61CJ68OlZSZNVmt60rLNTAM2HU87FR3VwJAlAVDEgXBziHLhG14rZEY1iqDHEm1dOEFgTxkADAh5lPIsEvJicVlAOyIYbe4BSxu6p+X99Kvb6mzy6JI+aEniWUMu0jyEuAe3lXVsGSbhCRWjli0mU5inetOYwiwm+WS7Sb1yEfpc5UE8lkHOFIxwI6Ap8M77toGYBQvGwCzg9CJUSDkPhWXxJ7618iF52zWzeaZsBOulCRW1XFpWM5Zc8SosJJY/7Ue+NtUgxsxs8JJqfUHdAG7lgMiSkGa+5kVcxz2SWKZh90QYAf4IF3IVqHqAnZXYPd/qHYVHJRKtqPiXmHbendsa/LNi9ousaWTrIY+hl3KJLwndEKEgN1VYNgRkyguiaVNIM6w45uDigF2y4YYdiSJ9YFOPqmvmjZ5/YjJo2IME6AL9PUAdicVZ9jV7piC11OJzPf8JC8l38Mu3m7DwKtwk08IYX9H80qeEttJdrUedgawC9L14h525K8csPX2tFZ127F3SJbZQHsVt6Clw+5eNozJMTrsISgeOrG0ktja/J/mmBI//skH+nBCD7u1AfUGmHDRIsCOM+yCvqmPJQe48XIZk8SSf1Tk2pR5FvewY8dQoLbjfJT5ddlqW/Z4bDwDtg+dYCE/HaCFAaUPl7V9bjpruYgk1koUN5LE6rbRlcQ2/tqi42EXWbvYlNg4iETPDAfg6ZitpY4nid09cHJRJQ1gpyA0YGmu0xxr699Wg4FZpo2SJJY21bSHXVwS+9SxY9PZvmQUw87/nFTlGU+JLZKbCLGQk8p62Pnj2DqQxJbB5gGf+x+UEUks/ZtVh1GaCJ1YB756g7WtNUxPbcmwo855/IE5ltjwznZHEmtlLm6RJ0c0tIJJy5p67Uxik55vcUlsKqyCFuTeOdFktSOf1e+tl3ohUSGf4GMRn7TQzl4KgLSSWPgDRzJhlz4nBCz3qSzD7qbV+nvgSVAEpjaQ0QlJKnSCrlco93QMuwarhujgKQ87up49HZ1h2K0y3WkMSWJnOWNF9UlizbmcYhFN0BRmQBB84Dw3bLrFTcawSwN2xPD8tPSwW953PweSWGpz5HE5tWQmbKBNkwLsQm8QU0UWY9jFJ4MFZza2bmcyZBJTzXKJD6ln3L9jQBlnFjEfsbyY44BJYhWTnwOwffuY0AkAns/dIuFhd1jmHrnqxqcDYLdzhl2iDcfYAVunxO6CrUdS/6X/b6pE+qhXKXmSPc4RqaIJhphXr30Q+P99O/AP/kD6NY+xKkUMu7hclMa9B+eV63OUk3cRK2zNUmJFyLAjlg4bm5tWIelhR6ETKWAgybBjigdJoROBJJbfq0i7F1LqDTAAaNaBP1z/nDj02ZxFNpzJWsMx7Ny1pDmxZSXQHJk2zUgSa2VzPSmx5hrtO8NOh06MZNiZMLJXxC398oSH3aaOCNz3KGSLZpYBk+HX/7//DQDnYUes7tNV4x3L6EUg3HhsTemBTn9DAG2KYUfercumu+ngfPW67y1SDDvAPqO5aOxzebUksc3wOBh9P5e68j6lD7AbHvfss922+jt4H8juDd9A6YxzERVFJ6F7QjlJbMTDLiYHthu6kXFxkGEXeI8hIomt12w+cokAO2KOy5lmrxrQcibcRjr1hTwlVthASfI6ZeqTzG8Db33CgVcUaDGKYRezAomdQxA64caeUJJK7TjNsLMedkq3UwLswsRqvil/MItIYssuYNfxsJsd6/+vT7253RAhp1MXKMV+5JJYnvSafhGBXSEwZiSxjJVRjJDEShb2UDcuYTYlCSWAJZTE2nCHcJCkncqGS2T8CRYVPWz1SjOfKsjRPhbEjAnZiRawS3iIEZAn2SQaAPKUh1+wa7uXZUGlW07r38OwI9ZmDWlj0XkdzSQewnRazE+OQGkRUPwJsKsahTMzCQtN8G1N8LBbZvoYhkInRktiTTs7xTwOrJhB0QJ2SjngkwN2xGgMq23t7o4YmXacqjJnKbGXQRKrlN/maHCgPyek/WNLCAFFKb6p65GQxPoMO1q0kiTWP55QijzUr8+LDH+r+WIAmrkZY7YpzqRmNP+sXOCQSWLVKgDsTN++VOMYdnP2mpQkNssEjmfunN+QxE6oIVkJ91W1O4ubAdQ+o2FXDLvz+DGNuT6pVL/YxHUodKKvjz55Gfjh7wE+8DfTr3mMRSb6WciwE74k9pSFTvBFqmXY1Qorwuc64Q5dhl3dKKQkxRawG2qXtu/r3h9aDDxcMcBKtf59jbS/PBOuv6xXlt0hmT9c6nkJ+8pZZJPBMewMWxHuWtL8OUzRtQs2syiSgWzM80wLgOh9Z9hVjRofOmEAu1czPW/hIF3LzM+F2AyxswvIVmHZErtFAW3D/KMk7hmdNXnWPWlYLadGElsPAGvRkoEkVshOv1YPMPecJNb8wgPs0gvTQrKU2BAkN8eVo7FS9TcksYizz0WG0EsrCuz1ediFTDjORGMElgfLyq57O89NpD+k+75Jf7CqSDYYsrpqz1bI7pz2Mew28bCjfo5/7iWUxEpjHdNKc+5mfTZDZdf5DrDLWP/fQIghhp1+/+c/fxPf8cs+G9/167/QXf8EOOrV2JRYKTyPuWRKLLW3iBchtUVipNMGWW6uQRkAdp4vXyGd93qPJLbrYUegnvJ87KeHTgz7UG5aWwJ2idSbnlKJHVPvNSlJLP2bSRbzcrihed5xVe0YdinAyvw+CxhmWYJJRAwaD0hLdLw1peSuNPOphhzvY5Hw3XEedvH7QOESOdxCqFISRUJObCXB+yzjsaDSjVEMu8Yy7LLoJOl4XuBEmYGvOnUPnWXY+deW75TfO9evSQIGY9gcKy2hOIXuWIYlsdk4XxcjiT1V82iKpiDATtV6V2F96haXi5vaIxBIM+wYqJ1vK4nNL5mHXXXuTzjMPaRqLcNk8467zUhuH38WiWEXMk1yKdAof4DtY9hZiWuzZiB1OnTi36l34teufy9+0fqPRr0dqJ8Xbe0x7IpyhnmRYSkSDLuKpcSOAOx42uu8xx7hqWtu8nf76AosJoaKLxa2qUEPO86w25WH3S7YeoEktk+GlKrUuUc97BILrTEedhfoebKLch52cZCNM8sdw44lm5o5jy+JNZ8VpsSysblq26TX0aAkdoSHHfVbZ1WDhpI9O2yY7j3JhPDGKW9BMiDDCvvKWN9ZBAy7jPkBdhh2GfMMhLt+eSD38VJJlb+gqPc+dKJxzJnY8/qz/wT4679F///VnwIAfDLTDPAYwy40P59ShQULnCRWf5HbsKgZo54ksE8c6zHn1PzbSlenSHNNm1rAjKeRtj/Ww24Z8bDr+JCxKnPpUmI7/SFJYhlgNwYA2PeKAnYTxiO+XmsTmz+d7xkeQ4s8YMJxdhQDJrgktqPuiWyI8cAfpaaBdusmlMRGNt88JmDpHwevgZRYGWPY1WQRwAC7SyyJbQnwNtdgjrXFIygEygPs2gYHhbSAXQOJQ9qkjsxXvvVL34qv+eyn3Nx8DMA+UhKbCT8ltk4wd4tQkgouic2896zMOUvLJPQZotcWjGFX5g58o/ZVdAG7joddcQCQNzdT2VVWQTdy3LjAdrcVYOekmBMksQkfNv9Ftffa8L3c9yjlw+YdJ0tMbOq13SnKEpO9LBE6QZOilCS25Qy7wJuFiiYeDrDLRydIqsQDY4HEBMOJfi/R2uueAq6AkRLOx13EgptdH8WwUzVj2EWQ8uN5jhOwh9qAL2QCqoIJCJey3DvTk5SUh5ZjLA4z7E4My+/avP+Z0my0EewN0/GcYR6V32RcutCsHXMxK3QHZj3sUgw7d05bp8RySexl8LAL21vgfZBKu55SLQvaiVYiIEJvUlC/NMCwyzOsQRspa+fd2RM6AQD/rH0PflY9k2DYsQmbmRSsVIFFmWt2A3lKdCSx5GFXpBmrrG4euvbbB3I/c8NNap+/1R28r1yFKZmblFJp5hgVT3vbdkd7px52wVyhY849xcMuXKBG3psMnZgADO5pmh2lYVqGnZ3bGEmsjAB2EYbdum6ddxZ9RiCJFUL4C7IE8ExpcSq10AjfFwHsYum23qI5eL397gxef1lzD7uhhO2QYRcZk+m4aM4qOIhIFgmtfw+sJJa8f6S/GKm58XcAuO69JHYodOLv/B6+l9vqAAEAAElEQVTgR/434C9+PfDSjwIAPpo/D8Bn4XhpvhsWvbdVwDlvkgzUaZDhM588AuAYdgTYnQSS2E1CJw76ADvO9owUpcSeNwygNrXusXYppe9L5ZV0hADHsNvPvmxS7dLDrq+P98Iphr/H+SgS0MCALQZMnCzrNMMuMm/k3t5TWXaOYRfzsIuMo/TzBimxtm9jQA/9bL2cm3V6/N7jchtRZlwz12AGJok1nrJFnnls/6N5bjfVGpXhaGb+1idltfLjERL2kaqNPBMsFGKWlOk7CXaMYUcbT8YrHrQpUAFQHUksZ9gtStmV+JLcNfL9zl5CsKTYE3dMJPeWI9dxF8js3BKwIybGeL8CNcLDTqU6rQCwWyuJYuRFtB521cqi0FlCTkuMqDB0IuVhZyVvEQ87pJJu187DbnSCZEJeIweAUwImc9Soqtp+b8o7zwGWe8ywIzbT7Nhn2CV2hpyfWBadsB3PC1TIsRamTSwfAErZCYgIOgCZCdupkPwhBTAkQ0y889GA3QOlO+hro0InxnjY6Y7nJMGw83ZC66UDoRY3dQdGSUVMJuwV67zlLiSx9pwugYcd968DOulC7ZahE/q9hr2buh5NvA/OmW9nTfYDCW+6QrowHNRry5xO9SfhDnwUqOaDOwF2yN1rzfMkOqETXBI7PNG6xeSttw7T49AzjGH3ltufDoDdDiSxHnCRkvszBtSugiJ26WGXDJ0YA6SlGCUR1lwgE532PcMyqMdZazLX78hY9bnx/qBV3MPOvybrpnWS2I5U1X1GbifyLHQimC/KQQ+7UBKbZtidrpiUlx83YAEyXnmWMa/VlV3cFhEwLKyuh11aEutfSz1nTXnYZRQ6ETDs+iSxpBS5DJLYhq5FuJF39jrw8n/UP6sW+MQPAgBelG8GgGhK7CQZalB8znxSsc9pK3tdK+R42ow355X+3Z0j3U7PLcNuE0ms7tMWYuX9mxctjmPBaoDxd4ILkrEgY6tYO46zPu0iOeHBVqKGsODMVWLYMSuhTT3s+sKbJodOBGb9XBLL1ikPlxWzKAglsd3v4W17Koi/6qTERiSxMYZdDAegZPcESzOU+wPAutY/t54ktt+eYB8rVwHDzgB2c7FGBlq7G2Y787CDanE0yy0ZqUbm1Cd9LP9mA4bdAJFHZgHDLuFhF5Nghww7YrWtWvfc5WiYPJ8Ydu4eH85kN2SCMALv+/1gJv2F3aRYGzoxlmF3gYqJ7QA7WgBOWKirxATMK+v/FgfGhDEmryeAXTbJlXkm5QOAnUx52HUAu65szUo+EomyilJipxjSJ0Mn+hl2siCGXYPGLJ6bRFoqP2axrww7pdwDNTtyDLu26jJ2TLUJ1iYVUWrPhHlgVw89KZ+IDB4kwbtrGHaLMgWAEmOxR3pivObuNbqD7gMfAGJFjWHY6c89wzwqGcxkiZbkQPXSD5wAgPkQYOfaiNxyV9WXxO4xWEy19CWwXKoPwJ5D2I9NKeov2zpxPdrIZAh6wOsw7Oh4Qjae52G3thsxWWLXrcsSibR73lc1BNgVdsEqZxo0y9q1f6/N7uo5ZkmJOS/OsLt1lH5mnv10Y9iNCTsYKt6vJBl27HndFnjaltHgHVfgYZcwSt/Iwy7GdB/0sNtAersnRUERHQ87C9i5++0x1cx4R8Fb67rFsu6XxAJusl43yrUv71or5GrA3D40NbdMPtdXlea4T1a1n6jNzy8in8wyYWVJaCp/QWIX5vGxsJSZ95ExD7tQEou26UpiOx52BNj5Hnbk7VRZwM757KlLwrBb1a2TxIbrhpc/0H1DeYSPFm8F4LNwaGE2eoM8UnzOfML30Fi7aZBZeSkx7MiGgf49lOYaLTPGH2Lp/ZvXoIedGbvD1F0eNBBl2PGU2ATDbiYqCJCv2lUKndiQ8e1tQPUwbyeGW7iUWGLYccDOl8R6/RqvGGDH7QgmyuStnDrmmxYD7DgTLizLsIsHIeQhMwrsORfscy+hJDZvSdFFHnbEsFtbPGLtSWIZw26WQwqzQeNJYnsAu/qiPeyKJJs4FnLSCZ0ghp1i8wPUKGn8l7QR4s7teF5oXIAXrWe97w887IBoUux0D7uL24DdkSR2uoed6gMZSEqR8IPJDGBnF5kjioIhWgbopAAuAiAz+A2cHhgZHhelxHo77r7Uw/6aGHZGEttMOAfq7DvptRgA7MzgWaCxbBsddhG//eRdlW2z2LvIqpfuoZgdaxorXeeEjx35d4mEPPHYUGqtLHb1wA0cAETET4EGp2GG3XhJ7Ou17jhvDiRZ+my04dCJE8yji4NZKbGE+a566XsDAo5KHPiz2eKA3daSWO7LdwkYdtSXEAsxIYndzsMu9z4rLNrRDjdN8swx7NqAYZcF/dcskMTSc5/qTzoskSjDjnvY6edojcIy7ARPbeIgOzHsRnrY3WLPye0ekPtXfP5z+OrPegq/5ee/DW/+dADsxoQdDNWAl5f+PWPYbeBp638WX7j0SwtHfxY9k33JfKlKyZhiEpMhVUDfBsSem2NbwC4RFBH1sAuBL2j/Lkqc1a9po/MkT6oSa8dsvAvDoGxN8LB7cF5FwzJSbT7PhNdf+uy1fnmzEMLb4Cgji4AwdIID2LSB4zzszJyYADuzKArZAzWXGlkvZgPe7Dlgt66ZJDZcdN7/hP7/0dOuDb31y+0c1mPYESFpG4YdmzOfVo2Vp3FLgFpJrGp9nLSQpA1Y+veQ11y0OoBdjGHX/7m5zHBYSieVNG2BGFJAvE36DLvguQiPC7hiDLsdSGJTmz+d7xlmlvOUWKVUGrBb1czHOHhuIpJY3mYmS2Lr0MOOn3ukT+zbUBxIiY162JmHWxFQXK8de+wS+SnmJInNQw+7yiakriMedmhrXJ8xhiSyrodd7Fo3aXl9p8b48UIDYQ6wmzG/zsDDLkxpRdcvznnYsTETNWQgib137taLR7Nch1HyovUsq46HHeCAPraWW1tJ7ETAbt9SYi2za4oklvy8RnjYhdItAvsyy7AbvxC2zLbKDSplEX+QredbKIlFShJrPps9ECKx497QDoBZpNZTFvPWYDLBsEs0EMmYhM1KX7sGMsmwy/adYWfZXsYLS4hBHzsrT0yg3hQL/ZCCJ5YP7MDRKoE8smNIgMKJSf5Ke9iZdtt3PQ0g9lql2+SNgSTLGQPsev0gzbU6U3GGXSkzLGnxUUUYdiMlsY0SyHtM/8dUmWeoxvjy7UsRe+fwjv5/fe4NZnRfQs+4SSX677ELiPDbJ0/GpsAVYRd9XYadC52oWOp0OnSCV1RqzYNrzC7eShW2DZblwjE7uSzWAnbFKMDOY9gdpidmb751gP/Xf/aF+L2/+LMGP/NK1EiD4N7ibS41+YixCHYZOnFhDLsJHnYpX7po6EQWf+0oJt9+MgEcw44AO18elg6d8CWxJ9wEHQjus/t9wT2KYiFlLHU6KYkNF4Q9HnYPlhU77mHAzgudqNc+q2nEM8DnCbHNjlnIsFMc2Aw97Oj9tJksvP9bDzvOAgxAAc5C28eqmpYxhYJx8IEB7F74SuDX/FXgy3838Ev+WNefCPC9Bjcsvug8Wzc+U435Q69qDaZQ6ISVxFYE2DFPwbFl2vShSDPsqgEPO0DLx/oYdrF1QSGzdEqsaUeHYOP4hDXh3hbfLLCKqQ1CJ7g3XcxmJDbu9awLCThQyoAd3OstkMSmU2K7m0TSY9htJom1Y4EnB2YpsfbL+hh2ph2FPmSmYgw7Ol7FmXsJf+d9rkIFKcvEsBNr6yFJyiofsGtwrXT3rwXzsEtJWZVi4GjcL9Cr2FymbYGf/gfAvY/aX+UZY9jlZdLDLg9Y4IDzi+ukxDYCFAhRovYktwDwf/0ln4U331ro5FvAhSVSRSSxMeDXetix9e7mDLvdz+e2+kRa2IkpzBrLsEsvJFIedrTwpejjeoLUzHrYrRxymqcYaTIOsKSAMeczFdtx929ym+V6bmUWErUY35nYMIjg2tFAKhOeU/w828qBnalo+yxx/ntT9DCVR+76zm/oJNMBhl1KnkghD/cJsFs9tMygFQrMiu77QkAhBdhlxLDru55Guvqg1R31GEks7Tq3TZWGrk2s9Wu4FmXYlXmGlcewSwF2KYad2VWGHL8DkahZLvFwDGtwX4qYYYdPAK9/SP+8PrUyYpVg2U4qG9KTYtitzcv89iKEsP2SlcQmJP1F7nsyiYENgMOg3ceM0wUHjBjDjtrgwTzHOUocYuUx7FR1BgHgXM1HSWK5vPWpa5dnJ/XCaxcedvwZTDLsmFRt24lKbFd+Y3ntEGA3hvmW8MDpDZ3YRBK7gT/SI6yVZdjFJbHDDDt9Xjq1kI0Rykk9eR9JE/m64Qw7NnbWbpEnkpLY4B5FNlCJDVI1Ck3OjlsEi86g8kx4FgJNm9vf93pVmdKbFpV3DLyoj/RAlRTDjjzsrCTWMOwCuU8sdEJcRoZdOC8gwO7ac8BnfrX+D0CefUy/3GPYbR86kWU6FKVpFU5XNSpIzFB5DOMaUvs11i3o628fBpLYTY7FgGAHPZLYIQ87QBu01yc+W4azSGLrgrkEcmGe/44kVh/HEQGJIrtURv/JouefWeNs7mE3lmE33H+EXnN5IiX2wbIe4WHnzkcIgTwTqFs1GcTf3MMuBtiNZdh1pZT2c1XDxv7LMy+0YUpWEquPfYbKglTrljbKBGP7N7g2d89tDek8oFOhE20NTJGwx+YyH/p+4K98k/75d/4EcO0Z7WEnnJdlysNOhl6McH5xNAdwbFLoe9usUKB2ZCpzv9/7phv4p/+XX+A+PJTAxhh2kfASFzqhcaK2Vfb4+/pUry5wA3arT6REkilm84rvOiRKRDoTwE0w8kYPDPUkSWwOKKAxHnYrleuUlUiRtE8iBOxMSmzQuC1gxyaVNlE2uGmhD187xcPOMt/8azc2JRYAGuOz1fR8byold2/KJsQeu98NMOzUwM4VSWLvtQvNO13dZ2b5RXRifTTz721KEkvXvxewM9LVU8xR5tlgQmYpXUpsU6/Td/PkZQDAK+pGnGGXSyxVoTcveOgE7UiQh13o10ZlfVvkVlITQC9UqpRXzT4WSabn13Xn3NY+YNf4i6xNivqLpCTWbpp0B9zWXEuSxDo2XsiwcwtQVa/tYCgTg/hRkGAcY9gJ2+bdhG3FJLGHZY4zzDqAXbM6RQ7gDLNRoRNf9vY7+JPf/Ln45P0l3vPc9cHXf9rUGK/YobKy1DLq5eV9zy5YcdHP2nB33KbEUuhE3HdpI+abXYixid6QJFY1ekc7dh0vUEKxi1o3+vl2klgf/OIbNX54g/+6h5zJRp8TASs9dlQemS+a/qRWWTIYpwP0ReaUsyjQWLt7lGLYZYJtcKxRGd9ZySWxPc8A3ziLzSvILDzmYYekhx2xGMjDzmeheIsO5QPRU9k0j7rWddthhNl6+JL+/7VnvF/HGHa7AOwA3d7P2ybpfVhDYlW1nq8Sl8Q2rbLZaEUPE65TIySxY4DA43nut3cwwC6xJpplbO4aEilkCQHGsLtEAElv0Xkya5yNJbG9HnZdYL4XsAu85uZjPOxC/+wE+yyXBrCb2CdYDztaY8TGcv5dfRtmQymxESmj/ZmDfORzfon8FMs2YLwZH78Z1hawIz83z8NONThmDLtRHnYciB7zzIrI57z+s+7nVzRgpxl2bu7o/DoDSWwkPITAMyuJtRtPrQPsRO08bPsY9rNrjmgSYdjRZ7dKA3NZJjoedhWb46X6xk5d4AbsdoCd9bCbIomN+7B5ldDx03vz1gB2Exh2NJGsVy7sIUVxpPMJQycIwAsniZa1xSWxCdCRFuAk620mnAMttEUbP64UcFqwTqxejgHsiGG3BTvjIisG2PGk2EgNgSdWEtvONWC3dB52K8YM4nUQAnYJRtAoibFNc13g5mGRZD9ScUms9SjjdfoacPIp/R+Al9UN3InJbzjDrjqPMOzIw+5hfMHJjJZTAPjYmgXhB3tXP/X3gB/934Hnvwj4Od/qdvCKA93RL+/7Pna7MB8dYAJlZiKYRQbcNvMZdrbfCCZpMyntdW/rtV2Yp/qTRSGRCVj2QAwIpo0K7mG3QmGB6INSYqlmGihmkljy9jxHOQhaA3pX+Bvf96bB133a1S5CJ2JSltT3NNUodlFv8Ynl1vJa33oiybDbtYddJyU2kIDGFmzbnusF19Iw7ARC8IsWDnyhwBl2xkLEAnYxSWx3cuulIJaR+2QksWsUaWAi3BiOzCmjYRmqgd2n7fOwYxYCzjcs61+Ym+L9ZYydTAstT84WBEXYRY75N81VaVGUdzzsuqETl8XDzpfEBs/r2ev6/wd3vF+H569/3j4lFtALt/OqwSkH7LiHnWHYnRn5a5lndn6pmXfM93eSJNYw7HoksWPO8dqiQK3867luhgA7BvgEbbuVJSSAI2HG8UsEkPQWnafHsJuuJhvtYdfUDExPz334urVq0h52D86rDjBrK7EhpkGMdoOUWNfW9eduwbCr+gG7aEpsyLAD3DrxEgHIhQ1Tmnn/n6NCIYzfZMLD7ho79QaZU8KkADt+7TcNnTh91f189hoAmJRY8115mdxEsOw5HjoRSmKJBV8r+zwW4IBdz9x0cdMBdkdPdv7Mj6duFUoPsHtojs21semS2D3zsJMDXkfxbzSgU6+HHTFB4rvVpQHs+kCnzkeSPGw9ArAjD7uQYZcE7Ch0gneKCYYdyXqJYTcFsLOLYP/aDQF2ssitXxQBlk2PTI8kzmHoxt4UT4ilGsuwSwyEi0IzxB7a0ImHjmGniujE2noEsM+I1SiJMWPYDQVOABqooLYUBez+yjcBf/aLgU/8IADNsIvt5pc587CrV5HQCcOwU008gdcMAg2yabvFkdIMuxHeUo+rXvlJ4Ef/KvCxf6P/TdejOGBUaud9MMTqHFUyWHgGRYCdiCRet4FUnzYRupJYZ6LeVOduYyIVyiOEi4yHiVEPX2NB6tpK2NYqdwy7mZbEAvDaFQF2VbbYmgnxaV0jDYJ7K2YW3fkeHjpxAQy7TaVVoz3seq7PFA+7VEos/95Un3aBnie7qDUF8CXYakIIO/a1MS84YwnxcBVKYtu4JJanIMY87Kg/QZ4GJsIU4B4PO++423bwfkhPErvyU/BGyGE4IznGTqZ5RZStSAw7m4po7gF8fzbrD2Q97JiPEAGpMpDX7mmtmtZL5fUq3GA0FXr4Ae48t0mJBVy78Rl2rv+jlNhz4193UEpvM/fh0vUDmzHs0kbxozzsehh2KdnXXDLALliIqkwfx7Fl2F0RwI6eYe6xuzHDrmc887zuhkMnZCZATbhuWjdHBwKGXZUGuu3Ggv89MaB7THUlsVwOTIBdLHQiMq8dy7Bruww7Tz2yIobdZQLsKLXVnLsBY7WHHTHs9DUOU2LvHLh7eTwvnXQ65WFHQLSQ40gFMXuKMwbYGfulPMsYw27W42EXC50gJnjmvaZqW3sfY6ET0eLkkjvv6Pw5GrJiATu9JlmzMJ7xgN3FbcBuB9jZhd2EDlqyTixRdmGZkJcUhjbaTPB/o9cSYFchTy4ICfjK4R+jTEhPibXFJbFZYtLXmsGuaIhhN8HDLsHUyi2QGP+snBvQG8Cu7SFXygTDcG9qA4bdEPtDCIHjec4AO8ewW6KMgl2hZC/GwgMAmfs+M9EyQM+JWowC7PQHmjYd7lK9+tPAiz/k/epldSPuYSe5hx1j2NH1LA+dp08seEI535Yi31ISm0snc99Hhl04ybAMu7nb5WShNi41c4uOe8DDjpKjYvJVu0lBoRMJRrQOnTCvXTnwLI+AgFRcFnt90X2dxwa2DLvSLlAPSokzmInUmqfEasCuyeOGw2/UyBphPTFYsZ3xsKhtNwnpy5SKethtCf6lJLFjrs8kD7sEM4IffxKwG16kPc5aNcSwIw+7LshGrLCGA1/KZ9gBQAueEtuVzQLBRD4GrBqGXd8crnOPIvMxPqZbxpEn5U1swInQw46nxA7fS775FxvrHcOuK7ekY0qlxBaBJJaOrbKypMx+Fs0npy7OH3VVdevmBeHzmgDsYovBdlcMOwYoe4AIl8TWjfWrWxTa35fuyYNzdw7TPOx0P+QYdt1+NrU45nU8L3wmLEYw7ESaYddkoVT38gAkvRXzsJsUEshA5j6GnRfcNG7cI/CgapXPHvJCJ+o0wy4xvoZA/9jqlcTG5LcyshFDNeRh15MuWuS5u8a0eb6nVhOx6gB25hosRG3X+SvysAtCJ5480r+vlMRT1xnYmVITTE3RjX3OaRewk5lAKRyglkrE9jbmACilbD/kmOLMz5Yx7KSda/Yc++23u5+Zt6P7fs6wM/0bAXZm3kjtShrv0lF1gRuwWwF2Q9KpaFm20YiJcsfcVF+AmSLAbvwFsfJZI1nrY+fllmHnT2Qsky0ROuHJ1sjDLiGfJVlvO+Gmki+UB/y0LTJjHJkK0dCAnZmcrQko7JHEEsNubwE7Q3M1gF3bqmgcMy9iO/X5iR3Pi2hK7FgPu2vzhIcgpcSihTUvCcvsBp1hjpuHI58nAnNCht0n/p33zzN5DS/itseKoprlGVaK2CgsdIJSdoRwwGjMx47tKudbMuzK3E8r3bsKfcE4w44Apprtxu6i447tarGigUtGwTVfEkubCCFDOM+E7R9bFsqT8rAD3KISiCcaezJwK2HzGXZLAux46ITpn1TeHWDfqAkVMow2qdjOeN/3bCsB36mH3cjQia087CKS2E0Auz1PiV22ul8XPeAXscJiaav+RqIIpJ7d6+aMpts4E4N5Yg5LYtMedtx7r4keU0ISK7mHXWVNs72U2J5n5trCfW4sXIr61jbmYUeAXRMAdnZuakInpM9CaTgLMNgQn+pX9ahr3fDQCT7HVgywu+G9J54Saxh2A3YjQ1XGgF62YdEoiXXdOsCu1AFvB2bsu88Au9FG5kDEw67bdjy2Z6JuHpYdT0AeOgGlgAef9OaqJIltIDu2KK05juOMmFFXjGFHczoh0UkBH/N+bvEQ9bBj88qpgF3dAkdPuT9ce9b+6AN2ASiflMR2maljqpsSywB2C9jFJLExwG6TlFgG9NBnE8PuEgHIpcE2ROF72C0Yw25pALuCh05A4c7CeLIhw1PXGGCXCp2o00zdaMXmTEYGC8Ax7GSYEmtYvwFDzd1HY9vA7ieNzV5ivDlOHToxQhL7S/4YcP3NwM//PdE/8/WqBX+JoWpUfEPM42jtgqiRqK1W2MRAmwTYjVhIEIOsK4nV751hOmBnmWxkJtjDMEtJYp30ND6B9xh2dnfZn8CTD19BgN0kSWzE/4/9HF+068mL9TsbAdjJfZfEmo74PDvAV/+Jf4wv/2M/gDNhOncmSfQqxdpklWLYrVBiFpG78pTYMs+SKbFee0lJsMjDDnPcGMmwU6azUqnktNl14PhZfO8T3wZAdFJtAQ3YLb2U2Hv6Z75jbZNiI9eW7SqPpgwnivvy7SVgF/qCVQQuzaFol4rtxu5CEiv4xCestnEy/cgumbL9kmn7CYawEAK10G2gZYB3vgVgJ/jGDAO+yb/poJQ4V8w7kd5nwLs2MVl7o0YWn1ylNgmGagxjjgMq24JsF+FhR+25A7qNADRT52+v7YjQCf7sp/r+PQ+dsAy7REos4Bi3HsjUxudAntTTSmLd2OGnxEbuE5PYDwJ2NI7EPOwY49w/7v5FcyYYYFevAg+74Wfg2sL9LQbY0UZgrdIBHs7DjjZXfWaVk4Tq39sFLQvGcAy7PQfsvNAJNg5W544l0mHYdX2umhFg1pgaAnorSLTKSV9p3kWy2Htn+hzKPJ7ImqxOSmyMYTccOvHE8cwHzcEYSjID/vX/AvyJdwH/4Xvseyh0IrbmIobdMXnYXSKApLcsSzt9vXuLzxf7GOMcvBq56eUlXHKG3a236kNuWpxXzQhJbADYxZIzR9TK+DXGU2LNM8r7RGt1sKuUWCalpHO6hKETBfT1EAHDbi4qC4JZwI5LYgE8YZauNTI8ecwZdtQGgns6cJ07xQIubNGGCaB902EYdkwSa9ndCQ876rPqiF8c/X9dK/uclIIDdj339tZbgf/6x4Cv/L3x02GHYxmlgSSW+sVyytp2Xxl2RNHsk06FRZOErA+ws+BKsLA07yWkeRJgF5hQ972XmGoZlDfJzocYdvycInIQAFDmHEq1AWBnGXZxwC7FsBOCA3bDkljaEd93SexPvA78zMsn+Pjdc/yHT5nrkGDYpRYPvI7nuWPYrR46wE7FGXYeaLFID+YeoB1r901tv+tUzXFrJGBHbasL2H1S///n/mbgd/04vn/xizrHSzUrJFbWw46lxC5u4qX7S8NepOCJ+92DIA87lU3bhYjULHfhB1tJ+S6qQj8lAzT9qX/2Ij541wfxAOxmp6WPCcTuewysJzYvyWmp3whTYgGgDTY0Up9Jxe/0jYgk1vo2tg2UmRisVWElsZQSC8Bj2GW1/lkUh8nvfqNGVDYCKBqqMZJYbpi9Kw+7ZpyXT291GHbBOYzysEssnqKhE4njzTIHRqU2IbZlJl5wnVvALmTYMUksJZt6IJMPDFEpT+ppFhFRSWwbB5556MSY9GLvmN338El4HWEG9oVOVJYJvnam2p6HXfpecklsbBONftd6YJCZv5i2VwUedpZhF3jY2cVQBFSk+1JdAsAu6m1Li8Usdx6ypvpTYrdXAlB58xWmNgCAe2e6/zwo9Gvovt4zDLvZ1A1O06cdijQzxgsXSdQTR5xhZySxJGmUAvi7hpHyf/wu+56ZIOuTCGBn5g4OsNvPjYfJFdoqTPXmG5sS6216jRv3PCCDe9jd1IDdiQGLW+UDs7YS/VSMvTamrIddEQB2AGNyxTzsIvNaGrMTtihRD7uWMaEIgLpkDDulFEpFntS+h91CVBZ/IMa7J4kFcNucZgOJF55k8+eYIgBg87uJgB2fM/H1jgFIdUosZ9j5/qpUofx6zcInrCSWs/BMmynHMuwGSgjRtU4ghp2VxOrfj06IBS5UMbETht2U0AnLEuuRxFomSDDRCwG8KWAXLUiJwdEnifUWqtTIlXKAXTEsr0kx7GjRvzCAXZ9EM6zM7qbyhQJbtIfMP1Y00KqKwi76GHbEMNxCTnWRZQC7Dz5wHcAHXjMPO3XSQakR4MnxvMAJ4pLY2APLJbHXewC7bAiwW7tjPsUiyliKVpJh96L+/7VnAABnzPw4rHkhsSSm0+rEyo3/7geX+KL/8R/i2//Kv4MawbBrkDmT0w2rzF3ohKr30MMuZLuZZ+nuWuLjD02HXzsPO8uE3Sp0gnnBhcWe/aLoYdhZwC5tYWA3MMzzUymJIhK0Yj+bsbZixunka5qp2srwddqyYdjNZFQSS+nZMc+JN2pCjQk7GKopKbFc+rItK86T0WwJ/u1EEpt4r2dN0QO6DbH59jx0YlkbQ29lLB1UF2Q76njYOVZYFsxLGg549kliG+Xff+oDzdhQQaaZRKFXcszDjjHiY+BYkmGXuZAePyXWsdf6FhJ88y/GsOpeSxbO0UmJ1a8l+xbysAsT+Oj1BZfEmmPcdw+7NU+J5ZJYskaZX+/INPMIC8cCq1tmGfG5oMewa5zaAHBMuoVl2OXm9+vO54wqK4klQKM75teJxTEvzbCLA3a3ZXz+XApi2HX7t8aw8496jutSlvWwM3O6qf2zBTgGPOw22PQqOJDx5GdrhumtF6yVDbE78yIx9qQksdwzbEJ1PexYO4ltmlkPu00YdmYzgh2jz7Aj5cZp93v3uJpWYSYCwM5LidX3bNVGQifgEmZnsxK/4Uve6j54KHRiLAMxNmdi6x1ax+qUWBoHnYddSOgIwTIe8FAGDDvtYecksZbwteW97TBKLcPOKDE583hspbyPd1Cbr7CVstG9+ZQOum8BakpYJki4Wx1O/MZfEAp7oHTWegTDTr+RADvXmMIFr2XYsQciJetVIeg44abGPOy4GX2fhI0mFtMAuz2dyJmO4aMnrvn+DDFzkwy74YHw+qLAQ0WS2PvWS2Gd8LB78ti1+z6QLfcksWnArkaONYrxoRMp49aHhmF3rP0sTo2XSszDbl4wSezJS/b3f/gHNOj39/7jp/BQmcGjF7CTO2DYZXbHut1LSSwNWOb5M8/SEqUvK6ayaXybd9x200JF2g27RkXZw7AzwF5mQycigJ31/dD3eIWid5D6ync5GUZs0SnMmCBVhbpyjBhKkzwscyeJpdAJpZCbMJ5s9gbDbqvyvNM2fJampMRyVtzGya4kDVpvD2JZhh2FTiTmEr1p9Ylj6AudiI2rQ+DgtlLiC67TOgyKGCGJTXrYAcq+Jp4SayfpnGEHuHbcUEpskZY3jvCwm0WBl+GU2JylxKrapcRKDtj1tNuv/iztORV64FLdPtJ9ZyzQgD7XedgZgI5SYgNmggud4D57/n3Zew+7unVecbwvo7le2R0r+hh223rt8nmO561n2iXN8e8Sw44AO7OxRR52GwN2IsJYMtUkFse87hzN3HqAPOxM+3hKve5eWJ/bDbyyh2FXm/O9eqETW0piox52MUlszFaif5O3yIlh1+rNzd/xw8C3/wv79wdL/X0Hc3MvVONbYyQ2FkJfsbGV9LADEoBdn4fd9JRYJ/nPuiDOJZHE1q3CnCSxpSGOGJbhXKwta+3cSmKFf50N83xWFF4q9XDoRPw6d2oIsDN9RS6AQtBccJZkNoebSg4cE3ZNYZmkTRsAdiMksSOqY50QAHarehPA7uIUE5tv6TLArcM466ksJusMSrRxsCtk3E0JbFAWsNM3oo+dxyW+bb1GVh56jbRjxh6hiqYZdv0AXl9Jc/6SXbum1lPHVgkURQ/Djs63Hpbipjz89qbMzurrtZsYvLSSQImkh10yeZjVjUWBB9bD7qEFEk4x82QsVDyJp49h5wPAkWtKgRPGhy/maxMrYRl2wbMUBEecrXoYdrnEq8R0uv9x/Xmza/jwXbfz9dKqxDUgETrBUmJ36GHX1qseDuxjqo4kVrePczVzsmIvJZba3PYediK22DcLhFplKCJ9sGPYGaZLwsNOv7YAGkCsxwF23/4VL+DeWYX3vul69O+2D1GV9c1co7ALCZ0Sa54fAlUYvV6+AdhtV2PCDoZqVOgEl4RtybDL2SR+az888z4ChDZh2KVkTDFPGMuAipz7QHDMPjPs2lZhWcPNFBOsuGhKLAFDmYQQbr2oRAYoeCw8fu7Of03597+ptESocRL7ZIBAyIaOJL9yiwgfaOxn2EkO2DGGSJ5xSWy63X7p2+/gL3/r+33ZEqsveMtNfPVnPYW7H/p455hEgmGXIeFhF/gDFTJjG0k5gOpSeNhVLOTD/cEAdhH7BOuPxMDIRg37u42pks0FXXqtkz1meQk0wOunum3Q4vnAMuw2BeyCNtUTOtF3jneOZhYAVU0FAcdueRKv+S8++RQwO7IpsTFlUm2IE0cw4/glAUgGywJ2GzK1OLO66RnPvE2vcWNBKRlgB2iWKSsC7BbzGchODKp1GyMJNrxlHE0A8dvWpXt2POwAJilmv+Pjc9v4a2jqsxM+xmECtj5eAgyFkzXaN1wOALlpFWbmZskIw44UftQXFnnmbxASYy7lo9sJnRhhecIrNmeqIgy7lrEm83RKrNuY8xl23KrCtUcniR0dOjGiqC1ZD7uOJHaT0ImLk8RuAdgxZtcEwI4WoH0edla6Fe7MBrKvdgOGHTE4+hh2nEFX1ZWGMzzALvVAMIadmUB12CzhOU2RxBI7kQFptQHsamS9gzQNtMKwxvq+N78kHnYP1QLP3Vggy4DTu+Q9F6f0p/x0eN08LHHCU2JNB3Sm5rgTmVw9zZJ4UgmxACA5YBO7puZ7Tg2TbawkVvCdOV7kQze/AQA2rewgsqO/KKU753sfBQCsCn/w/+SywDsAJ0HhxSSx2wJ2uczs5K+TfLsPFV5vAzCdo3SyYi6JtWDBFh23ZSSnAbsKeXzybz3szCTAAP0xr0sl9cQuW+t7vGLgWqxmucQf+LrPSf6dGHa5qnFuGHatLO3O2eEsxzmxEgmoY9JYGWFNvFETygPsNuzHx+xiUttmDJONdz3pffVq+13K8JkLj8mOw0qDSzHWTQTkAZDwsOtZaKU8ZKhG+J49rlrVrfN3A5Ieb0dhsqlqrCpBZDkOCmmZ3m1UEuu+wyYgNioOPFPoBPI0W2qEh93x3P3ss9kGJLFCYEVMcGbdkEsWOjHQ53/p2+8k/yYzge/69V+A+qUF8OfgXyfzuXXgYWf9pDOfmUALby891HyWnl9Xk/2qHnWt6tZPH1ZKS2BpvIjYJ8QZdsNy0TEVD51wskdZlMAKeO00YNgFHnaTjMyBSB/W7WfHsAgPZ7nd4Gsa/XQva2LYveq/+PQV4PYLljFTRQE7CsNI+IVe1pLB/GSyJLYL5sY97PimV2LMCYrme6smzoSzgSezEiAOQ1t3x6IQsMt8EGVMce8xB9ix8+yTxAL6uQnlx0BSEhtj2K25d2MRMMYuCYBcM8DOSWL1/2csJdYCdllmxk0BQKUBu1ToRNMvPe4UefHy+WSMYcestFpR+CnqrDjwqpRy4FjO5wLsXhvgtRQ1xM4YdgH4mwid2IhhdwFenhuvsBs+UZnwQAjmbZR8jZVu+Q1PBEj5FLBLWcDOMMx6sMoil2iUuZHmPLlPWGfBa45TsHNKMuy2AezyLpDWGGCjGWA4EUBJgF2vJLbYc4ZdVqCWC5xggbfcPsDztw4cWycliU0lD7O6cVC4lFjV2JjqU8y9RDmqJ5gk9u1PHSc/t8glKtWzaLMApD6HsZJYag+CA3ZKAUsTDrG4oY/feNgdRj3sMnfO9z6mX5/pc6EJ5Ssrc81i15Yx7MIdlI1KdBdCe1OhjM4sGJaY+cEdpsawOge/kgC7GNBrjqOCRCm791YFzF+XKNsdSFqT9CYNw26tCm/gnHzcpp/PUbtk6sw9LwelxFIFHnamfZ2rEovZfsoDL00JJpeI+cSMqWbELqbHIthyEsUl/mO+u69SvnP23zyUYwhI29bDLmB7hWWlxPvX5s+rxmfVJBh2b3/yCEDoYecWhUcMHPMsRJQPPAFuMbqum/h9sqETOZJTnjGAHetj4scdnyPx0AnFUsHzkZLYMSWEQEH9dMvAT3Od6gTDTqYYdm0kJdZsPO89w65pfaCIrrFl2HUBu3hKrP7/toAdl1LbeV3j+j9pFsCvW8AuN/8nbzv9+8kbnMlNB1dVYnEc1vGBnmu2Zv1AKZ+31V3/hSefAqAXyQAL2eDfCWqDKn6cl7Vs2uimoRNszt/rYUfj3sDrWJVcEhspAuwWc7Zmjm0wpSSxCSAwVivuPWYBOwKS4ObEKcCOj4usP01JNaVNF2X+lBxYCd93SRh2ddNaD7vMhk4YwI4z7BSTxAJsnmeunQj6ldSG4cYMOzNfaSp/DrQ+AZTyGHa1KJIy/YJtKtSMpck3MgrGJFWWYdfsThKb8rCrfA+7mCVWtNo26vG7q9p4RVZB4o9W34w/Xv1K5OVIDTScnLQPsLNgV9CZiAA5nwTYUcJIawCrPoZZ5qR5dWWMZOser7iI5CVLediN2CVLVSy9lQDFIcCEqPvSdJ6ql2Go/5bvq4fdr/3f8V1f9s/xD9svwNPX53j+1gFOLGAXZ9iNAU9uHpQ4w8yxBB5qT7czNY9KYguZ4Rvf9xze89x1/Lovfkvyc3MpfHPisMwxnxgAYyxgJ6jt8M9cPXQdhqHJn63SDLt5Ll3QhgFrHkAvvr7MsABeOjfnzhhQthjDbrLEI1ZWFrfHgJ05Z2Xo4Ocq4WGXSIqe9JUGiBOxxf4Aw86mCBvWCE2oO5J+AK2Z1ORMEjuZAcBKMja0MjtvKnPfezhzKbHKSmKNxBhlVL79Rk2sPp+YMTU1dMKmwW0K2FHM2cpNPjedbA8w20d5/E3ysOsBefoS8fq+Zw9qWTVu7AKSMtZvfN9z+GXvfQZf9dk66Mhn4knfr40rEiKfVXLfGg48W8BO369xDLvG/3/Edw/gvnrDktjM87Bz45QcKYkdXdSWlJMX03zSSj0zYti1kBn3/vEXtV56qPWwI7bengN2det7p9E1th52R5339DHstt1Y9EMnmLee6UdIcXSXJLEUtGTGtAebetiF43YkRXOMhx0AXCPAzrSFpQHsjlUwfz55WX8e3MZsWDWCtn5VQidoHKM1xaYedjxMYsjDbiRLfTYA2JFP4pEH2DFwZUASOyU5elW7z/XmjJ2UXXb9+Pnx+YllMxa9GyZA3MOukKIrpb0kAHLDPOwy2oTIHWBHHnY1cgjBQHnLTqT5WjhfiWwwAtMZduE4zNc69Pn1ErmRq65UjkZxmb7f30nWRzWtsm2Zb2RwxiepJH0Pu+3G2c7GDl13M7asa2YlMab4HG+fPOwqUeLPNF8PAPitEySxxN7ql8Qayn4gPZUBMMgZG8NfrB/amUlnbXoAq0IKnEFihhpNZQCxSueCtUogD8Ab2vXkLBhis8iQ+SIDcHPCJN1eOy6JJUCxLzENxmdCAbIhSWy6MRUEqgqFpq5702cfV33qgb6PT12b46CQOFOMYReRONnk4Z6J9I1FAUDgFAsc49SGN2gPu/gD+ye/+fMGj7WQ2QBgpzuHE7WAzIQn1ekry77iC06Sw8oZUCxQNa3duTgouvd8Vkg8VP4A93qrO62f+9Zb+Cc//QpO2hKQcDuNvFrX/nbBsBMyB+pI8u0+VLDwbtdnkADOEfewS6VdTykKmokz7PoBO8UXrZ6kPyKJNRODjAZbFJhtAdhlPGnbMEgVmxhwSWy70teRJnZnmFtWwhu1RclC+9dsDNiN2MXki5JdSWJ5P7OpnCWchPYx7pJAWsIoPObl0vbsqkY8bqPfc4kBu1xm+NPf8vnAq8fAn0bAxMs9wK71/Iq6QGfJJbGAvnecpVK7EJuDodAJek/ke/g4q7hsaEToxDriYSfFuJTY0cWB4cDDrrKSWH2tMtF68z9aHDlJrAGrpHCMawLsJrBpHket6zZgefoM95gkti8lNttynhINnWCbmXkxA9B0JbHGY/relqET7kC6RIkxHnaAAexeh/VWW1b6Oh2FgN2ZDqHok8RW4VpqrIn9vhdd7z5/0r7i48Qohh0LWxqYM5KPYgqwe/1U95E3jtjc3huv4mMOARNTkqPXLHDCCyDLcv09NJ7zc88krJSTz08GAicA17c1HmDHgJXwvZdQEmvnLwaUn6k1FGO5FpJda7qHqTTjpIfdxA3WcN5TLbuvWZ1Yf7kKOVTb+inqrPi/q6a193AWk8Q2rVVJ7jJ0ouNhRwy7egm0jV07bwbY7X4+t/EnlnmGP/or34u6UZOo3fkEhl3oYZeXPrAwBbAjdsdcUehCekIlhLAThMZ0JiQ9rZF1kslUZMddkIQhlMAGC4k2BPB6yqa38tAJM2FskEXTGqnIG4w8/PoZdszDr1rvJWD30n0D2B3PMC+kY9hB6cnTzN91dUEmaaDyhmG2PcSBBuweaMDuHHGG3dgqpGA7sbHQCQ1onGKOG4ti9ISSZIeev1kgh6XdXABRINCTxJp6udb/fsvtAzx1bY6zByRdjEliDXi1Aw87wDBQa2wOMlxkBaETykpiEx52ifCcSV9pvjOLAnZmAFd5nA0XmzAiBdj5fesaBY62SP3NWD8nKsOwY4PronCS2HZ9qp+OtQvxOBoJWr9RPcVTVzepMbJUyRYb9D0bg2zkGcT6mY0ZdsH7OqAbl+SkgLSm+1oAUU+YXg+7CMDnfc/+MuzOqwbaNTfTqfEciIsm4sbYc9J7noUnie2mxFp/pjoAQUNJrCo8WY1/HKEkNsKwYyCiEtIEYdSD98Nn2OljyYQBgnaZEMc3XALFRhg6kaNBweYNIQslzrAr/c/a01o3LVoOFJGBf48kti8ldts0e49hR+uIdQjYnVmWEykbnCRW/360zIqqk36ZZtgNJeESkEMpseeGYXdAgN3ipg4vM77FhQmdsBJgVqtwGRm5H5eyRoR8jHr/oIddRBI78F0eCzlSJMe+ecgBu6b7c3A8HQBjRBHYOw/bsyx00nCMYQfoc2xW/vykHmZ99abEykjoxCUBkHXoBM2h/NCJEms0RvG2RjDfp7GGGHOpoMtwnmPna2MZdgHOYaXOM31v1yfA+qGVxK6RI2tVUqbP14t1E2fYcT9bYtiVqCCaLdUcpjoedrztVGeo6JhGS2I5YLd7i5ONZ4izXOJXfeGbp3+h9UfrAewMg0wEC0sZAnYTJvP0WWTcOCSnbawk1gBiFrDLMQvZW5TkqFznKS2jK2DjBZ1HO4E+ThMs7i3XVM7Drq8IsCsb3Xk2Wbqh85TcZh/N/wF86qFj2BUywzlmaCG07G992gXsEr6IvG4e6mv0oJ3j2QzAiZbEnqrZVnJPLbGOGHZSUegEFqMDJwC4xGXeSZzf0/83cljazT2e59oUO6hFwUInTL1c6X8/fX2BZ67PcU6AXZRhZ6QSajeAHbXx/WTY+YtA8oM8Rxn1sMtGtLmhykYx7GRCEssZGsyDs+g+++FGwkr1p8QOVVnkaJSAFAoZSUrYd8hMoJa6nbUrXxJ7hhmOZm9IYreurQG7ESmxVsa63oEkNvK+TeVV4fvCSTs3ax70sBuxY90LYg0BdhsyOB5B0WLMAnYqzoqz5Rmtu/Pi4JjdNAtAPaqOPxMHhQEr/an6VAWhDDkCwnHAxE+JHfawI4YdHYsFSHYpiY2Ec1Cf7jzs9L8z+Aw7m5JqDL290Anrtbb/ktimVWYxlUFBQPDn1UpiIymx0STJuDRranG/2FaWGuhl/r55qQE7qmPT9il04v6moRMBEKHyOcLWXzXjGHY3j/Vn0aYiSWIPGpNQcON5DdiZDWBreB8D7FTQ1iOMx0tZIzwDeyvqYddnmcAksQP9x5Ak9rUT/Tm3jme6H+GbI0BaEhthrw0VtZ1ZqODpSIoj17NZ+ZYUZk6dSogFXNvmCdBeCnbIPL0kAWZ1q3AgAoaduQ4asDOvg/Q3HWicsJLYELBLkEU44DamuEUDf38+18e7PgGqc8iWLCsK5Lb/7jLs+D9rBuzxtYyVaDet9dkuRQ1Bc80Iy3hKdTzsigXsvHB9xnz1Rm7yXDDDbgemU9MqN95GUcaIKQK7QiZIxytvCnIeAFRtD8MMcF4NZMpaM4ZdZzCMTMgzmxLrf08WnIOaxLBzu6lUTUMeYv0LXJIAzwxg1/YCdu66c+++fSraQbpzPDPhDwLnPT52BKb2AnaGYXcffgd/hvn03VBWWhLbFzpBHnZz3Docv9gltqpQbMCjc5/p4AjazU0BgZqd6A+OL671dXzieKYZdiQ3jnjY0Q5tEw4iG5awMt899rBrKm2uaiYX146vWQ87RR4ccCDbNgw7em+Ukdw4aVi0fcYWz4gz7MK+dIVia5CaWCiy6gJ2AOxkRIWhE5jhMOK3+EZNLB7isEmNkR1YNp2Kp8FNqXDiKOTmTKWOLCYyzo5lvqX87/gcRnWBp87rU/chBQzuQZEZfcstHfoARh5CwkDMIxbwkHEwzRo0u+vGjaYBuH6DJukN7eAXHbUD+xLzHeRh1wXsuCKBQsZSkl9eUgisDUhBklg7J9wlW9IukNwxEeNaKaBtXYpujtbbkLNMmbb1ALmCMezkJQid8ACJTko7SWK7C3IZSbtMLRynljcuUntnrOAy2BA7Chh20c8ZU8UwYaHh0ueeun1NXzOaOxIwv+CAHWAZdtbwPrLOOFdBf39VGXZbpcRSv9Ania0mSGIHADuzPrp9WCYsHOIbC9uETszDYD6aBxgFUWf+F5ufbMmwK6ToMk8vSXusm9Z62NlnnRh2iqfEBgGTYejEGM9dwAF8YxURKQ+7Yu6Od31mFV+VytG2fLMoIDoJwVJgW9uO+DrSpp0HHnZohqXTY6ojrxaCJcWe2PlPB4xO1QV72D0GwM6wxHoAO+f/FujrZ+GDOOFmBY2yHkCVG4NaNwawstLYyIBFu55ZxMMuC+SkWXDM4b/7yl47BtgRoNj0pL4CsI19rvTEQvXs4PAU3Hof0zrhDH1vHhS4Y9JaKbQhDtiZHeoYWGFqXkjM8gyvqWve708x38oEv5DCmfX2hE6cYm5luWMq6gcZ7DrfP9fX6cYi/rnzQuKB8ie8rzYa7HviaIZnrs9tOEAsJZaejxoyyuCbWvb+NHsIFGdswcCYdNeOr1mGXbOOedhtzraQfYBd7ajn0cm/ZQQ2dlJUq8z6n/AKmb9rbMewy6VjoeRmMRN+B02kRBA6caZmvkn9G7VZPRJJLOtX6m0Bux2al3cAu8hnDQFpKaZVNHSiD8Qa8rDboe/ZjmtpDMVbLyhipPzX87Bz15CCdDw2W0QSW9lYz6Adc8AuBb6EybyJe/lzPuMmAAdgjJHESiaJdQy7ALDbiYcd+37TRrmlR9W29rpJtN61IKaMUuw6ApCZAkz4EFlq1BP8qh51eYBEYEnRmxJrFn0tZ9iN9HcbKt6Wrc0DHUtWYBGMXYc7A+z881yJbp9WjwQlnzDtndZh9JzPajN3vm4AuyUBdrpdr1T3mThFfFy/9LVFQCAAv732jaVcuTHSB3asJDYN2JEkNmDYWUbThNAJA2rMw3klnSsBdqnrGQudiMi97dsi/pRVm2DY5YsLAU4uovo87ArUWAh9TzvqFxs6QSmxCUlsKnRiNMMu4WGXz1i66hnzmM1R9zDsAGZd0CQYdhlj2BnS0VzUENVuALucfb8t6r+qMwdGj7XE4nOHHouyTeuxAXZ5jyQ2xbAr5/5D3FkA9pQIOosh/7s68LBrCbjrAez4A5FZRle/rDdMvu0r8vTzJLE1edgNAXbk4acfprZnQikyidbsOJPkdp+qblo8MLHlNw5K3DnS52alnasuYJfyRQzr5kGJV9V173dnam7lDJtU7oVOxDzsDGCnFrg5QRIbTVy2k1jdgQ4x7BaFxGs4xppJHT6unsDNA82wunM0wzkBdhGGnQOys61SRamcL9/+tTvPa4Qx6Y6PjlEJ4wfEZMOOYbd528nsPY5JYh3DLnbtnVTfLUKbcHeOKti9X6HYijFZSMewyxsD2BV+n6tKAuzMtaycxPgNwG4HtStJbG9KbGQc3RRo23aB5B1D6Pe0BcMuFVihWo2IeK8dYJ31fs/+LSzO13oe02IsYMe9xpxE5/rCXUO7Edu2UUlsR+5F944WJOb/q1EpsWkPOwD4S9/6fvyJX/W5+MynzZjPEln7ATvyDTKAHfWVu2RLCnZupq8X7Do1rfIksXlEEgs49hTgqzNoLrTPDLtVY8ZQgY4lRT/DrsvCIdbQtgw7X94dAHay7DCNyDt4HrA0pkti/TF6GUpRMd7D7s4NbRlToAaUsqBLWRPDztgdkYedWa+tI5LYExX0rW9IYv3XN+sko837HQf2BiSxHZ/PoF470f3F7aMyvmGU6Kdc6MQESawBe8P2becBtB5LBUHtwsOuJmZp5gPGl0QOCwBN02JuJbG+hx2vFcqA5UubRwmGHbdWUOy+jrjWXqUYdvnC9U3VubcuaRjDLrZRUjAmdL+HXYvGWOgsROU2h7dm2HXbku2/1md27JyF7NFUXbAf8eNj2CGx2wwnJw0Bu2LmDwSiR+celggm8GpgMdBaSazvYddELhnJ1gSXnRHDLpiEy5BhN2Fws6ETUCDDazq+uidEA3AMO/dhQ4CleZCq/WPYEVgHANcXBWa5xLV53ssEy0Ymdt44KDoMu7s42iq1spACjepLidWTpBPMrSx3TDm2ah/DTrdbvmDiNS8yQGR4GTft7z6u7uDJY91Obx6WTvLAQCoqKxmHHJRhjClZ7C9g91f/vfY0XFVrey3WSmIxn1ngvWXJSbbNbdF50zMfBezMgFupBMPOY7tQclP8PoVM32097DhgZ69DMDGQBNjR4GslsfM3JLG7qG0lsWMMsGXuAwv8e6dWx1R9lwy7yMSOM1BjlfSwC1JTgfG+brHa49AJ8idqY0ERfQw7gKXWSbzvLW58sSFWic/qsEdo7kaMgMb1e0m2VAiSJq7xvJD4FZ//JszJBmQIkASQZQJr8ixtSRIbjO87kcTya6m/h9sr1Aywy9FASs6wcz9ToADgwgP0x+tzmMKmedRlEyhlBjGFYRfzsOM+flvU8dz1b3ZdYQG7vANcOIad3ya2Zdidtt1+1vr0DZzjE9edx/PD8yWWVQuJBnlrnrFrz+r/E8POzB9WKu+AOadtaHVxVQC7LSWxNH41lVOMxNYfXOo9kqHrALvu2FUxQsOtw1kcsEsAiFxKP7YsqNEJnQhCpMIxOPQZBcalxEZARWIJl1L4771E4HHDU1ctw657HZYo/c30zN886kpi2b+Zz/7k0Ama91A7qhnDzrLSTm3/TAy7vo0S6yHXtJZh56fEurTzxlyLA8H8krf0sCtkl62J8sieCz1foy2xLtje5JEDdmU5gmFHktiQYRf4v2XF+Al9KIVUIyWxreloCRhrY9JT6S9MATAPuxB09M9Bhr58PSW5N0brH9dYhp37sIHztwzD/ZMm3j3T53w8y+0D/cTxDKfkxWYAMF4iwdoM6+ZBiVfhM+weyJtbySgKmTlJbAx4MZO9s8mS2AjDjgZHM1ARNT7FsBNC4LDM7Q4qALyEW3jymm4ftw9LnFlvwIgk1nooZlvvXAMO1Mn2ELBrzIAllWPYLVHicJYjK8mPzYGaWaIfm1IkqY9ZCLQDktiMbySYQTbFhMwC5u8a+XahEzJDFcpngok8bVbI5txot96QxO60HoUkFuiOJZsmu2aZP9HZ9HOA4dAJYDyQ1rdwo+eyVxI78D177GH3YGkSsb0ABDrXnk0CgAF2Ob74bbfxtjuHeOGJQ+ReemJXEkuTaBc6QR52JIl1C4IkC3iEh130uJlf3JjQCcElsUqhNw1yanlsRb1Akez468Z52GmGHZcSuZ9XDLDjc4U8TJzdwyIGUZln3eeoJ3SiLyV2iH02VF7isQXsDItIlh3p60V52IWAnVLKgtxD7PjDhesPX773EMuqwQFW7gXHBrAzDDsJ98xVgQzzpL2qHnZbMr75+GulrjFrBqbcGBP0hH4PO7ILygRwY1EkJLHxsc16ik2RxKYYdkPXLwwTAnxftERJ0X221zwFmz8n5REuS7VrDtiZc5C5N2a1EN25Of2d1h4pCw/AB21tSNhUhl0A2BUBw45JYhvmoRpbQ3OvUedD2A2dqFtlVZELsR4lnR5TUYYd9V/rUzv+zCZLYi9GLfHIAbvCSmJbn57JKjeTijzYjZjN4wu+MRWyO4aolBTS4Bh2aUksseh4kqMDHQOGXXDMeTm+wcmCXY+WpLrjGHYdRuGA0WRtPfz2j2F3zwB2Nw7dOd85mjlqfg/DbigA4MZBgVcZw+5MzaCK7WjVeSaYJLYvdGKqJNawr6BcJ2onsXqg+sRd3bE9eyPdzg5nEt/fvA8AcHfxGWggTZAHcOuw7JXEto1b0IkdaPZdkMb+AcU5B0jNtTjHDIelhKCBo3aT3rFtrq8cq7YL2NGO3FDohFAupaxKAHFZsBioRLkVSF3mmUtSNCWDhZU0Sc6Z0h577blOpHuIxRuA3S5qW8BuLPgQjiXbSFn55HGsGXKspnjYTZWqehPgkMEVY9j1+JcCGBXu8ZjqlYeBFHPI4423ldrt+M8Lie/7HV+Gv/tffTn7rMYqBTj4Rx6bjmFHTBVfErtG0cOwC/wJBwG7kecHIBPCbUaYeycz4bMXLoxhJ601Ts087PKOh11XEltI4atADKvwMnjYzfLMZyIBvZLYPOJztSsPu2M2Ntl1BVlhZEXHL5gksaGtymKskTlVMEY/bPx+mS86B+W2jFn1qXsnOK8aLAiwExI4vKN/Ngw7aZika1V0fNMeXFmG3Q4lsdYvrM/DboIkNgzmYfWa9fcukWUinmrexMerPBLWMlTUvyRDJ+yHhxt7kfnJCIZdPAHa9HF55oN0l0gS2xoQqkHmtxN2LSqhAxb7QydGzFcAxrDbMHSiijHszp3HrCo8D7vYuoMDxKseSSwArIW+DgvOsNtGhQHW3puUJJbA6IkMuwuayz16wK50F1glFhLks5GX/knPytwzPZ3CTstCSezAjSZJbCd0IpIuq+zCeJhhV3YYduMHt4IdM0l0SZI4lHqrAoadGDj/Jjj/fSryZePy0SeOZ44JFvOwG8l2unFQ4mPqSfvvV9W1reSwwIiUWC90YvykgD9LTiaiJ46naoYf+uhdfOyu/vebbqbb2WGZ43+qfwU+/HP+O/z5d/x5ALCA3e3DGc4ozKNeduRjbUMpgrvZUSBfPrmHDDvrJwdl79m5muFglltJrOAMu5G+iX1lfQrRusWtqbpyXk6x3XqXuOtkXg2yqCRIBoE+Q6E8QzXLnSSWKgu+I1+wNlmdoT4zgJ06eEMSu4vaWhI7zgDb36EV2+0u8mdlmzbYWSz0MeyG0lt7GHahR1qMgT/IsNvf0AkC7Nw5DHi88fNnDDtAMzAKyZhSKUlsyB6he2kZdjx0YqqHXaJtjg3VgF4wUt8muIcdf8524mHXZdghK/wFKzHshEIu3KIjy4QF9kgSm2eZN37nl8DDjkti3cI0YNhFACIZWYjZBNVtATsmic06ktjC92vMhN1MCxl2k8e44Dwf1P7n8XMdZMezvuaVe6dYVg0OhXley0NgblQm9TnQVJANzTUK6xdmjyNk2F0iGWJvhf3xZMCOhSpQ3xDdODKfWy9dfzgUOtHDsCNVza1D8xkTUmJdCMAUSWwiSbNz/YJzCp9nYBQQE2NFWXZWJoCD2+7Flwg8Vma8rFD4gQVs7kJWDB4gb5Oq/fHW/T2iCAC2YNjFPOwcK43G5wo56qbfwy5nKbFkzVB6klj3HgrZOcDKedhNsEWLVZxhRwEamzDsrhhgVzIZa7XuAnZKKQvYhX5vpcxsGiOAToBDX4V+dx3GXVCWYUehE8xcPywrPWMsmFzFGXZFwBLsJN/2VF64c68qYv7ph64ZmiAGnaco+htUCFjuU9096/qy3TliwFKECUaSwpC1GdbNgwI/q562/64htwqcAAiw6wud0BLeUzXH9USaa6xyDkJTR2Emjt/zQ6/iG//Mv8C//fBdAMCbb6bb2cFM4iXcxs++8OvwsXN9TZ2HXeG8AYHOtbXA8Y4owLkBIQVnDe5JSX69zc7zOUocltJKSkXjaO3Wx3ILSawH9gULfqLQV8jjMlfJNhKsh138tUUxs0EzALDMtpMSaMAuZBf7u53zco6avB2rMzTn9wAAZ9nhdLnQG9WtRyWJ5WNpPtsuHcv7rB0y7GISm1DiEVYKuPEAuxGSy5hXD68x4R6PqV415uU22XWIgZZlzuvGptZl3dcAPjgWSYl1oRMphl2e9uoKr3nke/xjiiTX9oROWElswxh2HPjdiSQ2A2DOjxZjsvBZAZyZKH3gjQy9SbKWZ8K7DuQFNYVN86hrzZMDw/6MWG0R2Vufh93WKbFMEmttaqwktsB1tul667C0yoODwm9Ph1PnlcEa5kHtfx5nvg0CdplEa9rWaw9OcLpiktjiAJgxH+flAwtMr9Fl2D2spBvHI8d5aasDMG0K2K36wRHr9cYkkQPrFBvMEwHWqM92gB31bdy/LD62O0+vKZLYhIddR9U2gmE3QuqYR3zHCOwpZOYDdpdIEkt2Op30ZzaXWZlwuyJnfRi1lToB2IkLYth5HnYpSeyAh91A6ATfkFtCH+cx2Bp0S4Zd3MPOrFPWZ+m2naqr5mE3m7nGsY4EGjRNi0KYCUbhdyba7Ne9X87Go+cd+eyAWSF51VkGG3nZRZhslMaYtcMMu1DWm8/GswSLPHfprea41EiGXThQDAOW5GG3v5JYzrC7viiYdDMIR1DK3Y98CLArcc5i6n9CPb812yeXwoZ4qB6G3QkWuHk4flLgMVAtw05/1sdO/Uf7rXfS1PBDwyA8WdV42TAqnjQMu6NZjlbOHZiz9gE7ei7UUPsbWTkHkves7eUceDMg6zlmOJzlVtqesWO2DLuBNtdXhSeD99tOYxh2tSiicmQbhqOc71Sj4gy7WSHtgAgAK7mdlKCMMOxCFt8BD4qpzq0kdp0fb/Xdb5SpmEfMlBopz/EWNtvuLHqf9Rg97JRibIfg/GOhE2OCGFL3YZe+ZzuuV8zij9i6PqCVAr9GLiCYtyb/rJI87JqQYUeAnf7cpSo1oyJ6DFM97GIMu/j5eYBdyzzseDva1YSdjoFdSy8lkX1PR5FmXreqKEGRgYrsc5QC2j0F7dZ1D2AX+PXyiqfEUujEdsueYwbYPXXTAFssJfYG20h+4sj1Q+HG78GWDLt7lf/+ygPshkFJWjO8ev8UD5cVDsAYdjJ3TJPVfcZqzVHVfltZNsqpW4BLBZL01s4ksVU/OGIBF7ZuGRhzO0narF68p++jtcGJMuyo3w0ZdpTKOUUSO9bDLgTsAok7MI1h13QZdrkUwCEH7C6PJFYZwLYK7a0YAL4yc/QiyrAz7aezQRbZYAQ2YNglQieKheuDqzOPAV81LagLjjLsKOQkGTrBwpNM+OE1MI/6i/CwKx1bMNm2UzVWlbJhPYbQiX6GXc0800KGHQAsGfqcT6Be53P/wc0GPOzIZJkAlrbPw45CJ4hhpxSkoLQmf1ANGXXlfHyHoqUY+vvrQBLbDHjYhQPFkCTWpeTunzTxrgXs3DlfXxS2M7MdCRWXgQywnWh39C/c+p148dlfiN9b/abpXiNBcUlsHWEsKiPhPVXzjv9JX3G2qvMVcN5qVN/8hW/uDbMgQPJsXVsJFAF2QgjcOpzhnK4tTZLp2JmH3S4qCkLuSRUlB+w0uHSuZjicSSttl4xhZ9Out/Cw86T8IcPOAHaNiN9bYcNwams/UENGd98XZY6HcH1TlW/LsJMdwC5kFx+WOZY82dkYXNdXZcL/uItLcjapsZMPPpbsErDbimE3sLsP9AN2HvgS9G2C+QKpEBCKhVIxU/FYjWUyPoai8UB6DDuzSEyy1WgBGshpw79zSWyEYVd1POx0e7RMhDEedgMpsbaiIGKaYRdKYmWW+fd3V4AdHRe7lpKzAth1mwt/8U6LISuJlZl3HTg7cV9Zdh5glweAHW0exlJiI0whmxK7JcPu1kGJL3jLTXzem2/gHc/e0r8k5YEsvLkWhXcBXUnsZJ/WoH94rfbXMBaQzMQoP2Gy8nn1/ilO1w0OhGljtK6aGzBy+cC2vxUKrBufkbysGnit5+ipESdzCSp8hjeWxK77wZEYODcwjpJEb1l12eEv3iPfatM+Yh6qFrgPFGBMohjWyw+X+Ko//o/w3/+tD3i/tx52oWwwvF4dr9uIZcfGHnZGTikz4OCOe/H155Kfs29F49o6ZNgx0HGpIoAdXcfkeMuY2h5gxxhyY4qP20DCw+7MA/c5oBzbKKHzqJp4YI4Qwo1jZq1wXRFgJ7aeM0U97KKS2P3wsHvkRkGZlGiUgBQqCtit10u7V+MtkE3dxzHehJf136ew00LAbiBhlnafLIONpLGRSaqwoROmcXKmXcCumQeL1nKCJFbv7EoANWrDTqSFuBqaIAYNKAaG8mqEBJRj8u1TkYcdnxjdOCjwEUWgUiCJZQPVmJRYAPib2Vfh+H2/Efc/9COdidbUKqSwKbFNXcE7gqaCMFKfqR52ZSFRKakZqZZhpwG1UzXH7/qad+Ar3/Uk3v5UPwBCgN3JqsHLD3Qn/OQ11z5uHZY4W81wiFWHvegYdrsB7DwQcs8Au5wPbEsD2KHEQZnbvkiqyi5oMzON3SYlNu8D7KwcPv75xO7N2hpNXSNHOnTioJS4p47wlLgHAKiK7UCzMs+wUu64VqrALJDhH5RS75oJANU5MgOCtqWf0vxGbViPLCV2hww7PlHf5rM6oRM9DLtYP+P5kUXOP5NAw9hYfR5pdB5TvfL2oL73t/48vPJwhfJv0DkMS0Y9Tyage028gAdiMTIPOwMOdlNizYKEJXQPe9iZa6t67g///VhJrCJ/UP35RcBe20oW7h1XbiR1XBLLGXbufPLMB90ItPIlsQ6M5MBV3bYoH/3+/WCtuIcd78/axjGSelNi3YKRZE/bSmKzTOCvffuXQCkF8UMf0r+kOWfme9hxv7tw43fyvDJoU3eXPqgSS1nsrawAmnN87LUHAG650AnaMJtdAx5+Um+kkcxNFRagoVpVjbUx0u+7Igz5rVNi2UaDDZ2IfEZ0M6m/bcxLAuy6wNonDGD33A2z1oxtTCXG9r7Qie/+5x/GB185xQdf+Vn8F1/5Au4Y9mjSmH8oPT7rAez6UmIjx+gYdpnfH9x6Ifk5e1c1KWaCNsKeJ2KZ+R52tKlDKbExlr/07SyA6eBSr4ddRBKrctt/A/GNkoI25+rW35xhlUuBulU4N2OuZQIXi63HWZ5Ca4uFTqysP+NUwO6KSGIBoDY44bpadv7WVO7hLSIP7bl0C8ni4Mbo7ywXQULhgM+ClcSSFLaHSWQXxmZS2LIOKDScn5casKQqJsh6hfCBHwA2JVYNTPbD0I1BwA7k4bd/HnYOsPMZdo4FFkhiOWA38CDdMpLU107XOF3r902WLgSVZxla4/HRYSwycLHOD8ZTbxGwmOyuswbszjDDC08e4d3PXR80zCQvlZcfLnG61m2YGHYAcPuoxJL8ATuSWPNc7IhRUJaFez72LHiiyJlXi/GwW2KGo1nuy/Pr5SSQeOg7bSUYdm2CXStsv1Rb5nKDLCqXWRQS9+H6yGpLWarMhMeGPkfZGfQOZ1wSewq51jtn6qpM+B93bSuJHZ0SuyPfOcCfbO9UEtuzKIp52PFrFpvQhv53faysIeB0j1Nin7m+wHvfdMOqCMYBdl1WmP93NvGPeL50Pez866fM5y5VGZX3688LPez6WXPeMQ2cXyEdw06nZyrjYTdwXTapqCSWe9i575pl/uJdZhneKT6KaqnHbC2JpYCT3AM795ZhF/Wwq/xN2d6U2N0z7KiEEFFQ586R+92z1908O8uEB2psm4R+99TvT2IMlb6i+cFrD/Sc8UZuPq+IMOxs6ETeYXWdrhucMHb+zsDqx12d4KKJ8jtPEkuhEzFJbAQYHLiGc9NHnkcYdh83QXNdhh17re2rAsDOpnZ2gcB//9G79ud/9aHX7M9JY/7O9UsAoBumxLaKAXYta/tCAJ/3a4Gn3g28+1ckP2fvyqxbq17ATt8v7xm3G2SJlFigy44DHIg8lWEX9bCLS2JpswiIb5TMLMOuZf2Xv06gf5+G4TYDKskxJe04EfGwq5yHXYc9mqqrFjoBALUBveqYJHbNJGURcGXBJiXF9ac7f0/VbOEvAocCK9ogdEJZD7sIwy6QxDYcsAsYdrNcQsE13NnhNDaJTW8NGHaDHnbBQymHQicsYLlfoAnAJbG+h5314Oow7Nw5hL6IYVHYwssPV7h/rt93bb4d86FgHnZNeD0NANYogcPFtAlByY39A4bdmZrbpNehIk+WD76spblHs9zz7bt5UHrAilc7ZthFQcg9qTLPbEoTlvcA6B2vg1KinLN7FwJ2W9C281xireIJw60ZMJss/ixT2IVUtd0IqZKSWIn7yi18mvJa5zVTayncNTnHLMowsBP95QPkFQF2bzDsdlKPShK7S4YdX3xvYygcLq5ii62+MAh+zWLPrwieyTGhE6n7cMG7sjspjxU3BNiFHnYhwy4G/rlrXFhmWIJhVzuGXVoSe5EedplROujK0ehF5EUwJUPATha+7w7zKyoCht1vUn8Nf2/2e/Du//jHzd99SSwHrpoJnlWPshzrQvpehnbjUEQXbjEWTrOj0An/i8IkzBy5zPDX/4svwdd97rP4Ne9/i/fnW2zOelBu97y/HgB2Uxl2ND8ozLrlVmHaL/XBFDzBGXYoOiDR6arGiboiQRO8wns7NUxjrCQ2bL8j+o+FZdj592Jdt/jQK3qO/vanzJo3Fq6U6OMsezfSH3zsdUeE+Phd9/MqybALn42Uhx0bf6thwC7qYVez0AkA+Ib/J/Dt//xSedhRH1+F83lmEXNmAbuYJDbhGQt05yuAS10fzbALxlTuYWcBu3MvJZYzQOMMO+dXWyUYdhawU1s+j5Hy2Or2cyl04oQlII9l2F1sgNhjAexIFFitIww704jWKi4rmMENUk9dH89Omy98iZcsx3nYEdijrCS2+zBkFDph0Ou6SrNrZCaQM6+R+URafGMmaDZ0wjKcJjLsBs4/ZBjuU739ySN87ptv4Bm2e+mHTgTtquH3o38RSCDXum7x0dfP7GdvU0IIez07qbsGXDzDHDcPpy1QZxxAot0SxrAbe9wkLf7JT2nA5MkA6Lt1WLprm2TY7aaD0ufUI1V7jFXwlGqTaEqhE4vZHJViiysO2A2AxP3fKZxvZgAsKNNXtokBl3wqM9XYfrWBjA6cmmHn+sh2S0ksAKyEez7PVdlhjx7NctxT5nvufcT2n1jc2vq73yjsQBJLbJwJDLttJ8j8/bMt2mAIfvWy5GKAHZt4xdgOYfJeXwqplf4k7sMeS2Jt8R36Pvkvf+0Qw66pokBa18MuCJ0w47uWxO7Iw85j2PWz8fJMuHEXQIHaZ9jtEnilYyDVQFb4KYlsbjELPOy+rfkeAMBnf/x/04cVsACzTNimvbcMu5QkllJZy8Po8/koGHYAIiwiPeZ9/vM38T//6vfh+dv+GuUpNmfdiGH3zOcCAB6oRQewq5sAtBgoYtjl0G3CMuyoD/YYdvpvKxQ4X/sg0cmqxnfUv0H/40t++/hz2fcSwu+TNwXs6vVA6EQX9B0qmkuFgN3PvnqKulU4nuWO3RkDaxKS2KgJP3Rf/Mn7DqT72OtuHbCsE8b8gymxkXFxUw+7dhpYvZdlzr0OPewYw25pQCvPD86OEYkNMv4aziSbGpAQtiPPw848G+tTCwSukQ8y7Oh+rWsXOlEG95Du92kbXpftSQUy5mHHJLHrFHs0VWPnzBvWY9nSXYsSUHHAjlh3NSRizShvV/bnMHWpr+YH/kIiHwLsTAO3zLoxDDuz4GxYcMZQyMHUQZvkxJapNVISK4LBJh+dkrt/gN13fv27O7+7flBYQ05VncHrGkwHU6vMlxhGal5I3DgocO+sws8Yxtm2gB3QA4AawG6JcvL3zHIGIFE7qE4hoAHAsZ9H8e+0gxYy867Nc5yRJDZgL9rnY0cyoHkhrex73wC7UjIw8VzLA7SHncSikFih0LvV9dKbcORyGijPq5BZ8noQYKcSAy5J9XNVYUXhNJBRQ+qDUuJJOMlDs7ix8TFTrbM5TO4Glph1JnSHsxwfI8DutZ8BAJypGeaL8Rsxb1RPbZ0SO3K3kO+cF9sCdgyk28GEzFbM62wMYJfa4AmNvHtDJwaYjhecLLaT4pP1qQy7cM4Uk5+yRapNQGwChp3ZlBL1hNAJuuZjffcSICKvQvoJ2CVqLS+9iPsYJgAyhh0lOSohAdWg4JLYiGm8Dp3wwdY8E6ga5S1+96nWNWM45Ow5onlIJHACiLNwau5ztatKAHap4mqNo/kGc6b/5Lvx4G9/B77lx7/IKk2orKQsnyaJJf+569I8K3RNCShYPfQ87DjDTimF01WNf6HejVe+7cfwxFNvmn5O+1zFgQ0Ymw7YsfG3j2EnhP59n89dUAsL2PnP+Y99Qh/rO58+dvO8mBwyIYklACUMnXjx3jl4F/Exj2FnZINDDLsOYBcZF6ekxLJjJGAlaZFwCUpYhl0ITLk5Edk+lfw8LcNuwMMO8G2GNpbEBgy7PGTYOTauvS+JIJwyEjqRYtjd7wB221vnFDEPOybvtZLYqQy7qySJJYZdE2XY6ZtdJSSef6P8pQCAH2g+d9J3HsxLrJT7zHwg7KG1gJ0viY1J/0j2SqmQtZGfNUqgyPsH5TFpTryawMOOUmzVEKIbJC/mA4EdNiV3z2SJqeIMu2YVl8Q2kKP8PYhh9tOf0oDdtcX2YFQb3DdbZiJ+pmaTAicAI4klVlezBpTyQifGAnY3gwRZHjgBaOPkM57myctcWzFgkju2ZjlbDO2dh50zG1eGYUcedgelZJLspWPeYEsPO5mhoW468NpSdf8ET5oFTobaeiempPOLUuJftZ8FAPi4uoOs3H4wXGeuj12i6JhsX5sXuEesvte0effrOLYS7Tdqy3pkKbHs7xOS26PF33/RXoax9DyqocCNEOyj530TSWx7sbuyOyk+WR8KcCDwLcWwk+zaxTzswtAJzrBTijERyvT8ia6lavR7hliBko05I0InGmRozbZgSQy7i2BKygCwy6SWtsIxTKhPLwUbH4xlA1WB2gRj+OcWW/zuU9EibuYx7JgkNsHojbFwmotg2IWMqQHA7mdfdfOnmxPnewCAW2/D8hv+An5MvQ13zyq03Hi/3iB0AtChZQBul2MksbkFaADtoUaHcHDzmavjX0fF29c2ktihDSDebkb0HwQghPJk8pl73/M32OeFY5VifbjfxzkPOx/Af/Vk5f2bwukAx7Ab9LDrhE5ElDQEOvVc674E6JCddZlK2BC5MCXWzYNeV/qZLPoYdlGWf2RzcrIkts/Drj90IrWxVli/2gbrUNZMrzH3+7TJLcMQwE7mh3EPO7MmWZ86Sexohh1d06skiTWmim0YDgDnzVYnyH+z9/8GfNPq9+PPPPnfTfpOLWdzDVMOBFYoSontMOy6x9X1sDOMLkjE2um/bt8FAPhwOz3+vLHMt2kMuyxIyR0C7KyEcw8lsbGa5RKtGRDaddCuGuffNWZ39SkDWNFguAuGnUox7AwAdo4ZbiymofJlKIlt1hCmM23yxegAi3Di+FTAsDue50xuHDLsKIxlR5LYIttfDzsmiSXATnvY5ViUkrEdnSS2UWIrhl2eCedTGAILZmAUKYZdTgy7BrW5T03Ca3BRSHx387X4v1W/Eb9k9YfG7yj1VCXdpOtELTxfRECzYu8ahp0yDLt76shLf36jtqhtJbFjJX6cVbdLSWywybTzGsOwS01mLeNshEfa0H2IgFZ7VxnbNNiZhx1n6zGJKfnahB52zRpoKggDjnaYCN538LCeCcm2Izzs9AJCaNsWaDDM87Db5WS9w54oOrI1B9ixRcfDl7yPeUrcjQZj5DFJ0B6VlxzIGUtcEhupGBBZX4iHXdA/DChXfsdXvR0A8Ku+8E2TN+upbh1q78amVR6QQudXpJKTw5LkYafbxK3CtI0YYGdDJ3yG3clKv0eIDVJvL0N5nqobAnaq8Riy0eLA7xaS2B/66D0AWpJtK/Qe8/xZA8AuIYklP296dLgce5lk2LH+OSvSNhV8Y34Uw64vJfbyAsbEsKs7DDsHTL1KgB1noVkWttkMiM1ZYpuGu2LYFQsW1HBqv0NLYh3DLlZRhl0oiTX/XlYNHrBgvF0AdtH2biWxpyxQZWSfesGbr49lhthkJdCmGHb9gN23ftkLeMvtX433v+329C9mbWZ+/cnel1rAjhhs9P8Yw850RDKQxKbkZ/9V9Vvxm+T34S82X4N/PPEUOkytkUl+5cKXF+WLfmP31gKW+8Vy6qt8dgjUWhLrVesA1HEMO3/StW3oBGAAUBUJ8TAD+TmmM+xmubQSzbZaIWPst2I+frFLkliqJ6+FgF2B04Qk1mn2d9OVzHKpWYOCffaeVCEzPLShE3onc53NUOYZDsocK1Xo465XQZvbHPwq8yzpYeckFPEBNzMDcY7apknHJP2ANsA+wxx/pflqANO9NWNVZY4tdQ9HeFfwmdcXhfXNEyd6gXlXHe0EIH+jMMzsGqqxDLs5G1t2Kom9aIZdX+jEgDypkxI7RhKbAuwugSQ26mE3ANilmHheqp3qfFYp3YKsbZXtx1Cv3CIBkYVN7BiAaTLeEZJYWkBUyDFHhVJUBgy7AMAu3IiVgYcdgMbM1WacYXfyKe9tN/DQhE74rMeUZ9W+lA/YUTtYD0piYywcy7Db5aI+ZNQNMOy+8X3P4TOfPMJnP7u53D+XGZ46nuHF+0t84t65VURMlcRa0NYQDW6EoRPUr68eMl+qALBb6mflqMw3BiD3ujjjeyrDjoNwtm9I9Fn89yPSLwmwW9Wt7iMzgdNVjZ946QEA4H1RwC6wbwA6/QsB+FWQEnvvTB//W+8c4oOvnOLu2RpKKQghmDF/0M+XAxt5O/KwU0pZe4DL7GEnGmLYBfMAZk/zGvS63Ust7QChkfEntjk5dYMpbEcxD7vq3AuForaR2iShsZ6HThQBOEb3e1k1eKAO8KS4p/8w37wPpYp62HmS2DdCJxzDLmRCgTHsEtKtQmb4xe95pgMyjKk5C6y4eeNmzyvhGic1amuu352QZ5ZhZyZQxvetSVze7/y1vxB/RP1n+C9/5S8afexUNDkjhp0YKcOYHfqNe354o/f1+xw6kaqcWIQhc3MieBICVrtl2AUx7Gbiea5KXN9AEksMu7paWbbeSuU4Ohg/uQg96950058EH89zJ/esfWq8DWXZmYdd5sD6fWPYsUCMbKUnRq3ZdT0opWPw1ueOYQe51QIhz4T1sOuA50RpL+KTQB52oczmSEoSG+4gTWV7xqphO9J31REOAobdYSlxD36/dA9Hk4HrNypRW4dOjASSOLC2tSR2hzuov+A79P+/+jvjf99KEkuhEwTY9YBYMjJZpuLypH2WxEY97FKhEwlGXfhvBr7xRQf3sFk3bZC2aPoxJdCOBuyGQTiXWDjCw84sIGgsKNDoecVFAK9hm8gKu4ChRSr16QUH7M5e8952LM71ONT49+6v/Kb342//9i/Fm27uZ8rnirMuvNCJfklsjIVDizI5loE2pkLAcABsyTKBz33zja2BhWdv6Pv1yfvuGZosiQ0YdrcJsAs97JaOYbdWfujE6Ur/HLLnr0zxDaRNJbG8YqETgM9yGvE9CwaOEQvoRz9xH60Cnrk+x9PXucQ23Fyqun+jw4gA3YBj2L31jn7eqkbhgQFrrc9XKBucDWy+xTYUp6TEmmPkz/hodukeVtYQwy449yfeaX98zTDsPACps6kzMmCrz1cxeoDBfCnlYVd1AbuUso2z6VMMO5oPnFcN7nsMu+0BuyLW3s2YotandozttO1U2XnjxWy+Pj6GHYA2TPMELBOkSSwst6m1KlAK3diuDYAwKujknIdd97ik6XgkAXYkP0P8Jv/Cz3kaP/adv6hjrjimiGFnmVojd3XnDLBbqRzXjvsZWPY8LxFgV84PgRNnSm3LXKuxgF0oCX3mxvCO11CpTAJtjGFHKbGzjpfcUHG/t3q1RMkSZ6eAHjcOStw6LC3N/V1P+4OrB9glwNBd7SjMcolTzHCGOQ6wX7v+XkqsKZXrgcqXxK5sv9Eg22oSkcsMtWEc1nXlfzv5ByYo7TwZujVtI8WwyzKBg1LizEzGdwGaVdJn2C2CHVghBE7LO+C3+SV1C5+1A7DwjcIOALsBkIOKT5wSjJfRxd+/7YTsy34X8DnfCNx6W/zvWc8YZ8GXsaETPR5pfffBkyftMWAXlbEOsNVS/5YRwC6SEgtowG7OGXaVC5zotbfoMOxGJtuOYNhJC9jp+1WiRpaJ8c/LlIokSOYdDzt9TkXGOlKzoUR1DWc4l1nn3N79XL/S4nGXz7BjzxHJvzbwsCt2KYkNwZUR7Khd1DM3FsBH7uLFe24+NpllZOZsf/Dr3oVve/ZLcP0ffZf+PYFUM8awM2u1FQpPhkmS2I0CNC5DbeNhF5sTp8YTPocbIb3ldjfnVYNFKW3gxHvfFDzTIVjDx7ugf0lJ5Amwe/La3M4T756ucX1RMIZd0O442Bl7TrMIYLcBw44f62h26R4WAXZtCPY8+dn2R1rvzTl20BkjYu0uuNZt67CDqZJY2mCMeditT+1myrmaYTEgiS2sJJalxAb30DHsWjxQu/U4jnq4WnmvU5ONZ9hdAMue1WOBowmwUz2AXY3dn/A94W7wIH3bdnJ+yliMSZTZ0InGvJRAxzQquwlYB3Dmm1ms06J9oIEsDl0nXiHH4YDkzYZOxFgBe1ozkwQsm6BdMYbdGMPhp1jowizP8MTRyA6tp2gXvAPYrSkldoYbE5l8eSbsLn9dLa2vyxlmk1mBfIf9Lbf9wfV4XmDJ/dl47VwSm+Eb1v8Dfl72l4C3fvlOPnNXVeaZlr2yUh7DLuJhh2wrhl3JQifqILAkMwBAlti1zfnvV3qB0/R4DXLW8tS2GC3GtjrLjqO0+NO57+P5orr9BsNuV/WoJLEew25L37njZ9hnbSmvFQK4/ULaCH2Uh91Q6EQgiY2N+b2AHfvdBckodlLcB2msH5z9dwLA4/M/7mHHNjjWdesWFIxh15sQG37nCF86x7CrByfdVhJrAp9KVHqn/iJTYtm/Q4YJbW6XYAy71Yn3tmNxpuc+Q/duzyoJ2JH9x1BKLPe5avsN0Deq8PsHPOx2Vc+aTeRPMMCOFp1jbF8A2Pb91IHUnme0QC0Dht3qgQVITzH3JLH3z3Wbv/ZpAdhN3IzKsu5zlgyd4Ay74TYkM2GZSASY/cjHNWD3nhCEF+Q/SptLNB8Qnf7Qhk4EITQE2F1fFHae+JrZ4Lcedh2G3cC8IDYuTkmJNQDPmsl380vNsDOSWBnK7Gf4iTd/M36kfasNhvP8yTsbYjFJLGOQA/413yR0goU/oWAMO9XYVOVzlJaNm/Swyx1gt04whGm87TLsdudh5zHszLmIZo3csI8/rUMnKAVFhfI6OLArxQTZpj4q3zL6tSqYzKsewM552JmUWCuJ3f05dCSx1uSw/6E7PHSNWyEescyLzvMyedjNjG+bbNfwEjUpdEKNY9h91jOO2fHE8Wwn3hwudTdYHBIrTs0mS2KFEKgN861eu+S0MzUfZJCG9au+8M2YFxl+/y//7M6E9to8x1IRyB4w7JQxHd4hww5wNPt9qkI6gNSWmdweFLkD8+qVfW7qbSWx0kliyS6ASrQGsEtIYvPS/V4Qw67nPt1mgN3Uthire4eO2ZQn0rKbgyfRKnd9XlS33/Cw21VtHToxkt7PvUS2lcS+/WuAo6f1Dvvtz9zus4aKgzRhDUkbRMiw6wud6AFOuTxprxl2DLCjRNzUHC28BiKL/50z4dl7skxY0KFqWuZdtvLkNr1juRAJGe8AK3AEYGePzUpia714vggPu44kNmdJjuRhZxh2XBK7DgA7hIDdHrc1VmnALgCXgupNid2lh91jYtg9e91IYu850Du14E2WDBbxIQhK/frygReOdsYksQTa3N7BpvZelhc6scG95SCfyHo2DKYx7AAX8kD3gxh2HdZs0m+12xe6fjdg2J05wI7miaTIIZ+vTujEEMOOJ3NTjUmJDRjGNQPsRoPVe1hENGlDDzsAP/Le78DXrf/v1nanF7CLMjsDNcE2gB2g5wCehx1r52evAzB9BXnYJe6L9bDrk8QyYPpVxdr29TeNO+6ektazsSuJBYADrFBIMX6TZ+ycecN6PJJY2QfYmYXujlInef2Tt/+3OPrA78b/p/5a/MmhF4eG1D2hE+RhR+atBMpcBGAXAj+0aB9i2B0u3ICgwgl0rLIEwLTHNTtgA0R1bj0UVFvpDIORoRNvuX2AO0clXj1Z421P7CapkICSDgBKHnYoN/INa0wn2tTOw24Tht2v/aK34Ff/3OejHdPxvLADRb0697ivgtrhFkmovGjQX1aNNbXdlyqyriQ2K/XEYlFKKxtu1+doaw3tVcgx30YSmwnbjyQZdokd2TKXqFWGXLR2h7yPYccn3bvwsKuPn7M/PyzuRF9z4/gQ9149xC3oBeYn1W3cPnpDEruT2loSS5OPIUks2+ncVhIrC+C3/Rvdlx09sd1nDVWfh531d0mFTgQedjZgIQbYjZTE7jPryUpG2ZxtrIddyJawqXZmwi8yIOtO0qumCRh2K3tflqocnkRnOdA0o2SunjyLJt0JUIsWjCSJLUTt+8NdJGAnc+SZbmshw67oY9jhXAM5Q0zDPStvESfoOaqYJDY+PwtZOPrni/Cwe0yAnfGwe/H+9pJY2wetg2s6M4vj5T3LpjlTM5ytXX/52okB7DbwFL90NVUSC+j2QPL0vkAmroYYydI8muV4sKxxtq7xcFnhQ6/q+9dh2IVSxp4NCS5R5BVj2L1+apKDbUpsj4ddL8NuYkqsZQEqc6wGiM+GiSj7XDSf7zDs0A2Bm/VKYmMedjtg2HHcoK19DztZ6HbW1sDpKwD0GL20DLt4n+RCJ5Rtc53QCelCJ35Svdn94c47xh13T0U97GSpN/tUgwVWaPPgeVo91Oca6w9spsDFzOUeywxRkVlwKK+DA/FS5ujb1Ld//VfgD+V/Ef/p5z83/GIzoSEGm+rxJ5G5fhgodKIeIYndtCzDzhxPZo5PpMxMTXEJ7gLd6x6WMgv7yySJLefsAaqXdsCoK+39VUH2+96YEkLg9//yz8E/+slX8N/+4ncOvn5M2dTh2l+0qfUZBIDzib5zVLUodfpstbST2PMNADsgLRWZFxnWZrLcrM98wG7HrAJi2LVKD8j7tGOWZaKzkZCZ3Rguia3XZ1AE2CmJoy3OQbMoA99KU9KA9TLBsCuk9jjMsbYMu04CFSve/nYhSz0sc3zd6g/ii7MP4N/d+HnR19w+LPFv23fhF8kfBAB8rHwbDso9Bi4uUz0qSSxfiDyxg/5yfl3/d9EVMg94jQ2dGMFaiC5Mwu/JirR0dx+K5jIJ3zmvOhKdoP3QtSM2ReRzyjzD6doAdvT+eu0l0A3aW2S5Bvk82XEqdIIz7PrbPX0vsa1L1H7oxC7Za51rV0AarzpaZDTE9Ms4w+6h97ZjcWaSbAcSfvesiDWmF6gs+GpAEhuycPjPY2xRRlcmNTuKgOxH5WFnQgVejEhiQ4ZKskKGkwXsAkksY2ueYYYH525N8Lpl2F1RwO4hS1teDAQVxoov6vvY57zdjGTYUdDHybLGT7+s79FT12ZdtmNo/dDDsh0C7G4sCtw61J//+mmFplUWVA+Dy/zE9xGAnVLOI7vnGoTsWQv0XOKEWACQrWHYRfqQ0P/ZZ9hN8LCzgRGUFl50NsvSB8g+t6mYJHau5y7lkQb3zTh4jhnmVb8klsC5de0ksWH/RX35edXgIy2z0El5E0+oaEo6ncvqPg7ECjVv1yevAH/m/Zrd95t/oLvxdRVDJ1puIhz+jQIbLgCwu74o8Ed+5XvHvTjo5ESPaXFmQIZctIBSFtxrL4JhZ5lvhlk30sMOAB6qBY7FOX6sfRveN/J7LlPoxNF8hqUqMBeVZxjZ1HovvB7JsAOAX/65z+KXf+6zOzu2JtzhMFWvTlHApMRuALI1WQE0Ri5pZCKnar4bDzJTQgiI4gBQQLM68/9odu3EjhYA3NxzVbd7NwiHgJecmdCJwqXEVqtziLXu2yrkW58D2QNQ+jRVpnRbSgF2ZZ6hgsQCQGaeB9XDsONm0nd2IHE5muf4EfUCfqR5AV84iw9gd45n+H3Vb8BsfoC/cPoluHFrN4zWNwrbMeyU8sGkvnrindqg/NZbgee/ePp3Pa4KfWp5DYGVHZkRzQ8izzoPNAjrgiUUOysrYx0Bfg156tC/iWHXs3BchQw7854limFpo8yBCt5cIA3AMnB7wJc1ywQy4SSxFrC7iHsZuZZ5ZlQoFDph5pkF2CJ7pQG7l9UNPCnuaUmsvHweds7QXgIt3aNhSWzIwtE/X4CHHaBBGQLsHpmHnQY0Xj1ZY1U3mOWSSWLHetgFgIn1sDMbMNzqANpKZ4kSD5auH3v1RJ83gThXrr7sdwIv/QjwtX94sw0VDij3MfR4nzGWYWd8A09WNT71UPeLlOLqVScgKc2ydYCdL4m9xxh2BM6+frqyclggxrAbYN7bcdGMKU0Fm0A2xsOuVVDKMbN2KnV/DCXNdVCRYJJQbuyFIITjVNTDLljPNwMKgljxcbplgB0BjLNjDdiZOkeJBUliR4VO6Hsf+vtTCMX5usUPqnfih69/FT73Pe8dH5bRU3mEia2/9EADdlhizdv1B75XJ7CfvQb89P8JvPMX+++7CB9bVo9lNazsjmmMYWc87B7zhIIAMMuwU+mU2JzdnLap7cL6Ihh2bciwU+MYdgDwDe0fw/c2X4K/8cRvGf6iPrnQntbRTOIc5iFmXmtNRX5i+fjdxx2X9T4MZI31Uu9qLoVOX5paraDE5ZXnM7ILDzJeWTk33+N72GVmkZLlu2LYMcCuijBfHnOR/yZVPtMTJM2+03+rV0s05j5XyLdeIDjAzgdecnPt8xRgJzPLzssM+7LtkTf+ui/6DBzPc/yRb3rPxqE4vI5m7rtuJiQztw9LvIKb+I0n34Z/2r53JwEvb5QpyRa4U4tPnocWEAe3gN/5AeA3/r39ZomF1Qek0TVLTQo7HnZbSmJ3FNpzYUVA5BiG3ZBEJ/SwSzDsAPKw6zLsViiHpY0D4RbRY27rUcBbLjNUynnY6dCJC7iXHQ+7ouNhV5u2mEcksa8Yz59DsdRhHpcOsGNyOx4+QpLYhMww5mFH4N3OWfscjHhEDLubB4WdK7103wSxWDbiyHkk94ZUirEWzTXN5147afMDAAIPzruA3Z2ryrB7y5cA/81PAe/+FZu9n4N0vZLY6Qw7ml+drGp8+FUNtn7G7RGAXQ97vBxg2F1bFLh54EIn6PkEIgw7D7CLnBP1r5b1xfrpESmxgFbipLzPLlvJ1qgLI5LYkGHnPeMdht0YSSwlxE54bnl7qc7dfeOAHatzNcN51Q+mxkInUgy7VdWgRYa/9rb/HvjqPzD+uHuK5hAeww6wffoBVn67/ui/dD9/8ke6H9he7Hzu8UhizUAhmi7Djphj7QV42E2qkGHXMxnLmKF609QXy7AjaWUgiZUjAJPv/q+/CX/i778H3/L+54e/py9Bb0/raJ5bHzG+q17b5OFs97urI0tRMnLA5mjMxLrNFxv5L1hvvHplJ7FnaoY7Ozbuz8oFsALUOgydMAy7He0oCCFQ5hnWdYvlHgZPtFkJTmQoFm6C1EgtT67XZ8htmxuXTNz7nSSJDRh2UunvyMv4BK/MM9Smi89qCp1IA2Jf/MJt/Mjv/4U78wHhgF1qQv/EsT4eGi/vHF/Rif/jqD4p5lDxQIAxi9AdJHY98uoDNAclsSmZ0VTA7gJklBdRFmQb4WE3CNgFDLvInKpkUhnMugy7lSrGSWKBkQw7WtRWo+5JngmsFTHsKiOJvQCGXfhZMu+AUSSJLQUbH9YE2N0A8BHMsdass0vmYUeJpItCAsL0Q9W5A8gTSdIhC0cIcTEedoC/ofGIADshBJ67scCHXj3Fi/eWeMvtQ7vBOQvN/1OVs36pOofdoKFrKoRmTp9rE3llFrEPlq6dfeQ1/Wy96eaW3qVXtcYy7DhTdIKHHQCcrmp85DU9939LFLAL2eBp5nyRs7AfVtzDjodOnK4oRTPr2g0VC+AL/nPg/ieA939b97jC8dcD7IYZdoBmzfqy+ctbuQHs4gy7UBLLzjWVws4rtEexHr0TNsiF0G2mrXyPVOrzAp/Cc8xwbvwuU31uaYA8HjqR9LCr+9l6m1Qe87ADXJigWOEhP557H3U/3/1w9wOvoiSWHsYsBtgZZsrjZthRAxcESND/oww7BtjVFRoLOl6kJNbI4RQxnIYfvDffOsCf/ObPG/dFCQnnPtdhmeNclYCAt6tObKcW+WMzJSUAVASLNpKYqk0MbQG0pmNoa5cSe4o5XtgxYCdNB6YCViwBxlkiBXSTmhnAbh8ZdkoWAFsXFXM3QWqzmZYnr88hLGC3fZtrRK7lyAHwkptnP58lGHZ5hjPTxUsL2PW3i10+H4cMsLudkMw8d2PR++83aotKAUV3PwL8zd+mJ3af+dXAgxeBt32FTmil4sDMvss1Ny3JGDthDUpiKXTCLGwICImN+X1ptNZk+9Es9DeuWOhEKryqAzKFLLERHnbWjJqnxAYedkNMKQvYnbvjTQZl0IKmHhUekWcC68Yw7ERzcR524WdleYcVQCxqj2FnALtXoRl2C6xQXEIPO5LEzosMEGZsqJduYTSQEgvozSApLsjDDvBBmfmN3X52Tz1zY44PvXqKT5rgiVXKSyxVlrm68kFtfj6zYwvY0bV+uKyglMKyavFJw+57W0yK+UaN97Dj/ngTPewermp8+DVi2PVITzts8LQkds02y5dVY/9948CFTtw9XePUADJ8c9arX/4/pU+gAyIxiWXPPJQHGDSt8pOkL3FZwC4yF+gCduzfo0InAvsPqyCYOLeTpQHsHrjfWYZdBLAb8rBj47zzIvRfWwRJrrvsv/OYhx1gwccFVtqOgYoDdvc+0v3AC96AfUyAne6Qsr7QiR4myKMo8uQiyZ9NiY3sBnN2W93UUIYJcxGAXRuEQZAkdleSRCrFJ7CXpDTDjiSxzMOuohCQxzdJVYlFmzIgm9gwXZEiwBUzYtahE7tdZOfGq00Ez6wgwHiHi/pZLvEQtZV47FPV0t2nVgnMZ+zfuQbs2vUSrWlz9Q76gFZIHSzCJbFtaxdoRYJhV0iBWklAAJlZ6KpHyOQhjxUAdpIXVrgj/Hxsh/iN2qxSoRP/8DuBn/0n+ucPfr/+/7/808Cv/xsauANGT54vdfV46TqPlyFG1vAiyFsYd75nw4nzoy4bOkET0jzdLsJd+5QktsfDzmPYWSYQS4kdGzoBuLlA3xgl2QalBWvTfWUhM1QE2JEkdscBTPqzQvZE0fHdqc28xgPsDEj5mtLM1wOx8n32LhlgpyVhZpyrzl3bS8gMQxaOzKRdlF2Ihx3V4e3dfnZPPXPdJMWa4AlK6xwviWUbOhQskS98H07mYycM865qNFj3oVf1e64viqTlxad9cbZc3xyfA70jN+/HM+yCecAoSawDMO6dmTm+0N9J9/r1M8ewO0wBdn0VHteIhFggfLavHmAXO/9F2QPYDYU8AWwuGIROTF23kS8sAXaydP0FU1m00P7ZJJlOjdXUVz1Y1lCmyYXgJLE+7b93KH2OpYnrL9HP6iGWmFO7qs6BExZCc+9j3Q8cUmZsWY+lhWfG94lYH7wsYPeYd/WFmShZZh1JYyMTnZyxi9qqtrLHi0i6deaRxLAjSeyOrxed/yVi2B3NcpxbSSxLzyKG3QUAqKPLDk4Bm8MsJuiZmFotWwyqtZPEbhJg0VelAaZCkD0zC9V8h4Ax0b33EbBb5W5QeoADHLPrrKTz+Wssw27766JERBLL2lFRphl2ln1R67axK+nymPqsp91kP7VIunNU4pBNRt5y6w1pzc4qxrBrKuAnvk///M5fCrzl5wFHJnnr3/1/3esqBthd1RrlLTcydEL1MJcs4BQZS0Pj5n2tkGHXB/iEc5EU447OPQJylpzpwb22zLi+VOUw8GJlvCS97en7+OJxlIed8FJi8yy7mMl65NrlQaBClGFnrtNdA9gtsNYL2svsYUfgR70cDJ0IWTj6//2Lx42Ly3IPn9jtZ/fUs5QUG3jYjQYuuCegvZ7BPHTmxvBsdmifuXvna/yrD2nm3Xvf9AgSvS9reZLYkQy7iZLYF+8tcdeAam+JMex4AjbQL4mNeNidrPTrj+cFhBCMYVfhdKX7nI0Au3D8HZEQC/jPb9Moyyy99ICdsbhpI+c/D87NY9FGbBM6lQWEEbspNZEYRd9lQo28e1W6tdE6PwYgcL7ul7HSWu/+mZuDhX59eSCn3eV9zlMedmZcWYiVY4+evOy/5uzV7gdesCT2sbRwYaiTsjnv/tFMrmI67kdZYeiEnZjHGHbsd3W9toEQFyOJNR525F1HDLtixw0kC87/EtTRLMdSdQNNiJl0IQDqyFJhezIlDGAn++jyPdXKhfmcc1RLveN5hvnuAbu5Pj6KHqe6CIYnDUbLPZTEVoWbwN5TRzieM8DOTIBVtbThObsInmmCoBn9S8fWKWcJDzuZ2STDgvraR8jkefr6HF/7OU8jzwR+/jviCxkhBN77phv23+96+hJ6oe1rxQCpl35UywrnN4Bv/svAb/g+4D/9Hv23n/mHsNuclwVI2qb6GHYW5BkbOtEDhOQMaOh8z8Wmiu2sbOjECMBuUBIbAmndsYMYBcu6YX2WsguFFYrORL57zOZ7yEy/75gtY7JxLISe1+eZC50oUWnfnbGpylMqIontetjp65CLLmD3OnR/OsdKsxkuGWB3biWx0i0Oq6W7pwMedgADNkkSu2tzes7ySxzPRdQzxj7ik8SwMx5P4yWxHAhPAKAMgBSLW3jKeM6+eG+Jv/nDLwIAvuztdzY5/E+P8kIn+gC7G+7nwydHffS1hX6Gf/jj9wBoP+AocBYy2agPiKxlC7YZ0Jrn5cSAcgRcEGB3sqpx1wAthxsE5jkgcRrDLsuEJdjWrbLM0sseOlFYhl0kdCK4voclu3chwNvHsNuFJBZggB27V0wSuzLrpPUAmEpsOgKcZSY6DLpQIrtTwC7lYWf69AMscUDPlLUGMGuU6sxtdFBdBMue1WNp4cVC39ii6TLsNkZ+d1zEsMush12aYSeyDLXSl7JtGhc6cYGAHU0qycNu5ww7C9htkDD4mIoz7IhtBjAPu8c4SRV0PQM2B0kV5fyo854x1RhWl2iWqJe6E63lYue7TQTY5YHvJDFQd9n+5oXELM+sSfQ+Vc0BOxx6sk9hF+Yry7BrdhCeQ898yxk6TB5bJjzshBCWfVG2up09SoYdAPzPv/p9+MHf99X4jB6Pm+/8+s/BZz1zDX/wG96NJ69dYYDoUVdMEvuSSbZ67vMdCPP0e/UCfnUfuP9x/buRk+dLXX0MO2IYptgO1sOOjLx7zPxZv9CpywKMhqETfXObDmCXSold+v9mRRP5s3XjzwWX9/X/xnjYUfsn5sZkSWw/w85uhqDW/nAjpLSTK1xU57OOhx0Bh7nqAnb3lJ5XHIiVYdilN573sTwPO8uwOx+dEgtoFg4AO5+4UIbdI6xnDMPuk52U2LGAHRsfSBIbGMfj+Gn281M2XOIv/csP44c/dg+LQuIb3vfcZifw6VAcpOvblOeS2CfeOeqjnzzW9/9Dr+hnIepfB0TAmjRozw3/K8NIPTOy1wMDGl2b5xYQ//hd3c9sx7CLeNgNFN+0GAKFLksRwy4255gHMncPwAuvV9TDjpR5oSR24vyO2gwBdvxY545puy5veG9LgamWYWdCTUJ2HdCVwI6W/I+otIedAezEyoHRZwawu/G8u8Znr/nvu2BJ7GMZtXODxJZ9DLvHvFCwDDsD1PVKXqA120CLuqnswlpdBKOLPtMy7Agw2fH1MudPDKrLUNzDbr08JTe7vWDYCQNohQy73DwDxXwzhh0ZlIr63JKuxIZsvb6icIVCrTQLx2xxyQtg2P3t3/6ljy0cZKgaRvu+r45wzAE7Jtkh38RdgMQkiaVAHn0g+mavlcSsSF/7OgAMxSP2yirzDOXAd77jqWP8nd/xZY/oiD6NKgZIvfYz+v933uF+l5f63y9/APjUfwRuvPnyAEnbVC/DbkCewxlZSrnwiSjDjr4nwrC7bB52Fvzq6e/DuUgKsEv9G25xeL5u/M9b3tP/G+NhR99Lm3d9xxyVxPaHTqyM3UEhauMPNxxWMbm8aycA6YBK62FnJbE0V1W2/b7OJLGzPAOqy8Owa1tlQahFIYGWpcTSM5uY6xALRym3GGsuysPubV8B/Ohf3e1n/v/ZO+8wSapy/38rdJy8ObKBKEGCgKAgCCKSQQUBUcCI+ao/5CoqqKBXUUSuiIAi4S4gSBJFCQoIooiCIDntEnbZZcPMTuxUdX5/VJ2qU6erc1VXdc/7eZ55uqenpru6+9QJ3/N937cO5tmC3dpRW7DjOex8Fr2+OCGxbsGyMhcYT5cAAL3zsHAoA6wCbvm35a47+W1LHeGI8MHjsKsS6inOd2csr+up5/R7+1nf/HWAkM6AO+wqO4FFYaVoMKR0y0kHuKKcoigYyiaxYTyPVzdZ7aZi0YlqyM4/PrbUERKsqQqKBpOqxHZG5etK3DFwHF7fMIyhZHmIuVqtz5LHW7++XS4i2ezmUpnDTviuel1naFF6D5XEVPk7S/tUuJYd0UEKsxVz2PEqscgjy92MU8PWbXYGMDULGFtjhcUOLnb/LwyXvUAko3Yia7lUkqx8Aus4kCIW7FRJsOLVMJUKO5MlaEiiZDvsLBGNheqwsxpGwp6kaQGHxJaFBHcAmYSGnO2wK04Jgp29q8AinKRyQUvOCagb1jWQyDQXCsgFO7WUA7Nz2ChN5sOrRjorPGcp7wyq3IGqB9j+4irWAQBLiw67XiwQJyr2hEwp5WDwXJxBOOx4DjvxWrSfvwi9LEmrSDFiwY6IEFGw4yL7xpesx2Zs6T2WC3ab7L+XajjMugFNWLDK1HTYCTnsTMHZVM1hZ3g3OwB0jjDquNXqKeAgzN38KrM2INhNFgzr/7Wk1Y7tSXNdOewcwW7c+x58j5Xy6tU4PiGkG0iiZIfEhhDeLE787QIwsiugaAt2Gs9hJ7yHTbDGqzRsh12+cwQ7MYdtOqEBpi0m8e8TqBpmqNuLesMJiQ0ph93OJ1jX9uK9gn3eGszqta6zkckiSobpOI2aqhLrhBhLn2fffOH+PCwuuaJTNqnhk++oT1yatmSFcOFslYIkW+wNLHyL5XavU0SZK0UjLKsUxSAXvKuysSC6mYolE0jBtxLsjJ6EJdgNW+NBT6qZkFjZYccFu9qGAysdgtlVVWJvGjgZ96xdj/NSDa4F63HYydEWzeos/Lltp7tXsHPF/aLssKsRElvpdwCWe10gFWDoM0+rUS0k1mnbXLDLDFnX8tgaH4dduClOIhm1U1m7ZC4rd9hxwU6J3GFXf0gsABiK/cWXik5+OeY3eW8VKYGoZgt2QQom1hPbgmUHCXaKoqBkh4gW8m64NXfYheJ4rBPenj2CnWlajjUAqUxzIbHMFok0IwfYlmo11dxzVSPjEeymnIWs0/70+C8AgsAUdo42sx5PDjstwcOT826bC2BhZNqLNm8OO6sdFZCoOkEvKklAGIvUuAsDRHA4E3JmiUqaDgyvsh6Sd/EHFlm3TkhshwhJrcDFa7H6Msd5/xVcEWIOO3GMrOawAzybHc7vQPxz2PG2VI9bTfxbtcUDx+czyySsxybtpNVI9gBTBWDCSvScQ6J2LjL5nKvtessVZWscr6mKI5QlnZDYECqwip+V3W7kHHZlDjuh4NawHRKbVAykVKOjctiJOWzTosNOpMriVnThmCYDX5MF7rBTVWD3jwT7nHUwlE1CVQCTAZsmCsgXeQ67RqvEFt0QYzkkdmiJe79/AQ6YNxcX/tlyaR+603yqDluL/gXufT7G+qGngI//uaGnlgW7HRb0+x9YViW2cvoGTVWcNsULT/AcdlkhDHMoa33vr26asv/WTEis5PpyHHa1q+RqwqZFwc7d2OmCnZtjs8H+qUyw8xm3nA1GKV9gw0Un7Of2ddi5gl0pNej5t0prFNlR5yvY6eE57OQCTu6LuEUnnLbNQ2IzQ0B2s/cxTjdWiU3bDruMj8NOtXe7oxbsuCPKcdhx4a5C6J8JnsPOzYESTpVY+/Xt80mwcAQ7nutKZZ1TJRYATFuwK+XcHHaMhyhHOEnVnJBYMQ+ZO7HOZJsT2RTdFexUe7GRaDIfXjWy6QwMZg8kRfe61UJw2MUZJlTzeoMNenLYaUnbdWjkYTp5E4Nz2Im5yJgtKBRqOOxKivd7Cbw4DRFfRLGEu8h4WXoxNxEADNi2/tHplMOuisOulsNQFTbORMHOz1UvTmrlsFjnc465MMo/K0ewq9KPiG2mWj4d55jyPpIvDh3RhqciGHsdADCObG2nlN7AOfvNDaqFxGoqCswOiYUdEhtGhTjxuew2wnPYFQ2ew8522PGwbHvha6gJTEBwRCkF1w0axmZywPCCE0lNtRbosniuZ2qELbvuCYO5C7LAi05EhKa6FTs3jBdaqBJbJSR28V7Awd8Fdv0QsGw/7LxoAB95+zIcsuM8/Pch2wXxNrobUaTrryLYNUFvSveYtXdYUKFaryyM1aiCzV123LHJc9h5HXbW/75ih8T2N1PkznF9NVYlFhByjxluDrsgnVdR4Ibs+7+PPZfNAABsNUda35WloPD5Lpw2YPf/TRedkAQ7cX4khMQWsoIzF+V56Djy2sUvh508zgdbJbZC0Qk7h10P8uh1HHa2OJedAfBIK+405IRcdCISBSPdYwt2yKNUMqALO0Kq47CLdgLrhsTaQp3d0Cs67OxdTsMoOSGxVRMzN39i1lPbk0MdXDAJdmHFhclOctgBdtVUAzA8DrvoBTvV7hg9n6dQYSbT02R1TO6wM/NQ7cICiSbdetXoTSeQQxI9yHuERh6GowWYwy7OpLO9+Ezh81iirMXV5sH4srDrqNq7MqqZd6rEmmoAizdeGVoQ7Ir5SSRhhYbN8Mn7wCmpKUBIz6AF3E8QMUac+BZzlujCLfzC5AoAMGAnDt+82rqd7g67WosHseiEmOzfN3+MboWGMrM8X57RIcJoWXhptZBY4W++u/11OOyckFh7vOSJ/SfWAwDGWQaphnPYVatsW8d5CqSkkFhdU8KZrItuE/tadCvbeXPYaZLDztTSKEBHianQFRNZ5DvSYZfi45ueAqDAsYzXCB0TXTjigizwkNgImdWbwobxAjaM55soOiH0f5Wq7qoqsPdnnF8VAN88YvsWz3oaITrsxPsB8Z4d5uEPT6zF7L4UZvdVGEOkQoW1wvaSmop8yXQ2BCakHHaAK9hxZjbjtHQcnpIzuA6HHReAiobpVontdIddjaI4/3vCrrj0Ly/hpL2WeP8gz1F8N8kkl2Wzzv5qOez65lsVjnMjWLfsGOCfq5w/VS46UTuHnfy9BlkNmI8RRTmHnVgltsxhNwNI2YId/xw43RgSm+21BlpVYRibHMdAv7szoNqljdWIc+fIgp1zW2HS5zjsSiUnJDYId42MIijljDEnh13ggl0HFp0AAJZIAwXAEMQwM4xQlQbRHMem4LCzHXFTLIm+THMXuGIPbrqRQ8K0no87WIOkL627gh132DHmCsbTJDfaUDaJ35tWrppZvUlPvj09yb+LfKBtjgvNTBB7C3mrHnIeiaohMCVJMFRJsJs+qKqb+6s0BUwWATBLPJLz6cghsY5g1cWCXUsOO6HohFlDsFMU63MsTlZx2MX8umwkJLamw076jHyO8eSwA8qEhDFk0FvBiVD2vPWIjPI5KZpbRdmHVEJFgVeJVUrWIiKMKrHi++aCnZTDruA47PjC15oHmFoGgIIppNCHKWRQ6CjBjjvsHNcFv474hmG6+jxHdE+IC7LAQ2IjZGav1aY3TuSRL/GQ2AYFOyMvhMRGU/G2a+mdByx+qzVG9AdfTfcbh2+Pmb1JfHzfKrkE5XDIGnPThK4CeZ+QWCFPnSzYDWab6PMcIZE77LjLs/acI6Fb13ChmdyNMaVWjs25/Wl843AfsVyeO/jlACxrA00KS9VCYvUUcNoDABjYGhXAKudPFXPYSY/7RQvJFXKDddhVyGEnhMT2+DnsHMFu1Pt/Trh5FznskkKC/fHNwx7BTjPtPFzJeITE8kmQk8OugmDHHXamURKq8IThsLMr9bAiSqUSEorV0BIhFZ3oNMGOd1ZMzEXj5BSMzgXG85t5HHZcsEOyuSpLcKvLJs0pJGyxO51t0q1XhZ6U7hT0cCbMwkJVj/h6bRczetw2xJM+c5Ipe0HFCo7DLpA25zjs3LZTylvfQR4JJKrkvCgp3nMMWtgnYk4iY03OilOuCJedWT428XCd8XWW46JTQjVbwaneWs1hV0/RCTGHXYXJpJ6yBTtJHOQCXqO5ZNoNn9jXCKcq+1u18By/4208VWIBQMrLOs4y0Grl+pEddtX64lqVbSWSmivYWQ47NZzJurj44nljpTCeouyws9uUaR+fQxJ9mEIK+XDy7IVEznbOeBZxiYw7/6jXYWd0t8MOADaMFVqoElvFYUe0hqoCH7nDuh9CMbUFgxmcc/RO1Q+Si07UCN3n80lezIG7nHuFPHU8hx1HFvDqQh5TnE2y2kUnHIddyeyaohNGUDns5DyUgOsul12WjW4UqlUEOwDos/LYJdQN3lOq8N3omgpdVZzNJ1/BLhmiYFcph53jsMtjSq4SmxFDYmXBLoRNO4FIWriiahiF1ahGN63z/I0LdlrkDjvrS+Ihf67DrkIOO0UIiTXDqxLrvL5RRLHg7tbrqXAEO63DBDvuOEPBDdvk4knVkJiQ0RP88yx32E0i7Sle0AhJO/w1bboCJXewBklvSkeOWW3M5J+tkI8vMU1CYgeFiYocgqClrImGbhbc8NUgOm4xX5YNF+wKSqpqVV1DEgKi7leJNsPDJYpTwMQb1v2eOeXH9cyyRSNmVb/ii+K4O79aQXSYyNQKCfYrOlFNBOHPU+awa3Li3G7kxV3dgp1f0QnpMR93Np+4uw477yJktJ4cdmUhsdUKZdSRB0ggqYshsUVrkVuPmNkoYtVO+1oW8zcBYg47+7Pim5X28ZPMem8plu+oHHY52WEHeEW6GoKd6LATF2Rd5bDrsQW7Vhx2pULlHHZE6yhKKGJd3ThOtvrcVWK4KQCM+4TELhj0jouygFcXopBomg2FxCadc2SN526MKaUaOewqIs8d/KKduNDWctEJHhJrC1UV1hOyiaDadyOKdH457OTH2pnDzlMlViw6USkkNow5gEBkLXxUs1x1k8NewU63BY2oF5Zu0QmrM9BqOOx4SCwzSsJOawgCkX1xqmYRxYIgmATsnOE51zpOsOMTXCHPGnMmqVE67OzvTfw87UlSjiXRl26uraQz3h1RkynoCUGw60vryNsOu3zOntwJOdUSyekTEsspc9ilre8iwQrOZxOIw84WB5hHsLO+A7mohAyTBmQ1RTvo04qEIBSNW/m/0Du7/DhF8eaxy9thhDUWxR2N47DzEex42H+lxQMf25kQEltVsKvwWo4wGHfBTnbFtRASW+ZmK3/vPG/MZLFCSCzLOuEslc9DFuyqiYy6N+dwDcEuJQh2btGJEHbXRQHF/tx40QQeQlVk1u/O3EJa+E7B+r80mxLE5fhvsHHBzpPXSCj65CyaKqA57glTSOiuVN3g6jRm9dlFJ8YKjrBSd7QGhcRODyo67Pz7AFEMA9wcdr0ewc47LjbnsBNe3yw2VHSCizZFISQ2qcV/E6IatXLYVUTcVFQqjImC0ce6bXKsckJiR8tfW0B2ylXLOyf273UJdu3IYWfrCFmxSqwnJNaeF5eFxHZhlVgAmNQHAQD50Tc8j+uMO+yincBq9geuw1sltlKuLtFh54ZgBi/YucULiigW3cl/0KFuckhwp6DbF5oiCHZc9a5UMKQd8Cqq4udZzFuTpEmk0N+kwy4lFZiYQhID2eCvnZSuOiGx+Sl7MS8ISEGHZMeVISEkVk60m0rbDgiUoBg81C2AjtsZbAXBznbXyjnqypAWxxoJdtMLvuAvTlZ32AFujp3RNUKIVPAFbGKDs2D1qYTuOAwrhcTaU6dWHXadUnSikZBRsc/z+/zqcOu5IbG86IQUEotM7dChshx2Nfpi8T3WELSSurdKbEoXQmLDEuwSXoedExJb5rDzLnz5uJ1knVZ0wickNjPo3q8h2In5ibh7pZvCYQFglu2we2Ms53xePfUKduImAoXEdi9ywYEaYg0Xw3io6UShPIedLNjJm9cNnRc/pyaKTuRLXVR0wt6AadgBLH6Plfp1OUqn2ZDYakUnBGTBrprrV+yvBnxyIWaS3v8NMldhxRx2dkhsBnn0JHVrbOcVYadbSCwA5JNWieLi2HrP41yw01PRWrM1O4RR5Un1YXV2lZK28xx2zCgKk6IQQmKdXGgFlGzBzmRKRedf06/DhcEOE+y4IKGKC6OQVe964DnedOHzzE1Ynd4UUq7ttkGyPb0oMfcyHkMWA82UWK+BoiiOOJSbsh12HsEu/jv2QTAjm8S8/jSySQ3ve8siz9+SQp+l2TvWSiAhsUL4nU3JDkuuLdilpV9pQj6t4N9/MQeM24KdXCGW0zfPuh1fNz0WcM6CNVf+t3oddqbpOuyqpcCo9FrNhqa0m0YcduJ78SsMUEcID68SO+XjsGNQMIF07YUNX1zwENFafbEoHNZYyCR1IYedUrIWKHyyHqR7zVN0wjon1xXAi074O+x41fIpOyS20wS7KcdhJ1xX6UHh/gCq4akS26x7JeZwh90rm9yUKHXPJZ3NnCkKie1mHIdd0XtbqUosF+wM6/rzqxIrb1Y3JZaJfaxRFIpO1CPYuc4ox2HX4YIdF42q5aT2RXQMVxp7ZJdl01Vi7eexIw8rCXaNhLGKaYb81q5yUb125LAz7c2uLPLIJlVXrAOkkNgKDruQHOyRtfBS2hLs1r7+Gr5+y3/w4nprFzRhC3bJdLQhsZo9idSdKrElz+MyzLaimkYJSoiTIpVP2lgBxYJ10RVDqB3CHXbcYdgpJDLWhEMzhIWRGcLOd4PoPJxF+Dxzk1abLyhpJ8ylUXrTCYzCnWSNsN5QBDsAKKnWNVnIWYt5nqetwDQkq1Qq7SZ0TcUdX3wH/vbVA/Gm+d7FaDrjfg/JkiXGsgCcM4qcfwJuDjtDrd5PKtIGg04Ou+lFQkgRMGFvjvX4hMQCQK+VMBjja4GCvYPa1YKdfe0ww+uyY6wOh51QdY3VkRfMEU6nvI93ijDaSA478TPzE1XK8sXVUXRCqGo8oQ8CUOrPYcdF0lqTaPG8aywaU7rmFHtIooRUQg0nf40nJNY6J+4uMaQqsapUJVaxq5ZP2iGxCXMq1M3koPHNYSc67PrnV/1/T5XYZt0rMYfnsHt5o/WdJzSlatV4D7yNFyddF2o3O6qnK04Ou/pCYrmDiTvX/EJiFUXBu7e35gsffOsWTZ6X5vbJxSmh6EQ9IbFWGy8aJgqN5m6MKU3nsBOpFBJbyWXZsMNOajMVUpelJVdcosr6dobgqvNbu2bCLDpRIYfdlGK72RUTPZrhhsOm+q30GXxeIwp2punOBbsth116yBpsDxv7DQ5/5OP46S9+YT3Owqt02QiaVHSCO6O0CqF/pmIdb3pCYoMXTvjra2YJhu2wK4VR3MIRLDtMsLMdRLopOuzssOYIi04kUrbQCreyajFnTZJKavOiTk9KxyhzF3ub0ROaYGfY51m0c9iVSlbnb0ALNK9A3BnIJHw/42w66SyeUsUR68E68nHUxB4kFaEqr2kv/M0azhxFWITmWQKp5PRwQhI2CUEochx2c/2P5c678TdcIambc9iJi1P+fgFr4cCFjUrvXwwxqWeDzlkcy4Jdh+QKbESwq5VnTN709BPsEnYOOy7YcfcngFF9lvU0tRY2ZedcS7Br1GHnhsRaDju+EA5wniEWnbDfr+scsxbUeZOHxHqrxGrcYcdDYs18Rwp2nhx2osOub0HV/1cVwWHnVGDsrnnKLKnwVd3hsIC7SVDKCYIdOey6DtlhV6PoBBd883JIrCScXHjCrvif9+6EL7972+bPTUwVUazf5ZkUKtl2XZXYVjYV+EarjLjBCNRsAxUpKxjVusNOzAs+6BcS24YcdobJwJgr2k3APac0y3kLTgDufE0MiRUMFV0XEju05M0AgF4lh73Up3Fm7kdYtX4cPbAmtJmewahODYAbEusIduCCnf9EjuewY6UiFFtlDSNnGg+J1VkBxYJ10ZVCcNhxJ6EoMHUCKZ743xSSezs57KITK5JJ/nm6IVQFOxdcUWte1OlJaR6H3WYWnmBn2p2zI9gVucNT6/jBMgjSCc1J8J0p2hbqSg6dBlB4Ml0hJLZuwU7YrZxCsrEJPdH56H6CXSWHnS2KjK3tHOdXK+hJdyLLFwuAMAlTKjtOxMp79YgglZIUd8rn3EhIrNi+/IQvuc/yOUYMiWWMecK4R3XLbVczh50sDNZyE4jnVWOjJamJVWJLSOuiYBekw05oF3aOyfIqsdVDYnN8TEJBWKjFPAQbgsNOFAqyM9z7/dUFO94+DNN0Pqvuc9h521pPsoHxXXQy8YJEcd84IBqnkruqwnooJeewq1DMJJ3QcPyeWzRXcIIjFsVycm/WnjOLlWx5SGynO+yKYfZRmuSyLDUp2MnfTQBFJ8SQ2MGMT3oM6bmCXMOIm35iWOxkUUGeWa+jFCe9BScAb5VYLvTx6wroPsFuzlZv8fw+SxnF448+iKRiq/l91fNThI1mN2Qd1oSRO80qFZ0wbIedUe+Oe7Pn5RQvKKLIE88j+MbhOOw6LCQ2ZVdNTQoOOx6irOjRCXaJpNCx2QNnyQ4tNVtwYfWlEhhlrmA3ofaFtovMNOs9GHa+k2LRddg1nHehC8kmNUzC+oyyJUuwUwKods2FZsUj2FntW64CK6MKr99KrkSiQ3FCYnO1i06IDjteJTbuQlKrcEGkIAh2XFRL9bvFJWQc14JR33iftBfC3MnC6RjBroGiE6Krzq8Cb5n4VzkkljG7+ECv67AbsQW7unPYcWotBMW/1xD3UgkVBXtCn1BK1vgXRg47cb657aEAvLnZACBvC3aKVHRCsQW7STuHnVqajEU+33rhOew8IZ5bvcu9P7AI1dAEYdPJD9Vlgl06oaFPWMDWXSEW8IrSeXuDkQS77kMT3OBAzeI4qQQv6GDANJnjcg5ls9fjsKs/JJYLdgWDuQ67DnfPGrZjuqm11N6ftW63PND/73JanWaLXcnfTYXvKqGpnvdR3WHntkNfh53k7JTFwFYQN/3EsNiJQskxX6A4KTjsbMGO5+ZlhjuHE9OqhBQSG5ndQp29NdiCXcFyY5jcvAG9xgjYC/e4J5aOduBIJF3Brmgw6LbTTEv6N3AmOuxsB5USQplpPckddkVM2oJdQQl+8sWFSafyWIfAQ6mTKFizfUWBwh12EU5SU0nhAjYKQCINI88Fu+bDENIJFeOKu9grJKpXTmsFluCCnbUg4FWKS9C6LtSkGbJJHSMsZRlzmD35CCQk1upHFCE8ndmfPauxCFWFQhiTLIX55LCbXnDBNj8OTG607tcsOrHWFV2SXb6AS2atxaoopHGHnV/BBI4YYmJPtCvmjwGAlO3Uy3eqYNdASKyYBFvcdRb/riWrhuWIk/LJQgkZISR2k26137pz2HFqCnbC8TUWjaLDLoUSFEURcuUG3MeeeL3VJhfsYp2anMPO1AAVUE2vw46/Xx4Si+Jk87mLIoBXPfUs2ObuABz+Y2BqGBhaUvX/xfxETgXGLtxYnNmbxJhTGKCBNYeqWvOTkhCmn4rWKEGEQMUqsRWKTggVWCcK7pyzIfdmvYhFsRooOsEFoKJhOqG7nR7l01IOuwO/CSzYFVj+Tv+/B1V0Qh5Dq4QvpxMairY4LLvkRJbOcuc+8wfKx2jRORm0+1B8Po/DrmBgAmkMYsKaG04NW3/gIbGJrFVkjBmWyy7VKwh2SmgpJ6JbvakalI/fA0VR8MplH8X2q3+D3k1PALDK0KcjzDcGAElbmNMUhslCAQnbaaZXqIbJc9gxowCwEB12gmDHK0UaSvBqbsrOuZbWzMCfO0wyWWthpIJZnVIi7ew8qxE67JKCw44ZRSgATGex1ryooygKiol+8MhlU8zxEjS2+GTyCqWCw46wBhZnV8ZGS7Uu2Kl8UBVy2CncRVEhRN9ByCeVQ7LqwEl0IdxBtvkVu7KXAmRn+R/Lc9tNDbsiVNyFpFZxKiWKDjvuNqkm2AmLILMO15ITEivlmOmUZO+NhMSKMOb/uJaqKh5pqoKUriJfMjFZMDBzxgzgPd8HNr2I+zYcAmCqccGu1kLQExJby2GnOVViE3ZUSNN5gWqxzcGeX90qsXYOO8dh5y06wds2D4lFYbL5hVoEODns5CIKu3+krv/3VIl18kN19qLejzl9aayyi070phuc4yazkmDX5Rs005EG85eJOewm8rZRRVW8uSSDQnTYNVB0wnHYCTns6i62ElNaymGnp4Cd3l/572WibZPpG2SBrsr8MJPQMJazxqT+KmmaDtlxHn5+0lswfyCNmb3l464ibAAGHcklftYlw9U6xnMlq7q6AmvclENiFcXqK3MjdkTGfLf9BpAGqRLRjl72F6HP3hoAsLTwPABgEgG4UlokmRJCyaYmHYddokKIG3fYmUbJ2ekMw9Gl2wv0BEowbIddUQ1+8jXUZ12IvR0m2KWzQgdiT0R4KKEascPOZPYEkruj7DAsJdHaongq5VbQm+pd3NJzVUO1hUVmi0WGLdiVSLADAKiqgpzi7bsSqebdkxzF3rxQxQIwfOFVY3BQhOqKBSXtGfyIaQB3iW180brNzqjsAMoMuRM7Llr5VfnsJniSdTEkth6HnRhmxCe/1UIhuSAnh8R2SuhxIw47AHjHVyy3zn5f8f+76GarMC7zsFgu3GCv04BDz8OIYn0vWi1Xd5nDrsbmhvj3Gs7olCeHnbQICjlXLl+sOiGxpp3Dji/InYWvNTbwkFgUp8LJsxcSvEJwJtncMoWLc4bJws0PFTGLZrhtdYGPQ6UqnirE6fK8j0TnI7urahTHcUJiiwbG89axvSk9nLmjJ4dd40UnrCqx3eGwM1kbctg5baDZkFipf6kybxFd8n3pyuYlXVPxnh3nYefFgzVfnruug6KSw240V8SEnd4IhYnykFjAnR/y+WIb3OuxiI8aWPQm4N/AlurrAICcGn2lIlX40CcnJzDH3kXVk/4DmmlP0sSiE2HYInlIbIIVHcHOCCEkFnoK6Jkd/4WERG82gyLTkFAMsMIklMwQVGYNOpE67HRrgp9CEYWCXV/OXiSqLYo6G3q2BeyxLjewdWsnWgVFqnToOOyUWHQjsaCopgHBVJJIByDY2ZNoVaxCZA+4So2Fpd7jOuxYCI5fIuZwl9jGF6zbSvnrAGsDrXcuMPqa+1hPBTdet8A3S4oTwD8uA575HbBkH+uxqg47sUpsHdVBRYfduieBNY8C27zH/d/YO+waFOwOOBPY/78rz4FEN1uFPJzZpI7hyaJbKdam7nxk8uKiVnoCvX6HnVUl1nbYQV4Ihy3YuYtV02ROZXInx6kQWrbDgn5MrRNDYjvHYTdquzP6GnWN2fg77LpPsFs85M4xFg01aHYQxRFy13UnToEku38wq4v2PAQxb5iOQ6qh3IiN4MlhV3/RCS7OFbooJPaZ7xwC02QIZU9dLJIFtFB0Qs5hV3l9I3a11Rx2UaIoCnRV8YwRgDX2jDH7veY2lzvsADd9AN/cdhx2XS7YzdziTZ7fC2r0Djtx0pWbcHfFExVC0Jji2o55aEIYDjtevCCBEgw7SacZgsMO/QuA018I/nlDpielI4ckEphCfmoC6QFAtUMJtQh3D5O6iiloSMEtFqLYDkA91ZooOjq0A2AX+VJmbdXSc1VDtx12it0xGXanb5LDzqGoZSDWadEDcdjZ4fnMzQelGtZ3oCWrT26y/a7gEot+lWgv3CE3YXcQlSrEcvrnu4Jdqr8jcl21BN+QGn8DuP3/Wfdfute6reYuFENM+EKomrOKL4anhoErjwQmNwDbHV5+HnGlLCS2jqljtQ1LcSyu0MZ47jJZsKvbLSU712tWia0/h11KV1Fg1mfiCHb1hEYHgOOwMxiKpumkpJCLTiCRxU9P3A13r/gzMIyOy2Enunuawc1hZ7o57LpQsNtihijYNTjfENt5tQ0KonNxHHYNhsQW3ZDYag6plhCr2DvO4Npt2KkSW2JOldhOLzoBWFE64TxxUEUn6nfY8XEaAHpbzH84rz+NtaO52gc2gWYLdh6H3VQRm2G/t9yIkMNOFOz4JqytD5Wa/EwbIBYtXJ+5DIZwKkU9BpNXRUHerr6am9jsPJyo4LBjKg+JNYSiE8F3cgk7VDeJEop5OzSxRqXI6UQ2oSFnJ1menLQuJC6gahE67DRVcUJoigXrwlYDEuz6F2yFTxc+j1MKp2PbxVUcNC2i2W4xLtgVi9bATw47l5LmXeil0q33ZYpdGVoXHHaqPemqVYV29oBQQVgfbPlciA5DDuus5rADgKGlwrFd7q4D3JDY5/5Y/rdqVSjFRVA9Qg130K263xLrAMvNB1iLlrhX7ZQnoa0W0/E47PzfOxdqxnJFz+M8d1tNR0WdFe0cGnDY9aR0FG2hTIdh5XwMK4edBK9sVzBMFA3mpKTgxbWcaot6Gstm9eDjB+5oPz4lOCti3t4AjNuFFHqbFAt8HXZdsKiX2XebWY4rZ9t5DbrkxAU3Oey6k4r5y/z7AN6v5ktmy6J5TXg/OzXiPtZQlVgDeTtlQqc77ELFCYltMd9qAw47Md9cq0LkL0/ZHTsvGsBVH9mzpefxQ3eqibvhtmO5EjYzu2+cGgEmpaITQHleYic/bJc77KAlsCExH3OLqwEALMzE+Q1QskMY85OjzmNKhS/DCTczCq7DLoRcJrx4QUopopDnDrv4T77ahaoqTpLl/JQl2Gn29xFlSCzgFmco2IKdZliCXSLTWjjU27echR+YewEAzl88VOPo5uH52Li7y7QHflMhhx3H1DNA3v09lWndYafZopzosNO4w66Gg29Ov9tfrdbDy29IxBTZJVapQizHI9jVcON1A9yF9cpD5X+bsbzy/4lhRvXkLqsmfvJiH3FGT8PKwGzvQrfqCPTksPOfUw3YYTSbp/wFu0Qt8SUp9Y0B5rAbzCacDTjrpIQciCGnHkg6DjsTJcNEsWJIbNZ7KzrsOmCTd5yHxDbrsNPEKrHdGxI7py+NB//7AKzcMIE3zW/QJSeOD5nBQM+LiAmOMMcswabGeOWExJYMNyQ2bIcddzABjVWJFRx2KRLsKiOLts2GxDbgsJvb7xbDaZUdFgzg1s/uE8hzyYgbO5zRXBGjsNfluREhJFYU7KS8xF1fdEJgvMct0W72zo/wTFyKtsOuOCVUdqsQ5sGEC0LlVUlDcNiJ1UZN24ppdsDkq50U7aq5uSmrCiv/PqIMiQWAop1rsGQ703RbsEtlWxPs3rxoAJ/cbzm+8p5tMaMnvPfIBTvNtM6fvw+THHYOTNpxSmVad9ip9iApOuz4d6DXCIntS+n47+LHcIexO+4bel/L50J0GHKYUy0RbroJdrwoS2Gs/G8zllX+P08OO1soqTbeV3Pr9S+ofo5xQFG8k/NWBTtPRVb/MWswW0mws3PY1RLs5N3/Wq5A8VqpIe4NZpKwM9Fa8IrvQBscdvZi1WC2w06qAumExGa8t4XJtuXZC4LWHXZu6HCJh1F3adGl+QMZvG3LJhzR4kZC77zgToiID+IGglGsIyRWdNiFnMMuIQl2WrKu3O9Jzc1h51aJjY2cET/KwqKbDYmtv0rsNnM7w7HL5xGGHBLrcdj5FJ2QHXZOuonwxv/YtHBzaEvnfmJoYYRn4uIILDnrCylAR8WMkHanyJjhCERhhMSqYg49uzoJCyOHXQdTUK1BoOAIdtGHxAKuw65UsC7spGl1mqlsax2boij46iFvwqf3Dy9/HeCKT7p93txhRyGxLmbC+11msq0LdlyU05m7cOXfQSJZfRGqKAquMw7AJ4tfwpuX0oR82iE77PpqtIEt9nbvz90h+POJG7Lj8F3fsoSbgS2A+TtX/j9xAlyPw653HqAI063l+7v3a30ncUGcnNeRZ6gqoouiQkRFbYddrRx2DTrsxITSNVwegz0JJyQWgLf6bxuLTpRM0zkPxajksOtxH292oRYBrSa8d0KdhBx2Cb07BbumEVMk1HJfE52J2B+J41WFfiqVcHPYOS7Xdjns6ky1wCvZTuRL4DoLhcRWwTEU2WNEs6kRRPeYmqj6/188aBvstHAA3zh8+8Zeo804KSZKUkgsz2E3+hpgp6/ybGLzNCdOSGz4DrvYrLQXbLkTsNK6v2iLKqEobaSkJAAGGLbDrggdFaUxoQpLmA47z0Qrbwl2ZgdMvtpJSU0BJlDMWYKdBrvCbyJiwc5uTyX7wk4y6zbdosOuXciCnWFXiWUhVEPuVAxh8VlgGrKp1jtv3RbpdQiCnR0eq6dqT3C+c/SOuOeZN/Cxfas4hojuRA7FHKrRBmZuCSzYDVj3BLDTceGdV1yQF6m7fBDY+7OWuKZWWQCIIbF817paKKSmA8ydEGKvT7vFLfo6wGEHSA67FgU7MRdMxj+NQy3BrmaScVmwqxVqJe6e13CX9qV0MKhORXqPwy7kFCVJx2Fnolhyc9jVdNh5QmLjvclbKLnVH/tSzX2euhDqVLcrc7ohtvNOCM0nGkfsjxpy2BltcNjZfdPkRvv3+ubLaVtUHBXym5JgVwVNcmE3mxpBHENrzAFm9CRx2+fCCWMNkoQwnnJGc0X0cofd+met22SvGwYLuI58R7ALv6BTbFp4z1Zvd+6nZsVjYVmyHXY89NSoom8yj2Bn50wLY6dV1VCyvzataDcUCon1UNKsTt8R7ByHXbST1JLtRCsVrE4zYwt22Z4q1QhjRNoW7FKMO+woJFaGCYu+zeh1Kh22AnfYJQSHXcIW7BJ1FCz50F5LcPkpe6AnrEkXEV/SA14HkxjyWomTbgQ+8xAQYsXp2CAKdj1zrCq6ml5drAOkohN1hMQCwO4fsW63OxxY8nZrwqeowHaHNXfu7cYj2LW4yeTJndWoYGeLL7UWaGU57GosBnl4NAD0V4/yUOxIiwKfE3KHnZas3XZahIfEmsxKuu4KdtxhV0Gwy7m5mOMeEisWGulJNTeG8vZRMlj9eQ+nG56QWBLsuhJxQ90UNpgq9AEZWwybKhgYswW70OaOfBwZX+f9vQZcsNs8VXKfiq7tygj6BEzTbQONikviHEDc4OpgkkKKCc7oVBEbmD1H4W1T3twtKzphO+y6vugEAMzbETjxBuCNJ63JbAwwbMGO2ZOxUjVhgl8QrBRqSCwAFJCEjhySXLAjh50H0xbsjLwVGqJzh12FCr/tggtbpWIe+WIJGbs6QW9vg4mCI4I7AZPIo2SYMErWYMmo6IRDqt9d9A2jD7MD2PXjLroEygW7ZLrFao1E9yNOzOsJv8zO8IYHdjPiInVuA6EbYg47HmZSy1l1yHnAju+zQo1TvcDH/wxA6RxhVFxMtRoSKy4ia4TEjkx6BTseulJTfJHDq2oKdkKbrzOvoFV4Iu+KYSGGw3DEUODJgiDYOeFOkmDHF1k8HBaI/SbvpglrfBvIJJqu7OpxItYbRj3dmCn0PQt2iew0iBBRFGts4uGwNUJi+SbzZMFwQmJDc9jxMWX0deu2zkrFaXtevXnS6idUpTsrQAcGn5uYJdddBzTutBYduV2SD9QpYCJViTUx6D1Q3tAoKzoRfrqJeLXwbd4N7PPF0Hco68WwG7liO+xK1fRNu/NTjBJUWyAKqyppQbEaRNqwBDuFBDsPhi3YlWzBjofEJiJ22PH2ZJQKGBsfg6pYin5PX2cIdhlbsEujiImCAWbwkNh479a3k+yAO6CNq8E4J5N2WG0KRYBZbSYJa9ANogot0eXw0NZdPtg1k6zAmLWte3/ZfvX/n1h1rYZjwUHTgaX7uI6yWVt3jlgHBBsSK+bzqzDfazmHnap6halai0ExpLmvduGzO7/4DqTTtkCX54Jd+HMxUaicLBgoMSEk1hAcn7LDTiTmIbHrx6zFz+y+5j9P3j7ExPTksJNYsAvw4d8Cn/+31R8R3YkqhETWCInNJq1jp4puSGxoOey46JHfbN2m61sLcVFxky3Y9STj4z2KJWKlYL6hAzQ+DogbbUap8nEdBB8TxBx2o7ki3mCD3gPlNBllRSfCF+yolVeBO+xQnLB/r+aws49lJWhODrsQBTsGZM1xQAW0GonnpxvM3llnBVuwYyVAiT4kltntxyjmMTE+Bh6MoNUR1hgHkmlrkZZBHuvyJZglLthRN8LpG3Jt07nEYCDPmRDz4BlFQEsgbbvtkikS7IgaHHAmsN2h3oIShIWeBE57AHj8emDPT9T/f5rosKuj6EQ3IAo/iRbHrDrGDC7YjUqCXclsIB+Z6CYQQ179WLAbMGM5MGPLuiq9bTO3D8j0APmNQM5ecLbFYee+76miYbv8YLVDXnACEIpOSGOEotYO346Y9eO2YNfbimBnOydKrLE2M91Y3sBGBdGZaAlLqDGNOgQ77rArCTnsQhrb5BBYuap9BXhIbK5oiSxBpJ7pasTxNqiK5max9jEdgLixA1jCndWuMmCJHii2/lOWTiZZISR22jjsYoZpV19V7S+sWq4uHv4qOuy0kAS7omo1iAHYOdoS5LDzYC8szOIUGGNOSGwi6pBYx2FXxOS4NcHPo74y5rHA/lx1xcT4xJTgsIv35L+dDM1ynRkztMkqR9ZPIukuAlkpB7OYc37neQUJoiLJHsvZ1Sn9TLuZtxPw7u94EwrXQgwxqTeHXccjONpaddi97XOW6PeWUyseMpCt4LBryC3l5qWpKcIl0sBn/wl88IY6npf/j/05OFUOw5+LaariGGWnxJBYZgD2JqUlytnvV0t4F2wxd9cBrsNuVksOO7E4BznsiGmMmMPMSeHgP15l/UJiQ3PY9VX/vQJp3TuXyZJgVx1Ri+BjhJpoLppxr09btwd9p/XzigE8JJY77MT8qRhY5N6XHchlOeyaLOTRAN0+w2wJLthp9q6lUW0HnYfECjnsVD2cj7dkC3aDihWqq5HLxotTFW0KRYMhYQt2qYgFOy5sGcUCpsati3xKSaNj5FYhJ9Dk5ChMx1lC3Qhn9qwZ2MR6MUMZx4vJ7bBdAM+ZSrvXd7GQR5EVecFxZLIk2BFE2/EsgKaJw04sDiHnh2uUwS2Ar7xUVeBycthNFcEYcws9NJKPTEt6XXa1aFTU5nMNLti1KTdcQlNRKJl2Djth0cUXD4msN/w90eOGncU8fx0QjMNOzE1EOeyIaY1YJKnOkNjJgoGxvDW2hZfDTpq/1ivYJbxCU4ZCYqsjzk14zrVmN5fefQ6w58eBoXgUB20VuUrsqJC3UVm8J7DBrhI7s5ZgRw67SDHtDi1Zsr6QklL5i1B4vjuz5ORMU0PacedVUPsVKxZdT7dYsa3LUO1JtFKcQq6Qd3LFpSJO0M9zvZmlAnKTVpsqKOGH0ASGnoJpuyymJidh2DsKCgl2Dildw+/3vRX/UzoB6f2+EMxzJnQU7TxFxcIUcnb1Y5MpSCXjv/giiK5DEx12deaw63T2/gyww3uBoy8OJs9wIl01p+Jgxpp/GSbDRMFwHucT67qqAta5AGwaXRLs2pRPOKHa43Ch5M2tzENz5bx14u8Rpwaph56kjsUzMlg41PyczZPDzqCQWGIa45tz1b8f4OGlhskwPGEdG1oOuxZDYjnksKuBuBElVjRv9rlmLO+afMgpqegET8HRn9aBNx1hHTTvzcCi3aV/bH/RCVppV8OegKdM22FXpYE7IbFmyQnBDCtnmqF6RZ4ECXYeVO44LE0hNzUJPgQkUxGLY3Z7KhVyMGzBrqh1UP5BRUFBSSLN8shNTkDjFmAqeuLhQ+/aHVPv2DWwvBpJTcUUdCRgoJCbQr5oLT5ySCJLCxCCaD++Drsun07N3hY49ldte7l0QkVSU1EwTGyeKqI3pcMwGex0ZPWJL4v2AJ77Y3gn6TjsRqzbNuSwA4CErgIFA5MFA3kIQnE9gl2rFX7bwOcP3BqfP7C1Igi6yhdiDCWDQmKJaQw3jxTFggP+G0yi+OXmsItZSCwJdo0hVgp2XNgdtPYMEbnoxFiOF1pJAFsfYOU4nrl1+fXC22op580fG+L4SqNXFZgdOpA17aITahWHnd0hqkLRCS0khx2TJoWJDAl2IpqdX0czcsjn3AFKadNkuiK2M9Is5VCYsl2bnSTYASjajsD81BhMvqPQASE27SbIJLiqqqBgL8qKhRymJqyKhLkqjl+CIELEqbon5rDrcoddm1EUBf08LNauBsh3wQFbtKrF4RcA2x8FnPL7ME6xPCS2XQ47e5ExVTRgQIPBp/K5Efs8pHmFp8Lv9Jgv8vZRLFFILDHN4Q47sShNhfEqoall7uW2OezqrBIrh8SSYFcHfP3b5s2luOMIdrYLe9TOYdef0S2hc95OVjSATFIQl/NjrhhOgl1E2JOvATtXnFlFmFBs950nJFYPZwJvat7Gk8pOjwlYvfCcfqqRQ84W7Ewo0Tsg7OIgrJBH0Q5rNPT473aL8IInhdykk2RTTcQ/xKbTKXLBLp/rzHBqgugmPDmBponDLgJm9FifMw/NKoiCXT3iS/984LirrKIrYVBWdKJNDjsnJNaaaxaVpPc8qjnsWi0Y0iEk7fZRpJBYYrrDx6s6K4SKG85JTQ3PYZedCU8xo965df1bucOOxt6a8M0kvqlDDjsA3lyngBgSW0O/0XR3Y8wj2IX3udLoVQXF/uB5NdZqgh0vMKEwV7DTQxIylKS3QaQzIedp6TCSdoiwbuRQzFuJIItIRB9zb1/crDQFI2+LwB0m2Bm2WFyYmoBiWA47hUJiQ6eo8HDqKcedWVBJsCOISBDFOe407vaiExEwo8eaQ22csD7jkuFWfU0EkUevVfjOu+Nsa5PDzl5kTFYU7KR5hUewmx6FilznhEkhscT0RvUJia2ywSQKdEM9CafgT+BoOtA7x/29b15d/5bQVM+GTZARLV0LOex8qRwSW4cILBaeoJDYiLEnOT2KNVlkWuUGrvJ8dWYRGuykyMlwJvC6tEOaypJgJ5K2K2fqRg75nCDYRYzKJ/elHAzbYcc6IJ+MCBfsSvkJKHa1KZUEu9ApKa7DLj9pib0k2BFERIjhRHyiFlIKjOnMTLtK6MZxb0isripQ1RiEN0bksNPt915ZsJMddj3+97sYvhArGYxCYonpDR+virbDTktWNTDwjRLrfsjze1Gw661PsAO8DqhsggS7mpDDzhfRiQ2IIbF1aAZi4Qly2EWLIn/wVYQJnXeIhuEUnUiE5LDT016RR01NjwlYvWTsEOEEy6NQsBZT3KEUJYoj2OWdyjJKh+12mzoX7CadUDA1QYJd2DiCXSGHUs5qO52W/5AgugbRTccnauSwC5yZ9sJx04Ql2PFdcD0uwgufIxrtLcDk5rCz3AClhkJiO2vO0Sz8MyoaJooUEktMZ/jYZK+Hao1VM3vdtevMnpBT3oiRa6J4V4OBrPse+mqFLxLlDjsS7AC4IbGFRkNiAXLYxQlVzvVRZTKmJawvVzGLSMCaRCUT4XQiSbnIxDTZMa2Xnh7r80mxPCYn7Aq/MRDsNDuUWTNyzsWtdJrYaof1GoUpqCbPYUdOr7AxHMFuCqUOzX9IEF2DmP/HcS1EP8Z0GzNtdwcPiS3GLbRRLu7QJocdX2RM5K3N4ZJaKyRW+H265LDTxRx2MWs3BNFOnJBY7gavPlaJDruhsAW7Ld9p3c7apqExdCgruAB7Qz7HboDrF212g8edlkJieeGJ/GhbHHYUw1EFNSULdpUbuGaLFjrLQ1Ot3bywqpKmemd4H5gmE7B6SdsOu7RSxMiYtZgqxcD9oKWsC1kx8lBMa+DU051VMITZnZGZn3QEu7ByNRIuhpoEDKCUz8G0Eweb8mKRIIj2oKrWIsgsuYm8qehE4PCFmBsSa82t5CqGkdFAFEaQpJwcdrbDrkywk+aeKWGeMV2qxArV/0oUEktMZzRZsKs+Z5/V6/Zj8/pD7tP2+RKw7B3AvDc39G+DQsjirLBFxW7AcdhVcGFPU0QnNtBoSCwX7NoTEkszzCrIueLKQmQFNDsssBc54cFwOpFM/0zvA7Rw96DaIR8Z5DE6bruRlOg7dN1x2BWgojMFO5VfA8UpaLZgpyVppyZsTHtBVizkYeY7M/8hQXQVWsor2JHDLnBmOUUnrLEmX7IcZVywihw5vDTVnnzC3GHH3QDO/MYJd5LGBrH64jQZNygkliBsuGGBiwo11qZiGOyWs0NeoySzlmDXIGJI7AwS7Goj57Ajhx0AISS2xENiqehER6KnZMGucgNP2KJFryJU4QlJsMsKgt2U2mPt9hMu9veURgFjE3Y1VjX6Dj1htyfNzEEtWe0k02EFQxRbxGalKaimtROhk2AXOqbdlxjFnCsQTJNcRAQRS7hAlx+zf6dcnkEzQ8phlytak+p0XJKMp/q9v7fJvcYdhlywMzUp3EneXO5fIPzz9Bg3RMGOQmKJaY0m5bCrUSBpp4UDzv1ls+LZXwxmhDx7vTT21oRy2PmSlEJiHYddXTnsqOhEbEikvR1VMl3FYWeLFj0eh11IO+6ZQeeu3j+38nHTFVvhTitFjE/Y4YMhiaeNkLGr1yqlPFKmLdj1dpZgx/PwKcUpaMwW7KjoROgwLtgVclDsnZyyHJsEQbQPvmOdH7d/j36M6Tb4QmzDuJXDjjvsknFx2KUlwa5NDruUbgmWY/biwqiVw65vvnt/1tZhn14s4OGvxZJJVWKJ6Y2Tw06oEluFvZbPxFuWDGFefxo7CuJdnNhqjrs5Moty2NWGHHa+pBLeohN8E6yhkNjcZqDEBbvw1mUUEluFVMYr2KXSlb+IRNK6GPpsh10eCaSqlM1uifSg+7r99ZfBnjYIHVFhYsS6EwPBjhfDSCsFMGa1jXS2v9q/xA49xUXHnBUSqwKZDO3UhA0X7MxiHkrJFuw6rWAJQXQTfEzJj9q/08ZF0PDQrLFcCYWSGX+HXapNDjseEpu3FheMtz3b9V62yy+GxC7aM+zTiwXeHHYUEktMY8ocdtXXQ6qq4LpP7AVVUaCp8RS5j9t9EVZuGEdK1zCYjX59F3v4uti0xozpkhqhFml784vPLXiV2IaKToy/4T5GOeyioa/Pu1uazlRu4HJYYAk6Qpu+p4Udj97ZYb1K5yJcMEpuBEigbcmgq5GyHZopFMG1XKXDwlN4mLhSmkJStTr+dBUhmwgIe0FmlnLQ7J0crU2LQ4IgfHAWPZYYQA674BnIJKCpCgyTYdNEAblizHLYyY66tjnsrPfP7KZnymKx7J6YtTWw9cFA39xpM2d0cxMZ8ct9SBDthPcHDRRIiru4rWsqzjxs+6hPo3OQ18BVUnxNJ7jDLlc0YJoM43Yhp/pCYu3xfnSNdatooaacIMGuCkkpJLaaGyqZkgQ7JcQE1Fmh6ASPRydcVA0lJQGdFdGvWDtKSgwEOz5oplCEBkvN77QKvwlbnEujgCSsnYhUmjr+0LHbLyvmoRmWYCeH7BME0UZklwI57AJHVRUMZZPYMJ7Hxok88qWYOezkkNhke4tOcJgs0MnCoaoBH7w+5LOKF1ycy5dMp93wxRlBTCsoHJKQv/MOM4uEBZ9LTBUNjOVLziZYXQ47Pv6PvGLdpvqAsCIrQTnsqiNZRrP9Q5UPlR12YQp2ySyw3eHW/e2PCu91Opiian0fA7B2lNRYCHaWwy6tFNziJG2a4AcFF7HTSgEJWDsRCi1UQ0ex3TusVEDCsPJkJjPksCOIyJAddXEYY7oQnp9o43gcHXbR5rBzkMfgNp1HnOELsXzJFNpNTIRegmgnZQUHSLCbdsjzkw5be4YFHydyRdMJh03qan2bgpkZ1u3oa/aThZvvkRx21ZA+fF0o9iAjO7hCFewA4NgrgVcfAhZPj3wkjWJoacAYw4BiC3ZxKIxgh+pmkEcC1gSybIc+5qhJ/h4KSCp2LgQKBQsd3r8wI4+kOQUoQDJDAy5BREaZw476wTAQK8XGzmFXFhLb3hx2HFN2S5Bg5xF1eSLxNDnsiOlImcOO8k5PO8hh50uaO7GLBjbbgt1APQUnAG+0IxD6ep4Eu2pkJEddtS9DmqwbYQt2mg4sfXu4r9HBmHoaKACDsCr48eqmkWJP5nsx5Qp28g593EmUh8RSKFj4aPaOqFnMI8XygAKksuSwI4jIKMsbRv1gGIiVYl3BLibCi6pZC6GS5Xpu13heFhIruyU6bV4RAqKoO1kghx0xjXFy2NkVzclhN/2QN3FIsAMAZJLcYWc4DrvBugW7Gd7fU+E67GIy64kpWgIlXQiLrTYJkibrhhqyYEdUx95BmqlYFfy0OOT7sjvMlFKCqtiB8h3msOMDf1opIMUFO1qohk7CzpFZyE8hA2txmO7psLZDEN2EJo3x5LALhZmiwy6OoY286h4AVInCCBI5JJhFVPwizuiqArnAZWxCqQminchzdHLYTT9k9zeNEQCEkNiSiZGWHXYk2EWKLu5EVHXYeTtEM2yHHVEVNW11RrOVzQCAVJWCIW1D2gVnaqLzkr/aDrsM8sgg73mMCI9kyppgFfJTyCrW556iHHYEER1liyDauAgDLthtHC/Ez2EHeAW7NlEmPJUJdjGY70SMoihlodOpuIRSE0Q7kdcZ5LCbfshjAjnsAABp3XXY8ZDYwWyd+k16wKoM6/we7rgbo1lPTBHLX1cTVzQdhvBxGirttkdJMmsp3XMwDADo6Y3BBFbTPTtbSro/1IoyoWB38kMYh8ZdggnarQublF2dN8GKglBKAy5BREaZw44EuzCYwYtOTBTiWTzgrZ+ybrc5pG0vWVuwI/cEUP45kcOOmJaUbS6RYDftKAuJpQ1/wN38myoaGJ4sAAAGMnXqN4oC9Mx2f5fTqAUM5bCrhShG1BBXStChwfrCyybzRFtJ9AwCgCMqqXHZTUj1ASW7Qmwn7oLbtupZtnMRAO3UtIFUxs0dmOWCXZKcjQQRGWU57GiTLgxm9lif88aJvFMxNlYOuwO/CSzcDdj6oLa9pJzDThVDcbQkOWhsLIdd0fmdBDtiWiKHwJJgN/2gHHa+cNc1Y8CGMS7YNaDfDC0Fxte690OERq9a7H6qdbvDMTUP9VSGpd32SFHKOqeYiBtiHoFOy18HOLsyGcXq2ExFJ3G6DaR6rAXZkDIOXbHCwigUmSAipKxKLI35YTCz181hxx12sakSC1hzizcfF/ruuojsMFTFuUTIeXQ6CVGgS+oqlE6LaCCIIJAddhQVM/0gh50v4ubfulErP3jdIbEAMGO5ez9kwY4cdrXY54vAbifXNRkzlARgRwkqtNseLXLnFBdxQzyv7KzozqNZpE6e0cDfFtJSiDcA2iEjiCiRx3gqOhEKYg678bwl2PWkpvfUVXYYqhlBsBtY3OaziS+isJsmdx0xXZEddeSwm36Ia7dEliICbJKaCkWxHHYk2HUDcuneChhqErDNLwoloI6WuCbYFAtP9M2P7jyaRao0pMXlc+1y1LT1uc9TNgEACmoaSXI2EkR0iI46NQGoJAiEAQ+JHc+XsHHCSgcw3QW73pS371d7hTw6cdmcjAGiw44KThDTFnLYEeKauH9BdOcRMxRFQTahYaJgYM2Ila6qoZDYnT8AvPIg0L8QmLVNSGdpMb1nPQFjaknALhimJkiwi5S4Oux6BFdd39zozqNZEllAUQHGwzJp4G8L9u5YUrEcJsVEP2h/jCAiRNysoA260OjP6NBVBSWT4ZWNkwCAvmku2PWkvOJTpk/YVM5tBmEhinSUv46YtpDDjhBTJZQK0Z1HDOlLJyzBbrPlsGtIsBvcAvjQzSGdmRcawQKkpLmiUFkONaK9xDVef1AIV+mdF915NIuilFurifCR2jNLUZ4igogU0W1Mgl1oKIqCGT1upVgA6E1Pb8GuT3r//ekE8O5zrF8OPieCM4onnpBYctgR0xVZoKON9umHJowZzIjuPGKIPJ4OZuNphyDBLkCMhLvjrqZiIhBNVzKD3t/jUnRiYAv3fn8HhsQCkmBHA39bkARnNTsYzXkQBGEhXpO0QRcqM3u9gmjvtHfYed9/b1oH9v4s8NXVwPL9ozmpGCLmrYtVZWGCaCdy1Why2E1PPvB/VmjsUT+N+kxihSzYNeSwayPTe9YTMKYwgdczNIGPlJ7Z3t/Tg5GcRhm9c9z7S/eJ7jxaIdULjNn34yKEdjvSBkCqt30VCQmC8EEMiSXBLlR44QnOdBfsxPef1FRoql39lDaKPfSl3YVXfzqeizCCCB05pzdVkp6evOkI64fw0CeNDYMk2HU/g4MzgPXW/Rkz6itUQYSER7BTvLnjomTbQ4A3fwBYum9dlYdjiSh+6uSwawtS7kBNdpASBNFePA67/srHES0zs9cr2Mk74tONnqT7/hUlwhOJOaJTggQ7YtoiC3Q0fyQIB3E+oShAPwl23U9v36BzP5GhCXykiIJdIgPEpaKmngLee2nUZ9EaokuwzgrKRIsoiuXi4QnF09S/EESkUEhs2+CVYjnTvUqsqroqnUqKXUX6M7rvfYKYVqT6vMXiyGFHEA6iw25Wb8p1rMcMSuoQJOKkXQyXIdoPLaDCQ3QriuIdES59Qs7D3g6sMEwQ3QSFxLaN+QNuzqVsUkNCo6krZ6pICcQr0U8hsQRhbfhqwqZHXFIEEUQM6BccdgsG4pvfkWY9QSLuuCdpAh8p4q5zp4aexhXRvUjCUfvoX+DeH1gU3XkQBOHNF0YhsaGyZKabK3XxEOVNBYDlsyzB+JAdO7DafJsQQ5viGuZEEG0nSbkuCYIzSyhqNX8gvmmeSLALEs8EnjrEyDn2CiDRA7z1tKjPpLvoEVx1JNi1D49gtzi68yAIQnLY0XgfJktmup/1oqH4TqjbyU2ffhu+cODW+K93bRP1qcQW0TnRP83zHhLTHebeVWnpTxCcree687f5g/F12NEIFiTiLjvtYETPDscA2x0BaNTMA2XGMve+XI2XCI/+he59ctgRRLT0Cs4mxiofR7SM6LAbkirGTlcGs0l88SAS66pBDjuCsJmxHHjjqajPgiBix7bz3IjIt20ZkwKVPpDMHiTbvAdYth+w9buBOdtHfTYEQGJdGGx5ALDHx4DFbwUW7RH12UwfdjoWWPgWS4geXBL12RDE9CaZBd77C2DujsDOJ0R9Nl1NOqHhohN3w7Zz+/DBt24R9ekQHcLOiwax2xaDeNP8frx9q/guxAgidPb6NDBzK+Don0d9JgQRK+b1p/H+tyzCoTvNwwHbxTcvO6kZQdI3Fzj5t1GfBUGEi6oBh/0o6rOYfszaGvj4n6M+C4IgOG8+1vohQuewN8/HYW+eX/tAgrDJJDXc9Om3R30aBBE9u33I+iEIwoOiKPjhsTtHfRo1IYcdQRAEQRAEQRAEQRAEQcQIEuwIgiAIgiAIgiAIgiAIIkaQYEcQBEEQBEEQBEEQBEEQMYIEO4IgCIIgCIIgCIIgCIKIESTYEQRBEARBEARBEARBEESMIMGOIAiCIAiCIAiCIAiCIGIECXYEQRAEQRAEQRAEQRAEESNIsCMIgiAIgiAIgiAIgiCIGEGCHUEQBEEQBEEQBEEQBEHECBLsCIIgCIIgCIIgCIIgCCJGkGBHEARBEARBEARBEARBEDGCBDuCIAiCIAiCIAiCIAiCiBEk2BEEQRAEQRAEQRAEQRBEjNDrOYgxBgAYHR0N9WSIzoC3A94uwoLaHSHSrnYnvga1PQKgPo+IBmp3RBRQuyOigOZ4RFRQn0dEQSPtri7BbmxsDACwePHiFk6L6DbGxsYwMDAQ6vMD1O4IL2G3O/4aALU9wgv1eUQUULsjooDaHREFNMcjooL6PCIK6ml3CqtD1jNNE2vWrEFfXx8URQnsBInOhDGGsbExLFiwAKoaXlQ1tTtCpF3tDqC2R3ihPo+IAmp3RBRQuyOigOZ4RFRQn0dEQSPtri7BjiAIgiAIgiAIgiAIgiCI9kBFJwiCIAiCIAiCIAiCIAgiRpBgRxAEQRAEQRAEQRAEQRAxggQ7giAIgiAIgiAIgiAIgogRJNgRBEEQBEEQBEEQBEEQRIwgwY4gCIIgCIIgCIIgCIIgYgQJdgRBEARBEARBEARBEAQRI0iwIwiCIAiCIAiCIAiCIIgYQYIdQRAEQRAEQRAEQRAEQcQIEuwIgiAIgiAIgiAIgiAIIkaQYEcQBEEQBEEQBEEQBEEQMYIEO4IgCIIgCIIgCIIgCIKIESTYEQRBEARBEARBEARBEESMIMGOIAiCIAiCIAiCIAiCIGIECXYEQRAEQRAEQRAEQRAEESNIsCMIgiAIgiAIgiAIgiCIGEGCHUEQBEEQBEEQBEEQBEHECBLsCIIgCIIgCIIgCIIgCCJGkGBHEARBEARBEARBEARBEDGCBDuCIAiCIAiCIAiCIAiCiBEk2BEEQRAEQRAEQRAEQRBEjCDBjiAIgiAIgiAIgiAIgiBiBAl2BEEQBEEQBEEQBEEQBBEjSLAjCIIgCIIgCIIgCIIgiBhBgh1BEARBEARBEARBEARBxAgS7AiCIAiCIAiCIAiCIAgiRpBgRxAEQRAEQRAEQRAEQRAxggQ7giAIgiAIgiAIgiAIgogRJNgRBEEQBEEQBEEQBEEQRIwgwY4gCIIgCIIgCIIgCIIgYgQJdgRBEARBEARBEARBEAQRI0iwIwiCIAiCIAiCIAiCIIgYQYIdQRAEQRAEQRAEQRAEQcQIEuwIgiAIgiAIgiAIgiAIIkaQYEcQBEEQBEEQBEEQBEEQMYIEO4IgCIIgCIIgCIIgCIKIESTYEQRBEARBEARBEARBEESMIMGOIAiCIAiCIAiCIAiCIGIECXYEQRAEQRAEQRAEQRAEESNIsCMIgiAIgiAIgiAIgiCIGEGCHUEQBEEQBEEQBEEQBEHECBLsCIIgCIIgCIIgCIIgCCJGkGBHEARBEARBEARBEARBEDGCBDuCIAiCIAiCIAiCIAiCiBEk2BEEQRAEQRAEQRAEQRBEjCDBjiAIgiAIgiAIgiAIgiBiBAl2BEEQBEEQBEEQBEEQBBEjSLAjCIIgCIIgCIIgCIIgiBhBgh1BEARBEARBEARBEARBxAgS7AiCIAiCIAiCIAiCIAgiRnSsYDc+Po6zzjoL73nPezBjxgwoioIrrrjC91jTNHHxxRdjl112QSaTwcyZM3HAAQfgscce8z3+9ttvh6IoWLBgAUzT9D1m6dKlUBTF+ZkzZw723Xdf3HzzzWWvfdVVV+Gtb30rZsyYgb6+PmyzzTb48Ic/jL///e/Ocffeey8URcFvfvMbz/8XCgUcfvjhUFUVl19+eQOfEBEGTz75JI499lgsX74c2WwWs2bNwjve8Q7cdtttzjGmaeKKK67AkUceicWLF6Onpwc77rgjzjnnHORyuYrP/fTTT0NRFKTTaYyMjPges//++3va3YwZM7DHHnvg8ssvL2urt912G/bbbz/MmTMH2WwWy5cvx3HHHYc//vGPzjGrVq2Coij44Q9/6Plfxhg++clPQlEUnH322Y1/UEQoPPLIIzjyyCMxY8YMZLNZ7Ljjjrjwwgt9jx0ZGcGcOXN8+xWRn/3sZ1AUBW9961srHiO2OVVVsWDBArz73e/Gvffe6zmuUCjgJz/5CXbddVf09/djcHAQO+ywAz7xiU/gmWeecY674ooroCgK/vnPf3r+f/Pmzdhzzz2RTqc97ZQIn3rG1Eb7ts2bN+MrX/kKtt56a2QyGSxZsgQf/ehH8corr1Q8j+OOOw6KouCMM87w/TsfK/lPIpHA8uXL8eEPfxgvvfSS59j169fjC1/4ArbbbjtkMhnMmTMHe+65J8444wyMj487x51yyino7e0te63HH38cs2bNwtKlS7Fq1aoqnx4RFmHN9V555RWcdtppWLp0KVKpFObMmYNjjjkGDz74YNXzaWR++K53vcv375dddpnTfuU+kIgHYc31Nm7ciNNPPx3bbrst0uk0ZsyYgYMPPhi///3vq55PI/PDrbfe2vfvd911l9Puqs0JiOgJeq735JNP4qSTTsLChQuRSqWwYMECnHTSSXjqqaeqnkcj88OPfexjvn8/88wznWM2bNhQ9fWI9hCH+d7vfvc7vOc978HMmTORTqexzTbb4PTTT8emTZuqnnsjc8T/+7//8z3m7W9/OxRFwY477lj1tWIF61BWrlzJALAtttiC7b///gwA+9WvfuV77Mknn8x0XWcf+chH2GWXXcYuuOACdvLJJ7M777zT9/gTTzyRLV26lAFgd911l+8xS5YsYbvssgu7+uqr2dVXX82+//3vs+XLlzMA7OKLL3aO+8xnPsMAsKOOOor95Cc/YRdddBH7/Oc/z7beemt21llnOcfdc889DAC74YYbnMcKhQI74ogjmKIo7Be/+EXjHxIROL///e/ZwQcfzM4++2x26aWXsgsuuIDtu+++DAC75JJLGGOMjY2NMQBsr732Yueccw679NJL2amnnspUVWX7778/M03T97m/9rWvsXnz5rFUKsUuu+wy32P2228/tmjRIqfdnX/++WyXXXZhANgZZ5zhHHfeeecxAGy//fZj559/Pvv5z3/O/t//+39sl112YSeffLJzHL+OzjvvPOcx0zTZaaedxgCwb3zjGwF8akQQ3HHHHSyZTLK3vvWt7Pzzz2eXXnopO+OMM9jpp5/ue/znPvc51tPTU9avyLztbW9z+rvnn3/e9xgA7KCDDmJXX301u+qqq9i3vvUtNnfuXKYoCrv99tud4w4//HCmaRo76aST2EUXXcQuuOACdtppp7FFixZ5+udf/epXDAB7+OGHncc2b97M9txzT5ZKpTzPSbSHesbURvo2wzDYHnvswXp6etjpp5/OLrvsMnbGGWewvr4+tnDhQjY6Olp2Dps3b2bpdJotXbqULV682Lev5GPl5z//eXb11Vezyy+/nH32s59lyWSSzZgxg61evZoxxtjGjRvZFltswQYHB9mXvvQldumll7Lvfe977IQTTmB9fX1s5cqVznOefPLJrKenx/M6//nPf9isWbPYFltswV566aUWPlmiFcKY6z3wwAOsv7+f9ff3sy996UvsF7/4BTvnnHPYVlttxRRFYT/72c8qnk+988N0Os1UVWWvv/562d/3228/lk6ny/pAIj6EMdd75pln2MKFC1kymWSf/OQn2WWXXcbOO+883zmcTL3zQ96uHnroobK/n3zyyc7fq80JiGgJeq534403smQyyebNm8fOPPNM9otf/IJ9/etfZ/Pnz2epVIrdcsstFc+l3vlhOp1mg4ODLJ/Pl/192bJlTrtbv359nZ8CESZRz/e+/OUvMwBs5513Zt///vfZZZddxj71qU+xVCrFFi9ezJ577jnf825kjphOp9khhxxS8b2n02m2ww47NPHpRUPHCna5XM6ZCD388MMVJ3G//vWvGQB200031fW84+PjrKenh1144YVs1113ZaeccorvcUuWLGGHHXaY57HXX3+d9fT0sG222YYxxtjatWuZoijs4x//eNn/m6bJ1q1b5/wuC3aFQoEdffTRTFEUdumll9Z17kQ0lEoltvPOO7Ntt92WMcZYPp9nf/3rX8uO+9a3vlVxkm+aJlu6dCn70pe+xI455hi2//77+77WfvvtV9bBTExMsEWLFrGenh5WKBRYsVhk/f397KCDDvJ9DrHd+Ql2XGQ+88wza795oi1s3ryZzZ07lx1zzDHMMIyax//nP/9huq6zb3/721Un5y+99JLTP86ePZudffbZvscBYJ/5zGc8jz3++OMMAHv3u9/NGGPsH//4BwPAzj333LL/L5VKbMOGDc7vsmA3OjrK9tprL5ZMJtnvfve7mu+PCJ56xtRG+ra//vWvDAD76U9/6jn28ssvrzgmX3755SyRSLA///nPDAC79957y47x29xijLELL7yQAWDf/e53GWOM/eAHP2AAfM938+bNbGpqyvldFuyeeOIJNnv2bLZ48WL24osvlv0/0T6Cnutt2rSJzZs3j82dO5e98MILnr9NTk6yfffdl2maxv72t7+V/W8j88MDDzyQ9ff3swsuuMDzt1dffZWpqsre9773kWDXYbQy1ysUCmzHHXdk2WyW/f3vfy973g984AMMALv++uvLnq/R+eG2227L/uu//svzt6mpKdbf3++0OxLs4knQc70XXniBZbNZtt1227E33njD87f169ez7bbbjvX29vpuSjUyPzz66KOZqqpl4h+fB/B2R4JdPIhyvnfNNdcwAOwDH/gAK5VKnuMfeughls1m2c4778yKxWLZazcyR3zve9/LdF0va3Pnnnsumzt3Lttnn306SrDr2JDYVCqFefPm1Tzu/PPPx5577oljjjkGpmliYmKi6vE333wzpqamcOyxx+L444/HTTfdVDWMUWTevHl405vehJUrVwIAVq5cCcYY3v72t5cdy8No/SiVSjj++ONx66234uKLL8bHP/7xul6fiAZN07B48WInTCGZTOJtb3tb2XHHHHMMACu0Qeavf/0rVq1aheOPPx7HH388/vKXv+C1116r6/Wz2Sz22msvTExMYP369diwYQNGR0d92x2Aiu0OAL7whS/goosuwle/+lWcc845db0+ET7XXHMN1q1bh3PPPReqqmJiYqJiOBZgfY/HHHMM9t1336rPu2LFCgwNDeGwww7D+9//fqxYsaLuc9ppp50wa9Ysp7978cUXAcC33WmahpkzZ/o+z/j4ON7znvfgkUcewY033ojDDjus7nMggqOeMbWRvm10dBQAMHfuXM+x8+fPBwBkMpmy51mxYgUOOuggvPOd78Sb3vSmhtrjAQccAACe9qhpGvbaa6+yY/v7+5FOp32f5+mnn8aBBx6IVCqFe+65B8uXL6/7HIjgCXqud8kll2Dt2rU477zzsOWWW3r+lslkcOWVVwIAvv3tb5f9byPzw3Q6jfe+97245pprPI9fe+21GBoawsEHH1zzPRHxopW53o033ognnngC//3f/10WXqhpGi655BIMDg7irLPOKnu+RueHJ5xwAn7961975gi33XYbJicncdxxxzX0non2EvRc77zzzsPk5CQuvfRSzJ492/O3WbNm4ZJLLsH4+DjOO++8sv9tZH64cOFCvOMd7yjr71asWIGddtqps0IPpwFRzve+9a1vYWhoCJdeeik0TfMcz1OWPPbYY7jpppvKXruROeJRRx2FVCqFG264wfP4Nddcg+OOO67steNOxwp29TA6Oop//OMf2GOPPfC1r30NAwMD6O3txfLly3H99df7/s+KFSvwzne+E/PmzcPxxx+PsbExT86KahSLRbz66qvOwnTJkiUAgBtuuAGTk5N1PUepVMIJJ5yAm2++GRdddBE++clP1vV/RHuZmJjAhg0b8OKLL+LHP/4x/vCHP+DAAw+s+j9r164FYA2SMitWrMCWW26JPfbYA0cccQSy2Syuvfbaus/npZdegqZpGBwcxJw5c5DJZHDbbbfVzAUg8sUvfhEXXnghzjjjDHz3u9+t+/+I8Ln77rvR39+P1atXY9ttt0Vvby/6+/vxqU99qmzBeMMNN+DBBx/ED37wg5rPu2LFCrz3ve9FMpnECSecgOeffx4PP/xwXec0PDyM4eHhsv5uxYoVKJVKdT3HxMQEDjnkEDz88MO44YYbcPjhh9f1f0S88Ovbdt99d/T09OAb3/gG/vznP2P16tW477778JWvfAV77LFHWX6vNWvW4J577sEJJ5wAwFp0/uY3v0GhUKjrHLhgLLZHwzBw9dVX1/0+nn32WRxwwAHQdR333HNPmaBDxJNG5nq33XYb0ul0ReFi2bJl2GeffXD33XeX9a2Nzg9PPPFE/OMf/3DaJmAtFt7//vcjkUi08I6JdhHUXI+3kw9/+MO+/zMwMICjjjoKTz/9tKe9AI3PD0888US8/vrrnhyz11xzDQ488MCqG7ZE9AQ917vtttuwdOnSioLeO97xDixdutS3H2t0fnjiiSfitttuc/LDlkol3HDDDTjxxBPreetEh9DKfO/555/Hs88+i6OOOgr9/f2+z8/7SLlNNjpHzGazOOqoozx95WOPPYYnn3yyM9tk1Ba/IKhk53zkkUcYADZz5kw2d+5c9rOf/YytWLGC7bnnnkxRFPaHP/zBc/y6deuYruue/BBve9vb2FFHHVX2mkuWLGHvfve72fr169n69evZY489xo4//ngGgH3uc59zjvvwhz/MALChoSF2zDHHsB/+8Ifs6aefLns+buFcsmQJA8Auuuii1j4UIlQ++clPMgAMAFNVlb3//e9nmzZtqvo/73rXu1h/fz8bHh72PF4oFNjMmTM9Iagnnngi23nnncueY7/99mPbbbed0+6efvpp9vnPf54BYEcccYRz3De/+U0GgPX09LBDDjmEnXvuuexf//pX2fPxkFje7irlyCCi5c1vfjPLZrMsm82yz33uc+zGG29kn/vc5xgAdvzxxzvHTU5Osi222IJ99atfZYxVDh9kjLF//vOfHlu7aZps0aJF7Atf+ELZsQDYRz/6UbZ+/Xr2xhtvsIceeogdeOCBDAD70Y9+5Pz/fvvtxwCwuXPnshNOOIFddNFF7OWXXy57Ph4Su2TJEpZIJKrmUCHaT7XQQz8q9W2/+93v2Pz5852+EgA7+OCD2djYWNlz/PCHP2SZTMbJdfLcc88xAOzmm2/2HMfb9OWXX87Wr1/P1qxZw37/+9+zpUuXMkVRnBDDtWvXstmzZzMAbLvttmOnnXYau+aaa9jIyEjZa5988skskUiw+fPnswULFlTMn0JESxBzvcHBQd+xVYSPqY8//rjzWKPzw8MOO4yVSiU2b9489p3vfIcxxthTTz3FALD77rvPN48nET+CmuvtsssubGBgoOr/nX/++QwA++1vf+s81uj8kId47b777uyjH/0oY4yx4eFhlkwm2ZVXXll1TkBET5BzvZGRESeHejWOPPJIBsCTZ6zR+eFnPvMZtmnTJpZMJtnVV1/NGLPyQCqKwlatWsXOOussComNKe2c791yyy0MAPvxj39c9TX6+/vZbrvt5nms0TniDTfcwH73u98xRVHYK6+8whhj7PTTT2fLly9njPmnmIozXS3Y/eUvf3EajZgzYmxsjM2aNYu9/e1v9xz/k5/8hCWTSc9g/L//+79ljzHGHIFD/NE0jX3oQx9ik5OTznGGYbCf/vSnbLfddvMce8ABB7DXXnvNOU5MkqjrOiVdjzlPP/00u+uuu9iVV17JDjvsMHbMMcewtWvXVjz+3HPPZQB8k1nfeuutDAB74oknnMduu+22sscYY44gIv4oisIOO+ywsoHwmmuuYfvssw9TVdU5dtddd2VPPfWUc4yYfBNAxWTGRLTwgjannXaa53G+mOACwze/+U02f/58Z4CsNjn/4he/yObOnevJIfHlL3+57DHGWFmb423mS1/6kifPSi6XY+eccw7bbrvtPMced9xxnsGdL1bT6TTr6+vzFZOJ6GhkAletb3vooYfYoYceys4991x2yy23sLPPPptls1n2/ve/v+zYXXfdtezxt7zlLWWP8TYt/8yePZtdddVVnmPXrFnDTjvtNDZ37lznuGQyyb797W97khWffPLJTFVVlkgk2I477lhzQU5EQxBzPU3T2D777FP1dc4888yy/IeNzg95juPPf/7zbPvtt3eelyfKJsGuMwhqrrfllluyRYsWVX2tyy67jAFgK1ascB5rdH7IF6Dnn38+GxoaYvl8nl122WXOQpcEu3gT5Fzv1VdfZQDYSSedVPU1P/jBDzIATsEmxhqfH/Icx0ceeSQ79NBDneflfS8JdvGlnfO9q6++mgGoWUhz4cKFbOutt/Y81ugc8YYbbnA2PH7wgx8w0zTZ4sWLnc0PEuwioFJj448vW7as7H9OPfVUlkgkPEkN99hjD7bPPvuw559/3vl54IEHGOBWheIsWbKEvfWtb2V33XUXu/vuu9mDDz5YpjbLbNiwgd16663skEMOYQA8k0bewC688EK2fPlyls1m2QMPPND4h0FEwkEHHcT22GMP34o11113HVMUxdntlDn22GPZsmXLPO3uqaeeYtls1tk94+y3335s6dKlTrt74IEHPEUk/Ni8eTO788472YknnsgAsC233NJJuM4Fu7POOovtscceTFVVmsjFkB122MFxZojcd999DAC78sor2cqVK1kmk2GXX3658/dKk/NSqcTmz5/Pjj/+eE+7u/766xkAdscdd3iO57u0vN099NBDbHx8vOo5r1mzhl177bVsr732YgDYBz/4QedvfLF65ZVXspkzZ7LZs2ezZ555ptmPhwiYeidw1fq2F198kWWzWfab3/zG8/gVV1zBAHg2pbjz6Mc//rGnPX75y19m6XSabd682TmWt+lvfvOb7K677mJ//vOf2eOPP+6boJhjmiZ79tln2YUXXsgWLlxYtjnBi05ce+21TFVVtvfee9ds30T7CWKu14jDTqyK2Oj8kAt2f//73xkA9u9//5stW7bMcbGTYNeZNDvXa8RhJyZzb3R+yBega9ascYoA7L///uzYY49ljFXfxCOiJ8i5XiMOO0VRnAqvzcwPuWB33XXXsUQiwV5++WXW09PjRIuRYBdf2jnfa8RhJ260NTNH5NfCaaedxnbZZRd27733MgDsySefZIyRYBcJlRrb6tWrGWCVJJY544wzGAAnPIZbKyv9vOMd7/D8v1+V2EbgTqlVq1YxxrwN7MUXX2Tz589nAwMD7N///nfTr0G0j0suuYQBKBMd7rzzTpZMJtnhhx/uu6DkJaortbslS5Z4JoatdjAnn3wyA9zKOmKV2A0bNrDtt9+eJZPJsgGZiJaDDjrIt309/fTTDAC74IIL2Ic+9CG21VZbsZdeeomtXLmSrVy5kl177bXObtjKlSsdN9ydd95Ztb/78Ic/7HkdcULWKIVCgW299daeRbO4WH3ooYdYb28vW7x4sWNbJ6Klnglcrb7tG9/4BlNVleVyOc/jmzZtYoC3CvXXvva1qu2xHhG6Xl588UWmqqqn0qJYJfZnP/sZA6zqx3wBQ8SDIOZ6b3vb21g6nS5rlyL7778/SyaTTrREq/PDLbfcku2///4MAHv00UcZYyTYdSrNzvX4hqlfigjOKaecwgA4lalbnR8ecMABbN9992WqqjphYyTYxZug53oLFizw3cgQWbp0KVu8eLHzeyvzw8nJSdbb28v2339/T4VOEuziSzvne3wsPfXUUyu+1qpVqxgA9qEPfch5rJU5Infg77///p7Nuk4T7HR0MQsWLMC8efOwevXqsr+tWbMG6XQafX19AKzkmolEAldffXVZ5ZAHHngAF154IV555RVsscUWgZzb7rvvjvvuuw+vv/66k6yds3z5ctxxxx3Yb7/9cPDBB+P+++/H1ltvHcjrEuEwNTUFANi8ebPz2EMPPYRjjjkGu+++O66//nroevnlxqvMXXzxxWXFKJ599ll8/etfx1//+lfss88+gZzn7rvvjiuvvBKvv/562d9mzpyJO++8E29/+9vx3ve+F3fddRf23nvvQF6XaI23vOUtuOuuu5xExJw1a9YAAGbPno1XXnkFL7zwgm9Vy09/+tMArEIRg4ODWLFiBebMmYOLLrqo7NibbroJN998M37+85/7VvJslEQigTe/+c14/vnnsWHDhrLKVHvuuSduueUWHHbYYTjooINw//33l1UzI+JFPX3bunXrwBiDYRiex4vFIgA4hUkYY7jmmmvwzne+02mnIt/5znewYsUKnHrqqYGc+/LlyzE0NOTbBwLApz71KWzatAlf//rXcdJJJ+G6666DqnZ1fa6Op5G53hFHHIEHH3wQN9xwA0466aSy41etWoX7778fRx11lNP/tTo/POGEE3DOOefgTW96E3bZZZcW3y0RJc3O9Y444ghcc801uOqqq/D1r3+97O+jo6O49dZbsdtuuzljeKvzwxNPPBEf+9jHMDg4iEMPPbTp90y0j6DnekcccQQuueQSPPDAA77t5P7778eqVavwpS99yXmslflhJpPB0Ucfjf/7v//DIYcc4ltkj+gsgpzvbb311th2221xyy234Cc/+YkzLotcddVVAIBjjz0WQOtzxH322QdbbLEF7r33Xnz/+99v4J3HjGj1wmCopg5/4QtfYADYnXfe6Ty2fv161t/f78TZM8bYVlttxQ444ADf53/ttdeYoijsf/7nf5zH6nHYvf766471UiSfz7NddtmFqarq7Db47Xo9+OCDrKenhy1ZssST746IDr/w00KhwHbbbTeWyWScfBJPPfUUmzlzJtthhx2q5kM68MADnQSYMrlcjvX29npyWdSzIzAxMcEefPBB378deuihDAB75JFHGGNehx3nueeeY3PmzGFDQ0OepNtEdPCk6ieeeKLn8RNOOIHpus5Wr17N7r//fnbzzTd7fr7zne8wAOwrX/kKu/nmm1mhUGCTk5Osr6+PfeQjH/F9rb/+9a8MALvuuuucx1CHw+65557zdQ8MDw+zBQsWsKGhISf3iZ+75KabbmKaprHddtvNY28n2k+1MbXevu2HP/yh73NccMEFnvZ1//33MwBl+ec45557LlNV1cmvU69D5O9//7tvWOtDDz3EALAjjzzSeUx02HG++MUvMgDsYx/7WNXXIdpHEHO9TZs2sXnz5rF58+Y5TibO1NSU4wwRc+G1Oj/kSdfFMHBy2MWboOd6hUKB7bDDDqynp6fsOzcMw3Hg3Xjjjc7jrc4PR0ZG2FlnncWuueYa5zFy2MWbIOd6jDH2/PPPs2w2y7bffnu2YcMGz3Nu3LiRbb/99qy/v5+99NJLjDEWyPzw3//+NzvrrLM86xBy2MWXds73GLPyq/M2LudD/Oc//8l6enrYrrvu6jj5gpgj3nLLLeyss85ia9ascR4jh10b+elPf4qRkRFn5+G2227Da6+9BgD43Oc+h4GBAXz1q1/F9ddfj/e973340pe+hIGBAfz85z9HsVjEd7/7XQCWevzCCy/gs5/9rO/rLFy4ELvtthtWrFiBM844o+7ze+2117DnnnvigAMOwIEHHoh58+bhjTfewLXXXovHHnsM//Vf/1V192HvvffGTTfdhCOOOMJxnsycObPu1yeC55Of/CRGR0fxjne8AwsXLsTatWuxYsUKPPPMM/jRj36E3t5ejI2N4eCDD8bw8DBOP/10/P73v/c8x5Zbbom9997bKVH9+c9/3ve1UqkUDj74YNxwww248MILkUgk6jrHyclJvO1tb8Nee+2F97znPVi8eDFGRkZwyy234P7778fRRx+NXXfdteL/b7311rjjjjuw//774+CDD8YDDzzgu5NHtI9dd90VH/nIR3D55ZejVCphv/32w7333osbbrgBX/3qV7FgwQIsWLCg7P8GBwcBAHvssQeOPvpoANYO6djYGI488kjf19prr70we/ZsrFixAh/4wAfqPsfHHnsMJ554Ig455BDsu+++mDFjBlavXo0rr7wSa9aswQUXXFDmThE55phjcNlll+EjH/kIjjzySPzxj39EOp2u+/WJ1qk1pqqqWlffBgCnnHIKfvjDH+KTn/wkHn30Ueywww545JFH8Itf/AI77LADjjnmGADWbr6maTjssMN8z+nII4/EmWeeieuuu87jAqjF1VdfjRUrVuCYY47BW97yFiSTSTz99NO4/PLLkU6n8bWvfa3q///oRz/C8PAwfvGLX2DGjBmdvTPb4QQ11wOAoaEh/OY3v8Ghhx6K3XbbDR/72Mew/fbbY+3atbjiiivw0ksv4ac//Sne+ta3AghmfrhkyRKcffbZAX4iRNgEOdcDLKf5jTfeiAMOOAD77LMPTj31VOy+++4YGRnBNddcg0ceeQRf+9rX8N73vhcAApkfDgwMULvrMIKc6wHAVltthauuugonnHACdtppJ3z0ox/FsmXLsGrVKvzyl7/E8PAwrrvuOixbtgwA8Nvf/rbl+eHOO++MnXfeubUPggidKOZ7gOU4/+c//4nzzz8fTz31FD74wQ9iaGgIjzzyCC6//HLMnj0bv/nNbxwnXxBzxKOOOgpHHXVUax9Y1EStGLaCX6VW/rNy5UrnuBdffJEdc8wxrL+/n2UyGXbAAQewf/zjH87feclsebdV5Oyzz2YA2GOPPea8di2H3ejoKPvJT37CDj74YLZo0SKWSCRYX18f23vvvdlll13myT1Rbdfr17/+NVNVle2xxx6esttE+7n22mvZu971LjZ37lym6zobGhpi73rXu9itt97qHMNda5V+Tj75ZMYYYz/60Y8YAPanP/2p4uvxhJ38+evZESgWi+yyyy5jRx99NFuyZAlLpVIsm82yXXfdlZ133nmevEx+DjvO/fffzzKZDFu2bJmnehQRDYVCgZ199tlsyZIlLJFIsK222qpm4la/fuWII45g6XSaTUxMVPy/U045hSUSCWdHFnU47NatW8f+53/+h+23335s/vz5zvVxwAEHlCWireYu4Tt1lXJlEOFRa0ytt2/jvPbaa+wjH/kIW7ZsGUsmk2z+/Pns4x//uLPLzit47bvvvlXPa9myZWzXXXdljNXvEHn88cfZ6aefznbbbTc2Y8YMpus6mz9/Pjv22GMdhzHHz2HHmJV8++ijj2YA2Pe+971aHx8REkHN9URWrVrFPvGJT7AtttiC6bruPN/dd9/tOS6s+SE57OJNkHM9kfXr17Mvf/nLbKuttmLJZNI59pe//KXnuLDmh+Swiz9BzfVE/vOf/7ATTzyRzZs3j6mqygCwdDpdFgUW1vyQHHbxo93zPZnf/va37F3vehcbHBx0nnOHHXbwRNiEOUfsNIedwhhjDat8BEEQBEEQBNEF/OlPf8Khhx6KffbZB3/4wx+QTCajPiViGvCf//wH++67LxYvXowHHngAAwMDUZ8SMQ246qqrcMopp+Ckk05ycoYRRJR87GMfwy9/+Utcdtll+NjHPhb16cQOyqRMEARBEARBTFsOPPBAXHnllbjnnntw6qmngvayiXaw00474dZbb8Xzzz+Po48+GoVCIepTIqYBH/7wh/G9730PV199dc30EATRDi655BIcfvjh+NSnPoXbb7896tOJHeSwIwiCIAiCIAiCIAiCIIgYQQ47giAIgiAIgiAIgiAIgogRJNgRBEEQBEEQBEEQBEEQRIwgwY4gCIIgCIIgCIIgCIIgYgQJdgRBEARBEARBEARBEAQRI/R6DjJNE2vWrEFfXx8URQn7nIiYwxjD2NgYFixYAFUNT/OldkeItKvdAdT2CC/U5xFRQO2OiAJqd0QU0ByPiArq84goaKTd1SXYrVmzBosXLw7k5Iju4dVXX8WiRYtCe35qd4QfYbc7gNoe4Q/1eUQUULsjooDaHREFNMcjooL6PCIK6ml3dQl2fX19zhP29/e3fmZERzM6OorFixc77SIsqN0RIu1qdwC1PcIL9XlEFFC7I6KA2h0RBTTHI6KC+jwiChppd3UJdty22d/fTw2McAjbzkvtjvCjHTZyanuEH9TnEVFA7Y6IAmp3RBTQHI+ICurziCiop91R0QmCIAiCIAiCIAiCIAiCiBEk2BEEQRAEQRAEQRAEQRBEjCDBjiAIgiAIgiAIgiAIgiBiBAl2BEEQBEEQBEEQBEEQBBEjSLAjCIIgCIIgCIIgCIIgiBhBgh1BEARBEARBEARBEARBxAgS7AiCIAiCIAiCIAiCIAgiRpBgRxAEQRAEQRAEQRAEQRAxggQ7giAIgiAIgiAIgiAIgogRJNgRBEEQBEEQBEEQBEEQRIwgwY4gCIIgCIIgCIIgCIIgYgQJdgRBEARBEARBEARBEAQRI0iwIzy8umkSn7v2Udz//PqoT6Uyf/wacNkBwKsPR30mBFGRomHiv298HDc98lrUp0JMEybyJXz5+sdwzzNvRH0qBNFWGGP40Z3P4uq/rYr6VIiQeH3zFD537aP418vDUZ8KQRCt8sAFwAM/jvosiE6kMAn87ovA83dFfSZtgwQ7wsPNj67GbY+twYd++Q9MFYyoT8efdU8Aq/8FbHw+6jMhiIr84Ym1uO7hV/Gl6x+L+lSIacLNj67GjY+8hlOveBhjuWLUp0MQbePfr47gf//8Ar5x65MYnihEfTpECJz92ydx22Nr8L6LH4z6VAiCsMkVm1grrn0CuPss4O6zgYkNgZ8T0eXceSbwz8uBFe+P+kzaBgl2hId1oznn/vqxfIRnUoWhJdbt8MvRngdBVGHjuHv9xPZaIrqK1zdPOfefXDMa4ZkQRHt5eNUm5/6DL26M8EyIsHh27VjUp0AQhMD3/vA0djjrDvz5mXWN/eNzf3Dvj70e7EkR8eL204ErDgeMADeRn7w5uOfqEEiwIzyMTBWF+zHdpR60BbsREuyI+LJBEOyeWUviCRE+r25yBTtyGRHTiefWjTv3X1w/XuVIolPpSenO/aZcPQRBBMZorohL7nsJhsnw4AsNbpKMC2k7xhoU+4jOoZgD/nEpsOp+4JW/B/u8NXjklWFc8deVYIwF97oRotc+hJhObBp3F3mbp2IaUjW01Lolhx0RY0TxRBTvCCIsXh2edO4PT8a0/yaIEBD7WDFSgOgeCiXTub9uNIclM3siPBuCmN5sFuYYRqOiyKQg8I2vDeiMiNix4Tn3fj5A44KWBEr2GssoAlqi7JD3/sxKnbBwKIuDtp8b3GtHBDnsCA/Dkx0g2PXOsW6nNlU/jiAiRLyWxvPkBiDCZ0SYQIvtjyC6nY3CZuO6Udog6UZEUXY8X4rwTAiCmBTynE80ej2Kgh2FxHYv659174+uCe55NcFvNjVS9mfRVfdSlzjuSbAjPGyc6ADBLtlr3RYmoj0PgqiCOIFpeDJDEE0wlnPb2SYKiSWmEd6coeSw60ZEgWA8R2MqQUTJuGeO2+Cm9IQg2PkILkSXMCkUFBldHdzzFt0IJj/zzqgwPqT07pC6uuNdEIEhVhaMvWCXpwTERHxpafeRIJpA7L8phx0RNE+/PhrL3WrGGDaQw66rMUyGvBASO1GgMZUgomRSuAYbdryKDrsSbbB0LaKxRsxb2AqmARTd9C+YLBfsxLQYU0Wz7O+dCAl2hINpMuSEhh1fwc7OW0IOOyLGiBMYCt8hwqZQMj0L2tj230RHsnE8jyP+9wEc8KP7YrcBMZ4voWBQ2+9m5CITY+SwI4hIEV11DY8JoitKdEsR3YUorIn3g3rOCs/7+mZXsIttAc0GIcGOcMiVvBOiXCGmebdStsPOLAIl2kkn4kmcHXb3P78ej782EvVpEAEit7EpqqJIBMg/Vm5CybTywtz9dLyq+skbIlNFw1OggOh8JqX5KG2CEUS0eNK++K0Xn7kduOUzwMgr3sdLBa+rLighh4gfBVGwC8hJmZdc/j4OTU+0YJcUYKMqsYTDlNThxnbBlxAqg+XHAT0V3bkQRAVayu8RIuvH8jj58n/AZMDvPrcPdlw4EPUpEQEgO05i238THcm/BYH/uXXxSkfB85n1pXXnOhjLFTGzl+YG3YI8P6UcdgQRLWJIbNmmdCkPXHeCdV9LAEdc4P6tIAku5LDrXopCJFxQwqwcXecj2InRgt1SgI0cdoSDvIOZi2vct6YDesa6L3f8BBEDiobpcXjEyQ2wbjQH2yiDv724sfrBRMcwlvfuIsoLXIJohXVCiMkbMcsRx/vX/nQCvSlrH5pCJrsLeQMiTmMqQUxHJqpFkYytde+/8ZT3b3L+cXLYhUKuaOA7v3sK/1hZnuOtbXgcdgEJs/K63yfSTkyhIGsbnQoJdoSDnCNE/j1WOHnsSLAj4sdkPr6LC3G3aSxG50W0hixQxLr/JjoOsYL8+vF4CXbcwdyX1tGftgS70Vx3hMEQFpNSkQkSZAkiWkSRrkwUGXvdvb/uKYAx9/cywY4cdmFwwd3P45cPrMRxl/wtupMohiHYSQ47n+cV57/5LkmPQYId4SDvYObi3Mh5HjsqPEHEELmCXZx2eEaEfA5jtKjtGniImK4qACgklggWsQpr/Bx2Vj/Wk9LRl04AAEanSNDpJsrmp9S/jgIBTQABAABJREFUEUSkiPPaoiGtF0fXuPcLY0Bus/C7HBJLVWLD4N5nA6rK2gqFEEJi5RBYH4edKNJ1Sz7brhfsHnllGF/69b+xIWY7wnFEDqGK9YQoaQt28k4NQcQA2Q1QKMXnWhoRKihSHqDugbs4Z/dZebsoJJYIko3CHOqNsXjNp8Zth11PSkd/hhx23Yjcn3WLa4IgOhVRCCmZDKYpuOhEhx0AjAviEYXEtoXVIzFwLorfrU+uuaYwpJx0pfL3mS9WEZM7lK4X7D70i4dw06Or8YXrHo36VGLPpCTQ5eMs2Olp65aqxNbNeL6Ej17xMC6+98WoT6XrkfM/xmlxsVkMiSXBrmvgbkku2MU2BynRcTDGsEkIiR2dKoKJIU4RM263/T7BYUfu4e5CdtjlY7QJRhDTEVkIKYi/T0p508aFyuJcsEv22U8UA2GpCzHMGIzR4ncbmMMuX/13eCMEyWEXEZOFEi64+znc/p/Xax8MNynmX1+g5Oq1yHVK0QnArQxrkGBXL5f+5SX86Zk38P0/PhPaYuu8O57BTmffgZfWT+/cgrJAF6cBQwyJjVNuvVCY3ASY02Nhx/MRzrEFu4JhotQlO4tEtIznSygJk/+CYcZqE4LP83pSGjJJDQA5TLuNjimKRhDTBHle6xHwZBfdhI/Drne2/Y/ksAuDpO5KPJFFzHlCYgMSZmWHXY0cdoU65sHj+VKsNiH96DjB7pZH1+CCu5/Hp1c8gnWj1e2VsVCXOwi+g9ljT3hzcd7B5IIdOezq5vHXRpz7r28OJ2fERfe8iLFcCT/447OhPH+nwCcyipVOLFaLW9FV19UulPXPAj9YBtz40ajPpC3w75U77ICY5yElOgZe1EFV3D4tTiGnfOOhJ6Ujk7DmL3LEANHZyOIAOewIIlryssNOvEbzo96DxwSHHc9h1zvXuiWHXSiofLCG5YqPBDkk1gxgTlqPw04U7GrMg2//z+vY8aw7cM0/Xmn93EKk4wS7NUJMdi3RQRb0QlOYc6PAFYcDF+7m7ZQ6DL6DOZhNAoh5DjsnJJaSldbLsBDS9Ny64HP/ieJP3KoIthu+mOhLWfmU4uSwE0OLurpK7N8usm6fvDna82gTPB/hrF5XsCOXEREEXBDrSyecPi1ORR14O88mNWTJYdeV8DE0qVnLljw57AgiUsoddj6VYBWrP8bkxvK/9cyybo18MEIO4UFMa7U5KsGuILknffLNNYwcWeejA4gO7Fo57D694hEAwJk3P9H6uYVIxwl2GwXRYdNEdVFAbqBiDpZAWXW/9bPpReCFu8N5jTbAO9+BjJUDJtYhB5olKqIU0nfahawfCzdp+IvrXetzZLs5MYFfSzyfUr5kxMZuLQp2XV10Ypq5b7mo0p9OIJ2whvZYb7oQHQNvW70xzRHH23lad0Ni41SZm2gdvujqS1uCcawjQAhiGiALdr4Ou6Gl1u2UkNOOC3bZme5jZnzGk26AMeZxmUfiiGcMKE54HwvCTSmv+30FO/e91xvhpKlK7YMipPMEO8G5s2miegOU8zNtHA9J3Nn0knt//TPhvEYbKJsQxXmxRw67hmCMeVxvYQhqooA+Ms0Fu3zJey2ZDJ4cUFHSaG6HtZtznZkLTewbYiKWhgkXUHrTOtJ2WKCcqJ0gmmFCEOz67Q290RiJ/bxPyyQ1JySW2n53Ic9PyWFHENFSJtj55bAbWmLdTg2X/y0zw31MzktGtES+ZHqmvZH0l6U8wKTXDeJ7rsdhV2fRCTG1gmGy2Bgr/Og8wU5wyQ3XcMyVCXY1HHlNs2mle3/Dc+G8RhsodwWZ8W28lMOuITZPFT129TAWW2Ixg82T8aoi2G74tdRvX0viY1HTSG6HR18Zxl7f+5NjGe8oxEG80P1FUHgOu7607oSNxaXNEZ2NmyNOcwSTODnsuDiXSlBIbLfC+7JeLthR30YQkSJv+PoWnRjcwroVq8by+ZjosDPiM550A/L4F0l/Keav41FxQQh23GGn6vbrVHfYFYzKWsaYtBaOLHS4DjpPsBNcQhtrCXbSFxFaSOzwKvf+6JpwXqMO/vPa5pYaG+9s++0JERDjSRFViW2IDZK7NAyHnSjYFQxzWockFSQ3ABCfa2mqAcHusvst9/CdT3Vgbk6xSpm4u9uliGGLKTskNi5tjuhsJoSiDnx+EKscdrZ7IJPQkEla5zdZiM/5Ea1TsDcc+1I8Zcv0nV8QRByQc4N5Q2K5YMcddj4hsekBQLFlCHLYBYrsMI+kSA+vEKslgUTGuh+EMMvbSqrP/r1cBxDnvoxVLkIq60Qk2AWI6Awamax+gU9IDjv598CY3ODenxoJ5zVqcOu/V+OInz6AM37zeNPPwSdEPSlXZKiVrDEyHIcdhcTWg5y/IBTBTnrO6RwWy5O9ppMaEpqVFyEubicxN2XJZDCrhOry6pAdiZgrYxoIdq7DLkEOOyJQxJDYbAwFMSckNqEh64TEUtvvJgpSmgnajCCIaCkvOlHFYSeujfO2wy7VV5/z6rFfAz/d05t+igDWPwv871uAv/6k7E/lgl2EDrtENliHHRfoklywK5+LFKuFawvIkZgk2AWIOEms5eCRv4iJsBw/k8JiUNxFaCPfu93KnffHJ9c2/Ry8882mNOcxT9WfOOHksKNdmXpoh+13sySg1xLUuxk+OKQ01a1qF9IO14/ufBbvueAvNVMEcGSrfLU8dqFtcrQDUcyPaCOlnbiVPHUkdasPrydHIUHUYswj2MUv5NQpOpFQnaITUzESFInW4WKAGxIbn/ZHENORikUnGHPFmoFF1u2kj8Mu1SsIORXWJIwBN38C2PAs8OD/BnTmXcLV7wU2vgDc9c2yP8UqJDbZE05IbLKn4nOWzCruTwHZzEKCXUCYJvO4QxoW7MJafIoiXWE8EhFp7WjrTjM+IUrpGnS7WkpsHXZavBx2jDF8/4/P4KJ7XqhovY0S2fYbRsWg4Ump45uMb8cXNnxwSOoqUrbjI4wBkzGG//3zC3hm7Riu/vvLdf2PvNCpdl5iHxvbvqASYt8Qk34iLBhjbtGJlI6kTg47Ijj45D+bdKuwxqmoAz8/KyRWqBLLGPDyg0BuNMrTIwJAzgubK8Y4xzJBTAPkuaOzQSjmFu9fYN0WJ9zHC1yw6wc0O89zJSFHTDmVHmjthLuN0dcq/ikWDruC6LDj33MQIbF2O0r12r+Xtx3ZbFTRYUchseEgN8CpYnUBTv4iZAEvEEqF8oTmEbnsOM1OYlzBTkUi7iFVMSs68fLGSVx874s4745ncft/Xo/6dMrgi/mUvZCXHXdBvgYnNEdrB8AHx5SuhhqeKAr1Yn7PapQ57Kqcl9iThBFGHSpi39Dl+VHyJdOZoPSldaTi3n8THQXvM9JCFdY45SjNldzzy4pVYv/yQ+BXhwB3nx3h2RFBIFeJBchBTATLC2+M43u3P42L730x6lPpCPj1l7Zz5joiSUlIR9I7181Tx1OTcIddsre28yovbLZQYQovqlvUzpOzGT4Ouyg22ByHXcAhsY7DzhbszPL1bEX3pwQVnQgJeYJYa8LIBQMuUkyGkY+Jd0CKCmSG7BNrv2DHHXFA8xNp3qATmuLm3YrrhIiHxMak6IQonDyxZnOEZ+IP75Tm9FtCZxjuCPk545TjqN14HXbhhcQ+t87dLFi1cbLKkRaMsbLvqdo1XhL+FueBzBePwy4e/URY8M0oRQF6koLDzoiPqEJ0LlwQy8S0CutUwV446oIDsGAA95xjHfDPX0Z1akRA5GNcyInoDtZuzuGSv7yEmx+t7FwiXJzKzXbec0cU4fmDFc0yV6QHrd/52tiTw66G80rMRZwnp7SDUQJM4TPbvNrzZzkiJhqHnV10IrQcdpVDYqsWRBGQjVxxKqYl01GCnTxBrDVh5IryrF5LpBgPQ0Dgbrr0oFuiOjcS/OtUgTEGQ3DVNVsNly/cE5rqLPhiGwan2xd/TBbib4y557FmJH7hd9z9Ntu+FsJYbMlJvuO0oGs3eVGws6+lfAhJ0MW8dfXkDCwaDHLEdjUXljjIVxXs1vwb+NF2wL+vrXkObUMs9d7lO7NckO9N6lBVhUJiiUBxBDGhCmucQmKdohNJV1D0bFymKJSq0+FJxHnRE6DDK8W+cDew5tGoz4IQmNVnrSs2jHe3Iz8o+PyCFyp01otcZOOVQbMzrNupYcsdJYY01hJyuOgDlLnIpjVyIbWJ9Z5fYyHYFUMKieXrfqdKbPlzlgl2FbQMeQyJszGhowS7CUlwqzVh5LvCM3qsDiGUHHY5202VHnDVXrGDaQOTBQNiFOxwk8n+eQNPCmF8xVJMc4Q4RSfiIY6tFwS71cO1nU7thldXntNnfW5hLLZyBel6I8EOKV1zw8tDEL/FXISjdYQ5i987dypUF+zc46sKsDecDIy9DtxyWs1zaBti3xATJ25Y8PQPPCE7VYklgkR02MUyJNZTdMIWFMXzU/z+i+gkCkLKljA3wdrCI1cD//c+4P/eD3RCHr6V91sJ/32qMXYT3NwxPFnwRBcQ/vA1Y09SmkvyuRcX7Hj02dQmbwqpZB1VYkWHHeUidZnc4P1dSs0lC3SRFOnhWkjQIbGGXHTCT7Dz9qulCgU05c8pzoX2OkqwazQklg/moQp2/CJJ9QKJaAQ7OQa7WWeTGxKrIhH3kCotbg47VxyIo8OO235n91kTkjB2pmWBfDpX6RNDYrlgV2nAaAUxr1w9O0N80FYUN4yh2kAuDmb5ahNYMTFwHDBKABPeV5dXkxYLTgBwHHYdETK27ingD/9Nk/E48vefA3/6NjKTVvX5dEJ1Q2Jr5BBuFyXDRMm2Dad0N4edZ4OkE0QRoirihnI6xEJObeH5O63byQ1tj8hpihtOBu78OnDf/0R9JqEylE1CVazuotlIpemCaTKn33VCYh2Hnb0G0rlgZzvsJje5Ya16BtB0ColtlsmN3t/zXsFOFqwi2dxwHHYBV4ktE+zKn5O3RcXerCtVKAYpr39CqXUQEB0l2HEhii9GcrUEO3swn+kIdiGIT46C3BuZw2487+3ock1OYvgFntTEohMxnejWKgXeZkYm3PPYOJGPXfUynk+O7yAWDRZ4uPOU5LCLkwOj3fBBwCrgEl7FZdFVNzpVrNnuHCFRCHuv6rATBvm63VpTI/UdFyay87bLi06M2ZMM7pp0c9h1wIL24r2Bhy4G/nJe1GdCyDz0c+D+H6EvbxVSSiekHHExQFyYJHXVOT8dwsSbdcB1QFRFHLu4w65jQ2LFNcJo/IqUeRh/wxUHnvtjtOcSMpqqYEaPNUdeX2cRr+mKOLfIpqw+15nj8qITCTsSSgyJFfPXAXU47Cgk1hf5syh4f683JDRUCmLRiSCrxNpjeyJr3ZqVQ2L5Bp5h+r9/Pq702aIzCXYB4YgOXBAoGlUXqHk5JDYMx48j2PVEJtjJoXBNO+z8QmLjuuDjF7/PhRoFYtsqGix2Fz0Xz2b0Jp3Hgp7s8nDLmSTYeRx2umpfSxV2eFpBdNiVzPKCEtXOq1bYJGPMs/tUUbAzpdeUcmlEguy8nTYhsVa/2DE57MbWuvfXPxPdeRD+2CFNzHY5pGMYEisuRBKagpSuQlGANIQFIAl2HU/BFmYTmljIqUO/VzGcbXRNdOdRD2sfd++PrYvuPNrErF7KY1cPomMp44gi9mPcFcdTF4khsVxoStkVPhsJiZVcZNMaWWeQfpfnftE47EIqOsHX/TzkWhIBDZM5pnq+gSc7Djl8DOFrYwqJDQhHELBdQobJqqrGuWIbvgg/wa7YZoedJNg1G6vuFxIbe8EuJg47WfyKm52eL66GsgnHIhx0Hjs5BD0uDowocMRv8VoKYXEh5rADaofFirn1nLDJCtd4yfQWqKgo/uSkqsixcNhNeX+PST8RBPc8+waO+dlfcft/XGcGD4nt67QcduJiVU6iTEQPnxDbIU5psUpsTNxNYhtPaioURUE2oSEN4ZqXNxWIjqMobDaldR4S26HfK6+WCQCjqysfFwdEB+DEG12fumAwa60t4px8Pg6IOf54iHpJFuwSPiGxBdlhV2MtJwpRXb7x2hBFKVd6WUhsDHLY8XaQ7BG+5yAEO8lhJz1n0adtGpVCYtuROi0gOkqw4x/sUI/rEqomCvAGGmpILN8tSPZF5rCTJ87NOqd4I09oCpJ2GF9sF3wxC4mV3QZxE+z4dZJNug6JXCG477ZkmI5INVNwwDbFTZ8AfnUo8OrDQZ1e2+F9VSqhIaFa11KpgiW7FeT8lbUmmQVHsKsdEiu7FypujsiCnfx7FMgOu5jkugyCU3/1MB59ZQTf/6PrSOOOXm7r5w6U2PbfHHHhGrc8iISTg0ixQ8wzCc3NHxaThP/ivEWxd6MySQ1pRbjmjXzXJ8zvdgqGu6HsOOxi0gYbZkJw2MV9o0LOlTXySjTn0Sb6bZf6KAl2VfGkIrA3CB1RRC46keUOu2E3D12y3pBYYfO1i+ZxLVPmsPMKdvJ8PRdFX8lDYj0OuyBCYu3nEItOCNGW4nvPyGKyfIrSunWMBLtgyAsxyZpaW1DiC86hrO34KRoVVdamiUFIrCzQNXthikl9w6xsGQhqgGp9AMRdsOPh5JmE7nRgQTokxLyJLRedWP0v4OW/xua7bQaPw865loIPiZUFu1qbEmLYe6qWYCe1j8oOu5Hqv0dBl+awE/uVlzdOYoOdZ4e3A578ORX3/psjLganhqk4QNywcxBpBg+JFSp0xsTdVBT6Wk4mqXlDYoG2Rz4QweLOTxWkOtlhV5j0OsALMQ/zk6tRxiHlRYj0Z2zBLkeCXTX4BnRCU6DLeZqdkFi5SuywEBJbr2AnOMmmgWA3kS/hvufW145uk3UGKaeduDkPhGMYqIkYEhvkmt1x2NntC8zjohejmXhIbKWqz2Wp00iwCwb+JSSE/EvVcljw3TceQguEkMdOFOycKrHtHYDlz6BZh51fQvpKcd+RE7OQWO5g020heWPMBDvRYZcOQ7ATnmuoVUcrd93wQb4DEQdLPpmpNGC0guwwrnXt8z7RW1imToddvSGxJNiFxjOve8ORnrZ/d4tOdFgOO3ExaJbavtlF1MCeEKt2KFI6oTliSVzaVkGYF3KyCR0ZWbArSCFEREfBq6zrqigax6MNNoRc6TLufZ7ogga87sAuhDvs5M1Qwot4PSYqOux4Djuh6AR3lPL5fc0qsUK/beS7flPv/93wGE6+/B/45QMrqx8oh8QW/ENie+xN3FIUa3nfohNBVInlOex6hMfc5y06+U4VZ01esUqsExJr6UShRGIGREcJdqJrxU06Wzsktj+tO1/aZNBfBr9IPA679k4MZSdM8w47N6lvrcV85PBdmWaLTjx3B/DqPwI7ncmiNbgvGrIWOMMxE+x4eGpPKpwqf/y5LAeGvaBrRqAyTVfw4ZWlOhCxSmyYBVxk0bVWIviCYZ9XwmeSJdF0SGwscthJ11+X7My+NuLNzffCG9b44xadkKrExrX/5sjhVnEPD5tu6Fywc0NikzETS8RQSY6/w44Eu06Gj5+6psQuLLshajhjYofcR8uOuy6D54GlkNjqiNejJosiXLDTbLMMF+cmN7nzw8ygfUwNh11ZAbF4ra2C5g9PWIW4agp2XGfomWPdluWws74LHlEVST76YkghsXLRCfExCG1TdYv+VVrnyCGxE4USzBAKBAZBZwl2QtJZt6x77aITYqLkwKt3Og673shCYsscds0WnejEKrHNdN6vPgxccxzwy4OAtU8EcjpcsFo0ZCXBjF1IrC1UZ5JuSGyQVWL5c2USWl1iekXym92KfpnOFew8VWKdcIHgBwEu2PFEyXVXidVUZxOjWMEqL39/FRfochLqOOSwk/uFmDhxW4WHwHK4YDcqFZ0IszJxoMjujTi4MwkX2yGRMK0FWEqYe5VMFopruFF4vyqGxKYTKjKKtNAzyTHTyfAFl+iwa3auGyk1ck/FDi7Y9S2wbqdNSCz1F9Xg4lxCmEs64wGff+m2SMM336c2uWN8etC6rRUqKT/eJZuvfoii0kwhV78vvN/omWXdSoXW+FzfCQmNYi4oRiAGWSWW56NNZoXH3Dl+QchrWxauLSEXnWCshfzrIdORgp01aazu4mGMeVwuPLdP4PHJTjWctKv2yhUKQ6Y8h13rVWKTHVMltonvc1jYuQgo0Tl3Ni0ctNpAnAQ7sSBENiSHBBeKrJCpFhJC8wV8stcd7DuQvCDYcedHGJb0nN3uZmTryxvYyHnJ319Ft1ZR6u/kkJ8okJ23XVJdbMOY1a/Msiufv7LJ2sHkxUYG7cVGIsQw7ECRF6txcGcSLnYVtpTtVkvqbnQDEI8cieLmCCel+zjsutyZ0e2Ijp6W5hhRU+awi7lgx893xnLrttsFO3LY1YXrYnJFEddhZ/e1jsPOFuyMglsZ3gmJtT7vipW8p5Fgt1HYkE3ZxoqKcPdadqb9uzcNDB+be6IU7DwOuwDTWPH5vZYEFPtz8oTEunMC7v6sGElkHzuQScA+NLZ57DpLsBOrmPoN2OPrgdf+CcBqnPz7SemaE8cd+BfBrb96BtDtzqnNHUp5DrsWi05oqrPgi8OE3JdWEliKYVcBiAuMMUew4iGxcRLsxN2CTFJznAhBfre8zWXEHEfNPL+T36Jz3XWAuLmgOcJYmCGxbqGPGjnsfJ1/Leawk0PNZAEvCmQhv0smedxht/OiQQDAajtEdvOkNYEZsAU73WlzMXfYyekjKCQ2XuiWw46LXwlN9TjZ4hByLVaJ5aR01UewowV4J+M4elTVDYntCoddzHPY8fF8cLF12+U57HgeWCo6UZ2SkEJJk8MO+QYpXxMne9w126aXrFseEqtywa7C2lyey3XJ5qsfE8L8fcNYjfdZkAS7Wg67KNbyfjnsgnC687Fc1X1DbcW2WTuHnZsmiOtEgUdiBkRnCXY+IbGeAfvivYFfHAi89i/PYjOVUJEN64sQrb/25LYs4XnIyI46OaddvYiqtN4pOexaFuxazx+SL5lOHtSFtmAXp6IT3IWlKnZONUfsDjCHXVAOO0ewGwzozKKh4HGyVQ89beU1+CDEBbtaVm7RpVxr50m+9nn+uzJkgS4OuaLKHHbdMfl2BLvFgwCA1cNTYIy5DjvbaelOUmLaf3Nkh10cwqkJFztqIC047HTN7TvikMdOTOXBSSU0JCD1VxQS29E4Se4Fh12zm9ORIvd5hZjnsOPrmYFF1m2XO+x6UsHneO5G+NxCFxL7OxuEjsPOXqcpihsWywU7JyS2lmA3fRx2oqGopumDV2Dln6vksHOKTiQjLDrhVIntqf09NwJ3Y6oJX+eemNdWrxFJJJorQovEDIjOEuwcB5jmXyWKDyTP3+kRI5Kait5Ug5Ux//Rt4I4zax/nOOzSkTvseB6rZvJ6mCbzVFZJhhjGFwj8IpXKOdeFKNjJ+beaQBzYF9ghscOTMRLshFyOiuJOdoN02PHPIJPU/MX0euG7zbzke4eSF4Qxx+1UCvZaEvuymb31OexcIVFDQnVzUfkhC4wVxXu+s8d3+uJQjbEsh113TPL4JG7Hhf1QFaudrR/PY2TK67ALMww7ULi4yze74u42mW7Y30tGKUBRXCE4TiGJYioPTkpXoSlSX0ghsR1NURAIkiHMYdoG7/OS9hwn7iGxjmDHHXbdLdjxfOdzcy8BP9sbeOrWiM8onhSdKrFuSKzB54yGJNgBbtQMz1HNhaYqQs6jrwzjiVclR2cXC3Zi0bipogFWrSIu/xx4aHHJX7DjDrugDQN1wTfzk9mABTseEqsLzj2h6ESpXEw2KubqdtdqXLAbj2n+ys4S7DwOO83zmGdnXlE9nYmqKsgmuXJah4gwNQzc/yPgbz+tbf8WdxLsimrtDgnjDjtejrzQhDAgXswJvXZC+shxBDs0PhEXE53nW3d08EmjpiqY3WeJtpvG47M44AIuDyMJo4Jk3nkN99psyn3h5ITMVD8uxjDGPK6PREhuJ37da6riXPs1BTsh7L1WSKwhiT01c9g5uTRiGBLbTK7LGDJmTyRm9qQwt98SU55bO+64JPmmTSKEsPdQ4AIdr3QW9wTs0w0hh11CU6EokmAXg5DEouEv2OmQ2n6XuGynI6bJnCgGXQ0nSqBt8D6vd47397hSlB123R0Sy9eK/y/3U+CNp4DrPxzxGXlZuzmHB1+M/juoGnbohMSKgt2Q9wn65lu3it1v+xgvjvnZg5jMSRFrXbL56seElIO6qoOYC3T8cy36h8RmnZDYNm/emoZ7joksoNq55gINiU34pscSC1GVVTCWENMEUUhsgLg7qUp54vzNr7kH5jZ7wjsBN/HiZI2k7ACAkVfd+7VCJmPksOPqcDO5ssRcR8k6bKSRI+7cNCrYBeywE9slr+wzli/FJpyYCzt8kRWGYOc47DxVYpsR7HiS0s4V7ESRRCzuEHQOO/Ez57totUJiuSOmnqITssBY8fssS34bgwWIHBLbJeFwPBF2fybh5Mt8co216ZDU3dxOescUnZAXryTYxYqEm8Mu5RHEWtiUCRjer6Z07/lpFBLbNYgbx7qmIKm1kCc3asqqO8ZYgGDMddAPbmHdFsbj4aIPCS5wzGTxzKe61/f+hBMvewiPvzYS6XmIjleew65UFhKbcv+hf4Hw34o75ldwXjlreMj5iONjhgiaSclQVDUikAvpPLS4JBedsL6LrBMS2+a+UkyNkxAddi1usjAmOOwSvrnxxLZZa53DnXcJTXFDYuvRiSKgowQ7cWJWtsPLK88AwOhrzkSSf1nZVAMOu5FX3Pu1ihKIyTUjzmHXm25BsBMm3gmh6ERsF3yq6LBr8OISv9MActiJrqX+dMJR9OMSFiuGxALuwiZQwc4nh51hssbbj+Owy1Y/LsZ48meKIbEBi9+TQhgyn2TmajrsXPG2lotWPt/OctjZ156zexvPAbgRDJNhzN7560/rTkXqx1+zBDteKRgQqsRGURmsERzBbq73dyIe2BtjSZQ8OeLCqDTeLL4hsQm1PIcdhcR2LOJiKyE67GLQ/hqG93EVksXHClFM7J3jbpRPRu/wCgsucMRx5Hx5ozs+PrO28bWLYTKsr1XMoE74Namp7nqxYtEJABha6t7vme0KLRWEHB5NkCgT7Nq7vm4nslBUVbBzHHaD1q007+Zrejckts0t2hH1FcuAEVRIrNhOVF1w7rmPG0LbrOWwE9sxz185Xo9OFAEdJdh5QmJ5lShuGRVFmKnhsjCJxhx2omBXy2EndEyJtPexNsEnLX2p5pNLFgwTOko4XHsI2tRG6PaOSdsv8npRVd9yznUhdmwBVIkV84KpqoIhOyxtY0zCYrmo7TjstOAnu17Bzi1H3vBrdEFIrChsiRWXA3fYFQWHXYL3b/XmsFOh8UlWnQ67in0B3+mLlWBn9/Nc+O0CwU7Mq9GXTmDRkPXe/vWy5QSYO5B2/u7033F1SHP4LizfbY97Pqfphr2oSsDwFnWIUUhsQQh/4aR0tdxhRyGxHYs4pxWLTsQliqEh+PjIc3oZBSCuqWdEcUTPAFnbFdjFYbF889NkbtXpuLi6nl/njo+aolQ50p/PXfsI9jj3bjyxuvVUQHwzPqEqgihit2PHYScYK2Ysc+/3zXXvVxByxisJdl288TIphWJOVdMr5JBYZnjGOC6e8rVB+x12vOBE1io6EphgJ4zjWsJ9XrFKrOm2zVo57Bw3nqqgN2W1V8phFwBiXqiyxPniIrGYc+209qLUyWFXj2A3JeQ4qxUyycU5TXTYTQHVkkUGjOywayZMoFAy8VHtD/hp4ifAimM7I6SK7/bJ4W+1EAXVAMQFua0N2U6XuDrswkjYzF8jk9A8C7vGBTseEtu5DjsxRFpRaluym0UUYuv9TsXcDjWLTkjnW7EvkENi4+CS4n0C75NbteHHgNGc9Z7SCev75hWp145aE7e5fe5udkf036YpCHbcYUeCXaywx1hdKZU52ICIHE6mCfzlPOCFuwG4ToKEFBJLOey6B3HzSFeVUNJ6tA3ZGSM+Fjec81KsxXFP9wt2XOBIKMJaMSaFNkTHVTNhe7f/Zy0A4Kq/rWr5XPgGrpjY35njGj4hsbO2ce/P3Nq9XyG32Vje6q91eeMlrtdKAExIG+5ThTpy2PGQWMCznuVClCvYReSwS9pruaBy2InjuJrwFQKdGgaaKyZX2rw2hHbMi5NSldgAEMNc3aSzdoMWcyoUp1yHHc9h53wRdSzcxA6hlgNLdNhx+y8z2+ro4JOWnpZy2Jk4VrvP+mXNI0JIbIwdGj7lnOtCDEEIwA0pupYAOIUn1o3GY2DJOe436/zKCrYE+BqZpAZNVZz20/BrdIHDTkzGK94GnW+nahGeSv/jKXdeo+iEKQt2lRx2cQyJtfsE3o4aFfVjyGaev84uMMJz2HHmCQ47RySOq0Ma8OY4oRx28cQW7BJSSKyTwy6KKrFP3gT8+Rzg/94HGCWhT3MdJ74Ouy7oA6YrvB/TVGsTrLOrxPostOMqQojzMUVxBbsuDolVVQWZhIYshO+kGI+cfaJg12hifHFuyJ1ErVAS55Ly5i8X7MSiEwt3B2Yst+7v8kH38RohsUkunCZ77ReOcc7HFpEjAKuHxNqfQ7ofgD32CXNvPn/n6762F5CUzRdB5bATtRVNKDohPF5yXHNurm55PQNYBQLdAqVUdCJQikKusLKQDLFDLU46lVKdHHZOldg6vgixQ6gWEsuYfw47oK0DMG9wPOy3GcGuYJgoQnd+1xWe3yrGCz6tvDpMXRSF7yYEwW6BnVtqzUgMhAuIRSe8DrtAQ2IL3kq0blLyBjvnLig6wQdGvrMTltupKAiD9ToOXDdKbecfP1+9VpXbkiTYlaaiD/EpE+ziOQA3AnfY9dlOap7DjsOrxgKCSBxnB4oo7PKFYBzcmYSLPcYmYZSFnAIRCSYr/+Lef/XvTp/mKTqRUKErFBLbLRSlsaijQ2L5eJnscRexcRXsHEOCPbY4IbHxcJyFRU9KQxrCuiIqwe7Vh4Gf7wu8ZJkpcqLDrkFRYbWwHlEbj6Yto+QIHYozx3VEETHyzHlRFTjl98AHbwS2fpfweJ0hsV00l6uEbCiqmMKLMaHgZcYb3WfD1wepKg67tZtzOPQn9+PqKo7Lf728Cd/7w9N4cX2Dm6l8LpfssW4DC4kV/l9RfXPYlXwcdn6b1+JDuqo4UYrksAsAURgpEx3EyX8p5ykEALgOu1o5nsqeK1cl1t8sWW46oFywK7ZTsLPOwa0G07jIViwxGEJz6DOG7eeK8YSIh8Q27LATRLoASoSLriXAXUivHonHJCxX4iGx4VWJlV18TYuCXVB0QnbYJUNyO3n6Q56XsGZIrNsv6jWSsfIB37HUV8xhJwl2QPSJtM3uE+z4ZK7XdtgtHMp4XEVbzel17tcUWeMA73u1JJDqs+5TDrt4ITjsxJBTN8IhglDzjS+49zetLBt/AV4lVg6JjUeKCqJxKo2pnSnY2f1eIh1Zobq64eM4P8+e2dZtF4fEAkBPAkiKgn9UUQO/+Qiw9nHgqiMBuBvjQJ3RYgJixM+midb7QrcSpyqEHdrXo1/RCcCqFCuKdUBlwc4WTXhILONrgi7eeJEFulyl8VVcwybSbv58QXfgOdvSwvydSam6fvnAS3jq9VF849YnK57TR6/8Jy657yV889Yn6n0b9rlUctgFFBKrJirmxuNrFV0V1jk+ayPR3KQLVWLJYRcAfgtU50soCjvzxcmyvCYN5bCr12EnHqelrMbDdxTaOADzCSsXJZvKYWeYGFLc99pjjACIedJyNZ4hsTy31OqYOOzyRa/7LRlCiKYjCureSrQNh0x1g8NOcgPozYYH1/k6SU+KgOqTONGVV5YoWII/znfoKvYFfjl5og6L5X2CzgW7zs9h5xYZcUPbd1o44Px9R+F+kHkTGWP43h+exs2Pvtbyc3kQd+ET9i5sTEKPCBuVF50oIeXjsIskh93Y6+79iTcqCHY+VWK7QLSfrjghTvZY2tkhsYIIppcvtGMFPy8uCPTYm3JdLtj161K7impcGl/n+bWVkFjxfzcGINi5IrrihMS6VWLt+ZdWR+htxRx2XoedI9hVS20wsQF45e91nH08KcthV1GwE4vBCP2IYEDh309a2GiTw0JF/c5PHCwZJkYmrc/70VdGap2+F66d8M3YoItOlFUZFgQ7IU2GE+HkYzgQPw9dVdGTJMEuMETXnJsXyv7APUUnpsoKAfAvYrKuHHbCc1UTg0Sxh+8kODtm7Yuz5+81k2w+h12hZKIX7vtOmZNNP1fb0JroAEzTu9MehGAnLRiWzbIWn881UXY9DPKSmBaGO6Jgh77y5266imA3OOxMrxuAC3dmwIVovDns6lvAiG21ZkislAOjUpUlpyKYOHGIOrTRcdjxiUzn78ryimF88wkA3rvbIgDADgv6sUCsEhtgZeJHXhnGJfe9hC/++rFgxwMxz00i5k6T6QqvEqtUyGEXiWAnLGLH16Nopz+Rq9hSldjuwXVMSIJdJzvs9E5y2NkbX9xh18U57ACgT5f6iqgE1bS7CQfGvEUnGhQVcoIYFERBPHdj2idawy8kthIVcpvxkNikLdiZ9Wy+XnE4cPnBwAt/quMdxI8pSbCrGBHI+wtFtT4/Hm0mVDPm30XGTpUlPsbRhNjoF94oj25YN+auj3NFo3Z/mx8DHr/e+v7LBLvy0NWmMOx2r8qCnXvNcnOBpirQZDFZQK4+znPYxTUkVq99SHwoCgvURJnDTgqJLdnqvBQS27DDrloYBVezVd1tjHoKyKO9OexKcg67JkJiDRMZuO87Y04C6I13SJV9oT72ygZsNbfkXGxVkb+XAEJi+cDFRZMdFvRDVazqjWs35zzJ4KOgvOhE8LvTjnikeQtbNB0Sq0f7mbWCIbkBtBrVWJtFTLZedw47odI2A/M8JlOSQ2JrOez0lCW0lnLxcdg5u7LxHIAbgU/mxAnYSXstwcE7zMNQNgFFcSdftSoANwIvdgEAT60Zxc6LB1t+TgBShXV7Mk4Ou3hhLwSSKJUVdQAiEEzyY95oiok3UNCt68JbxVYrry4YRkjsxhetMK8OdoR3AiUhMTjQ6SGxwhwn7hsVYvguMG1y2PVqUt8R1bgkzoML4x7RrRWHXcVQywbwVOLUpGgNv6ITlajgvOLhodxhZ2hpS7CotvGy/mnr9pGrgK0OrP3aMYMLRYpiud8q9m9i/jpFcQ1DwnrWLTrhzheLhun5XXRajk6Vf66rh915vMmA14YnsXx2b9lxDrd+FnjqFmDNv928xKE57HTvrSAEGoJpolp6GLn6eJ+Twy6eETmd6bDTVWfy6Cw2JUeHWbAatCvY2Q67enLYiYNnNUHHuWiETpUr3Q1WJDNbWFjJOeyacUGUinlPzoaUwR12cQ6Jtd7v929/Ahf+6fn6/keeGAUZEisUOHnT/H4AwAd/8Xc8vGpTy6/RCk7RiYTXYRfkZFe8Nq3XatJhZwi7zx1K0fC6Afit3w5PK7gOO63unIFFQeSrJerwzRA+wFesMsUnZ1rSFciKETvsurDoxKQTEqt5Hp/dl4KueYdyPcAq3xvG3UndM2trVE1vBMdpknS/p7iGhk1XKlSJTTbroG6VMW+IGMbfcB12ZVVipf4q6D7gmduB/90N+Pk+lHsxZBw3jxQSG4nDs1U6KYedvIHq5LDbGM35tIleVXbYlW9APrt2DPc++0a4J5IXcqgXJpETUsw02va9gl3r1w3fmE6oqjuX5PMNcU5YiwpCTq5oQIUJTbGe09DqCInljK2tfUwM4frEUNb63Cqu0YrCJjkgOOzc9awTeSfMF+X5oJjL0E8AXjvq7ZfWjdZYLz91i3X794uAgj0mBi7YcYedXvF5nfyKQkEUv7mwXH2cqsQGSF4QRrgQV/QLiQVgFizBKenksLMddvV8EeKioWpILN9FEGy/WuN51S5/YCW2+8Yf8d3bn677f0QKjmDXfJVYI+ddYKdM62KLc9EJpljvV4eBe+odOMMQ7KSEyADwiXdY5ctfXD+Bj17xsFPhMQr44MxzGYSxOy3n8WvageEM9K2XnY8KOUG2kysuYPFbFN+4o7F2lVi+uFWrVk8C3ArRfMA3KjrsBJE1yQW7mBSd6KYcdvZkLpvUahwp5E00zLJEw42yXgiLGMsFOJExBIcdF+yMfFd8V12D3Q/rMJDU3XYXWUjslLT5NTXscQ1zUroavsPuoYut240vAC92ZghWpyCnmehowa6TctjJpgQnh113O+x6tOqC3csbJ3DwBX/BKb96OLxc1abpLXpYnPCIbo2u87xiX+tjrBOmLlTiLMthp9aTw66SYGe6FWIBlLQa6U08uecD3FhsIzwCcDBjfW4Vv+NSBcFOGOP4d5HUVfDgC3nTXXTY+ZmZZNfd+vEq62U5DU7O/g6StiMvcMGuWg473jbVqoYJUbADgF47EpMEuwAo+ITEOmF9kmXZtDtYp0qs7T7Ll8zaIpTHYVdlkseP0/wEu/onh9/7w9MoGCYu/ctLdf+PCL+oedhvM644U7rYkrbDLugwviApwnq/Gsz6LayykMAMNya+SWSxCgCO2mUhfnXqHgCA0VwJ/2yny65U8AxqssPOEbsD/G65aNlySGypgZ25mFKUQmLDdtilxBx2NT5vMYedu/NUKSSWF52o0l5Mw7qGADskljulog6Jta9px2HX+fmr/EJiK5EUNg9abXehCXbihpcYUhhXt8l0RHTYeUJOmywq1CpTI97fC+NOZezaVWID7AMYA177l/v7qgeCe26ijJLkWnc3qDpQ3O+kHHZOTmEph11pKvo8tSHSU+aw864vH3jBzeG3dnNI350chluc8gh2jW6G5wJ22InXZFlify6eNFR0wnst54qGv2BXSfCZFNZYakdl+3LgOfYHstbnVqi0ljcksxC/9XHYaapS7oB0Xs/9LP3ShclGkzdGq7T1SWmNO/KKdRt0Djv+//Z7qlZ0Qhdy2PmtX5ziFPa4Iuawa3WjOww6SrATqyIm5MWmvEC0HXb8uGzKXeRM1orfrzeHnTPwioJdudJdi1bDTvn/85BYw2SNh9gWvINDsjQRyLmFScG0k/rDwNrRXH07Tk44Qo/7WIt57PwEOwB457Zz8P63WEnh//XycEuvUTebXwN+sBz40bbAyKsAhKITtmBXS6hphkoOu4YXdI1Y6WOKnG+nVjXWZikKC9V6q+Y5/6PXX3TCzWHn89yeStlCSGzUk3nejhI1JnkdRKWQWD/EENlWN13EsIlQHHa6kMMOiF7sJVzsfjillCDqxG4e1DYLJrkR67ZnjnWbH3dyGyckQVHnKT6C2tkX2fyqN+x//bPBPTdRBh87NUew6+AqsSVBBOuUHHZcWEz2ugaFLnbZ9ahSXyF9P+PCOBiaG8dnTZtrwWEnFjQIIoed607yyRPmuKBqz1Uq9c/5kulxSRdrCnZCmHaHziG4aFYzJFZeJzm6gyuw8Y3aamGhOWHDw68gpzzfEzdvyxDdoADwxlPWbeAhsdK4zm8F443H/Wm7C/00Efc4azzptQW7ksli6d7uGMGuZJjgn7fosHMEJUl0YUUu2LlhgLxTqVkptt4qsYafYNd4SKxIo6quYTLnwuwRqgeWnr8L+Pm+wFO/re+JpJxTCSP+IbF503YwwYBhMrxRrTPh8O823S881ppgV/TZ4efssMB6nZfWt0nAePlBoDBmDV4vPwigvOhELaGmGeQqsc3kOLrsLy/h9WHbRt3RIbFuqCrgCqRBO+zywgYGX8AYJqt6zYphtLw/rJSbzikLzwU7v/MX+11edAKIfsJUFhJb8taw70AaCokVqn9VmtibwthR9XWFyf14PkCXklh0QlXdhWDUbYdwEfrhtOa2lWSzGzKtwhcFAwut28J47ZBY3icFGRK7/jnv7yMvB/fcRBlymonuqBKbamqDv62IBTIAK8H9NMhjl1Gk70Nyu00I4tdYWOlu5DzAxQmP0NZo2xfH8Xyp9VQZYnE1vSyHXRAhsQYSdh9uMgUllItSHjyCXecVr2KMOWGpNUNiHcFOctgJ83FRjKo01xedln4OO962+dqxIcFus2UYCS2HnZ0Sy9dhJ6RQKAvXFpCd26KGEsew2I4R7MSdNN+QWOkiNkrW7wl7YFcUxc1jV6tSrCjgVBNzAnLYiUzUUxRDQLygxVAp7b7vA2sfB67/UF2ClCJ1cAnbYRfnkFjRYQcAI/WUKue5QpI97gXfomAnhibKLBy0BIPXhtu0CN200r0/vAoAkOMOO10OiQ2x6EQTOWYu+cuL0Bm30neuw65oyg67cKrE8nx0CV31LFaruQ6KQuhybYedN2mt73HOtaNYA6cTEhvxhEkOiQUA1oGLOwE3JLZ2uIe4eeD3vTHGcNwlf8O7zr+vpqguLhKCddhJleTi7jaZjgiCXUYVilJFlsNuxLodsJzrKOVQsud6ybKQWOt8mZMfMcCF9ehr1u28N1u3I6+2nFqDqExZ0Qn7uzZZvDeVfXFy2GVa3uAPHT5f5n0zMC3y2GUV6fuQIpDEXOjjQY6JVV4ThUlPiGSj0U9Tkquu1b67JDi4eHSiYTJrY9Sp5NmCYFcynT68CM1JgVRR8BHnnFFHeDRBvmQ6ohIPia2cw07K9e1TdEL8firN9cW5nV9+/9Ep67Gt5lh56KqaYmTBjpMetG6DEux4Ch61smBX9AmJ9Vt/laT0RaqqNFbvoM0EIti9uH4cl/3lJacMcxiIuwliSKzToCXRhdm/i5M4p1JsTYddvUUnBIcAx8eaWg3ZmlyX6CQgXtA8h10WOWhr/uketObfNZ9HFux0ezHVTAGLdiHmsAOAkck6PnOxHLbPrkRT5yE5qkQWDlmLhdAS08oMC4Kdvevv5rCzBU752gkAuVJuowu6iXwJG8YLTs6K0WL5Z9kplKTFRWg57OxwtKSmevq5ajuvBSF8rGbRCXtw5xsBviG94qaFolhCOBC9YOc47ISFRlwXRXXSSEisVfXKuu8nzI/lS/jny8NYuWEC/35lpOpz5TwOuyBz2Enjpx4TsZdwETZOUh7BLqIqsTwktn+R85BuO1E8DruECp3nsOPtK8hiJrwK4YJdrc+IGcDo6uCevxqv/B2448yOXJQ2ixjeBaDuDarYIed87TSHHeA67CY3lB/fJWRkwU76fsTFfKCbWCKy07w46RGny+bWwy8D/7zcFXMkcpIZpFV3tCfkUuUCOvNujNaTS65CbrN80XDSGhjQUGJcFawwjxM/rw6cQ4hFHwYzDYbEOmtZ63HGmG9IrLzmy3scdn4hsdZnvXwWF+yqbKbysVmm1+4vAsthV7tKrOic40sj08dRKqcvAtyw2K512P3gj8/g3Nufxqm/ejiIp/OFD8qKYidR1CuUkbZh9m6nKKJw5bTmF1F3DjupUgvQ8I6ZnNSxLtFJQNxlSesaVAWYr0hW9ddqfy9KyTs4aKb1GQRd2TJIinYHzjv14XrETvE780nU2QwFR6Apv5wWDVrhOJsmCp4cEqFh562z7ltJP/M8JJY77CokIG0F2WXoJiWv7z2/uN4KweaC3cqR+HWW9VKxSmxIDrukrkLXVPAoyGoiqRi+3WjRCf+QWCn5rV/RiefvAu79H6vqWbvgg7foDOjwPHZT9oZYPSGxQPXrfJ2QKPvljdUnt+LO/GigRSe42MsddrztkMMuNggLroyPYNf2kETusOuZ5SxWNDsawFt0QnXcGSbvm1iA4+/oGuu2fyEwsNi6366w2MsPBv72U+DhX7bn9WJASXKtewS7TgqLlXO+at6Fduxwcj4LTvXsLOu2ix12KUUa56T1nCckNrQcdnJI7KRHcCnbcL/8YOB3XwT+fpHv0+WkzRX590YRc9jxrrdkMu9nVZdgV9lhx6OnSlBrO+zkdXuHOZ65CJxOqE4IasXNCEN22HnXsuJcXVdVN2RZeNwwmef5J/0cdvZ8b8vZlmDXUEgsp3eudRtYSKx9zgovOlEuBIrhwKpSu0qsLuhEvU7hifgVNApEsLvjyXUAgIdWhlcJU3TwKIpb9cTptHgDtsMcucNO93PY1XICioNntYFUXqwCDe+YyWWTN081Kti51k9VVaBrKuYqUoGDTbWrz6rSjoTKBbt2LrIbhIfEcofdcCMOu0SmrJNrFkegUctdYf0Z3VncbKhWEjsopoTv3q7aU6noRJAFRQpS4m/HgVHn7vfrtoDABbu14/HrLOvFqRKrhu2w83c1VlvAuPme3F3RSufFBzMu9DLmc6zskvIrOrHi/cC93wMevaqOdxUQfFKgd5Fgxx129Qp2VZy0a4VqXy/YYnklxDwngebrMeS2Qw672KEoKCnWoiCletOSABGExBbGrNtUv5UAH4DuCHbu+JvU3Bx2TLXnZEFe/9xh1zcPGFpq3R9ug2AnLkK5aDgNMBxxwB1TuYO4owQ7cV2gJTsgJJY77IQ1Tq9d8GX09fafT5soF+yqOexC+u58QmJLnpBYqd2P2d/Hs3/0fTrZMNCyw85wxQ6PKGIKn0cLIbH5ouGs7UrQUGRcmKnweZdkR2JnOZC5w64nqbspvyo67HgECY9O8OoO4jxd1xTfzXnZHe/nsOPtfPlsK3JmeLJY+Zyc/LKLvY9zR27QOez48/E2JrQLMcqJjxn+DjtvMSPA1YkCzdccEIEIdvXu+LeCXIWST84chZjbgO1JHG/Qooji5rCrIgaYptfSWzUklru1hEWhMwDXKdhJjoXJBl1YslCS1FTMgySc1iHYyeerOSGx8XfYcZFnZKKBHHZ6uqyTaxa50oyIoiiY2WO9zsZ6zq9VRMHOtihXKjoRaEhsWQ47OyS2zknButEcAIak7ZbcmItvu6tFRYddwKE7BSkUu55FdFE4N95cjQrJh0tSSKz1/9Jzy4V35KITYv+58i+V30zQ8N02caERZEhcBPCxoZ6QWMDtj/z68NcFh93mGhsd4kQ/0CIDcg5YLthRDrtYUVKsCWw6Djns+EZAsgdIWXM9XtFedF0pioKEYp2b6Qh2QYbE2ovj/gXA0BLrfjscdhtfcO+nB8J/vZhQkgQ7RVGcjao4VvOriCGJGWGFxK57Evjt54DNLYZpiylkOFyg7uJCK0lV6iuk72e8LSGx5UUnREeURzgRhfwKrjZ5HhCcw04QRUzmFWRacdgVDWfTxYCGAhfsKjnnZGe+LHjGHJ5bP5vSnLGsdtEJqUqsPacS/09TFaGKr9sGctJczq8f5ZvE8wfSTn+7vpLxpGBv/M7byX0s1e9qIm3MYecUnVCrF50whOM4PLXYeC2H3ZpHgb9d1NbIoY4rOsGdO+UhsXYj4jmUbLXV47BL6hjEGCar7YjI6n21/GYl6aIB3Ko4TeawkxOD1kLOn6ZrCuYqI9YfB+2JZB2CnSINSKoZ/xx2edth12N/5PU57IQdwwa/q4pPKeUsk5nRa7WPTRNtcNiJeQTs8CHeMXOHXaJGKGSjMMbcYgZNFp14fXPOqQgFAJtynZvDTk6QXcvJ1vTrOJsYmn1bO0ytIITEajVCo7m7Ni0shMsddlIf6Lik7Mnm5tfcY0UxOWz44K0lAfC67vHbMWuERqrEAsJ17jOh2Dju9vfjNRzn4k5soDnLZIe67hNOTUROCdY4mRZcJ07Kg3bnsOOLsGTW2ZxNmFZ7SUobZknbEWhoIYTEcsGub547z7JTUISKWAmxUghSF2JKOewAYbyL8Ry1DMdVnLTz+zS2wV83Vx0NPHIVcNMnWnuekk/RiXY6SiMiCVmwk0JiBcFOXsMFRlkOuynPeqxkMue6wGah76mw4SVfJ62etyFEkjiiCGN1iYceHMGlvCiG7nHY8WRklRx20vvuMKc+z63fk9SdsayiYaYsJJYL/1b/4nHYVSg6IX//BZ+x3C10pmF2nzWOvjFaYUOVt9e5O7iP5cfc+xW+54apI4ddUXDOVQuJLUobQQDQm7I+05rFZH75buCOrwF//1nDb6FZAhHsWqwOXRdORUTBSQb4hMRywc7ggp37RWxvPotHUqdhxye+X/mFZPGmrhx2osOusR0zWdBotBOVhRJdVTBDGbX+uHA363bs9dpfkn2+edVaNKlGHqoCaEp8hRMu2M1IW7dyPkBfxJwcPlbaZij5qPQiM3qsjk5cJIdCMecdpIoTgFF0dtK4iOY4bwISkOQKzuJtvQu6dZtzjlMSADZOdbDDTq4Sq5XvbgWB7LCrlQjeElYFwU6pbBUHyotOAD7inuywc4pO2IO3uAufrx56GSjOoJ4QrvPuCImtV7DTqwiyYlqIWtWwxJ1YeVe2JcrCqUmwiyOGnWaEu58BIMXHkFKb+2m+EZDsdeZdqj0PS0iCHXfYGUE77Iyim7+rb75bsbZVN1M9iOP7VHgpaOIGHztVYWHV9jyK4+tbTp9S2RkT8Nxw4g3r9uUHWnueYhWH3fCq9iz+IiBpb06UwMUA7xpBjIQKzeEpO8SMQtlY7sy9eW5PwP3uJcoKDgRUJVZ02HlCYlUdqGf9qPrnpssVDScPqVFXDjvZYddZIbETQo7ihG5HEDZadMLuR8S1hiYWnTDFuZws2FV22KUTGmbZgl3FPHZFId3Uju+37h/2Q/fvFb7nhuHjuMIdduU57BznXI2QWC46i+k0BjLWeqFmejL+HTxyZUOn3wrBCHZwPwgWUgfuVER0RAchP49RcsNYJcFOFFGO3vhLqArDjq+uqPxCZQ67Kl+a4xAQHHYN7pjJSfnrTdLPERfggHVx9sPu6Gdt455LDXcLd9jlNTvMBEW89L3D8J9vHdzQ+bSTvGm1gaGM9d7ryiVRbMJhxxjwh/+2KrP5tG/ZUSXDQ2I3hR0S61elJ7dZCIn1OuyCck/KFZyBxh12GycKSML9HtZPddCuuURJdr2GlMOuKIUh13LYGSZzmm9Sq24VFx8XQ83KKo6WBMcAIOSws/ugcWHyKO62hY24CxeUFT9i+CIhXXdIbOXrXFxw1BLsRNd3OA473nbsjS85Fw0RKSV7oSTmsNNDSKtQF3wRlsg6Ai8vkCX2UwAcx7ahBCzYjVs5m6EmgOxMQbB7tfL/BIW4CG2nYzliDCkvLNDmsOzX/gX8aBvg4rcBudHmn4fPNWXBLrZFJ3wK6w0sthK+l6a843sXkbQ3j3O2gUH+fvLFNgh2skPMKJa55Jz+V+wXKoSCVqsQ2gxiFVLNk8NOckDVgh8nOaBzRaHoBNNQNHlIbL0Ou86aR/BN1J6UjqRm56OuGRKb8t7aj4tVUhVF8d28lTdf/dx8vI1kEhrmcIddJcHOiV7LWELdh38L7P5R9++BOexqh8QWnfyK1YtO8ONEh90MO2SvriKWQFtzeQYeEhtWzrO8UHQCgDcpoxi2muoDACh2SKf4RUATOpBKwqIcH9+0w64+15bc2TcaEluQBDtdVdGn2B12z2wgPWjd55PMCii2UFnQbMGzA/II5Qzrux1MWbejU3UsyMWcHFqdC/nxdcBDF1uV2YZXlv2ZlQpIoeCbww4AZrRLsOMT+MwMK3cAADY17LQxHsbERWzfIgJN4CfYJRvMYTcyWXAcdgZTMDzVufnGikIyXsBbJTbIDY2C1Cfy20qDvNg3J3SlbsHOqjLFw6hlh51cJZbnsLMnkGLYVlsFO2FQD2qiECGGyZzvO5usbyLshEH4fL+iYFctV0fRMD3to2iw4IRn2WFHIbGxhLtMEoLDriyHcLsQQ2LteZduC3ayw063HXbFoItO8Al633zLQcIFu9E14fcx4iJ+cvo47OSiE0B9KSAC49nfW6aAjS8AL93b/PPIG1xhhcQGBe+LxSqxehLot9v88Kq2n1I74H1dTrHXdtJ6zptLLqRrXnZz+jjsnDmdJ7KmgmAnuaHLNl8bPT2hSqzquJgAxj8rboioRaWiEyW36ERdDjs5h121dFYxhFclzSa12qYKR/i3P2MpHztPg8LXIH5pkOQchnI/WjJMp53XJdgVhfD5zBCwfD+vwzK0HHblxpuSb7h2+VM5axxh7jCYtT7L4XrX6xUi68Ig8JDYsHKayEUnkuJiRBzsbIedwh12gutJVQVngpgLREQeOKsWnZAGX/F+nWGWsi210ZCjolN0whUH+rjDLtVv5VgB3KpmFVDszi2v20U7WrX+twEeEtuftAW7ukJihU6lXofdmKCgr7zf+zfTxNde/ST+lPp/SDH/5+lPW68TWvl3Dt/5TQ84Qm1xYpNzfcpVYoFgHBJiaCYfuBvNLzM8+f/Z+/Nw6ba0LhD87SkizvzNd04yL0lmgkwqBXSpgGWh1tNV0rTaRaPYTytWd0lVq2jbVLdd1eWEPg7lTNnQ2gwWlA0opSkIkkyZzJCQZCaZyb2Zd56+6XznO0PEHvuPtd613vXutfYQEefcOJd8n+d7zjnfiROxY8fea73rt35DYXY1C6Q4HOJHuKFlJwsrU6daJ8kuD/kGBsYQ/llknGEXABErj+Sh5YcmqfkTETqxYGyEN41h17MzewmKb+QMl8Tqps8ndRgoifVtIK1tjjehE9L/cPM3i34zFTHsJpE7fgBvIsNusmuuFwLspIedkcTqlNu1edhx/zoA2H1UyXPq4vwZRwMW5m/FKhmbh2qSXCBg99Iv2O9f+eXlnyfIsFvj3CTltatsEpoxeub+PwWtvFUBO2LYgQA7wbBj19y5Mewk4FTlrfHWXPs5sxspTr1G+PJvQ97Fgw+P3ZP8vqxKusZHMux4aEBVo26AVAOnjoddkGEnNvo2FQQPlGHYTVLj0R8c21rA/9T5f8uwi52v3AapJYmVHofstbmHXVASS+efNu1lcSblKmOS2YwPe9iVjDRhFU7heyJ1GHYasOti2HF8ZCiTdA21FsCOa4PPa/AqRPKi0zDyCUo3cZH+8JzQierQPu4o4DcigbYu4Mo3mY2VxK7IsJPnJU0i7BPDbnYA7D6ivu9h2MX6fReXELDb02PWoLQmnhI70MPuW//tz9gfZIPy8FU8UTyHJ6M7uHbqD/fYnemY6PNKk6LKNSAy3TVM0/zUTuSzlCSxTOK4DsBOML0Avvs97Ho+PM2Rad+QHGmvTG+Ty6bEugw7wB8AsGzJhGiSCIVAUj75OztPPaETScC0Vv2x2Okj0IWYMFw+tDi6OM8bB7C7/B521MxFkQVm+yrr8KocKon1eaquzceuEgw7A9j95gEiLkNZwM5eCxMZ+rWOWjwEvvX3AN/7x8OPKZgkVvddWUASa+RUBNiti/1Gm58E2CWpSosF3JCd8ygud7sEKoh1VeXxsLObghfAnL7HlBWvf3T555E2AKkrZVtLSWuUVZ7byNwEYHftHerrvWeXf+4NrlQDdmcBwI73UmtNTudFa7BIK2LKRYst75XEAt45NBcWKqv2/tzDjt+XtWHYDQXs2h5kdKxOSqxh2IUAO7FmXbcv5DmXYdhNE+sR2yuJlQw7DdgJRnLqYdhJ7EGCg7z3m6Yxbu2pe+H2w1DohEdxyIsTplaZi6mP7/Cws0CcZX/6TqWPYXd1e4AijpMPomEb6OuolQG7um4cqdV5AXYtXyhDGW3QUOOSTA3iTBJPjpxulWzxGDKkbEliO4CrSjAEgNE7Zm2G3XIedjx0wjDsZvvA9jX1/UAPuyIlSexlAOzUZ7ubLcGwS2d2QgnFhEN9Hp/81DPsRYV/yV37u4O538NmTwN2gzz2VinOPtBMp/JMHW8U2XuHA3brWHAZ4IgtmMbsfpdVjaN5aTyHCqT9kdobXNw/AbC7W8B6feykf2WfRMiMFUmMKGK+IyGGnf7vJLKmtW2GnZA/ZBQ6QYAdTzJs3J3g86y3mIedSevKEkQDg4C60qD5xtBxB2C3MAnTsXm+9TPsBGB3TkDEN//gr+N3/PX34dUHn5bcjqmyaQN2dsO0BH7jR9Yjz/zA3wde/kXgw9/nZ1mWub2HJzvG8zBrSBLr3he02CvW7WFHDDsC6QBg/wn19bx97PhC/BL0aOsqmqO8KbHnzbCra1dl8fCV5Z+rksyYc5DESrBmFfN9LnPjdf2z1Nc7v7H8c29wUS96agA727s3TeNKYs+LZUz390RtvtcMgKLbwKy3pW+dD7AzlhpqPF8VsKuY7JKHE9al6An7ytOf0bEmZk2QoGjawIxT0krjkkliRzHs6HpMhYedvkZ46IL62t5gI+XFVub3Aj0znslqvTDYw47L53lxAHeVXrwliW1fP07oBIXredZe3OuPyjLsOtbrHAe4wI2zlQE7+SGPDU0YWgXzUwIES6hgsiw9ARJgxx+XVezEBow5LXrPmr8QK4YGULpZ6BiAEaETYVR70N8Llk0Sx5ZhN923HnY8RchTSU2AHTHsNnv3tmkaw7DbztS18XBe9nuEleMYdkfzArdwaP/DASDgAHb7J/6Y+72pZtidN2uMUjgnO4aWXM5VszZL7UI/iSNjLbCqjwXQ9pcEWILbgKaA0nhIEpsjw/Hi8soXS2GQ7TLszsHDbmDoRCE2PfrSa6khSxitvOVRKnf6JEtKAtwXJYt1POz60sVy4EP/AnjYzUJ+M2tsQizAgwG6GXaLsvaCeoCbgE0M3fUx7IT/4Tl62D04K/BPfuKTePnwDN/9cy+s/fnfykXeQT4Puz9Y/zDwz/9QNytuaHGwyweKcLB/smOul1mkrqNMMuzIww7nLIkFmI/dOSfF/mYF7Iw5eHtT8NxDJ05uu3PH0SqAnWCkn4ckVoLdqzCWuZE8Lwq0e4sCdom2tzlBmwFZsvAu4PxsoMxaRatlGgbY7WgfW8uwExuhno1Reiz97aqb9Vx2mfgYditIYg0JgGwNECOv+ySx0sPucq0hTnLq8VLXo99XoZRYDVLSZ20YdtS/s/Ue9XY7en0q1VCERRCg1yuJLQJsXKp1AXZDQicYXkRTho+Y4LNauLo9IHSCK4fykwtTDq0M2EmA6bwZdsT04OBAlRMIM2kz7Niua1axiSvE9KCbnKPEoYuLx1dTrSiJHe1h50mkdBh2W1f1Ex92Pg+drzLTgF212OjI9kVZo9ILiZ1UHWdVN85C1FvGRHeYh93DeWlDPIB2QhiTGs9yP8tg1zDszlsSyxl26nOsNEAyy4S/T0jiuMzLCpYn/37I7jftZBxM1bEUTYJ5EQYRNr2Kln8E8/dYo4SMM+YAnszrvwfMWKEf17XzBFgKuSOflY+lsZHGPUrppvtM3i8XBth5POxCO7M//feB7/+TqL/rD649yXdddTYyIRaw151Phi3HyXkfyJvGJrRm7Qy7liR2/YDdB1+wDPNnb6/AOPlNWMRsINYJYOePr4/+F/Ufn/yx1V+Ibyr6QBECHuJMjTea9TPT6eLSw47YGfl5Mez2HrP/Z5JiL1IS+5sHsLMSL/t/F8awI/CYQKvTu8v7bMqF9nmkxEovr1XGU7rGJMPuhmbY3X0mTGi4xJU2qn84aQgIsWuENknlvDzs9DXhAey2p9r+hI6lxapsg7TUl26tiWFXejyOAaAuxkpiGeCi15x0jmex+rlEgrzpk8SKe/KSjY+nC0qJTVjvFgrHpN4pc78Khp0kODkMO/3579K1JK6HMwHY3dq3gN2//+jr+A+/+Ufx3/3Ah+0f+AJqeK0dsNPP5yHe0Nox6WPYiXAOALiqGXYPzorwGpSvY5rqwvwS18+wOzfAzkVCufyhzJkkVoMwtENi5Gh1jaRiE1do16kWVFMgfHHJ3TL+/UhJ7M4kcX4eWi1ZXFRhGpFsZBfYuqK+75HEJvp9V8SwAzZ6wJsXFUp9+U6TxlwXvbJYI8PiKbHdgN0W2M3YwRjKSv9CcPeiGHYEQjNJbDVX17lc6GeGMbX6/VqUqwF2h3on45q+5QqdSnhySWWxcnMhZozGi2DYhcbgvHT9LvtDJ/Skx2Lha/lYuQAxHnZ610neLxeVAMoBO/KYCDFsfvW71UNf/zW85//5g/gr/2YFj6JzqrmRpg4H7LpAeR46AYSZ8dyUd3puDDtx7cgF5xqK7wp/6s6nAbsxRQulzBM6cQ1H3r9ZqniPcvRq+/dmQ0pvChDDTs/PYcBuzR6WxsPuTQDsHIbdZqsg1ll14y5AgfHBVksXBYncfJc1VF9WFlsJVc65SGLF+LmSJDbAmrnyGWqtVZ4BR+d8zb8JlWi1x3HT9rCTPe35SWIFw44dA83Fpp+Un7HnM6fjNJLYFXtRzk5yJLGjU2JZT9PUzrFOE82waxLkJnSiZz1uft7c9auvfAy74AZyK7zGZdhJICrxrPfoOrYMOz95iHrOm7tTTNIYZd3g67/jF/HKgzm+/Weex4v39JzE1Wu+4l5v5+xhZ3zE4+5wPUmuAIArW+q6bRqr/mr/4RrH2BG1fobdOUliS2EO6MjMCoY2G0msDp2gx8lFQJ+HHaeAhxZ6fFFINVYSq28SihIeHzrhsmy2Ix7AsT1YEhs3Og56wgC7DR7w5kWNslHnPWkq7OubrJfFZgaVKWPYhf/m6KzALGLnQUpiGSDhMDhZ7c0GHtuqRYDddNcsauqcGHbuQr9LLjf6ZcU1yL8fw7C7SoCdXmAd5+d8vs6pSuEfAXSznZatXLBrzTkPNJByrKAxtGn8u088JZbmsxbg2PKw0wsa2nWS98tFJXeNYdhxKn3VjJKdXlQRq21o4ATAfV77GXbha8aCvIZht645XjLsqNE7B1D39rEdw98ImSZ/urxFklgyYgfafnHqgSueVw7YPRwA2BmGXY5UGJ8Dqi8AgLxZsyT2qIthd84edrxvrYu3JLvJV9JEHbhAhh3NYbMrwPYN9f1p9wZ4sIyNjpTEniNgt6wktirsPSMX4UkKXHtafX/nE8s9/wZXonuCk7r9+cjr7fxCJ4hhp9ZkTWnTsGlur0KAXeH+3DSN6QOov1lVwcItU1YLnWgzr+gcT6nvRGwBuyCBRp8vWsNeMkms8bCbJmacCzPspCRWf9XXjCQ4pR77G+rtSCJdN+41QVjEVK8d0yTG5zy23zqUn3n2rn5C8rsMpcTGJkBlPR52HSmxDLCMQ+ogMB9Gdv2mSYyDrR5ZrMRGLoiIcHkYdrW7OI2iyCw8KwPYWUlsLCWxgiJcL0KAnf6AOAX8Ahh2BDiNZdjlIiV2SwN2DSIFShHDrkcSSwy7Ort8DDvUJfa17PQohIhTEWCXbQ3ysGsx7DokfmkQsLMMu16PvVWKL2i0+X+jr3O50M9CIQLLvCxNrj6G3YCmgAbFK3rdXkfEsLvcgB3ftTET8BolsZJhZwGVgR52XKrruS45YGcYdkFJrJ40aTENqIWCvF8uihXCfS76GHYMyNvGHE9eDTQcb2ItPPdYX2UdoLzcGAotennYk/GwW9ccb9jOgmF3HoAdY9jdOc7Xwiz+zVIkiU3Y/WOuLTBwexUzfsAF7HzSeQIeaEHAPOyypH1fJNBsDVBDv4bPPD8BFhrA8XnYnTfDTvZkG7ypus6qPIDddMSm4EplALuDwYqVYF2IJHZNHnZ8HPbJ3EgWe+eZ9u8ueZFC66EB7OwaoQXYXZCHHR1DxjyFTf/eEzRSMd+9lv/dsocnQSHaAF7Www5oAXYzYtghwaLukcQawO7yBCfyIkXRVsYkscGU2BDDTgN2UhIbtxl7BsCd2jmcr9doY5bbKX3RZ1xtHcqztzVRxIROBBh2wHoC4MxmfBx8Th/700dKsAGB7mYfBU/cOxmYSLyKT+iIWhmwkwv+8wLsfNRFWnjWntCJWHsQmEZOeNYtTgNeSkYSyz3sQgs9D/V3pIksnS8CdcYynkiOSL5U27HWsCczFQ06lGFH7yWZ2t20DZZczMvKeNihKg2LrVcSy6OnB3nYFdgCuzmlxI8BEmnpv2lJElvVzfrkZL7ioRN60mr0xD2VklhacJUSgKlVSt+IJkwCR/z7IeMBSWKvTPTkHF8QI/GcSiZaA3bcOo+UWNq4mCR+LwqqXMjnHcDO6+/AGHYhSW9rAZLZCTQ/tfeLTjpDuYEMOzb5Phrdw5NXAx4cb2IZT5dRktgwKD90o40nHq+bYVfqsfjeQo8b5wjY3Tl2r7ugcfKnq1UkiU0chl0MoMEOWI8gwfkx1TTAGfOAlfMs0Mmw8zH+Yg0wzkEedmuYT0gOO9lVHsFUB0+pr6d326zidZYEdja4R1tneQG77KIBO+YJvSpgl0rAbp2hE1JNtORiki9KfTI3EzwxkmH30i8C3/nVKl16Q8sCdu3Qibxy5z/JTFpbSQ87/XOaxCZ8xfRtEkAQP/N1pfWwW60XlfckMZnGp8RyqaQG7CrysFNfHYZd6F6h/6f54dIy7FIvI86pkpGUgFbohGQk+9QWJoRkagFTPpb6lFP/xZc/jadv7OALnjzAn/tKdf8/e/tYzd9S7u+rtQB2tftcdJ1xwI71rV2SWHsNu1DYFR08ce8kxLAT/+9TbN55BvjBbwKe/5ngWxlbqwN24qY/r8lT+kIBFqQqOc1cA3bEGDNUR4GA5mcBwI7kkUnG6Js9zAy+kzByx4wYdZQkOnbXQ7JmiA1WJXqCpd2ZUMiGLpqgVHAHRURv7qJmXtQuw25rYLBDyTw5kv7B42heGNYigHYiDGMCJAEPu+1JYgCPh32A4irl8bCjZm0mE/RoAJeL+Q/8XZX4933DU/+8oRNLSGL39a3TaEnsZWXYcZCDqpfiPrLKqgY91fCU2MZ5HPcd8QF29RCGnc+vRLM7sXhor8ndm/rAL4phxz3s9OfQBK5FNjdsY44nNhCwo3lilCQ29jPsmqaxKWx6HOhLFk7j9TPsXrunFsLf/6Hb+oDPb6Po7rE7l71+9JsD6FhHFXqhxEMnkjjCbpwjidi1tYqPS37izsM+8K/Dw26StoFsAhhzbZ2xFkksSV73H3f/f+uKkcj+xAfej1/5xHPAr32v9T9bV7UAu83t0dZZFWNMUF1YSiyXxK4LsLsMDDvqlZMpELUBccuwGwnY/fy3As++T6VLb2iwHRE+TsE87EQgwh4DOs7lGjQMu317DFCbJa1Qgp5xgW/irislVgYbUD/ZrCSJ1TYGRAIwKbEJFrVd7/kPSEpiL9fYSAy77UnSv8EfGkdM6ITb3/lDJ3QISZaY29sB7DxEjFt7M/zwn/0y/Ktv+B34gqeuAACev3vqgqNJB1C7ToZdh4cd71uDgXnwkysA4MauDtg4DlxDLYadZ5P5O/4A8HPfAvzwXwy+lbG1BoZdI34+L0msNRGkMhc197CLiWFHklhi2LmTVhEC7AzTLLMXRJ8k1mHYjZPEmqSWmd/4cejfT4QktpSA3aIbsEsbNgAQWr/Bu7dKEmtv/n1i2PVKYlnq1QCG3Vleuwy7pnIf7wB2/sYoiiLDsnt4niCUSenZNpNWrL0s2qETAUP6X/g29fXVXwVO7g562YVZ/Nt7c8oksX0y4EMN2O1l6nFvu3UF3/7Hvxif98TBoNfftCp9vggdk8YyxUEYEzjTlxIrPifHB7SPYRcCHH22AMSUYgnK2NGA3UU1UUMZdk3jAA07WJj4+k0qK4kdkRJLu7RiE4g37zQuha4ZupYn6XoZdieLEqmeo3/hRX3+z5FhJ5nXQTPhT5dTdd0Y2SstYqmuxKI/WIe5PZWPYUfAgwHs1CJlEpWYdDDszgiwW0dK7P3n1Nerb2//7tZnAwB+6n3vxfV//h8D3/cngO//k6u/Jq/fpAw7GodiBhxdWOgEXYtTzrC7F358V10EYLcuQ3TjSRWQuBHD7u5ISezhC/b702E95kVXpNeBJ2DvXcg1ac3G/2+tVboAVMQksS2LlR6pPCeCnEdKLP9a+3rCrooYDCHO8SRRr1FwSWyQYafnJ1rzXrLNDM6w4xv83vWTPMeCYUfrg0TIlTlBo2BEC9/mR8iGJU1iRFGERw/UvfHGw4U7fiUT3D/J8Qf+4fvxzT/46+5x96ldhlTIw45dF7TOyjjDrmeNw+sx/d5efxCYX+V47Ru/j15WX1/+Rf9zLFFrYNjV4ufz2TEpPAw7atIcCq6eAMlvxSCnwoSznAcALA7C9aHBtWdgGjkB0421rXc9xjYf0sNuWzPsylhPNLTbkB937mYluhmPUy6JvSD52hI1LypUjGFHkuKjPoYdT70a4GG3KCsXsAPcHUsO2HXsZJJk9/g8ZZ7G42fLLH6jglJipYcdsW/Y9VYVwMlt+/MrHxz0snZybUtim6afVfbgTF1ne5l6niu7O/jyd9008dqXrUpxTwKcYbeexo43iMbDrpdh535OfJLy+TtQMp9i2AVo5b4xkNidJB9LZ3Ycuogxpa4tm64vJbacA7Dv6SCZmxj7TaqFMQAe4WFHoLz4bPn1QeNSryR2zQy7Nx4uMIG6duYEqJwjw47GXeoHLqvc/qKrqGuT2p1IwC4R82IPi7/7hcTc2SWJJQ87rQTIUBq1BS8jiaXQiXVIYrsAu8e+AADwF7N/jqciPY8+9/7ezdJR1QLslhxPN7i385WXYXfhoRMH58CwG7fBP6gkYLcsGGgC2gKM8+vvVF8fvjpODs838o5W9L08pyJw7Kxhm3f6/+h628psOMD8PHzsWh52arxNmYcdManMZ0wkBHF/897PB94sU/KeNCFmYxl2UdRaaxuwKF6GYXc5JbE2JTZxGF/eTX4jrae0acmwc1U+qZdhpzfw48i7+ZH3bBLf0hvbD84KzBesF0gyfNfPPo8PvfQA/+QnPumqytbqYUcMu/Zz0ntTdj79gJ30wH1kX/Wir4YAuxZAfjHX2sqAnTwJ6/Ro4uVbBFOTVpVs0UiSWL17bxalMnQiD+zicxN1uhBCUgovw24cYEc3yM6Sux5WEqvOBSWaGoYdDV5N1bkQSox332Vh2NUoYdH6/aEedsbofOZF5mUtytoNnQDc88IAu7gI72QSk+X4PBl2PFZbL34jPcm3U2I9CZJ3n3GvW19Sn6e6POz470NFbJcdbTA7eGduQ8u3ubBuhh2fWOm5JwaE9b+G8bBLtecI21TqYtjxBMZKPrdcgAB2QU3Xz+zgYn0x+XgdJ927emJxc2NSIPLJf97kWiZ0IpQSy8E5Gpf6QN7fkX8A7yo/pv5+DQy7N47mmGjJ4gsPKnVfnCPDjgC6x6+o1+idJz5dAFTfVXpCJwDgoAXYrcCwk+PCEEmsHnMmKJzNIgBAXSPWoRPzmvq4NQA79z6pvl75jPbv3vFl7f+rS+DVX1n9dalkr7LMePoj/y3w198G3P74eo7pAsp4DTkb9uq6PH9JrL4W1wHYlQGG3TrZQPKaWPa5yx6G3dYVYOeW+n4oy65p3GAW2tTbsCLAzmHY6V5nwfpd4xN7HkQVYslNBcMujtsWK/QZG3aZew2QV3WWRNZKasVjps1nybBrKqZuGFoCdDE2O5H1sHsrS2KbpsFf+H3vxjd+5btwdXvSq36xfXeIYeeqfDKP2oJ7Wvs2+33rOl4HW5n53d0jtikVp/iVFw/Njz//qXvO7wCsCNixQLnAc1ogzrJRfaexFExEKsOwC1mnyGurD+9Zk/R/ZcCuaEliz4lhJwYHgKXSGANGDtiJ0AkxgFVF6IPgDLs+DzuRkAgMAoF40Q203bNwCpUNnVDnYqZZC2Wsb2Ce2tix05vqxVNySQC7RckZdoVJ2T06G+hh56TEhv9mUVYGBDXF2QDs+7g8DSbREQPwXD3suIRBAHY+WjMgJu37z7vPN7CZ4tRqKr6A6rumSRK7nerHpZsnSRxT3pTYPhPZkcV9AwlgMn5kAdC/EJseUcQns7Ahaxx1MOx8zVkmGHbTfWuyvU7pT6j4/dzHsBMgw7VsM4Ecm9g1JnTCw6KFy4gl5m1o0VtWDb48/lX8ucO/im98/k91PnZMcYbdWZ0oBpwBddffaBNg9wQBdn3zxKcLgAbsApLY/bVKYiXDzmNZ0gLs1PydoWqnxLJ7/YwAu2VlOLc/Dnz7fwb81N8BXv+I+r9b72k97OyxL8XzjQIwnq0fwy/U71a/OHxxudf11To87D7w91Qf9EPftJ5juoAqN4Jht/+bi2HH1SihIpYdAdl9NT90F7urJkufV2kCgwmsAVoMu2kaGxb7uaSOGxBOediRTDeJI7MZ1wqdMGw89zO3m7Uxsti/kTe2LIuLNoBlSuyIjXcJ2NG6lhh2TYJ5pe/9oaETl4hFHEURvv53PY3/y+/5LBU6wdYO3YCdJyW2aVqBIMbPmKfEEojLJLH8miCblNZmGDtmYtkZwC7OgCjCS/ftGOSw1NYJ2FFfn7Tndyd0opNhZ1mGvB41DLvA5rG8tvrm5TVtQq+BYScksatKvn7yb6oEIfGGq8odHAC7IKk5HVhfwKluLs0EL56vCTU6/Ebou7jWwLCjRfTOksk9UuY20/LNgiSxcWIX0B2SFQI4oyRjgN3m7lDkZW12/l1JbEfjU5X2sxyYErsoPAw7uvmqog0CBHZ1dg1gd54MO2qwtsyuaFKpwVIu9Cc+9s3RS85jxjLsOCiYJrFhcPXJvIlht20YdpdTCkt1ESmxhVeGnDi/a/2NYOMC6JzMuKlw8HE+ht1EMuz2L5ZhJwG7ToadCxRcTTezyVuGYRfa/ecMgf6gkhp/IPlp8/MW5mti2J1hEmmDaWRqDCCGXXm2VjPyeVGZMYgYdue6cfIWKiWJJcDOPWf78TolsSM87KifSTsksWwMsB52S869P/k3gU/9JPCj/71lEj3yea2Hvfiwwtfl/w3+Lr4W3zD5y/hkrUIoTFDFOqrHq2pUPXh5tWO5wOKbR1QX7mG3FkksU7IA5xQ6MZL9EXweptgI1d6j6iuXuXaVBOKPhvWYF176nBVNgjp2PyPeR9G4s2riqrcECEcMOx4CZuZ2GgcoubqVEkuMq9hs1q96zBJEp7ZytCQWaPVoNnRCvUaJGHPDsHPnoRfvneK1B3MPw24ze7khxXGOlqoFCAP/+ndS6unzM+bXsa8PNOu6DhsWCmc4fHjqHM8rh3Y+v3vMPofz9LBzGHYWiCPs05cSa65hAUo+ahh2IZyoRxIrx7ll5wtRI+4of8mb3kezreoG3/Ljz+Dzn7yCL3vXze4nfN9fUV8//P3AF/7v7fN6QifoIqtLluxKHnYgg076tAYCdsaTiUligwy7dXjYuQy70GI7VNLDbtoIwA5QA1hxOgiwi9PMTtAbTCku2M4/D53oBMQ4WOCkxHYBdtbDbtGkmEalXVz4POvKuV14sroQSaxjEqwb3JAk1rPjYhr4KFGD4kCGnS/+G1D357yo+yWxxLCLKXX5skti25NAyyR4xfIl8/Yz7NqfUxJHQNXt7xDHCBu3+sZAWlBTEz/db3lsnGuNAewEK+jKxgN2Y0In/I05B9jp+bo87G7CnqMnojtr8bB7eGLHzgKp2mjZ1vNOU6sGKF0PcM/HXJI6fFoSO6wUw07NXZEAvHYl83wdoROTPSB/6H8uw7DTCzI9pkyjAlPJAmANtGHYLZMS2zTAx3/I/b8rbwN2b7Ue+sbRAi80j+DfHnwNHr+yhVeeua5+sU7ATi4MQkqRUPFFy+md1Y/ngqrbw+4c/MN4EcNuug9Av/7SgB2pgTyAXdP401hHv8aakoSNJLYjNZ3ug6FpyFzq/o2/biW1m1Z6rCuRokkyoM7NeeVSwnRNbDVvCcAurn0edsSw05+5SZQVhBcmEbSJoSsy7IycUINC+utaJLHE7uIedoygQffKaV7iP/l7P4XjRYlPbRXq7pxePkmsrISNA14SlGEx6vGDq5LKRUvq6du8teuByAvYLQLrOl7Xtc/4EfVzSYoHZ4UTrniHJ62eq4edOid13Rj5axJHSJrI/L8sugekJJYAu+NFiYfzwng92z+UDDtxrckNx/khcPBEx5saVmv3sPNdXP/sA5/C3/rhT+CP/dOf734y/rcihcnnC0UDjyOJjckguXIfXwogK7RwNIPNkJRYz8A0kuJOg//uNHF+HlotDzvDsGM3MFGEOxrqBOp8xU5K7OYOeHlZuR52RhLbcd4lYGcYduHBoyhzJHqX5xB6IjCAnfpaNRHqhq4z/3W1d9EMO20UnOhJftaSxHoSJCnV5vEvVF8HNvQhrwNf8lDrkKvaDO4zA9hdcoadh2a9dg87k/jaXsCEmkff33QlKNWcYRd6nDcl9k32sOPAXJx0S2IFs+cg2VTATodO+Bh2H3uvMrcXRdefnJPzEQy7sq5xENl548no9loYdqdn9rznSNW4zReG5XokBIAdc3enKQ62BmzsfLpMFZVl2MmeZhaLc7gOwG7nhv7ZYy9hADsKnVDzhGLYCaCD9Wwn9Qq7+sevKwARAA6eUmPJ7/0rXmDljYdqbLu5N8XTN3bxCjRgt05jfQJjaIwdu/Dhn9Elmmethx1Lok8uShK7Toad9J6iz6DpvT6bpsEnXn/Y/36HJBgOqWIAw44AOx5W1lW0kL3+TmD/cddOaJNKfxYFEjRCiVMytZcBv9ZtBdU0FgTQ67dI9y8JszIxr2v87roZdkkcmf5vXSmx1NsSl2YtklgCi/S6tESCecnGXP35vHG0wPGiRIwaEXmUXkJJrKw4joxCaZQkFgCqwigf6bNOPQFknFhAfeCCXROLotvDDgCuacDu4amev+NMsR1ZrR+w62bY8TAVRxLbwbDjayJAhYDu6zW718euz8NOevDSps+KtXpK7AAPu3/5wYHU+/kheyL3hPhCJ2igqLk0lTVx6jHkYaeer8r04BdC340vXbYaw66DtcXLMOxYSqw3xrnn7+mCmzSats29F2jHocPDzjDssom9+TfYwy6vauthVxXDJLH0fpKJpg31p8RWhb1OHja6SRYMuzkmyImsGjhnO/rzPc3PcTfY8bBTn2Faq+th2pLEejzsiGF363PU14HJX4sQYKfZO10NJk/1nb5VALsuht26UmI7fAPJm0KW9LBzjys8mSVx1A/YcVsAaphooTrjHnYXsAlAY3iU6ASy4ZLY3Wj9gQfrKGqeWh52H/1fgO/5WmUjIeRFIYYdB//6WCpF1eCAMeweje5jXnRcw6f3gO/+WgUidtTZ3F4HJRI1bicTGAbLWOZQRx0zwM6EE3Vt7Hy6TJW1y2TntRWJc7iKJJbmTQLsgDaDXUpiOWDXCp1gHnbVCoDdvU+pr1feBvzpXwX+7y8Dn/NV3ofefqiu6Vt7M3zmrR3cb7Sf1JrkMADseGsAu5HXMd+EW6Ps/LzLzEUXLYktc7t5ID3slpnLDZgh0h2BXmDtxz7+Bn7v//CT+Kbv+9Cw16BrZGmG3QAPu50lGXYELG1q6bGuQoLaAHbq8zEbskns3/he1+sbAEqHTjQ1ItTCw04/phU64WfYpXHEUmJXu/+lh525N2tGehlaMiW2EB52XBILmHGPNt5ovQ/AMrDHjo0bVmkXGGxISnr8iGPmn78wPZ9hPybt9YcjifVsftC42qXquLarAbuTM3M8907ccezcGHaRvh5Ef8/XtDx0omnaLLtSnCdejx2oDWRvUmyLYdcjid0UDzs5UPn01oN3s0/v+r+HRU19lHgH0dcgDIUoGORULxTriTbw7APsIpYueI4psbS4JkCnacaxcKThPxl5FxH3lNIDWEdDnRqG3eXwsFtKEmt2DDWTY4CHXV3Yz/EIBNidOs93hikWcCd1WSR5Ps3PidnRNIJhpz3s6lDohEc+eSQAO5+PkKdywfKkmg5oqMm/bnea2qTiyy6JpbHqHFNiTdgMT80mRmOPJNYHJMrQCT6xdQN2Hg+72YH7uyn3sLtAwI6agxGhEyR/37SaE8gm/UQ+8i/V1yoHPvy9zq/sZxZm2NE9GpbEugy7HZwZwM9bP/7XgY+/V4GIXe9nbpugCrEKgYgi18duTUVj7vY0wf4Wbex8mmE3pMqKpbGLeXIrEudwlQ0+mlO3rsKCtgKwo/7FSGLVPDFB6UmJ1bvt3Kx8GUnsfQ3YXX2H9gMOywPf0IAdMewOG71xsVbAbkWGHe+rV2FEXnDVgs0DwJtsuPbiPdB0XyWjAgpMGdgfOSUX2iMAu3/4PuWf+P0ffLl7U7/l5bUkcOFYrATKSGKHetgRYLe33DFdVBlJbIw6cnt7w0yKLcNu7R52vE+iex1AglorHsTr0mdOHnbiWuJeXTYldlWGnSsntCmxtC4ebt/R8rCjNYVJiU1xVtl7n65p8qKdcMCOzpfvun/mR4F/9KXAD3zD8GN7k8qsGbwedj6ykF23Gwm0CJ0YI4ntS4kFrCT25NRKYu+futfeA745uhYPO32MhmHnhkdygJOrg4A2y64KMOwA4LEratzjfnz2D3sYdhKgWxP5ae0MOx9qz09Y50TDmwnhn+VjrdgEWEYzZ8lhzmvrATDeUgNaXAcmR2NoyAC7UFPE2XhUIyWxdNPsTBP2f8MH/9zEdWvAriHAjkvUaBEUvmhMSmzGPOw2mGG3KGsXsKOFWKcklgAt2t3sR/tr3bTUTYTjRpxHfVMqhp0+3wFAgkJFThbnxLCrCjuQZTPTZGX6Om952Ekfi6axjKhbn62+DmTYBSWxAxrqQz24H2xlfvDnEpZhA8dtYGztKbF8PCRJbE/oBAdvQ956ZQiwk+O3LymbFjVUswOnmTj3koBdV5MgjmeKzQRyaMe5JYml1EoAuP0x51d9oRPTNOld9JZV7TDs9qKzbobd7V+333ckB84XauxcNCmAyDZ1NPeskWF3qiW8W1livEg+HToxrIqqQWFCG4QkVjLsVrm3qcHNtpmFh9hgzPWigCSxA0InKsSYV+7/jSrqQw+e7H3oXc0kuL4zwWfe3MF9KFCiWStgRzI5WpSuIInNjy8Ny46zvakuJCWWpEyTPQvY0lzmkTn92197Ff/tD3wYL97z+BsDbUkst9PpWTN8xvUd833QDJ2/xqpeXqXY4PbVtpZ9nx0Oe06euLvJ5WXYkST2Ajzs+Fg6cQG7JPZ52A1n2GUS7FuiuE8YgUHm3lxjSiwRSSpEmNdsDaMfR3Y6DsOO1ru+8f7svupRDl8YfmxvUiWGCenzsNP3OPeuY9hDIcDU1LP+cEMn2mqoIYDdtR31+sdnlmFHgB0lrR7zzdFz9bDTgB27F9M4QswBO4lXBTzsAODJq+o64om3pmSv0/pZ9K+bw7CTiGX74uJ2H11+Vg5gJ3ZXS6HJ5t83hpkzaUliLainTmiiF5NpU+DMJ0/k+ug+SaxvJ2HZ0ImJnbjHUPylh10GD2BHE64vJIEeQgCn42G3uR4AuQPYVWYhtijrMAOEbiraMYz60f66JIlxijPo82IYdloS20wswy6waCGG3cl5hU7wzzbbNgvfDAUi1C3ALpMD+Mkd3dhFwM13q//LHw7aCTEDuwydGOAxQwv1txJgVzCPE6rOlNjTe8B3fBXwa9/b/l3wNcKS2ND4YZmQzMMuCjDsGgHYRQHAkSd0U82uuI+ZHVhJ7IUAdsLjgqjzja/xcY9nIhOhN6S8oRNlblMrAeDObzh/4w2WgSth77tm6mKBrciekx3Muxl2h8xgn+SEnlostEVFpL09aVw8B4bdXM/z25OESWI3E5jdtCprbj0hJbFaIpZQSNUK944B7LbCnrsBSew0KjGVDbdhyDDvo2V29akn3b7W+9BDPZdd3Z7g5t4U5UQzjc8Ol5NPyqortim3JMPOGX+bzp5wk6rqAOw61xSrlg9gIga5YNgVVY0/9c9/Gd/xM8/jb/yQu3liSprFRxFbM3TPjTw8R8rOvK9BDLuVQyc6GHZGInwv/BheJBWbHix3TBdVJK9DjDoiqSFJYn0edmu+BulaiFPHnyxF5WyglnWjxmUimgQAOw54p2vwsJMbuoBNcG5WksSq90H3dGpSYhMs+OESYKfBIFq/qvNF91MbAP+FZxQpoeQe7xtadG211gxNw+y42FqJ1u3VwrDy6LP2feY8sNLXB3b6Juu6riWxp2d6rIgz3Ndj09uuqTnq4doBu4CHHQHqJlFceQFyGwW5zrFMxPZ7fOKKOn4vYGfWqnTOezYv1zTPriF0wr3pfSmIvJXqBCw4o0cglDL1BLAsoaZkMdIxMezIw85l2KXbauKdoDQmwU5x9Lbv4qKbxieJrctBTRot7rcYoDJmx1B62BnAjnvY0SIoxFpoGgvYZZNLwbArqhoVSw3am6YGGA7KYmlRQO+PPt8OqUylAbscKc7onNLzlCSJnWDR0O5GD8PuvCSx5rPSDSDzHZmiwExI6TI5QB+9pL7uPmJ3TYG2Ft9TPuYWwD1mwufXBezeGpJY3+ZCJ8Pul78d+OSPA9/3JwaD5D6QdJJ2N2K5R0YbOi6XVh4hSQJJS3IBArQZdjwl9iJ8RVo7cB3AvAAZyFJg04qaJ+c+Pn7dHbsEYJdJnxvxXNM0DvrcUSULl0Wygx6GHfcy6kiZXuTaokJvmswpyOIcGHZnBZ27hIX/sM/5/vPAL3zb8tKxt3AVVWNDJ8S9O9UMuyIlYGAVSawPsBsmiQWAWSyuScawO+OS2LGMslMNRGwNAOx02vmV7QxRFOHGDSUXjNAA4j5aqvhYRedo7Hgqd/o7fI03qbyA3UWEThBozCWcBN4Jht3HX7O90ideD/RNXmbMsE1+8kgEehjChmG3N+h5gyX7ZV8RYJcfD+td6B4m9t+mlp4LqiZBJTzsrCQ2ZkDIuiWxLPCDsTAJsLMMu9pdcwRTYq2llJXxLn/fVKI/BDwMu1GSWH/oBEli6yZGVaMFzhhJLNkzJJNOb/If+EXF+n/54TmOGWuqkPrFuZ99/vlVzgJBXPYj/9yMrQ6zRllWEjufE8Muw309Dz6lAbvjvLTrhrV62Pn7e2n9k3Qx7DzzChUx7F7uYtgZFnNPauya+tmVATs5UPkWpPwxnab7vOEL7BBwJNQsVj0edlkkJLH6BEZ6QJui8NPKuZyKmBm+hV7TBCSxjOI+oJniTJnJEgNpIaRxWWMZYaayHoYdu3mSNGNsmM0F7BTDjj6fAnEcYXfaI4ula0oCdl2Dh/6bHCnOGmLYuaETZ5ja8x1i2J136ARf8ERRC7CTxqFWEqvvTQqcOHhCNZO0czDAp2UVSSwBdle2OcNu83e/uqqs3MkSQNskmBdnfr3+a4Neg++OUU0S9Rn3SWJ9gJ2cyLhvRhx1Mexo7GXjjWTY7dxkdP0LYLCN8bDTiwxiEdH4uWk1N5JYdh+faHCMGB9n9yzAAGukK+dofr/2mWbHpcty2os6POwWx0DBHv8wnI6ZLwiwU9eFYbufi4edlcRSmvhJXtn3/APfALz3zwH/5s+s7TXfKqU87NxFEtUUErBb4d7hC9RsoCSWzROzRMzhnGHHL1cfy7ariDnEN7ECZecy1T+97dZVHDd6Hl6HLJaPnV0+TV0le7pVgkIusLikj+pCGHa8r6IiUERYhnzkFQvgPXv7xG5C8JKSWP59z2fpAnYdPavxsKO0zFUlsR2A3ewAhpIx5Br3nc9NLDZ+VJFg8DCSRCb76HWVsXmaOMBXikptoPKN1tID2LVSYi0wEbLKGHV4rI+VskvvurivhP0U9SiJBuwqxCiqxib2hkInGAYg76e7xws7Z0Wbr+IJ+l47gN2k/X2Zt/wFfdepIRbEAQ+7ABGDF6XEnlKIWNJm2DUNI6r02YwNKWNbRqETUhLr+vfFnGEnporK4zdO9YSRxHpwEzp+GmPluqYlid0Yhp2fYsiLT1xnvknM/DF704FY6tQjiYVHEpuiRJZEiOjDogFwSgy7wh/X65PE+hZ6/ILjPhQjTGTrunFihemmGQPYyYV7qtNe8zEedmxgSzIG1lzE4nrJKqoalUiv6w2eKEWzMGDwqCsLgM4lw4487JoJFvS7QHO0O0AS++GXH+D5u0saQcvmKrHX7wy5h2EnFuoUOLH/hPo68zelvvIllgIWRO5qqImV4EpiLzfDzjdWBXfLANf/ZWD8tw8kzVJPkAg/Lu13OfF42LWo4uxnnizWYtj5qPmSYbf3CAt4uQAp4hgPO33NnUVq4t1UwM4rTzi+rb5efbu9bxnLLgTGcf9D2gALeisKRs4O5mGGnTQe72DY5Zph1+h73fQFxDxZI8OO+o/tiWXYAWyeeO6n1NcPftfaXvOtUl0psbT4WaTE5FlB7s7tEPoksfR7NuZsBRl2CRz181hZ7BhJrPbuubKtrumnb+zYoKqB43pncUCUZIpj388lBexocRl7ALtzTYmVMmzA9kZiM5NLp6q6wWu+dEGf7cdAhh2XxD5cdDHshCR2WeawkcR2gGtxYuf7IYDdEF+8N7uaxqz5FGAnGHaOJPa8POxYPx9FppchDztHLknXTRQzb0v3WqoY4ypklTGmfAy7WAJ2fF3cV0ISaz3sCLDTc1Di9pHH0sMuzoJhgh9/7aEJpzCe4xtchr3ZQpnY+wqMIxxXALiHnV8SS49zJLEh32RW17WHXcQCOMnD7rGDmXleM3b12YwNKSmJNYxKN3RChqEAbQ/uwkOuoHryihqjXjuat+9vmcTdAuwkw25DPOzkxeQbuDhg1ymJ7WLYeUInUsmwiy26PkHpfgj03HqyTaMabzzwgCNDJbHOTeOhpcrHeIqfuyxlN80YSSyjtQJA2pCE0wPYhS4adrEpht3mp8TmZc2kOur6osXYUUguYFJi9fsbklijm+SyC7DDBIXZhQt52KnXCjHsXj48w3/6D96Pr/w7P7nc5O/budTg3TQq2h52RhJLDDstiSVzbZJTDJDEGk+sxH2NMQy7g20uid383a+uknR09X1gtwxwWFFDgz58bLmsRyIk5fNAV+iEfY6YGbcGGXbcFkCyUXYf7ZQprL1agF3Hxos+/tNI3TdpKIzoTS7jYceBd2LY7dwCrr9Tfc887QwoL2UAHoZdaMyJBNNtNzoLL5C5HBYIJgc2TYNa21g0+rMxDLt0/Qw7eu6tSYIsiY39xOD0+t/EVVR8nvUDdvOEfJNWuHd8gB3fla5rBp4QYJei1i3sNPYz7IoWw25ZwK6bYVfXjWXYaRbn0zd3cUoMu3UksnK/0GUtBiQQfkmSYn0MuwtJifX1VcRoFnP1K4fuub197OkFfSqCgRvknOwwiGG3auiE7JdDNcbHbuhzvpnF1gMlYsaw02sB2pDl4Ne6ATsjndb3uZ4n/R52bOwMhHs5vns94WRDyudhZ7zCfFZRfRUKnTAMu8j7OEqAtwy7sCT2aF5iqn1XT6oRct03qYK+1wagZcGYgL1WqpxZiGlcwNMLcuzAx1YOETF4bU0SbGWJw3C8p0kYV3cmhqhixqs1etjdn1fq85cMu9pdG3G1a4hg5mPY3didYpLGqBu0N1/o+IOAnXj8mvrZ1Rl2rdAJD8OOXQTeoAcq3vBJDztG36QiBk9kWB4peEps6nxSLsMOAO4cesAIGqz5zeC7uPhgwAemOLFS2j7Ajp27SRK3fcUGlFyEewG7tBuwa9hxptlk8I7fm1kLH8Nuq8dQXO7uDUD7Y5qko4xJYil0Qp3PM0yR9zDsdowk1n9s7/8NxZbJqxo//6kBjY8sn3xBN0VTFJi1JLGCfUOAHTF1Ms+iKVC9ktiO69nPsLu8gF3TNN5JoNPDjoftDABIAXvO+e7XpMePzJcsGwyd0B9ZKuQO8nFekJWuIart62zX8yIksSzpG2DWBr6NF3W/nkRq4k03lWHnk8QSQLZ7C7jylPqemLKwzZoEYwtnZ7Vb0hOLeXi3K3Ti9I77c4BVlFe1YYLTdWMWo8QcOpeUWDUGOxs78nq+JKmZF1Vl1aAkr1jRz1BAyyIlWcgKG3zGrmJiWSKc/cXnIZaaSIvpWSSuST0GVE0sGHYjFwrEfpYyf1EPF6VJTaQ+5DNv7eAY6npuBo7rncXnx2UXPnLhIH0CN7SIGeF62LWTDddeBiT2SGKFL+GrD9xz+4bPcsdIHcdJYqu6cd5nN2BHDDt/AMHgomuljw1H98YQFqlUuWxisXuq4gw7weDJGMMuyFBftgL2PUkkPewatwdL/ONCxSSSmYdtNba4pySp2GhTNyIVRbIMw871sEsMw0771ZvHqfds1h5grxlQc5zmpdlkelhuPmDX62En10ls3S43OFJPL8ixA99YmgeIGLKu7UwcwI6Y5td2MuzOzgOwU3/7V3/wN/Anv+MXGZOzAeqKkbv09RhFBrST6xcLvrcBuziO8IRm2b18KOZNwn+MJFaGToh1xOYw7PyLAapaTDQnQz3sRPNX+Bh2NEBwWZa+WVOULmpKz83MY+8deeQAnJ3RBejwwUBK+AYuTrlUiS+exhiYSg+7tNED2QiGXUk+Tk2ENEkvBcOucDzsSBLrMRTnVUqGXf/gQddWFWWYmyRY/TzkYddMbCpv0MNODXrHAYbpr75km52PvjKMZeWUl2Gnvp8hd5k5QFsKd/i8+nr17e7zrAOwG+JhtzV5S0hi+b2bOQy7rpRYBnQMXNj52HJ9AKn5G48kth064UqQ4lDzwDdLzJPK8TBuSRnOtYKSWM950dfcw0aBAMkqoMM51twXOjE/VF+3rgJ7j6vvj6xvXKgx52nBNIe2ZBe6JGC3g7Pw/Syv3QBbdFHWSDXAEunrwmxkmMCj82DYqXNHTeTxomzLuC5JauZFVVkzD7taAnaaYRevwcOOLzpJysfZX+b7yAEQaDG9FYlxhXlQFQ1bcIyR4jSNvaZ5SqinjPl5Ghs2+9uv7+BUA3YPHxwOf91Qca9mYb4+uGR/ssE+xbx8oXMXI4mlvopLYolhJwE7dS7J1+m2L9RuSUms9MMLqkj484T8lYYWXStdKbGAZfINCTCRQNQmFlsPlEhQCoYdN7W3G17rlsSSJxgx7NSYkqJ2POyKqmYqhzS49rS+ylHbv3qZw/OY9bc87JaSxPo97IhJLcc98ziTEpsx0NK9R07zygB2R5cAsPPJWNV/hAA7u24vhTeb77k4duBbq3lVHZ66vjsx/RySiUmwvrI9we5UXY9WErs+D7uijvCBZ+7ijRP2XHVp70/P+isUrsdxJV6P7Ktz2rJPoz5iKMNuczzs6s6fpX9VcHcecEG6FqW37QuVGoYd06/ri3gSCYYdPd9kB42m1x4eeRYUxtAw7ZZMmsEgaqfhCE11qKjRiCM18E2X8LArpIedPq6FD7ALLIIqLU8qkao0yEvAsMs5w65yGXaUUtMq6ckRdQ8eTdMg1gBoFWc4g2DY6eebY4KSzncoJVZTg+dF7QVtXmeU23unS5z3ToZd3mLYtdic959TX69+hvpqWA4DADsPeAQA0wEhKg/O1Hs92MrCE9ElKj4hDmbYcWBjIGC38ICk3NfEd43JsYIfl/SmCzHspAdEcLePGqubn61/r+6Pw+NTfP7/69/h33/UL5dcS40JnaC0MS1dizdVEutj2NG1Mt0D9jVg9/BV8+tQAiyXU/c173Gl5ow8UYu/aVSEPSlpwbb7qP7ZD9jNi8rsyEbGw04/Z1+i+RJ1xkInAGBPj8XH8xI4GcYKDNbiIfDsj71lmXlOSqwA2yeNmuvmMZnbr/CZ0byZTG0TzOceCjPJtq3ZNGA2yiaxZNhZD7uKt7ljQifKhe3zeEqop04W2pZjahepsyxBpdmHd+4twZqXVTPAbmCP2Sq5aXtJADtfSiz1y6H5bi01InTijpbA/pbH1e/feOjpBQlcSTlg17/BL72/x0liV02J7WHDGYC9G7B78d4pPvKCnvcvCWBXIWa9PUliral9Kq1l1lU0HgpygZLExi7DzuPhLoF8e//4/cpGHx4DAKnMvbmUJNZda0sPO/JRbQSwR71IZgCjLLh+PWOA3eM3rg4/tjepfDJWAGFiA2PqluLz8fV5nARlNz/sOGMZdt0w0bWdiWE41lFqxqZr2xNsabDPbDiswcOuruzcDgC/9CIbd+rSvC++NqKWQa5z5HmS9ci+GqdagJ3xsNNjY8jDLl2vYmRlwI7eMH2o8uKSAF0nqs9BOimJ9ZzYCVEePZJYAJhxI2IWp15rJPrBcY+HXRegw3c7ZQ1EkeUCus+DyldmwKIIY5LE8l3lPoZdoc57gUSd38vAsPN469zcU8d929coAcw/g2jm3R52RdVgSgNRnHV42E2RU+pQD8MO8Mti7zC/k3vHSzRYnsay0Tujs6hohU44ktjFQyvLvKIBOyOJ7fe48ckzgVVSYi8zYMfMeJP27qM3JZYD6QNSeQG/hx2foHwgqWTjAgh605mUKZI7RIHjr9hmCa+v+W7g6a8AvvZ/dn7/2uFDHM1LfP13/GLn+1upxoRO6Pv1qFH3TbyBDLumafyhEwSQccCOMexsw+d+ZqUjie2WxySVGjPzTLFKZsgNeNgqunYPtCQ6xLAragbYqXt9bjzszoFhR5JYbUvgMOxyyQocCdj92F8DvvN/A/zof7/qYW5kFVXNQifcRWCmN7NOCbBbKXSCARkmdII14iYhdsf5M2K/TKUklhIdEaMGa8bHAFz89QmUCNSxDgHYmbqskmSmgL7Dw3UAdj71xzjArpEA3QZvyvKijSLOmuDz3ShZ7L1PqWTo2x/vf6w3dEIz7NhcXVS1Wag+fUNdo4dnno1jA0z70x1DJa2E5l1KJRk6sSzzVSpSQjUQsPvT3/NBnJzox/Sx9t7MkoCdTIk15JHYstjPM3QCEIAds7twPOw4u8wdFwomkVxHsq05B2w9Tj2iIdCMSokVQJyQxDZGEutuVFiGnT7/TuiElMRWhhX+xe98bPixXUTVFfAtvxP4W+82ntb0GUvbMY5lOEU/V4sWc8xHGOAqHUMWKu3vfaQAX13bmSDVDMdcs/GjSBFotvS61wB2PSSZITXPNYlGXxMvH7HxrS69MtckYgA3K5mmK+tRA9iJ3kamxMoxlsZ58vfcFEksXQBEm5SDgEyU60T1u0InfEbukmHHDScBbCXstUq7g0u7+g+OT9HInXHuf9SZEtuxizCwmSoE2NaX8uh9DmMMqZF0zRBZNMM97GrDsNOAXWJv/E2tvKxRNe7N/8ievrl8UgSAeXLM8OK9U/y57/sIAKAKfE5FZReWdTzBvJGAnZXElj2S2Gkam0HBFzxxh4F0SzHsCvveqJpEh04gx7QVOsEkjve1HHbrmpX+EMNuwEBjgaAVQie2sm4Q/JJUGZDEdjLsivGAnTcllgGEvjEkF+MNEA7DIK+HRFDqW08b2u171+8F/tgPWMambiSN1wVGLrLGVMvDrothp47/sN5cwK6sG+OP5WXYTXaBPd2AcoZdQMZs5wxumt3tYZdPLGAXnJ/oeMjDcHHkZZ7Ni8o0eEYSW5CJ7/oZdtQs0qbFnpZpPFyUbdP9sYDdz/5j9fX9/8NKx7ipVToMOwnYaQPvONC0jnohBmQQAMBlJPQ5Mf86AIb9Mm1JYrWHHRIAEZqoe3POWzQWT3bbKgpRx5phtysAu8m2mk8fHh0Of91Q8c2RQBJiX91/IOaXS8ywWxqw+76vV4nQ3/01/Y/1edhRj8Q2JMiLN4qAJ6+qa/TYx4LrksR2BIhIht28U6kkJLHLBj352IW+otfpkcR+8MVDzEBgw+Z72NWI0SBGQZYARhJrPbKCLKhVS6pN9P2eEMNOv25VNXZcSMLjQkUAmHPMq3vYpR61hkN6GVoBSWxsgDjNsIvcuYh6kRTsNUOS2KLENKKNoQ0LPYkTZUt0/JohTwS9BkPrJMbUlaBVJj3LISSxHv982iTuA+yuM8BuUavHXt2eIIkjo+xqM+yWB+wWubbw0vDVi4ccsKsMOJ15iAlSIeQLM+J1SwN2r7UksYJhJ8dY6meIjb2meXYNDDv1AZNvhxy4pPdCp9zTCZ1YOM1+6ZHdmRQQDp6xiXCWsNdmqD8tEooib3uKDd3F7DLWFLsAobJeCOo9GdP4MSmxgmmTaMBuPsbDrtATERI16NKNv0oDfs6Vezzsbmm9+Rvy5qJinhw/8Csvmxv9bO5fpJdV48SFW0lsOyW2FNHvsqIowo7ebZBJyU3TOIli909WkMSynUtiks7QZtgZv8S6YXLYt7MH6GtmiCQ25GGnX2PB7/mmAZ59H/DxHwLw1gudoHEqjljMPeA2WLI4ODEyJZaz5ThA6BtDvCmxgdCJUkxkSYghWA8EWanhbOy1/8DHQFhHcU8XoJthpx/7oFb3TVQtNk7eyCWojp9I7mHYndw243bIt8PxsPM0crySWgB2UYGqrv2PJ8COkqar3NuozIsaGQF2qZbE5qTBJobd+oAE48Wim0fDsJv7ALuR/qGbLO1aQxWOh507bxFgdwrycVmFYcfSM40dA/tsjCTWZdiRJNYsxKho0U3smC7QPlRcct5TBM7QtUW1tasa9tPjkUCwr/hCeEkvoLNTcb1vsIqCl8/DLo0jUDDlohrxub6s2d33Ptn/2M7QCTtW3NebrFe2MtXLIOCl7AtpSlwGl69aDLsQyxmw95LxV1pynh3qN0fS2x6GXdPYZOnLwLCjsUMCdmYtGnPf8fNi2JEk1u9h5zDsYi6Vdz9zE5TBGHarbJj6POzoe8eiami1ADt1vZM3HQF1MnSC2P7UTzQdoCWXxG4cYAcA29fUVw3YBTf5fSxdgHnY5a3+3dcLcoWfzw80pJySdW1naiSx8zrR/6eObabXvGb8WgNgVxYuw+7FwwVALPqqYESo9rXZksR6rmNexLBrYQq0lqCxsRU6oR9PbOw1zbPrY9ildEF0e9h1glFOk944J8EXOkEfSMwlsczo0kkOY2AAAXYZKg/VkXvYuYCQ+7gBDLueiVKyBlcJnbCSWD2QNaxx7FkEEcOuQqoSf9JLwLCrGuth11RA0zC9eUgSa1loP/PJu+aGz3M/QJZXNSZ6575JMpwFJLFnmNiFQcdnTnIZybB7uCidyfPeMoCdx2+kIsAuyls+BCkHh6V/HbCUJHZQ6MTLvwR851cD3/2f4+z5XzLjw9WdyVsCsCs8O49AD8OOy/8GAhW+cx7HNrXMN4aYCXpI6IR+LMkcEh/DrmnYIrKnOdOfaVRzwO6cNgRaHnb6/fr8q/QYd9ywBdmGLWL5ppcriWWAwvZ1e98cvwbAv6sKuHNGX8pdqiWx5eSKPQYEfOzoePYeg2mgPADYvLQedjGlxJJNQM/m0jIl7xViQR0vijZgN5Dhaorfr2tkBW5KlVVjJbFibiPw/TTSn1lTt2RIg4szdY0k1hM6ISWxejE9gQBszKKbFnodvVyoRgB2tAknGXZ7+0oSk5+uISV2DR52Ze7eV/UluWbrxl2AAmoTdLIq+NC3OeMNnSCGnQVhqWe7ujMxKdRenzkZJsC/7wLsBPFBAnhOGUmsPuZlF8dDE10pjbYHsAPAGHaXAbBTY4cF7NR5tT3eeuSl3gqlxEKmxNbuuBCQgzoedoGNvDHlYyYlq0hiI3d8Nv7ugmFXi/fXks5GiQtasvv7ZMEBuw28/rZvqK/aV9ds8gc97MIpsWaDg7ztPX2e2bhN4xaI2zSN+f0Yht1cM+wIsCPfYONR3GNDNaSKUn32j15RGwWvPZg7QCBhUI5XN0lixXhf9wB2FDrRYtgZD7vAGEv379YV/fOGMOzoYiKGnby45M5D5yDRkbTh08yblFhibSQTIIrMTT31edixQS1F5UFOfQw7TzPQNSgZSm73RVkZ6qZm2HmMH7uqaZqWD15sJLEcsOsOkag0w8405gMaiDe78rKyDDsAqEs8riOYX31w5t/xYpPgJ2+fGMCvDCwyyjokidW7rgawm6KK3J0fX20HGHZHgmnUmQAWKg/DrorV8e4kpYlep3Lo1jIhFhgVOrEIDOxewI7AQQDHrz0LQEnVdiaJ35D5kpXdfXXPdzAltircwX4gUJGL+56qa/fUZyIbDJ1o3InMy7Dj40Nfc5bYhpPqMBQOs2qN8bCj0AmwBdmGycS4l4hzH3NAIYqAPR32cKRksSEwlnxKssRKYkMLXgPYTa+Y/5sh9z+eFmyzAytr9ISozIvKpsRqhp0BAM+FYef6/+05DDuxyBwDFLZScQ+XPcSNraKqbcpqHQDswBb0y27ycV+ezAfYkYedK4klz5xJkGFHUqolzK5HAHYPA4DdlSsKsGsWD7sD14aUrzcd2aOVC3Ueq0bbc0jG3YZWiAlBPUYwCEeW7PX6Qp58slCTEsslsRqw2564Hpm8GhEQQBVI9uS1lCQ2tJgcWoVgeYXKB7AHahapY2s2keFEpccIGjvMukivH4zcMLHhD+fHsJMedophlzoMOw+QL1NiGcCWcjucZQ+vi2HXiP4Laq36oKvfox5Nb6q2vOnMOO4yi43Ni1mnuaQdfu2fFeVmM+x2NGB3qgG7kF2Jj6ULsHV+4WHYuZu3CjuwTDS70V+b1yRsayqsjmRd25kg08SWs0o9z3Vi2GlFyNkaJbEUkvm2G2pevn+aOyBtziTrVEYSK3phAvDiKATYWRKQY59Gx5+FGHZSErshDDu6mGYBD7uQHMdbHYa4pWeBSkyR2AwQ6kOj5mwrZheFM6hZP6WW3xl9EFE8TBLb6WE3jGFHA51h2JXDBlJ+I1PjYiSxNRu0jKmt/6KpjUGz/ptLETrR2OMFFGB3MMPOJEFRNXj+rgdo0kBbnc7wxsOFBfwCgF1RNjb9Js4wb0li1fMtGs6wCw9ExLA7EaETcie21egNKc9OcBWrwWQ3aT+fkyDplcSSh103YNc0TTBNyAvYsQb55EhNTDd2pwqIeCsw7DxMYKCDYbdkal+I1dhK/3WOzbPzFDgumthaDDs+afGmcKAkdsI87M4PsBvvYXeKKWq9iN20cW9ReAInAAs2ETi25ybFhnb/fY1aaCMt05LYerJvzuMMeTfDbrprgRVPeASXxBLDrqSkx3Ng2C2EtINAFa+H3RigUJtDmzo7XPYQN7bKmjPs3HmE2PwnYGyFZe+dsodhR0xvEf5A7Jesj2HXxbINFfeI7CnahJOhE3u7alExQ46X7q94TVdsITzQdqX1FHpzljYojh72s6I2oXwedoC9pwcz7CSDto8V5gud8Ehi750USFDhsVmBvRlJYsVnwxd1I1NiZchEUBLLQcGVJbEEGvUw7EgS2+FhR4tdYtgdlxvsU6zvqUYy7PT/+1Jix6iiBhWz7wFgGXaRYtgRc6rigF2HJNbcP4wVmFd128N9YFUeAk1bEmvHwr/57z6OL/hLP4yffuaO/wlDHna6ZyMpbC0Au4WRzhLDLnXXD+zaP80ru7GzyQw7LYkNBtX1MuwWrc9HSmKr2gJyWWwlsdQb8vXDNOuGia7tTsz8e1z6GXaLQvTkY6wpRFFK7JPX1dx69yR3PGpL3zqHrH/kqaR94sQP2JHNVl7W7nqFrnEaG1sediSJJcBuQ0In6MIgf5h2Ip2UxHYMENIzjTXP0u8NsJ5NiWG76Zta39zTmC8uGSodd0hiqaGL0+5EEy7DlTUQRZbGkD7jx67iuzoTwbDLGw9gF5i4a33eK3q/lyV0QjDsoijCZ95SzcP3//JLeN/HXncnJL0AOK6nqGorqY0Cg0de1SZVqIknbUmsvj4dSewghp37egTQ7eud2XlRt5lYfSV35ACUxLCLPYAd33Gg0AlKiAXsoqkHsPOBxuZn3/XMmtz5kVrwUrrvWwGws3RsybALTL4SIBgIGPjAN6A76IN7l1ENZtj5Upb4td73mSXEamaA3Xl52C2REps3KXITHLNZDLtpluD3/5ZH8R+955b7C8kA2hENX8BcOmfXjmnkAnNO2tDCYWrAtFkUYNjRvT3d7wTe5gWTxGb2usnL+lwYdi1JLJesSQbxGKCw5X93uOwhbmyVFfewkww7nRLbTKykaVnAzvGw65DEZoJh1xDDzu9F3ASYGYMq94OEvjo2DDuXjRDRPYMcL68K2PFxLZAG2f8UGjDRrMjjk8sN2I2WxMpQmZ6ghE6GXXFqeur7pzm+Nfvb+PvPfxWe+MR3AvAoJXg/nXgAu47P8kwE5yyKwIKX9/iGYVf0S3995VFteGtASqzZNNH99EnjWTdtStHYofuHnBjGLUlsjMkaAhy8xQLyAJgeJhOS2KJq3L6ZA/keD/iU2aYAHsXH0MPzeEq2ADu2ifuPf1ypaf7ye3/d/4QiFIiuF5LERnp+sesswbCLmO8g3zxmc5bjYZdsIsPuuvp60uNhZ2T1MnSCSWKZbJt/pc+NP2eWxq1xlI+nkogh6/rOxPRzp6XLsLOS2PUx7Br9t8Swy8va6fG7iAnt0AnN5Aww7KZpYsBHh9xlJLH6/pTvh36/aQw7Wq9bDzu5m98tkXWqtXi1b9KaZtpDposw5pJY2Jt6EvCwo8elUYnbDwNxvZxa62VmdHnYDUvwktHL2cjdQn4uaRCmwXLesMaxx5OuJjNVw7Drj5l/syuvarvzD5jP7be9TUlQ/vGPP4s//v/9RXzLTzxrH6PBp8NSvb9YN71RU7XCUQA1CZM2v44znDZT53m4JLY2EpXwOduZkIedYNTpndhHD2xjJB/TW57GsojU8W7H7evQDOBl6ZfEDgydyD2gMZV395vJSMoTBdjd2KXr862TEsvTrIERDLuBnkJ9QR++cdY3kRGDrs2wc4878flp8PEt7mnAmQ0B1eEyachDqgXYdTGldROOFDkB8hvGsHviyhb+x6/77fh7X/Nb7X9WhZ0vCbAzpsXqvgpJKjhbPUv9j6EixnaUTM3iQTHsPHMiBxBNMnl7/FApseRhZ+/1RVmdM8NOh06Qh51PEjsGKJSA3VuQYVd0pMQmejF0VqXMfHlZwI6nxHr8U3sksVnjl8SS2mKplFi6BsVr+orm6+2JGAd1Qz+Lcrx8uCpgx72qllz4GEaxus9aIRQbWqE0P59Zeme1GHZ9klgfw45JpPWY9/DoEP9R8iuI0eDqRxVgd7wo3Q3jKrDBxRbawcPWYxgFWkiJrCl+PXCQcaxnVF0xmXqfh10/YKc89xrMNMPJ2MtsYunPyTDsGre35wGI586wM6ET1lKEh04oDztGWOEEEnYtcDUXV38s62Nn78d2L+mTxFJthdhagnklAbvGpMS61gbUB1NfWUWJuyZnrPC8shZHG2m7M7uivuqNv6A/YkgSm9h1u1yHWAl1m0GXOaxL9XfmvMaRE57nq2s7E9PP3V/Y/wM8oRPGq3A5hl3TNGj039462DEbGDVT0VibsDaYLAkTRknU8R5vaULJaw9Yb2gkscRilhuGBNjpsXFTPOyImUETZ1sSKxh2XTsRstljE5w1UWQMOxO04MpTCbDzMuzY7mSGyqQ72TfEAbsBDDvfQnWgsaJsQqSOvK/oposie0FSAMeCA3YsPcZXtU5dqS8Rw66QDDt9w3zNFz/l7Pp88qf+Beqf/SfqB91Q3C3UdUIIfYK6DdxCsUHJawlxYlNi60JdT7qZmzfZIEnsNkliBcOOdmKv70zNtSAf01syVQpAEalBc9vLsNNsk/Ke+tsotumOwOAFmLMTM8TDjjXM1ekhAA7YXX6GnY8JDAhGI6/WJsWwRZ1NifUvYPyAnTtWO8cViDunWynxAXt80yKwQ2WKBf1QyfCVtVUwdCIsic2RIY+o4dkshp23uPcSLZi29Q5tS1Lh3zSbJLHrZemplOa5lDHseiWxewx486TElrUJCYjTiTnOxTkz7FoedqtKYuUC9ez+0se4qVXWbGNMMOxoo3TexM5iYani/qUjJLHEsMsgG2bmaQSgFqbmg8qXEBooSjkmFr2p9JwYdgM3hWVF+jOsdVDAJ16+g7/9wx/Hqw/WB5CfR9H4JL2Guhjl3pIhOIMZdgywSzL7s15c79z7iP31XI0DTQOc8DmO+psotmsEYJAfIY3Z+1pu69tgBuBe31z212PP0yo+Dvb5fQ2QxJ4VjN0EYIEN7vFqSiZVn0shxj8OhqQj12yDS8qRE7vhmcRxwMNuIsAqe76tX3rsABmDgW5RhYfxSjhgLPovDlpvyfGRigE5ZWUVRrFWvMUUOmEep9e5wuuujhIVFikeB6jPyMwTYxJsL6poI0D3UeGUWOb3yiu16yjp+U8gbd0ozIaHfzqSWP3/0ve3q3anKWaxevztU/X31/SabqY3Sef0eoYEtdx1d3RWItF9/JXdGa5tE0nLYjV2DeZh2ImXpVMrN4J4EZHmDVJjctsBGmPl+GqCf/RnujEMOwLsuKaeVcs/Z4wk1tkh0LsaMQfsNPujcRFnK4kNMOwY26Plo2QGm6THrNyV4To1MMGLLiy6mKYdi23/39tBOIoioK4QQf3fouaAHTV3IYadOk6TunoJGHYq6CBiMd/qPbzn0X38yJ/9Mvzr/+p34vHpHH+r+huIf+gvAK/+qlkA3F6ov7m6p5quxAfcQoHLxhshTjHnTUZxahajimHn947gRXKZFsNOy2n2ZqmVzY5l2MlUKcAAENvSkBt2gLpeKr8rHDzpMtvMwrl7oOHXcMgQ2mkKWMMc6Wb35u5EmQv4DJkvWZWsMeKVhJK5lmXYBYI+aEz0LWBoMvaFTlRizAmFTjjSWR7k01cGsOMmwOcM2NHYbMZxz7iqx8QCKUojid3cjQpTBBYlUztebxHDzpXEyvnEpoPZ3faQAXXSqM84zjjDricldrrX6YG5YAw7JJmZ9xZFfU4MO7f53J2qz9kL2I1JzZR/OyAl8bKVmxLrzknO5uCqyfK8PzOAHbt2ApJY2pgMAXZm0cgT5YeWD6wJFAEorQWpZthNsQaGneNht4TEF1aBkWhvnWlU4B+875lWENamVSUkXlTEml1aEtvrYRdIShXBE7sPP2V+FZ28gSux+ruHXBbLZd+8BoS8Rad38ZfSf4YvTj6uXjbkYecw7Gb+/x9SfBzsTYklhl2YrakAO9tjn2EDARMqIYk15Ad9/xHpJE0im7i6dsAuxLCrkcQcgGCS2DgT/m3MA54BbFyltmzwRMXOARX1uDYEUn3GD5j1CQE4rTLruMpZL9BzEXhaR+7auhU6QcQJz4ZGXtbWOmET1xgE2Okxqd/DTkpi7Tpf+uPzz6msbVglMeik93VIweOrKIqwk6rnu3OqvhpJrGTYLTlvUd0+XiCO1GtMswkONGBnsIu6NNf0xFESqa8tfCqwEcTrkT01jpqkWA42hnxC6f3RZ7opDLtSMOxqwdSQi4VOMEqCHbQbWDcWCeWhE8SwI9YGedhJSaxMZ2K7FW2GHSHBiTOIBI91hdAJ24TEzvvJBw6irQU4G6AXDftoeYiEx8uCQicuC8OOJ9z4pCFP39zF5z15gD9y/eP2j177NdNQvD5X7/P6rmpEUtTOpEJVlFYSizjFAhlqumWKM8uww8RStTuaLpLLnAhmEZkT785SG0wxtoH2sNNI4jfrkMTeLDRgx/3rgMFMl1DghPo/bTgaCJ1IFqp5vrk3FX5oG9zM9ZTZ3ZEpsSQplfd2K3Ri2D1nGpVQSqxnnOUx7lTW28F9bCh0wgEcu5KyZdEmSVQDelPh7NwYdsIvozN0QjfhSFDGNE5eBoadXmgSuwFoMeyMpCLAsMsSxhAIMez0ZliUTi34EHkksVKi2+NhZ5nLGUt6rC7Gw45CJ+alZbRuXdWvu4KHXY/f52WsompQ+lJim8Yw7M6qpJfF31slAzMoJbY4sf1YQBK7aPS40pLEkgSHmBkdoH2oQmCNp2gTbpZdEMNu4KawrFifp+muBuxQIIqAJ6/2g5JvZgU97MamxEpJbC/DziOJBVrBE9P5G86v3zlVLLtjHjxRtns09XP/Zu/v++Cfwh9LfwT/5fE/AqAAMG9gAF+rcCnr2OAJGn/jzGUD+mqgJHamGXZlE2NRrbz0PL8KetiRJNZK7owqaklpabBo7BEedpZhx+Z23oc5/m322uNqrjiODICxLNDo97BTX2XoxL0TOycE042ZJHbBwGhi2EGvJSqZEkv9dqS+VmTr5JGZF1VjN3Y2cY1B95FeI9kN1wDDrjWOWGuhShAH+HqkrOuWEmiSupu7ixGAHQDspOrxxEa9vut62M1bHnbL9f73T3O2Jk+wp3s5sy6vKwuoe/wVJT5F7YCcV3g9ckBJsXpMdHxC+zzsNGBX5eN6j0CtLolthCS2hWCO8LCTckKxowG4SHHaI4md6JvYOZnM/yND2cGwS71gkD22Dr+toaETLUnsch525pywC2lecYYd3diN90Yhhp1pagngq8u1XGTrrpIl3HQFg7xni8nGXv2QWWC9cqYHlT3V0CSovIBdWTc2VjxOAEQoaFGfn1gPu4Z52HU0XTt6t+FUgHHU1O3PMgbYjZXEih05AAvNsNtC+5joWrtVvqb+46oE7IYlBXcN7H2S2Egvjm/sTl3/lk3c/RpYRi4xNCWWAALasR8tifXLkH2eKjwdVB6XDJ2oBMMu9U14fGe3rxgTmWSxQVnPqjUmdIJkLk2C0khiN3OjwikZOAFYwO6MPOzsLjxf3BVM0mMZAv4FhwPYpR2SWEeiywE7n4ddbdOCk8ywZBbleTHsXA87K4kt7GdN/jGjGHZigbrGY96UKuva72HHvj+rEsbKXxJoNTIfxrAD7PUjE5F1EfulDdi5i27b0I+RxPpZfb4itvCWBOyMh11xPh52I4EY8h3c3VMA9RSFkjTJ496g4hv20hx8bFBbSxLb62EXYtjtO8+3l7uA3WMT9XdHHLDrZcaEwe5bxx8DADxZPGf+zwtS0vUdJS7QNpbRYgIn+sFqs2mUHwfDLeZFhVmk3t8ck+EA65tRXGUFICfyg7537KZszBjqF8ewcz3sGve6iiK7JuKWUmSuL9eaSx63z1OS7s1YrMf5Z91ab1Mxj1F6fBpHiBqyfdIbLwyY4dJZYnjZ4MT2GjznBIxNXGMYSaya64ix2LLR6UuJLRemx7P9u10nFFXjBI8BllxhJbHjALvtRL0eJSobDzvtMWd6/WXCn1jdO8nZmjzFjlatcYYdqThTh2Hnt4ehdU6XJPYRnRRrAkodFnOAYUefEd9QXwMBau2SWLnwazPsOnYiAgw7vpjgdF6Sx6YidKKSDDsHDLC7EH6GHVvsdfmeeKKrTZlmqgewEzcV3TxjPewsw455RNQehh3gvWgsYCd2JwKPf7PLAYA60tKemLIG+fAFC9idaDnovloYJAGGXV6xAV6fmzymMIYTc27mmKAxFOx+D7vjQErs7jQ1oN54hh2ZdjPATvv7TGWCHuw1d62+o/7j4Cn3AWMZdkMBO7aojfQx39ibhg2ZL1mNT4kVgEGVD9p98rHl1Ov6Qf+KLXp8klgJJNaC0UCmrA6wEzK/9RV7DMkhz10SO4hhp+cYJKjiS+RhRwvNiQewMx52fnNpA/amUXgXVxeZ+SeTmQUfULQ3lQiwS7fUmEwLPc+5VKET1DhnmFLyocOwW8+8U9VNSwVADLt5UaOm8Wjrin7dMQw7Cdi9RRl2JtyJbfixnuqsjtcbOpFtAdDjpwl48jOd5nqOS6UklnsWg3kfLSWJHeBhV/R72L364Gw1ryufh92IhU/TNEj0eZrtqg2iKQo8cWUAKPMmFvdXlWFOoz3s5D3bxbBrmsEMu4PyjvPrR1P1d15JrPSeGtA7+mrhk8Xq66FEgr/83l+3ljFjGXaG4TUgTZMA9qYOblqcFRVmuFyAHalmFrV7DnkCZ9Yzfy5dEjAlkklUOimxjocdXUcexmZZucBEMNBg6OF5GK/UI8aNZUABAwE7FvDoWFgIe5OagZH8nG8ngmHnk8RyD7tNZNgZL0jNsAt62AXIQol9z1KyzAGpqm5astFMM+ykJHYakjCL2tLnv0SKJI6Mt9yslRK7hDUFq/snuVVURgl2taenI4mtCRfxhE6wuaRpmkGhE4/uC4Ydx6lCHnZ03fL+fA0bumtj2NEAIM3LWx52nQw7v3Effw7OsKPFagL3pjaAXewD7JiHXaSYVQ7q6uxQdRgkroVh51I3uwzjfcU97NTrqWOqmggFl8TyBbVnIdRISSyfpDeQbeKcnw6K7dWINWOHL5jz88KxOjc3D1QTlkY1Hvg87Mq6JbfOdfIqsVgA4AwTFjrRlRLr97Cj0AlHEjvaw44xFHQttE/I1ONhR43GtVq/j71H3QcMZNi1QGNW3t1v9nwJAXacYScNmS9ZFaIxouozkG2IYQcMuudoF2kqGXYB0N9NlGaAXeSniktJrJdhJ73iuoqx8G5sqec6P0msu0PezbBT/1cgRWVkfZcAsPMy7MjDTjPsuG8Jm0O5nJrGgWDohAbsYsawU5LYAGBHx9MliS0ZYBcHPOzGAGcdxRfy9Do0xgJAnQtJ7Coedm9Fhl1V2/R4wN5bHLCrVgydqGvbY1GAjfGx03O4kcTuOH9KXr1JqGGO5Q78GMAuANZ46kzP10GGHXLUjSsPG13cw65jozJ4jEVl2M3pTN2nO2mNP/E737H8MV1A8f48CYQseVOrfSXv0Q7fNeexQQ+7ByiqGjd0H0UbtzdS9bwPBzHselJiRT+wpZlq3vesr4dFHeH/8/5P2Xt3NMOOGF4DwNyM3ZMBWey8qE3oxALZ8M/rzajaBResJJbWo8xSIh63ZhtcnR52dqOtquv2WtQDVlmATUske+b9vpKSS8D2iLHwsFuwjdng505AfF1asChLDLAT0Tge2euZK+9mmuFlggg9oGVecmb/BpICaBMgdyWxYQ+7UOjEopUSK2XQhWDYyY3+rnWdryh0okCCJ69uGXbbVgiwW1ISe+/UZdiRL3zJmJdGJu0hJnBCGV+KSeY2r0dagB07dpoXWupQfd1lM0sYWAOWsjaGXQixb6XEDvGwowaJKMhcEssWwiYBhTX/gG3OKInOAQKZ/0eGCk0DHHF2Fd8d6ALeujzsBvqLSA+7ScAkPFSWKeF62BVI3fMepzA71p6moCWJdRh2I3fmLqBoUIkjIOr4jPYaK3do7j5jvn9O//fNfduIH521F2pl3SBlgwPAALsTu6M6x2SQb2HIw44ksXszK03x7p52lYdhN9f+PtOm/ZnTQH6jVmwc7D0uHqB3DnoWoTKBkZd395uBIRN9XDf3puFJ6JJVSBIbTInV99e9ihlEDwCMQgw7b9CH+Jk3WV7mHNAKnYi9KbFjJLH2MTe31eufH8NOetgRu8bHSNCbHIgZw27zNila5fWw04BdfgwUcwew43MoD0ZJeySxmV5kJdnUNIQz5E4Tro6HADt9PB2hE52SWDPurAc09aVYT9LYjFcGsCOG66iU2Le+h11ZN1YSC9h+oLKbg4s6Xi10wrEs0fesTIo1klgLDjRNg7leTCcBD7toJUns8NAJGstmAYadAlka3DleYWwZatcSqONFaRgm2ZYC7D7/sS384S96quvP3vTic6bcCLMeSQP7pZZnbMf93gnYkST2Ae6f5ngk0hufj3wOAOBGrK7X44UPsJNStp7e8fSe8+PjqWL1+SWx6jqkNVDJmCejijZMeHBFqOK45b8ly2HYNZPx/e1FllnbUeiEWF+xTVnqv5ZlqgWLzr/Xwy5y5+1aAHZ0PXlSYtv2S+fBsAtLYoPMSuYxauSYSczG8bb0kZ9zAuwMQO1RuTkpsZsI2Jl7SEnL00BvPgT45yxQKu57aEEtTRYyG/3q76i/I/VDX800w65oUrz9up2jKXRiTmveaDXA7r4jiY2NWqL0XBdZjySWf9/FsCPA7s7xQoH1dF9xUldAHYpkslZf5vVJYgOhE0t52Bl5haZ3swEyYkio+kCa1k1IKHwW69fi0q0oMid5VxslOrJYvtjrSjTpZNh5TJo9FaIpD6WLF4Yp4XrYFUhdYCCKwCOfZTUVUcAT+3izS7N5i1dHX9/RuM4KmwhG8ssmmeC+vm9uXrGL3ePT9vssKsuwo8Z/EelrUzdRVTxBg9imxHbIGojZIT3sTOjENLVsk7E7kB6GHcmFJlIuBDvR3mhWZNgFwg8AC+K5gJ19vmlUYJbFink4Rl65wRWSxCaxOyHaP1Dn4/ZZZHZy7x6KJDtPhcI+QimxTox70t70kMxoGqZp58nu9i0piY0is/t5Y0v4Wqy7xnjYsTGzvowMO+7pNT2wDdHZPUc+xsNOvKETgXnZAnYzs2idIW973xg2km7W+kInuCSWj3lmx3KxFv9UGkfjyF3sk49dTZ+1Zth9+PnX8cbDgZ8/vTdi2+RvPcCuqGomiYXtadjmYFHVKzLsxIYqYEGyPCyJLaoGuWaRGx9j85y6p0loE7cDtA/VGElsHpDEsr+dosDd4xUYdo6HXZtF01fHcwvYRQSsb+CGrCy+hpBpfi1T876SoHpXf0OPTaZt1j8xcs/u48HDY1yP1HgcPfK5AIBrETHs1pASe+YCdo8k6rm7POyIceL1nxxStGEyRBILtAF2UfPcetgtLokk1gB2tbsOtD1ebGyZlmWqBavFsNPjnPCwKx0Pu4n7lUtiBYCz6nFXPmN/42HnbpjyzzooXeehEyUDi8TGiwvYWeIG+dWbucrjC1mWJZKocX+/SUXqhKYCijOzZmj7Xvd52OXm3DgEJ2JVVk0rsFJu9I9l2B3o01kiwdM3LWBHBJQ5fe5LbDTxundSCIadeuHS+ExWXq9uH2GiayOI1/WdCdI4Qt0Ad45zd3wIkbO4JcfAtfSQWpskduJb0MEniR3gYScYdtIwkypLYtv4A1bn3mLY+Qe03Uwdy32uq/fuYoap534PO/oQu5sIuUuRJYFFfaCkcaRdfCbtm7wjxa2phYcdsNaLbN3l0Hk7FuPx/H7r/6qparS2Jwn2tmwzcrbwSGKrxqQPGT8GYthpn6gy1gDegKQvMshsMewWNnTCLl5HTqS08GTN4FlN4Srt95YlMTKUuAYNDu0HGHZ9HnaVei+dHnZ8cc8A4Cly3NidKhA+tGt0yaoQVHQqo1qXpszM12ahU30HAXby3tcV8sHM2STGNz2sebH7eALw6G14TVsNYDdAEgu7kXJ1S9Dk111jPOz0uFEiQZNs7pjXKlpMcolgHDNZ7F0kcQT6qDnDjjdroSRZQDGYJiSJnUzNmKAYdmJ8kp47JKUKMOxS8tWMuYcdY9jx51yh+OYOv+5pZ5YWpsVEgW51cYbv+tkXhj05jWVGTvtWlMQ2LmBHG1J63MoJsFuFYecoIPT4L5MnCQhg13tR1Sj0plRS+72I2wu9EWMOveZKklgO2OW4e7IOhl3Hzn7XMTJJrHlPl2Csq7sYdgGbkWCZJOsD92dfFR0sM+MXeg/Hd14GAAUeX3saALAPzbDzpsSKHqcPfBUMu/2kXxJL13tBXtYjrhN1rMTwGuhv2APYLcrqEkli9dihP6d5SxJrwS9SUuTn5WFH5z8mr85KSGIbFxwAvNeTBNjSjnl/0OF5GHaJZNglBNjZzzqvan+6MQNyqLeYpnGPJNaqWciv3kgjBWhZ1w0ifg9s4jpjsgOjhMuPDeA0OnSCMez455MykFbaaRlLs1r5upnPYGAY0d5EPV+TZPgjX/I28/9GEktr3lU97E5dDztaU5eNfp912bYKg2XQcWIC/74rJTaOI9zaU/3Na0dz/8ZZXbqBO5zQtYkMOzo5ckFaMBSc/+x/MgLs9CBFOxqeDwDQAyYH7PTJK/UCLaNFgRzQ9M26p6/vB2ecYcebomUZdsOMXivBxrESwmEXc8jDrkTqMCqc4/Q01C2GHdDvq/EmFoEP0x6GXSsRDMBicgWAMpKMmJQvz3sYdnrymRuGnQbsEvWz9bDrl8TK5tKETsxS5skyVhLbNjQmwG7ik8QmEW5BA5pxZhtQ8wBmptmxyOkMnfAFILBBa4ZCyWH58V92hp1nZwtAb+LTWZUg13T+09MOXx1dLTm8rpAPJnneyTHUAnbu88vQidR3/Jz2PaBoEXFdM+wuzsOu39qgRMwYdpcAeAmxf7YsYAfAmwJLi4ssjZydR9lIF1WDiZ5Dk5Qx7HwedvJ4DMOu3aQsysovieUedsBaATtpnryrGXb0Gi+dafsAFHj2docRPS9agJuE2bcew05tlkZ2fjMMO8tMLaqG7e4v8Znx+YXu1ZYktg1QF1VtUunigIddZDZxV5HEdoMWTdOEU2KTzGwYzFZl2FUW5LYyyuFjqGK2khm2Po8b2N/JosVnFLWlSwTYEcOxt+geNSEzHYClBE14sYCf+d2XAAD3k+uGbbsNde2c8jkuuNDuSYmdHzo/7mnAzstWYqETAEs4Hcuwo/MyRBIL2HMUmDsXZe1KYjeaYecyxOYEehpJLPV4zAP2wjzsFGCXcIac8RImQkq737EBh9rDLiS3HFjVEMCOJLFsc69pAiChJyV2miYehp0dx42XYBwxwM4vic2r2lUabeI6I4ocaTmdzxZmEiI3pHbN7vUYZCAtbeBS2ARfRxRVPZphR/Pvf/dVX4B33rK+yjx0omma1T3sREosKSWMZ39d2vuTh070SWI7POwA4Bb3seMel5yswHsLbpm2SQw7KYmVNyP9TGBFELCrKwD6b4WRX1m3PwBAXUy+m5CSYjKiv8qJUt/MezoK+v4JZ9ixwbpLb93lYTeQ9lmIQZRujqGDaCFvKrbr3RoUOy4aYtg1l4Vhx8GHrpho3TwcNXaH/DS9AkDr0pnMYbFoNzQFS4klcK/NsNM/D/AtNAy7liRWvfbeLHX9nMYUfU5sIiLALpX+PlAT9iORBuz2HgPkgDUweIQW/97QiT5JLHLc2BFykE3c+RpRdtfPPZ9hDzsN2NWxkXedevwUZYUksV6QFGFGXohhRxsvNJGZIWZZDztYwO6qkcSeU9MuPewGSGLLJr1cDDuzmBQLKpJnUtJY0m7M+YKDey1KZndZ15hoVkTqMOw8KbFGsigBOx/DrkMSGyf2eloDYy3ksUkMu1ifxzul+uxTVHjh7kDgjTa/6Jy/BRl2dE20NqS4JJYzI1eRxEaxpfROmAdi0wBFm+2Wl7XZ5GgDdu5Cz+zAL5US282wy6vaGFhvSUksYM7NNMqVpGbZ8qk/RgAx87wyC1uzMLwEklgDDngWVS1T874yqdCaFdsFMJtNUM/inm2MFIeKYXeU3TDndbtWY8iJD7CTz9fXOwrW2n6sxp1uDzu9cdcsuUAuRjLsCNgLeI8WVWMksXNkG+5h54L988pdz1kP2GjltNVgyfndeNjVTkpsVQ1l2Ln2S6uGTshQA2CYJBYIYAD0PA0H7GJzzuOk7WFn1CxJbJRQRhopFE9qLcfur4E964UXyWIXD3t9r1tydUayoXPsY9gVVc3stIhhZx+XV3WnN7m3NFZz68qe898z5oG3KOs1eNgtrKw5TozNlNmYaCoD5PK1kQmd4Ay7gZJYQCTF8lRmfh3R/9eVtd4wqffYEIYdSWJTP4OETh4hrUHqMG8cZOhEQGbWYtjpm5R2l4y3nWSC6Mft6HPt97DjKbG+hV5HQuLABK/QINryBwqUkYamrodd2STtm7zDJ4NSYhvu07HRDDsmw+wCR3XT8VzziPmvo2gfAPDowcya0QOYFz7ArjFovpm84QJ2BUli455dUgA7FDqxcK+ntXjY0eKRLeBPSRLrZdjFFrDbf6z9fAOlaZ0MOyaJbZpGb6+xlNiowa1dYrq0AcfLWIZhJ4CxOA40SPp9n1QJci3vOpv3Awate19XFpBoyFQoqhDDTu6gGoZgiPY9oGgRcXWqvg6WMY2tliS2w7+KMxLWSF0/9wqBCVO7QwvA3YmnP2UNDW/U2gFRjdkQSyZTx8OuNT7RQs0AdgS4+Dzsaicoyo4TYsNuLQw7v2SfvE9iPW7eztW4PkE5PMmTrv8hktif/RbgW34H8MoHBx75ZhRdE42cZ4lh16SqX1lH6ARvfnlKbLmwj2GpyHllAbvW69aUbryCJFaC0IHiTOGZT0Kkx8cJStxdKXQiIMUZWIsFu58uEcOuEgFIvLYNw27geWgBdl0Mu3aQl31hzbA7u4fm6BX17ewRM/7OGnXtOHPcACmbtwRgtxuTJLZjPtNAXWFSYscy7EZ62BmJtX8MzBnDTnnYXQJJrAmdcAP7eLCYAUHW7WEnPQSZJDaNY9fDzowLroKMf+ZFoJ9blWHHgY44jhCjRkzEG0qJFZ+1lxnqhE6wOVuAf8aeoSotkSeOjNTfSGYFaFlUjXlME6cWINy0ov4tPw7LloPjiN1wNgw79j45AGjUefr3/HFFaT+D4YCdn/XH58N5UXVjKgPqwSmbw+LEbLxa6X9lSROeQBTHnWlg6AQAPLKvzq1i2LEUZP5+hfpAPYZ72G0CYKdPgJHEtkIm1M9bEwL0Qgw7DtgRw871DJBG7mlsPeyaKDEsIaLFprSbGIi93tbJJkfcZ4I+DCcBZGRK7ECGXSkurLG7NS3DfyZTaQEDpinwMezoHF4Ohp2TIhQaAOra3CDPNTZQ4V6jBsRH9mdAZKU+IUmsXVhqMMUAdspXxHjYDdjxNs1lUZnBIi9tKtLelPk5jd2B9IROHFfaqFb6+0DRyC3D7tHW75EwhmkXw24AYAdoELoqYFi0uh7b0u/zLSOJpYnQz7BrDX/6ejkpY9Ncz+fdA3vNJtwWwy4kiTUgjZDqRu2dJ/5z0smwc8fVoqrxgWfuBKWuBNjpzaqwAfGqNTR0grG6S8QbPea1ynjGCYYdTxoDvB51HOzlm2CSYVfVNtApzWaWYeeVxIpQgJ7QCS6Jbfku0uewBsbaIrBTrKQUDZJafdavzXVyfDQCsKPrhOR1xYn/cVUB/NA3Aa9/GPgXf2zM4b/pRddEI+c3w7BLVg+dkAwRwIaX5Kdu8iQLWclLK4lthT2ZRbcInRgF2Onrb9LNsCN2F2fcOJVaMPju0GvLV1zqP8AzV1aes9c2gN0lYNhV7QUY1Ww0w05KYrsYdkKWyIu8Qk/uIjl+DQCQb90y1+e00gw7vjkb6nH6POwES5kAuy5JLF3v5rofHToxPHAFQG+6d1HVxsNujuz82PXrKLMgJ4adWF+RnDC2HnYrM+xO77kWPtITliSxkZsSW9UNI5lQSmyHhx2FToT80QZWyCMtc1hsfoad97rlHnYOw04zxRJf6ATzEjSSWH/oRF7Wxt4j2uQ1hodh15JbB1Ni7eduAFoevMA88kshiY3jyFwTRdV0ruu8FcBDMrYpfFZU3TZjPVVUNc7mrDePLGCXc0ks4SLs2Ok0cHyq7tgIkvXIATHsFuy9poJhJwhigJbEbpCHHZ0AWjjKtEG6MGZa6hcc2LoYdl2SWPKpYzeh8bBrhU64sddTDdg5EkVHdrCsh92w3U/LxnEH0U6fP1YtDzvaAUKCuhHgadrRUJOHncOwW2HH/JzLed+hxTjb6ftw/Xbz/RuVGhAf3aedK83uyNsNTVnVhmEXk4Fqi2Gnfm4GSWLtgoQazGN27e2uIomt2rvBp3rXIfEw7JI4wtVILeqbreut3wMYNNDkAQYL4IJJeVl7n+cRWgu9RSSxNo1LMOxoM0EidvpzO61SI4mdn3UDFXw3NxPn3TDsAjIE+TmFmH80BMWSYdfhYff//slP4o9828/hv/n+D3mPm+QKexPLvFyq7n0S+LFvBuaBcA7pYRcKneAeL0jx/FNfBfzR7wf+gz+53HFdZNEiTkqWqOHLtSRW+KA0TeOMn3wTTM47ZVVhqufXmKXETr2SWJJQ6THDsOQ8gF3JJbETC9jRc6brY9jZxlN42E1TTFAi0oDtK9rDLkOJs6Ia5q9IfcV0Xx9vYK585Vfs9w9euhyAsC7qUZpYAERMEls3QN2xIdhbYoEMwPWwW+iF7GTXYUYUPBBDspNISpXqzQQmmRlUTdMGoQNF14qXXQeY8TFblWHHPezixP2/AZV7GXabfy3S3ORjQVhJ7FAPOzcVupth17GJuHtLP98JDk6fAwA0u4+Z8XdS+Rh2Ac9XD8DilGTYReo9+FhqFZEckODqdmY9vUYz7NqKjc6ijaMAw65gHmKLZjJ4jfOmlL6nYtqkr2zohPJ6VT+mSWx63JXez/wI+EdfAnzbf6wAqrqynxedf32NpC0Pu8azQdm+nqSENeiPNrAkAEjPafzF2PFI8oF3beOkxHIPOwLZNH7APexq+56on2gBdvrvi6q2YOImrzHYhqvzGfMKjSOM5e5jQPKgkhbZB+7aIbTRGazQMYFtquSMYbeEJPb+aY5YXF/kRZzXNnSi9LALjZLII4kdBNjt+TzsNFOTFDxeht2medj1SmLVz/ShBRF9DnSYC0+ETnglse1mj+jgbcCOPOzUDTuLPIAdp+B2eR/Vnl1hqoH+Ir6U2Cej2/iMxcc7/46q5WGnzyHJRJwbvQOAMx52/L10AXxvcjnof4jNyHb6fr7+bPP9zzXvAaAlsQCgGXaFRxKbV431sEsEw+7kDfWYWC0uo75dUqjBjz7rU33NkX/d9iRBEkcsdGLEgFaVVu7HdoOPy0CCHlSzsQ/VCNaUmNZ6UP9AYwJAfB52LcDOPg8xI24Q3vCWYdjRRBjwsJPDn75e5nWMnIyiF92AHQdL2h52/kYsD4ROpB6quDpO8rBTP/tMW62Hnfosv/WnPgkA+Fe/8or3uKmZ2p/YnTzJyB5U7/3zwE/8deB/+hr/74d62LF7tUCCxcFnAu/8PcCNd44/pouuYhjDTvqg8DkhS1RyqmkMJcOuYPd9MrFeXD5JbCkYGR0Mu0VRW/Z7nLavWeOHdH4Mu91ZahgfAPD8idsz3DsdMO/ReNYH2N1/zn7f1MDrH+l/7g0pul7aDDvL5geAOqZ+YRVJrA+wO7YMOyaHBbQXj/Ho8nvYxcmSDLtyjpancqAoWGDb518HmDltgmKNHnbjJbEFv58JhLwEklhiQvgYdlujJbHEsBviYdfBsJvumbH2qbNfBwDEVx4312hKDDsO/IdsP/rYkgKw247U8/iYSvO5+jwrJHjbtW0Uy0jBgfZ43ldpeLwH1DhMfqgFkqW90y6kpIcdS9rlfZVKibW9zNL1ws+q9cSdjwOv/5o7hhpJrPocE9SKycbDLgKhivx6kuCECaNaI8MujiLXJy4kifWBhMzbzPinZVYSa0In2HjPe+1UP85c72I9tigZYLep/nWAs+FKm/5tD7vQOKJ+bjSwDAjAjjH2fDZj1k6nHs+wM4BdGw9xWNCRi1WMqfsnBVIHsLMMuwUD7Hx2QXFH6ITPG1XWI14POxlwQh52gmW6iQy7LHBxFQawC1x8VNzITww4dGNKJJR72DXsJqSb1uziVwJZ11+nsQZNHIadx8POC9iJRSGv0R52sX4/Md4//dP424d/Brj3qc6/BbgvlfBYgAccNSCop0EzoROXhWHnkcS2ADvVMDXJFB9p3o5P1o+iuv5Z+PHTzwRgb0D6+7xon5eSp8Tqx50SYKdfb5Hs6Nfpl6hEUWSaemrkyL+O0m6mvqCGvqrEwlrXsd4ZTKqFGzkNNXgfRBqwm4UAuyEMO783GqB2xGnAn5e1wwIkL8AbMyGJHeqZsqFV1O2JELDU9JYlgH7fp7Vl2OV598DOm8OQJDbEsBscOtHyPPEBdi67+fED29z7dm6J5bI7cQ1uR9ezP6q+vvDT/t+3POxCDDvW0CIZHGG/EWUWVNLDjho+DdgxGYT62gZ7JQuPqsrFwoF52AUZdkYSy0IDRHG2BZfEGg+7wLjzr3/1FfyX3/VLZpNjSIUaz4OtzHgqARFePNZeLvq47g0BVgzDTp/zEFj14EX357vP9j/3hlRLEms87CzDDgCqVQA73vtREWBXnAYBu4UjifWnxBIz3oRODF0ocOChx3h/HkqINX+vJbFRiTtr87Abz5wiSWwZsV3/pl6K7XCRZcGBdo+xxWxGBtUoD7ueTcQ95f17pT4EAGTX32FAvLQ4BtCYjVkA4U3JPg87MYZukxecp0c8W6j3U0UJbu7NGAN1rCR2rIddvyQ202xtkyy9qWUAOzUendWWxetsePGU2FUAyJd/yX7//M+4817qrlO6GXaJ81iHYScAnCB7a2DJtSs9Z+pj2A2SxHKGHfNPMxsv0pOxEqET2sOuI3TCMuw2mBTgkcS27pWQGilpz8Gp42FnQVqruLG9OLfTWYwG7MJjJWE/i7Jmn/P4++XeiWDYcUlsbYFAHqpG1RU6MYRh9+iBGgdfeyA87ID25hkP44uizWTY0cBVN0p2Q0UDGUn9ggOEz1CX6N0BmVkWs5RYBpwZDzuIEyhCJ6Y+hh0f/LoSSOWHxmtoSiwzzQRgdqAAuIN4oFrJj2LX25lE6Dh9jDnfDreJiN48j5NhDDvVmEXZFna2t/D787+BZ7763+KVY/W3hmFHDX1ZesDm2qQPGYZd4w5Ic2LYGVlD92dugyfU40gSSwPPUpJY344cLMMuQtM6P2kSGYZdGWLYGZnDch52ADAjwK6oHJnFvFHn69pUn/O3iiTWEykO2F2cliWAPifz2oZONEX3wE7nPI2jlkyI75LxsrtOIcDOfQ26F2xKbAfDTn9mnGFyeOqOG03TGEnsTmqfYynAjoXFeO+3UR52qgokw+n/m1BSgkplQicIsHN9UChhG7BztkknF+Nfze975sXR7WEnJLEexkVRNYwZP2GgYt35t//1d38QP/jh1/B3fuQTrecMVcg8+cpWhmmkw5bSGe4tNPMgok28AfMeXf8zzbALbW5JwO7wuf7n3pAyUmrJIGeJ9ABQDQhdCpavl+KSWA0++xh2QUDCSGIJsAuA9qGi6zmZeFkDvAgsCktibejEoqwNwDe6vB52w5+r1BtBVZS653rDWXY0Z/rsAbe43GpI0Zgyu6KffEmGHdDy/t1+5LPM+Bs3JaYoDPtSPV9ood3TO+bqWnzYqHFxG1oS67mOCLBDlGBvltr7Y7QkdmRKrLExCIdOEGCSI237cm1SGbBfy+l50IFk2K0Y3gBA2SRQHb1sr0kufScPO82w83rYCUIK7/kNOJGIlNglPwcfw04BdvpYmKf8oNAJ1qORhJaHTpiNF0cSa/vgxDDsJOupNK85uaSS2NAmfzfwb/39qHgysG8Df+KVxA7cxO4gMJEd2qKoB2Mjvrp/mrshoywl1nobWvYgf28+FUlXmJGsW5rgczQvsaCNbLpmJUFLjvObxLAzaSSsIeZ9P93Y04Bk1j6Rx5/DxGj7ZWZxHGES64aSeXe1GXYM8WRfM43Khz3sOhJNfCCXObCBDLvKHUS387v2l4IG7ytafJlzb5LbPAy7Lsac72ZL1ocKr7tcwC4gdWH+M48fbCFHhl99bYGybhBHwM1d9f6i2F4rcpdWpcTqCUN74RiGna55pJkkA02gt6eaYWckscSw0yByynYjhlZlmSL8M3xYsttbDBZZHBuGXZnt+593wECzCHijUVnJSmWep0kmBrC7OgnI1i9plXV7sgBY6IRgOtI9myO18rIeGXqILQfwXbI2+AyEQydaDDsxmfk8IJxNFsAxVD8SLKhFaRfXWxywG+vVWJy5u3Pzw/ZjhqbE6nOv5HLR8N3ETaiQKTg1fNrDTkpfOEBKn2moea9Kbp6biJTYPoZdGLDLSzfMpyWJ7Rl3PvDMHe//+8rIayRgt51hqpkqdTJlPUONGPUwAMBIYjWQVOVop8oA0CmS2Htcfb3//ODjf7PLXBMtDzvyytINc9RvCREsyRABhIedZtixwAlAS2JDHl36OBI9NlmG3UhgZ4AksF8SS6ET6pi4b+2o8nrYDT/fhVYRKMCOzbMbDtj52DxUowG7cgzDrie5/uBJ8+1Rs4WD64841+gO5v6UWAkA9oHdOszmTqP6tC2o9+Db7JovrE3F9iSxQPUIr0MA9r1Ly4VQDWDYTQxglxklwkZW7YJERWPHGN5XpXFk1l5L+/ECbg9zctvOe3wzjjHsYsGwa6Q9k+d6sqyjyPm6OsPOBex8PnGyx+uTxBqwKIlNz0Z+giULFygZMJMEPewsw4775m5sMWa5ZW/KNUNgraRJNhGslZMMBQHU2sAHanEP/fGhE2E8hIIU52XlfM5jy2HYRTEQqZCnaRq7QK7HlmhVht3eNDXz++GxnkMEntSSxMYbCNiRdIp7WHFmF5082n0MUod5NHXLMLLDwyJWH3zN5BQ0SVmGnUA8acdTs6eOeZKTYyg4gGEXeZq0oaETwhxxa3Hb/pLvugSq7WHnMuycRXvaIVnxNcyGYbeBgB2/IUPgKEtRfPyKarp/4VP3AAA396aWrcl2rk5FI60GeXfCOG0x7Lad5+lrfolhR03+sWZyGEmsSYkdMaCVbCeY6fGPy6T9GF1xHOGAGHaTEGA3wMOux5yUGmrFsNM7/MkEc6jzuBW5jI2N3v0aULIxoopDDZK+vwpYSWzfPddFV7fGsdI3xA8kWiBOHJbwd/D6nAkpG5d7PZy799KirM0u2CRqnN28UXX8hvvz6d32Y1oSkRDDjgA79ftLxbCTKXJUTFIBtKUvfM6IIgLs/CBvXbL5hFH7FVNIbpCI4+GeRqxJapoGeUAS28Ww416HD86GgxShneIr2xPMNIBSxlNrzg4liz0dFTqx1/4/XjpRHE/8NvX18PIAdu9+dA+f+8S+2bAyC3+y39AesGXUAzp0lU8Sm3HATodOCIZd3imJ1QsWEzoxFrCjDb+d3ocaSWyPh91epq5hOTYOrhU97ErNDGgimW63eSoKXl1MiO0xktiqtNfnEA+7sodh98hvMd/+RvMkru5M1FyjF2hbWLgedsYSJCBl6/Gwuw91/ZP3pjTzB8DYHyl2pysw7Igw0BO4YooeF2LYMUli0aQ2YGgTiySxxM6F7e3LSn2eaRwhiiJkoSTPMXV2335//Lr/umPEAsWwY/dCJcASb0qsew+tmm5rWa8MFIkiJJHY4EG75x0qiZ2xjd2IFHqMUW16beZlb8KFhMy8rBvDnt9owI5ZiSQh9mafJBYw/RXv9zkrs2WnBWanU9VBZUKwugA7H8NuKNOd1f2T3Equ2evszVLmUVuatQ5XZPo8uKWKqKuiKDI2Wg+OT91jkGSdEMMusJkxplZeoZQ+hh27H+limxoPu8AT8aZNSmI9HwAVAXY8MIFu2qQndIJuYMOwa5oRoRN04fgAu2G7WgRe0qA3m7PF6NHLnX8LhD3sKt1EO2wew7DzTNz0/iLOsLsMoRMdPoOMYffEFXXDvF8zM95xwzbhEQfsxCKt4B52+uY7rf2AXcxBZsmiYmU97FyG3UqSWHN9u43lWdkgpx1WD+h2EKlzVE6W97Dro07PDGBXm2upjCZYaHAqouurI2XoMlVorDIMu8BumQLs9LW8CsMuAL6EvAaTwHGZ0AmxI+uMKWxiaprGYY5In7FFWZldsDSqWLjKyEaXFu9UXsBOhk4EQH1icBvA7hJ52BmPoQDDTktiMymJ9TRqZtEhk4IZmKxei0InCnU/O8cjUmsJdGsqv5cOT4k1vothDzvO2BzDhAztFHOGXR5N7L2nj+10iIm9D7DzjZXEoHjsC9XXS8Sw+ydf90X4N//178JsIkAF0WtUqwB2naETjGFH4R66hklil0yJzal/6GfYEbsr7GGnzt1+pq7FMR6MTnFGM18kdPQbvChYq6F0OzrfG6ii4OVj81A5huZ9xcGkIQw75rnrrUc/33z7ofhz7JzPrAPy0srPwimxAdCZSl+L9xs1zpi0VV/ohGbYRUmC7UnKQidGgsSSMd1XPYvSvGxMoE+BdGlm14UUjR3kbw17X5el+l2auMBX3Xh6u6F1dmi/P37Db3chPezY/N3I8bNDEkv9XxbyVB5YlVi7AqpXtMEOCXvsAMCO2U/R77cchpQYx+vKIby0GHZCEltWzeWQxLLNShkYZirIsLPXC7G5+ZCZMgZd6VlD8JTY8Qy7cAinVY1VTBE3ftPq3mluAWFGlNqepCyMxM+wiw0xoQ3Y+eYVXz2yr+aBwxN9f0oPO8J7agnYEfFlAwA7WsBx8/PK8bAjSSzJNPsYdhnTBJOHnV8SCwAzD8POyFuawAnUz08TiAHsOOgTxWEwCOiWxHoGTF/JC2a6YDst5NvSUQu5CK/dQctNie1gzBkPGY8kdgMZdsUQhh2TtLxdA3SvPlA3zDtuMGkN27k6EYu0smosw06fm5NGgGKRHmD54NnxuZPm/nThhk4QYLcUkGEo9O4AfppXWGDiPoYVedgVWQiwG86wC3rY8YbaMEATw7AzTfRbRhKrr00xCQRNfjU4t0BmQYOeRW8Xq5Ebx/IKgXxxAKypBcOOdqGc42ef2aKsnXXj0Zlg2BU1aj3dRHUVDMfoq3v3BEDXybDrCZ2orAk2cMkYdtIzjqo3dKK9wRZi2DUlyR71+dPjwTQq2hI0KSHkC73C2juYXXGWEjuEYcfZmz5mSahCO8VXtyfGw27RZBaUxAiGHY2LXKrpu3eJQfHYF6ivD14aL1F7s0uyNvQ9RkAdMe2WA+w8CXMTFloSCJ3Iq8b4frZTYkv9lHqhV49cKLANv76ia2VrEvC6073UngHslmXYeQLR+P/3VKnvZxMuZnq8zduU5UWbYNKvFbCsxnlR9wMmXJ5PQVsBRpj6HUlYAz3JU1+CBzf/Axw2O/jpnd9j/19fMxRqY8aSwMaq7c0DgJ0+xiOo580avdHgYT8sdLBIFGfYmSaMHTY2dEJf/5OBgB2N2R0Mu0lE9h+JN5RqY0qPJVGSYZLEDvuaWKqZCQq012SxbPAEl8Ryhh2f2/X6NolqpHHsgAyNZNhJiR7annPE3lo2/MPnYZdyDzsGikmGmHdtw9baVhJr/86GTlhghjPsrIddIHSiviShE6b3OWWy5ZCHnZTWJ+aznyE3LFAqnjrrU9xkrA/MpXqvq+ra2s34POwyn4fd+Hvl/kluSVjsdbYnCZPEVt61Dq1jag/DbogkFrBBlccE2LU87ATDriWJ3YTQCY9nk492SA1zcGeFDzoCsfRFEFPNtIddHdkBglhFsWHYiZ0t/fw0uJiUWBnHOyR0otPDrnuSNLRi2q2pGagSiEfnZZNeXA+7Wh+308CkHYy5xvNeuh7/JpcDWIRky2yX6t2Puo3+Z95kMhd9rhJUrUVozhh2iabHP2jcBuZMe9hFfLHR0RwRYEfgIDFH9rdcDzspaews01jaCb6uG5wVlWGytQaLcoGtSDd+qesNZGpESmzQw44DdsxjcdGI4wrJRS5ZFQGGnTe0AbAMuyZFrs9J1LOA8rGkqGgclk2RLxUKANvFE4dF86/wOXPGFDYGynunzbBjbJimWkoSOy8q/KXv/Vn3P0luyGtw6IQGHfQ0eKkAu6AkVoROiOvO18z0edgZQ1/DsMvbxvkytTbJAOhrjc0hZrxgu91DPOzustTWMR5gQ1Jij+tMO9dp9sFYSWw6DXu+No1lUNx6j+pBmmoQg36jquVhRww7DdgN3Gzwls9D13gxHqOZhyWxfQy7NF3Vw67fw+vMpMQGxg89p+2mK0piHRUKB+yGPR/dz41k4my4JJZIAT4mBPcNnPf1TJwFTJuRXYqIPoZdNsO/++J/hi9cfCvy65/t/D8A7CUE2OnPx6TOih6nz8NO/92R7j0nlBLrYRVSEnCUpNiZpo6306gaAVgDYAw7/7qlYKETBdLVQhrOuxgwniaRHWMAVPqzoDmTAxpLJ99ySezpPTuXdjHsOGAn2U0eP21JDslC/ejA8rGTYp4Sy0MgBTjj9bCjtX1jAw9mDLBLTHhQ28MuiSMkeg1b1H7Qsqwar7/expWRxJ6Za6y9ZugI6KMeLSpawXcGAKwabx/opMTqTdFpiDXOi2+EexSHDsOuC1PpqXunBRJzfdnj3p4ktkdtbHowf2+xZ51jVUTDXv+xA9Vr3zeAXcDDrhIbkJvEsKOLiTfEXsDOSGIDA0SI7g94KY5UXQw7Qt1b/lgJAXY2QaaoanHhsdCJTsDOJ4kdGDohPOySajnAzjLsaAGqB7eBoRNRV+jEBjLsHPQ/xIJkPhDvedSV0vzWt121PxhJbNNapCmGHRnQamP9xl00nFLoBPeb6ABqd3SDSa9FTKQDAdiNk8S2zZFpEWFZW+Jz1IvIuomQZ+57MjVgoOnzOqBI73lRmeszb2IGJOrnfstIYv1jVRiwsz5hxUiGnd/DToAf4m9akthA6IT1DVI/+xl29jOTkqS2h13l+ExYv4zhwPRHXz1CTYt3Kl84jxybDcNO3FO1BZCBSySJbRq2ISElscSwU6wkngwGeHxP0Q6mMEXNbuQ2HkoSG2LY6UWGE2dvxw8aux1J7ACGHR+bT/Nq8EJjEWCjzrIE16bqd4e5+h0loU5QDpPEclP60C5qfmLng61rwMFT6vtL5GMHgMn2XA87ksRa/80lwB+fh52WxD54cIgf/KXfUP83KiXW9bDLx0piR0gCF30psfo+2E2IVb+sJNYTiAYM9icjhp0ZD4XP06aWj81DNWNjdm/wBPfZjAdssJoeMtyTvHyorpPHrzBwRV8z+ykpeHqCtfoUObp3e6gZdmmjmWoe4INkz1GiQydC90df5SMBu46QIQCOb2mOLOxlvgnFTOPTOLKsLgBloT4L2pDlgNVSPnZlbsFRQI1Px9rL3ONhl2jAziGvVAKIEnJQoG2/RF+XZQXae9JlMRnfeDaWy7nae5546ASNp+wWJXlywaSPnCyUGLm1n/VUVvUlAezsfRRkQXapkXT/pRh2fluesm686xS+iT6OYSeITqKcNS3zKhxb93noBHudHcer000PpqK3wdWfUkXUV0T0ufPgxD0GSdCqxVp2kxh2dC/yk8NvUCOJTQKLAvNHYQ+7omPCnvoAu1qGTgjAjkAadtGcLMr2hdd1cRmvuy7ArvuilO/LZdid+v7E/ftKyJH18RPDrvIx7DzNWUQmq16G3eYCdpkD2Ilmh9GGr+1M8HlPWNkn/95cC1Hbt0h52LmS2Dcqd9HwMN7Xv+cmzuHF3raWzRBLxDDsKHRiGQ87j0ktLXBbTDYqTcN/iC2UdWDAWgfDzkhWLMMur5kklhq8t4gktvDsPKqfAxsWxsMuMeBqXPcAdoNSYiXDrr3rBCAYOiEnM68HHxtX24Cdh2HX2KZsGen3r730APuRGBe9gJ30sHMtA+zx046/BuxCDJlNq6qw809LEssYdk1jrjsriVXn+8uaXwR+/lvVYwIgb20Ydm0Pu5ZnlC9Vk8YjJ61OX4ew4IPxTqGL0DPuyNcbyrLr8ti8NVOvd1Sq99ck1tu2l2FXV/YzSKbhkCaSO8WZAqGufob6+RL52AFAK+SAEpaNJDYwzwwpaVkCGKAgrc4Qk6Sarm1dRVWHbQT0cWYZSWJHMuxKz/UcKMMICQF2ek7bTleVxHo2tQHzXr/tpz6Jv/FDHwsCgrUe75r4cgF2Pr8sqjiOzIKw957lrLEhKbkh6RmrVx9owO6AXSf6mrmSlvq4xDpEhlgYpmM3w+64Uc+bNsSwa8+dJQF2JnRiGHmgVcsy7AK9YiFCJ/KNZtjZuWmSxmgQGxl5pc9vJoAvYEmGHbc+onNI7Gsvw65GEkeON1kjNyg993UpVGqrhk74U2L5Rhxn2AnAzocBsHWcmbPjNsOuYAy7ggEzMUliiUktGXZ1g8klC50IeQsPYtihaI2XfPPWL4lVvx8dOtED2BlJbFmH1+sD6h4PnWAedltZYtQRSirdJpH5JLFdG0G++qxH1Nr/7kPdjwiLNdNbtCSxG8iw4zRdNzrXpVaGGXbMR01ImCqjVfdIYrUXTs0CExYkiTUMO3Gj6hMd14X5UI8XpdvMxUlYSsX/r0sS27OrReeGbqSEfaDNAIZdLlHyLsCuK0TCLDxYw7nB/iYOSBSi2JrmSL3vv/D7340vePIA3/rHvsgFl2gCQ9Vq+PKqNl5LZF591mQOq+Vuch0AkCSJ8j3kr+2pnalm2BFgdyYkscukxHrALmoSiygAvM4fAAAeNDvh3c5BDLuwnxrAPOxyy7Bb1FFbqts1CV2iKgNjlW+HB4A5JwVSNPrz6wXsOkDSkNS0JZ83x9XNsItFY+o0W2bMzlrsBnkvLYraZdgtIYl94d4p9iDGRZ/X51APOwqdMAy7SwLYcZ+gUOhEUwHFWSt0goIdvnnxV4F/++eBX//Xwea9NqCM62GXRjXyQlyjPkaSRyZK6YAZ87ohPz2THOhha0hG31jAznev3NhS79cE4BBgh8p4jAaLj/HpJLxg1eMsZvuKdXhFA3aHLww6/o2pVhKaev+0UWqZPKtIYln/oa/jnWhhvFZl6IQjiW0FyqjjTJdOiR0O2NG1GRw/9Li+Yxh2a/awq0o8e/sYf+W9v45v+fFn8T0//6L/z4lh15LEbl6Px4v2EUILq22+KdhV/DN1PIf7GHZhwO75uwrYeuIq36hQY8F+qp637WEXSHesAgEigmGX6f7At9lVVZxhlzJG0gV52IUYdi1J7GVg2KUG4CL2dV26DLsoiuwcuwxbjc5XMgF2bqnvH+j7l4J39LEAMCmx/HUtQBCWxEpwIvX1cyPKB3YkceyVxLYZdj7AzvZoeUsSG6n1FZhHHZPEZklsJLEmZE/4QpZ17bD6N7bYfWRlnCMYdqll2EmVD9+87ZPEdvlkt2ogw25ecEns+Hvl3knOJLGSYccBOx/DThMmfAy7gYAdMezO5pTETQEnfZLYDWLY8YWdb1FH9yYt0Kq6QeOblHx0f1pQGemoh2EXkfmx/QBJ/kA3cesCZzHqZPZ/sqgQDp0Y6WE3MHRC7noknGGXn/r+xCmz+EntxQpYwM6ZQDokrrGXYdcfOPBmVeFj2MnFuJErqffxuz7rJn7gv/qd+MrPecR9HEuJPfFIYmmAMB4K3GATwINILSLSJGr7/HiKGHYnRhJLDLsVJLEdDLsg80FLYh9gJ7wzOGCg6RvYnZRYfZ2d1TFj/pEktn83+zKUbSKkJFaPfy0qG7GYYsT684t7DOlDbDnAjgXyM/VJIQEEmwLJsLNMPA/DLs5aiyXpJ6RSYu3iepnQibvHC+xKhp2PiTzYw84NVRiTPvqmlknii9qLSR6AkB+35uSiqrELds4+9m+CO7kNyR4Fww4AmmLhzuO+ZLu0Pee0QieSySAPuxbDbiDo0bVTfH2iXo+Ceej+y1DitG/xz8fEZBreEKPzQosvYthdNkms3IQUgN15SWIB4GakQc9W6EQdNtUnD7uMPOzGSmKHM4z6Nq3oPtjWgN3xYklJLD9PUcQWPwV+6Xnrg/Wx1x76/5zsB+iz9DBgN7Eqj8SJ19bQpFgO2MUJjMdm6JrtYf03TYOPv67O9bseYdemkcQGGHby+Uzf3XgB5UaPgw+1h13SdAB2GpSNExU6YTbJxobcjE2JNaETgZTYqjYMp3zjPewsY43IFATYSQ87wK7flnpPZpzZAra1VQ+xr/lcLjzsAAY0tPqd9pho5aOuJ/GywKkkm6jjAVJisXHFm/TG9YE1XBKr52xjTxknNhirthJvHjoR90hii0vnYXfa8h82NQSwi8KS2Kqu4fPBXjol1iE6eQA7h2G3nCT2LK9wVlQsdIIx7LiHXSh0goZBB5vS2NVASezeLMOj+zML/NI1LgHyWvQzPWPjmFpdEssWdv4kDmLY+T3u7BOxG12AMCEjdwCY6tCJyhM60QLsPCk6xHg65pLYOFUN0ZCUWEbNNDU0dELQimO2CBjCsAt52BHb0BkXO0Mn1PuLeMO8wXIJZzAJhU7QIrHDfwSAA9ideSSxdHMm+qas6sZ5LUqfi6MIQ0ycDcPOhE5oD7vtzL4nQKduDmwAvAw7DdjFAZaclmodNTth1usohp1fDuQLnTirYpYSKwG7Dd79GlBWEuv3imv7hNld5zhT5ztp8k6PLvJ986bEBphrLTaurlBTIBOUvB58HR52cyHXWZQ1m1S5h90IwO4kx65m2Bm/v1EedlISa1OLgYF+HZtQvMmXzUYc20Z/8ZCx56yH3SMRM7nOT5gk1r0GKCXWbIYxMH2K3C4Ym8YPcHg2fRalinewO6VZh4edBRYlg3Mo6NHVeN5iDLtbe1NEeuzJULbmglbxeTHJwgw7eV6uvE19vWySWLkJSQFXBNhRWusynre+zc9sC7UGVG7R9So97EqWEtuSxKrrJc3UZ1qNNd8nUJwD0IHqmwPp3G1FqzLsxHlin8lHX7Hens/c9rCOYc3pIyOduxwMO5ozQwurmfAFDj8RA+ycfi0kRe1m2L3xcIHD0wJxBLzzFgNX9Pi1l6jz3e9h18P20z37Q6jnTQzDrv1+LWCXYpYldp4cw7BrGjuvDpbE0pgdlsRODMMuWT5R9SKKqaeoJ6gNYEeSWL+UcHTx+WHrmvqe2NfcAkBfqwkD7FJp9dECEMIedkEwaGD5EjbjKGLM+TbDzjIRfQw7u6FiJbFW/kjHa7xI64qtn2PEJnRCsp406ccB7DZ4jeF42Hk2yevKEkZ8wGNmJbGt0AnW55WeTf8J68N65zReBguJ4UtwMCSUogqv13vq/qka80xyMAPsdpyU2NL73nzEBHP9eLIRQvXOW7sMsAsA5NKPfaMksY29cX2LOhNKwU6e94btYth1hE5MDMOOA3YaRGnc5tIy7Ozz73BPsZCUanRKbIeUlpWkFcdM6hQt42EnUmJdhl0YgCPpsJN0usG7r25KbCh0YiBjywB2bUlsUTcG0SdJbFE1aH7Hn1YPeOpL3ASzAfp8w7BbhBh2diAa3AB4Gkta4FZx4HNfqAb/IbbDu2wjGHahnRg3dEIDdmXUETqxwbtfA6pku368KAk6JIktmwSJXlxmUeltxqmKsoNhl/iBsNDfxFEAsAtIYh2GNKN+S0BFMu5USqydVKdLMOzuHOfY0gl5dxstj/NKYuWEGqDhk+UCVEPo2xDayCp7wASWsJm1GHYNHo3u2ceeHZprQjLsWpLYODay7SkK+5lXOQB9TXAJoU8Sy82fASDxeNiZ47dzoLyezvJh101X4/mYJnHNmwm+4KkrZuzJUPYznPniO4rCHrFSWnnl7errpWPYSdmHep/EPCmiAHA2pHwedlGERaSu7wNi1bYYdoy121SunJA87FIJ2I1l2A3xsNMbKMGUWHUfzGJ1TKt72LUXCq8c2t7xuTueTQwAdSkBP1c2tqlV9SyslmLYAf2b0j2biMRkfMeNHde/UD//bkySWH3eyxBgx/2PPcdCkljtYZdUXZJY9VpJmmGWJmHJuKxnfhT4ib+pAI5yDjOeD5bEUq8YSoltLk9KLJOYWoadJkHouSxL28yk5Rh2jMm4rex1zNwwYeOd7mHSqDbglWXYCUmsHKvB7iHhYbdssq3Pwy6NY8aAanvYUUCMXxJr13EWsLO/o9cpnJRYiwtYSaz+vQyurGtMmA3HxhYD7FKfKsfZKOyWxLZ8tJnK0eeDPWHqnHEMuw4sBEJlNdDfX9a9E/W+r9BFwT3sJikqTdJqGJDL8aLEs84ZGzoBKCZ1C5SWADm3dwMGecEPLf8ZHlh13ZgeiRthVo0HsAukyNonoxu9zZoKsVYAYKJ3LSv2AeY1edjRCRSAHRvQ9mYEoDDAzixQujzsavcxvKRBc6AkrTiq2GQXmPh4tW66mvz81DFxL0HbnHhSYvV5cgA7I/HZREksAx+CoRP9/iMAzGedom4DdmVtPBkSNsjXv/svIrn5buCJ347yX6vd/yQexrDbZQy7pmnwwHjYUeiEvcbzsh62w2FSYu17PdFNogHs5GChd1BPMMXWCgw7kyYUCp0wg7Vl2M2d0Im3FsPOt7sDdOxoOpJY2h0rMS9qbAdOxaIjwWmS+gMEfDRxgEtdxWFJSSyb1OoGSCI442ovw66oEJtFc70UYHf3eIFZRIDdngKeOhl2tPESkMMRWIr48shhgX65EskJ8xOkifqeh048Asawmz9AOutm2HF/2CidAVWOaaSCJ64CrizZCZ1oL4gLlrwNAColtjTHpo5/2xy/OcwWY3NYw9fVeD6iX2aBDF/yjmvAhwgwr7yG7k4Jy4VgUyaZKiSJffiqGvtkaMimlpAYWcBOnTPjlbWUJNbf8J9hii3uWSk87IqqsYAEvTZdc7UFLpI4sqbUMik6VCM87OhamQUZduqYZjog7eFA/8VWtTYi7OLn9Ye2T3twpuRicqwnc3rT522wioKXZfP4x2jysKMNhLpWUtV3v/5exLN94D3/a/VAyXZNXBZOq8xGqP8e/fhratPzPY+61yVdMzvxQIYdV7bIY6lKRPqaJQ878rj1zZ21w7CLzf3RVAU6l6Xf9b9VX9MJ8Fu/zv6/9EgNFZ2jgDKorO1GTY6s1Z9sVLH+ge4ho1rS55evRUOhTYOKzw/bmmFH1wlj2NVRghiSYSclsWHmrCSHZKYfXe5z8KXExjHackHY+3eaxXi4CBB2mCSW7uMZY1PROc556IRR3kWITOhE7L6+PgcOwy6+DIDdqd832rHiCAN206hobUAb38KqWxK7KOtO799W9QB21uapAvQm3FiGnQHstmLg2H2tnUmCIz3O1Wz85O/fn6/gkhKG1Oc+sY9PtRh2/s3MdujEm+xhR8DcFubY+//97/B/ir5f/b+PYcc++OEMOy3rC7BWAGAaCa8usNAJI98QZq8Mfd+ZMoYdNXOiIarrEl/9jz+Af/i+3/Afr6yBoRNmwNGDXsQmu6guB/y9uOmEJNbZyTAXjScl1khiLwfDzhlMQoBdKT7zUJm49LrFElIpsVoSm7EdowbAF3wNcOOz3N1f5o0YKpsSqzT5dC9IDzv+PnuL3iuT/5rmNQmAbrpROG1m4Ul7AMNu0WO4PeO73wwgqSWQGDJkvmRVBPx2OJPNkTozSSyxlyYoehh2wruS1YTMeQeHTqivtRiTWww7Nvaa8Z1NTPLekccvJbEtGWRPNU2Deyc+ht0QD7vAGGGux/TyBE4A9p4JgT3OLq3bmBdVjYOIgZzzw2DoBEnouD8szQtTFJb1RvNWnLr3r2fsaTHs4qwNMhPgWNjj7AOEQ9XlYbetGU9f/FlP4I9+6WeYY5+gm+EKwF77NOb2edjRZ7J9Hcj0+yNz8ctQQmJEvQkx7OZNe5E4uAK91Gkjru+dm86PeclSYuVr86THJB7PsBuREjvvY9jpa4T8lkMprr0lvf6Y9crrD9z5nSREvAhsMH0e3as+m5QNKgMOBNZVTg8P4Dt/9nn8F3//exH/q/8z8D1fa+/B0Qy77k1fYti9+1GX+UmA4LbeXLIedvrzkzYtcWwBC3ksbIOdPOzipkSCytsf1oxhN80sw84Ejvjq+DZ7U+8FFtoDMd1ypI2d1RM6wT3E8iZdmtl1IeV42LmS2FqHLWU+D7tl5KX8miRJLNXEBewARSyg1zNAA41prfWt3rRnxBrLziNPuPUx7BJHEss97DRgl1IYomfuZt5mNNdv0aUXxeY9W8CuMIqANI7NWn/RSNBS93h1jexSpMTq+6guDWvQa0MDdEpivQw79pn7iAW8Jx8XOtFmVfJyfNnN5zwOKKb5zDDsGFFqe5qaDbmanR9OaNguH+Am7rsMu6Z9DffV5z1xYPyX65CHnVSLrZFhtxpgp9/8V8a/hOy5H8M3NN+DW+KkGHSd7T52e9jxlFi62cISMJLElqxxy2stMW1JYkWjU5VmsncYdib9Q5sl5jk++MIh/tYPf8JOvvKxvJLAAlFUywdA+j/0yGINYCdCJxpvSmxX6ISWfToMu80PnZgkTDMfYtiNkMRK2VVZN4Zhl7JB3tHBV8xfZQBQS4zOh/MCR2e6uYojs0scRZHjYzeoqvZOMLEFmyQA1BqG3SzcPA24BvoYdr6U2BIJ0gkZccqU2A2eTAdUH8MOUAw1+4OelBGb956h7GSe5R0MO5JqSElsyMMuKIklmwwPw84Cdpb6TU0WjWV9ktixkozTXIHbUwLs0CWJlYBdKHTCnvtBTNZNKZoXQuwH1iBIf7qiqrEDNs+cHYZT7qo2w87s4KKwjOQQ48+zSaTSArlJcdKWFBlJbBiwG8uwe+q1Hwa+6w8BR6/YX+rj/tzPeESNU+z+6x17DcOOfEoGethFkWXZXSYfu0BKbJMID7tlwB+fJBbAEez1fYqp6+kECp1g9y3fKKtsfzZJGWA3OHRiuOk+Mez6UmLJw2vdHnZVmeP2sTtH3z9p9yBtht3mbsry6mPY0WYn2Yt8588+j/dEDAx/46Pqqxw34x6QOSRh1fWxVwOAnR4LtjRgZ8LMKjFm8AqBh6z3Oo1tEMsEBXLPGNhwSWwWmwT0suu+fP3X7PcPXjZ2KZjt+x/vKxr/msrb/5YsdKJAulyi6kUVA8CIiWYYdlWbYSeT2EcVB+xIEkvFGXYgYkFlljzUU0atfsdl/PBzTRuv1Be0QtAGFs3Vbkps5A0FkD72fQw7WmMbwC5mHnY187CrLOBCa33zezFfXbrQCQCZDqF0zhdnb/mknKw/C3nYhSSxZu1Q1r3rOqe6sBBY7McB7JZk2O3PPIBdZj3sGodhp99/0+Brf/X/gB+ffiOmxQPz+z5vVF89fXMXW5r5+WAuVJaVwIYMYLchDDtCKD87fsH835fGH/UmcaRJZK6vbkmsz8OuPThQUfNfskXFQktio2BKrL2ZtzwMoC5mxi8+d9/9vy6GXV9KrNRay92pnuAJ8qUyC/faXWA5flmJBSlbh+v1sNtcuUTOGUYhTbxkQISK0peiCnNp1F/WzMPOnhsOMpjrO44HSWKvaJ3jg9MCR3qn/WArQ8QGjSlRk/s8Wag8jSVNek0imGxUjGEX9N4YcA3YxUp36MS8rG0DgRTZTDefxGSQC+BLWgQmy7GK066dZpUaCqSo2cKuC7ArDMPUMx4yIIwz+cw90wISra8Fr8Z4k6L1fsy4wsZVev6DLc248UgYyWcCdRlMJg0VLXKJtXDPMOx8kljRNIZCJ/TPVROH2TGbWLSxE2L/eHxQ6DznVYPdiKeRP8Qk0r8T11xjPOx8DLvcgmi+hFj2WL5JlLMgH/J/a/kuUtPKJbEtj8RxHnZf+DN/GnjmR4Dv+SP2l2axpI9bj98pqn6pdstYOGA54QN+rmjA7vC5Qe9hIyrkYafff24ksasw7Owc0jQNXqsOzM936/3WGFWUArDjvQ3rz6ZpjJqZlQ+q0DXtqf7QCT2uR+rcLc2wk944unc5PluYc/P26+o6u3vSXhwYwM4wAza3x+PlY/Pwojnn6Ez5aj57+xjv5oDdaxqQkuNmX7/WwbArq9qEe7ynxbBTz0+A3ekisA7h5QkK4H9TNRHy2F6Lk8CmAi1Y0zTDJIlRkj1O0fEZP3zNfn/0kv1ZeEZ2Fp+LPOuWom5Y6MSGe9h5JLGVvmca3ac6KbGr+MERiDzZsZJYKuZhR5ZPGSozpychwE6AVXzcpLAM4wm3JHDquyfjOEJG6e9MdjrGw66pSzO324CB1JxjsrtyJbGxWevnLUlsYV4z433HplYyMRYuBNjVPsAu9B4MYBdOiS0Cklhad/L5aRjDrkcSy33MGTAra1FW+CPf9rP4qn/4frx4zyUr3T0mhp0+XmaBptKwPZJYujbvfwoHi1ewEy3w5MmHze99wSl9lcQRHtlRr3XnjAA7fyCXlcRuGMOOT46PRvccnTBHwTuTaXjTJiWxelDJPCd26mHYzYlhF5LEspuZmE3zvGo3jh4w6DZ5hTTtnQRTAz3sSrm4l751PYhsOyWWqJpaEsvPc+wO4rxosIsdOdPmetg9djDD0zd2VKO2cuiElcS2GHZVhVQvZtO07cnAv0/iqPMcU13RzeXDRWkGof2ZO9DRADdcEksm9Pa9GvZLCN1nHnZB0CQkp2W16NmJ2XLuLw1ONQmmW3oBS5/TW0QSG0oechh2/HQTZR+JkZep0InlGHb8c+Asu5CHHc3pMgxD+js4gB01XCy+nAAOYpC2GHYFZ9hVwWTSUBG4vR2r6+R+o3effddmiGHX1MKYXs8vSC5PQiwwShIrk9mKssY23HO2BzUWtOblLoZdVBgJWtDvyzOHFBWTptD1LuXRxoOPhU60JNbjGHamXvll+z3Nt6m7gA8thp2Si/kQk9l3bi4lw05sQgrVwoKntQ5NN6eq3OsBUPPX681V8/MdHLSALnW9RBZQ9klik0ww7MZ62A1g2PVKYtW1kTXq+I/XxbAjwO5UHeveLMWtPXV/ehl2FTHspGzscoROhBZWBNg9OCvwyTvHaBrgMR6s8+Bl9VUGifRZmHQw7J67e4K8rLE9SfDUVXGN6GtmBjVGmF6sy6YllFirx/ocmerP9UJ1isIvidXvJUn1JjClm4Z8+gDg9J7786u/or4Kz8jO4sC2Z04umRVCgWS5RNWLKnafUZ9CklTydQ1JCUcXvya3rrq/Ywy7ijHsWh52jX9csHJQOx6bv10lKAN2Te4w7KLIpr8n7fVSJ8NON6INW8cZDzsnJZZYP4Vh7mVJZNb6lmEnSD/MQ3GjAbsoMuNHUvkYdj3hfKw/k2oa/pn7lEBTTa7gDPD1eNhxhl2YzPSvPvgyPvDMXfzqSw/wd//9bzi/e/1InYtrW+IahwqdMAw7CptKIkuCeeWD5rHX55ZcVjfjATsAuLWrXvv1Y8Gko3lEKgYGWEsNrdUYdvrevB4dmf97JDp0LrDakyLrBQgchp2LwnIkXZZh2DHArs2wEzcqa1SIAXSaV20ttses3HiDdOm2B3rYyeSe1gfa8/ctmZuRxJL3HmfYdaTEwsOw2+Dd17/zn38h3vfnvwJf/q6b4QFgaOhEB2BXVxV7WGpCVfj1W/Kdpg4WI9X+lh1oX7x/2vo/QAxwQ8ojtbCA3cx9DBUx7NDFsAv7HgKKBdHndUApsWdF5YBTWzOSxMqU2A2eTHl97L3AP/4Pgdc/6vx3GQDGkiDDzvr6kYH7BEVnQ+ujs1Nx4ImDYa1EaTouPamFPOy8kljDsLOMD2pWSZ4kr13pYZeObHJpsb6jWSoPQAzNAYAd241zFuzk+YnLxrDrkcRm9t4iGVnJJbGRuzG0rWXGspFuvICd9bA7IcCuDIAbnkbF8bDT4yXNX8Z30QB2xwb8aXskDmfYkYy6VS3GDZfE9gCCQ0MnyIePn5trT6uvd9ymdKOrx1h5Tgw7NKPlLj5J7MmixOtggF1zYAKaqGgcrE0PwH7PPezSGDVZ7o+WxA7wsOthmdN1RZ5EZ0Xl+pgOLfOeXGuXk7m6Fg+2MlzZVr+THnZN05ieNb5koRPSMF8WBXYdzUs884Zive3yMe70jvoqQdgVPOzIv+6zHtlrm5YzHymA9WJdNi2eZE8ApvfKocEjGn+j3M8C1j1rmqnno56+7pLEnt13f37j19XXMZLYKLLzkWDY1XWDuoEZ9xfIlpOPXlQx4gb1S5X2SCdAlG/ABi0lhhQH7HZvub9jElmagxPYlNjYMOzEWlQy7FgfmAqwz0ueGVC+5OYkjliwgx0LqfeYdXnYESDKADubEpuYe39hJLGlDaOMgEinGi9CDLv6kkhiATPnpJphV/kYdqF1LRt75Hg5YdepbwOf7IuO2MbYoI3sgQy7RVk5XoWyPvDMXfP9v/vIa877fkMTpa7ogDR+fe1MLMPOMIw5u/DQEspuLixg16Xc7Kqb2+q5X3so7jvZG0nArjgbv5kpajWGnX5xF7C77yz+rGFsFJRfARAedlISGw6dyJgvAqAaEwPYSYadxySQGEBKEitYczGlzdoBxgJ2QySx3c1hqxFpGc52N1Ktm85QMRPn+dWL9Etik7S9MNtEhp1TIU18j/+I/XvrYSeTAbmBpYoWb1+/Fd9pGsCwS+LIMOqI9ksgB9XoBM2yPYiTJDYOMuxUY3vadDDsPJI25ylY09XnYTcvLMOuRILtbQJcyMPukqXEfs/XAm98BPjBv+D8d8EYxbwchhq/L+mcNCkaA4b0eNh1JDjxCZgHT1i/S/9xSYZdLcamOLaWBuZ64ZJY/b6DDLuysvK1ujSNwNAdXvJ7pJTYB4Zh57k2W0wUdp74mGwYdpfNw66HYWcWTqctfx3lYeeeMzqnrc+ipmABv4fdSYth1y+JLcrGlcTClXEDsIAdGgOALXoYnKHKyxpPRrfd/6TzJ4MF6Hiisj8lttWUBRb/PuDnkc9VX0mqdxkqYKwc6f+f14HwhyHl6aUeLkq81liJ2Meap2zapq5cW4I0kQfsYL3cNE1sSuzQRfWI0ImuYBMAFrDT6Z510/YYHVSmv3NZBidnejGznWFP9xLSJy9nAVpGSXFJALu69s+pVJxh9+xtBZDv8nThU70QbIVO9Gysd6g0Pq4Bu8+WcljAAIKTRn0uJ+R77enTTJnPQhyLHjtzZI7tSoaqtalQVrUhKWQpAXYaaOra/D8TDDvahBwjiQXs+C82LUh2aRh2TYq6aW8SbkwxAMz4ftH6sqTQCXuvW6nhMpJYxvI+eMr93f4T5lsCJFJUBqizHnZiXBD3Na0Do8iCfL3Jtg9eBl791eBh+1JikzjypsSWwsPOe57EOm4rSxATW8+bEluZnmYS2/tgURF7WJwD5qG48WsMAuwqdW0467OBktgZ8taGvrEeKRuvpzWRK6jXnqSxY9UULImbiCKgdlHULl4i5uIPv2L95Y4XJT552/pTW8COAFnOsEsMg54ksc4G/Nw+71ZpsapakBKG1o1t9X5ee1ioMUzaGUjFgBnvm5XZ7GuRxF4HB+zuuUkcDIn3xhSbB3YAduT15jGdJYYdAXZF1aBAALCjppqh71seU3zJzDADB4B7JDWgx0aei3Rg6EQpb5oWw65PEqtZMzJ0Ap7QiQ4wyXrYeRL+eo7hTa+gh91Ahh1LX5Kyq4Z/fnFqr1824Tgo/UCJCfnYPX+XGHYu6DvhMdhDyrNzS7u6UaCJop29U8zC6VY9oROc5RLaifF5RJZIsLMjGFKhBLVNLO75cv8551d0z7UYdr7QBsA5J9FA0/uQvBVwmcx8URjysIsDO610iXNDVmoQzTw7RhJb1o7x+1gPFdr1I5nR4SCGnfCw068tH1ddOklsj1yP7vli7iSDAcrDbgcuA2JLn9PWzrduPEIMu2MCUGSwApUnOXXBGXZCEptXtWIC8efRTGC6vkIMzlAtygrX8ND9z5M39HGTlYDrYTcodELudPeFTkzYe3r089TXo5facrRNrdAusn7/lmGH8QCQBKKgGHa/UL/b/Pzh+u028EuXZdj5ADuXYbd86MQQwE4dxyzE0jUMO3t8kjE6qIwZvgvYnWqG3ZWtiRl/jxeCjVjWRq5mGHYb7FPMq49hxz3sntUMu1sT9p5ONGAXAOj7GXbtnoR6t6dv7rR+R2PBpNaSWBonO0MnPCxRwIydC2RqnaD/NtUpsZypeVpUBpRNMhewa7pSYg3DTp/f25phNz3wPjxYgTGwrBpEqDGJxFptU4MnGABmZIR6DiTWuc/Dbil5KR9Ht664v9t9xD6MALvInrMkjhGhNuyysCRWE17idi8XZNh9+38K/JMvA177sPfX3pRYHjrhkcRahl3Yw47GuO1JYse7KLEpsYxhR+d7GttzYhh24n66NKETQEsSWzfWU3qwJBZFa4ODS7dbgZWwnw8x2adDe+KhHnZlZVWL/O+g1gufuqN6vadvqDH1Qy9ZoO0NLYk1gB17np1JauZ3YtjN+Ab8wuJT25X93gTrjWTY7evh+7SK8am7J212dEgSC6zsY7cyYLeFuTFXBYArOHHYGjyJY7CHXeSi7UUXw44ZmarXs0bEZuchFDrRVNjmkj0JwhmGHZPEnoyQxHYwrdSxSoadliA17s+hKuQi3HjYad8Kh2EXBpPMJO8LnVgm9e0iKySJXYJh15bEuoBdmrQBZycaeuCONclWPvG6Wkje2HVBRdqpH2qsbndu7XulBUGc9afELhs6wVlgYUksMexqRxK7uyMYUpeJYXf0sv3+5LZDczbNkUxjjT2hO3VtJJolS4lVCXDLMewAuwGQexh2Q/lPkvUAAQAASURBVCWxkmEHWPDOMuxsA0TPTwwPGeCiPOzaktjBDDvNGJk2xLDbMc/VYg2HPOwAwbAjwO6ySWIF0CSLAK/yrJUGpySxbtNAktFCzss0H/kYdpGPYSfADcPuta9X8JRYPd/wa7KsG/V5EUtQM4Ht9TWeYbcXibT149viuAmwY6EvVd3NAJHziwecdF+DAXazfeDqO9T3HSyGjarWLrL7/vMqglnwj91F9vRSx/MSzzZP4H+a/GH8cvqF+Mn68620UBf1P42v32KL7mkSM4bdOQB2fZJYfR9EVW6udZl6PKgkk0aPa6dn6v462MpYCr0AN3mA1iWTxFYevyxetAF67yQ3ktibHLBrSWIlYBdi2IUlrC8fqud64opn00Tf6xln2DVNt5wt9FlokG/RZGosj+2mQtO4vehZXiGF8FyOiWE3wMOONhKoxjLsAmoOx/AfbK22qcETHOw3kljXJ9ObErsMANkFwLD1WKUBipSdxzSOzOftPH5AaKPcyHPqwUvAvU+q73/tX3gP2weix1FkP2c2lpvQiQEpsY1ea29NEgcToD5mbgC7whz7hJ2TvCbJJK13fR52mw7YEcPO3kdmzTCUYRflrVRtAueKqrYeduwx1AMbwG5oT9zrYacJKJJhx3CVl+6foWmA3WmKr3i3kob/2ssPzPHepZRY0kmz59meJCYNm5jEQYZdbTdv++aVUBEeVCLGR145CqoPzDHy8X5FxeLKktjrkbt7vR+d+Bl2cexlKNkHhj3sTHCFB/FN9U2Y065N2TDAjqjoYuLldMpUPfdpXrEgCZdhl0QNoHcx7rU87JYPnWh52Omb8RjDTArbHnYkYfLsZHQ0J90Mu81u5iS4a6prN5OXAexqByCr68ZeP/pxFnBue9gpSewwZuVNDdCRD8qtPbeBm7CBdVB5GHYkw0iYn5VTRhI7hGHn3xUwwFESpk5veSSxBRLs7+26x36ZADvOsCvn5lwCXBLrGauk/JQtMEukBiDNou6UypAfHdXE4w9Hf5MJkC8kiZWhE/yx5vJnskDJsMtLF/BYlJWzaJZSzb5SRu2NkRkdwhoyt1jAnR52bUlshXhYGtamlDRPl8U8MySTsShr7IjQiZlh2ElJrGZsM3kLT4ltAXbBlFg7hxQyJRauTDsUPCEl12M87PYgADti2LVCJyx7Rb1mx2tIBneQYRcAfh77fPX1tQ+phvR44XjHbFy1GHZaEqvHrKIGAy1HNqUeDzsC5/7ng/8j/tr1b8YZZi2GHV0rjdzhbhpnDJhmKzDsQj6RoJdqDDM/uMBhYC4tWiX4OKgCHnZnC+1htx0G7BZlbRb3ps8LBR1sWPUxIR7ZV/fey4dnhqWxzz3sTgiwE0zg3pTY9kYo1SsasHv8imfTxCy41VhwmlfuORY9zuFpjufuq9/PF+LeKUkSm6rFNQvGAdxx8CyvkGgWW6SvjVgDd00XiE4LWgnYydTSvgqMgQUHS2DXarLn2JjioRO0ZqXNxopCJ7iH3UgLG17Su/nL/q/q62f+HvdhTBJLFXNGmz5e9Vz+lFgOzpiNPB/I+NIv2u9vf8J/2AGGXeoB7GizcNrlYaePLdK/254kznrchE5whp0edx1JrAmdcM9B6TDsNnyNocenuLb3UdkC7AKgY2YZdjJ0YsJk0D6LHMmwI7uw3hoVOsE3z+2Y8MI9NW6/7do2vuApxez90EuHAGzQZxpH2KG3zZ5ne5qa+6PSTGKnn2eA3XZl12q+Nc6gIl9EpMrWSjBaW/c09/dka8VlaqVVSl03OIB7APs4dRp/w7CLe2i4nN1GJ4CQTA+ll4puQhpQi7o2OzgtxFM2KgB2NWDnMOyEhx0AxBqwM4uUTg87Gty7gRsbphGpVbA+3hPoD3egh51ZuJtzqCdERxIbZv21vE2ASyOXCIdO9Jhzmr/3h04UtW1wG0RAHFsD91BK7EBJ7CMHbpN3a9/9eXTqFC2QWGNJC4JkEgLsOMOux8MuwLKkZrEL7JhxSSwNdE2K/V3JsOuhem9SPXzV/fnEemS1ZO6sWhsW7JptMeyq8IKuj2FH/+9LiZUgH7Hm5CUgQyf48bcAx9gy7LgfI19MLEqeElt27/B66jQvkaEy9gSGYQe4AIFYrKuvAYad2SlLLpeHnUmJ7QmdKM5aTEYvw06DoK3xhjaAfCmx8KXESklsm3HRlRILqA03AFZCaiSx6rMyDM4BDKWqblDWDfZEyIZp4GTohL5ejDl6F8O5FBtCZr70h/u0zs3jv019feHn8KGXDvHb/8q/x3/2D97f95bevJKWGnp+JRl/UdXLM7YqO45QEQNtlsZm4dDysDNIjgTs2OemWTLVOTHsiqoxBOu+0AlUObYnGmQbC9h5xzUC7NT5vrKVYXca8LBjDDszHvYxzDakqo7+HwAe1f3ToqyRVzWmaYxpbUH6Zv5AnT/5mcY9gGWAYVdUtUktfOKK5/rQz0+StpNF6c5Roif9iU/cxqE+hE+8fNf5HR1bjszpMc2mAptjTxnDjq4NYlN2AnY0Rt18t/v/+4+H/8ZXgX7RAUtgGXbVxjLsuIcdSWJd4NORxHrWBYNL+qv/7v8H8PU/CvzBb3MfRimxTBKbxpHDXLTjQjtwAQASzzF7/eSOXrHfH7/W/j3smtzZ0I0ipFGYYWdSYn2vSZuq2oNxa5J6JbGLirHxdY+cRer5qiZCSeo0cQ4KzvLceMBOjx+l7Vssw64nnE8DQzPkLYKTtR5pvBY5tFaj2sqGAnY9HnYkiS0qFy9hc/EL2mLgbde28blPKMDuo68eoaob4193a29q8wQ46SpLzNqiqshPlh3LPCCJ1ad0rIedUX4icQG7UEosYAN8FsKeZWStLIk1zbDW229FORo2OXEWWdJFHR7gYeebsFPtC5JrSmRZMYadQTzFbjhrDLdTdSxnTkoseR8xQ009EZqdUQnu8RrItHIaEQaknTb97LZKJy8BXBJLjAgPYNcBJtFN4IZOzIDZATC70vke3vQKpc4MBYBiu3PlAHZVwxpcdV5SD0PUoZsPCJ0AgEf2BGAXYNgNT4ltmyPTgiCdBK4lSoltpuFGoy90ogc4AuygX9UN8lwbwCLB1X0ttzAedpeUYQfYHXxYAMrHBk4isWHB7kXFsFPne9IXOtHhYcf/34AfHX9jWHPB0In2YyuPJHYhJIuAC6osyhoV+VzVpdnZKwZe4yeLyqTuAcAZplamwsFosVgH0JsSWyG5ZAy7HvYPY9VKuU5eNZhCX3dbikFBP8uNNLKUcCWxnpTYoCS2DWLlHkksn9cNCDPRgL6RxI5n2BnWp/Dsw9mh+hrwtCJz6kUHaN5qnD2JuOrAA2DmO75MfX3up1AW6rnGSjMutGRolR6vyXKhqGr2eS8ribX3KY0dsyzBjga5Wh52RhIr5l3BjFcpscSwGzDeNE3Yl1EU95kNjiFs89MJORtTHGgU0jdiZV1xGHbuZ8AZdiFz+k2tsocJsTVJTJAXoDyQ4twujKK6UPdhSxLbAdhVpe0pBcB27yRH3QBx1LYz4c9PgN1Zi2Hn/s2L907V/A/gwYkYq/TcplJi7abeVqKOjV9/Z0XZ6lljuva6elIC7G6sCNgFFBlOMniUoIlWALguohxJLIVOuAw7ryR2lSAZuhajCHjyi1rsRtpw4Iy6pMWwI0KKu/70seEsw87zGRADHQAevu4/bE+4WhwzBiBbd1HvQYCQ93PX1ysl3u5NGWAXx+Z4F7V9vUZf01lEG6+pXZuJQJnqEkpiYwbYtRl2IcDO9mdBD7uyNs83cQA7d/4aDtgNZ9g1joedvXZf16DcowczvP36DmZZjHlR47m7J8a/7ub+rG1bBn0f6M+bGHazgCR2uzk1PUzfRlCw2LrhxfunHruQ9gaksRd4UwG7prFyEza4R+ygDFMjtoOcd5DgctSABt+3QDU7TY2WxFa1CZ2Qu8EtDzsAW4mPYddmZhCzwyxSpHyWl/wAA+XIKdmEfjyAYcfZEEbmpm8AAuycgbEDTDIedhyw238c+KYXgG/8SOd7eNMrGDoxzsMujmrHd6usamvwSoBdp4dd3F7UBOqR/an4eV0MO/s8tLhJpx6GXV2Zn08xDXqJNORPtPBLYnvT8QDsTO09dKy9dpCk2Noiny1i2A2UMG9CMYBO/exh2HkmgTZDzWXYUXPdC9itwLCTzD8TMN0KnbDeo+axko3H6PkEvG1NEjMB8hCXReGmxGYjd6XPihIT2LFrgQxFRFIzfm3zxToxpWMYfy3+e5p4m7gTdN64CqWyUhlJ7GmL1VlUtfGsw9ZVAMC0mevfScDO04gxDzuSTgQTNT0gVl41xsaC7vUoitoybpLEauBEetgtBgAeND61POzmh/q5hZRXH89MS2w6GXZyEzAkBw1KYr9AbYYtjrB1R6XFjm4cL7JaDDuSxKr/zx2G3eqSWJqLZ1mMbT2HSBmpGd8kU8oL2OlzOwSwq3KQBUrwHtPFgeO+lFhUuVkEjZbE8r5NpF/PNcOu18NOsl9CvosbVlXTBgdkPXZg76/PfWRq/aup5g/aGx30/n19Or+GRU9y51j97trO1A8i6ns90uPiSV6ioTkqzgBhl/HS/TMUev1ydHziPpf+bPJGh07oz47WLXyMOss5KKsZWUNAdALsrj3tvleWUjqoPJ6lgJrjpyyhszfw4M0uLomleYlUWxWlxLZDJ5ZKia3Fxk+gSiOJdRl29ufIXlcthl3bq8uSDzzj4bHtZ3HyBnzJ2j4Pu5Ak1njYpR3rf0O8UK91sJXZNXZke0oTKgGgKdXnlJkwk8SSgRIXqC7qxjL7N32NQZJYL8OuTxKrGXZRHgTsciaJ5UzRFsNuXZJYBp7l/FJiJJt7x+p93didIIkjvPtRxUj79VePDJv51t6U4S7usaWZm4btMuweOI+lEArTPiwJ2CmG3VnbLoTOB88EmBLDzjL8lqmVJbEGsNu6itNII8MLe4Iqw0CKQeelOyWWSWIHhE4Yhh0sYGeYHHQCpUF0FBmE1gB2DsOuzcwgs0PLsBsYOtHh0+AAkaxpOm1ooRNupPhi3EweBtnVrCb+2h1gkpXEbvhA5qugJNaDcnf8fYrK8d3KKyshIT+Qfg+7YQy7p67ZXfs4At5xw00aM4DLWIYdk8RSwz6ZCmAMsA0aKCXW/zo/+huHAICmXCjqr6ghDLs0iZUfBYCTMzUBTafTdnrtZZLEykFXA3Y1Y716/TYT0bDoa7ZGjAYxItodi4pOQCIEvlH5PFWCKbGB0InK05C1EmU9kthJErtBI7qclNi6MmP5UFD6ZFEZ354qygBEDLBj17ZYrNvvXV9U9b16beVhd5kksT1yPSOJnbeAUQXYEcNOAXaZDvJoecsYT1Sfh12Be9oIeH567D+ekCTWNPX2eTN5PRCzSaTE7kzHM+z2W4BdQCKnx54tAuy6UrplTxFk2AWYWnECvON3qeN79QPqqTy+lxtTgdCJOCWGXTPYEqJVnoafxr8txrA7ESCXASvM6wq7Ev2c03SkJLZg10svw87aQoR8XPl9YBh2owE7/p5cD7uFAex4Sqz0sKvai+lLwrDja4hQfd6TB+b7L33KfmYPG31vL45s30Ny+y6GXYeElca96zvdsrSonANQPYHZ9PRYtLx0/8yQDI7PBMOush52PNiMGHZ8HXCatxl2ZhM+RB5oGuurNN1zx/DRklj/GFhyhl0ysZtIG5sSa8ejTAB2BATz/i5b5f30ATD0sMbPsDObX7zX8fi3AS4r0Eh9+xh2dQmc3m09pOW/Dj9gV9fMMkD3hd6eT6+1FTGmwf5W6qyxfZJYw7CD7eNMbypBS3ENbnTp+yguz9pBdQMZdjMUrTXIRKta8rK2ntYXwrCzz6t87Nokm7snasy4rhnLn/OYYqR97NWHeE7LZT/j2nZQfpukbriOs3lWiE0QPQ/UHtufQUWszSbGK4dnNqU+EMilDmhTGHYkiZ3u4zRSMpbYx7CLom6GXVfohGdwoEq05j2vLd2WMznUC3r8zPRFs+31sGsz7G7taNAhL1XE8hBJLNC5o1t5GHYVYpyhv5HiUjLpYUcLrIoPjB3NmZdhd1kqBNj5UG7v31sPO8A24EXVsMlHP8YjiV3Gw+5zHz/A1yTvww9N/m/42tlPt3Y2fKEBneXxWiHArsVkA+yAhUQxlQI7gx96VQNsUYlPvPag9Xu7WOke2MnX7GyumtbZdGqbu7pU9/llksTOBWCnx7uCNWy+zYU4IImtdLMSsfGpKDrA+h7vQB9Dc8EYK7xCoRO1h2Hn7IzzMTDJzMJhksauZwV7/VVSYk/zElOdRl7F2jeLALuCLXJ8C1uAeaRUrceWSC5pSuwQDzsXCCvLwrIdtOyGGHbys4jEfKJekzzsctw9yfG3f/jj+P6f+w39ugLc8PigOvIotkjJZNCOkcRqwE7//+4kdR/XUQsD2OnztX1DfT07dFlUgmE30czqvOy4NiUjOGQf0OWF9vRXAAAOXv1p9VSbfAm2QicIsNP3Yllj6aAqmaoGVxJLGz6nAoSiayKSvQ0H5VqS2CGAnf7MoqR3IU3H2SmpZyynbSOJ7Wbht4r3FMLDbq7niivbGbYykg8LNmJZmx7HWL1cEsDOboqGH/O7dbJgHAG/6x1qcVQixr1GL5TmDywQS2NLpySW/i9qLUTvajbI9d1Ar0IMu6YymxNnp/q1Pf3NneOFAYROTqUkVqfEYqIlsbSpoPtVzrAr2qAsMeyiEGBX5faemGwDv/Xr1PePfeEKKbFthh0f81vWIJtWlV3bmY0k7WEXGYYdl8SuwLAbuFFd6PErZgy7JI5aKiA6bv4+fGw4n72PKaYYAQCc3Ws9xMuwiyxg51N5TYcw7KDWYvtbmbPG9kpi9fsjC4sCqX09jyx44mH/bWTx/k1ukvcCdupvp8hbG/p0nXI7Bn4dy3XccIZdt4edCiVU38+LyhsUeefY3QR5D2PYPaeDhN5+YydIlMpMuI4G7Hg/XwiFmJ4HjJ1VgPgQLGY9VtYNjnJhceQjC5GHnWT7jayVPex2yR9muofTWDGFksIeFDe8tDsrXQw7DtiRJDbMKCHAbqFZdXnJJLFoBBjAU1DV97OYvOlKZnJJ1GJ7Udzc0eatjQD3oh7ArgO8ccI0CLCLMka/DktLLEIe2Z1dASI6YzFnf4nFedJcZsAulBIrzFxDFbnpSzSYlRVrcA3Drr0rRdfmmJTYg+0Mfz37NrwnfhF/Jvne1u8nYxsAETpRVLV5H12AXZ5sAYj8qU0AXjyyA/uzr95v/X4Iww6wMrazuTqGrdnMBc+LMwb+XALAjhh2Ozf1z2qHmjc/WVdKrGDYVbR7yxiSVdF173d72PlShqmxl5NyaEz2JSgZwLFp3HEtyYxfXpZYtpoL2FUOy2XsrjRn2NUaGMih722HYecxYQYCDDs6/5ctJbZPEksy+DPmO6g+n4YDwdqflBh28hqIWGNin9sy7F66f4Z/8L5nDJDaSon1eBq5KbGcYUesUH0MInSCrmVi2A0ZGwmw24v16x88qb7OD12Q16RGqvuPAM3Oa1NuAqZtNqE60EDoBAC84ysAAPt3fhkpykvGsFP3f8zmnOVTYts79MTOVYCdn2FnGMRmcSYaZi0TmySJYagMY9gFfAc9ZcbVLjYCkwqbEKZ82LhnyhnXSOqv3jd5wx5sZQYQlKEsC37fyTTJjQ+d6GfY/Sef+yj+5h/6fPzwn/1y3NrSgDumOIL+DM8OLZOM5Pbmc/H0a6anmgKCgXGXGHY+/zrAAeevZOqcz+ckx23/zYOzwobm5QI8NKETqVr/EGDn87DLq1bPmmQ9HnZMbYFsB/iKbwJ+318Dvu5f+h/fVTT+CwDUCZ1Ip93rwE0oJyVWz0uNOu+xXpNxy5OxagGn+kIE6GFcEssk4olnLoVg/Bg2XNIG7ArfHEcer1Ryg5o/p5DEEkBNrCM+h047PexcwC4kic1rmPU5gTPEsCuR2B7cE7xx2Rh2KOem5zbnsQ/gZZYl0hOXeiy+8cUxFblpLYkkweph2EVRZPrrRcEYdmzzrMWwe1wBXB9+5QE+qQG7p2/sBHEXksQ2ep6kxFuF/6jnnut7mMY8X7CeUy/8LHD0avv/9THs76hx/t5cKI46JbFvIsOurpk/zOwAi1jvLLFm2JiXR5EZMKT8Sv0nB+xcyqRNU/UsgrUkdgEPww5QF7jHlN94QWiG3byojf7ZSmLt613fTsy8fbLwsPF48ZspMFG25HP6GMsoZYBduJHyLtrFMTlAjHNMbjNHk3ziia/f+PItxIHBE6FJBozoOqBrrt3g+j3s1Nd0BGDHQwtulK+1pM9kyD88dMJl2B0z/5qtbQLs2C4DGbkn6n4NLX6fe2Bf/5V7h63fLwYCdvtb6tpbaHPs7dnMvRd51PWlkMTqQZckI3kbsPMx7FqNKjVUJAfI7DnpAuz6zjsZJRtT9qYJ+g2a0AkxJhsrEF9KbN0ITyUbOqEksbFznICaqH0Mu3wEw4487MhbcWEAO5+HHfN0ARjDjt1TumG4tJLYIMOOPOzmZn4w1yY/V8LDTgJUkS/tijWE5mm0J14tj8eTGrgo2ymxgIdVTIvqliS2Q1Yjiq75bQIU6X6dP7DnIbKsFfo6iewcECwpifXIf9WT6M9q4gF/rj0NTHaR1DneHr12OTzsBMMu0WOW8rBbURLLrjPacJpmsfnMz0ToBH2+cUgSq+fjacYksWMYdj0JsfwYOgF/ujbqEjuZ+oxlgEZv1aw3pTFZ9z55rn53ZTszrIhTUoLQcRbtDUjLCt1sht0QD7s4jvCHv+gpvPPWrmFUlPEER5Qmfvy6HftbgF0Hwy5pA2z39OLy2nagV0kmIM/UaxP1Oc8XZ+5rsjo8LWxyqhw/SpLEZgo8il2iQTslVqhCNPMkCgHV1HslU7XAnO4B/6tvaIUeDKoAw66oa7PZhiRrW4NsWrHxiHrxXEhib519Evhb7wLe++fbc+yYGkgsKBvWn+jP0pWgst9LSazHXL8zdIJAXFr/MosrczweX7yYAYhN1AbnOhl2DICJUStVDvUjcWKumaaxG4gmsdeETnAPO5c9W10mwG4Vhl1mFRByQ59+5htfXSmx22vysAPc4Anfmv0u87ADgN/y+D6SOMLrRwt8SgN27350L+hhN5m4ILUBHxkWdRcaNNMMOxus55lXnv8Z4J/+PvUv8H73ttXn9DAn3XJX6MQGAHZlXWOfPOym+8gjNWBHzAOEU2eHMezaHnZ0E/qM3GNi2NWaglvVFvAC1AXuu8ipmYvthFeUErCLjJRiN4uxTYbBi8JO/l0edkBwR5efA0cSG02woOPv2Kn2pj6KG8cNneDHxBrqpjGmnZeTYRcInRgsiXWvAwvYNR6Gnc/Djk1cQxcsr3/Y/fnuM86Pk2T4olQdhMv2MHLYLEE68ex6kpG7BthDTJIXDu37ePDwpPX7QYsVwCS45bm6nne2ZupzoUmaD2KeBnnjinYc9zVjxyeJ7QqdkJJYECCcmfGmXoFhx81lATUO0Eu2GHacNceKhwXJ91R7GXb6mFLuYedKYo0srS5HJ6ud5pZhZwC7psPDTtLzCbzzMOxKJJcsdEIviIIedhocKk5bO+mRTi6soxSYKmlYWqvzN0wSq+7PLQewU39/0ogm0iMTLaqGpcR2eNiRbK04cRLRiW01xN+THrNFgN3eo+rr2aGVx6VbFgAxgJ222RgiiTUMO8+1WJV23PWxteIYuPXZAID3RC+O91K5yOKLwLo2905iPOwYw25pSSwLnSBJbJoYEIovNJqmMZ9vJKXXAgCcJEwSO4TR28dgZWWtBroYdvZ97aZunzG4zLjGmTQaRNCLmCtbE3Ou6sb1N8s9ioGlQ0IuuKyH3cD7oyTAjjHsHjKmBN2LRubd4WHn2cSmsJ2D7cCiOYrM2EwMu0WAYTcvKpwVlVEF1dK3mhh2jfCwI0ksGwfPigoJSST1NZdqhl3UBADinGTCO/7fj6kAy7isGgbYTdp90KYVk92RUoLY/EmtPo+3H/60AoF/4Vvx6OJTAAJstb4aKIl1piI9FqRx7A15sJsrLsOOM1SNWsgHMhKIu0cbXB0MO7YxnUSRWUsSqFax5591edixfi1FpRh2rJdz7n0C7PTvTUpsk9hryqz1lcquqhsD7G08KYAx7Nprhj5JrPrbmSclljZF+WYRf8y2DJ1YE8MOgGuTIwC707w0Fg7XtCR2e5Lisx+zkvynrm0p9l2gv89MGjZ52Onfs82D+2SPIBl2vnnlo/9KfT18vs041ffszpY610YSGwo5BYDt6+rrgxfbrzWiVmPYNQ12yB9muos8duOIawFK+QAP+2QdHnYdE3ZCDLvGLlIdhh03EOaTL0liI9s4FUXbS4ViiLcyYFvLcY7nbELy6LaPmNyhDiSG8snKkcTGmUmMGpIS6wPsosQafpriFw973oYtYNNNH8h8tXLohPr8JrFlWgKSYdfvYZcmPHSiZ/f8UNy0x250esbMQQeV8FM6mqv3vjdLncHflB6wynTbeQ+8mqbB4bzEIpRexo6vXxKr5QR6YbGzRYtcfWw8xOEyXIN0vPuP6Z8VYGfNfSOvAXlIEluSLDuJUOlrqBuwU3/fmxJbtpt6SXsnyWvTwGFkGEksex8xv/4dT6UhoRM8JbYavSt9mleW1aVB3bnZ2GDXdui+93rYafnGZZPE9oVOsHtenudIn6s6mZjxIm1crxsq2gzzpcRendjPdqaZj4eFOIe+0ImSedix55Ugs1lUL46dcXDXSGKHe9gRAxB7+n6dHzLQk4EyRhJL3rlDGHb6OjNyMHbfspS34Gd1890AgHfGLw8HJN6MMuBG6Wz4ESu4qJrlGVueJpxLYil0gi80+CZEbJp1IUnRxzzhoRNDUmLN/dUviR3mYWdBmt2MLFhGAnYenz8emEXeoXyRxYMtFh5/s8siifX5ZXX/AQPsiGF39LL6mm7Z68wAlp73L1QLvGhDlDYivaXHgyuZBv8Nw859PgL/qOevS3Es+r0skKkeM6ENZpLEcoZd2fqMM+NhF2LYURDHbvi9DC1frwlt+H8pU2Kthx2RKGIN2F05e8k8/FqpQhqWYtiNTInlxxfzlFje7wiLAOsB32bYtea4urJrZtHfOscTSIklhl0dZc7josgCRn4PO3svxR5JrGOHJQC7tOEMu6b1fKgKlLULGm90OR7E4pz1KccMYOdJiU1pU1SvHxI3KClNYtNfAcsAduHHOww74WFH7LpJ6r7+V//WJ833v+uztP0QXa9CEksMO9q8MvOxvparZIoT6PGJALuueYWv0V/5Zfd3+rgJsHtI7U5XSuzbvkR9fe79nUGkfbWihx2wDT04T3ZQxGoyiiuS2LiA3fIMu7AkNq6JYacpuFWDCjFqTUl3PBochp0GEVCZD5ekBVxKVeuBcicFdsgweM4aUs9F+u0//QKqRr3+J15tG3YCHoN6vQCoo9R6M3WGTtBNxy42YkREHoYdB0IYiFiyBuFySmJDgN2w9CUL2Omd79LKoWTiltfDjkm+g356spgkFgBwcsf5cbps6IRg2CnAzrPrSRLOZFu/Tvt+PM3VrhRdiw89gB1PyOuqAy2JpR2u/Z1t53hNQxAlnYP+RlRdByWxXWnWAIIpq8afJIlNo1N3sWtLC475Spog88RZ+Tec1cMbqdqz+0SPrRsmiY0SII5Z6ETEJLEuw65iDLtODxVPneSlTTfV143xpPAy7MRiyuthR43eJQPsiBXRmxJ72p5z9bhYJ1MG2LmNPVXcIYm9NrWP3U/V4+7l4px7xh5nI4QBGS3jbs3+Q37sMIVIppEPGBvpPpm1ALsHflmxfp8EKHaOv1IyZ8BJzmRmgJ3096O69pkAgLdFbwTHjY0ozrBjfUk24R52/X2LtzySWJqHtzKbMs5BLg7iRi1JrLvRNk1ZP7h2SeyAOZAtpncSdX2PBuzoPSVtwC7RjJQoipAlsVnccnNxl2EnAavNlsTWAySxTtGmRDzFQ+jP8OgV9ZUzyRIB9DrPQaqFdk98pEE2CtPylr529lM9lpiUWPf5Dk/12Bti2BlJbKpDJ9TfzzxJ1md5u2fNNNgdBxl25OvXD073VoBhV8jQicvkYUfzUuMCdvtzu6A/KO+qxyzlYTdsnVI2bHzRY5jjYedl2LkpsW7oRGDDlK+Xab7kG+qAk/zKgyBjFjpRa0CFe92lXZ87A2CMhx0j8fBjb/jmEey6okCCptGvKWypLqUk1vGwG8iw0/dxFlU2XIyeVvT+vn5jj21CzEaHTnRJYtmagOYffR1T6vaNnYkDIP7RL30bvvZL3oYvf9dNfONXvku/lr+/zzSTmO4H4ymr5/I62cJpo8cnAvE8pARTD1+x34v1OR3DrgbsHhiGXYck9skvVj3iw1eBu8+2X29graSBrOoG21oOg2wHRazjiEkj3LiAXXdKrM/DTgN2naET6uScmZTYGkCEAhmmyIXcjgN2Nklne5KoFEOaLNnFUEcx0ADbWWSYI4ucM+zap/CDLx6iRIIEJX7+2dt4z2e9q/UYThVOY+thV8U8dKIjKZLOCW8UK5dh55znOIHy1XD9p6qyIHgQaXYZJbGhhbikRof+Xjc2hmFnJbEygUl62PGJa5Qklg8GQCuVyRqwD2XYuYO4Zdhlfm8lwbDzyRLpOci74+TkBE3TOAOqZdh1D+yPHqhxgaRwV/cIsCOG3UPn+De6ihOYa4skAxQ6oa8LX+AE4GHYkWSBALs4UgmoFdB0AHaGzRb0sHMBX+55F4tFD/+5ahozIXhDJ/jxCymHkcQmsTF8pXuJ5GslA7RHM+wWlfGwo4XBWd3hYSel8B0psVWTdJvGb1oZQCEgYzKA3dyOWRSOYxh2M3O/0Rwqme+xmZPbktgn9mJ83uwAf/LLnsbBvymAArgzF+fQI4nNK+ZnxJ7XpMTSmEeeH/MjZyFEktiiS66qy8gVqUchxkB+bO5ZB5TR54MkNuMksR7/Jlr8ZNst43pT154GALw9em3DGXZsbqvam3xF1axBEmvv2QVLiaWgkdOFuwFgD00w+6SHHU+JHRQ6weTSPTUoKT2OlR9UU2MndfuMwVW3zxH1PilqXNmy99IsS1BUZQvgNGqSFsNuswG70Qw7zZ6tEs6w8wF2He9/AMNubwDDbl9LYou8m2EXZ1OgAeKmUEnatLg2oROZsgQyLGCfJLZkjCt9beh7Iw4B1TReDQCne8sw7KQklnvYTbuVVptQbPzIEr2RrwG7RN+Hu2dWYr1XKlKGs/FdadskT8iIU0MlsQ7DboSHXdOY8+xn2AUAuyixoWpCEtuyc2Lfm9CJyGXCJ3Fk0ji9zHXWMydoWimxmc+PmDzsQF7EFgNIeM+iGXa+dPqNrJQx7IKS2MB7mFgZ6VZz6v4q4GnHa3+W4dUHaky4sjVwPTbEw477Wgt8RwZOmL9JE/y1r/4894kCHnZTvXFI499MeNjVyRSn0M+fu4CddyPo5K79XkpiycNuR4139+fu/3tB1WwG/KF/Ctx8D3D9M9uvN7BWlsRuR3pwnmwbT6y4UieJ39gpZ9j5Fmn8QxeUycKcWB/DTktiNWBHTXapBwxnAAoMakT9LIr2hUeN3lYamUVdzg2DPRfpR155YAbYV+/7TQb5uYkjWOZDPDEgiQwj4NUdOqEulBYw6gGUjAwYMAa1l6p8DDtHrtcDQuprbUINkFcSqydr0Whw3y9uCBxM5KKi5BmS3AjAzkgal2TYPdC7tle3M9tE1YVdrNCARYCdB0A3Ug2QpGKBhwt3x2bRw/SiekwDdqmeMK/t7TjHa6Ku+5qbTShiNyFiKbEkie1h2MnEJ+ahBqgxstaDfNNx7+el595nFZLE+lggvOHifZShi3PKPF3/3MNOHy+FR2RJbCZnkrXR6zsMuxHJakVV///J++8o27b0Lgz9zRV2qnDCjd33dkudWwGlFghshAwYCZBAlhGyCSI4jec0xnvYz2APy+MZJw0cMDgCQwYMz2Ae2GBwwDLY0kPoWRJgQAEkdbc633xSVe2w0vtjft83v5nWXrvOubq1T39j3HGr6lTtsPZcc37zN38Bu64Xhp1hwC7FsMtJYvekxO4bwzeqJHk0J4mln3dbcN8i0hTaiA7lXO43ZtiFTFthZSQYdivT4C/+i78Uv/6r342FYUlsAFpIaqgby7s2nRI7C8fDwpn0akZpKgE5V/x384HGx+mL7h+Z5ZyQxPLmcpoklt5jApyclDZ6930ALMPuZnvYqXWWG1JToqZ0tsfysEsAw1oS6zzs3PrDn21VGBc6IZJYH9zyJbFTALvpIMZWhWOMFr23ZXVNSeyIh12JDrdVAAIzEj1JbBuzrwQ8uuGS2C5hcD9axJ4dSuVhJ4Cdkn6OHbCOMezoMPN8OdIv09g5K5lhl/bEu9jax5rN7GdRo8Ol7rNobdsOFNYgnsvss6klsV30Gc9q344kfp/M/Nvv17i3MinRTeeDJcXYPvCdrmFQoEAlPdZWADuS7zUuiOGUGHbewfef/Z3Av/8h4JFvdxPVxHC8djDoSbXlPOxMci319jxDrxRqcS8XHdYL4/JUrcE+YBfZOfHTGihJrE8aqYpCPWf6c+egCmYMi32BsQfNvDxK6AQzDeEksfKceq/ft+j6/ngAO+5JlIedY9jtGS9lha2xfx8BdkH/n9oP6EMI9pPbW1M87FgS23QK37Gf7xsXnLo94fkyzzWfsWLSPuYZS2upB+uqJa4GDmPzJbEhiQEAcKVYdet7/r/RZ3C2tHP8/W3w2YgyJbgeX/ZtwLMfzB/eTqjHlMQOYjiNeoWmtBekpAWz80ApM+5doGUM8mEMQN+PMuzYTHU7aIYd0JG0TCagEAxQQA83hG0YOgEF2NXAgjfCTZ5ht2k6vPpwK2j/Gw/9m4ZLo7vGOA+73tQOsLu2h51PR5ZKNNS9alaYVnpUFYC79mvfEH+0aGIfT4l1gArgFhx9fcvS5OW5YV1azwu88BX2/3pywIEMu75zDQY1XW9d2c/3zsnMH/fcSNE90VUn3vvR9XBNYAZtEGZoBQjk4mu1nO0D7OzExtfzlNJ1HGD30Hv9N7oELFnZRDUA2FHoxEiatf25kpQCzmOE5oq6LMTgf1QSu4dhx/PkThh27OsQs0A8SawCoFOSWGHYdUO0KZZgoNJEDDsG7OSUeOiVBHL/GOfNLQMpMWCXYNiFzUMqJbZ3J7N7N9w3pbrGvcecjEkBDTMOlOBNL30/VAuZGx3DLg3YGd14JGRPDIg9aIO5NsE6awI/I/nVIjikmN+y/98+UGudOegwQ8Y99yjzU3cCzSb0mkXFbOtJkljfNzS5WZ0C2J2/BAB41jyUsIsbWZph17r37t3HCYB2rD7++oUFJxKsWO0N5zzsYknsrCoU8MKS2NjD7loMuwMksYt9KdP0Gk/o19aHMuy6xLzGzH/Ti+0E4FioniS27RX7igG7NMBy02rUayhV9H76aoGHA917a7Km0XPmaEosA2xxT3IIw44Buy7DsOPHKqn3rtHiQgN2wrCr7LrOhwopht2uiz7jGT1ugRxgFzCFH6dyHnZ979jxN93DTvfuKp1UGHZDA2DArHFEjJPGbugFVNk8AH7qL9p01Z/+X8afb2JKbNcP3oEnYPuxMlABRV93jQeacfH7ihl2tF+en7r+NvCw0wdZ+p40xkjCel/wftyBhaMKO/W6S/TWH7JP77+cJJYZdrReQz2nMd793ba9k4jedCWPMOyu4jTffZJYAJvCznHLfu39PDzgTwUl6UOIZ6cAaMA0DzuPYeerXXhfeXvsAESei30Ng/cyZ4Yd7TF5bqa1fKiWMcOO9zghgLa78rMPNveTr+H81H5O9zb+fs6t1U8eGH48wG4YcCIedqdoSRJbdjFg5zHsRgG7yv/gh86ZuSc97OxFuuqchx0AtAx6SWx5yLhwOnhucFpmmyk9fScMO6eL1qy0cOC8QnTSlv7urUdpwC7yuxJvodpFeI8wtRzrIPaw44ESTYwJQInfSz8YFBkp342ufQy7QyWx4mE3RKeVZeBh51HDjTMERiZoRIopts980P7/yvc5PIRF4jXb9F7vkSfA3VUA2HETSqzTvuKU2BRgR5v4giUYjbDuuASw2yMnfPkOA3b2/Rj+zI6ZYTdTgJ1IYglYyGwsIoZxFzDsSoOhYIZdehM1DINKiE4/z6xSiyMcWyV1oqZved/Djv5dLWYyVXkMO5prOtcU8jy5bX3AsDOu4axzkoxEsdn8klgFpmZJLDOREx524elWKiVWzIqPyMNOe8zkgCAFNNSDnQvEx0ZvRGnzyGtoeNo+xrDTm7K6t1/fb3OSWLchDtkW8hgy59F44NN9JYmdVc6fa3roxOAYdvUKWN62X3PQj8ewI69NmvdHZbc8/pkxo+VgDHxPAX5Wz6AjNsLd4V7+997p8jzs3OZb5PftYQy7H//cA/zK//AH8N3f938mQXZ9KOE87Ny66iWUC5jIklh/3Z5X5WGhEwd42G0mM+zsa1kRw259XYZd1sPO9Tm8EbvyGHaafcUedscROjEqXUoVf37VAg8R2Abwmg3sYdgFgLyqQzzsTkuaW9lGJ2DYXZLMm4NTKnTyM/06dqgt4EGvmYNxPA+7JmbYscdkmfOwk2v1JCSxCVsA2LWnloTOWdRH36jyALtaermtksSeYg0DN4/MO7smy5r02R91j6HX61RNlMT6gJ3zsHMBTgn1GAD0TcbDbo8kdnbiLDeC96CJ51GwATPsEDLsTF6GS8UBj6czY/f6gz+WGfBjj3Ym6/DYFkks9xDqkMlLST4Whl0zlhKbfw8C2AUMu3C/sEisWefXYthN8bBjhp0C7Ohem8RY3vNczHZjn9bTOT0WS2KrJdYcOsGWbQnmKQDg6k3/+0gSSwDjiX3Ot9Z0Q/C+fwKoet16PElsP2CpJLEM2BU0YXsMO3XDplNiEx529PMmocEHAAyDksT6J+/CsGOvmtCLIiGJdQw7N/n1CrBzDDsnCQnpjaz/5snjfgawi049aOIePA+7fCM1JSU2mhgTDUovoEGRTLa88cVjRVP+5f0Z7A0xoEWiNj64YRl2/ulVCDJ4DLvCTJfE8gRw+732/8EJ1uwQhp2WYFHDxCaed05mJDFnXZwP2HU1S2Lj52Fwri+cTIwnVnkbBwB2t1e1nIRFyYoC2B0Dw4434StnjL/1GXZlBkjzQhsAJ4kd+ASxwLBn09sp38R5mb7uHv0c47ItfbqkU6X569CjRP4toOY3SrbkRbjDycwLBa5nTY8TxRuYU9rsFjTOt+y+ee2UWNfojXpQ3aTiDZYp8w1BUcr7ZzCNx2YhDLu5Y9gFaXLyMMKwiz3sNEgqgF0YOpFKifX8jBRgF0p0BAx/KMBvVRbKn3H/uNm1TkZtn2QJLIi5l2LYsYcdn9iPSmIDjyvZiA+ul5kC2BmDq7mV1t/t3sz/3jtdsvlpvU2DJJp3g7sGEwCg//5vfQ4A8Dc/fR9D4p7VDDr2sNs0vay52xTDLpcSW143JfYJhU4A8hoX5Il1MMMu6WFHG1n0eyWxPsPuuEIneF5KmoMn/4ABesWw41recV+PpsSyJNbfN3T9gMtdwOJIFfUyJ3TI1LHMOtiHsPyVvSBnaH1/Q+Vhp32Snc+mL4mNUmIZsPt5ZdiFklhfjng8DDsnieWAq2rY4RyB1LCz3wtgx5Y3AHD/U3uebzpgJwoFeo02lTXFsPP921KAt/4MBp1ayfvl2anze2z895tj2AEQ3+8u5WEnIGF6DmZJ7K2FzyTk3s0x7Oz3pmNJLO3ZApWdZ+OgP9djYdi1G+nP5T1NkFCvC/u5zbsQsNvPsFuqoInQUy5bqQTzoLwgOtkH2M9v0gEIV8bD7mRF9i7MsGNJLO0NhmrhQic4dDG3rkSAXXCQSmPp1qldWy4aHq+hJPaGMexaL3RihZYksVXAsOMbLUo80TUC2LXKH8krtdBuen8D2PFjCMMuGOBJSWx80tsNMcNul/C643r1oR0gzCLa7HbeKRhXZKQrgF0l1N6xxneXuibBKWzMsIsBpZbAxw5HsmENK+lNdcANo2QlgC+JjRl2/qYy8nKQjcMIw67vLFUeUICd7xERxm+PlsiPnCT3Hkli757MLKAcsmLonhjqvCSW2QwM2M2xk4mVizcEnmH/MNjoapWEa4zBX/wXfimeWdJY5XF4lAw7dQLJfjjdFugaJ93PMFUjhnHPPoGKYbdnE6WlgDxOwlpEDDfeVCYksUHoRPi1nl7ktE+nxBb+XFOXhR/hrv5fqPvjEA87HounJC8qaCO9BUu6Jkhi93jYHQ3DTgPGYxtYAuNnQ1oSa5SHHUtiw3lAALtCrZ3hXNK1csL91i7DsOsbOZb3PeyUJJbHA98bHDqxfYRWedjxetf1w94N37btnGUHYBvhxW37tXjYxZJYx7CbIImV0Al12MDXRn9WI3U1fx4AcOcmA3ay+Wm8E+SkJHYCAKT7li4R9iUMu9Ix7AA3F3hzWngQ+diS2AlSZqpJoROArHmr8kl62DnPJy0n4gO0deP6kF3Sw+44ALsux4TIFQGupl7iHs78f9OAXcjM9B4jHTqhwbTVWIoizSsnBR18ZoAxlr+yJLZC58lceS4RSSxblBj/PgBsP+YkkuTNLOmJvWP+eu/zCXrYpXw8YfsdOaSp5jFr6CZVANjxmONQw2pocMv4jLNZxx7G9H70Bv/BZ8efbyIbp80w7BxAG88L/H6ahAeklsd6+3HxsDtx8vGdD/xoiXpI8nApsb78tSoK6Yu7zL6G5+hbc/bqCySx9Fkwww7MsKOx1QW+eZphx+m+9g9uOGAnDLv1CMMu/x6ujJ175r0/TudV4bWMqZ7327/GWnTcWdUe2260poROiE1OH9lYsS3A+XLC82UZdqTupPEndgWN8zMNJbGOlBA8R0CgiSSx1GesFnPMqiLGa5hpd9MAu77rVOjECdqSpG8dyUJ7ZlbYUTLuYaeoverDGLo2nxKlgKerzvdSihh2oXmsupm5wekSSDFLWxfFIAw7BrlGAbvKyWtCKaF+nUJTlQ2wYtiNMLUkldFLiaXEKZaphQt0QrLZB0mVR1dJSew0Xwj7O+xhFzLshjhxKxi//BkaQ2O82A+0CjgFALfeY/8fMew4QOUAhl01lw38m8yw41P30FuIKcEM2CVOvJgBwCEIM7SxJJZen8ew+6E/APyxbwX+/D/n/e577q5wzrcgj0NJiT0mDzvNsFObge2jpLmvrmjx5VCdQY0vut4mB9ipMZELnYgYbiEL5OJ14If+ILC9gDHOzFcz7FKR597rVyd9wzA4dmGKYUcHFoVs+juXEjuhaWeG3aqkx6lHGHY5sH7Uw+4IAbucfx2XBErQgYxIYpWZOo01bmbDeaCc4mHHbCSMAHaAzFO7Lm3+LJ46YehE36Kj91yVxlvv9oG9u7bHEqrBLSsniWWGnZcSy2s2h06MjE0JneA5dh7/GwM/ez6ry9kzAIDb/Q2WxGrfICXj4k2YD9jt90R75YEbNx0rG9Q40wy7eVWAWz8GujwPu2IcsJtXhTNsPyR0YsJ6xHNbSl7kFb03ZtgdnBLbqf6YSwHMtxTDbikMO3d/2NCJgI1zACPynazUWjRaNDeZeoE3h3P/3zyG3Qhgp+dJVRpoHfUtpHllZXguSEtsQ8CuNq1/wM+SWA6dEBZwzLBbNzHDbqZ9qVMHyZIS+wQBu0RKrJvzZ3k55k0oDegXpTC62cOuGpqIYVe3JIntE4Cd7vdTNXFz3/V92sMuxbAzxpsTU4C3/to7qNOhEyyJbXzgZyy1mZmfDJ7pnnjUEgtAzwy7eRAQxAcTtNZwoIVhpuHAzxlIYlM2DsAosHQjqnYMu0hGLAcJ+fFyZWy/segvLUhPAJUxxturpRh2v/j9z+D/83/7JfiT/9Q3TFfcTQLsNMPOV7uwcutsCsMuYF1ycWKrk8Ryv2Ln36Gc4SqQxDI+Eq0rfA/I94GsXZSMNZ49mUX35UH4w4H1eLuUVk1csxO0le9hx/0/T9Cj3gUZDztp5pDwbFIL7brzZYR9GDoRItJq88gnZV1CEtsqht1CGHZ5CijLEbWBZshMAhD7CihJbHuAJFY87Hrr1wM4dl90kpE4UeX33Jkj2bCGlQTsDkC4OZloEsPOPzWKkjSFwTjCsOPFfHYGrO7ar4PY9DA0YLQSJ8GvPbQ/e/6cJqiIYWcnoDGGHTf7DrCLPeyYYadp1Pgr/6b9/8f/SvxaQ+kTj8ejYtgpwKSsFej4yPlS7mHYudMyJ0cHCIDbx7Br3WlpHrALQx+U3xMA/InvAL7/e4D/7f9lH8so5hxVShLLC5sF7BxgoafzqjB5hl3l7tVae1/tKWaKnBBgZ6o5ZmWBbSp0ImXODkRNgn0d7GF3RJJYHn/75Ho0LisC4+SUndh0Rklii32SWJ0eHs4ljQNe3twE49EDseyc1HS9C1dQDY2TxNJrmJ2KlH9Y2/mxKozXA+ybH7dtjwVvmFlmIpLYV/z3o14Pz/ujjy/jn95jUbgxFzHsxj+rq8qCCGfd/dHfe0dLs/NV4IZjg/dJy41csXUIYA9lveeAD8gZY6LgCW9OCyWxAbjlpcQeFDoxgWEn/qDTGHaLghl2BwaM9ImeRvWYtxIMO9/z73gZdjwv5da7+A/s+CyrOe7j1H32QFoSmwSy0gw76XnqMp0uyEXzCido98JkS0ti69qlxPKYAiCfzRaVnSNp3+IYdm48X+3aCMBhSWz+fT5Jhl06dKLpBhU6UR8Hw47sjvggif1y66HBOTPsaC1hwE4OmzRgt9fDbtrm3jLs/B4m62EHeHNiq/yFuTzATh/U8eudn+5l2KU8JRkwZnmrZuPt87Bjht3ZPJirDYey+ZJYns+YYdfDf06fYacsfm669ZOETqwdSDk1JRbAFSVjL5r7wH/97cDvex/wxs/anymQLrdm/cIvvYuvePet6a83YEKmaq59tQO1CwccPo4k9pwZdmaAQe/sClSf5iSxdL/mxjHfA3yNA0m4Bihvr2YxXnNTJbFG38jVEl3BDDvbxIsMxxzCsKvsDUXNeqsAuyh0onOBCRv6HMVfrNgD2AnQ02AhgF08+XWwr3lRukEn4RSJjTmzm5iVUKPD/au4gY087JScdYokNvKwU4uxyTHsEpJYZhU+VQy7a0hia2p0OHSi7QZUxm9ww5PBCHSdIoll/7rl7WwK07VCJ+gkuOsHvEIsz3fdYsAuOPlkwI48KprE/cjXYaCGdWYSDLuJHnZSoQ+PeNjd97+/ySUpsXT6yLLY3YWShaYbguhkmSWxzLArjXxWRWYTNcUzaS6AHQFmvKmsS7uZffXv2l/88T8HQEu9Y0lslmGn5mvd8FXliIedlsQWLIHcP8aFYVcos/uqUAy7ROhElBKrDzb83+1QHE9KrIAJJ+O/R4yJSoVODMMgbDoL2IWhE/48wCfXSQ+7obNjiV7Pepjh0TaY9/Tf0Xi2zOWUJJbmPP58jHHzIx1o1GXhyc33gb2ehx2/bpbE8qaSfSgB2QxXBGqOh04kGDg8fzGgNVFaeVXZ13Ta72FjvJOlP0vx49KS2GGvnF/XpQKTTOKeZbCU5zk+FGKAI50Sy6ETI5LYSQw7/tymM+ymetjNEt5jkyrlYceHjehxe+XGYdbDLpBLOsCq8efFG1YHp8RST1vWc/Qo8ADqHk962I2lxAYMOzo8GpXDAgLSL5jhK4zcNMOunjFg1waSWPs6tkgz7DS4t0542M33Anb5NNyDK8ew6/1kcAfc3MAxF6isIkkslCT2lrW0qZsLAENaEhuydXRpa5E9Ms0+6WFXOIA2F6rYdxkPOyWJ1eu+eNip0InIwy5/P/L4Y4Vbq/znpf/N7Gu6PZJY8VBmTzsG7IRh56vs9AESH1TeeHYd4NadoZNwGdkzTJDE3jeWVfzeT/154JM/YHudn/oLAPy92hPreScw7DwSgQkAOwmdOEQS68+/t07coWiJPmLYoayxZklsEDoRjWPej5++YP8fANaaeHJ7VTu8Rhh2N1QSa4hhtzVzoCjQEjJckQk1m6uzCXtZTgDs+MOkD1985ZBAQnkTgBK8xvFk0IuHHU2uIXtHoe8rGkx9ShJLDLt5NcigS3ndcTHDjg3WSzMuiXUpsUoSOwSDLVGRh50G7AJfKamUJLY9dkls4uQ8Zzw/8velITNrFToRnlaG45fHt4zLIG48WbyYL287n6Z27f3NtUInaPP9xsUWXT+gLAyePwsAO0mJpUWZNpKpEBhu9ocRhh0DMp4cSFOVw+vAn1EoiT1Whh2ggicuRBaaSrMGVMMRSGKZYVcVBQxLYjNy+CkbRJbuM+jKG4BFVQAXzltQQgf4dWkPO+55MkbF+qRPN3xVkfKwo8YqJYmd4NPoUmJp/FQLzD3A7hBJrJsnegbshiOUxO5l2NEGsGcPO5suPAf7AC4OkMQmGHaAve50P1xiIWbsUsY4hgp9Rk2blsQ6xqUaDzw/7ixgVxYGhWLZ7fP43LY95rxh5tfNklh5DnWSXHKiIjfJI/NvioETWg9MZENeEmB31t4f/b13tHSvw4cWZe170ZkEgJ6pK5WEaRLsMV77+PE5eIKtGrTHnReIAURsNC8ldgpI0E4DWgF9GLJn/hDvMd96Y3Lt8bDzGHYM2CnZrZ8Syww79Vj7grLewcoyIXJFfXNFINhbUPc4A/aA6odTHnYBg5bqKqUqSBXNNzL/hJ6XVAxA82u1Hnbp0IlKedixbF+zgG1KrA/K1loSm+pLVaLuY9cow84d0nhM/ZtWicAaANh0dD21JPbWywAAgx5LbN1hkwLshu0IYOcFIUxh2Pl7vaowEalASu1FUgCb9Z9zjy2lJbHCsPNZgp0C4cJiIJl7WkdqKAQkzH3uXcSw8z8LXgtYEstjnZUAfSDD1SzDgh5ruOkJsQB0EBZbenQRwy7/Pt40Vrl1cvkp98NP/XUA/l5tVNJ/SB0kie0jko142E2SxKbH+2Lu5rkSvWMS8jxexR52YrUQMezoHjixYWCeJHwYvPTi26taAenM8L+hklhDk/2WTA57SomtxcPOX2hHvQvCD51BJ08SGzLsGLCrZLJkIKuPUmJzklgXOtEHcqquH9AOzLAzimGX97Bjhl2xz8MuZGepjWZ4kpKqmGHnnqPIpcQmGXY82R0rYJeSxMaeOPv+nif/jdoQuNNK38NOGHbhQph6LWHxYr64HXmgcR3GsPOZHp+/b+/JF86cua87+fQlscwOS4Em4rFTcuhEgwdr/32tBbDLjJ2rt/zvQyA1Cp04JoYdA3b0Ge4eeaeJqYo8POh67JSHnSFpTM7DbjNBgpWVxNaln4B08SrQ7pwkVqfEDnGTV2jprDq50vOMZtiFktiSpZV958kjhpQZtioGjxeFM67OMuxyiVWJ0IlBJMml3HM3vib6ovG9VA/KNmLXCVhmqpnMGTzWwkaaAbtCS2JDmSvNJVfD3GP0hK+D56ltxsOuTrEuCLAzGzs3MhDuBR2M1LZVibTMlFnc8n9Jz8EiiY03w1GlNuCRXHgaG5IBu9ObLInVGwQGIkmaztWHXnIj5THshP3g5jSPQQfHDGCAw2MNa6YYkPSw667DsJvkYTdREitSRjcn75v3vBrzsDN9MnRC+61t2zj13uuJb7Aslg/hpzPs7HspaS19rVf3/DMfdF+PpsSmATae46Yz7MhPLwMAMsNutodhtxsqyy7mlFj490HT9T57OcGw67pEX/pEU2K5z/THUtsNx+dhx2xrWpcuewL/sXMMu/N3yUHgGdZuPVIm9e0mMLBX9fc/r3qxCSmxHIDIr7H0QieCfkeBVV1IDqFyn0NCEjs7dT3uAQw7PhTo4ZNGqsII4SGl6AEcYHc+C+ZqZhIHDDsGBxmwE4Yd72fUemToUHIo8sy0G1PVHCBl39LwYep0ht2b5k78wwefs4+n5q29vqtTK3WYFBSrfraNksSyh92aPeymMOzSHnZ6/Ms9AXj7lMuB1nMC5LLSbsaMhGGnADsPZK9wa6kYdl0bsGZvGGBX0uZ1S0BdRzc4M+xCs1gnqUo0woN/MuQYduS5YxITBC02G8zktN0x7FgSSxPmhJRYZpvxYFg3nUwi80Iz7MY87Ng/g5v/fo8klhl2js0wSRIrDW1AHwZQ1Pa5+3BiTEgA+vbYU2Ida0dqIs0cgIsMp0aaQY62G2KGXTB+I6nGFEksL+bLO/b3+TRFJcXWExl2D64a/Lkf/TgAJ139xOv2nnzPXbWhDzbNPAGZOUliExtTvg6GmrAZ2jglNpTENmv/pH4dAHbhRBYx7I4BsAvYFzMna86mWVNFJ4xh6ERp5Hp7qVaqtsFGNlWLUBKrZbRhZPnl63LC5DPs8pLYPpTEqvFTGqMSoXyGnwPsWk/auK9xX/PmXMlqZlWBzZBKic00sCmGHR9WoPCAhxtduwAwzhX7yfYOzLzYtpiRp5LPsCMJaCiJBUti1TxaKJ/FdiPNzxUW2HV9LHcRY/sthZP00mh7klgJL1CvgYInzM7OD+xzJ/PjXsCuw9ywJJbmFs2wUc9hXw+t2bQBGJfEJpqyKlhfZa4YZ9g9Km2DfXKjGXZaEksbuHLmyf87M10Sq8GkQk6sXd/Cc8JMGHY+COUx7EKmVCCb8SWxEw7BuGHXcuncr04NnaD3xuFW/XAgYJFgIXYiie1wW4VOMJi0aXzALuthB0wCWd+piuxj9v6BfS/1zN7zr+vgiWc+4L4eA+wyElbn27tncykHJgTY9f7BKtcFMU0dYNdh28Qbzh3I+02CcfzDOL4vws94PitFJbTbpZiE0+aoSRWwqeUpej90IvSCvlGVYXU9UoDdOdjD7raVjgJYmY30f/3WbfDL5jKdzgvg3/4L/5f7ZkJKbCyJNRGpQEqBVU1IDqHi+ykdOnEi7w3txttfRWQT/ZjMsEuEToxaYsGp2U75UoQpsfT3g5r3AAh7rg988zQpp0jMnze2jJH5Y1XwYSqtWxMAu9eG2/EPL14F4LPqnphv80Eedp13eN71g1ipnC8nfDYZDzvd73/X173L/Vwp0EJJ7N7QidPn6XW2bj0IUqRvLWdoWRHZNz4OcdMAOyeJJYYdpcTWAWB3PYadHwRRpxZrWhi2qNERU4PBB/FTyTHsEimxffAarnatNHqzYpCmTDzsEkENDM6VimF3EXr7wJ0yOA+7RErsSOM76mHHaTkhMJowhX6qGXaTJLEhw86dWDqvJfossx52hf98kySxdArCTBll3s5gzG5E8jUMA/7pP/Fj+It/8+cAAJ99ZDfLP/2qBag/+qJijoSNlF6UkV5ARU5DC8fMxJJYPt0Vhl2YiKXBob5XoHzAsOM6Bkksn0izz4Qy5pXQiYyHXRE2LALYOeZQUfkgSlhTJLH8b7xh4//PqwK4DAC7i1cVEO1+nPJ3yKXEOnDPvseIYUfP73nYqWu0jyklrx8OfJlnPewyp1sjDLvBlFkZ842rib5okhKrgN+rXSeMs6Kay5qYY9hVwrAL1k7NJKPmh+UGV2H6pcw9W1qj4W3euIRhp8cCM+y2zLDzAbspKbHO7JyeK5LEaoadXQv4xP5gSWyWYTe+Gb6o7uDV4TYu67ujv/eOlm6QBbCrfWmV2d+3AHbtcoDdIAAp37MaiOW1cBWGTvCcUI9IYpWsjQ9ehymhE3zIOzsb/z1MYzwDcMwo4/qUKUmxb13u6IAkPiRed9RXo/MS9hZ7GXal+z/3fTeZYbcnfT0qei/sC/eftd9u9wNf/o/443gsJCXDsLuSQ8o96wXd8zNiOMsBXMCwY8bofE6AnQkZdnYu2aG2cyTNY+yzyfcKj6WQRWnHvn3PuyYF2L0dDDtfEt94DLv6hjPsAsCOevuHHfVlGPCcuW9/Z3lbPucldrIedUoGW6CPAEyuT7/hDum/8GgcMO88SSx91l5KbNDvKLAqB3gnPwcvdEIxwxXLbgxA58O4TsCz2MOO9+phsZrtdJb2sOP7n5l0lelQlwaGQJw+9LBT+7Gyd0yroyjaXyyof5ElkeeqsCdT9SqeiX+4fstiHW8rw25EEqtJBMrD7mLj1sNpDLsMYKfwi9/9LR9yP1f7lJwkNgKeBbB7wf2MlVVe2nDtS2K7xl9Hb5oktqDNw44Ydj1v7vsN0PeRRlhOVlJARPih8w3futOEqNiQldICm26Q04Q+DJ0IB7gCevhEcghkB+udY9iZoZemLMew6/tBwLlCnYRdJhLBIpoyDQRTJjTRiYo87JQUjDef0X4mAW4dv4cdfwaD86c5SBLrjJsB5/u1G0uJ5TGW87Ab84PRoRNAknbuGHb5hv6HP/EmfuSTb4kn1atXA/69//nv4cc/b0GzD2vATjdSw6AYdnZDnPKCYlYTM77mYww7XgT4vXF5VGL1t+Jhd4SAncilaBOuPr92DxMgOmGkccoAfVUYFCTjKYddsqkRttzIYssbtlCSOq/KmGF38VrSU4ZPn8oEw64NUmLdhor9Ppn+ToAh+1HVimGnALJ9XmQxYMehE5zi5MDuLFifYNjx5t1MmSduSoWS7FzRWlx0Wxl3F9tWACyjATth2AUedvDXMvfYaj6he5xPLzehLFb9Ln/OzoDcPW4yQY7Yb2Vj13C+rzgZfR8DeeuFTjDDLpTEJhh2DKTnAMG+c+NIz1mhh91EcPUL8/fjG7b/Of7MV/zno7/3jpZx/lkiiS1nMMalVU8F7Lat6g2hPm9aP9OAHYNQvlx5nkrWDiWxdYGeJEaTJLHXYNjt9cCUcCsfRBurH/74m/jYv/39+K4/9MPOGkb1nFf0Nhfl4PXHDG56HnaN8rDTh7MyZvf7Dr5TNZZKmf4D8rCr5zAG+OnhPXjzn/4bwHf8l/7vyYZ+zMMuZNhx6MQ0hl1FDGcJkQr2IQ6wI//vSBLLDDvq64Mkaz40vdp1MOhRGJYDsqSzED+xJsmwe/tTYtuuF2Y3ypnzgp5i+fLzXcHcwevSRe/WqhcN29rckrl9ia1bu0KT+oSPXdv12G0JjB1KfPZ+GtTj6nRKrMewy4AlCqzKeUBWqUMytuaZnfpjQvVYUySx/Fo1u0/3xSmSADPszmbBXC2hf+RhBxc6URWF9Hx9KIlV60IpgPER7DEA2V8scDjD7tN40X3zJf+gm+8vX/fsi7JWRofWQR52nfu9oZPAiXlVTGP85RQ0RQGWES8KNbZoXTOVSokl1mvK9se+SLpfl3fc8/A9HTDsbmtJLAZ30APcPIZdQQy7hiWxlWpM281jMuzYw44W39TpGnvogQG7XtB10aqHEb1cpQNXeOAOgYfduum8dDHeJHddeoA+2rbCftYMu8sEwy7nYWfKSjHsDvGwczryrPQ4caLYy2R3rICdet18DfrMpj1VxJIsAg+7thuiE+m9HnaJUI+oQoYdsy/UIj8XD7s8kPEDf/91AMA3vt9uOHdDhe/7a5/ED/2sBWS+4X3qlEWnF3Y7uU4FSWJTTBK+DgwgpUInRB6SY9hpICWY6LzXJa/zCBbT8ESaTyF3l9L45FJiPQ84ICGJdQy7Gbqk5G87ycPOZ9h5xugRYPcKZApJSWLVCsHgXT+Eklh/np9nGHZ1rUMn3DXKpYZx8cZzppquWVlgl2Iiy+sKKfOx6fxA80RxVIDdVA87B5TxGnG17XxPNwmj2QEYYoYdS06qELBbuNdCB2IbYtlf5QC7buuCBOQgRAF2IonVDDt76FCQXYAw7CZ6fI6mxHJ5klhmUXQABuxyklgNbui+Igz3mciw43V6skfXO1XcP6jQCcDJViV0Yg9gp8eIMG8AB9gpwIIfO2bYqTlN+TV5/1csoz5gp4wWH/Jq9mWmphygAJDXaPpWQMh9gN3/8dOvYRiAH/vUPXyG2TiaYacAO11L8oDyUmI9T141343JQm9ItYfeH3z4Xc2c92H9THwfTkqJvWboBD1XRY/DjLgQMHgkgJ1b9/3QCUdKqLQkNmDYXe1a168C3vrX0jrZjDHsptjH7KswQZyfoh/U2u087CbkTf38V8Dg4bVz2xmxnXnRkNXL4pb0f0uzdXu6NgDsmLGr6o2LnYBtDSp87t46+h1dbYZhF/lScinygKwvQV/KBARvP85r1uzEk2bqXn4MQK8ihp07xNbPn8IAdgTYndS8J/Ytqvj5epWOXZVG5vsxSSwrDYYnMc5/Poo9MK/hYdf0A3777nfj/nv/YeA7/pALT7h4zQPplu8IYKc87PpWJcROBLdyHnb6+T21nZvHRRI79EC7zUu7tQItTEr29rGlz7ADfLD+xjHsWBJb0uYhQORjht2Ihj2kOkrwA232UpIlFXkOWJCFfWckDUYksbmU2FaawSHY7GmGHfpOBnvqtBMAHtHgm1WFJCKW6L1ENHnpdA1E6ts5+RFv4KdIYpltoG+ayNw+es/Kw+7YJbEmAdgpGuzeYhlUQhIbM+z88RtttCTUY2LoBKAYWm5BnOLR9KM/Z5uGjzxr3+Mzt93m4qMvnuGDzyt2QKVO0RXrjQG71P0YAnZzAuyY9TUMg7ARZbMSmNMmmU/2Qe3/NeUeOA4Pu9DzRTHs9qXERgw7TimVlFiDkqjwMzRJBtGklNhc6ERVJGXLk0MntHRWp8QGYRuLwMOON46SWNe3MMbk56mg5O8l8XOOeVUKs9qXxGa8SlIMu46lukcE2E1MHtVsBwYILnetYjrMHYgAa1buBYAMQx6w4+du1/J6toW9DyLATrHOeD4bl8Rqhp1lw1UNSWILP3QiC6hRbdvOvV/eTEaSWAXYqfW8RpeXxOp12QPsMpLYcJ4LaoyxcKMqwbAD3GfnDhrHwR99gOkZRAeAXV0aGJqbxMNu6zPsbEpscFAWSakKDIdIYjXLZN+vsi3EPnaAYrwsAsuCXP3E55xk7tX73Me6e/GySTAKACxrZ+miX2eR2tz/gt8AfM1v3TtG38nqOrfpn/YHDoRyzMzEtR7zHOZ7OOgh+XFW+za74iFqH2cWHhzA9pg81pcLshNCK2MKw+BCJ0CJzPSa2feRf3ejGZSA9xl3dCidBOw6t6bqerBu8O3/2Q/hV//HP4hPvB4zxMbes31ctyZ7vqXVbNzL/J2uAOz3Dl9p3XsBqoenn62wtXNSuxNLBQ4Tixh3AF57tJFr0qDC5+6PA3Zd3wtTUg7cC+M+87CHUWBVjmGXXHObgHEpa5r7PMcAdMewy3vY6Z/ranqa6wWwCxh2zMz0GHZG5v2+8J9TPFHbnQrbOgJSAKBCaw5PiW27AT/QfzU++y3/FXD7PcCKrDbW9zwp/52TJwRe5g7JVXl7EiWJfUinTudT5LBAxLr0asQey1QzB9gBQHPl9jihh51m2IdJyRqcNAbnywCw4z2vKX22wxOqx3rEKmDYmbLCZnCnsE/Swy5JhxcPOzvwdl3vorWFYRc3Ot7z9K0gzUMwQWya3ksX402yhFMEH4gbfLU7CTNpSWzUpAvDrpYTsVFJrJzs+jRpFKUzhw8ldYkGZRDj9SMF7PSNGzLsplBSWRI7+H5fTTegMn6Dm/OwO0gSy+ESzOxISGJ5g931MesFsGDZ33/Fbiq+5JZ9/R961zP4Ld/wXnzo+VN872/4Kv8P9EZSJOJLVJWTkofFIIkGkNp+8IIMeHjJSU3o1aEBvFSEfbghmrBBescrYti5CZ0bmTqz8S7DBimUxJbGYzSmALudDpDIlAPMEpJYHVEOAOt7DohLMOz0YlbpeWVMEhsw7BjY1ZJY/Xh7Pex4Az+4Tc/+lNgJHnbc+IaA1E2uicmjutFmgOty24qEHkoSCzgQLQSTAaAMD7s0K5gamba0z7dugrVOJVTLIVNSEkubSr2JI8Cu3Nk5kzcYs4kedtskwy6QxPLpc/h60OYf3wPs1NjJSmLHwdXIWuGmFm8CGx+wE89V7lv2yCu1VNMDGdjDrlVgHBUzmi45dEKH72Qlse6zkcCbfZLYrnXr2ASGXXRolSul6PAS80bq4wooeeMBzdsJSew8YNilQKpkSiwAfNvvB/6R/8wmXt7QOhjQVpva5RTAbkwS+5gpsabdoCyMm/PU42ngerEgz1Etie1bgCTjW1QWsKCxXtJaqEMn6gxgx719UhKbYez84R/8OP72Z+7j773yCH/4Bz8x/l659LXSAM9RpcQGHnZqDhqoV68poC6SxHa911/dA80fXTwfvvZwK9ekQYnP7mHYdb2yLRqmMOwcIcV5dflzlDswjT0TpX/Qh3PyWvL3I7MGWd6a8rADYlusvh8UYMc/5P04H2gzk5vJMJ3tG3r2Ig487EoG7JpkMv2NLrr+HJrl9gz7GXaR5yf3PJsHHqvumScG2I2AaFRPnGGXAgdTgJ1IYmfoUGI7uB5mr4fd7Czenwf7i9vLWQDYOX/ft6Mek2Fnb2IG7MrCqCSOdZTCId4FqZOVrCSWQidGGHYNM+z6Xga2MOxSXjOAJ6MQenswGDZaEqsZdt04w+58UTlWFvpkszDmYTflpHobNrUphl0IxDyVklj1GfBnnfl8xv6+QAjYJRh2wfjtQhbSFEksn94zs4MXRI9hN27I/+rDLS539nTpmYX93aKe49/5jl+A7/9d34Svec9t/w9k07xTse0n8jxJhh01guWMFw77nniC1ewAoVmHDDsN4PFnYkqIS3l4qn+DT/mlxMOOGxpHmXYMuwxgl5HE8oRfF04SW6NLSqY88C1TIoltOwzD4KfE8ud/QglIV/f89FdYQFgOKRMMu7YbvJPokFq+CDzs1jv2sKMGYfBZ09E8FRRvkrSsaFYV2DFg1yUYdhNSYrnROCqG3USZpcewo/F4uev8EAYFxLFkqQ1PcgGYKrg+WiZAzU1TZhh2SnYrgF0Q5gOow5AEw64mhh2Pr2tJYvm9htdNS2IVwFOj3S+JLeduLgPyDLs9n1UUXnRTSxh2viSW56IdN8N7JLEaqEiBDMKeU4cSJ6EkVs+DkSQ2ngPK0r5Gs4/Vo+VrBzDsZuVUhl3r+/lkqu8HvP7IzWuPrmhMqffEPvWzwn9P3M/q9WPXdigZaBhhQtzEum7oBMoZVjUfvieu9VhImEoX1OV8e6d52Jl2g9WsVPOuezz2u55XBaqaQyeUJFaBXjvUFrDgfpXGOAPXV7sxhh1JYtvU+0yrUf7az7whX3//T76a9NONqijd86rer4lSYtnD7iYDdkS4UGOur4J5fHnbAXZmZ+dxYtM1Q4mLwf7+0AQH2QDeuNCA3VSGXehhV6AymX5HzYlNSCygkv5L9//8uXGoGq/f6j2M3Y88BsOU2LIwHjDSBPPw5a4VcsyqynjYBQy7Gp09HBdJbOBhR3/Xd43v3XsMxWEmlDIt5JsJ6rFQ8SKA3fYhXrjlWLB3nzjDbgywU2sSrz9Dj0cUOqFDk8afy7ep8or7J50EH1wvD5/aB9jNTxVgTeM/eK+RJJb3h2+T9PrxGHYdM+zsmyqNwZqNwHeX0Y3NG9Zxhl0giRXALs+w2xn7nG3nUmJjz7pc6ETnTssCffS66eSkAL1j2LVteoA+5MG3rJ0HAtp0SmzkYefYHmJiOArYBSe7SgrmMWG89xw0tvCTEo+yPA+7ALCbgnLT+y6EYeckseHpVXgyGN3wUySxAtjR6ZsAdjHDDkjLYvnk/b3PrFD26cbSK0lqXHuAXTnCcGKQhRl2q9JeHwaluXGtCmc6jrAx8Rh2ic8kBOgmMBre8RKGXZwS2+6RxEZSEJHElpKwyp/VzOQksfs9k5jBMQx2/DBwtqhLJ8+49bL9//peJInV07MXOqEBx0RKLDML5wIY+gy7mZLEYhiclG5iSqwAdhI6MSaJDU+cY4adNL7HCNgd4GEnkthtqzzs5nRNiLUWAnZqjSjDwCZ9yECvpyXAbh1JYnXoBAG3xm3euGYpEC4A7HiemU0cN1udEjulUS81YDdBEhuF5gRMr4mhE24d2f8S39ESDzufYTcXht0IAKJKA0mScqgOcjz2HFUYOrHVvxNJYhOAHYPOwx7ATluojCTxuffCc+s0DzvtmbwZYdjdXzden3y5iQG7y53997nx+zxmUaynMOyOoNjjdDrDzgF2i1GGnTpACu91YdhlJLF7GXbMzNjgZFb53qFUvC84nVfSO9aaYaeAbwvYOYZdIQw7J4n1POyMG4+OYZcC7GLGzqbp8BOfd3LsNy93Hng8WongibYbhCnEydLADWXYPfMh4Fv/I+CX/UsAfJZvFwJ2i9uyDq+wsSAUzY1rzEX51WxjSezDTeMksUOFz92Lf0dX2w/oBn+v5zPsQkWBm4sjcghV8pAsZNhVAWABB7RGB0x9LyFCDGK0Ss6ubVBCksCDdSOS3xlL/DMedp3nYVfIvD+IjRZ72NlrMLS7JMP1RhcHeCLnYTcuiQWUhQCTQzYP8CV33Z7rmdOfR8CuVodUCnvhIMPJkthretgV9LkLYLe7dISyXOjE7NTro73HLh1gBxhnY8a90du0xj5Wi1gyw46a9bIw2AwsC9kIY4M3etM87EJJLE1OYww7Mjvedb0AYUPoh5UD7LrG0UQjSawfOpELp+DKMuwSHnZRNHbHBuiKYTdBEptm2CVOToAkA8x52B1XEydljNLEh5LYKR529lqZwQcX2m5QDDtaIJiSHYROyEIYnvSnaqcmAyCdEqsWwhRo81la3N97d5VtLL3SG2zlz5M8YaNikKQmht2qsNf2Acm+ebPhGZeOedilJvWjlMSGkgH+/C6Vr+Q+wI5+IJLY0s1v7AuFNh06McnDzv3bpul9hl0TA3ahJFbPz3ox85h4ChRvAlNjZth1/YC262UszWaqyRh6J4Pcx7ATwI7H+gLzqnCMnimSWOPmcfcSmGF3JDIJQHnYTUuJRbtRoROtz7AzRhoS/rmwHtQaUWQBu0s5AOjpZ+uQyaKCGHgc1kmGXWIsEGA3ayh0ghl24vE5Pm52be82irof+OrfZP//0W/z/8AYdziDbr8kNhw3ZdDcTfQbdEztG47YhYlpDNhxMy7eu+Obew3YpaRKKYYd+wxfbhO+nFlJrFubKgHs9khi5UBt2lrE6+DexD21gZ7CsAsBkvWGD+bcdXpEbzdk2PFr4XtxGIZk6v2xlDsQmuph5+Y49pq7StjSeIc6Yc+WY9jR4+w1bGeGUrvGal6KFxUU6MNM09NF5a37IpWmXqODDU3Rklhm2G1TDDvyV5K3Rv1xm2TYxYDdZ+/ZxPuzeYUPPGc3+D/5hYfx36Yq3ODCMn58SazfR9+ouvUS8Av/SeArfwMAUAo2AVtFsKecnytJ7M6uXbQeXmEuB4pXV4ENCYCLTSvXpEWJz91fj7IYu0TohOdhFzKOJnjYJSWxoYddnQBgc6ET6h5iFlwoZ8/JoR+uW6VmC71IAw9x7WGnQicYsGsEsJvRw+0EMDdHEzpByqYh9LCbIokNAFoliX3uzM1nz5zMgY//78Af/Frghx8joX6Kh5226VH79YMlsQd72NnrZaiHdUmx69jSikuHToQHEAEDd1mXmJWFY9ndZEmseNiVxLArjJwqoFlnb9ZpoRMl/Xi/h12jGHaSEhuehkSMOweuyGlZMBjWTTp0os8Adg4trr3Gf8zDTt4XJxZWs4kMu4Bp07mbhvf+0XVOpWLxZHesDDsgvlEzn8/Y35rAwy6VqhYx7PikiZuj8KQ/VSHDjpkyCtwqCjPKPnrlgW2GXjxfZBtLr1SSqWbY6fsxbBYEsJvbCWtZ2O95guXT+4U+aY487LQkNgXYHaEkNpQMMMi4uxLgKudF5a53yLAr3N/QwjJHm2bYNfFmNqxZWUi/vm07+SzndeEWo1vvsf9fv+XSX/llqbFQJgC7tvclseGGSrP/Nq0D7DgJj997nWoYE8V/X/auWZlrhl3fqBefufeFYeeeyzDDLpR83uRqpgJ2CYbdrlP+cTPv/8x6E6kKy0wG48AOLr5PVUosJ8RHDLtKM+xonCRCJ7i59MYCBfPMWgqdKMPQiX0Mu8737OP6dX8Q+HV/APjW/zD+I2a6mE4CrKJqM3NuuFmd6DeY3QDdtMqkxIrcZdjftwBOKr+sS1QmbsBd6ISSxM4ZhPKlgNbDLjgoS6w1FUtiMQBj8j4O5Qm9DhNl7Qb2H6AA8DbQnp+Prld/Evjz/zzw039ZALv3P2eZ8Gxkr9/TQ2LY1cZ/HJbErpUf7zAgnRJ7BCX7iOtIYvlajDHs9N/Ik44z7PamxEq6pmXYcdqj9A0ALgh8PplVMoYrxJJYtvyxoRMsiaWUWBpDl9s2+/myJLZtEkB6Gx8+fP6+7XHefXuJL3uXZef81BceRX86+r61JNbzsJvfbIZdovgAln1a7Q/P7Gchktgtun5AvyXAbnCA3WadYti1subuUGHT9HjrMm8lYFNifWJJVRiVuJ7zsGuylgujktgodEIx7HJSQjXvM4ARsvscqy8hiWUG4RD2cgTQcRo5PXZpOttziocdedaJn4u9JoOWxNbHwrCz+MUc9p61NjSdwyjGALuQYacAu696+RbefWuBr3zp3M5hf+I7gLc+AfzQH7j+a53iYceHeo1i2A0udOLsUIbdZA87Auzoc98IPnWZDp3oe7dHnp/FPV1gt2UoeEIwm5stibUvriXAriiMuyDtJrqxy3LkZCXjYcfgWHKDShexNfaiNl3vAI6QYReyBHToxMwPHhDATqfEqtAJYdgZ/zWxHvt86SjuJTrPs0VeOtP8Aw+7opqhndD4Og+70H+vjphg7j3HDDBh2B2Zr4lXEWC3nzYsRUClUZLYYRjIw86XkITeG5GHXWrC0NU1saF1gmEHuMU0tWl85aF9jBfOF4hCEFKln8MD7Nz41Yt20/VuEzkjL4XCjhke42uRWap74LElsUfIsJu5aztVEhvKDpuhcpv10jGeruthZ4xRPnK9/zfMjrnNgN296KTVY9iptcwLs9EpsYG8X29et00nLBSRxAJA1xzMsBPArppjVioPO8AB1zLOJnjYsXnzMUli+f6dzLBby1xysWljiSg1FgzIh2lkDaq4MdeMXRpPXWXv5YgVmpLEyiZDSVCTKbG3ATjAjn9H5sZJHnYJ+Wo1Az72O4CzF+M/ko1zG/nsSHXpzbxmE9oXOC10gteTSJpx0yqTEisA1EQPO56PzpdVEmRIhk7QYalj2CU87MYksR6baoRlt7lPT3hn9D0Adt7i22V+AMMuTPGW+oHvBf6vPwn8N9+FNy/tGHr+bI5nT2dJdhwz7CLAjh5/1/boegcqun7muHq9MLxu/x8oSWzuWgM+Czvstfd42E2XxF5hVRdYgvu0BMNu7gC7WUISyyQILYk1DNh1Pfp+sAy7ICSNiw/ju4kMu8+Tn9q7by8UYHcow87NAa1OiVWWPTcyJTZR4plaqHmc08ZFEkt7UZLTXWEhKfbtNvanu9i2ck0GGodfeBB73XH1/RClxJYewy4E7NxeRA5UA8A78jrvO9c/8ZqlgGeuyCNNXqTb97RhSixjABmw9mrXKY8+ek+DP1/JuKHrUKOzj8c+7GFKLIdOdI1i2B0JYMcMO0mJ7ZENu1I1DEMidIIlsQ+xqEv87//Pfwj//T/3D/Jf2P9dvHL91zrJw06HTrhx7FSJUz3sRnxYU7Y3dM2KMpDEJghl9udXkGsyO00w7Hgec+/11rKKGXY3URIbAnZVIIkNAbvDUmJJj945vX5UAcOuUZJYfZJlX0ROEutSYp0fAHkwZUInhswAZfbR2cJ52FXoY5kQNM3f97Arq0ASG54GE0PLk7mpv0dRRZ5U7ho4GTCX87A7ok1rWOGNKuyfKSmxzLBzzcO2teElexl2oax5nySW2XWAksTGoROASt7r4rHzKgF2L95a5P2UvAdzPmua7qs9LfRGWY/X2YJOejh0glikmiUhNSaJTUkVQ8+6Y5DERpIBx15kED7pt4lAUgrIBrNF6dgkpfOySXvYTWN0SPBE0yEZOsGS2Ku3wC+XT5x0WmyhTp8KPa8oSSw3cPz+jDEyfjdtL+yG+UzNwUPnWFX7POzo7wvZXMwxr0vHsAPcgtq5gwuvEos5g/TlMaXE8hyiwxJSpRl2DNhpD7uAYbcwzMbxGXZWrh0CdirqnsbTQAy7KPmSQa12i4bGYYUYvHeS2NjDbt5dwqCX8TWrpnvYRaET+4rTAccksXsZdhs7znjTvwdcPR6GHfUImZTYTc8HjRMBu0U9CtjpOe5k7g5R9e9YD7sg7VP5+XLVmiU6Jotd37P/J7B4/H24x9nPsHO9QZZhd//T8uXVhQVIbi1rvHC+SDJpHmzpfsoAdoCd/3dy3x0fw05vQK+TEhv6qXqlPDwjwC5zEDrdw476uqHDrfmABQIgBPYABSD2KIcc6LApsfyh/rN0Y92oHnPX9bjcaYad/9rEjD9M8AYQmrIDDrB71+0lvpwAu59+dSLDrlRzIFXbD8nQiWNj2G0qteYya4n6PwZkm00siW13MWD3aOOSS9ly4pURwM5n2CU87CJ7BreHDPszrjrsv7RChse9OvjjyjLsPMDO97BjEkmdIe2sd61nP+U9nnjYFd5jl+jtewhYVwIE070ydEeYEsuJxORR3g1D8PmkDwH1PVUnPOwAe8hVlwWiNHdmlx9aEwA7xk62be+whr6/RkosjY2UIjC0xgKcJLYOJLG7K2fZpscx749NYedqGf8BIUC919urmQDU7jDzJkpiGbCjZr00BhveRDUJhl1OEjsMsTaZ6ayjHnbk8VCQJJY8kwDEp9phc60aqKosMCsLlaLFHnZ9kmGXO8kShp3ysOMFOJQcuiYk8LDTkljAH3yf+mHge98L/Jnfhi3JbF3ohBtI2QUxEYpw9KETgNqMB5LYKTdNwQw7d022TU+eL/4JTxgaEDWSRQyIesWbbW1onQidALTsK25qXntkx/3zZ/OY8ZUqSXXUkthTb6LSUjQ+jS4MUMlJj70+IcPOA+yEPUgLhFrkk2EAkST2CAC7EYYde2olE62RYtgxYFc4UIQ9xUzOw24/ww6AZ2zO4Kr1sAsAu77BqqCmgLEaNW/oMeJZGihQvO3j973gTWnTudAJ7WHXd9IIT2XYmYBh16LEwBuuNtisZ1Ni1TXtjxGwI6bD/Hz893RKLH0WDzdNzLCjeWhBHpVdAkz2JAOAYo+4EJue7oPIl4tfR7fFVhh2sSRWNg96zSJQ0mDAGdYqdGKaJHbX9oebTSvAPCuJzfnIlIpdog8r9jDs+pCpfVMrmxLLgB17Su4D7OwYOV/WsuEc9njYsQriUkInOvc72ZRY7WHnzz3ZYsBuAsNOA257ATvVG3iJebp2rgfoHlrGw9mixvNncwfGqOt0f0NAbwDY6deyVgc2x8iw09PBdRh2yzGGnTH5Q9bMQehaJLF7QE/V29yuds5LUwN24mFXy1xSmR67hqXd9jXsBpbE6ter+tXW+mSHihAuMeNP3ZcJtvDnCTh66fYS77lr5/XP3hv3WJNKeNg1nfISLWcuFO9YADu2lKhuux+ePm//z2mehnqoje3x14MLneh2MRBnGXbE+qJr/4UH+aRY38OOgL4xDzuVSp3z6or6Ua2QiTzstCdh5oCJ9j3tUMh9m2XYBT2fbz+V9rBzDDvtYVcohp19z9I2e6ETB4RP3YRKhU7wZ2DKWEFCpbEVUe/xvop7f66LV/3v1YHRQXUAww6A9zmzJHZy6MQkD7sEw64KJbFXsUIO8AMnjFEM07W8ZvuAbh2+tawd+zU4zHzS9ViAXd3bN9EpSax42LU6Ntc+TZZhpy9wkBLb92MpsURDJsCuaR3DzoRNcpiqF8gXl7MyWvD8SaSXTXDupNJn2JGM0nSS1ui99C6gFdP7rGqF1gI++PO5H7Mbzp/8C3i+/ax9WxI64SZu3vxHC2LSw44AuyM6dY0qvFEPkcQyYNc7BsemteyK0F+nCjaVXXhyJTfxkN4USFy0YpbViv2mSjalCdDm/pUdE3dOZsqDZGSC8Bh2ThKrARa9gG52zkjbBKb0D4OU2HmKYcebnX0MuxBkPCZJLDcyim0k93SOYRcyX+meb1EplqYKnRjxsBtLiQXUJrp1Hpon88p9/ifPyXPdHh56ryuXEltowE4z7MLEa7hxsW17Zczub5r5OmWlh1T27wcUnWM92CbaCLvaUdYzCdESJa8ZdnQYdCwedsMAbAiw28ewU402r52PNq3ysEtLYnn97Gle8QJR5LHVIQM1gUNt790IhNAedm1vmXIJVoCcnuv5rprLSfK5uYpCJ8aA3q63zBwniR050NDFG2d015fEthv/AGbPcx8Nw05CJxiwY0ks+YRNZdg1zLCrUCFu9psEYHdCAAkznDzWsEhiGbCL+zPvHh9Lil3ft/+fANht1EGICUHtsBTQstB+ProuX3NfP7KA3fmixvPnC3WddOgEzbvwH6cojDzHeucAuzrhF3jTSx8kXisldl8ir/TEGYbddSWxZS2f1XPFhfu52pc4Say/Ae8YsKPXsAMDFnqs7zyfWp9h9+QksS/fsa/3Yus216OVSYnVDKdsKN4NLe7FH5XK1/KU7BSotz4hj0LxsMNcrkWfZNi5z6uqGbDbx7Dz93pVYfL3tAKi3fqS87ALGHaFU4gJk6tJMeyCvkA8mctojxR52AVr69XOV7Ppx3MedvS3GrArTAQYCcOOAbuuwUwOPI4ldMJe99lAQHCnGHYj/YRWBUg/MUvvMfEoAOyu3rzeax2TqVJpgoEmQT08WBJ7qIedvX4ledhdiST2SqUda4YdkWoY5NzjYQcQYCcpsevo359kPR5gF0hiywJphh3bM2UMJ70LzG+U/OE4JTbJWqGLIx52/eAGbChDCdk8ARtqNSsjP4B1kBJbUhhAGUhnuXwPO8ewA+KGIdKZdyyJnTlJLOA3v9xMAlg0RG+VhFu3ILJ0LZ8SqySxYth5PKeuUYU36iGSWEWjZVbQpumClFj2sPPp3DzU5Ib3fHISzU0YOAH4bBVVvFlJybIekCz19rJ2sqvJHnZOElsWRpo+vTn12HP0uNxwsSQ2nRJLC8rqbvyeUqcwEXPniEInhGHHktgrxzTLpNnxiZcD7ByLySUNk8wMTTJFcLok1jELRMZTDW4+qVeyKT2HHRP9vpRYBhwHH7DrEp4mWpLLG9vlvPLuNwfS5Bv3YRiwbjon5QTAoRMA0JpADpcLnDFBMwig4Ma3ntgsvNPVrN3cdg2GnSeJZbCJNqSLwMOON3ctqrwkVnti1sywCwE7Bxxa83E1pjVgJyE7wVgg6dE5Ll3oxMjcyCX3iTAKJzbqU1Ji90liu50AdkO9wmYPgzQ6+LmpJWABv3/fw04Au5SVhyo+hLIMO/s56ZR658/r5jgGSDjtc62liUUI2CVCJ+oDJbHsUTVSkS3JWHkpsQmGXbt1zw2gvLKbqbNFhefP5soDzL6PXds7wC7xfjSzbEdAuXstRwTYqXsnBBzyf+QObPU6lKycKiIDyl9NTYkFZKP8jFFyUiVlu+CDtFnlAQnChOsYsNMMO/Kw6xrMaM7cCcMuA9iJvVDwHjMm9gwcvevWEou6xLOn9t8+cy8OT4gqxbCLJLH09o4FsGOGenHb/fDsBfv/2gfsmjV72M1h6NCsD72dQX6ydHhWEZgwBth1fe98stjKw2PYhQeUKnQiTA2lithuchityC76EIpqX0psg1LIIuHvVgIShpLYzrGUeEwGbCoB+xRgV5eFzPeRh12hAbtY+n2jixl2BNh5DLuRvZ6eLwUzyfikY/2W/z0fBh9aExh2dWnED1t7MXqYyaTnmsKw05JYChspZzDGMl8B5Bl2EjjBgN0UDztlY3aTU2KFYVcxYFcoD7u1uiAkJc1JYlOAnSS8sF4/BdjZi7sjwLBVZvlFyLALwYCAWr6clc4PwLhmJzzVmFcxE4+LwYyzeS0fKD9meJoaGelKSmydl8SyITKARWffuzS1CvnNpvEmJbH70fEbX1HoRMZ4Pvm3bhHUp7FN1ytPw5yHXQBU6PGQksUy3VYzybKhE64Z09V2vUxyt1ezSZN4OiX21Hvteqxwc7uoS8f4onhxkcSmGld+D+zvkUgjHp3Ipjbk71R1rRtjVcCway5lg59j2EXXWskOXUosMxrTDLvdREnsXI1lBuxOSzUH1UtgaYHV8+HCe105iZ6QeTOSWP2+9aZUxlNVevdq5KGSKNm8Q91P1UKaaAHsxGMi0zzIfe6ey/AJ97FIYlkOC7NfPq42Tty4PdKSWGHY2ffOklgew7xpbIcybsx5PtleyHxi6GcRa4gb5HaDpuvdxk3/GxKn/Vw0l9wyl/I6nJQ6P24k6ATB/bqvRBI7khKbY9ipgA0+rNhgho9+z/+CH/rZN7JPmfUEumkVsTgIsGM2V6fmpBGWHTPsTuaVBCZohn8qJZYBu01jgxQ2+lApksTGp+D1oZLYCR523jq5r5Sn1DzFsLvyN08lbaYsYLeIbFjur3ciDSsQv5+VYiRu2871MsBR9Xp6Y384w66W8KUsYMdzUCiJzYDyk1NiAdlz3CHArjW11+M4D7vKA1x6fm76/xZ8YGzUmB6woi+3LXvYZSTP9H0fMuwSJvbDMAjD7qXbS+//n7ufl2xKKQsELi90opodH8OOeo37UIdkzLATwI4+qysniS1nDNjF1+1q18laOJsxYJe/vm2X8rAroj2KlEqlTikg+O8B9TnIYbQa87yP1imxYWCi/IPrZ3nv3wUedrm96dXOV7PZ/7NfGf0t9wjKw64qjQNlDDPs6LEV8zqyArnpRde9JhuYfhgcAWKkl9H3lHzcev+ni8kbXNu3D7AzxghLvukZ87gOw27Ewy4ZOuH2x6UxLnRid5Xuu7Qklv4OwKiHnZXEBgy7GymJ7chDzvOwcybTzuPL/igLJGlQij8IBux6ZtglFmsagE1pn1+nxBazYFDnGHb0+D7Dzi3yoRHmoi6y1HMGM86Uh92i6Omx0gy70MPOlDPMyhJNKilWMexmnR1YzsNOhU7krnMoHQFkAD5doROxR1L+b52cdhGcSofjIbyusYed3hSkALuE/9Te0Al/3DzcuHvlfFHl2R66MimxAJIsJy8BlhaHkgA7nmAfif+KGjf8WphBqBvCHPPpmMozfQ087PpWGu2ch12hGWqAk8QOOnSCGXa50IlprA5miz5YNzJeV4Uak+XcMewG22SGDLvQu8xjmCYksfpQRTMbhLE5K9znP3QuaGCkcWcmTciwk/vDuPXGvokMMGzixbzgk+qbzrDbXVr/0p/8C/b7xfl+cDvlYbdOMez80AkBbZUkNtooS+rYAwfYzQmwG2HY7brerZ3quQEF2GUZdlcCCOcOM3QJmKK8kyYVzeG1aWPwkCvnYaebOzq8eHNnx/t/+QMfzz7lwSmY71SF9xStXQzObwY1JscAu9YB+MvSXuNeNeBeoAQVh04AluW0ThwqYejt/Z2QzdT6gGNMEvvoC/b/qQTh6H1Msyewr8V5SmkDbqlgM2VoM3W+rPHC+dwB3fQ4D64aYSqYBAApkljysPNks0e0BusedtL9of2w96XEAp7EVKrv3ToSbPD5M5sE0lJvcIssJ3bGfywvJbZwfqw89wpgJx52hTfnnFT22mzpUC7PsKvpcccAO/u4j7Yupfa5M/t6X75j38fn7k0B7AKLCtg5XYcdZfeBN7R4bfpcoeaEZz9o/0+fMXvYNRt7327NAiY0rFe1bjpZC2fz/Qy7fhjQDf5eryy0PVMI0jrmaBSOJ+8r42GnAw2SKbE5hp0C7DIMO+4lwsM2XxI77mHX0nWoDEtiaQ9bsofd4P2dDZ2IPUBvdNF159CJqQw7bSchNg05hl0I4L2NDDvAHXI09PkNfedITlMBO2FdJtbcEYYdyhmKwmAtHnbrdN8ltlU5hl3Ow+4IJLEzYdgRYFdoU7+10GIrYdjRhi+US/SJZoI97LoRSawAdnaCabpBGn4TetZFHnY+eLWsEx52u05Nkpphl14Y2SvqVAF2cwbsAnlblCipTPmr0rgBoBfVMYadmtz2h06ohXvMxPFYKmLY0TU7RBI7dJhT+iAna+5n2AWAnV4MxjzsNDsmy7AjQCLYlN6/su/tbFGR4eohDLsEYFfGC6gDWEppwEoaMwxK8+nwqdpIyWuR0IkJDLvv+hN2UvwN35d//TelUoCdYu6WNFnnUmIjD89U6AQDdqbJhE6wd+A0Sexbl65ZXBYKyC4KkS6zJLYLxnW4JnpSFi8ldhrDbu4x7KalxPK8eVKqhbIo5PEbtmDo9jDsWBLredjZr+ub7mH35seBP/qrgf/5X7Hfz2+N/z7ggUc8Fqy0OGDYBaETDFI5SWwZs9v5/r54FQCNlfk+D7uNDYEQ4NV4mwweC9GYZ8DOXIrUXObGUYZd572vQxl2VQYwt+/Fl4RKiSRWMexIcTC2ORVVwD4ftHe6wvWUrikfHly1mmGXCV6CYs1WBRYlAcTqwDAVOmF94uzX613np3WGzHbphdzr9e5xtTZHRvoPPmv/f/5S9vXL+2A/0T1sZwAeC3CurDek2DuHqmDAjhh2VSCJvXfVRIwbXbw5WtPhY3WkgB3PR4Xx7Rmy5al1SnVwlPOwc0CqVALIAuxYSSUYZ4t6u1t9GrDz5GDGyHgVYI1ex3ag/lOHTgA4IbB71/W43LZ5thWnZ0ayX/W9AoIBC/jyuvHSnWsw7LzQic4LnTjWlNhP4934bbvfjX/j5HuAD/xK+4/0GXNKbLtxJJIh4efHpW0+Fgv7e194sMkGe6Q87MqiyO5FtZqqyQBskUVVimGXeA/ZkKTe9Qz8O2FCbY5M4qnZwpTYUQ+7Iur5ZFypOVdCJ6amxb/TxQy7a3rYaTuJrIdd+P21GXbTVHp86MYMu6ZtxC97uiR2BBxM+FTrXq00BlcDA9CX6b6Lbat4jx6GrmQ87EQVycEeN04S23cik+sJsCuMkShrtBt3QVi/vpdhZ9wukS6+SGJHGHatYthxsxdJYkMJUemDPMtZFaVorRulqxfAroiks1xXW24iHWA3K+x7DU/4InaWMuWvy8INAN2AKIbdarDvPcWwkxSmcPJPMew6f1I8ygrjnK8jiQWwYsCu7bFt4xPLKCWWmUU8ORrjXktSEpvysEunxOZkX/fpROIWx2BPkcQq2WZoqpm6J7dawkgLXEnUbD4R4YSzs0WwWVKPrWURydAJAPjyXw/8q58DfsF35l//TSleMBnwAizgQeOjIE/PnNdOyZH2zCISCcEBoRMJf6dU8UblrUvXgJcC7tIiRD5NZ7ShiCSxAYDgMQS1JDYM0AG8Tan4Hc5Kd936Ns+qUsUMu7OargVLhplhp9Yb++L2SGKFhdujILCpnupv9k7V6Qv+9/sCJwCv0WbZeoHeJUryfCEAsb0u/FmIJBYVon0yS94Z3DAFCmHYBQcVIpHa+ZLYAOyqE0xf/Vw+w266JHZxqBRGSWKzG8pMgqTHsKNmmE90P/F6cJqtqk8A3jeywvWUfXb4Xu/g1r8Eq4RL+3A6hl0sidWgiJbUXO6UL+as9MdS3ySb+nldCDODG/of+eRb+Np/6/vxn/7Vn6G/7R3D7tZ+wI4PExYHMewcYDfGsKta+/3JvMLz53Pl9Wcf597Vzh3qpgA7ZpaRJLY8Ug+7HDso/wc+CCXWEAk/WP4d+3daDaDGrrrH9ec1jWFn58TT3vpNCxucKpSDMUNoaHcWuKF7aEMMu6oovP5pKQw7C2CXuQCCwF7IvU91sE3XlwPNbi/da2VJ7GcP8rBTAI/+TMpa5rluT9jUTSn2TL3ctfjB/qvxt5e/2PkvB4BdR5K6rlpi4GsReNh1/eCB6Iu5nUd3bY+3LtPM5K4f1P1OVh6FSaZH2++dBF88UoP1hddR6f1bAmRrBQjVMWCXT4mNGXb8/zpYu8O19WrXqgOItIcdE36YoVWCDn2Dns9JYl3I4vFKYq/HsPNIA0wqaK58b9lQEvs2M+zY1mLb0+dI4TpVYaZ5ggJ7JLEBcWcYfElsYUYJZQAiyyjXR3NKbNrDToJCb6wkVjUY7GFXlQZb9rBrNuqC2MFTCKIfNMIpllcoiU0t2PQamOHXdL3zP1lMDJ1gSWxdRrKDTdNHkthZVURSScCevkka46yUf5tlJLE5DzuUNerSOBPDDMPuFHbxnJel//dFpa5zsCAmJbEUOnFETVxUSmYHIElbzf+tAuzo1x3DLqRk+5vKJKW2cAtlVCkPOz79yEliA9CGT0BvrwLAbuzkiDf4Qw88/Dz9zG6EK9n8ag87JfWhxcEMFsDkJvNCyzm4RBLLgF2cRpwEhqcAqzehmswJFy2IVWvvyb0psaEkFqVbYCsniY3YStApseMLHHsYvXFhP5OTWRWf0JEk9ow87EJJbMho8E5HEww7feLKGxoGeOVnat6dctLObM/zij1wCLArQ8COxto+SWxoaAygvumS2JNnHUMQsAm/+0oxHRhQ8HwAuaHg0Ak6gebPYlAMuygBkxl2fK0XtzGna7gNmSxqA9d0PWqTBuxcAneOYXclc5UE8uQ85uA26MLsmNqoF8ywu07ohLI3oAOYK9jP4a3L3Sh7AlD2GDe1wvW0ZoadknimkuiD0knXo5LY4FCCG/6H60bWK8/DDiCGXbyBmJVlxFD5x//wD+P+VYP/4H/9afvzqzfodRvg7F3Z1x+9j0kMOzfvTZHEzkhBsZpVeOZkJmmQF/TW3rjYqvcTA3aaVbttAoadueHjTFXOfytbvQ8O7ZfEJjzs2jTDTs9thzDsTtr79jXAny84dfWcD19pHJdo7ZwgoRN27NQlERro81spht2VlxIbyiP3SGLVe7y/tj+T/hLAuwmwe2VEsimVYNiZzl93orCDG16SEkuMSO9+p894QYDdQAc1fbWCoTVnCOZCHou83yyrGZ49HZfFWg+7UBJrsvZMWoLP1zncQzt5KgN2wYGu/lqnxObuSVaMDEoSG3jY5T77K61mC/dxtDbUUehET6ETPuvJhU7wHrpVKbE3vNfjYkyFGXZ9P4lhJ4ngKYYdBn+fGUpitw+u91oPBOx2zLAjwO58We9PWZ/yXDlrLAA2jFOlxKqQQO+2iCSx+z3sbq+OQRJbzvBn3vUv4/c23y1a/cLzsFtHlMMs8yv1IUxh2KkkNsAOVj69rZdn/u+GqbGBJHY1K5Wx70joRF1GBsD83DxPrJSJrAPs/IahCdlZnQOZ6rJQkli12CkK6xnW9HqCpq3UDDv/LSclsRNvthtdcqOGDLsJKLfaKLCJ70Z8X/zPOaRzN6l0vyDMxCvxsNMMu7QkNs+wo4ZqGWyMxlhC9cq9z3ufsv8nsKZOMOy8YAN1DWdocO+qwTAMThLrMezotfDpRJsA7I5lwUxVbsGkBbHqWBKbnlYjNqOSxDpZNYdONBmGnWOnjBUDqa8+tK95OSsTgJ2VxJ4Kw45e1pA+Qa0ygJ0A1+p9M0h070oBdpXysOs75aGyX9p4WtHv0PUR4/aQYZcD6wt/Htf3Zz274WOyKH2QLmTcpUpO99dyeukHd/ihE9zQityf7uUudZIZMvyWd9znkZXE2pTYUNrHVZfB5kGeixl2h4ZO0H1ycOgEbY7RoumGNMjWZUBh7UcaSGJ3XZ8E4IG8Z+SNq/D9Vuxhpz57Aez2S2LnVYkFtzmKYdckJLGAa/g1C8UeApQAlFIhcTg0rwt1+GqDK3R/tN51wCt/135z50snrVPbx2TY+ZJYn+0w720/sJqVqMpCwJkHtG949eE2YtzoWirAbtcFvcxNH2eqDvZ31CyyolZpuTlJrPP6co+hJO/qWvHnXZiJr4f9zZr7AID14I+pkGFnhF1v+0/un/hQStZXGktL5WF3ue2ifpXL0Hvsw540MY8xw04UHICkxL5xkQfhpVK+bR5gNz86Dzu+X9lz0JuX6DNeDLb/MNTH9/UKBR92B4f3Atipw6t33XKy2FT5DDsOnTD5oBElB00dqALKw47X0VSoQeLzzD2ePoAOGXaSEpv57Ne7Dh3P4UoFod8bMwSZYVehtY8X7PeYKORJYkMrkJtedBhWEcOuGzCRYceMRjVGNfah95kM2LFi4m1n2Nl/F8CuTai09tWQGe/6+fn16DmotAw7nRKblHaHktipHnYMNvM1vXGS2HqBv37r2/Bfdb9GpF4e5bDdRhu/LKMiCdg5w0gg52Fnm5yBGC4cFgAA9eq2/7shwy6QxC5mZUQvXidCJ+ZVkVwY2VMFoGaJJbEmDdh1IdgjzBDrYScMuz7RSAA4M3ZyTXnYMUAabYSlOVEL90T9+Y0uBQIAgE4Jm/y38Bl2u7ZHZfxr46j8vKn16d7e44XyA0B52KUksT7DLudhxwy7W6sAqBjbkBrjJmUeTySHlEVQjZWt9kFQiwMHIVzuujTDjq97MnQiI4k9pkqdQAKyIJbtOGBXhM1Kxw1OFYdOmA67hIxnaugEL4IM2FmGXbDgE2h72ttFqhPfkXRD5r1+JYltEpLYZW2fnzfXdWnshkMtqhI6MXLSzhutM064JWB6Lgy7gIks4yyYz4Rhx6iku7ZHkRJ7+nz661wx26tvwPYgDF4NMO5zqJhhZ/+N1yXHsEs0U/MEYJcCIQCv4dlqD7uQYSfs5WDNonnq3FzJ+OL5djsC2An7CZmAiFxx6EQAYHqV8w3Vhy8NS2Ld7zxYp0Gs7AboplXYkDPDTqee0v35Ix9/Bf/Kn/3buNrF66CWvC4KknrC3a9JlgBi1rAxah7UzL7ArBywCgrtkRQa6H/89Qvg83/TfvPSxzIXwK/re9jtZ9jNyR+aZcBL8vq7v7X/f+3hJjKh1yUedruAYZcC4G9wtRk5X7YCex0dfpSsFMCcYdCKzL5OsI5TRZu+1fY1AMDD3rfpYfa5+Dcp/8xt0zmGHXvYBV7JDOKuKdgpx7YyOUlswouT5yjNsOPwidcfbbMsYanS7f+kaG0eyLc0Ct+64cXrzUUKsKM533JsOhQMiNQrFNxXBAw7Ccwp+BBSA3Zpn8C27yOGXVEYJYMODyjdAYEnS331J4Ef+SNA38X78VR/KymximGXk6nT62pUSmwTrG05Dzs/dCLtYVeLJJa+R2d7ymC+dww7dw2isK2bXsyw42DPiQw77sW9/UFRur/R6wz7rZ1QPxmGUkytyR52PsOubex9MTkhFhhXauW87AFh9ko/1lyl+67QZz5k2CX2F1oSO9xYSSwI9YVj0JXGiN8CmrXQXvd72CU+cGbY9QlNNhcPPvLPudx2cmoaScZC8CYhiQ0XvCTDriqS1HM+fVnWpRe/zoBdeLoe+QCEHnaplFi1CM6xQ10aJ1tTZoghsOSuQUKu8lQw7IIb9ZD3pD5D7puY+p5j2PFnl7zhRyWx7GGXCJ1oN+5ECTol1v8M2cPutnjYTdyQMmDHJQy72DvKS+krKpFg3CIfsTcvthkPuxHALidVPKZKeXwAjmFHm6ycJDZm2Nl5pEHp5gHVULS72AdKs1PGipmPLGNZzRMMuxUz7Aiwo8VeJLFhSqxRDOkUw041cCEbZsGv17j51F0PBtF64E//FuC//a1yL7CH3YlIYgPfrCEArgMm5+W2xe/5c38HP/SJe/K83u8BmM2OoInTrLpDGHYAVgR28ilzVyjmCDPsCLBrAg+7LpUeXi/9uXV5Jw1CAGoDN+5hJ+E34ZqlGHYM4LCn0GhYSeO/5+kMO/u6+LAmyeLLhU5ovx9q3CSVDL48XNfxeNjlGHaxJPb3/vm/hT/zY5/F//h3vhA9DDOVZmWBOXn8tloSm2HYccP/Js0pKw2cKEAsZQy9mldqQ9jjE2/4jLa3LnfAx/8P+817flH6/WfexyR5pEptdGxUzbCjXpau6WqwmycG3jic4/7G/v/Vh5tpHnYNedjl/M1ueGX9snIV9BlJ+bGupIddWrVw0OcNyMHG7OoVAMC93s3JbWcPPgHNsGO2M9lhtCyJZQ87ugYFg7j2PXFPmGfYkTdeKFNPSGIfhB7JgMg1d12Ph5vEQbSuREgB+x8zYzG7P7mhNROGnZu3pBR7aYktqo5Aj9kKZU0Mu4BtLP6bhWObs+w4F+zR6dCJwR2QZiWxipDiBT/8qX8M+J/+ZeD/+F53SMb9V6q/TfjwZQ+YCBDuUMqa1gX795z1hfWLz9iWBPsvAbDhp8Tye5Z+UqmdclYcN7aEYWeve+uFToww7DKHXUklF685rN5o0mNvb01NiaVD/E3Hklj7d3qu2f9cIwdPkZc9zTumAEpLZOJ+bGiuxM7PUzaIbRXtYSOGXSytPlehE/2NlcTCNZoaPXcMu43cOJGHXcj8GmHYCf03HIDtTv7NEMPukVpMwmYvqoQk1k1+xLDbxck1Cy9N1g0aL7VM/VudkcRG3hyq0ZiVhWM2eICdmzTnaPxNu7qGuVOMlCTWDHQNj6yR8ypC1g8Ah7Qklr7kpiX2sPOvayvjW421MUlskNAKIEtXzhmr3w897KakxAIxYCcedvE9KRuqqrAbezppfm5pf/fNy51KiVXXmMFDkcTqU9anABjOLZg0/9Qsic2FToTzH92H3VC6+U01FF3CuJ0DQfalxHJMOjfYt5Z1gmFHgF1nvSve+8pfBv6DD+PsZ/6C93rD159NiVW/v5oHgJ3Mi4phF8ogP/XXgL/3l4Cf+ovAvU8CcKfRJ8ywYwYiy/CoeXMeEz5l/X/6u1/An/7Rz+DHPkN0f/FHcfPx7KZ72AHAcx91X5+9uP/3FUB1QkmpDMr1hWpaWWIMZtj5HnZJSawxMnYAAKu7ShaZZ9g12hc0mJtdAMmYh53xfneUmcnWGALYTWzUlSQWyPjksVy4CAG7BMNucHPF8TPsch526rNXoAMAfPbeGvjc3wB+/1cCf/fPAnCf26wqhGXSKYadd2CkaklsszeJYcdgln1titmeOBw6mZXoWXI1dHjtoT+3Prr/BvDpv26/+fCvHrsKUppxtbdUX8B9myfT5I0C3dsnZHnC/SRfp3sC2G39lNiAreR52CUS74+lJNjr0NAJGquLygGXyUr1axmG3dTDMimyDig39rDoUb+QAyi9V5FDTz4sEEms72HnbDNIEkuA3T1msWdAWZbExqETKUkse9i5uW1Rlzib++zWbIWMFPU8HKpR5gKGbmjxevOIJMzevFTN5RByia30gMX8FAWtOaEkdr2zn5sD7GZ4mZN476VBkzYhiR33sFOAnb6H7n/a/vxH/pD0a6MMO2bqq71nuK+X8iSx9GeRh11BjxFLYvvQkzMAZ8Q2g65DbaiHDMZx6GFnuiOUxNJnwEFxnRc6MeJhx6ETVfDZ8J5zlwLsnrX/vzbDbtreLmLYtfHhwN5K5R1whR52wYFEWRhccT+mroMfOhF62IWAXXwYuKhLF5p1YyWxUEwMBdiJp1CzFlosLzTirRYedk0A7OpwclCeH4YGI3tCAPtTFMOFejmrIuacFzrRO6pp6iSLAyd4o+rS5giwC074HE059LALJLE86PrOayrmaPyFQwN2woSBT2EflcQeVyPnVeRhd4AMqijA/jfcNz2QE8v0CQ8DLsnTX2X2GlWYQAP4k69aFLOhE8KwC6QH+xgkGrCbncr4TDVPUUofNR4v0H70zYudvI40w47eX9+4jcTTwLCT0IkwgZpkEXsYdmU4/1Gj0ejQCdVQ9EG6GODYJ3slsXP/fraAXcCwI6bWefcWSnT4FX/3dwMXr+Jd/+e/BWCIGXa6wfNSYmmeV+97RadpzIYRnycVEFOVwdj75A+6J/vC3wbgNlorkcT6KbGbELAL2DU/+7pdJ3qRj/mnt/1gsJofwZh8+Re6r9//y/f/fllJo7tiwA7+xsn+HvkmBYwyZmN0KUksAJy/23092cOuF9AwBH+072qvm/lre9hR4zowW2Yiw06FTgC+VQDXQGPtj/3I530gQNsb0Fy/0Qy7TRqwOxoPu9nK/z7wsNu1vcxfLCn+/P018Kd+M/DgM8Cf+yft70mSXYE5gQ5tCrALergTAq/evOA5RQEnWj2QOBxazvzQidcD4KF65W9a5sqd9wF3vmTflQBwKMNOedglGXYBYGfIe5Te45w292+u7bV57dEGrW7fB3+cOkms9U4scl5XN7y6EMzuYnDSK+XlDLh1Z70PsDuAYTfJsxCIDkkfDUvcI0CM54KTWRl509WmtXMbvY4tZqhL49ik7GFH7FQ+FDvh4R58xsKwC70OE2nXKQ87wJfFjlaCYWd4DqYDjmPzsONeIymJNUYObJdmhxl52RWzEwHsyhCw40NXJYl9aQrDbvD3OVVROCA+DG5T8w3vUzjIxv57FfdfKQ+7kZTYXOiElsTmPOyilNimjdRs4d6U9yrb3klidehEweEqYUpsrySxx7L/oF6i9FJiH4dhx73JO8ewY0uLDX2sLXnYnR/EsJsiieUnYBzAXi/LsHOSWPkzfalEBRcw7HgvlrF2Evn7zZbE+o1mETDswhs7YphwjXnYMWAXDsA1SZxmZ6hJ0sQnIGVBfkk8EN/1NfGLD0Aey7BzQFzXD9h1fcSwm1dlBOQAwBXRpdlzhP+NN0LbkGGX9bAjSWwodwjYNnPT+I2iuoYaMfYWxTGG3bEkdaYqlw4zFYSkv2dJLEuX6iCEpApOh7oEUKHj1KNS/hbuuQt3c6sJcybso5BhZychaahy8qywtFE8yWEBZTyr7smI4UAT3jM0579xsZXG8+6Jel5m+2mPPgGcn2aGHQF25DeR87CLGXbkk4XSJUQWhZzWDI1/zw/DIIDIPgZxaOR6a1krwJFe/5kF7Jb9Jb7O/Ix7O1ev4XnczzLsfEnszMke1O+fCMOO2DC8ufY87AJJ7OXr7sle+ykADrBjlpgAAnSNxci7Cxh2dB9+8nXblITzuA78WM2OYBP70W8Fvu63A9/2HwMnz0z7G2o2ViUxA1JyVGaUiYcdMezo8+1TklgAOH/JfX3rPU4WGaXEUsPTbbHrhqwktlbj2QPJNMOO7pGcv6eubWNTreVwbbIklpg5RV4Se3Fl5/E3roCf/MJD9SZoXu92wMayVi/gnjfHsItAiZtaoQ+weNjFktgZpfN+5t4VcPGK+5th8EIleNOqvRKjAyMqBqFee6SSr7m0JDbJsKs8P+KQKXT6uj0g8IDxPXU9hp0OnVBji3sDYq4usMOyLuUwfEZ95Fsbe/3euNh5rMSQ0b+MGHbHeTArh6KlAV75ceDfewn4z3+JzxTRFfQZe1NiA6WNfdJxD7vJDLvA6/MSCwHXooRYQB3ykxc3vY4t/J6e39tJba8Ng2gcQhF+xkVO9ZHwer6f8LADnCx2MsOOD3z6AfXg+4dl94E3tHgM8VYq6r0IDFlhK+ET5cIx7IohLYnlNQZFhZcmMOxiDztHKhhCJrzah/D6srj8jHrAnfT+3SjDLgbsskEwdA9pSWzoYSf+hcnQCV/y69hUhfd8O2bYcehEIFMUMJC+N33j+o6pafHvdHGQ59ChQmt77gnkjGToBJCRxNIh0eMw7PoeQHreCYv7bJbEdt2Bklg9XyQZdhkPOyGnpAE7b27lYMhZANhFCp70oUjBsvKbLYm131sPOwfY9cGNnZVq9v6NCSDSI0eS2Ku37P9Xd6Rh5EVQGr3f8meBr/xO4Lv+ePzig4V6WSsgrqxlUo1TYotk8yMMu0D6xYBdThKb9LArEimxrc+2GWXYKQDJO8lIeNiZp4JhFyDrh0hi1d9zwyOS2CANOOdh5zPsElJmLm4yM0wFDcrmGHaed9wwTJfEagmbYsfIiVfOw0499rML+zs/98alNC9eY8fvWXv0RWEARzzO+B7k0you2sjOeg6dyDDsxGyZftC7BkeDXR1doz7wnNm2vZALlns2iadTGHbzcxl7v6b8Ee/3P1B8PmrIvGZL7rFKNWVuPlqGHnYC2LmmU0IneDBdveme7NIadfNpNLPEhGFH68GmZ4ZdCAzbcfnptyi1LWBK8+/1KMRb40ZXWQO//g8CX/87p/8NXaslQoadmisYYCFgi+eBXiSxExh2z3xwRBLrGHa7MUmsGjue1HVx2z4dtCQ2fZiha9P2firugaETDJCkZFv3H9lGd4cKn3lLNbm6kb56AwBwOSzlXr3YpkEDD5S4yaWZ4YDMHXwvWsCOQQc75u4/8sMU8OgLLhisNAqw059/miXAc9rnyZhdzPoBXxKbYNivAoYdJ17yYy4vSCr23Edy7z6q63nYOUmst7bz3Lyyh2kL7LyDBGYsvnHVC0BjSg3Y+WPL87BruqOVxHpg9id/wF6n139KDnTiP/AZEHMJnejTgQkphp1sjDMedpMZdj5gdzGshMEWJsTq11Kzh52ETtT+3EBgzCn9KQdLrYRhl5bERj1pysMuw7B79sz+zn6GHc/39jWlfEuPjWG3CADaSL3FacDYYgl7farFCQrysCsGHygVhh1LmBXD7rVH23gNReBhR/e6ZdiRUiBcp5XSRw5INqq/2j2S9VHW0aSHXcAwgmbYBdeBGXaDZtiRfJY97HIMu13sFx+C7/wYO2IaVhw6QeO6EA+7QBLbt5ibI5PEKlLHArvpHnY5BY5IYtV6zPvRx2HYaWLKHva2AHaMpx0qidUHDiYxB0eAnb839lNi3Xv1GXahh50/n4Ue2e6pCRwe0v3tk6onwrCT0AnNsGscwy4MnZiWEusDdtEmeE2A3dL55zza2gEgg/XdXwN85/cBd740fvHBh7usCw+g4UlVpFSplFh1qiHm6LxR5kmGJbEB88A16QVNUO5UoK4SktiQYYcMw66sPWmNtyiWbhLn4gH2dHnYHZgMaNjY2X7Lp4x10ORKo9H5HnbewlVkTjMBl8pTp5kKOolJWCRdCNipcaabzH2A3e33uq9vvcf9mRjPunEiXi3cmNBj36WX+XGSGZ7MSv+0mceoZmKEQMqxUNJTtYdhNxuoWct52MmJJn2mShKrG3L2GAsZdjqJejUbv1/PguSlpIedMcKyCwG795svuEAbKs/SQElivRQyeX12XDD4sogYdp1jd/IY50MYALi0gAf7vSwykth1GDoRAMMsyc0z7ErfC+tpKmq2F4GHndHjlyWg9G88D+xl2D3zQfX1B/KhE6rhabo+K03R49/zsSOQ6AQbAbWZjTeeLtxhrgG7Axl2DCSlQMHt2s7TW9T4+OuqAdbPQeP3EgvZ7K4TiamAmw9uviRWAXblTDpdT+LJEmsGiTev+49x9abbQJaFhHK1g7sHc6ET3Nh/9i0C7DywY1wSu5pXHoODffA++DyNrw2xAPU6uaemJnbb1xcz7DzAjjfESw3YucflEJTXrzoBaO6eqnU26DcWKiV2TWxTAEcH2LXaL+viVfcPl6+n/yATOgFkgidS7LMuzbBzqcATt00Bw+4RlniLJbFhQiwA7WHXdL30TjudIg/InH1CB8yv7WHYlWXQH3ONhE6I5QrVc4cy7KjX8Of8kGF3HIDdcuZ/3tHnT/3fubmSg57Z8gxVRhIrgUjKw+7uyUyk1l+4H1uhtH2vPOzs32kPuz5i2Ln5Rvqz5sL7lbPessDlUGqUYadSYrvMAZPqqZisE3pQSg+s1tVhGLD2Ah7THnY8bpwktrU9Qe9bfcQMu1aBxkey/6jmEKsmNJM97HaZw67x0Alm2F0HsFNzyl4PO/vva2LY9bROh2zebA0KyB71sEt72RvjQsBMt5M10WfYBcGQWYZdMMeGHsk3UhI7GjqxTjDsfEmhVIrlJRu7zADkzd3yjkygzLDbGzgB+BIKOHo5PzcDcHKKKSmx6dAJZtg56RedAhgG7PxTE49WrE++SNLaDOHgCwG7XYZhV3rSGi86PZFg+nRIYoOG5GBJLDPs7LeOYZfzsPP9GTx/xVxzBIww7OIkphzD7orG2cm89EHcfSdHGrS+rQC7BFtFJEk8lumx787t+/3Z1+zCf0fLYfvOTajV0oHZEcPuSBbMVGU97OzGab6HYRexGWmMdCg8BvFA12hoQ8DOzW/75HPPn/vjwWPYaYbg+csAgHcZmk9f/AUAgPeaVyMAwQsNUpJYHjv6NYWA4jlLdBVgFzXummFH8zuHByyDlC9h9bCHnUiv3SI9DIMYcnMzONAYZT+f7lgksdcpmlcWBFwxgMUn/wBkHeRNFW+QGbBLhk4AwNf+VuAj32oN+u9+YMTDjiWxO7Rtm0+JVWPHA+Lo3irMgJoS02YTJLGbRm0UKSVsUklqLjHsEpvKnjejqPD6I7W5Kgo3NxCgcDksRE6mAXddRxM6oQ9i1Bwo7MqmF1YSX/tVCNit7znZTlVgTv1RM8TASg6w402JJ/vfI4ldzUp1+NoL8PC+Z+17ut0QGHTr5dy7j2ojAUAT5g/tYZdio/LcTIzS0gw4V0tlNTBg1+NTb9o+4rlbqo8I+o0VvaarpsPVrov8mY+lPNP6CzWWcoBdANZqdlQk1weSqpPoYItqIx52U0MnfA+7y2EhliZJhh2rctDauY0Zdqh9tjuNa96zcBL8smTAzn994q8UedglQifWHDqRlsQe6mHXdoPYLZiKGXaZfeANrfDzjiWx9j68C2ePMFueoZgRsydg2Mn8JmzzCsaYUR+7roslsVVhUNL8GTHhtYcdg2bNI+9XzlprKyUWFKMedu5zz6fEutCJcI8U+tjrJZ6VI33mUFXuC173aR6v0aIsBpHQsvRbPOwKJ4mdHZsk1hh34Gp2ti8LFTKJ0ux1r3jPmQydYIbd1bg/aKoOAOycJJb+9GBJrH6ulIddYI0VWBuU2sMOEDasN4wldCLDsMvsY6sqeA9v0z73iQN2LnRCMexMcLNOYtj5wEeE5jPDbnVXTvfZw26Sx4SWUABYVT6wxc2UAFkC2BUoE2lMV5r5BMgHxijuJqA5e5tcfQIjHnYBjT3pYafep2pUPMBOz4ylm8S5WBJ73IDdY4ROAMIU4IaHgd8qAGbDOPqU2f6oJDblYQcglcSUS4nlaPnVrAoAuz3v9bYy0r77AfdniXtypxgQ9vXZx741I0ksbRjuqCQxn+03U14mfDLxFIROLM6BZz/sywEBB9gNezzsJAzGB+waVB7oKwy7duf9/TpMoh6pu6uZ1+TfXs2SnjVaAtaZEvjIrwUAPGseRgw7T9KrJLEpT5PwNQrjT1kdRKbHxEoCIJJCfs/Lgp6PxhWzrLYhw04d/jzatrIGcTPIUfJNY6/FU82wI2D2tPIlsYWWvChWB6DBZGbYZe7X+Snwm/4b4Df/t0BRCAjR9YPPkFMNct/uHGAXyraMUQx89ff1StI954Odd3Jzo65N02Fh2FR9mf29qFhKR2t8ChTk+3I3VJLC7F4vPReBC1dYCDtlnQHs3MHmY7Vjb39php0CIzx2ZekDdrc6BcIDwNVbXqgEA6PNhNAJnVwJpP2/rCQ2bqpzktgveWYFYMCdlgAg7c24pw5j2Ll+NslGbX2GHQDcqlwPwbK6XV/g//szdm780meVV2woiRWGXYv1rksGpR1DeWuLx7B7Lf0HQZ9Rl0Z6nLAHB5Du1zL948EMO/VZAsBDrPZ42DE71few22CWtF05oX5VAOza+O9Jfp1YJYGXmnuf+0MnnqXQCQ58yVZCEstzgfg80eU7FobdVEnsM8YCds1QYrlcoGIpXnDdZX4LDiFfumMfJ+Vjl/Kw0wy7LtzKq/lGlEC7h96vnHT0ekcZdmpvQo8zLSU2bRvk9htu7uODLGFZSzCYv/8Shh1LYk2HuXFjyGQZdjol9u1hPr0tRX3aAtuAYbdfEhsz7OiwjVVew+DAqRUx7Ibe38dNKb3uTAydWAuB0v7tdMBuH8OOfsaAbyIldosaA/WTS2xRFirMp925dZh7He7nuq29ZhkPu7IOGXY30MMuCdiJh90afXBjO4ZGDrBTF4H159So1GEzKwy7u3LiwVHpkxh2oSS29AE7lmKVwSCwHnZx85PzsOMJNZTEejIyj2FXoy6N8rBjSWzoYbfLhE7UHmLsM+zi0AluBIsja+S8ekIedhzw+/BJpMSGDLu+d4Bdxrxbf8ZJ2QyAS/KwO51XSrrh5EnZetdXAS99zAIyX/kb3FOHoIl6zjB04tbMfy3PnGYAu3LmFkaRxB7nCb9XX/fbgH/hR4Ff9W/6PycAlgG7fSmxMv/xieSgQifgPMaGYPHkxmY14YS/KIwkuwHAe++ukg06nv8y+fK11UdELn0XDxGu+S7ldvAksZ68n2o/w64VkLLte7sYcpAQIGw7YbFwc0vNpLCs+ICIx5mSxL5Fm4uTWYlZbX9vu7P/vtnaf7Medkc8JseKGrvziiQ4tHEqqphhV1NDGzLsspLYoPThkQdEqLE2tBu3SUmcElcikdZrVoENnYrOOp/BGtoF6Nq2ShJ7yKk6NVpjDDu+j3aoZa2Q4gZva+VGF1jIZncvw+6me9hpb9KVAyM8xpikDtvP+TnzwH+M9VuebKdm6fHg5o5o/aG6HTT2PjtJeZElGXaVAL/bppHQpPc9e4JTrN2G7vT5zJuPS8zjD2XY1Ym1ndf++blsKBhoB6ysC7DA5l/9exa4ev/zZ5HXMxcfHF9urSQ2VAscS3lsngsF0unDHV3B4b8xBgsJ+Ujcf8KwS4ROBPOGA2gnrhfBwd4rw92Eh13MEpWUWGI8bYfa9/Cm3/NIBgBOeLhHci3n5eVVsKFtul7eY+iBe4cYd/czwTlSwrCzj930OmjIXk8+mOiPBLALPQsjD0Pq/54lwG6NOc4XtWziK/jXna9xLQw7+3svkioiTLAG2MPOv9d9wC4Ykxza2LXiNx0y7BbEMGpHPezUPUDjJZ8S614LH0oLWDjiYcfKEcN7g4hhRxLYkiWxjokqsmI4hl0XAHbFkGf23+gisHSBnd3HT2DYNSHZgitk2HU7d52ZYQccHjyxj/WmilPe1639HDlQ9FqAXUr5kbPG4vAXYwAYdBV5TpqdryJiABOIGXYAgdZpaXVdBz3mIYfEB9RjAXZ9kBJbGiWJhTuJDm/WaKJOSmJ9tD3aBN//lP3/+bulYeRJ4FBPEUAZttK/sYddETHsdEqsGzRXGQ87YdhFKbGK6h8M+kkpsSOhE5qtkPaw05JYZtgdMfMpbFoP9Uujv2ffIt5QhMCsNBqDHcNtihlRxqAoAM8DImbYxYCdY5G4z6/rB2fCP1OS2ClGqtUc+Kf/KvCb/pQnyeVxopMZmV3qQifsPX0nAOyYwm9fewawe5oksbkiAJYboH0psTL/Kc8Pj8JeBiAUFc8xUxlhen74kmc0YKc+g/d9k3z548/+avGzeMY8jCSxAjh2vbrHZtLw6QbuPEipFYadmtdLDdC0W9+j4uotYHDjfSHgi71XpHkTwI4Zdm6zzn5Bd05mWMzt7zUNAXY7FfiR+byOvuhazWGvA4MSJgXYDRkPu4kbfD3WfMCuBnuxoN3Ia0mBaHwoFzLnrihpddYdwrDr1XNN9K8DEIdOxM9hRKpWySGhVBDMcDVBEisHnzfew04dNCn2kJZDD4GH3TmC0Imrt1RKrJFQrmaKh10g08tKYhMedqdzlxL72oNLDIOVwrx8Z4lz0CalnMeBQiN1XQ873ky1mo3Kdgv1Al1px+tZpcaLWivuEejzwedP400KFW+OLnctrnZt0sblGEoSyEsDbO67f8gBdonP3iXFjnnY7WfYOQn0xPWiXrq0QQCvDneFYce2K2eJ0IkKnb0HJCU2CJ0oGLDz38+KbX0iDztmGo1LYq9UKM5JFFplrwVLerNV+gy7NuFbenQedqEkNuMP9gzs4cQV5jhfVqhIElsFDDvur0O2OR+wvvYw9rDrhsGROAbneSqAXUYSO2hyxs4H7NjCxYVOJBh2ej6kz3RfSmyjGXZBuKLYYql9Dd+XRWA/FXvYsaqCJbGdrB/2SZhhx3MdAXZ9I+v50UhiAcWw27keGdjDsLPXNSfbFkBOh08sbrk541AfO153TGllvCMlrG/6k4MBO9kfmDRBJVwLQ0ks779ofV0Rw06K/euqpVsX9L2gAbtgjq3r4D28TePsiTDsCsWw04Bd0RHjJKDDtv3gJzaNhE7wqVC0qXrjZ+z/n/1QtIBOY9jRBR56oO/90ypTKMDOR/290AkPsAsZdjTJZBh2npmuBjOMCSSxQegENQBx6AQ/hn3eJJsxAdgJw648rkbOqxyyPhUcomsWYAyR9Dn0BgwTkLzX0gUbOe0dkAPsEh52evN7pUzLT+ZKEhsaXh5QocxXP6eML3p9zwV7mZfvqPehr7kxT6ckNlf0eS4Hf74Ly2tUh0HmlDYInRhSvjoA1g3PMdNAlI+8cCavZ1GXaebpcx/Gf/uhfx9/oP1H8Tee+0eFHn/XPIpOUPn7wpPwVzLHaNDR8zeE2lwrxnKtA092wcYe9meySQrYUsYYzMoCO5kneZy5e5Y3F7dXNeYzAuxakpbtyNsu59H2NFRgAC5JaboJYblAKImlsTJMBOzKwjgQVUvPlBeL6XajXjLCsAs2cpegNFIC7HhunBw6UR8A2AlDrM8+R9ETewSVMGWkgmTIS7PEM3Qv8P0bFrPgb76HnQIjNWBHjKNhAHoGPNGgKgzOTXBiv76HRnx2CrnOO8Wwy7EEQoZdCuxA1yQPJmZVgYGS5b5wz841d08sE+aWobkn8BzbVyKRPIhh13r9qrBEhT2xRFvY8XpaaBCJ5Wbufvzq99yKex8qx7BrsW764/Ww02wezYCI1guqRJ/BgN06ybBTzEx50ifEsAO8jeWbOBPAjsOQvHVS7h1KiaUxsUXtK4zoM/RUQdApsWm5VjG0/r6rVQoNABfskVsWMbuVwPIHexl2qdAJf+0+upTY4P6OGLXCsCNW9bDErWWNilg3IcNOfMYC1hdbJyQZdgkPu6IwshftQ4ZdIhm4CCSxc/KE3fEal/KwKyqXyEmfaT4l1ilGekmJ9UkNKYadAIahUir0sGNpe+9SYudw97Rj2PE1IAC8UyDUMTLsDIdOHOJhFzLs6LCN502eS6uFHSsC6F0TsJuwr+M16YoxPgKezw/1sMutYfxzHvPBfkcwEbquyxxgp5UE4fjPEE9m8+AzOeDg75B6PMCOmafGSV4blOgG+r5jUz+fYQcA3lw94mHHDDCPgTIMwJsft18/86FoAZ104qk/9L6VxW83lOgHd5pWJjzsUpLYK/EW8yWxJb3+MKq71Uk7Cd+NNudhR03l3LSY62sSsBSTbEYtieWE34GBySOayMIKqdTKEP+Qv5+HEsDB/5z1+O36QTZz3k2faaDFO6BaxqcDiSSmFIuEGRplYewY7xInYgdWVcSb31gSa6/jHC3efcs910t31KQURGhH4HCQ3vlUFTEWV4YYdpn5xzNbVuOjRRmwNDnJKJ0SO5Vh9+//xq/Gd339y/gPv+ur7Q8yzIFP3P1G/P72Oy2rlxl2eIiQ1MzzuNEmyuXMNwaniuRr/L3ym/QCT7iBKOeOMbt9hHXDBs0x2FSXyjOV50c1ztjv8XReYTkj2Q8BdlsC7IbHWwJvdgXMXQeWxZtE3jy0AftzqiQWUF5mIZOFQdZ2OypTrXK+ncSwq0KG3WjoRJcGKPdVJImNn4MB6y3qmGEXJEP29an0BCmGXd8P4vOcA/pvTOn3puYQ3W+taTM1R4P33l3hFjPsuPfYPnKhE2UhsrApklhmKnK9eCtOO0anQyeC9Z/mnlceXNHjzXAyrxzDbnk79a6zJSEEB3nYNR4QKbJYBRK1hX1fZxqwo/fETMSX7yzx/Nki3uRSnWpJ7K5FcfQedoUP0mnwzvuDeEPFAGlSEquAVPcYmZTY1u0BJheFfTXzuxhQSMLvGxTe8Ky2FRE/UZLEKoZdXcUM/FAS6wA7/zNmQ/QSnX8YEvQDbLdyMo/7Cwbs7l81PugXVrDmNN2gvNp8pktqbr2JFQJ0IfuQ+7/nzX0AwAWWOF/UIpOrM5LYMpDEPn9ur10q2KPtB+Xx5h5P1u2wj2GGnQbstj5gN6MD5iaag9R6qQ7ceH+SZdgpFjD/jvxuGXrYxfsNTxKrDrRDD7td70InONQRMCiJdCL+eLwH7wP1z7GUYth5HnYjB5CTU2J5LmUgjwGm60piJ6wrzFS9amm/gA6FAc7C+yn7XHtsHSJrLH9PyvuZriTAzgSAXRg4AQTjf5O1dqoXmSDJJ1yPJ4lNJsAYbIllFzLstIm5N1mPhU7QTettaC9eBXaPLPJ5933RhDrpBEwjwn2DZUmGmiixaTsH2FU+GDSvy8jbDNAedpX3+Py74SbG8/8TGj8DdjollgE7ThFzp8CrMpZMyPOaEYYdIAOPGXYmTDk5pnpcD7tAEssVSp9Lb/wOKiV2giQ2lxALJJOYxKdJbUovuKGaldYos00DMIeU841yzxOHTjBbbod3Kxnsl79LTWzhNS/9k9aDZcrHVGToyqlDkd8mFf+46wfv5DOUxLJk0QTBJVcHhE4Almr++77zq/HtX0NG6pn7QsIk+gFY3bXvxewc4EHFY8Vj2BV1soGrysKTrEUMu771T9q5gZifugVz+wibHfuvxUDPrCpU6ETM5JRE5VmFxdzeI11LYAtJYocvEobdh54/TUtE+RSaZDsyDzDD7iDALmYFe6+j22LGYyoh458l/DQBm64IAFU73cNu0/RYjMhvs6VYLqnXAkBMxHdDFXvYBSytrj6VniAF2On1OQx5uXF1qrxu3vxZ+VIDUBedvX636w5niwrnzF67ZeegYXfpSV4ZsNv2idCJBMtHN/cv3VZr6R5JLABZ51+9z4DdHCfzCreMbdT7AGzdV9dj2DWoSpfyLfeK+Ect0RBgd1LS+FVm19/0Ze9CXRr8nl/zUXrctIcdrxHrpsPlVqfEHhdgx/ffzLQ+Cy7LsEtIYiuWxI552GmGXXreYJXM5JRYAPiOPwR8xXfgrX/gXwfgEl2ZYfecBqFL9ubi0An7u5th5u9/aCzdCto+lxKbA+x6f24O+gHpLxMb6NskiW37AZcZab99Mr/va7tBrd0ESCZUHTe5QklsBGhSv/Kisb7qj4Ylzpc1amLdzNB66Zs8b9QShOBLYlOAXdcPLkVV3evMsNPMW/sPCTWVeGhbBtGMJLGyF0952AHxZ5pNidWAnf0RW+2EKbF63eP1wGiyw6DGKRMmSpbEkqcdOuVtPI8fO7UvOirAzq5vC+zse5riYccMuyr4bMTD7tL/fx0Cdocy7KYzt3le2XT2cyzR43xZT+97tPw2VaF/fCJ0AlCAXY5hF9iaeOM/Q3qoF4Ev/WOQaMbqiUpimYGxIdZDSYBdWfp0WEACZ+gb1qrrRcl+uMwA82SHLIe9/V6gmkcGqakToqg0pbFvMS9Ic48SV7tOEt0qORl1MkFpftTAcR52PsOOX3+YUOX5n8kg4InJxCmxnc+wA4CVdwLrNyplalHUG3V6To4cL54KwI497B4vdIIrBGY9hl03pBeuXEqsJMQGNzbgDCrVZDkX2Zdi2IVJxBMm8H2VWkC5oQhDJ9Bu8c//ig8CAL72vbfxwecVYBf66VVBI/zFwLAjwC4XOuEz7HzAzpMX0AJR6JNBHJYSm6wM89QDztRidQrfS4Xn9zDVuk1Jw+GnCMvXHsNOsTt1IAtvnLePRMY0G2KwqS4LFzrR7YIUp9olKs8rrMjDrg0ksYcwyI6u1MngH/ruj+GbP0wyxjJmdfBcJ+sFXcfuAM9JL3zAex0MQG/2MOzSzAsB7DoLrMymeNh5oROHMOwIwGRvtcRz1AzYoca27f33qySxu6EE5ucOPElsdPX6fOMZdgDwS3+X/f8v+1fkR0VhZK140Nr76XbdYV6XjmF37gA7rros5DpvUwy7gCVgjMFdxUjyGN5a2phZ/5nB8doD+xqePZ3hdF6JbLedHSaJPYxh56sb5F7hg1zFsBPArgg8eQH8vu/6GP7m9/wqfNtXUaDBHkksALxxsT36lNhwLdoL2KmUvoUw7FIedo756J40J4m9BsPu+S8DfuMfw8kv/u0AgEfbFhfbFm+Q7PHZMw3YucAWnRK7Re3fCzSWluUg7w0AzmY0f4QedhJ+0GGrQcvOByaFYZew3FjUTiY7KovluZZSFXdd7+ZhCZ04Lg+7RWC5FFmSUL/yjLEb/iuzwqIuUc/UZ6vuzx2lY1asVKDPnXsklk3ravveseh4fRwG8XCLUmITAYMCyK2eAeBCnHZjKbH6e/GwS/d7OiVWJLGhh53sS9292AjDjt9fFwQM+PjBmgCfwgzCEkQ5i9l7wfzfoYzVTTe52GrHTE+JZfBznk2JpTEQMewCBp6uH//vgO//NwLQhuoAhh0f2vNYrdBP968DVGrwPoYdk5x8cI33L63ysCtMArALD+48hl16D7VYHgFgF4VOsMZcGHa0gQ087IApDDvfw85bsN4kwO6ZDwGIN7CTPJ70c3WtAGstSqx3jmFXVD7Tz/ewUwy7bcCwYy85mpTj0Ak16anERX6vLiU2kMTOTuSk5aTUNH7fwy7pE+GBlA29PpbEPkWA3XU97Ep/QioGH7ALxy+zUZIedqEkVibIBMMuOMEC0pLYCxljQYLwY3nYxawWmfSZXcqP327xyz/yPP77f+4fwB/5bV/vP1AIBoUn1zmZ0tNQamEF8htvaSiGwWtIIoadiqPXJZLY+pqbrsx9UejXVZRoSvt+TuAv3vz6jZ6vjYmMhbn0Yvzeuyv3NwDQ96pxV5LY2anzkNg9knmzGmLWw6wq/NAJL/a9VAy7Ektm2FGz3DQkiT0yT6eDSjUa73/uFF//HmoqEqETvHlorulhBzimUcyws6+j7PZIYlny0vobuUcDbfRaXxLbD3mWhg2dyD9Xtuj9ztjTL3j8tuuFGcGHah4Qp5q9ezjDyaISCbv2IOXSKe433sMOAH7F9wC/66eAD3+L92M+NL23tZ/Ned1iWZfOw44SM4etkzLOSnf42fQqtCQTOgHYVNfwOQH40saMz4wAdg8dw64sDJ4tyXy9fjsZduq19p1Lgaf5SPxrqyV2xo7XlQkOuwCgqH3vvky/Ma8KuZ+27fF62DFDZ2UmAnaJz34h89IYw04DG2kWhfu8D982nc4rYYd+9t6VpMV6Mm9lT2AlsZQSi1myxzR9662xt+dpwI6D8yTMgivwehyTxBpjxOZiNHiCe8WhB/qWQif8eTgVPHCTK2RUhgSR0Ld0S/2TTo7sVIAYj6MyAOxYdvxw03rrWt8Pdq0LgwiDHtIr8fNiD3gDw2AMpYLWHDrB67Wag7xKsCaBxHqlJLG8bobBfEmCADPsGDynsePeiyOyAD4be9aPAHbBfdAWR7b3IDDtFOvJHnYuGCf0WQwkr1lJbMCwu3gN+LO/E/ihPwB8/K/GT3gAYFeXBc7mlQB2BXrx951U8lyZ+Vd8G8cZdm3J3oA7f8+S8rAD4HnMZ1RKy9URAHZdwDBi4G4z0AUiwC78d/23AEYlsY5hpwE78q971gJ2IYU7mlBTVRSO0dc36nSgsAy7hsEYPqlgwK5Eybr5VEqsAHYBwy6UxOpNLg8w3jyVRpmpc+gE36xzSQQ60QCTUFPJYNGozTCXx7Czz8kee8fNsFMLWd85JH4qOERMyZNagSboI98XY4y3KIynxIYedsywS0liabJUHnZjoRMyvg9Jic1ULe9HSWIjDzs/QOJr33sn8hNyp9Iz/2/EW2z6xH50RYveCltUhbFy5UTJ2OmcJLankaYXDpHE9r40Yh0G2xxaqZRYuHmZLQ7a2i5YJ1gnf48lgTzXJO8D+EC2SKlVorMnjdENhJLEMsOuTgF2OnSiVcwaeo+XwkissFrYv+toHO4IsMvS65+GEsCOxpFaQ6QkmdBeO54HTJ8GPcYqYg3JcziJ9xjrjYE4vWZ1/SAMu5J8QLVHZI5lt/U87A4wAGYfqQzDbtP2mJNclseet7arzdu94QyrWTWaUqk3rUfBsCsKC74FcxyvSW8QYHdWtljUhWLYEWCnwpfq0jjLEGLYDcOQlcQCwO/5NR/Fd37sZfyh7/6Y/w+81rcbAGmGRUF9wmZLYAmxm26X5OVUBY36nrpWSixgfeyqgPWl7s0dHXgLYJfYvEbfBx52xhivLz52ht0qYthlPOxGQifGPeymMOxIEntI6IQqZoT+6CetdHJWFr7Xq06JDRh2dYJhh77RSkvMM5JYATzQ+XNzcMh6ESo4gmJw8MHVBIYdALQbtP3gyRaBjF3PDa4QsIv6r4CRIyFJczd+dlvXy4mH3eD3xHosaBYjH+q0oSTWU2lkJLH0u2VhHBhDPsV1lBJr77G//qlH+Ae/96/ij/7QJ+3Pef3cmxLrADvuJSMPOxOAatAedmouG/zDV/t89v2vFWC3oPeAchaTVIL9X2eObI875z58Q5LY/Qy7rGw/Cp2YyLDTIN0rfyd+wgMAOwC4fVKjG5hh1+GZcB85Vns97AJWabAnDQG7E2wyoRNKOQb4DLvMHmq5CnqHQ4LODqgnC9gxAk4NR0kbzpCBBwST9ZD4IGgjZcYksc9YeV7MsJu4oOrTSTkdqHC1a2WjWIUMu7pIethFhvBBaEZ4utfoayebI/Kw0Ay7MKK4msvEs/QAO//GcaET+v2WAHxZW0mbj/IxWFrveAlg1/mNVzmxOS0YsFN/ij76d0Dd9MrDzpfEJhpAIJ4gdfEErFJiUww7DUDYF5HYgB9YfNrZJBZQlxIbMwCjCrX9oYfGF0FK7Arb2OxVlXe6SNejg+/PATjAruobLzTmUA+7qDKS2CJodHa0cT0d0gy7IvAjzElif9WXvxD9re9hp8a4eGqsfA87nodZHqw2BL6H3ca/54oKV4oxcEKS2J4BO/awOzLGyUEl9y3NE8IciWVYzAQPQycOYtjtkcSW/VYZkMfrjfPT9BPkrih0oiSGnWfanwHsbErsNTzsOPgp42G33jmpbUFsaS99cu5klfeGM5zOq7y3H3xw8igYdpniTf5rG/teT4sGC49h97L9PwEtxtj3W4mHXRx+FEpiAeCjL57jP/iNX41v+YoX/X/gtV5vOIKxa8iUnA/i+NCJ01h3xWFNNssLJ3maaeC727mAlra3TRpvLuolNsSwWzDgrAG7cP3MeNgBllnMVZk9m50bWnz/sd2E9K97Pezce1+OAOajKbHBHOXYK9fbNr3/Odv7/cBPvwHABod4/k2l88/cds7DbjvUfuie6jG/9zf8AszKAr/mK1/Mb55ZIYI+YNj57zM6EA5KgifGJLF6bWm32GmGHYdOHJmHXSjbixl2t71vt4X9nGdKEttsXW+/E8DO78e07+89xWKUAIcIsNPBZeOS2LooHGC3soAdM9Zlzafx9q/9pZ/F5+6v8X1/jQE7f3/Cv1+EB9P0ehoVOhHaBvF+I5USazziRZ5ht+nd884EsKvjxw4OBZsD5/d3vGa2Dz4xG3uQOoFhl5XtR6ETrGjZw7B78Bn3dRKwO4y5fWc18xh2EfFjrPZ52IVkmWC/w+N1VznmYjJ04hoedlWonHubGHaPtXoz8s99FQNzLFOqiK7KNxozlLp+8NNLU3G9AUMtKYklhh3T//lGzZ0QRVXU9gPoGufZQww72ShWCgyi59rJaaVm2AV0cpowHWCXDp2wHnY+mFGXhU1sBGJJbLVAyww7HZIQgH4SYRzqzkt+z+xh1wEGKKvjauS88oBXDdgdlhI7KywIsGv7ALBz16YqDHYIGXYmeqyDGHbBCRbg2AW6wboMTYG7a2xIg6plk+yehyf9WQjY6aY2rFBGoozmvb99GiWxtOjNTYNZmW9CPemppHCSga5qyAuVLrbreiwKZyAOTE+JjSojS/akugCa0i5Yq4wkVlK36HFyEol/5hvfj/Wuwy963133QxUmVGuARgDtU8fS3D7CeneXnjM+XYw87PT4LOc+w45Y3z1LYtun2FORawrDrvAlsfxZMsNuOIhht0cS22/TwRf8a0V8SNH2Ay4YsGtYEuvGWS4pdtv21/OwE1kaS2IDht2uxXMEpJhqAWwDSSyFKwDAW7AJsTKXJyR5fM8VBllm7jHUKfU9r9CUsSoaLEuD84Bhx/f5rCxsP0jjzgF27nqnGHbZ4nGqgZzQGFqZ7wPAS8T6PS22QHcNwO66DLuuVWNCgXX0mvnAW0JT5CDCxBujnAUHbDL35ynkgD2aj22+ixh2py8AF6/Ya9Y1MYAZBLgBe1JiU4qITF/lPu/rrb8s5/7Bn34dAPDy3aAXZA87tNaygV5TzLBzXk2/4qMv4Ef/9X/Ygkj/05+0P88x7EzIsPPZImOhEwBwi4In7o8x7IrCvo9uZxl2XR1ZE1S5vckNrVlVoC6NHCas9khiT29Zr9iqLLAbSsxMh506jOf+uggksYAFRR9tWk923Apg5+9F9QFlt49hVxq3ByGGXcUedhJ8wwCxfT2fvbdG3w8oIg87nzUnxYfQQ+lYgWwbxKETDNZqCx56/qJUAY96bBjf5qnpDbrCWlMxSxDVXHAIJ4kt7H6L3ndTHhtgZ+eLHMPu/tUOv/OP/Si+8UPP4Xf9qg8DGGPYcegEjQHtGQ3kAbuHn3dfX7wWv8ZDGXarGR7SOK7Q47nTA/aDKWKXrtA/PlCg8f6E9zenZp1h2GUkse0mUkNKRUEtN5hhx8glK6LYwy6UxOqvPYZdiurIHnYIGHbDANwn1Jci040xHuvkZOqGtlTNDtN5hxIX21bAEW7yWGY5rzIpsUwnDzzseOOzCzYWnv9ZID+qS4PdEEpi3c3K9OeFlxLbee8p6WEHIPTseDoYdorNFfi9TPt7R8Xm0zTxfNH/Dn/8Jj3scpLYSSmxCrBjhp3yc4o8Rp6AJNYZvY8w7EJ5a6oihp3zvbP//hRLYhUIe17kQU3vnlTyAcCdPAJASYDdjAA7rscPnZgmieUTqJOIYWf/Xwx+A+4dPqiqygL/0jd/BN/4oefcDxWg7Z2Iao9HYtgN20fY8Gl0jmGnPezEo68CisI7RDlZzuk90ilw88UA2PHJODVhqY0o+3twSmzPgN3hDDsPhEi8jqLbSfpq6pChTsxFXTfgiiSxRcPsLCO/22R8kDZNd72UWPF7IiZm8PjbjbsnzMy+Li9Q6tkPy5efHl7AyWycYZe7d46teJP/+tq+j6VpcF5uURq6fgTYsY8Sr28iiSWZkx47KYZdtni90RuOYJ6ryfuzIMnsyyRRZOnp1kwfJ10/yNw8jWHnqxs8Nqo+aKjmWBNreMGssjF2ujoACeuu8gc64z89MkYxzwXLgT7X0+fdP6ZYdqOS2BTDLuVhl+6rrhU6oerDL9h1jcfNyzo0BfCkq0Pjeq0NZr4lkGxM7Rx1a1mTUidBfAge12M/BwwU7i/3M+xGDm4B76CoSXrYUb8xWAn8MZSei1bh/R5IYn/V11oiiTEuPLDZpSSxfP3d9ebgiXuXCozrXCAiAHeva4bdEIBn4nNoH6dKSGLLTkliezcPcWgkAHz+wTr2sBPWXHAfdOzt6iSxMcPOPxwGFGCnJbHy3owAC+K33Q+yB647J4ktdagbV+3usaY4wBrjJhRLYs0afd87kI3ur7/8E6/gb336Pv7gX/kZ/N3PPgAwxrDj0Imch11GEvvgc+7ryzfi13goYLesHcPO9NeUxGbm38jL3l8LGKfa0v7mHFc+YLe+Z/+/vOM/7gSGXez7eAMBuz68GQMPu6qPTdhTGvZJHnb8IW0fuUWZqL2Afyo0nWGXksSWuNi0cto0J7Ny/nc/dKKU98Lsl1Uoie3TDDuPnSWo7Zgkls0152hoQl14DDv/GkYGnKn3DAdMlcfsYaeTvsZOo3OlfLUYsCszgJ0DXfr0ZisniW1Y8peSxCYAuyTDLpTE7vc02FcCmiRCJxzDLgDfUhX6voSN8NMsia3mGAxLwfLNrL4nBz6NNHzPK4bdzIVY6A2sk91fE2TKGKY65p/9fleSJ18A2BWhhx09TqPnsn2l5OteKqgePyQF6DcP3aFQwleoLo1j2LW7aKOlD1FOFjyPd+j64YsEsAsZdomNKDczIom9vofdPsCu7Hd7QidillXT97ggTyDTuA16yjKAaxjseuw87A5n2PG62IYedgqwK+mgZaMZdnSICAA/3r8Pq3npzeXhBpXn3SPH66Tn4sPahdnhlrGfV2tqSSY0gQ8he+huO5Kr0PUujG8TsLd4ThPALl7/65rGOnoUBnjxlv38Tq4B2OkxPhnAUTYRHojr2XjM5BrKvZIJ0bA/yzPsdEq3EBmOzLOTPTWXDF4ubrn3nALsUqETlc9Q90r6NbVuZ8K8suyVifX1X3rX+/7L3xWEnKiU2EExsnbISGLDzzzn8SSS2M6fm2XzGayXidAJwHmsjXrYqffhADufSZb1Mr/BpTf2RdjnLG5539569t3yNauhWgXYiWdb718XADhf+GxHwK3J7P0VSmKboUR0bsXBZRw6YeD2F7RvZsa6x96Cs7QCgC882ET7E0mJjUInXHAjA3L8+fJ6nSKS8BruAh57xaZSsn4mS3S97I81YJckqaj9FnuXHU3N2MNua/sxviYEsv2tT9+XX/07n7NfZ+eoKHQikH/mGHaPFMPu6s34NR4I2D17OhfArkSPF84P6M32edhFklh/z8DtBO9vTs3am4vygF3Cwy5ci0OG3Y30sBM5h4+ebwIPO611T95UI4AdN3SyYPGgqVceW+l6gJ0CV1Qk9aNNI6dN8zoInagdYDfQZKwbAXnuoJHqFCMLCE4eAqlaVRZyMiMNiGJHsFx2WSROy/YBdqppHIZBNibHHTrB76n1gaGpEiN1Su0YdjElG/A9GMLTI/uNAg91jTHsdAoNlWxIk6ETLJd+fMCuLhRoAgvCM2tFThWD0IlkhWDQF5Mk1hj0lf1cz8YAOzUe+5Y97LiRUR52M5akbnzAjg8FrrlhyH0GPLUKw44WNGE1UEnSV+83+l3Gwy5Zal6sNVis/dWIYdeuH7o/k7GuGXZl4GHnb7Q0w+6UQicK9HiwbtBS6IQ5MsbJQRV52CXmC7pfSz6wChl2BwDsPF/kPOzm2APYJTzs2m7AFaXEGmU0z/NjysNu3XToBwV4HNI88RosgJ2/fu7Wdh7vUGBWz+T53N/XwDf9HvzEnV+B/7X/eizqUiR0wxAzAvvh6WDYnc58wG4+bMW/bl2eycag6LYo0Es/V9B13vQ+2HuQHBZw6w6PkcS45V6uRI8Xzxcyhjjde4vp40TLKycDdspXygO3+b4sbM9yNTBgxww7/0DXf8xAJqeKGVEAcMJ/emQHFDwfzZgtWy+TFiJSiWu1OFQSm2XYHSCBTtRLt5fiYwcA3/A+H8DTHnYDbZw7U6FHIWul/5qDHjO3eRbWcO8TB4KebZ8kVhh2+wA7tcFtu0EdnPgedoDPtLrJ9XATA+JSJ89C2LOAlW1TMbmiVYxJ+xkMKBKHYgyWasCO93CDCQC7zu1ZowAPsWRqAQw40X0ppcQW5GHXtL13L20Vw+6ty12kAEruewDly2w97IYh3iOlFHZbkcTGBJqUuqkfXEJ73RFor1JiPam12m8dL2C3duEagICQP/Oa64d+7g17HSQYJ/TZZCZdt7P7ZO0Zrf8fMuyu7rmv128FpvjIs3oz9fKdpQLsOrw3tAUYq30ediFZJlAU8fjYskd36GGXA+z0+M+QHo6CYce9Mr9pYwwK4yi19UAMOzVBlwnZyxQPO/FwuLIJS3xiy6VlsJMBO71Ya4bdtsUjmqDnM44pdymx0swTcMYbQ2PUYu6FTtj3qhdL7+QhOBWclUYBdmFK7ELS6RYasIsYdkQPDhdE1TS2/SBMsqo+YiClUCDZdYAhbob6TkxfhWFnCo/+4E55HADrn34qWreuUQ87nhASKbFqQ8qLuGPYPT4IVgab5F3KQ0g2/mMedkGTG4ZOPM2SWAAdTdhnRR7U9BpVupathE6oMcTeFWaLXdMBP/7fAW994u1LiY1CJ4hh1/sMBr4NysB7pe0OAB3U/eE1bxp8JsCuJ8CuLEwSnJ5phl239VjIgEu9W80qCQ8qMeD+1Q4dAabmKR2PAGKGXQrgD0MnOv/0/5Drw15RkfST5rwFdpjx5i0h45+J5EUx7LoelwykKEbNGMPugtbuxXUYdry5JRZpEzSouy1tclBjziBVKLX75f8q/t/v/b1oUGFRld4GPwQYs5ufI6vThQ/Y1cMO54P9vK6KU2/jtMJGPj8GitnDjsfOQXJYwI0nHiMJNtpyzubTPd77jHs9zN66wvSDL36dVWGmMwF5Q9q1vt9j0LOse+oDORn7CTDsVrXxf/9IitcWL0CGmW8pT93ERp/ZJtFBAqD6lP0Mu8eVxALA7/7VH8WsLPAbP/YyPvh84JUkHnYdDPcHBfnZVokesws+8z2hE7Ek1h93YrmSYfCf02H2w80+wM5JyJKS2CNk2DEb8he//278j2XtS7XV19zftZ4ktkOJHiaRZs3XnveUgFsjhvBeT4Q8SOmgPPQ4KdX4Xtn3wIDdTgWcdKZ0XnkgwC5g2PE9WYcHtEoS26lQPkB52CmFEpewqvXhA++fFDijQWveH1e8ZyrrNElFSWKPDrATSewGs171trSOvHHhxtQnGbBrHE7hld53NpcJSWyGYbdWgN3QA5v7/r/vY70F9Z67K2cDhB7vuXvAZ7LXwy5UJfrEApHEUijMmclJYoN7XI//jA94dCj8GDZVY/VYq3c/xM1mWRgxraw42ED7MyUlsSkPO/YbCTzsmGG38i/qc2cLAFbHfWeVaGxS5aXSMAhX4NG2xeWOJbEBw65yKbFND9QArpT0Soyj1QlfiR4dSuzaHidzK9nxEkYD1LYqRiSx1QwN+dvNPcDOpxBzDxmdvCggpe0GMdc+ag87DQ5dBxgybqF4kSi6wrALHkcvCsnN1nVSYutgYw0ojyYrozLGiCRSPEYmpAbtq1r7iMHfbMukH7LlUhWCQaHv3dMsiQXQCcNuBLDTDLvAw65OAHYrbDD76f8B+P5/Flg9g6vFHwfwGKETnQ+0cXlhGAA2wrBLh05Ug7+hOQh0UKfEXuBJq8aPeNhZwG5RFTCJsT6rCjm8AODusSD17mReAi17ova4v27QtARITU2SPsaqAyZKKv2Q11k+HWcJ8sAedocz7CLWG72OpdmNBkFUCV+6rh9wSZJYDdjN+HfbeMMnTJEi75eXrcK3RAgZds2WfH/MTNInU1K7jSSIFh74tG06zyMqmTR+hMUHXcx4rfoNTmEZAJfFqdfAzuEYZjzONt1jMuz4MxaGXXxfG5p77iwK/PZv/XL5OXvFrYfpPdC1wBt1WOp72PE9QcBJb/8vm7QgUMx/zDxg9zQx7GrxTV0mLUSkUpJYYdg9pocd/f38ugx3AN/yFS/iJ37vt6TT5Ol9zbFDz+CIob3UQQy7MQ87dQ2C9WAfw47v8UdjbDP1PtBu0PSDksT6HnbA8QB2/8lv/lr8qf/z0/hn/6EPpH9hfgZcvGq/PlGAnamAwWfY7dre98hW6zFfez5sBDTDju91+gwlKDEB2Kk+u0Insn9US8d25jCGrhegpglsASxg5zP1XZBEMIaF9FJ5+yNAM+xiCx5ew50ktktiAvrAezPUgAGqlub7ap70x/MksdUBbK6bUMKw2wgLXB98vfHIjanP36fAkBzDrprb3nugzzoH2O1Uz99unZUT19WbPvZyoCT25TtL9KwqMj3OFgfsB/ex+SKSiO9hLApQlsROZdjp8Z8hPWhAdFusMH+bFBNPNHSCv44YdsnQiZT/mmbY0YdKwImg6wLY+Qy7Z5TB7pfcTYAiqUqEFXTsYUeL0nJGvzNowM6+ph15ClymmC/6hI+85vhmasOThwDMqKtCQLk4dGKBrTDs1MIZ0KuFYReaG6hB3fRu4aiOWhKrmtZrMezcQvGP/6L3AgA++vzS/zcqHdKQ9LDLNVNTUmLV6ca8dDIqHi/CsIsksdcHWysFDAK+N4+ASGGARKpCQ3s5BWd2T+Zk4imptrYnsCwDS5VeHHoCqPg00zPwVQv1yc/8D/ZnV29itbEpTatre9jlJLF+6ASfQC0Dhp0D7PwG3LGFD5HEdsJMabrB99MRwM42Y8tZmZRz1mXhyTck5Yk3vtrzsXCneg+uGmHYFU8zYBeYRes1REoYdnQ6HqTEJmV4mcp62FEzuMBWsS3ieaBKsObavhdJrHy+cB5oKUmseDGVDNgdwrCj9TNgHMrrYcCumI8CdrK5rwoUhQvJiBh2mYTlY6vnz8jPTwWOnfQE2JlT28+VLI1uBMQ0A0tiDXoV5HBwEid/xjRnpNlo9jH/tV/9YXzlS853ajHYzc7lAQy7a/mZqd4rmRLLTCfq/bh/djLP/HtKAXbvUXKjZ1aF//tHUszEEXlwvYjnNV2JecuFTqQ87ALrGSBrNZLdDB9YSbAOkIPbORo5oGoLYt2lPOzCQ+Gsh507hBiTxLoD4fQYOSPywqMDGHbtSOgEcDyA3QeeO8W//m1fnjfJ1/tRBar0BLJ1QeiEgJiAd19zb3/ledjRNQrvdSWJjRl27jFrtDhhtnm9FJCGA4D6Aeh2lBhL8zfvZd+80Aw7+x52wrDLAXYF+sFn2I152O06Io1ob0ZhU8XqJgDYDsyw4wMa5WGn97zqs+iOjWHH+wCzwQmnZBMAud51uFTeua8ReLfJMeyMcXvPnWbYsYcd/ZtSeWF9n/8YOCNfxq2zqQFwMGD3/udO0BLsVJsD733GjExm/gy9PUNJLDPsSmbYKcBuGCZ42G3zkljF5Nwd4IV7aD0RwE7fSFVhnCxixMPOU5qMhU4g8EdiSubitvdaeoWq35rKsBuRxPIJh0hi2YzbGFTGB+x4ofNOptR7WVXMXrK/14UnD8GpYF0Y8amLIoqrOXaD/beZPqUJmroqddqgngO9Zdg9FZJY73O8BpNLLYRf857b+Mv/91+G/+g3fiX9W55hx5tbT86Ya6BHPewCryn4EgjewApjKJLEPkZKbCiHVIETwhYVht2IJDaXEiunHYeb2B9TNbVd+G6NAHaVB9g5+QDgvAQBKEnsBtWjz8iPX959AsDjSGLTn0HIsGPAbtEHDDvDgF0QOkFjZhLooMB1PzVXgc8E2BkCaBZ1mWSTzsqAYceADt0P3v1iHGB372onoRNHHbazr0ImyqgktoNBHzHszAEAex6wIwAYOyz5pD9xcCF+mvr0vRtwxZJY5a8yKonlg40i75eXrdJtbgEXqMLV0samNTPZuG9HGXZ23IkEMmD5OA+74wbsXrxlr/Ea7Dd4hdVgN1OPQAeozCAyjXx+DBS3KLHreiXpOZRhR+NUQPsESMuN/uB/BnMCxq766XPB4zHsxiWxlx2HtrEkdmRTNOJh91UvO1DyztK3ajmWcgw7lRI+llov10oz7EYAO57f9AFrxmrEfeZvE+ip7g9D740ZTx44kvNJ3iOJrU0udCKQxD4phl1nJbHiYXfEoRN762u/24Zl/bo/4P1YQieUncy27VFrwE6NVfYCvVSSWLlGkSTW9ZBZJRUsw26l113ag5i+kdfB6xoHTnyIEo3futzGDLs+YQUEOABxKEcYdrElFu+jCr6v+j45lvUayVYoFTPAlCTWuxaqz+iOjWHHklhssBKGnV1LtRwWAN68tOD46KGC9qkLGXYJH3UHYN0GFhSQwwdiXPt85cK3VJX4nl9n99bzIu7dRmsfOBiSZQKmNO9z1oV9L7dx4fYsuws3H44y7HKSWAfYFf3IPvkx64kAdmGCjgB25DuR9rDTDLu8JJYZYLJg8YChTR3X131JcJGnlDQ7jQPshhKPNi0utvaDWQYedgAcYEfJZrzQLfVpqwfY0Uunm0lvMqyHnY8Ep1NiFcOOALv5WOhESnoMQPuotF3/dEhiE0zJgxrTwHfuIy+e4c4ifSItHnZ9n05L0gEYusZSYkPpGnwPH26yXIrXk5PEeiwn9Vxzr0GMAcWowiY3K4k9rg3D1GoqOx+dYSLDTjF6Afg+SAzYYYPZo8/Kj5ftffv/J+xhF4K2m5I8xzIMu5nxpYZhEthoKTarlxKbCJ0wO7v5XlVw86Aa63VVYEBhUygBd/pXzdD3gxykrOal3McFety/atBQ6AR72z2VlWPY6WZD3Y81OpfYxh5212DYxR52dn5bmS2W2jw+fLk8F6neoO0GYewnQ3mSDDtaj2WcHnCyzimxDCQFj98zYFfM5D5c7xKAXesDdqnUb+Dp8bBjht3FwNKaC6xae/8+ZMCOGEQL7GSzxwy7hgG7a0tiaV7YPKDvE/0Mr+UBYDcjht3FcDjD7iB5pPRejfN7bPpoE3DRU+8bSmKTDLu8JPbF8wXeRUm4L9+a+b9/JMVry0wDdqMMu7yHXVoSm/KwG2fYPY6H3WjR8y2wg6HXIJJYvbbmeswsYOcOq7YpwK6aKollD7t9gJ1OiR0Uw86OxaKwXufAUwTYfd13A7/n08DHfof34456k04Bdp4ktqg8FtlqRBIbkQFov9INpecJ537XXuQaHVaFWnfVHmRJzK2OvFl5reUwgEebNmLYiWdxxLDjw5cK3RAQU/iwt0ww7GhMlnwvakmsF/inGHb0OsuGGXZzj0wh5QF2R8qww9qlZBPY+ual/TxfOJ+jMJYg9tblLs+wU3+LnQbsRkInNOOMmXhK5QBA2exMX1e++SteAgAUw4GAXSI52Cv+Ob+m4ECCx+BVZQG7U7NxTNcLq15CvRKgVMpj2O1X8M2GxLr0hOqxVm9Jic142DHDzvO4S3rY5UMnWH4qm0HaxMkAovqNH3sZl9sWv+QDvlR2tLx0UfYDKPDmxVYW92XgYQc4EHHX0wAQhl0OsPPBEO3RU5dFzI4bC50o59j1JVDAp1UHoGc+JdYZ9jZti8IEpzfHWBpZv470Mkxf0l9HDDuSGmdTYjOS2CkMO7UhLQsDQxMxb/KcKTBPTGlz5ENKA5CAOkXWJzRTQicihl3oJ/B0M+x2BNidjjDsOJSnHxTDbmDATjPs7Nz2nLmPeuco6CsC7Pik++DKSWJDwC7DsON53nnSXMPDTjWdLCW3klgFJhFgV5If1VmtABEvdILuxaJG1TXAhq5VOfeTuwOG3f11g2pnr/9RWwHsq5BhNyKJBax0JmTYHXK/cpMYM+w4dGLrvFgSgF0dBOAAFrzbsLeYDuUJpPy6mJ2wDNIJJxXNW/z+w1TXoXFStcWoh51/0i2eZQFowButYwfsXiRg6EKSVgecbG0T/AC05klasJOEGum7SmwbBygc7BMmktgH/ve6lFetLu5TL7qfL4Zdo/weuwhIf9RVQAGUHTNjrxc6YYzBX/oXfymudh1O/+aP+r9/JJVk2I152CXAzQV9RpvR0Al1/RIHG8MwuMPMtw2wU5JY+ux3xgXRSeU+82xKLO0rotAJv1fm/vJ0D8Nuf+hEkBLL/YLqU8vCoO+GmBl2zJXwrerp8+u9lNgOt016fT1NSmLZT7sEOrgDBy/kIfF6yhrodpZhB7XuVjP7vH2DFbZ4iFORxHJC9btv28/w0baN7rdGPOzSDLsdKnR9L4ddhXG9Y8oSi+d8UTt4klg3Fo0xqAqDth9EWVEwHqAlsVpVpjzDu2qiVdZNKXrtM9PhNvnB8t6AZel3VjMMg5XEfuHBRu6nNMOO3n9z6bxeRRKbmFP58GtxyxGk+O+4+sP7xLE1a7T2Mexykliad3gMXhWnGFDAoMdtQ+Pn8nX7f0pQ9kqP/wmEII89+4TrsVYe9jwqA8kro998KpbysNsfOkEbWdPBGNXQCsPOB+yqssA/9Y3vx1e8+xYmlx44krhT4ROUuGIMsFpQs68YdgwibgNJrOctZYw0iIvSl8RKEh+/rygltoglsTT4unImDLuZ0ZLYgGGXA+y0JFYDMMfMfNKpWTlTyNG/T5y8ZyYHB3ANKi1Jn34mPFGAaR52arI0xkhTz5vGSHqdMUc+pMITLzH9LhOA3WjoROCnF/7NU+5hx1HhZ8Pl6O8xSNWrZgvwE7B4oX7W+H4Rt2EXl/NDjFp1ZbyQChMCdmmGHY/9OgTscg1cqjzATktilbcZNRFla5//rNQGzQqwo41Ty54RysPuUiV3L+pCmunCDHjrciuhE0dtBbCvQiZKCuBX92OFTiSgThJ7CGA37mG3whYLYdjF82AlhtR+mjrLLK1HqR0nPOfuRkIn5tdJiWW/J/awC5gLA13LrljsAez44CNk2Pm/y2/12AG7Z05m+OUfeQ5rzMVUern+AgDgfs+yG/IyNDv5/EznDi52XX99UCRcV1Igrazz/mfA0tPLbjpIeK0AAnWIlWbY1RiGAQ9bGoO8dsq8fVjoBAA8czq3Xnb7DLtvaLEflQB22sMuZdGRkA/LfZpgwrpDe/VYCb9UzUw7mP05tRRgx599k2LYZUMnMgwUpVbyJbGBd2Ko4AiK+45d26cTd+V9ZFJi1dqd3Z88ZdUVDNjZ8dWTlU7YQ3HxHvJCAXZyjUwASHBQFMponQLgPnfTxlYUMz8krSWGHdsCvHTbztUXmmHHh1U5RYXy1GsVGFvtCZ0UVn+p9+Oxhx3g9iscbmQ8SWzCt/3sBflyvXwRR1WKlPScuW+/qBXzERZEf/7c3lc/96br15PeqkwWadZuPzrz12aPYcf99PzM4S0hw24sEClXMj8NlpEytRKsS6/CeTEgKAirdzDYsed4T++HGXY67ZlLj/8Rht36w98OAPivu2/GcMj7OqAeTxIrDDv1gMZJYpkaqJvRSjGUpEY87Er0/mY2RIYfpxLMrA6F3Ay3ljVKmUQSgF3HDDumkqcXSvGwoyaPN0XyvlKhEwiAHz7dwExOFzwkN7iGST2/fs9dg7ZRC/4xM5/05zhm0JyrVNObZdg5Y9Nkwl8RjxcAE1Ni/RNjOYWnJstJFmicJRrLQ8uxnPzQCa8pldCJMYZdAMiFQRVPuSR2UzJ9Pc+wA9xc2bcswbc/8MZQaowAuItHmFVFejF+9Arw6k+Ov8gMmM3PzX5al8Swm3cBw84ww87/rKUxO0QS23d+4IkGn5lh121QosNZpQ501Pjh+yOSxJazOLlbMexeebCR0Im6PuJ5b1/JySAx01ISeiWdmaEVxpcw7A5gIGZTYqlRvGUuZe1MAnY8HoJmnvsJ+wP7XkY97Gj9Xowk0maLxlchoRPB+knP3xUuJTYltRMvmYo97NIMuzZlq3CEZYzBH/ltX4//7Xf9QzDU3C+uLGB3r6fNgGbY8VzBsi6UHhBwuIfdYvx7IM2wGwaUJH++bKc/J4O0y0MCCFSfkfSwq+bYtm68F5MYdvnQCa9yYM4NrzTDbsSiI8Wwq9W1DisFfukAJCr9t2+fhx3dH6ZBQWAahwCkD4WnSmJ5L5UPndi1vczbJxnLjVPF7B/1sfNSYvvkwUnWsucpq56ufU9jiq+xSGKDXozZjVcKXM6GTijf9eR15P0kOgXY0VxMbKtbFYFsOx+we/ctAuy2rXe/9SpsL/aws8/RUEqseNxrS6zEvnQXMezSKbGA268wKcjIIe3cI1NI3f5S+XK7eheOqspKgLTnDLHdZgzY2c/tbFHjOQpC+cTrdo85KzN7BJ0Em0uJ1R523E/Pz60/IxAz7Lpr7Ov0GpTwXs3WvjUstAoIbJp47A3DgO3sNgDgHMywI8DuJAXY8fhfq/UlBuzMt/8n+Gd2/w/8u81vwsP128OyuzZgNwyDgKOaYVcWRiQsMzpNLxMMu3YfYEfNVYXOBw8yDLtrlV74hGHnBsPd1cztsBX7ykliKSVWpxEmHn8pDDtKie0C084geaQqDFpOiQ0MFLeoBMwT83d+D8FjAI4FGb3nvkWnPUCOTCrhledht/N/NqVSjXxmcvAYdqnNVlYSyx52KYYdI/hr78QhNHF3wDCP28cH7Oocw07fc1MYdiHb74ssdGJLgN3pRIbd0HNzQww73fzo2HRVd8yjPLvu+74Z+C9+CfD6388/eeZ0KGLYGbt4z7uMh10gcRFPk4NCJzrZhLRe6MTcAyxPsMEJp2EHm3Aeo8xC0JLYKLlb+fh84vVLCRWov6g87DKngyV7zrbyWRbEQioOOPhwHnZBE0Zz3h2o09mEJFYAWJ0S2w1+EjBt0jkldszDbgbFyplaKoQDSICPNE77cq4Au7HQCfs65doEjycSZHPcgB1gAfsPPn8KQ4D77PLzAIC3OvbJ4bRgx7DTmzwL2F2TYReugSkmt4ROJMK6AFy004GYdUpVsa80wy6TErttnARcALtJHnZ7Nj4HmoPflBKD+17J+UcBuxTDjiSxydCJwLoDUAehbgzxnGbMxDT06xRtzufKw44lsd5zZhl24x52Ffps6MSlYnTlGHZlYQRQGgfsdErsEPUL/FgA4lC8p6wGYdjR/o0ObJytiH9Pc79ymWDYmSgl1u1Zk9Ji6sVnaJ0HWsCwOy/tGOop/ZwPC95FktgLTxK79fxlYw87+3p2BNilrFJGPez48FQp3sL5iv+eSSsC2JW1C0/T1+LWS/Ll5sR9fTRFvfC7zFv2+7llhvH9dzqvxD/2k6QMPM1Z5rAkdneh9qMhYKdSYvnazk6dJDZi2PE++Rr7beAwWexUD7soJZYZdm7OEYbdQO/n0av2/2MMu53aDyXW4sXJLfxw/UuwwRxvXL49PnbXBuyipFN+QI9hN1USO+ZhFwB24mHnh05cqxKS2E4BdrdXdZJ9xZu9DY2fq3BzGDz+MpDEigeANK1BSmxKEkvNyRY1GgLzCr1gB9ewmMCw65o2/vkxlqZSX0d6qYzwpTJadR6/TdeDL23aEDgjiU2xpwSIGLy/0xvgbduJNFY2CSkT+QOr1D5iQNr0eyyVjSuMu9Yg3zCMnkw8DbXm0In+0ejv8VTYc7MlHnbqes/PsTPqOpGvwm1c4nyZWIyv3gLuf8p+/ff+x/QT9507dMh52NF43hjbzFXDzjvF54OZmv1XSj90opqykTFuUdVrwdAq9l81l/tohQ1OyrQXGW/6twUbzt+n35spm4LSe94CPT7xxqUEBz3dKbFKaj8EoKguGg+V6VyTfQ1JbD4l1r6Ou+wXUtTJ9cYxLt2aZTfsRtLruKEc87Bjw24B7K4tiR1ihh2tw105FyAgGTohHnbjKbHtIffOsRQ198wSeoMBO8WwY8BVJx1u205JYg/1sAvGdOozF3pzArTAYQw77vmWh0hilR3JXIPbau3ctJ0DqJuQYXe4JFaKN1ZH1ufJ/eEBdr4JvleJazWaEhv2a8OQZtg1Dkg2bxe4ru4Plmlvkwy7TI+ZBexoTos87Nz75AOuWVWMhke5pNgRHzvVL+YksdzvPPUMO+rjuL/h6y/BXcH9yGCpTonlNWiQfUrv9dQdypiYAXgHcVHYE/3/tCSrpR0DdjVWsxJ3VhRE4oVObLz1MMewa4eSLINiQkOZUNi5/bCayxIedvqxOCVW1AM5D7u773fPs3wWR1dETHqRAbuFtfxKSWI/8YYlM+U8KEUSe/UmALpGIcNO+QQLm86TxIYedo8R8ghE9hSjlWFdSkWSWL/f1WSx9cxmHdzuKFiD90+33xs/rvjjqr1dZh195tTeN29evD1JsdcH7NRNUQQI+ibwsCu1hn2yh52SxOqJ4Uky7BJSykJRO++ezJLsK5b1bPYy7OzfLisfDGnE+4x374EktkxJYmnCH2r3b0kJp8+wi06wVOgEe9i1KOzR4bFWKiX2IIru9NAJ8VBQm1JfEpuQqAzDHkmsYpuoCVNLOa5UapRIFlIm8gdWFaQ2h1Iu+0uBvDVVStYDwJfR6mvxlEpiH5V3AADn/f3R3+NGdZDQCfu9x04zBg9LxbJ7/ssAAEuzwa1lYqH4wt92X7/5s+kn1h49kSTW/r8Xhp0aT+wRAjvPGwNnIi2S2AOM89X9oa0OhnCTxJH2ZoMVx79nGHZbNrpf35fHcAynmGFn/79n8X8aiu/FgWR3XQbAKp3FAjfZLBM0BwTaOBAiHTpx24ywjKE87BSgIunVDGAzw07kt2p9+//9F8Cf/i1orizT0snoDgmdcOOhRhd5AxmaA4dy7oCAhJ/TVtLaiGGXkQuLD3DCsPxoK7Ar+UJL3zODyOycJFa8PKvHlMSGgF3iM+deTnvVqjXt0SGAHUtiD0nslpTY1r9X1Ny3aTo58DbMIBvbqEwG7I7bw67SHnZjB4gJSxTuZdIpsa4ftv9vIJtZxczdXhdIPqRoXl6YBhUlFzMw4as49oVOpIkDNTr/wEABxbyHyW72qRxgN4Vht0HTDZiLNYFbS0JW/9NaA31W3N/wOFqW6cNTAewSKbFG3/9956nCkgy7ipVuDRY6dAKQNfiM1Av9zjHszhe1sLR2XY+mcP2/BuyqcM0KJLFtYm2rEvt/XhNL9hPumuxYFknsEPTB9dI/AOZ979mL+Lee/X34tu2/jbI8rrkPgKyl7zJv2u8jwK7G82e+JDbHkJW+iwMW9M+0yotLe9jxmp4LnbiOZ7z++ym1jyUeHmQklIuA7bku5pZJd7d/w/7OvZ+z/7/zpfHj8nzmAXbpvvhZkie/eXHDGHa6j/Ukscadhs8RM+ySOvPUB6E2WD7DbgT4OLR0QAC9hnrmGr3bqxkio+K+R8GAXUcn7MRUi7wfaKAsCh8McRKygGEngJ1Byww7kcTaBXwz1EIH9jbhudCJkIGgGryeALseRziR6fKA12swuQSU3R86wYuPPqlMS2LVRNRu4JrAxGa1nIF9pHQTyk39pumckXpVKGbmE5DEitG7zwL1JbFL93wpc1v9Wvi6a4adPgl+SiWxD4vbAICz7v7o74mPQhg6EZxqX1YKsHvxqwAAJ9imJbF8OgQAj76QfmL9GeyRxO6GSph/Hg0cdn6vlcSl7wfHNJ0COiQ87ADEMiRiUJ9ijVWGYccsqy2HTnAMfTWTzZmYwhsfsKvYS+2pBuwUMDfWbJTc2LcRw+6QeTTPsAvmvIQcFkinxMqYNH5DKR52/Fxf+NvA//J7gL/3l/D+ez8IAMJSuQ7DDgAqtFFKLMsUh3IhYE2SYdf6gLELGfB/1xlzH/GBWVgsn6F6rTuzQLCXEuvbgTTsYceSsbfDwy4VOkHP3w8GV8108GAdMninlE6J1feKMOVrbBrl2SiA3ZgkNp18G9U+dsINLWbfpCWxYww77WFHfVTbxWbgck0He420zLbSgN01geRDSq1vKwp84r2Udz9kGXaZz5i+L8wgYUv2751kLPJHztQZ9R+jDDstodQMO3U9U8DN01gsieUDWt4DnjBgF/TDfP0vd62MVTk0KgOgg0MehpyHHY0d0yrAzrcnOCGGXU8KoO0ww9miwokin6x7x2bTktiYYccAYoW275NedylLLL4mFfd+fef2GQFgV4YMO65q6a2h+nr8eP1V+PHh/dP605tWi9sAgJciwI497Co8R5JYVpWcTQXs6hNHVuF/07ZMmhwl/x54dHfXOAjyJLEHMOwOlcQGNk0O0AUezSxgd6dlwI72UCnAjvtV3UNn1lFm2L1xecMYdvrk2ZPEFgYbQr8ZsCuCfwemh05U6PzEyicZOqH9P2jgLeZu0Xz5zjJm2Klmb9vb9yIMu/BGocdf0EMIw459OYKmVUtidxHDzg6+9VAp9h0Nir5Xcjeiv08JnWg51ee4mriotNnkdbzSkqET4x52+rTWAx5SzdROTXIpoNmY5AnHQpmaX4b+dcATksT64yTpITRTG25NmdYVhU6oprrPg0VPSz0s7EJ60t4fTT7iw41BJLGJ0AkAG/JYAAC85xsAACuzwXmKYcdAVfi1rhHQNAyd6ABccTJnANgVhfFCJ/T8MknWp+Tn+j0PoQci3Scrs8Vqj4edbHBZElvOHMOOxzE1JiVJYQukG8KnqjTAuXmQ/jngJLHo7Lrc946JeADDLhs6EQA4OcCuSvy9hOEwwy4A7OR3lXfjM+ufs6+9vw7Dzt0bNTrPTw9wDLu+nCvmTpj8OgjQx3N47tpIcNExM9zDok0FYIGwezjDpu3THnYsiR0qbJXx/eOnxKY87BLglmKFrFOhBJliwO4whp32sNOhE24+3TSdY4/w5mk0dOJAD7sjA+yEfaPZskqiF1UqdII+o2FIzE0aBO12PgioxpT0RYeEjBxaan076e0+h/dSHtggn/lESaxiDTccNOdJf52H3ckeT0Zm2D2cGDrRtzuUhs3OYw+7JDPsKaqB2GmOYUfzRunv17j4+g+DC7aJPOwA6CTVNuth5w7i5pEk1vb0pxRGMZD8foMZzpc1ysIIAeWK/dQVw64sTCwNl7m0zHvYJfb/vMaXldqHZdhUdeBh5/5h4eEM+nokwwGPpU6e8b9fWiUPA+xaEsuV9bDjfRz7tem9KLOJB2XRoEMnUqEUgCIKXZdh9wRDJ0KyTLAndWOvF4bdnfZ1ayl08Yr93Wc+ED8u94/cQ1eLrCKRGXavP0ysTU+grr36LOsSf/Kf/Ab88X/iF3mAWqk87MYZdmrhTCGnShI70zR0RngzspqDKiGJXS3c4H//c6fqVJZerwJ11q19LxIGEHnY2e8XNDnz6TqzArIpsWXhGHZC79SAXfBvGmhiZmKwCXf/7t5zT4t3d2RGxFGVqoHJJGGOVurkPSeJFcBOM+y031uCYSfR4/P8ZJMwUtZmyZepE9AnIIl1rBafBepJPyq1wW4ygF0IHsrmZBewu55Oht0DAuxKdA44SlTIsGOwPDyt/NztjwEAehTAcx8BYAMYzlOL8STAju4LUwLBSWOY2NZ1Ay5ZZhpQ4D2GXTnz5vFpoRNKEqsPYsJADJLEnmKNpQB2aQ+7NbOvrugUslo4aXfAsKuI6Sopbcc+942VMQ4A1YBdCG6IZIoYZWojaK7BsAt92jSAY58oJ4mNGXb8dVOopC5AGFrCsHv4efmbFzafBDAo36s0QJisQgN2bbQRKuQx5wLWhFI7vTbwHM5Mz/DaHPVmIlenL8iX93CKHoW9JtrDrizIh8ne2y1KbHXoxCHecMBjMOwovREVNgmmZK5YEruqr+Hd04ehE35KrPg1sqetyI6ehCT2yAA7NqSXHnnuwNguwWJIbOq0vUcki9Ubza5x/Vc59zZlzsPubVwvyhoDKS1OKW2e/QzToRM5SWyaOAAAHXvFBj0Z95f7JbHMsJsgidU2DPrnQNoa6WmsIHxtt0cSu6xLGXZMBGkFsNOS2FbW6TbnYVdx6ESDxZBh2BUM2GlJLHmvE3jIoLGVONPeNXU4K36knBKb8rCL9/98TWodOpHxsOO/34YMu3rlPY/e9x41i30V+O5RL3WpQo84JZYr72FHJKeHn6PHUqSAOkHK0JJYAewCht11JLHGpAOg9tU+lngkifVVO9rX/8HsRQDAs83ngVd/wv7e7S+Je1XA9RK8FxrZb79wbv/t1Yc3TBJblQV+6YeexTd9+DkP2S6LGLBLpcR6QFLSw46kYqYT6RMAh/AekvyWq0JNEDTZnJ+45v4Dz524gcWvUS2Sm85n2EWnrfR+5gXJemiyi4ymQ611adCSJG3oG8ugo4Xvqksx7DRgRww7s59hx1Hj3bFLYvWNei1NfeKUOtP8MEigN2XeOpDysGOG3WwEZBbTTw3YOQbHhXiMBCfCQJpNMLHCk85d6iS5KNymN2BcZV+Llq3w+DblcXsljtS6r/BwCE6wEhUDdonQCQB/5z3fjX+n+c34k+/7XlloV5jAsLvaA9glABhhPTPDbhhwNSSSkWCbHmeY7DPspnnYuQ1mSZ543usTSSx52GGDhYklNYBi2A0spaDXNTuJUjrlIIPDJr4YPOwAZZjrEnSje1DMqTvbZKtNVlFPn0d5M3tdhp1LDXZ/z1+3LHtufA87CZ1QUvBn2lecbxJwGMOuKLyE+jDUoujcIQnPz+uAYecBdtU0ht1TFTqhktbuwW4KLGBHDDtDDDsFGjSosOv6yPtvck0B7MJeDnAbaVSWBTixHMPugNcpvVfrJyqLnUSNbes87ADYzdMkht3TCdgJ+0azZccYdolrVZdGerQoeKIMAbv0Iei1mZ+HlDEyN96CXXcZLPFDJ5wXolcTADtW1fietjMHAEz2sBuTxLrD50EzcnToxBcNYKcOrqE87Ip0CExRGKxoXWEQ1THs1O8Ojpk7hWE3E8COxjWNsxUx7Hhd3Qwz6TF5bltrhh3LXFPyUmVv0CqWuc+wo9AJdSi3iySximEXEByEWR962FUL73meHoZdGrBbq6DL5878/ibrYcdgFAN2cwXYaVsmJmVoNWNifwpAzbcHritTmeG69nnY8b00dMnwID3nvLl8HwDgbvMK8MkfsL/34i9IP+6UQCuqFwmweyVg2A3DgB/7ubfwE59/EKk2DqknvvpowG5BTXOSYae9YUZSYgEnKcUwOPT3kFPzXPHzdc4Y/wMv3MJ3fO1L+JUffR4feeEs4WEXA3aanuo/PgF2wrDj0Ak+pcinxHo+dZ1Da6/6GrshBOy03I2kxKUzWPRKp8S2zLA7riYuKi0RGAEmsiWN/PTQCW786jKghqckscyw4wjtVIkkVgF2LLlqe3UCqhl2G/9vr1GySQ497MKksFTst67wuuuTxTEPnqekdm2Pzww2zVUMTBPF89/AzBJOiQ2aieV8hj/SfRv+r8U3CHV9ZjrcTg1rDdhtH8SNPBBLllXJIQrNFX2vGXYpSaxjvOnGK9nEhRV4LvH7Nq2/uArDzqyxFMAuzbAT+a78w0ruT2FE0D1efDF52AFpOn9YzOw2rZ0H1Nx1SOhE1sOuKLEr1dxHso7opSZSYpsMwy4KnVCA3a3+PlZQDdOhfrdyPbooJbaktXioF5IQGgJ2krRdFgKGOw87/9rwxqJ4mg4yzl6ULz9vLNsuZNjNqsIDDcTDTl27gyo8wE2GTvCpvjbeV5LYQxh2nBK7R0LoFc+9/ZgktscOFXrZPG32eNg93aETfP8X+hqMedglrpUxJp8UW5Sq/1MMu2D8XBtIPrSI6fKMsfP11UCbzSTDLudhFxIH3LVomwRgV83zKqGgRBK7nhI6sYWh5+lN6TFEk9ZIT2PRPW8638NukZHEAg40ZRscWSPKEgKqKFCrRSlsttRz12ixGJjosvL+v+LeqnUpsfwZM3vYedhtVKJrYr3iuXRghl3g1Y60FFr2w3I4OGSBoKyHXb30nqfzkuaPGLALGXbUO10pS4ZFXXphdC+cZw4oGbDje18z7IzxfewAn2FX5Rh21zz4Ngliy77KsC6l9M+bdcImzCUUX5S38MpAfehf+4/t/7/0G9OPG/bMI2SxF24xw84H7HZdj+/8L38Y3/oH/5ocjlynnvjqUxQG24EBux2AIcmw8ybq1AmiR2mnL/QC/SQYdgIqOD+Aqprh9/9jX4Pv+x2/0LJeQt8ThQiv6cus/0ORDp3gJqQKfFx4YM2UJNYMvQeSXHVlnCCrUep9HnZaEksGtEfPsFPpa9dC/HVcOlfWw46DRuy/R4uAasqlpjDsEqfGC2VU7kyB9aT0+IBdlBIrZv0hYJcxHeUKUz5ToRNPqX8dYEGKnxtICvbGTwM/90NJNqKMl4BhF4ZOcNN2tes8wOFunZABcToql5Y/cskcE98XEjqhGHZr8bALJLGBhx37cRrje5Vmy4SAXRig4jPsVtioVNogdKLiE+BgXNUrJYktvOcthg7f/OUv4CPPUwNyZBvYg4vnhg0x7FIAHANULAFVRvzVAanO8xxgB2BXKc/ZDGDnAnDc33OfIIBdGDrBv3v5pvzN7eEBTo062Dv0M+akdbRogvWzJEmsqRaeZYEuAYvVHOoYdqHfXSwbOvpSktjPFC8BICmi8rCblcZbI1tU2LZdmuE9peqVA16AaK4AEB0WAHCskKFKhxJkijdMq0Oku+owj9+fJ4kt53RgZtDo4AnpaRLPlWL0p+rIQyeKXvUXKtQgqgwbUfsBR6WTYjMMu5+XlFhA1vrnzX0AwAUBdj7DLhc6kUuJLURq24cJiqYAitKN5z0ANIdeXWynhE5sZF3vC3/d+WJh2LGlhKF1QySxRVoSCzhJIyu3ZI0ojQ/QK8BulGFnGswGWg+5l6S5eGloPeNQQ0qJBZxi7EoAu60C7IL5Wdkb2NCJIVaSqa+9lFhm2Gk2P9+Hxn8euY8TgJ1eQvX16AU4PMI1NvSwu/UyABV6RNfjS59xe8uXbmfITJpRBySUD8EeNCmJzXnYXZNhd5Aklue3TG+gD1n0vqXi0An7bdcP6PsBP9Z/hB63AWCAD3/L/scFRsliDJaGgN2VSn0+KKgqqCfPsDNOX16YATO0acDOk8QmThDVAFiW9Lva8P5JMOz0Qp0DejIMu24wIAwlDaaov2VJLLOXeENSB5t3fv/zqvCDIHjwmQLrTiXIelH0kN8BYl8q954d2DfI6ddxNXFRaWnzdcChVNObYdixd9J6xxut4BYqE83UFN/FcLIEvFP4y3CMDcMT8XMMU5uzjelsD2AnDCl6/xI6MXJvPUW163p8aiBmyfd/D/DHfi3wR35lFEDhJLHc3FjPkhD4FVnErgXKWk4U71QTALuUj90I81SaZzpI6PoBlxlJbKkZduXMJYFNTeAKGCHcwJnwvmVJrNlgyWypQErJIMhVCNjNVkoSS+NYbWL+8Hd/DF//3lv+63lai+cVBnFTQIY6iW+VJLZBdVCymjDsEpT/baWaw+Xt9Eut8qfvbeGH8syEjUfPxZJfWGnvu/EWvagD2XWAAjDj0AmW5hXVQnnYhYBd4J+IPMOOH/4oT/9z9fyXyZevVe8CEDPsrCTWrbchw+5gYMQYSZYGkGHYBX7EgAAKO1QYBrf+7atrpcSWbu7juWvb9t7ayWOnKRRgJ2DbF2HoRMuAnWJZl+rahJU5aOXwoYhhB/gAmBwcBQy7n4/QCQCG1r0XGLAjprvvYZdhVY5Ipwf63LuQYUfX8mrrJHZjxWAS73mSpRmQbRqwCw8Jn9YylQrEg9sDLtiXN/FZ8WcgDDstLdV7FXXomwQ+KxU6EXnY2f8vybbKA+xYEss9aE/jrVmjbYO9K1enD1/KCR52CrBjAkutxgjfh8F8xdfmAsH+v1rCGJO03GIywlGusXffL1/uFs9KDxwC7O9/zh2IvnQng40sQsAu4y3MezxJiT13fWSosOoS2M2UEv/+QwC7PaoYvbfRgB39nBl2bT+gGwb8sfab5SADX/tbgbvvSz9uiDWNkMVYEnvvqvHWGva8nZVFRM44pJ746lMVhefBscAurWH3UmLzoRMAsGDAjtFdUzwZeZ32F8h5n+kmLzBJ3tDku1cSyx52khKb8bCjybsojD/4GOku51g3fd7DrqjFn6hMXWf1HOga9CSJ7Y/deN0LD7nGBJJKj8uGTlDjR599RA3XIDAXgx5jm8dkSmwcOnE60589fbaPwTathNXij9FZKP2YKonlZk2MobfX+0yOrHZtj7/Rf8j/4es/Bbz1Ce9HoYddhzJ58sfhIrwxXBvytkkBds3l+PfA6MIaHqL0w5BNifVCJ6q530xOqRCwKwyAAUYzKAAVOrFxco4gGZzH6OWQl8S60Ak1nvvuaCViB5dIYu/73+sqFEDVu9CJBiXKA7zVBIRIbIq3UySxRcCag2vsOzkAsGMhkt/yGkn13iKRhDa1lFl3KInlIAtTL8SyoOkGb53ltUHL5+ZZD7sRidGx1q2XgV//nwBf+o34ofkvA0CfE61xC7PzJLGW4W8IsHsM6eFczQ8pn8SR0AnuqZL/ljLqAAEAAElEQVSATqKYYX9QSmyCYWc97Bx4wu+/Ec/G9bjNx1Rp0bECdhHDrh5n2GV6jawkVv+uDp2IGHY/T5LYYL561DFgN4Vhl/ZFAxRg12UAu4kANAN246ET6vORVO2AYSdMq+v7OR1DOYYdSWL5MEcYdvFntZSAIvuZMPhUFcYH6JWtShKwK3kdazHrQ0kss53t51N0zsNOJLEMHHbiSYWOPs+IYafY0jsKnUh52KWIJDu24Ukx7IL+TF7TEOx5aA+UAgSP2if22Y/Il50CjljCvqJ9wgefd2vfe+9mCBxhoEII4GlbpmFQKbGnbty0wf7vuuvK2+Fhp+0NGGyEu2cqtc9p+wE/NnwUf+Ij/ynwbb/f/perAxh2t5a19KavP3Lr01osNB5vv/E2SGLptJKQyzmatIZdN8JJSWwKsCPkt1o+GfN6kS+60ImYTq6+H3rHsEOJ9a5D1w+y2MUMO0rfM74ktg097BJNRlmpa8GDr5rjatcpf7vG/3t1zTT9M/2eG6HHH7+HHZtN9iqt9BqhE1NSYmnS58U0AltSgN0UJlyiCU2FTsgY00y3x2HYBUyVbGPKz5ENnQhTYnXoxDV8BY+stm2PH+y/GpeLF/1/+MyPeN/y/GcUKJJiMbE3EvsdrAmUOi8Sm5SQpp76jMZCJ6SJst+3nWbYJSSxxs1XBydwRQy7wjH2ACWJtRuXE6wxFzmHP855/rzsQ4bdiZPE8jj25vHuaDewBxfPK1fMOEvMFUoSOwxA12iG3fR1VmR+CYbdulTNYU4SW8a9Aa+VnUhi7Vj3PMCACLD7QPm6/SIAeSdVyaFZTRQ6UQ3ESKiXHttGAwERWIx8SuxT6WEHAF/324Df8ZewndnPeqsAO/Gw67n/qOV3trkDoymlJT6ptLfUwVyQ1p2UTCZKQicOkcSqg0Xfw87NzY5hp9fPwC5A11PvYdcDGMQLzUpild1GWBmWGd9/yWARfeArktjQw47H5dt8/eb+fPWIPex0j5D1sBv5jKnH78LQCXqsq4kAtAudGBlvwoB0vd8QMLuT+8CnsNgDlvs9CS+R0In4nubPgA8FPA82Lev3POzGQicaB9jx+k/9/IIYdgUB1VvMxA+NX8dF63qkbsehTyHDzu13WAHGc3naw87dhzvxsNNhOzmGHVnFIATsVvRcvlrEPtcRr7GzFT5dvgcA8Oa7vkl+HALs3/X178F3fuxl/Gu/9qN4+U5mP7hXEqtIGbtLCCFkfpYklAC4fh/9dnjYAe5+4j1QOVMkJjc2WCb9uVsfA77+nxjHC6JAq3yImTEmGTwx9UBkXz3x3Yq9KAZtMUfdbzA3O09bnvSwS52KKUaEAHZ8+vUk/OsAH1zJeXzoxa93XnctCqx3ndCWgUScsjDsQg+7TOiEev9VVaFvDQozADvajFQLXO1aNFHoRHyypumf/nt2YF8/MMPuyDet2meJgayUfCRXQs/dL4nlzyzvYZc4/TwoJdZNiHPPd8WOGQmdELZp+VjMtZDxmpUkhYakYYWSRnlNg3utTzE4suss8/WvfNOfw69/fwH8jT8K/MgfBt74+97vCcNONVupkz+e2Ne7FsMw4GqoAAPcniUaM80KaDcHA3ahjMAy7HKhE3AMu3J+OEOI77XBSStmOtGTG3uSt52YDebEagrZB8zouj+ElHUVOiEMOz2PfxECdmsC7FLBNyyJpfTfrt2hhB2bh8hIZuIrZxsi7Wl4r3a+ZnsZdn3cbLclN4x2Ll1ohhIggN329GXMLz6LD1av2inzcRh2phWPRq6axmIxcww7wIJ0fJgiLIqkh13IsDtif50JNddpqALYcUqsnbd6ugcfSxIL+ODs/5+99w6T5Cqvxk+FDpNnZ3PS7iqsEkpIKEtISGCBEBkkLZgcLMQHtuED+8NGmGCDsf0Z/zBggwGDVhImIzAmiSTxEYwtg1BCQkJpV9rVpkmdqur3R917661bt7qrOsxM97zneeaZnu6e7uquWzece95zypPJx1XfY1DYCdIwq8Iuq+dX/P2juVeUEktCJ9yi2gj0VEnsPCmZNRF2g+1hV2v4cOHBkotHt9gidEKOTfHPmeY3GT6XetilhE6odrmwCrtDvuiLXBpslkLSNvOTEu3ETxB24WeXBHTCh1vDaDlLSWxk72LJkB6t7UqllT/gJbG2EF7YSmEn5iVWuhpSpY8L251YeAM996Qktm4iPklJbCFFYSdLZaU3a4USduI4ZryoL/a1lHYFrSSWftZWHnby2I0KO83DTpGIusJOtDnZrighaAq/6Cf8/dhbUNzzK1x80h9jE8I+Uc6LZDDI6rES/uaFJzV/IV1Rp8/D6BqU2HChMBxf/wVBJJhKq0xsBZPavRWybDo5RbEGikRO6iGivlQkbpZ5l07QmdT7BOvGy3hg3xx2H0wSdktPYScvGOE5M2LVYymaZg87w+LJsuCLC7+kl8R2oCiKwVQSqxM9KQs9Dw7mSKmia1vJwVxMGopiN0V2YCp0QvewI+9dKrioS686pbAL49cToRMGU+JUU1fi9xaIwTvos13XBGK167PJ+1pBDYKm0Am9JDb8XuVOeNLDzqSwy5ISG1eQAOaS2ITCrsNrIQqdCBAEQWT6nVoSm+ZhpynsYgag8pwMbklsXe7cD08Ba48DJreEf2uJseqaJ/2IydNAeXVUPRyqNFAVMfYrigaFgFxkDAuDWiNhl05Q6Wpcr0lKrGvbUQiEWyRlD+152DkOKbEFovYjlAYjqKDoy7auEXZiEbPP066B4rC6PkupCruURL1Bg7wOpa9hU4WdIAvqka9XOx52QJKYery4PvqDpIjGDlUp7EhJrPRVtKNFIBAROpW68AATC8PZ0fC6O8x6TBxU+4RdyVASWxCbXE6xHCYmUy8yAaWwI6RTSScYBTw/5/XTZ4g+t682Wsuoh9elF1fY1Ty/M2Iks8KOetiJslyxaZnVw26unRIXJ5p70YCWgKjTZb/lKYI6Mu43B2kMtodd3QuS44MhoEsh5XMONSuJVURqI11ht2AlsXGF3SE//KyxfpgeL0XaGob8j/TO1TdY5fyypcKuJEIncpbE6vPx1FC8AYNS2AXSw04oNZsQdnr6eMx2hCqTsqbEWumEXVGUxDqkJFaGTqhN43qkjpYKu8QGrWhPITFrxT5rs9BJmiZbdJ3o86V42MkU41ndw058HmnhQYlgjyoU+xAPlLbjBu8pqAdCLEJSRnONP6XxeDnn+Ib441RFJysWimMiQVYSpEF8o6SJb2ZTZFWGU8gxzmrSB8vrSdmIURFTVIafK4jEsuIquxYhj2sMwRNRCndn428PPOwkYRd2FsN23fh4PCXWPMhKbzXpAafURx2kYsagyJU6aXhNFHaklCpU2DUib7GyGyMm6WsVrbh6SZXEysHfoDAMgyfEeyu2uIy5aqO5h5186zTCjijA5ODd/wo7E2GX4zOZ5LmtFHa1DB52ctDIlBIrdzcIYScXpQ0/GWzSJbUpDQvw/EBNTJMedq1SYrU2TBcXsv3m7dT7CJKgkAt4rNga/t7/u9jzlCxfpROaPezkpGm6Usee6aoK8omp0YCwjWUi7FqXxMpBzAuAOVUSO6c9lyrsSOhEZoVdfKAu2KQk1nYjFQwJnYjKOXSFXXh97PfTFXblVIVdfypOckMviTUR/KQkFojKpuqBm8v3hfYZOvExC3LuNp9h/P9E8iugFG6+VpIRI8BI2fbBocMAABv83eKg2gmdiDzsdOVCQZTEOlKhYFDuSA87WhKrFHba9xKVO+U/zH6AKv0ki76SVQu/Dy30qtbw1aZmeyWxNIl4Mvm40cNOVBnY+RR2cjGdq8SFetiRz+cTGw85/qoS8MZ8TIGXfM28JbH91d/VPD9umUBLYttIidVL0sPXNCnsFjclVuKAJ0gXej2YSmJ9PwpTMZ1j8T/JklihsMvYnscyKewiv1FHEi/auGOstBpAOOKaVQo72Y4kYWeYE+vkckyFHUuJjWxV9DTz8M2jkthCSkmsUth5UmFXICWxovy0FgUG+WL+n9jIk+2JfB6V/mrwsPeDcL5Jx8OiS7zpUzzslFVMi5LYgfGwQ1xUAQBz9UgklGuctCyVMgsAGNMIO6qio/519DEg7mPXrtWCJN3yeFg28ehUUCWxYk5I1qGRh10bZdJ0MzCDwg7QCbslqrBzNMJuRCPsJJEU27lOMYqVhF0idKInJbFmKX1ThV3NU14ORuZUEnaiJFZ2TrKxRCmxWsImwlIuRcwRD7vZjB52rknJqH3mwJclsX1OpNhkZ6YthZ1hIp9K2EmFXYuSWPoamTzs4qbqQBQ8MFdtqNJrVXYtS1NbdB6tQE3lG36QrnAoks7cBD1dzXGjTnkZKOwSysQVQmF38MHY89SkgfQjRsJuKPJ1emj/nCLsEqoCrx5N1Nsk7BKhE36AWRU6YfCwk6ShU1LkStuhEw71xCMkb1GGTszD9cyEt0wVfbyhXVeFYeVVZEqJpV6kqQa2gwJdYWck7MI24UrCTijsGiltMw1FwjrpxNR/j56HX/lb8YvDXpnaZ7mGuYFS2GmhE6rUsu5Hk8vCMB63w2tgNBDtth0PO7FYL8rUXIKi8PxxikItFrMtQHRMiJfExpRmBP6gK+wMJbFl5WEnNgztgnqO8nhqh7BrVRKrFglknBcLQy9HSWzd8xWR215KbD220PLrkT+bbDs+9YBtZFHYDZ6HXRAEqHt+NN5YdvgdOk0Iu9TQibiVSQw5POx6nRKr91cHvfA4YqmcptAJev5N59iO2l4QBIn5QObQCULYpZJtkuz0qnC9cL4YLHPCzhHK7JpO2BnmY3r5dtzDjvhte9EcUk8zB6DacBk1FZbUTknsfD3quwMxN0hs0BpKI+XGlWPwsAPC+SZV4hccUvIr57kpKbGx0Al3SM0NTd6IjT5X2KlgQDEXme+E/BknlQ66wo4mwUqFmvS9cwrRXLluIOxyl8QafONbIcumU8LDLkVhR4NcsoASdi0EY+smJGEXjU/d8rDrWUlsTaRcpSvsaPmhWcrtKYWddEOXCrvOSAoF4ueW2hhSFnoNEToxK8IAEv515LWi0InwubKTUkk7XvLzl1w7KomVHnZOCfOmkljFPNPQiaT5Zuzz+Q2VVNn3JbFANMGSF2ouDzvDpDdlgivPmRxMC2klsUA0KcqSEltIKuyGVfBAQ4VOJAi7Dq8FOvDWPJ9MTNM87AwKO8MEMLytnZNlQNiphdjImvD33OOxXSQ5ebFE+6rDSSZuARgrucom4p7HZlRJbGKRQne7RlaJg4mTbACMPpkStpbc5flNPOwsCwVSzpHbg0srS3Oowo4eGymJlZP+REqs+N72+xoJVZ4gCjvx3aamxPaX4iQ3soROiL5SLiL8RhQ6kWeSa1nRjq9eEjuNEVxW+0v891H/K/1QpcKOXC9yIRI4usKOGFur8o1R7Am0Usi2SmJl6EQtURIrE4udcjiBk8RShZS6JvwTEalBdcIud2hLn6FEvdqIh12RlMTKBMtqvcn4kwVDU+T2ZPJx2fcE5BxIlZ9U2GUoiaWkTznPcSqipREjtwNSNijniAFVlDYNnRhcD7vQpgNkfNDsNowKO3O/rqoVmqbENpZASmx8jJNeXTHbDOoPLM8rPf+GMd4S34cDUXbeiIsEsnoy0nUO9e8GgIcPzOP1O3+B/3xIzBkaVRT8sL+2tE2aVMueAYNdCNuq7cuSWLFuaOZhp/yLpcKO+AQbQifqcMzhHeJ6mbDIHE7O48W6QSrvXPG7gmRK7DxR2AVi/E1T2FlOQc1bq8o2iCrsCGGnKewK9PMp3+v496OsYmhJLGlbphRaVRLbj6ETAAkGDD/HvF49kgdUVTe6Nv4YTYKtiE1Q6ntn8jFPq0xshazjFkUewk6KnMh6lJK58nrJ5GEHxAM7WpbEJkMn5pcqYacalyDsylacsDN62HlmckR52MmS2IVQ2OmNIbHQE51oYGOu5ilpuNx5ikF8Htk5RyWxWhlZSklsUmFXxqwpdMJw0aR6RBhKYoN+L4kFDFLYHOSQaee9lYedwZ8hdhxAdH7ypMTWDQq7moeZSl3c112Fna6KSVU4qJRYA2FHd3rp55cLDEk493lJ7J7pKq669hd49b/+PLGjqUpi5fc2LBaPgQ9UDqjnKX7UjwyDTVJ927ZUWey9e2ZQhTQh1xR2atFiRSayJoWd6mNah054Pk2J1TzsHKKwc0sR4ZC1pk8bqAuOFS3IqKpBeFCNW7NwG+brR5YJHYRGypQnSEqsLIkl/i+xlNgB2KxoBtWvNPHRdOKEnacIO3OCcTOUUko/E9eHAcaUWNG+fJ2wc8nGibIcGMHuhpZ8NjyF3JAlsVYjkRI7DLHAKYcL67LBG6uitz1oxBVBv/vrtEIsDbUgS2LrsZJYOcZWGl5nHnbHPSu6bZpUd6kkVk6+bSvncRIlFyW3A0KeRAo74tPWiBR4CSilQguisQ83KOS1V7SikCMALTzszBtTJYMSVkERqbXou04NnejxeCE33QBUi5PwxBooNkeg51Bt2jfMjwtYxKdUTyYGIo+lVgvKkmurflr3sbv2J7/Dv/9qN157w+3hHY0KSn7UN1MsH4Vd+L1LhV3kYZeuTEp42BlTYqOSWC9oXhI7CUrYDcV+u8K7riitHorDai4nFVxztUZSYaf3e6Q9yTWSSoklbZeOcw0/iM0LLIsoCOVGtFbxJgllVXECxOZwsmKI8gsNP2Wt1ifQgwErBgV/Zpz6cmDTk4Bn/X/JasKYh50siaWloIak2Ga+mc2Q1XuVImvoBBCtOQlXRDcJvE4Uds2srdCiJLbQ2fjb9dE7UtgJDzvLrLCLEUlpJbGCT4wUdubdr7ZBCTtJ2iRCJ6zwscDXPOwczNe9pLcYhS0HSamw0zzslMIuqU4qFRw0Aif07ySJJ3NVD5ZU3jXxsHO1Rbh+TPDrgEyJ7aNJXCo6IexMk96UCa6cZKd62NkOwpMWRJMppbDLQNgRxZQss56tNpJKzkZ3CDvLslBwLNS9QKT0pXnYNQmdoAEbA6ywe9837sQ3bgu9sW7fdQgnbppUjymFnbymnUJIOlUOArN7FXGgFHae3B11kypNgYmhAg7O13HPYzM4R5XEaqoCpbQsR5PipiWxyXOQMAKOpcRqJbGWFVM8NPQAnVbQS2JtCxYpsVUQJW3jmENQN18/KpU0NoxZgGUpL6zYLqTtAJ7ow/tQcdIW9D7HGDohvG4EYSfDiOpwMZxzklt0baBqIOwacpOqGWEnPeySJbGBlqIdI4LUhsgQHqxpJbDDq5AbNHSCzFMCr4EhSyxsFGGXHjpBy+eU8jDVw64/FxOtoEqBSVmVUtjVqFF5uBCppY0/WXDYmcALPhEq7UxqCtPGnOgXA1seQ+sFBFUjJXyLm4ESQwjJjzB0IiKJlFKzQEgp3W4i9po5S2L7yAKgLvqMaINIU9jReYdEyrxNlRk2DOc3l4ddjxV2RPUyX4z6LrPCDmLtVG5J2EEQR67VCPuglJLYVmV2lmVhrFzAvtlawsfu1gcOAIj7i00G4cLf1sad5RI64RTDtuoEMnhQzBN11SiBTtilp8RGa1FjSazY4FxhTUd/y/5Ker75FTjw4IrAqWI5Ok/RcfjkmqsAKMZLtIFIdOMU4NjhekKuJVIVdl6gwtrUvFl+vhSFnSzXlcEWAIDZPeT14+QWEBW49K2HnVKGCR6hLsmfNvryLWcBr/6O+TG1xjOUxNLH6UZJmpVYK5h841shk8JOtA+pECT9uKokCoL8G6U0xEpaD6VgvSiJ3XWwgiAIYFlW5g2RVuiZh11NKELkBFe9oalUM60kVhBTRamwI2la3TlY4gVhSFpVUI2LetjZoiQ2/HusWUms5mFX80gHDBhl/M0UdkkPu+T/q7TeJgq7pjHw/QY5oMiOJg+pa5LnpnQO8pzJwTRBVFhWfAIIkAVls5JYkqwlIEng2SpNidV8BLpAXheJ2XtVT9dUx9ekJJZOnOmioomfQD/izy49Vt3+nwcPxB6r6iWxQNSxzz2u7pLzEssnKqaUiYScnPzmsZl0DzvZXgqEsKubCLvWJbF+EPoGhQo7jWyVz7U1ws5P7qI2hXatubQklpR8eaVwgHQtH87so+GdKSWxcchdSK0kFohPdqXKZtAVdnTCBZgJfqmws2XoRORhlzlMRKColGTxhXEilMUApbAjJbHJ0Imw/Zdp6IQK4BnC/RWtjx1pn7Arog5PpGeHbx1dC4WhcMe1rEIVaElsUmFnCtQAkN9Lpc9gKolVHnZanzRf61BhBwBPeD5wxIXmx5TCLlkSGziRZ2grtJUQC8RLLxGRzpHCrhiFItCU2EZyQ1dhgEMnqp4gESyN3DD4/QLQghfMoRNGQpYSgPI1te9aEsk997AjhN1sIVIHxwi7pgo7yzimWTIxFI2wz9SCTOYzlsQC0abxdCUuxrj70XDuXUUBgVharoQg7EpmhV1CUDBgcKWHnSCdlR0SmqTEFuNt1ehhp5XE6uFIANRYPwVC2GmPOV4FZUTz99JQdJ6iktiGKqGVCrtkSmwUOiHXSFFKrNnDruH7SeV9QmEX/37OPiIiS5TPZzFSP5k97PpcYaeFTphCrboCusYzlcS6BtFGpyWxrZThFLlKYpOEnfweaTJx5jZBFXYtCLu142VYVsj3PD4bXhdyc2PMVImZA90n7MTiT5ZwpSnszCWx8Q/jiR3RogydSJGrt3+wJCW2WQIJLaUgZvE1z8eBOVmqmG70KjtnuYiJFHbpJbHlWOiEJKGKmIt52GkKO8Jyy8bpNy2JjXvI9DXkuVTMeo42YpLnpnrYxS9wY8mYTtjlSYklcmNlsNo0dKK5PDcLqPojtfSjWeiE/JyWHf++JAEjCec+L4ldMVLE1RceAQC4Y/d07DGjMsRA2Lmah10jJSUWiAi7A3P11h52bpm0IUOpUIbQCSAk7fwg3cPOtcKStvCPkpoYZTbN18xm46ET0bFVraL6zHb1YHinZiRv21ZUon7kM8I7t5wT/l03tGPDZLefFrBtIUHYpZfEFiEVdmFbqQVuU0Wc8e1SlGRyJz1RSkOgzJXJZFstRNwMCjt3CPfOaYRki8mV+UAkYdeIHUO9El7zfmChJJQIUUpsUmFXzqKw8wZcYUfPkyLsamE70RI95+teb0sP6carhBfve6o5SmJz75Zr6Z6KlCTq56TCjnjYdUTY9d8GhQr2sDWDfrkIo0ppALHUVE3xEXnYpZvzh+XHUs24SCmxo2vUzWk3JOwsS+sf6Jile9iljWe27OOTCrsgCBQJPZKhTUeEXdTm6OIUsFBzwn54lRWO3U5JV9gl+/pBhCs87NxA97BLLyWUREzkYUdTYql4RJTEwkmEI4VvEp6DmMJOe8z26xhBNF8cGiIKO1US65FrRHjY6fMC0p5kW60YRA2WZcUqOuR4qNbCCQ+7eHseKbn411eejrc8bTusl90IrDkeuPzT6nHdw873A8glcF57j6UCOQeT18p8Lbkh2BXQCh1jSaxhfdF2SWyvPewkZxLxALTPyU/YkXl0izll0bWxejR8310Hwu9K2gcYrdNyoOurFXWxCsIu6WGXlKxGhJVG2EmFnQhtiCYu3SbsapDKDGNjiCnsBOkmuM7HpsMTYi6JlR52WkmsTIltVhLr2mio0AmisKs2MJlG2BkVdlpHTktixYIk6HMiBUD03UnlTB7lmUmem1IypytOjBc8DTMBmvtHSRiMlGWbmialB0kPuy4o7IgKIpF2KtFMYZeWYqdKYtsoU16iWD8RDlqPHYoTZ0YFkVFhF7YXy4/KDtP831aPRd9nqsJODp5uOV15ADQn7EhZl9x9moNZYSf7svAfC2iIdLHsJbHxRbPr2LAN5SGVuo8GRrAGB6L/lR599HgcGw3fw56L/z9s3nZmqLAB3YUk3y0tiVs2hJ3m6WYKYZAlsbYMnYj8FfMSdmnEVBaFXWSunAydsDT/lJiHnbgGgsIQHpkNcNAdxoQl+ql2FHai3yqJ6oCG76MIG435sB+bRRnDYrJsMrOvGnbAiykKO6/Pd/9bIZYSKyb8BctD0UJkVC7K9Q4RxU5PlExGD7s4GWYkdDTM5lAjxd8/nu6ZJOyilFhl0t+oko3qZqETLYjGPuzvZB8y7Mg5XSn+GwjHOtmnUS9dbU47VCSl2Tro3EuVxKakxPa8JDYi7A644fwh0QdLry/iY9ZS6aIUdrqHXQHVhq9IjSyqUZoUK7FnJj4fmreGUcKsIuxsbdxJtewZMLiqJLaBIAhUOyoE2UtiYwb5lKBvFToh+pBRS7RpKhgg5J0k9CpBAeND0fEMUeJQWfYIDzt9vCKiETmWKYWdYc3k+UHCwy78kM0VdgDw5O2r8eTtq8M/Xv/jxGsDkSCICoP6dYyVxy2rDUyWG12BCHpDdTr63kukFNRki9RulZ5p86wVsoxhrk7YpXjY5S6JzU7YAcD6ySE8Nl3FIwfnccKmiUhhZ+KJcqBnJbGphJ2pVDOFpW2okljpYddk4tLWwZpKYpsp7Hx1rL5ocLsPhp1hs5JYpbATnXVdpcSKxpJSEqsTdr5TQrXhR+mxnj5YJz3sEqauikxqGN+3b6G3iVwKO3EZZPCw03dpjKWA7SjsNI8mILmDb1vEt6BLHnYAYsmOqWlo8n1MoRNqV1r7zuU5kR38ABB2kkTbMx0nxRIpsUBElsjBA1H/aKvJlptKdm2cjM5tFDqhK+yickCjx4REk2udTqjkYBaFTsyEKcDyI1mE1HZKUUlsBx52JUPoRLXh4WCQDJPQochmuwyc8yZgYhMAqnIyKeyoh13/KE7agk7YmdIz7bjCriHKXupw2y+J1UNZMpQ6qp1k36SwkwuGsE8tk5TYQPQvdbuEuhdgX0A+M01FywpdYSe8tBqVcByeR0ldx/Q4JEym0PJ7SRB2wYAr7JSHnR+7vktWFPQly/UOzUdzxWbEbtuwDOO8qjLIHjohSwFzl7c48b5PtgmLbKbIdmRRPyFC6CWQVWEXmDcglzKkwmjMlWXCYv5gCvYCmvq4qZJYk4cdDbFIVdilzIu6DbeEz2z4M3y0cRluWnkFAAM5AiTI34gwSZljqdCJRiJ0QvrXAdlI6HFJ2BGF3WOH4nOOeaHQl4Sdpc19t60awalbVsQ2JQcRBaGwK1hejKBqVhJbpt5xiDZ1XNuKiwuIh50+roRvqq0NqMLOLUH6wK20QjXVHErEIy5qC/P1SGFnibllFoWdJMf1vpyq4BLezy087FohKnuU313/E3ZyDiZtxHpWEitLi2szKSmxJg872Y7zbl5lHLcosvhON1HYGT3ssnrQrj8pup0hyGyD9LE7EK7Tm4aT5kD3QyckYSfKmWh9PEAuKLojkLI75AUidCKhsOsWYWdQ2JnIQJMyQySrPnKwicJOdMayc5addV0PnTCmxDqRV51ofA0rfDyREmsgl1JTmKjxsTVAhJ0+mc3lYdesJFZX2MUHH+MELtXDrllJrDh+IjfWJ08rhotRDLXysOsCYUeSHVNLP0yR3hJppth66MQAKDnXiAnmY9MRcdbwoh3q2OSkRAZAAaWwC1qrmDauiM6tZ7cg7NwSmqbnZVXYBVJhJ6+fIDznYsIdJ+yKUblGVmJH21lzbZI6S0ti6348/bU4ZpwUFEjblQiCIGrHJg+7WErsAPR9zUAnXIBRpahKYmVKbD3yV8ytsEtJiU2MeQbQTSbfD2DbVqQQL8TbtjyvQQB4tXm4iDYJH7Q3YBuE7+FI+yWxJdEu5c52RNhFY0tUEttcYScn3WkpsYPrYRcRmp5dlFuN4TUv5n0ywfIgIex6QowYS2Klyk8o7EyEjgZZCjied/KdorCziJdfpR62MbvYo9CJPunv3veNO/HRH9wLABhxfcBDNJ+wXahgr0YKYacRIVIJO18zEXZSYVdLV9iZNuR6hF9NPQ3/9tvj8DxvHMC02UbAKYSbtvIzt9qAkgo7Q+iELIctunYmUsNUEkvnQwAwKxT6qyDsLLS57xsvOgpvvOiolu/V75AKu4IoRZaiDZka2ywlVhJedTVGaKETfjSHNIZ36GsDeg4sK/y7PotVkIRdOUbYxUtiw/7IEn1RYhwn1gLKpqRu3sylwZOJeYEi7Obif2eE7mFH17/9OsZKkYhsB9GGYJcJO6Wwm4nGSrrh29TDrs2S2KD1eKuQJ3SilYdd3o3Sw4Uv7tCKmM9oGmQlluSHZF85WupsDdwzD7uKKOHSQyd0yWo40IjbWuflicMrKIVdDwm7Zq9tkCHL+x7eHzZeI3MqnuMg8iJoeL7qTAqOJVYcyQVrqWCHKbGA8gCri+RdP5b0Ghg97FJTmOR7+HXlozUIREpS3ZVj585YEptG2MUvcOMEztF2P5XCrllJbHL3wrGtWBLQ1Ahpm6okthsKu/A9arQkVpdbNy2JTVEAqCAQWRLbH4uFZlgjIrv3zlSVP2SN7G7G2oMMSaAKO0sq7GhJrHnQ2EAUdqOj4rUSoRNygTEUDU45PeyoaFQOZvMg55KUxUrFtG85gOMqBVRmfxBtgVlwbGNiWqXh4bFgMvo/kzIMxDONnIOa5ytRYCIlVr63XOD0UWpiW0go7JoRdmLHnijs8iar0fJ6CqMCVQPdtZckmZzQ29ruLiV0GtWwfc4FYfv555HXAYedBbz487mOXUH0Y2X5fcjJvyTsrOjaiMzsDQq7DKETsXKnAQQtia35NupiTlNETfVJtiDLZF9SdO186atZYSyJjVdtZCmJjRR2OedNCQ+78HhkABHckrpubLpB1pXQif5SFAeI5q2jUmEn5xOWFd32CFEk51uWk0gJNnlNKsh5y1LwsEPUR0rfYuPYKs+7Uti1KomVCjtPhE5EJbF5PRnlWodatewRhJ2co0770lZAPKcLXsv9CNeNlI3hhrjYqGyWEivKt2VJbOT/asVVusQH2ZwSq60NEonx4XpktXUAADAbmAm7+ZqnNswsWRKbCJ2I2l/Cw05X2BEVXEJ5L/snFf6Sk7DTPOwaA6Cwi0jIeElsudubB3K9EvOwMyjsYh52HYZOmLwX05DHw87gZR9xIn4bHnajwB/fAVz140zcwobJ8Hp5RFfYLdWS2DmRMjiE+M5LolQz5jsR/zDSJ65gyed2OXSCDnpNyw5o6ERcAnpIMKcrR0yTqfD/HESNstrw4zsmlLAkn7/sktAJodCpCRJU7tqoY2+isEt4RNCkMl/ucPc/kZLYqWpHYUcn8ikTXH3wMZbuJBR20sOuWUmsWR1FSboVvSLsxAA6X/fUAJf4XCb/AomUXekoJXYm/ncfY9VotLiUuyZUTdSyJNaRHnaR/0jazt8ph02q2xtWidu6wq6eVWGXvqNLFXa+UDf5sOFJEpkoBIeEYtqzw3PttVsSiwDwfTi2FRkw05LYuo/dAZGepxB2BYPvGV2UxYx5Y4bN/aU4aRvUgwRIBHcAiDzsIFNihXcbXBRyGjWXCPlPUdODlgygj0kiS5I4ViHuz1h0bLUm96thXzjrCwX6+Fbglf8BHPXUXMeu4ErCTpDq4th9QQxWqcJOeukRZZbJYyYtjGPgFXaFiMCtNXylgiz40bzF1qoaOp3UpkJVSiRLYm0x79PTjU2Q/X7uklhdYVfQS2ILqu04JeJh11Rhl9G8u8/6u1FSXTAqPezo/IEGxkkYKlUkmpfEkr7FSyPsFiglFkDRCY9VLvLMVRxx8rel+Tstia37ZD5QUp6MIxk9GSVRTUtipTr2yNXhov+Qp7VVqd5ZZnCFUtaFJyxnpMIuvYRZD52IzclpH+JFoRPmlFhtvaGvFcQ5OawYzk/nUMYkWWMMi+Ooeb5KZLU9URKrzwvIhrAcy+ZVSaxZYef5ho28DktiEx52lLDrxSbQAqDgxDkTqbzMnVLeCoqwIyWxsdAJKQigHnZtlsSaRDKt0FboRNTmFZnrBe2FfY1vCH8yQIotdh2Mh04svZRY8QXMCA+kIcQXj7buYdfEd0IqzAq2TIntYeiEttMag5Vc6Okk14rh9N1PqbADwolrLCU2lmxFSmILduRVJxqfJOwKNGjAq6V42KWkMKkd2XrTCU7foaOS2BwKO+0Cb66wq4W74/K1mqbEmskWSRABwBRtY9S7rEPIz0BLHBITU7r7oiO1JFYSdoNTEltyHaV6lJNUSUZYlrbwNpTEysftgKbEmrvh8XIBf/PCk3Dh0atx1nYxUKQp7ApDqaQvgOYlseSYvSCSi/suSY2SH0kopj0nfC+lsMuqxKIEuN8IU2INJbGVuoddlLBLMXo1hRzICY1laQSR0cOuPxawbUNX1DVR2EnrBlkS24CbW/mVGjqRRWFHrgM5bsmx0pYTL68G+D4sy1ILWU+0zxkv/ByrOvVFcjWFnUycq4TlXXN2pJSOFHYGws6gsPOD+CJCXmt2ny4mWkGVxNZ9VD1PhecUggpR2MXHhdzpq1nRRGFn51LYtTn51j3sRJuwg6j/Uwv6IvG0baqwG8zQCVqxMtyMsKMbWE1IK5MSVkHOvWilzWKFTiDqI+X8wkgSpnnYtQydaITzFUNJbFYCQBLqM9Vo7bJfJMQevjrsGw/6Wh9s2ihaDlAJ7I1YBYsi7AxtVQ+dUL53thUnamnoRJOU2OhvrcJHzOk3ueG4NhuUcNhUMiUWABqiuisqidVDJ6K1pKMRdgmFHVE61fSSWHldt+l77WrklvxeLKt/VeyuUudLD7tel8ROR4RXzMNOtA26vmi7JLYTD7smn1u2FxU+mVTYeUGg2kVey5esWJ/mYbdUFXbTQmE3rBF28oLyFWFnJqwAoB5IhZ30sOt26ISpJLaFwk7uyGoD48rRdMLO9hvEw8YjoRO2pjCkHnY2GiBqFES+gIUSOUbScdOGrAJoEyWxdIdGko/9T6R0FDph2nlPmQDpC05jiYSaTNZiZI0ivUxIKWdcORp9jrjCTgxo3fCwE59phqT0JRR2VC2mTw7SFhTynAxQSiwAVTZwYD783NQ4N1bKpUpiozZg5yiJBYAXnLoJn3zF6RgdkSWxaR525eYKuybkvGVZkVrJD9Tp9eUATUtiA0HmKIVd3pJYcr0EHgo2KYmNhU5oCruVZr8b5WFnUNiVXSd+PgwbL/1SItY2dINcE8EvQyekh524nj0r/+QiIuziBIIc85qFCdBFgPKNE+1LeXoBaoNA9r1BLZwUHWqEx7t6tEPCTvRjJaGwU+VGYtc5RtgRjzaJZqETgJ6CqyXGDxhiJbENXxF2VqOq5j5OIX6+eqewM5Bboj+1C5Kwa62wk+EYuUtijQq7AI7qm0tRGVmJlMQ2824eUA872gZGVEos+fzGktj0Pl2Wj5lTYuV8rdLSw24hSmL1DUHje+qbzE0+O4BkSayas+UviZVENd3g3T8XHuvmqWE4toXpQNucTlHIDzzseNiHIuT95CalhCTKKiolVpbEEg87UlnVaJESq6ALBsScfq0tNqJQxmbim1xyIxV7XXgo2+J6S8xZSQWHHMsqNc/4XDlXjIVOuBph12appaMJVeT8NG+lwFJCgRCcQKS87F1J7Iy5JFatUYmPebvjSluEXYb30lWlKR52kZVPb0hcqbB7dLqKSt1ThN34UGdr4K63YrkglR4Gw0HcpF5FFMtJq0dOmHYi6uLwVKJOs7LVduASwq6pwo4QOqqMI/7FT42YiD65G9KIlQrV6STdMxOWJdeJFHYCcrJbLhYgE35iJbHk/2XH5SVKYouJ/7MHoiRWJ4vaCZ1orbDTJ09mhZ2cTNYissMpNSesFNkSv15oqXUsUaveRYWdGGBlp+LaVjIFSu20BHESEoiTRhTyexiglFggIuyUwi5NPWQoidUVdpmN/dPIOBU+Uk4lfQE0LYkFiFycJCj5cke2HhF2SmEnCLtE4nUr0OvJb8CJKeyiY6s2fNwRHBY9N0WKblJ0RSla2vfaxIt0YKErt0xKLqK+AABfLOb8Nr6bktO+h51lWZEhtVYSqxRHQMLHzhceoQfqgrDrWGEXXkfSf0mVG4lJ7HxMYZcMnTCluNFrnH43KmU5p1dgv4CGTtQaPqpi0xGUsNPmXAursBMbsIKgyaKwO9S2wi7pYVcg1ReB46q24ZbJ2CHnpiZLjSwLH9+PknH7pL8bMyrsyHWt+wQD2UpijYSdHFur6Qq7hUqJRdSnHBAkWGIcA0hbasR/p6bEEoVdSkrsUEbFTqSwoyWx4etNjRSxYriIfdC8U5etwi783h0rQK1WV+3IblISK89D3QtDGdR60bY1wUUUOlHPpLDTCbyQoFnh7wcAzKIcCzqzrMhDuw6NsEuUxEYEpBzr5tJSYom/ek3fyNO/j5xrBjmMKoVdO6WPSwyKhFShE7I8v0cKO78RrfGMHnaUsGuzSs9JGbd+9jHgb48F7r8l+T+ZCDutjVOFHanu7LXCbtVoCa5twfMD3P1ouP6zLcQ8IttB149WTrgPeeEgWNYIuwJh1wFEJ8FgFNsQCruiVNipwbRLCjtq9K9MLlt52IXH67hRo7EtYNJ0IsguGDXjjhoLKYm17NjuWMm1o5RYgXmRDjtcKsTVgUYPO/FwIiU2Kom1VXnvABApaYEHWWCayKcocPTyBOMCVHmiVCPCrlngBGDuDBFX2B25hij0VPJs90tizZ+pHBHQcvdFIo3s1v8egJJYwEDYeSnlMnIArBEPO0nYqXIGN9suj6kEiP5dKMcXHjqalMQCUbmA5wdqYhBIwo4q7NCpwi5O2BVsS4Ud0Gu4UvdwT7AJvy6eGPaN2y8xvpzJzL+alqJFF7fyWh90hR3F2Hrz/cTfCIgIO8/Kf72mlcTWMyrJXM2TUP523EK0cSYIaXl+AzF276+Hf68yqd3zQJbECiJZldVUQyXCvB31w0pBVm/e/mLqQYPCbll42HmRwg6Nipr72G4xRkqM9NrDLiBtU/SLjlDYZfGwkwq73JNvLSig6NjqmgOAahB97sKQaGOze0HuTH/NZoQdndf0SX9H0/TKtqkklsyxJJqUZ0UedkliIxCv9ZO7H0ajRjbA5ONpqeM9gjxWOR8zkoSJktgWiiSp9LJCpZepJDbrdSeVpSaF3YrhAqZGCtgf6GFHk5lee+BA1lb1elWNDXaTlFg6blTqUUVWwbWICCSDwi6REquXxIZ/rxGhE5vXrk4IEiRhVxMlsY4IyEmsEWR7sgtqDJdEcGpKrBeQQA1NYSeR28MuTm41BsAjVn6fKnSiVyWxxbFojJSgJbGm9UUrZW8abG3DAQg3p/79LcD0I8Avb0j+TxbCTm/zpB936Bonr5VPTji2hbUioPBXD4fzxsnhYsfEcfcVdpKw88MLbyiIqz2Uwk4viTV0XJKwc/WS2K4p7MjryEmcieiJlVKJ3XMS/LBytGSuj1eTKS82sa83yCI3ZZJRLjioBvHOa94LX2+k6Gj+e8nXcHRiVD1ABvrAbPrcl0iQRTmILHKeFFI8rsq6ws60AKVqKEXYtTDdlYSeV4upTk/cFJnGH0UJu6562IWf6VCzCaJlGRVj4bGklJMnSNQBaGeIZM0JhZ3eFoqG0AnRTzhBtDuaadBIU9g1yAJDedjFSV8ALQk7ufvk+1FQTVBMEnYlURJbFx52uSdENJXV9+A66SWxAPDBNe8B/td/AWuPM76cyczfpHACQIh5P9vgPyi44jpg9bHpqamkXAogCrs2SmJNqb1BQHbSWyhUCvqEWy1WnMQ1oPopQeDtr4ZtcFWnJbGiHRY1hZ0lNiqqTjYPO0pCWZal+odaTGEnFQD9W7LTDCVSilhvBKiClB+Secs4KS/tmcLOVBKrCDupsGtN2D0+G0/EzAwtKKFU0Am76DsoDomxY44QdqaqgSwedk18opcqRkpRGxiWhB2dP+jBXgBRmSU/41AThd3d+8LzMT07h9lZMdaRsajuBSp1fCFLYiWMC3Mn2ngPf2ctiZWhE1FJrFLY5fawi9rVgbnw9SaGipgaKWJ/EM1VPdit57+DihhhV0NVerI2KYmlpajzhLBzdYUdIez09PHwtV3lJQ8gaY8hNpQLtQMAgNOO2pR4ibJG2Nm+VNi1LomV41wWDzupzE/0T3k97BKhE/2vYC84EcEJmOcXXYFtxz2OnVKcD5FrTbq+aBV2k/peWso1ABx8iNx+OPk/WWxsmijsaCl2NO/qXbuQatVfPRQSdrnnCwZ038NO9DQHREqQrrCL6oglCZe+KyY97FyZspoiV28bJrLD1EEYFHblUvTlb1uVop4iu5/Uy6VOFXYpC+mSa2Me8c855wvCruQaO27akBNpvOqYoh0amVTpDEJJLCXoLMc4aUuFKbEmrSRW6ySNO64xhZ2QFrdU2JFyF1KCeNGxa3D4qhEcNjWMI1YbFHbd8LDTSmJTJ6Vyt0UmCEmkpcQm/u78WJcC8pfEktAJZTROFXZZSmINigL6Ny2JFcb8MXjNd+CpIauXUNhFx1/SFHa5d6psG6qc3/fg2umhEwBglUaAqW2pL2dS2EWm/3pJLLnOsxjYDgqOuRS4+ifAuieYH5flUpZU2IXnw29DEWtS2FHyrhVhp+8mx5R52g6v6nvF349Xwr87LokVGw0lqbCTKj+hlK06UT8sFzRxDzvpMRNvW6ZE45jafgARK4kloRMxws4pxLxdeqawk/1sTGEnynKLMiW2dUnsPmGwv9Jkg9IMiZJYO+r7LBtV8daWBbhlbb5QGI6On8K02aijDwk7WhJbspMK7JidjUSTTRhauh5oNjF37w1fo4Q6Amkn4dDNo+i7XYiSWH1OqfcjAIjCTpbEevH7dZAk8Jrnx+YNkrAbzqjYiTzsosW2LN9dMVIICTtSEjvvjJmtGJYDyJymXquocdFS5LLZU7hMwnpiYyAthZYlsYE5Jdb3g7jSUQ/uKo5pfyfXKJLEleIRV3nYadcBISD1sUzfyJb/2/CaeNhJ5PWwk/yCNn/o5w2xtJJYY7/QKYYIqVueiD9mstzpuCSWEHaHHolu77s3+T9ZguIShB1R2Mm5pR+Q4M/etYstIsDl1gcPAFiqhJ14xYNeeHAJws6WCyypsDMvnDw/iAg7W1fYdUmpY7tJCahJvWcwKx8qRw1h28pWhF095mEXM5pO2RUsFWzMI/45D4nvdKycUhJLLppEGq/6fNFzCmK3ZCAUdjQ2Po9/HRBX3kikTP7aV9i1IOzcUtQWa1FsdukH78V3rKvwnWdMxxe7ysMu52c1oOgKVawgoFIX1dLPILUkNiUlVqILx7oUkJ2wIyauAgWlsBOEXdA8dEKhlYddYSje7vXneek7ukBY1g+E/a7fpCRWKewsQdjJHcw8O1VkIyNMiZX9V3RsWU2+Taol6UOV8PhYjh52WaBSYsPvJBAKu6ADwo4SH3Qx0Sx0AkgmosXaV0Jh58T+frxrCju5uJUlsWLSXxMKOzda6OgedkEQqHQ8XSlmIjMHwWOnGUqkPVR1Dzsy2R8nBM1IcQFDJ8TYVRBtq5XCzvMDHBD9fu4JuFIVRNYTtO+r0rAcXZGUpqTP5GHXf4QdVVyuksMaXRTmLImVY4EfxDcQAOCefWKj0qqjGIjXIwb99HpdCMJOV9gZN4U18rfVhpwcW114YfAGsTFpN3RiRlRkBEF0TUwKhd0+QhTNuYZk8uUC24EvNigr89Fa2PKjElITJFE2X/cUuVCkJbFeXZ37sCQ2udFQ8/y4l6BO2JW0PsbgMyjbotxocYOUlFii2NRJEH1+qxRjvo+abpWhz09ze9jF173eAJTE0u8LiCw3sipic4G2kbG18cd0n/VOvFGVcIiMt9O7otsHHwJ0//12POzIulv5dC9A6AQAlbh85+5wo3dqeEkSdsIPyw+/uLKfprBrXhJba/jwROhCzxR2lpUkd4wKO7kzGxF2o0NlrB0Pj+MJG8eT/wPEjBXpQiZm1J4yySi5DuaD+OeUJOh42W3pYZdI4zV8vpIgU61Cl77PxQQlxPISkHriFr3dwsPOOIGjCWZZCTvLisoGpHpubh/wo7+FPf0Iiv/vg/HnZ33dDJALXznpSp24pRF2qSWxHZQpL2FIwk4SnNW0cj+psCNqEl1h18gcOpGmsCPqxqaEXYuSWDFw+UEQBdUYSmKLusJOTojy7FSRRaZjk7IwlxJ22Uy+FQlCSKFoB1JX2BE1ChN2EWw5GRcLME8q7NpIiXWSijO64G3V1iWhXTcq7OQ1ID3swteyxK7/rFCgGxPb80BcRwXEPSpdobCrF6iHnfTG8tRz5ZBb1vpRU6Jxbg/IPkPkYSdTYmlJbNQnUYXdcKkHCxEgJXRClMQWZUpsc4Xd/rmaWkesGM6rKjCEThD/TtXnFezkuG4KnAAyEnb952G3ZryMV527Da978uE4fIX43ui8P3foRHR96ef44WmxAEYVw5b0hI2+/yrZkLMWQCmml8A2V9jpJbFphF14fwGNcL5CgsJmhYfdcEZlqyyJna158PwA09WG6scmhwuYGinh4WCVev5saZXxdZYLGsKLfLYSzd2sFhuokiibr3lqbhMrifXr6roOQyeSCrtq3W+usNMVVENJYlWVkgt/TUf0l+mhEybCTvtbjfEmhZ127ebcNNQry6L5af8SdrrIKTVUrRugZdO653EhXuHQ0UaQqST2ECHs/EZs3RF7bh7CjpDSMQ+7HodOAMBhK+Nj9rqJzgUrXV+tyM8/K8o5C6iHEeJiMRYZTjYvia01fDRSU2K7qAhzyyTFsmSWbqudWV91krbj4htvOh8/u28fLjxmtfm1TR52Dc2ToElJbEVT2B30wu9otORGZCBJC6LfYarCjjxnSJCpTrcI0MUE3ZEujaU/zwTTznuK/FYnEFIDGgCtJDaDh0dhOCTD5P/87sfRYw//IixFlWWp6nVzflYD5ARxvyj1Sd25SS2JTSHSdeJ0YBR2YZvQFXaJzp+em+o0MDyFgmPBhg8bIgUTTrZdnlQPOznxHgr7BNsNB7tUhV1KSqyU3XtRSaxSGcQIu/BcK4Wd6svyKOwigjwMnZDHRkMnshnr6n4p4f+meNiptG9SEmv1xwK2p9BSYuWYFLQROiEJmlpMYSdKSm2rpZJMlcv48dAJ12misBPHW0URE0OFzn2mxPcRlcSG10NReP1UC5PqqSWlsBOG0LXoc+tKGTlWUMVhfQAUAM0gz0XdC1Cp+6irktgqMax2Y4qqyaEeKf6bKOzcYhlAo6XCTpbDTg4X8m1SAAmSpRRT2BWiPs91xMLDAsQ4ka6wy+FhZwh2W8r482cK39IbDd7VdFNUwksnrYpO6AsWBKGfIgRBXKl7eGQOQBFY685CagMoYRqpvReGVNfHLbPCTiNqm/j3hfcL1bAlPOzUJitR2GVNiSVq2NlaAwdmw/Y8VHBQLjhYOVLE44jIoCKakMnLAA2rgGJQxxxR2LVK9ZVkDFXYFRw7TnSQlFiTwq7a8HAAhPgf0YhTncAzEHZy06kSyE090V8mFHbRGjRZEquFTuQpic1p1+RoHnZtzU+XGHTOZMFKYkd1hZ0WjEjLWXOXxGoKYSDu1woAlQNxFWimklhtY4uswWgbUGnsPSRyj10fF3KlWqflQNdHIEkUzYEszklJmF7yknYS5ute7xV2QFyVkva6KaVUUyNFXPKEdekLBOphR9LSJIlWdInCzlgSGz+e/XVZEpumsMvgYUcurCGEF55dHADlEyXE9J2jVpDnyZgSGz8vlmXFSDrjuadKkDxKOEWQCAL50V+TBwNg72/EzYDEbndu5isXlnIxklth56URdrqfwAC0MwATwxlDJxw36l/E+XJtK2Y0njklNk1hV6/EH08j9lpsdrhUYacIu2RJb0mURNTt8HXa2sEkJeiuY6NkDJ3Ip7CLedipFK0UhZ1Xh1oIs8JOjQmO2hgL23XQRnp40aAiS70+DIhSYuWEO4j+V9vhlW3DFv1PLXA7T4gFEgo7OVEu1fYBACrFaGETediF350sh3VtK0Hgm8q3pZev08cKgGag1+9MtREp7Orz8ZLYoeg63DDZo42dJgq7YjFb6MSug2G/unasjWOU11PgAUGAokvUxU4xrrCzrPicoRslsf3a15k2m5qFThg+J/UFowq7B/fNqUqWqeAAACCAFfu+o7FoYTZ3MoVO6Oe9pcIu2pSJpcS6pdyhEyXXUX3ZdKWB/XMRiQ1ECuePNC6DH1j4xZFvzPS6gwpfbBTMV6KwJIuUkJpAS2JVSqxjad7l4XVRhwM/SFZTVRs+pgNCYOgEXRbCTvTfcxphlxjLyfwyobDT1Hi0xLOue4l1qrBTHnZxhV0/W04U3Lj4Rs4xEpYv3cDExui2rrDTKhw6U9gZqtoqB+PPmT8Q/ztL6IReMUnWxwUyF5lPSTDuJg5fNRKb/yxJwk6xwXAjvxKi0EgQSb6ZsAoJO6KIACJioFspsUBc9ZOm3DOETmRqoLHQichEtEElzimfqew6mNdSYh+vha8XetjJjtvsYeekEXa2o45rJAiJIbc4AAo7SlyV8hJ22UMngPgipLXCLgdhJ8swZOjEwQfjj++9Szw+F3kHdCF9a6gYfgYZOjFUSGnbLVNitesnUdYzKAq7OGEnF3nGCa/2nblOPBkwTInNUhLbQmEnFxgmY1gg5jFiQpTc1aIkVniv1JTCrg1TX+phFwudiI6tmlFhJ3dvKQlSTVPYyfel32GflIj1FE58Mi7H5E487GrEqL1GFxyt/p/svgPEw86gsJPnVxJ2VRQ6D5wA1MS0IJKc634A1GZR8MP3rRWjhY5OAsjJtL7oBswBKcrPdlBLYsn4OF2pxz3syCJvBfF3WT/Ro40dqbA1hE4UMoZOPLw/3ORsi1Skcwkv9DUuEjuAmMIOiKsFCinzh2VB2Bk2BOVco0EJu+YqcuU3Sfqm+x+fw6wQFxRE/1ezyzElohyLFk5hl8F2JXdJbJQSW2uQklgnIuyGc3hHUh875V8nrmHp7fg3jRfh1OpHML32tMyvO4hoCKV6lRB2rTyFVSlqzYvbQpDQQKkolcKWuhY0Vm14+JJ3Lu7EVuA5H01uqGcg7BRx6Iv2I1Ni9bGcXHs6Qac/l5Z41nT1qn7t5tw01CvL5Pq3l6WPvYa0GZHfVVR90oPPtO7E6Pbqo+OPFTSFnUcJu7wpsVpoDpAk7PS/W6hSw2PUFXbR+tiosOvhvMt1bBy/IVLZHbO+82q4HnjYRV+KLIuNKexk/XqLlNi5WkN1ROpEycG5myEJWRR2htCJTAs9ouiQC5Gqp3nYpXymUsHGnKawk4TdaExhVzcO1nQBnoD4zKMICTtnEIgUSg6Vx9OfZ4Ii7FqHTgBxIsAcOkF8erKmxAJJhZ0k7GQnJBV2ikCx0r1tcmBIm6i1XxKrtSP9Mw+Kwi6NsDORS3LAEEmxRceOSvwhFHaZQidEXxB48UGOeNHEfuvEXovBjqZzSr7OMnrYCTWTCp2QhEP7oRORyqQ7Cjs5GCdKBuR1TlUZ/bqI7SbE9y497OyuEHYGhV0GhYpS2Pk+goCaA1MPu7jCzvElYVfsPHACiNQoAVHYzYblGtWggID0a3rohNy51f3rgJTQiQFQADSD69jqs01XGuaUWNvFyZsn1f+s74LXixGqJJ4SdkIxUgrHpmrDT6SITlfq+Ocf3otfPXQQjxwIFysbV7QxltG+16+jXNBCJ6jCDuiiwi5DKdFShmlD0FgS29zjSM7bqIryd4/PJubZ81b8u17skljjppWesqjmqyl9tvQphRe2swZV2IX/O5LDO1KWxc5U6zggFXZiXiTTkz042I9xrOxCOmI/w7fC70oSdmUHkco35XzJc04Vdq5jaVZIgmAW/nJ6Umyl7uO/gu14efHvgJOvTL5JgrCbTDxFzmnnhD+sDGVp5mEnQ+wk9DVSgcw1E5t5iZTYzjzsqB1Hv0JPl0+1fOkGNpwc3T7qqfHHqBAFIGOOBWOCeTOYSmIThN2B+N8dhk6YSNteexv+2TOPw0jRwZsuOgpr2lHla+iBh130pcwGQ5iyZuIKO/GlRQo780mo1D00AhL2APRGYWcystURU9jlmPxQD7uyIOxIB1x0iMJOIzuGCy4q2kRib80F0GhSEhsdPy1xS8AtAbUZjEnCrjgIhB1hr/OWxFoaMQyQ85y8yNtT2GX0sAMiT8UDgrDbcg5wz7fD5BwgUrgVR/J3lAboRFOql0nLkljds04jEweBGAYh7ObCwaaZqiapsIsIKl+42WVS1+iBEo4MKJmPP15IIewyhk5QMsEypNzKCVvNEiWxckKUZ+Aj15vrkEUr6YvzethVjR52KSWxrLCLQ1y3jpg8WS2UKs1AU0El8ix4XeKlSDebClRhJ9q8IuyUh12hO4RdrCQ2CFVwwl/lcYyhQIhHWZZSzaSwE9eYIXQii/qwX1FybczVPExX6nBV6EQ1pjI58/CVKBdsTA0Xu2LObESzkthS9J7Vhh/rd97xlV/jS//9MIqOjaPXhf35xsk2Nsro4tOrY6hAQyeKSSXX0Apg/33h7VaEHYKQiDSNJXk2mZciTGokWmEi0WJTaqQkSaZonve7x+cwF8Tb21xQwiT5WxKpxrleD5DwsGuqsJPVR5KsTDnH0sNOKuyIalGVxOYgAGTwxHSloaxUpkQprK5y7kqf3MfwpcKuVgEwihE3gNqzTVWDJgm7Ykxh11DnsCY2QWoNH3TJqMbdNCVWIoRiMvU4ZqTCTqhQE22SCG+SCjtziWzdD9RYqEi9jj3sBL8QaCmxfaywK6hN6fCzZK0+aQsTm4Ad/xauW/R1tByDVEps+/NE40aTJOwsJxyjEyWxWTzs9NCJiBdwbAu2BVANU6+Vl088bAV+/a5LuvZ6XSfs6MRTSs1pCV1koKgRdnpJbM0nCjtxonqisCMnOI0IpDuzbZfEEg87j3QiKQmbQ0WtJNYp4kA1/L/xWElsJI2mg7Wth3tQiAWJY4njKA2A8onuRktiKStME3k/GoB00I7S6PcWUzlZyeNLg1I0zYQ+dZKgO+zMOGGXJ8giA/SJWqrCrmVJrHb9DKjCTiYaTlcb8P0A88Jo3qSqUd9ZjZbEhu3ME8RVLoUdEF+kyO++0EJhl9HDrupRwi6psFNlQ4h72OUq6VP9oh+WxFrJBVlCbZICo4ddmseHvM4brLCLQSnsagAC2H4j1N63obArGVRk1Xq2cwnEd98bHiXs7MQOr1QGO6JNVoNulcRG7bCEelgNMLMHAPB4MB5brEiPn5rnw/MD1fZM44KprQ6CAqAVJGF3aL6BYVUSG/ewGym5uPltT4GFHk6iTaETjSRhV6l7MTXWjf/zCIDwHP/q4XBR0VZ5S0xh10C56MQ87KL0P3GcNLEvNSWWtDO/AdiG/r3vCTtTSaxU25o87Mz91ng5IpkkHtw/l1DYTfvxv7NuHnULutJtxJTeqitUWi1mSUlstaGHToTzyTwlsZSwk2FlU6IkdsVwAaMlVxGjXemT+xieLRV24Xc+WgwAKQzNkBLboCWx8vlyUx+AbxcAPz7mAhmqFBLz8+SxyLXAtB/2j+UgJGsS5DXxl0+mxOqhE0Rhp6vvu+Vhp6fE9vH4WiRWGh4hOfMQ7Lmw/ffM98v+V9rtpFRHZoKqPjQQdpOHhRtVaSWxzcYxSjpbdqI9uY4du076rV10fWZEL1ZF2MUUdpHhJIDUkz5f91RKbE897OgkII1USQmdaAmTh13DV+XArm0R89d4Z1l0bTQcsvNXHFETjbG0klgnqbBLeNgBCTWfWxiAAZXuBsgdgKwwsf1NUjXpADg5bBhwaelWnpJYSojN7hHt3QI2nxHef0gq7LoXOAEkF5epoRPyO9Y70rQwmAH1sJOJhkEQknZqoWUq+VMkbDjBKtgWXCt8fkPsjGYaNGwn6iMpGdfQFHapHnbZUmJjCjsVOkE97MJzXdEIu1yEA/GMDD3sokWrRFbfIHNKrCyJ1f5XLthpGRWnxKqxx0IAFx5cw/nIiiIhsCQihV2Gkliy+049eUwedmNlFzZ8OKKUtwYXq7uosANCRUrDC5Q9wSPBqthihS7iaw1fqVVMi3tTW1UKgAH1sAOihcXB+Topia0m+qRVoyWs7KUap4nCrlAoqT6MhhLcvuuQ0Vbk1C1Jv6eWsCzSB9UwVHCIf6dJYUcIOz3hUYLOQ9PKYvvdw65h2GxqoyR2TIzbh+ajMqzdByuooBgGTQhM+8VY2awsGU2dF3UZQwUnVkYoFf0xpHnYpaldZJm/1RAlsVFlz1xdeBfn+Hzyu5ypNrBPlMSuEKWvlmXFwn+Wu8JOpq3PV8W45ZL+JC10ohCtF2uxktikL7wcv5OEXYtx17Iiv289EVQ7jkNepNB00UgSdqRSLJkSq5fERir6equS2JwBk8rDTgut6ucNMTVv8HxFwgI98rBrBim4aFTCxU8nVgtqw8FA2E1sCn/XZ+P/k2Uco6rRwE88rLfFflNe9pawCwyEHSl5AZA60CQ87Ki6rZspsVRCmUaAdEzY1WPKg5iJKDF/1eG70a5qUBhRi4HRkl4Sm5yoZPGwkygMQkns2LpoMrz+5Hz/K/8v8KEMvFRnlBxQizHCzjDg0oVlnpJYqQysHIr868bWAVPbwtuHdoXHlec1M0BfXKbu3KiSWE1hRxLHYhhQhV254Kjr+dB8XflWyfCOGKQyQpwzGjoRKewydsNaSSCApH9gK4Vdym6YUtiRSZ9dShJ2BVESW9VKYnOV9JH+tBAriY0mawm1SQpKBoIoXWGnlcRadldKyvseZOwpoqHap+O2kxIbN0gGmpQoG0B33+vkNQoGD7vRkhsRHhAedmNdUN+TRUMR9XBRIdTNjwQrY3McSihX6l7Tkli6Uy6hPPoGuCRWKo/jhF2lsx36dqAr7HwvIu+coiL4KVlz+yOh/cOFR6/GZSdtAAC88NRNatMmN8hG63CRhE44hWS/RRV2I6vNr7ccCDsvUoMpOBphRW+nkCBSGX+IKOwemw43RX2iYJwLSth9MBo/52vpqtlewLIsdaxACmHnaJvMhjVA/Pla6ARNia2Gny+Ph92YUivWsX82fO8pMhemwTFGheAygkxbrwgPu9GC6P8tO1UtpMIeap5aw4UlseK7rEUKO0tcFzUvnnCdadPzZV8BNj0JuOJ683FIws6Prr1hVJOvqeahhpTYROhE5FMbKezE/+hjQZoVQAoioUr4ulIY1M+WE8pKo+HHNpMWKrU6OhDJEwRx3iFn2TKAGDcS/vYjq6WxdeHvWhuEXYv5fFpb7Bd0vSd1TSWxtenE4w09JdbgYRdLiaU7aW3s/KciRtillFJSNlgROVlCJ6IJouyQZqsNtateLthNy3xni6sAGdxHyI7UlFjyHUpi1KywixMrVs5OcUnCsoA33wXc8VXgJIPBajPQcxn44cRetcvkeaZKKuNkii4sZXvJorCToQ7VQ5F/3cRmYHRdOLj7dWDmsahjK7VRlmOAvrPaOnRCV9ilkM4D6mEHhJP/PdNVHJyvtwidiCf/hh52UmEXXq+ZS8DcYtgf0JJYSd7JazjVw665asrkYWeXk4SdKxV2QTx0Il9KbLQR48RSYknoRE6FnTF0IpWwq8b/Xu5wKWFXV6EoVhsbY0Vi/SCRx8OOnk/ZtmxLWDwoMjps82NlF6UYYVfA6tEu9DGWeK9GBUNWLTwOQdg9HKzCKvI5XMeGa1to+AEqDQ8VRd5nC53wqNp+QBFX2BEPOz9Sly0IlMJOzIko2eMUUC44mK15sbb76KGwH920YhjvfNbxeM152/CEDTk9cimcgigHboQedsS/M3GdDGUg7KhCOJWwyzFnXYowbQg6cfIeQEtPpXFCMgFhyaD0X7MKw2qMnkUZj89WsXVVOHY3U832ChNDLvbOVMVtk8KOhA8ArcvFFGHnJUpiVUpsIft4KI/pwFxdfYcrSLjEHz11O+r/cSeedrxZubWcEIhzVamE49aI/Jqb9HvKO46sF12HlPgpX2ELllMAUEskXGeyFdlwCvDq76QfhxjHZurCP8+vYxgVQ0lsFH6Wlgqr/iYKu5YpsXqQXQvIeaz0sIsUdv27MUvnRHJDsOjaC68apOeiPt/ZRpDef1E1nVR7UsIuCEhQS8b3MwhaWpHJSx1dX7FQyeGcqSRW91bzzCd9vubFPezowNxNhR0tpUxTLJEFZq5GSog+yYYfqkSTxHLBaVrmG5QnFGEn1Tgl1w47S1oSa/gOKTEaBAEsElOf6AQXasLca4yuBp70qvz/l/CBcZru1tLFmJFskeRqfS46N5lKYonC7tDD4e2JjeEOxtiGsCT20MPA/H5xIJOtXzMDkiWxKW1bxr7L95doZFTYdSHRdqlgQhB2hyp1NYgaJ/Ra0mrBtlXJYUOkh2U2szYtUtRESTzW0sOuucKOkgmOUWEXvo4qiaXlGlkh+6nAQ8GxzKETjRSVnAYTCZKqcpKTNqWw69MFbLdhO8rolyrs3EJ3UmLzlcTKRDRaLiPOm0FhJwm7RmDDg9MdhR0QXreNCoZRCds4Udht0Pr8csHBTLWBSt1vEToh1aDRJlpjAEyxW4ESdhXpYVefJ33SAhHncg6kQszIxodbMqaI7p0Jn7NytAjHtnDipsnOjoEsVMoFBwUrUvglvNKowm50Tcrr0bmLZ35O36fEGkpiTaETLRSbUUls2L89dijsR4quHQYszYU+lfuDMTgz0evON/Gl7BUmWinsaPgA0LQiBEBUEosGanVPrTt8pxT1WTk+35Qg5/bP1bBflMROEcLu9G1T+PxVZ2d+vYGG+O4DsRYYdcXY2ERZLPtM6rdYcKzof6SHnVNU/m+5S2IzQHnp1T2gOAxUDmLYqiZKC5t52OnqNupTmxjjEyWx+Qg73QrKGwQPOxI6Mb/A5fkxOEWEnuxB5wp5xY2IfkutMayorJUSdnRsy7rxtPW8xF0FrR3k8t5eAuhpSex0IIgLGjoh2WI9JVZbSM7XfeJh58UH5m4STJSwa1kS67XvYVeISujU27kkdMKgsBshF6Uvvgs56TCmxJLvkJ6HRFmsrnTqJgHaj9DS2wA0DZ1oafZJfcvyBERQhd2h0Oga4xvD3xPi98EHo7hrQ6pTO9A/j7HMF4g60sqBuFmoyRQaiBN2Tqm9NKElCrlbHy+JNbQLVRIbTrBcQlA1xIZEMSvZ5RJ1ChDuOinCTvS1qR522VJi5a6sZZGSWC/ym5IKO1na1mgn5ZIoj13bJqETUfvI7WFHSBCleNRLlJXCrhb/m6Gu3ZJVUwpQp5B/nDWlxOYpiY38bfy42TZAUsqkh11BtR3ZHleOdGksE/31CCph2yIKO51gl5+r2vCakvcmMlMFUPXxgqIVZL94YK4WV9jp5fy9hu5VSxV2dkHN0eKEXXiMXfPhImEBQ8XIwy6wC0mT+M2nR/+nJzpKUF88v25+zqCUxNL5hfKwMxB2qSWxYswWm+ZSPbl2vBT5tQLYj1GlGgOoh93CfX90LjFhmo+pkljxmVv491HCzidBHZUgen4eEmCFOKZ9s7VIYWfyc2bEypEBQtg1mQ/LuQsVeIShE7IkVpAZbkn1F3Uvvs7Lo2xPPY4YYRdeI8OoJDdSSfCcPhfUCUPqU1vVS2I7JOyisMUBDJ1o+CrgrmeBE81gWfE5WEpgaCboJbHU5kkF9c1Ez6fq8Vbj2Cu/BZzwIuCyDyYeKpBrQVVu9BF6WhJ7EGLBTuJ5E2EIKSWx87UGHOphRxecVhe/5Bhhl1Ji2JXQibChHBSEXdG1Q9Wb+lzJCSEdtA+tPBl4OPKOiHl4GL5D2mnWPT++6zGoCrt2YfKBkYy+oTPaPNVCKUZVVfL85lHYVacjhZ0k7OTvgw9HJaldUtjpHiOTph1dIE4Qzu8PFY1ArLwiBupZN2CksNz1PjTfQEWWYBpDJ6RKLRx8Co6lSg7zl8SK61YuYEyqY61sEIDm1WQ+t/IY5ASqYNtxkrk2CwxNKsJOJli3VXJA+kXHsUhSIimJzbg7HJEg0SJbEUT6/yp1iyyJZYWdglME6nMooqFIMLuNEnbT+ciz018gynDpP6PmFEphF4VOSIVdDQVMDheyq1VbQS5OrAq8Rg2YDjdQHglWJdQF8nNV6n5TP0tT+bbXTmhLn0EuLmZrHqo0OIeUUS0IdA87jxD3th2dR0Kodp2wI2EB1MPOswtKYaeuk/UnAae/FthzF7DuxPTXdIqqzNaIvifsDERcWyWx4f2yJHa3IOzWjZfDkuNHw+ftC8YAQtipRfICqlroeDpqIgpVO5Lz1RbnWDy/YHkIiPp+1os+Ux4SQJa/7p+t48Cc8LAbWebriBRYJPADAIYUYZf+fSlV8pwm8JDnXRIcTsG4EQSQdPZOCLtitIkRFIZhARiBSWEX9eX6fFbfqKMKO+k9rF5Pv8ZzKqB0fiExh+hDSJKp5vlq82BRCDsgHKvrc6EgoKOSWM2DVBF2IwmRA4B8hN1hZ4Q/BlDith+rGro+gtOL9VAgCbuohI5eUEEQwErZGZqreRgKiIddI710tCNkKok1EXY5POy8KFVHGt6qBMO0hE0AI0UXz6m+Cx/Y/ms8cvwfAb/8DSHsDAo7g4cdkNx5SbzXQk2YlyroIKHvvhs6h9dfeATu2HUIzxIm1AlQkiYPYac84g5FxzEu3kMm5xx8KNp5oG23A0wOFWBbgOTQjcm3QEhelidDhd38viRhp7cjOtjqQRV9DmkKfXC+3tS3CkUx+IgShoJjq4lbPchJ2MlrXu6Q07LXhIedIT0PaJISKxMSvehvt6h8SxRh54VE4LwobZMTI11q3hRWtBFTcFNCJzKqsuRklJrxKpWTfj7k+zaYsEtAKuxQVySY00YYUdGJJpcSCeVQs8NQpFaAWkNLUHXjbXus7KKMSGG3dqyL45jor0dQwVBlDxD4qKOAvRhPkIJUmdXMzzJSQpDQiQFYULQC7RdjKbH1BSbsSCk+gESYQdmgsHtclEbS1MuOQMICyi4h7KxIYRfr857xgQyvKQg72s9T9LuHnWnu3yx0IrUkVqriw+/8UVESu3a8DAytU887oBN2IkV1eAEXyc8+aQNu/s0enHfUarMKhCg1w98t1C5U5UXmBvOCsBsqOLnUJlJN99D+OdXXs8LODEXYiY3aEae1wk4q2A7Mh+1QCTx0DzunRJLZtdCJLpTEUpuAYHgEFoAhy+BhR3wmdSJEV5vLsS5me+FqY7x+OyMG08NOfl9+W+XrXQUVBHRSEkttxgBC2A0nbIRizwM62niia61+VF32gLCLvoQDgSAuYoRdvFSz4JuVH9OVBoomhZ2hdLQjZFLYkZKDPH4gMYVd5OMCkE6sCWE3XHLx3eBI/OioZ2GFH34/irBTDHXN6GFHz0PDi++8JNI6B0z9lBuyrCTwMpXEjpcL+NdXnp64X0F2ODIcAsimhpMR65WDUdmrKokVhN2hh6Lnd6kk1rYtTI0UlV/PipEmHfDwVHhsc49H96WVxMZgCD/pYyiFXczDzjApoOXRCPs/OXGry5LYrDugqgxIKuyIF5vsP01JsrRUKmVX11WEnUYgFEfC8y0GT0cq7ERpmyQccimEiMVAWCJsCJ3IONk0+U4pL6g0hZ38bpa7sphCfPdFNCLCro0wIloSK71Tq7o3VxPQ3Xe5O17UFXbi/I2XCygJk9dqUMDGFV0MTxLX7TCqGJ0P1c6PO6sQwE6WxLpRG2zuYRf3ifT9QOUf6MbcgwT6XVQCuekwH/VfCxV6pUIn/DCVTlNu0fMo0UuFnW1bGLLFWGAZFHZZYfJzo+h7hV2zkliTws78OeUm23RVL4ktA+UoHGEfxuDHSmIXfpH8/FM34eknrEtX0ugKlVbnmJTEwquGZkhOEXOiL8rriSXJuUdEmu5QwVk8EmGJw3LJdw9gOANhJ8+7VC+W9ZLRIHoNtUmmKexmq+L9cqT/6iiTkljfHYaNUGGXTImNvJSpxYtlJTfq5FjXoCmxkkihwoY2FP7KI1/zsMu1obzEIL8bPwhDSIBFVNjJc0IVdu2UxNIgTyCusNOqkmLPAzrynu53wq6nHnYHZEmsJB8Q30lueEFqSex0tU5SYr0lorDL62FHQyfiJbEquadJ6MRoSaZaNVR0utrFojuMBn8qy7JiBt4xkImPB7t/d167iZiK0o8NiLmhq+ksGyhmSHSVJtOzjwHTu8LbCYXdw1GJuQyB6ALoIqHpTqn00qGEXVpJLACsfYL4fUKHR7i0IMtrDs7X1SA6WjK0lYIk7JIlsZKwy10SKydHkngy7UqavH2Alh52crGqBrNi/Pgd0V/N++HrqAlRHnk52V1zrQBFYrwukVVhVyYEkUSqp6B8X/n9tbMzOKhwJWFXVwSq247CTpyPIIgmzZU8CjvibyPHLbVjLzeaRH8zOVzAiBu+dhUFbJjsolJL+DeOWvOYnH8AAPCwHfbFaSU/tCQ2oe4k/ycVKZLsBgZbYUeJ2pjCTg/M6TViafBeYt4UeRGG52Wu1lBkzaqx7nvYAcCwI/1M3UjJlZf4GHjCzlQSSypMEs8zj3HjWujE7oOkJJasA/YGE3h8kQk7IPTMs9Lsf4hSM/Y7lbCLUmItFeJRavuzrR2PXw9cDpsO2w2/exk2VlaEXeuS2ANqvSjOj646c0vGZHYgIuxGS+1f98rDrubDd8NqkWGr0jR0gm5olaQykCDalDOkxFIf+U4UdmLu0NaG8hJDrGpR9F2Lp7AjHnYdKey0DQeZElscba6ws+zcZdIUdJ6Va82yRNBTwu6gqSSWEnZ0l1M76dOVBgmd6KXCjpAeW84yP4cmMrXpYScnYTXd76qR/rmoiufAnGbsSicsKYbyLpHSxh+IOsKatczVdRJ0It2p/FYn7MoT2ToZGWctDT0tO7pPedg9BMztC293ycMOiHZugBZKGEXY7Yvua2YefsV1wGmvAl70r104yqWDyMOurpK8jBMj2RbqMnTCVjutNVESm5j8pCFREiu+94KBsKPlsrJ/sNLJedlXyEmfKiGgg2cQwPHC15UlsXWvDQ8uEjqhUhIB1QcGQdChwi4tJVb8rRR2fbqA7QUEaTJsVeFY4py2QdjR8yXHOhUgkiF0wqUKOz2BWPOwsywL64dFu0UBGya7qbCLDLZXVB4EADwkCLtk6ET4masND3MyUTJD6IRHwqD6cbc3K4wlsdTfVVf89woxr1pK2IXtSp1HcQ5lOWzJtWMBYF05Bk+qbeTmTUGRJ+0TdgMaOmEsidXGQqDlAlIFRQkPu10Hw3Fg/WQZ2HgqAKA6tBa/DrZi3ywpG233vPQSqQq7tJTY8P4iGnCCaM0xV23vs02NFGMbMEzYpcMR85qi2KiV13zTlFh9vSjHToP/eCFFYTcjzq3uUZ0HQ2R+5QnCbsyuJsuniYfdUMFN/D8Ftb2o68FSxU4JO6neEwo7fdOvDxHjVASBu+gKu0YlVgadG3oAlCTnCsORjZCJsOtwDIsp7Ppwk7QHhB0piYUsiT2g7ouVxHpBqqxyutKAJ0tigx4q7DacApz2SuDSvwOmDjc/p10POzKR0hnxLAo7lWo1X8c+SdiNmAg7MWhrpF9B67yiB6KOcM5qEaCwXEAn0rSEsC1DTSe+CMnqNVcajQw3AWB0XXRdTGwOf88+Bhz4XXh7bH3+Y0vBKYdNAmiSECsxJFSAsZLYJmT6ii3AM/8OWHlE5we5hCCvzYPzdWVircrVKbTBx7UtUhIbXp8FN2tKrF4Sa1LYaUmyADFXTz+3cqIjfZQKjq6wCxfYlihtnlUedm14cJH+tBBQ9V/4+aj/WSuSpxlhl1DnyT6TS2KTEN/FGCKj30I5/9hAySxF2OUKnYjGLDWZT/GwA4B1I6LMFAUcuTpDEndWSA87q4opQdg9gNDnSlcKRkSP39TPUg+doONyPysAWoGSl/MQfRjZxG2n9Kkt0FIav5EsiVV9SXh+9pBy2FSlU15oariyKImtwSWEXc45h0ltRpFnzrrUQAOTulUSW2kgCAI8ciAkGdZPDAFbzwNe9jXc/YLvwIeNfTPUw05uAC0hwlNPWfRanGNSEqssKNwyqQ7I99ksy8JGskFy2EpeR6RBpq1Lhd2Q3bp6R980V2OnTo44ReJhZ1bYdUTYFaOS2IYg7MZtrZ/xGqQiqRgjf02b/1HZKimJdQ2EXQclsb70sBuAlFjKqSjCbrE97OrzZMOrDYWdrhA2hU7EgvNabEhkBP0uuxZQtoDoaejE/kCUAc7vDydHTgGObcGySMlMCnM6U22gEfOwkyqeLi+ybBt45v9t8RxyHHk87MjkbESbhEUKu3T/L1p2V6iH36uMU29VEgsII8+qQWEn00gBzNsZwhCWA2hNfQaT/pYojkQdTh6vuZHVESEny2GBsFzWLYc7G7K2v4uE3dsuOQYbJ4fwhqcc2fyJsmx3nirsxO5at8n0JQypsHt8tqYICTNhJ/0YwgGp4Nhq4lYLhIddboWdlhJrKomNKeyalwoB0YRGqqEUgUD9JKqRp8SMH76PNPXN5cFFzN8LoNdaeHw0QMKYvEswpC2ygyBI9xGTg71QO3JJLIEYf8asaJJUaENh59gWHNuC5wdqAVHNWN4MgNg4+KqcRRHahgTkVUNh+6sGBTxxS/csAqLQiXmsrIW+ofcLwk6f6MnJ81ytQfwsm4VOxA2xAUJKDiCGyYJxLpBtimwiLnToBBCv2kgJnVCBE90qhwVItYZYeCnCrqASAPMr7FoRdjnmrEsN9DPFSmKbhE60KIn1/AAz1YbysFs/UQ7Ntradh8l94djw+GxNeXC2rXzsJdJKYtPmq+I7sa0AQ4javSLsyvnHwg2TQ/jt3nBes2WKCbs0OIWw/5BhY2OyeWYoiZVoprBLS4mdFf1JJ+pgOY55foCaHb73qE7Y0bmmW8ZIKfrbNA7SjSs5R1C8AS2JtfKPiY7mYdcYgJJYy7JQcCzUvUCpgxetL4ptmooxvJ11X2pK7GjkaRvz4e7OGEb5qU7CWBYLPS2J3Ycx+JYLIABmHlP3U4Y9vSRW97CLly8sKNr1sFMGoR5GivEOI0voxHjuktj4d0gXP/E3jxRfVZsHWgDxHUvfI/e3uainA0+e0tXRNdHtVUdFty0r8rEDwvPfRQ+7Y9eP473PPSHcbW4GSdjJkli6u7aMwkvk5P+RA9GgYtylLmgKO8dSZaA1P2dKrK4wkgMaNW1XZYOGlNgm5LOc0EiFXdLDbhaohUm/c0EJtSCu3m1XYecKhV0djiobl8dgWfEdMRPUIrvhIQhCkkgKl0r6ZFEuciRhxyWxEcR4MioUdrXAQbnYXt8nCWhJ/uZR2LlkMp8ggw0JyJccPRke9+ho94IBADVGTlqzWFULQyfu8wVhp12vckE0W2sVOhFfWMnFhGUhV0Jjv2GcbGTMQTtHdmHhlF90zhb4Ce9VqaCSZc0qcKKb5X4a0VQWi3iqsMutnlCv2TA/3s8lsXQci5XENhnnUuZs5YKtxrXf7plFww9gW8AaQsiuFGnA1Yavzsd8u0RqL2Fr5zyjhx0AjMhNGbeEGVkd0IYK6/iN0cb/1pW88Z+GQlH6w4btacyVREfrkliJVIWdW0RJU25LdENhR9v8LARhZ1XiT6LXoFuKKVFNvrVyrihLzQGyCVYg7chP6c+aQHnY+XEVe6t55FKHnDskQisX/ECkh918c+/yVtBTrk0KO68WrcW7pBKnwoIsnspLDT0tiQ1goza0OvxDmuiDpMTQ0AlDSaxZYbeYhF2bHnYAhp14WapqLHLxWEgSZ1LFc3C+oXZ7o5JY0uDTFHYO+Z4pKGHnMGEHID4Bkm2yE4NLWgabR2FHy7JXHxN/TPrYAcDYunClt9DQQye8+GC9XCDJdJmsO1RwzD4ZmoddwY487KqC9MqeEitJei0lNlYq1MTDLoPCLkqJNXjYVUPCbhZl5S+mfMbyEA5WtBFTFN9FPYj6yipJeW1ViiZJuSAIS0KoOi9BmsjPX2OFXQKiDY1bgrBDoe0JjSxjrnkiECJH6IRMc2t4gWpbak5haNtrxPzxxC1ko6MbGF4FADjO+h2KQQ2wXfyuEfZ9ulJQljDO1RrpgSdIhk409JLfAYWcxwBRurTCQiXEAvGx3FASKxenc2Khu3e6ywmx5L3kPLIkFHbVwFFtR6/GaAk1dxnA0Ik0hV3Tklhzv25ZlmqLt+86BCBMiKXj9nDRVdf3PhE8IYm7RVskm6AveFPC+6LnR9fdGCLCblZ8tnaCCS4+NkrWveCY1bn/f7mgKAg7WVkx6iZDtnR0RWFXbf/cShScKBV9NkhR2Mlr0HYB28EISaU1joOiH5bHB5C5QYwHyL++ccj8gf52+nyMlefg0PxiK+xEv1snoRPtVD3qCmlF2A3H27gUJXTNwy5qU0uqP8+InirsAKA+HO5K49Aj6r5YGIJgUOcaFn5w9x5UGx7qXri75QUkdKKJEq3nUP5m9fYUdgBG3DhpphqLSSUjoExy5+tqt3e1nDwqhR0l7OLfjUrj8dMVdjWHd8YAkBKDOtmp7aBzGI0mM7HS1lbY9KTotkxYlaAE3soWpau9gk7YUdnyQpmHLwHoJsvGclggTtj5PoquTVJicyrslKpAhk5Iwq5zhV0UOtFEYSdKYmeCstq5rPsdlMT6njLAVmb05BiyhBRQ8qRS91U5m2NbyV1VubCVJZXsYRdBTJLGhfqiikLbExqlsBMLCEmiZnm9AikbrSkyWC5WTG1b+md2uaxyRBB2trAnWLEV817YnopO/HPIBcps1SP+idlDJ/q5XCcLxglhF8BGQDcnF3o+R6sltI2M4ZIsbRYlsbOyJLaL/YRWClQWi/iKX+hAYTfAHnb0HNHNG2NJbOu5+WqhpvvlQwcAiHJYDStHwufI898foRMtSsZsqrCLLExUYFba/KUJnrR1Cn9/+cn46hvOwZqxBSpr70NYxD8QgEo2b9b36ZtC6R52JUV20c1KIAqS67TdSgX5tBd+jhHoCrsocAKI91+mTTpFPlXqTZ+HFVtzH2u05hWhEwPgYQckFXaLFjrhEoWd14nCThuzpM1TcbTHhB0r7GLQS6PqI4K4IIRdkRhLywHnm3c+jpd94md4y+d+if1ioAwsA2G3KCWxJg+7HKETAIaceGeqFqOyszMQdpOi/HXPTFVNHtaM64RdLXVB7qoSnHSFHRN2AjEVZQdx1RLtEnbbLwGKY8BRTwOOuDD+2NZzotsbT2v/2DqBUJ5gdk/4W+6MuOWO4rb7DbJ0RiJ1wksXp/U5FN1IYVcXCuLsCrt4SibqeRV2TQg7Oz7pU/049bATg+oshtQmgNdhSWwhiErCJOQxZBlQi46t1nHVuqcWV2XXTqrz9BJYLomNIMaflXaksJscaq//04NA8ijsqF2GUqDJ/zO1bZPKtBuQ/ZzE1BFJg2z5VKGImq02omQ+g0qqoKW2D4IhdhZQhZ1lIZ6ivtCbPHSc18KSZDiGLImVoROSwOkKNGVUUZTEVgK3fWKoZUpsH3vYpc37jSWxrZXka8bDPuS/HzgAAFhvSJaWm3EyKVaWuecOA+kl0jzsUgk7W4WujBCF3Uw1bDPtlk0+55SNOHHTZFv/u2wgrk8ZNjZsS7/B9Haqb/hECjvtOiiUMaQU3l7sIelh14nCDoja/f5G+DlGrGr8CZrohF4nlkElJ8dPSRaXTHM1ANhyTvK+Foiq9+K2E/2YCEohCbr9whpr8UpiiS1Jhv42FbL/lq8hKw2LI2FfJecF8v4uEXa0HTBhh2R5R318S3hj373Rc6iXi5i4/PbxsBO48X8ewZ27w9KrckmcVN9bGgq7vB525DlFy4spPqQHVrOSWOmtUWv4CIJwYj+lPOxIGUTKhRPzCqQgoRN1t4vJev0MumMpJ7idLOjH1kW3aSlrK0xuBt56L3DlZ5Ok8JEXA2tPCNvVMc9o/9g6gfTYmxGEnRqsl1dpdcl1Yom6qeRGYQhK2l+bhWNbqgyqEUiFXd6UWE1hZ/SwI2oLVSqUPrDqHnaqhIAqBGMlsUJh105JLPGLdIXCrg4XviAw5DFkmZRYlqWCKSp1H5VGE5WK/vm5JDaCaEOTVkjKVoNC5JeaE5JwmK9pHnYZFJPUxkGOW7JMNkooo4Rdj+YFI3HCzp86XBFs+kRvpBgps+QC2KS4LWkKO1VO3ueLiVaghN3KkRKsxVTYWWTzVQspkOEYiZLYboZOaOSaJOzmPEspSrsfOjEAJbF62ZWJpGxREgtEc2q5xthgUNhJwu7xmRpqDV9d94uWzGiCrrDLUhWifEor6u8ZQZq042HHyAhF2IXftZNhPhaSWPRvx/w/hWE1/szXI8+3uufjwFz4Pis69OCUCvJ99bCNDLcg7Kj6yws0sQgiwc60UNgliJPnfRx44kuBJ70q97FG1Xvxkth+3xSThO3+WVkSu0jXK02JbXRC2KWUxMq5QUHbnM0jlGoC2tb6MXSi62fdti24thVJUleI0r29dwN3fA2Y2qZS32qeryYTHqIv7+u/DP3uhsolYA6ifGERCTvqO9LKK4LCssLGLEi14aKrJK2qTER2doaSnpGSi9GSq6TNq0ZLkTm1SoxMJ+yyeNjVXVbYAYjvWHajJLZdwg5Ib+PFEeB1PwjJk9JY+8fWCUaEV0l9NuxkmxDOg47VoyU1KUoN67Cs8LzVZsLvDEDZkiWxYZ+X2cNKVxVopQix27kVdpKw0wi4WOiELIkdMpQc5CmJjRbNji/9/Apo+AGKtqU87LLugJULNubrHioNorAzkX06QcclsRHEjuZoMANYYUlsapl3C9DUVCBS2rVK/AXidhly0u3qHnZeNTQttCzzNdANaIRdYyoKANIVdlKdcnC+rtShJlVDQTMHb/iD4a/TCpSwGy+7kWoXiCbmCwWVUO0nS2IJ8QqQktjRLvYTWh9eFCnZB2txH7V8r7kMCDu9rzZ52GUoiV07Hp9bHb46uWG9UinsajFj/KVVEkssXIDWKbFA+B025qOSWLesFMHtlMQyMkKWxFoNXHrCesC7M7y/ifeXZVkYKjjEP9GWD4RjndqsHVbjLfWEkxZKMZFHm5D90d6q8PrUS2K1NQC1eDC9t9y4OyQVdvpc7cQXhj9tQK15/cEaYyUJKrmAoeIifR66vpB9UDucjOIvRP9NS2KBsC3N7++6wi4WiJJhA3mpoSdHTHeMfem19dvvA599MfDPF+AY3A8AqDd8NcjWCWF3011houywUtg1elf6kgXthk4AsZ0wGq+tktNaEB40wWot3Q2UDV6QAOF98cFaKndqekrsyCpMF1ZhNijhrlVPzfY5Bh22iZTtQIGz/enAmuPC3xtO6fz4JGxn8cg6IHxv2WnPPEakzMuQsCPX5jrDTr0CJb0AlEUATR0uXNvKnhDpaoOciexv6mHXWmEnyZWIsCMlsVVZEktDJ9ooiVULzIbysKvBVZOsSg6FHX1epe4190vTFzNcEhtB7I6PI2yjNbhtJ5fKyeW8KonNobCTJS1+QBRohnIgRVr3aCOvNI5aaUr9WV1zsrqdRtg9Nh0tZEwLYOVhN2C7/60QSxqsNeJjRWnC8B89BLU30TYydMJOpcR2M3RCCw6Sqpv9ohkXHCu7RYKE7MdSS2L72MMuLYmQllRJFU+GEq3DpuLzlGPWJedSU4SwmxOqpYJjZfeaXQgkSmIzKFDE/8gkcLhFpQjutGyS0QRiHXHGlnF88IqTiTKpeb9Cy5RjaiA61hWHSehRRNg9dijquzpNIJcKu0er4fsMJQi7dB/2c45albhPT1nvZmlitCkW31Du95RYndSkxNOCgirfMggBUiH7aL8uEuNISSwQtaUue9jRuUiWDeSlhp6MQHRg89eeEJ+UeTW8qH4jAHFRCXKkAUeRWHtEKcLIECXssnVyPUG7HnZATPo5QXYbEgq7lLS0NWRH8Kg1ZDdQDtg1QthpixY3TWHnFPDh467FGdV/xIGxo8BAPFjEy7Bb2QoTG4HX/z9gxw3tpegsVVgWMCLKYmf3tGy/g4wtK6PJv8m8WkGS8WJQUiWxcPItzqjCCIgWM1SlohQcBoVdEwI6mRLbTGEXlcQqj5A8k0JSzu8GYf9fQ0FNsvIr7EhJrCCJjKa8+vXMJbERVEls2EareppnDkQlsYKwU+czS+iE2GRqRAo7NcGnxLRs34qw67JSy7JwcNUT1Z/zk9sBALaVbOvy8z4qFknlgm1c3EdWIOL6HxB/nVZI+BNRD7uhyQU9FjNhJxV2UdovLSnrbkps3LKgIPq/vWIYHSt3uPgxoa897FI8nmlfroIXWpfE6n5r29caCDuhqHx8trY0E2IBIgSQhF2GqhAtWAhOSSl2WGHXQ4j2uH7ECddkGavFVhDLFRrcExvrCiOKUJuvNxAEAf7jtt34+M33AYivH9uF7Bcfroh+0p+JP8EgOvk/zzgGl564Hpeftjnxevqct5uEnav5xMrf/R7spM9nF608X3nLUcKujTZG18RenaTEjmjv02XCjiQYs8JOgBouu+VR4Lw/Ck/q1OEAgGP8uwGIi0lMuGso4NIT18deZ8WY6ACWjMIup4cdEDMZpoqc8XIhnlSWorCjE4qj6eRCTtIoYZcoiU3xsAMwbY1iBsOJ3Y5lC2oG3c8lJAuBUVEWO/MY8R5YfqXVdPK/aUUThSFVqYGWxLr5du11GXnDpLArx58DZEqJdVToRIqHXXUGmD8AADiIUTT8AL4fQGxgRiqoLCDlPLYfedjJ3dCKCinINimJUtI8perSU9bC9+WS2FQohV3YRmtB+32fXNzKxW7kSZglRCT831rDR10ng50CIIOodMKuB+dy13Gvxs/8o/HnI9egGkQBMToBRUtiAWC0ZL7O0nb/B11hBwCf/4OzcPiqEfzNC0+Kl8SWF1ph1yQllhDN+0Q5rGNbbYevGOHoCruwzTw6F7aFtsrQs5bEWkuMdMqCNAUt/VsSIBlKYumm95O3rzaGLZhKYpdUOSyQCC+J5qxN2qqmooZbUh52rLDrIfRzldH7a5IIPCh5pyvshsh4+6Pf7MUfXPsL3Pg/Ycjjmi74b8rKsAdmhRLZm44/wbBp/9rzj8A/7niicUNan9d100tMKfT1MbbP17n63GnxUmLlhtN8Z3Mv+j9eLUnYJRR23fGwGybfG4dOCMRYTNcGzv0j4M8eBV4WKuvWe7vgohGWanpRSdRZR6yKDYyHrRSDK51c9VtJLJlMrSY7teNDbtQYgVSF0nlHrVa3zzx8ZfJ1RZkaLDvRmGPhHhqalo4tRyiFXU6fwuUIpbB7LGrDy7Ak9twjV6Ho2jh2/TguPGZ1+hPld1OXCjux+wcnH2GXCJ0wqIv0JFn6/CYDq9yZlOWLyuh/aEX4e35f+APgQDAapnj6QeL/M8GJ1AHSgLkWuKoEsqr6prwKOy/yS+OS2HwQbcgRSXZHbFzb7NlNoYgPcS4qORR2chJV9XxSbq359wCEsEtPWe8Uc+tPx4tq1+DH9hOVrYRpg2tCI3TSSBc9dKKuf74Bxmlbp3DTWy4I5zMjpK8sTy7sgTQLnZBpvzVPVXlMjRQ7LimLQdkahH2yK1Kyd82E10p7hF2rlNg+3oBM86ikY5kkQDIo7FzHxheuOguXnrAe//v3jjY+Z0qkAlOFnSn1eVGhh05kOcdCtTJuEcJOetgxYdc76IS6l43ooBsFsQComMJuKFIGVz1889e7Y69xxraV6BQyjOexeth+CkEtHvykFHbZxuCEwq6LSidXE6kMShK7TtAt2gZCgSrsWve3qdAJu3oLwq4bvvKI+8Ny6IQADYZRk1nLAsY2AIURuPVZbLEeDSeuYkCuBgVMDRfxpK1T+MHdYQLlltVi9zWmsFtgk2IgbvCawQ/K+L9eA6tGo9298XIhTtilfK4Lj16N15y3DU/YOIETNpHdaHmRyIZuOB6X+AHpaKpEWY6gpGwnHdFygFLY7QFGxIRgGZbEbp4axo/eeiHGym7zzl/zsCuJZMBaUMg38OpkhdrZNCjsYsb8rUsw9JIB9fewOL9zj4cmsAAOYBR1kuIJ5C2JJSVcasOmgLpKic1O8ABRH1Zp+Kpf45LYnNCu37WrplKe2BpyUjRf8xAEgVLYZdnRLBJSSxK4Mf8ZtxQuEBLBK93fyIsU6kFU1mtoVzQtGkhf/OqhE8tJYRcDJewWrSQ2qbCT522m2uiNfx0Q914DlCVANQjb0FiKOrP5a7ZS2PXxfCZt7LKdkHwNyHnMsDEFAKdumcKpW9L7t8jDrpoMiVsq0D3slLqwyZgp+vgJRGsG9rBbAOiEelrysQZK0sXGGDpWF0aUQGau3sAvfrdfPTQxVMBlJ21o/7gFxkWZ/gzK8AILjhUAlQNAQQTrSf+xjFU2+jyglx52jUEpidXWCYsmtKFrkE6CQG0nFBnJ8KdESqxo440elsT2ocKuJ720F1NekC/FtoHJw4A9d2C9tU+UxEYLtsnhAl517jb84O49eMGpm7BxSnQEgddZhHCn6ITMSZlMHb56BJg9EP7hDoXfjQGuY+Ptlx6X/rppf4MsOPTQCQDVZgvb5YhYSWwfe74sBEaF+mb2sUg9tgxLYgFg7XiGDQTlYSdTYgVhBzcfYefE1RnmlFjNmL9QztRn6aSBUswNC9PguX3A7F4AocIOiCt386XERh52kSWCC09MsqRKLuvOK1XY5UuJXWKLsMWETrgX27+eaUlsg5RNZyFgI8LOU+EMMRVqmsKuBxt5LimvaaawmxyKj71pi98odEIo7PzBWEzkxuia6PZilcRSokf0A3Jz2fMDPLgvnHt2NSEWSIROOIKwq4up+PhQG3MO2p+akKFUdMmi2fUtyftESWxn/boqiZ2pLV3Crh2FndjYmxQKO88pK/Vzu4ngjAzQz1VGP/bJkRSFnax6AETohEgQrTSUj+pNb34yNq0Yzh9gY4DskwLYOIQRrICwRxkThF1OH2v9mLpJPhU0D7vGoIROaHOnRfOwU0Rah6ETQNj+G/NiA1b08zJQcSFCJ/qQ++gJxegZFF0K4iJfi/3hRSUG2yoKmBgq4Pztq/E/73gaPvCCE+NE2ZJQ2CV3ZVuCEEFXnn4Ytqwcxnuf+4RQhZBTShx/3SyEXTyVjmK+WenYcgQNnejnHemFgCyJnXmM7K4tP4VdZkjPJlkSa4V9SBWFfNefKonV1UUGhR19nirBSJ8gJgg7ScANSyVCAOwPjYwlYScn+6b/bwonUh1TSwRJYORW2InnVeue+l+zwk7vM/n6VnB1wm7U/LwMiEpiG4p8BbIRsKoklijsYuXWukdjr1JiyfvWPV+R06Zd2aJrx0i61Sm+QSq1XbyWt4xKYmMYIcmBC10SS0MntE3gcsFWhOy9e0JSo2cKO/HeyhJAEHbthU60Kont4/lMMwWt/rnV5+xsUbdCEHazNU8lP+tl74uOhIddhsofsXG4whI+pXY0VzB5+TG6hLSS2BZj1oaJaExOJewKQxgWiaH75+qoNXwUXRtbVo50hawDIoUdABwKxOZz5UD0BEPoRDP0UmGnBy3K306eDeUlCJ2gW3QPu3ql8yBQeV3MR6rQqCQ2biOkRDQd9u20JLa81HxJM6AnvbQp5EBhLAyWWGMdQM0L4DeqsBFOWCaE7Ff+NpYvLEbipiJzauHOLJBDYRdNKrauGsEP/veF0WOVg+HvdnaZE35MhpLYJgo79rDToCZAXtfq5QcWsiR2do8KUuhEkTPwKMYVdiVIhV0h38Crh07UDYSdUwBgAQgMpEZ631nQJk0xo//yRNhXzT0OADiA8FxLMsa2kM/nKaUktqEp7LJ72MnQCV8p7Iw7kPpgzyWxEbqosKPm/VWiwsxbEmskbmVblzuvPdzIkxteDT8q601bBE0OF1TiYhphV9RKYttKWB4EjK6Lbh925sK+d6xaIk7YWZaF8aEC9s5Uce+ecFzrvsIuvuli+VH/B7SpdFK+pVXz42o+04f9nRq7DBuCjva5u/Q5x8suCo6Fuhfg/r3hmD3RjvKxl6Cey0C2yh+tj6zY4Xdacs2p1owuQS9fzlgt9rwnbsS3bt+NWsPHxhWk/Q+Rcu7CSEyJBwCHrxrpqmqbktUHxdxPBpAB6Fhh193QCbHJ5g+W7URZ+44WTREr++HGfH7xkg7ZV0nCznaj19LneT1Q2G1f0/6m9GKhN4SdQdGlIBR2a6z9qDd8+PWQsGtYRYzpuzxLTWFHjTZzl8Qadj9lp9eOj0sGtUihiYdd3kXxwIP6FPp9PMFdCFCFndxpW2gvon6C5mFXVB52OUtiE+oig+G+NOZvzEePZ4hf1yfsMVXTyOpocwHAviCUrcs011zlsEC8RESWxAauIjDye9glQyeMai5W2KVD3x3PuFtuAi2JlefDlK5qQomUjRq973RyoqclsWLy32iusANCBcRD+8PJZVoyn1yo+EG4iTYohti5sfmMMIhswynAii0L+95GD7uoH5gYcrF3porf9kxhF7c1sOSGhUhl1surMyErYdeP/V0zhZ2uOM/rL50Cy7KwYriIx6aruE8Rdkvsu6ObXkC2xbNGqFQQfn9cDttjtKmwGysXsPPVhg0NKvAYXYOxkotywVYijCO7TETQcvB9wXh4Y25v9ATpo56VsHN6p7CT89ggCMm6QdkUGypG39FYyV08gr1A1iCdiqiUwu5A+Ls4Eq5fgJ6VxNpkDnr8xgW24+gCenLWTxThCCa/lxhh5/kIxCSjUCwlJ/Sx8oUOIoQ7hSLs5qL7ModONPEXkWRHOwo7fcfR0Pm7Wj0/BZfEaqAkQpfktwML6UE0u4eoRCcX7XCWPApxwq4URKqKXLJsV5v4pZEVrqbEyzCZ1/vqWAnBxCZ1M7AL2Iuwv5JqtlwJsQApiTUr7PKEFACEsGt4mK018eZkD7t06GNQV0piI0/BkYztvKTKm1NIsoSHnSEpuUtQBtZ+dCxpCrsNk9H7p5fERv9b94Jo97/P/XVyw7aBi98JHPfshX9vixJ2guwgcydJzDx8IFworOw2YUdJJt+DJSo2ZEns+ok22rF+Tejo65LYJtd3j0pigSh4QhJ24+2UKvcSVG0fBG0RdjN++J22VYbNyA6dsOt0LVs9FN1esRWWZWHNWHR9dJ2wI4SunPth5rHoCRVxPBnXsa5jxxSAvUiJBcJ1b2NAxlja/0wML+L16hIiTZJpJvVzptfSSmLpnFOVxHaXsDt2/TievH01XnHO1r4M2unJEb//+SfiH276DV5ypmH3VKQOTmEGv21EhF25bNjRjynsejcxbwlJHNJU16zqK1Vq2Ug+1gnZoe9mGBQReiodhUy949AJASpb7+cSkoWATPmrHgKmHw1vL7R5eD+hGPdjKIiS2CoKmMhVEptRXeSWARwkpEbrnbCEwo7uSE4epm5aExvhVBw0/EDt6OYuv5DXFSmJrSNS2FVUIme2iVyJlMTO1cLv1jgYc0lsOhKEXfslsXJMma9FBCr1DmmGYkxhZ0hmLWgqU1NZeJdQIH44rVSfR64ZxTd/HfaFGybNE1hK9tUavkqy63d/nb6CMXQi6hd1JVUa+do25HywUYsp4mRJ7NpeEHb9PJ9p6mHXm5JYAFgpSqH3zoRtRE+CXnSosTyIk89NS2Lj/dJBL3yNJffZBg2p5cttEnZ07SfWpqvHSnhABOUcvXasvddNAe0T90qF3SxR2EkCsTSe+TWLjo15IYzopn9ifFPMHxgPO7pxFPMzXGgoNXcldyl0ArL9z+0Lf9M5p5znJQi7zvgKx7bwr688vaPXWEz0hLBbM17Ge55zgvlBYWI+aU2j7vmwxGBbLBtOuiLs/Mwy4p5ANiwp/YWVveE4TRR2nZTE6gsUI2EnPew4dKIlKDmsSmL7j4FfEJQnwmvCqwGP/0bcN7moh7SkoUpiQ1+kAqTReKGzklhJVhR0wk5fyLQOndBTtGI7kpNk42ViM5w9VkjYCSVcbnk+tQlQKeEuag3Nwy5n6ESl7mFW+IgZJ4FcEpsOfQzqhLArRiWxc+p8ZDuXUunp+YEi+0qZUmK7Py9Q46cfxEp7TTh6XbRYOXXLCuNzKAle83x4gqAu9Hm5Tl/B6GGXksYIYEM7BFozOERhR+aEMiV2XZbUcR2ZFXZ9OJ/JqrALgmzBCxkxNRLvT9a0c156CfoZaVvKobA75IXf36ISAMsBbZbEpuLsNwK7fwWc8vvqLlrWfMph5vGnXawlbX9vIDb2ZqnCTgpPchB2rq3WoKMZN/OygI6xDaJi7/cxdiXxUl1Ugp2GQeQMG0lAD52IEXbiNRuSsBNVb8t8Tb7wn14YZk5Z06h5gfLwGBoyEXayfKGOXqbBtYRsWKKkDU4hqrXO+r9NS2In8x+TbQuvqpRFO6LEnLqBsJMLEFbYCdCSWK+PJ7gLAcsCRtcCBx9UQQSssGsCVRIrUmIVYefmu/5USaxU2ElJuklhB0PZYBuhEwCw6qjo9tQ2FBwb1YaPquhDcivsYmpW4WGHglIC5w3EiTzsfGX8byTsdOUFJxtHKAyFZIJsWx2FToTffaXevsIOAKYr4XUSU1rSHV6gp8p7quyT7cpo8wHg0hPW4/69szjz8JWpBLZlWSi6tlDXUYVdfy8m+grUZsVAcugKt3XdJuxUSWxNI+zC41o/2cb76apTHVLZ09cKO8P3EisvJhUsXZi36T6UNLFzSYBuvlE/qWabUNoa4fF6+FxW2PUYut9gxtCJVIyuAV76ldhdLzt7K35w9x4cuXq0630WnUs9LhV2HZTEAuG68+B8PfH6ncKxLVhWyN/XfV+FT/T7GLuKbCBMLibBLueFgR/xFwbuIRP00IlYSWxvPOz6HQv/6UVJ7CRmUG94sEVK1vCQqSSWqNMarVUiPYNe1pqno9V9NiikFLRdw/7CECHsspfEBkHAoRM6FIlAPOz6cYK7UBjfGBJ2EkzYpUMLnZAKu2pQyKdwpSVAQZBOVuikRobQCZ2IcOnfR14c3T722XD+O+xP5A5p7t1LQ79eDVzVT0kPu9wpsQ0Ps1Wxa2tSdOkLuXa9NwYV5Ylo53x4qvlzm2CIhE7M5lTYUb+6mUojcd9CKuzo+x4Sx5KmsHNsC2+86CjjYxRFJyTsag0/2v3nhMaFgzF0IprPUQ+50ZLbfX8vGjoh3t+3C5gcLuI15x3enlday5LYDgmCxUS9yfVNx0M6v+7CvG3bqviGRdeJ205hO1Bp8DFv7WaEXXyN8NBM2O+wwq7HoJ69QE+qxS48eg2+/UfnY6Kd0Joc2A0xLzj4UHRnGyWx40Mudot/66aXmGVZKNg2aqIcNvKJ7e8xlirsxhczJIZu5EplZdsKO9H+5w0lscorT/RtTNgB6FHoRFOIhUDJasCuT8NGuEgbHjbs6MuJiN8gBoeLqLBTf+eYEDja4pniwO/C3xOb2zsueqEY1CJyIS29oSRqng8ZHFtihV0IVSrj9bdJ80KB+JoB4JTYZlAedoKwCwRhh4IqH8wE6lvj1UlJrB5AIxdwsgSj9YJNJw1iJElxJNzRfeb/BY68SJUKKg+73KETpCRWTGLrcInCLl+5viwrnqs2IoLIpOhK2AgwYRdDiXjfjG1o+2WiktgGZoWnYFaFnevYkPzvtCLsSDug5EQQRIufHpxL17bIsQi1X4eJdgUSBCUNsft997+vQMd5g+8XLf/amOJF2BGoKkxsVthuGf/950/F1Rce2dlr1lMIu36ezzRT2NHNcL+evL8DUOP+oYKzuItkEywrOu/Vmej+ZqSsVslzz4FwvF3BCrvegs53gM4Vdik4cs1Y9z03BV58RjjfP+tJwv/rwO8i5a5S2GUn7OhGSDcVdkA8bFHaQfV7Suxw0VGJ5VeefliLZ/cQtpPc6G537iWVedIPMVYSKwk70f8rm6rlzVcs/ChUGEbDKsINahiaf1TdPTJsYGlpCVd1Wty3BAi7PDt4up8Uxb77wt9T29o7LnqhGC6atJJYudAGWGGnYCqJXeZsflNMEpLZKQIjaxbvWJY6pNRbKOwckhKbKxWQLlq8arq6KKFCyhI6EZ/QJJREh18Q/gBwbRnyIBV2eT3siJqVlMTWPOlhJ0tis72unPzNVBuqdHHUtMByy1CqBIAJOx1UpTLa/vUsCdRK3cecUjxm70uLro1K3cchQZIVjQq7anwTrAfzAlnCWqn7ijxMU9hlhfz/asNHQxDU/b6Y6CtYzUtiKUm3fV13zdtj70UUdnCLsLJarJggF1CpCrs+Vic0s8Kh5GeXFXbbiXH/SMnt7Pz0Ck4xPOfSqkfel4ahuLfZr/d6AOzFLbFbDlCEXY5E3yWGt15yDJ563Fqcf+RK4NdDoR3Lgd+FlTZy0yyPwo7Mz4xztQ4gx9O6FyixSr9vilmWhRteeybmag08YeMiVzOVRiM7HqADwk5wPkbCLh7U19e2Dl3EwrM1loVqIWxwQ9U96m4jYUdLuGTgw6IQdlojydPRUs8Sid98G/iLKWBmd/j31OHtHRdlupuETuglsTJJseBYqal3yw6q7LnOBpdZsGJrdHtic+ipyDBDXpvCw84RNgBVFHDE6tG0/0oi1h9WSGmFrrDLHzqhExFpXl1ANPnpOCXWa2ihE5rCLmPfJMmg6UqksDMSRJbVUpW8rDG6OrrdwU6mLImteRHplidcRY5JczJ0IkbYSTXRvEbY9aZkTR7LoXkDedgGqE1FQ5Xr9Pdioq9gTImN+sVj14/jsKmwj7jk+HXdf/8YydSlhbseRqRj0BV2tCTWcroyF5kaKeLiY8NNizdceETHr9cTKG9torBrNmclhF09cPC72bBvW7vUAjUGDbGAkDoWNUCxTUwMFXDB0WtgO060Xn383sjHzLLjCv0WGCfJs0b7kg4gx+iGP1i2E0euGcWJmyYX+zCS/sbtWsvI+fes4IFiHnZaSmwfkty9wKIwEtXiCozU9mCoEp4oL7AwMWoi7AwTjEXxsOtGSazopIMA+NofhxNGAFhzfGLnKzNaKOxkJ6WnxEqfJw6cIDClxPbjBHehsOGJ0e2JTYt3HP0AzcPOFoNPLXDzEXa2HaXzyokSkJz46WX4GQJ7dIKuWam83AhQHna5U2KJh51U2AUkdEJ42GUt15cJadOVhgo5SC2zKA6TzR8m7GI4/38D118BHHZWRy9Dy7z3zoTnN0/Zi06KmUtio5JCWHbPNlckWSiVm51ucMnPVvcCNS47vNmxcIiFTiTHece28OWrz8HP7tuH3zt+bfffX/XNte6VxqkNmnnz46pioA/nM83GLpW4W+/JnO3vrzgFN/9mL556XA/aQTeQCMMrNg/DI76kj2McgdBrtJVMzMgOSjY3Kj0riV0wrDwceOzXwL57IyX+yOpcm3zjvSyJtaN1Lwc79QCUWIPVPvEsOQs5bplKYhtaSewyX5MvCmFXL00CM8BYLVSYVVHE5JDhRFhWPLkO6NlOelN0QtjpapfpXcDBB8LbJ7wIePLb2j8uStIZFp9uisJuvtWidjlCLvi8Rn9PcBcKa44NPVEqBzpe4A885EBUnwV8H5YYfF563vZ8HnZAeJ17tShZCTB42OkKOznY5fCwa0LCyVL7eanUzas6oqlpgryMe9jlLYkNr93dhyLFVWoJZotNjmWNo58OvOo7wIotHb1MybVVUtueaREqlaOd6xtJsZTYAin3puqbHpWsyffuWkmsuHbC0Imwnevl6IweokXoBBCqqy55Qg/UdQDZrKh2T2mjFjdpKbF9vNjJmhKbYYzLi9GS27t20A24msKu1WcnwoB9QVS+uHa8f5RefQl6fZNNyn5S2MUwJRSnj98b3R7NR2pT/qzbwT5y3VvzIoUd2050ETEl3HD7cy+9KrBpSWwfj2FdxKIwNl4pHDgma6GH3SxKmEgzPnXLGmG3CLsSXSmJFZ/hsTvC3yuPAp7/sc6Oq2XohJQGawo7ZQTOCjuFWEksG1y2hO0Al18b7rKd/OLFPpqlDRqFXj2o7n79xcfnf63CUPga8wfCv+1Csp3qHnaqJLYJYaeXxDYhJuTkR5Us5lXYUXK8IcuDDSWxmRV24bUrJ2cl107/34JhF48RYfOTOn4Jy7IwUnQxU21g18Fw9zRP+qU+LsXUnyaFXQ8XPvK9D3UtdCJZEsu7/wsIqqRfDKUL3UxptO6X873mIIZONFPYLXPfYb0kttX5JaETckXg2BZWjvYpcdQvsKyoMqI+FyVe9qvCbpVIQ3/sdmD9ieHtsXzENvWE3NDlBGZaWSY97Nh2oouIEWsdnDt9/k2JQJdLYk1YlNHNL4eE3Yr6YwCA+aBkVtgBIUFHNw6XgsIuz6SAmgwDwN67w9+rj+78uFqVxLrNPexYYUegSATiYdePE9yFxLbzwh9Gc1BifW5fdLud8n45QEqFXTPlgVzsdCN0gr68LIkVhJ3sZzKDkuOx0Imwn6oqhV0+DzuJFc1MtIvsYbcQmBgqYKbawIP75tTfWaGrTmMKO0pOKPVN786jLIGNEmu7GDrBu/8Lj1i4lFwELOA4r+aSQbQY6ZaHnVcL5y76Bk4/Vww09bAj41w/k5LtQn7+akaFHRn/HxcKuy1Tw7xhsBBwy+H1KcMTgf4lH2RFzYM/AzaJDb6cIVV/8OQj8ND+Obz6vMO7Hugix9NGLCWWbSe6BpMSrh1kUtjNi6CWZdi/G7AordgfCr0UVnmhwm4O5fQJfWxRay3ODlpHCjtN7TIjknG74ftFve8Mhp+yk9IJO/awM0DtvHv9PcFlLD3QKHRpsGq77amF5esows6UnpemsMvuYdc8dCJ8TCrs8nvYydS0miIVqyig3gjg+YEi7soZyZHhohNbdEymqbWB+DW9GJs/ywTSVPqQILryEHbZFHaVMHgF6KnCLiqJ7VboRLSJphYTA2CI3TeIJVQvosIOyF7K2PI1NY8sHUrR04cbtE1TYkn65nKcs8l1CfWwa4WXfx2V1Sfho95lAIATNi1y4uRygTw3lLDr15LYlUcAK7aFfeh//Wt433i+9ey6iTI+/rIn4czDV3b98JSK3Q9Yxd4LlEkacI6gkQSaEnZyTAvioUL9SnJ3CYsyU7SE+elqP1TYzaEUS42JgS5qe+hV0xS2E6ZPSeQi7MikAogW7COrOj+usfXm2wJycaCHTrCHnQGmkthlzuYzugip7JIR5u3uTElV2Nzj8delSHjY1eL3m142ETqRPjQUZEls26ETRHUsVCaVoIi656MqAieA7Ao7y7KUjx3QgrCj40cnu4OMptAV86mWFwYMFeLj0nCR/E0Ju2bqmy6hREIigOZEdhYUhWKv1vCjch1eTCwcaEK1XAQspM0K3TSRi/dO378wDEC0Iam2ouhnMkte4yY1tNr4qS9PBYYczyXxm0XMsPVcFK76ASqbzgUAnHNEF9YhjNaQY9QgKOwA4MiLw99y41iWxi4ByHVvte4l7mN0AcOkzxjugHBNlMSmKPfqc9Eaph/HsC5iUQm7IYQnoWKV0xdndIKzGP516jjIe+fZqaSpYEC0YB9Z3fkxjRGjz/GNiYepXw4Fe9gZECuVETvS7GHH6BbkYCQJ+3bLMeX/zYvSWhPppEqktJLYHKETzYiJqCS2TSN+A+lSRZgSKwMngOyEHQCsJj48TUtiQSZu/brD3QfQSdN2FXa2pYWPLLSHndukPLed1yMKO0kC5ia8Ge0jVo6/CAo7xw1TjYFo8d7p+9s2UBKqh+qh5OOLUfrbLWRJiV22JbFSYZdPqenYFq5/7Zm48Q3n4gWndqHSh9Easv1WhIdxq0TfpY7jnxv/e/1Ji3McBqhQNELYscKuixjpFmGnK+yIWs8pRBsQjcry7N8NWJSZoj0a39Vp2E0Wr3SgXswSJjoY5mF59fK0bhJ2lJEeTyrsXCeuDpCQpWwjRVbYKahSmUZUQrLM2XxGFyHDDuakwq5Nwk72J1JhZyTsNBPyLKETeTzstJLY3Koj1acHShFSQRHVhq8CJwqOlWuStXY8GhuaKux23Rrd7ucJ8xKHTtC1S9iNlNy4x80iKeyivzvbxCm60Saa3Ehjwm4BoTbmaotnZO1oi/dutF9ZmmQi7PrZ5L6ph50pdGIZzdnyetgRlFwHJ2yagM1ExsJAznnk9dmP1yLFlrOBY58V3j7uOd2xeOoSpGK9Qgg79rDrIqjCrpNKQX0NpJfXSvuf+jyXxAosSit2dcLObVKaRAm7dkzauwXK7OZZbLvErwmIFDbD3SiJ3RDdpuSdgCxdk6U3ErPVcAKnm3sva9D0OGbzGd2GKoltQrRlgV4S25Swyx46YVlWjLTLFTqRt9wg5uMUqkyqKAqFnUiIzUmMrBmPXnPdeJP++ayrw98nXZnr9Rn5oJfA5iHsqLJSDxRRbadeidp3J0llLaATdp2q0iU5V234KhWZy3UWEHJjrl6Byspc6HFe9sOSsOtGab70FaqYFHZ9mqDqe9FcrFm4klftb5++dqFKYqWHHc9XlywUYdclVe1iw7KAF34KeO0PgBd8YrGPJgY5d5Ve7fQ+RhfQLYWdzlnowSVyrUNLYpd5H7coo1thdCr2t9+MsKMd22KWMNHjyEPYOdriWSnsukDYHXYmcNE7gFXbjQ8XXLPCTibejZeX0eSmFWzTbi1/P4wuIVES2ylhJ0pim3rYSYWdHOya959l10Hdk2mY6cSE3K2UJQe5J0OG45AedrIktpQzEIcq7I5cM5r+xHP+ENh8JnDEhblen5EPK0ei8XJyuJCrvFlX2MUg23+jAjREymYPFXb6cXfq+1ogqnepsOs0eZaRA3IeJ0kOet9CH0PlQPi7G4SzKomdTj7WrxuQNEDDWBIrvVCri6eWXEzoQQbL6bP3GxyNsBsEOw7bATacvNhHkYBU2Mn5qWPnq9ZgtEC3CDsqWrLseIgmQAi7yvL0KDVgURiJ0rhWDtps8Uo7NoOKbMHQqcKuUQVqc0BdTBS7URJrWcB5b05/azvyy6E4JBLvUoM+liNioROyJJYJO0aXUOiSh12iJNbwOtTny/eJSqH5JHGs7GK6Kgm7ZiWxInSi3ZRY2w4XF3KRBelhF6AiQifKOb3Cjt8QJVc1JexKo8BRF+c7XkZubFkZjdWbV+Qjp5sSdlQ9ugAediOaoq5ThZ0kt2sxhR0TdgsGuTFXX0zCTi+JbXMsoEgrifV9oj7rM5JAXt+A+dhNoRPLqSRWjvPS+L+HSmNGhxg0hd0ShrSCkpVkrGDvMtYcD2w5Bzj0MHDERe2/DlXUDU0lPeNjCjsuiQUWibArj65ALXBQtIRk1aQSkaADdScRwp0ipvTLQ9gRA3jpX+WUFuSzyIWAnhJ7aF4QduVlNLlpBdlZ+B6Z4PL3w+gSlMKuyymxBcMmBvX5IqRYq/Y8Vi4AB0NVQ56S2LaSM51S7NgqKKJGS2JzKuye/oT1ePbJj2Ku5jUn7BgLgsNXEcJuKh8hQVNhR0taO1hgD7thjTDs1Pe1SIKgauxht/CQJZO1OXGHtfAbc3ITd/5A+LvdzRsKWRJ763XAj/42NIW/6B2Rfyl9336BvL5t11zqSktivda2DwMHSdBJpWY3iF9GbyDHKFmyPggKuyUKSdC1vaHMaA63CLzi3zt/HUrYmdYmirCb55RYgUUh7GzHwWPWSmzCYwAAr5mfm7sECbtcCjuiCJDqmpFVC2J4npYSe0iWxA6xgkzBWBK7vDsHRhchNyU6DZ2Q/ycHMKPCjvQ5XguVAkGZqIeyKOw6IhzckvKv82GjDge1ho+qKInNq7BzbAsfvOKU/MfB6AkOWzmMgmOh7gU4YnU+AnXlaDTWJgiymMKuEr+vB9A99IZ1AjEnTKET7K+zgFAKO0HYLUZao66w6wZhJ+fGv7sl/P2jvwUu+NPWKrWlDHl9px23XOQ1atHn7LfP2AkkQScVdkwCLV1IInlQQieWMOR8dK4WrnPb2lBm9B6t+ispamjMc0mswKIxNnvsNdjkh4SdT8MTdFCSrriIyol2S2Jlo6vNdte/LgPkorva0Ag7VtglYSqJXU4GxozeQvZdnXrYFbVNC6OHHVUhUYVd80lilaRqNesbXG0C1BbhQFRRvlMCYMVSYvOGTjCWFkqug0++/HT8du8MXnjq5lz/u2YsahvJ0AnpYTcvggPQU4WdXhLbqcJO7v5XuSR2cSDH+Vr+ZM2uIRE60QXCbmx98r7dvwTGSXpjvy12pM9gmhWOJOe82oKQ90sOUmEnyedutCNGb6DKlw+Ev/lc9QzSY1kq7HhDbAmjNAFUDwKnvCT5mLxm6vPEh3V5E92LxkjsL64DKrcBAIZWHpb+xKHJ6HZpEQk7Sha2Q9jV57ubEJsBsqys2vBi97OHnQE0JZZDJxjdhuwHAkGetzth0/tAY0msVCHV4lLyFtH2coIDAHYTk159AtS2wk7AFwuvat0jHnZM2PU7zj1qFc49Kv9Yt5Yk/q4a0xbgdEFe7X15ke6hN9Rhu6SqdxkGxaETCwhbK4ldDBKrFx52U4cn79tzV+SV7JYXXknYKaqCVE2b9xtLYpcRYae3mx5uXDA6RMJ7uAvJ0AwjuCS2j/DizwEP/Rw44w+Sj3FKbAKLR9iVDwPEptj4mi3pTyxPRLcXU2FXapOwk7uDDULYdSNwIgNKJCXW8wOVlHNoPlSQTTBhF0FO5L1G5lRNBiMzdJVAuwE6eh/YNHSiEpXEZljIyBKCVtAJhrZMfWOEXXi81Q5KYhmDgzXNEn/polSZrfcujIoq/IaLTlMiOwto6ESdPewWHkphJ9Rbi6KwE32fVA10Q22zYlvyvundkcK6H+cy0qA/zQrHITYmy1lhJ8GE3dJFQbNEWcwAxQGH9Fjm0Ik+wGFnhD8mKLETp8RKLNpM8b/WPh+/89fgbn8jVq9vUjJDCbvF9LCj751nR5ROxg4+FP7uJAo5B0pk0StVdtWGp+KuuSSWgJbELkD6IGOZQZ+g6RHmWaH3gSb1QcznK/vOFFXYNT0ErVy1vZJYQtiJhUal7qmS2BIr7JYtKEl25jZtrHQKAMQEXKoVerj4GdEIu04RC51QJbG8oFgw6Cmxi0HY6QRdNwi71dujeemWc8Lf07sIkdWHpUTC4zRhAyHhmMa5ZTRn0wk6ToldulChY9IShUtiewW5ASbXubwh1qcokJJYTokFsIgKu9HJlXha7a9Rh4s7J5rIg8uT0e3FJOzaLYml5N6BB8Pfw1PdOaYWoAvrSt3HcBHYPxs2fMe2OHSCIhY6wYQdo8ug/RgQL/XPA52g018XIAsZorDLsJD5mxeehNfv/C/8ydOPafo8Xf3WlqkvXWyI66zW8FERJAZ72C1vfPuPzsehSh2HrdTmBpYVjr/1ucgTtlnKfIeghN1YFza4lMKOpMSyx84CQk74ZUnsYhBZOsHclZTYCeCqW8JKgd98KwyfmN5F5jJ9SOa0UtjJc+fVluecTW83nBK7dKGPUVwS2zNEoRNi85fH1/6EUtjNcUqswKIxNi85Ywvmqh6ec8qG5hPWpULY0ffOM8Gy7bDh1eeAg4KwW6DQCce2VFKfVNg9PhtObFYMF2H1m6dJL2ELgsD3luduLaO30K95E9GWBaXx+N8m4s+lhJ3YmcqwMH3GCetx6zueisnh5s/VFXZt7WCSnbJAKChioRNcEruscdTaJmO9WwrH07l94d89tMoYIamw6yc6Jz0kuV2tc0nsokAGSamNjCVA2HWLTFt5RPh7bF34O1YS24fKhFYedg4h7JZjVYTebpbTZ+836LYNXBLbM7jCtmJOlcTy+NqXkDxLg0tiJRaNsNs8NYx3P+cJrZ9IybHNKbXOC4F2CTsgIuyUwm5hSmKBUKlS9xrKG0oq7KZGlnfDTyBWErsM/VAYvYXuW9luSaxOTpQNr0ODbhrZFXYAWpJ1gEFh12FKrCTswpJY6WHHCjtGCtwhAPuj8qIeLn42TkZjfTdKYmW7rjQ8VRLLCoAFhL5DvxgLgCw+pJ1AjjWze/tbedbSw46WxOYb5wYCvSitZvQGCYUdn6tewRUE3SyHTvQ3pGK4PkfW5H2oFO8iln5N5IaTgZVHAetPBFYdtXjHQSdZedUxcgEtPTkWKCUWCH3spqtQ6Yv75sId16mRPtxx7SXo5M/t40kuY2kiQdhNtvc6utrA9Dpqchj0JElTV9i1RWSQCaxVZoUdIwdKY8A0IjKih4QdLYM9OF/v+PVku67Uo5RYXlAsIHSCbiko7HTVdKeQG8Jz+/pbeVYTCrs0BW2BhCupz7mM5rUJhd3yXswuaegKux4GJS13FIUn7Lwg7Nhyok8hSe3abBTQtMz7uKVP2BVHgP/1n4t9FEDlYHR7dXOPpwT03ZUFVNjJxbVU2O2bCSc2TNhpUBPaICrF6McyEsbShH7Nd6sk1vQ61MtGJml2UUmiK4KG2iHsSJiQJT5Tpe6ppNrh4tIfmhiLhLJ2DfR48XPc+nHcvusQnnXSho5fS4apVOqe8rAr8IJi4WBr/cpiLAB0wk5vz51iSHgkVw+SNNw+JOzkZlOawk5uhDcqy1OBkfCwW0afvd+grwF76Lu63CEVdjW2nOhvyP5NrmGAZR+sw6uirKBBEXkbjW4wukAedkCUFFsV5Td7BGG3arQPJ3C9BJ3sBCItsx93pRlLE/rOv/QZyguamm36Gwh9mpxi6O0jfb66aHKsl6sOtVO+SohGWyxYG36A6Yok7LgklpECfQHfYz+gT7/qdPzn/ftw8bFrO36tIUrYiTG5rdAWRnvQNy4WhbDTFGPdVtgNTSJMUg5CHzugP5Vnj98b/h5dY36cnju5ob6cNlkTJbHLezG7pKHPvzh0omeQHnYSRZe92vsSJsJumW9KMGGXFaf8PrDvPuCYZ+T/X7qgsGzzIrtHkGmLstTskQPhTuT6CfZQiMFEzjFhx+gV2vUw0YNinJQuvDAsCLu9nb2fAV1R2JFSXnsoWrDuFyX7I6ywY6RhgQm7VaMlXPKE9V15LUl2zwhDbIAJuwWF7mG3GGN8rL1a3SfsbCfsX+f3A9OPhPf1m8Lum28Pk24BYPIw83PomFY5EP5eTgs6vd1wmeXSRSIZmgm7XkFX1LHCrk+hE3Z2IQqHXKbglpwVxWHg6e8Dtp2f/3+pwfzQigVtdLrC7pED8wCADZPLaGKTBZaVnNT22ySXsbTxwk+Fvy/8s96/l5wQzvaAsNP85TpV2LmEsNs3GxJ2w6XlPTAzmiBB2PUuJbbbkB52UkkKAAVWACwcloTCjizeS2OA3YNpuLRgUAq7PpvLUKuHiRTCznYiRd38gfB3v33OTqDbYbQbZMXoPXSCLq3Mm9ExdIKON8T6FPKakYTdctqMSQG35IUANZxfwMAJIFLDKIXdQUnYscIugYSJ7zKa/DF6j+OfC/zhr4Dz/riz13n+v4SD2e9/Kf050iNlIUpiO1XYlcdREEbB+0SKNSvsGKnQlSV9tPiRivc5YYgNJENcGD2ETtgtRhlhkbTXbqvrJKSP3aFd4e9+m8scfkF0e2Jj+vPkRpRU2C2nkli9UqfdICtG76GfqwW0RVpu0CtA2CO2TyHX44qw67MxrAfgVdFCgBJ2C9xRl4lnju8H2H1QlsQyW52AWwJE2Bhsd9nLbxk9QFp5Tx6c8ILwpxnkQkaVxHaPsEuUxLajsKOL1olNKLk11L0G9s2GFyB72DFSQQm64lhfeTfpZHfJteHYrLBbMOiq+cXYtR8hAUS9skeRCrtDD4W/+02dsOk04IL/E5JQzdThheHQv245KuwcNwyYaoSb8KywW8LQ131DU+bnMTqGvoHMCrs+RcL3kUVGTNgtBGhnPbVtQd9aLnzn6x72zlZR9wLYFrB2vM8mcAsBOqnlclhGP0P62cz2grCLT4h0EiIT1h4XqiFG1wLbzke58D3MVBvwg/BhTollpIISdsP9tfAp6+XkTEwvLJZCsubE5uh2r/wXJWF34MHevk+vYFnABW9r/Tx5/vxQmb2svcEW0BubkROFoXBN4QlFQJ+NW/0EfQOZx9g+RWKs5jU5r4oWAlRht2r7wr61WPhOVxoqcGLNWJmNOE2gHUI/pqoxGBIJhV33dqfohKjgWO31JeMbgP/1i3CRYTsYK7vYO1NVD7OHHSMVoySttc9Ki7qSsMxoH0uBsBteCIWdUFvJxPs+8nnMBZ2g6zdispvgipClDdsBpBOC7j/I6Bq64rHMWHwkxmpW2DFhtxBYf1J0e/WxC/rWI6XwFM9WG9jFgRPNwQo7xqBALlwqB8PfXSTsJkciHyhLT63N9UJRefBoKT4UsYcdIxVUobTAnrCdoivl5Iz2kfCpXYS5EO0zVx/dm/egpCAwuESWXg4/qJ8zDU4xKollLG0EfnS7F0EzDAAGhR2Psf0JVtglwL3GQmBqG/CyG4Gn/Dlw5EUL+tajhLB7WBB26zlwwoyYwo47B0Yfo4fKgzFCrtUafpNnZodO2HEZAyMVE5ui233m22RZVqwstq1yckb7WCqLgEv/FjjsLOC8N/fm9XWPrD4KZsmF5a6we+bfhcqTk1+y2EfCaIVjnhn+3vDExT2OAYc+d+S5ZJ+CPewSYBnDQmHb+eHPAkMq7GaqHnaJwIkNHDhhBt1t7zeTZgaDoqylD3ZxsOtIVZeCEULY2VacFGQwYhhbH93e2H+Ln6GCg0o9JLp5MbHAcAqA5USloou1CHjSq8OfXiGhsBvUkljt/BWWGWF3wguA454dhqQxljYuvgbYchZw4uWLfSQDDVbYDQgSangW0XAvP+AYFV5Qs9UG5moNAMAGVtiZQTuE0oBOcBnLAyWdsOuNGfdYuTtDCH2diaECbE7OZKTBcYHf+ytg//3Aaa9a7KPJjdGyi/1zoUk+pyEvAgpDQG0mvD2oi4BlUxK7zBV2QEhCM5Y+Jg/rLUnPAGDwieUxtj+xFOwrlhiYsBtwKA+7WgOHKiFht36CCTsjaIcwqDvSjOWBHirsKMbL3Vks0JLYyWEOfGG0wFmvX+wjaBtjpQKA0J6CS2IXAW6ZEHYDugjQUygHdQOShnZYzuASsAwGIxOYsBsQ2HZY7i89OpfjZowG9rAbcEQlsQ08vH8OALCRFXZmxBR2A+r5wlge0BV2XU4le9W52wAA77jsuK683kiMsGPFAGNwQdWkXK6zCKCqrEEleBIKuwGdz1DCrjgSD/RgMBjLDlwSO0CgoUL6mmYZghV2Aw6pXHl4/zz2ztQAANtWM1NtBCXpWGHH6GfQhQzQdXP+tz/jWLzq3G1dK6+nJMbkEBN2jMEFE3aLjOWwCNA3aAZVnaATdgwGY1mj4FiwLcAPwr95jO1jFIaB+f3hbb1qaBmCFXYDjhWivOyx6SoAYN14OZHIyBAYmoxuD2oJCWN5QF+I6iVSHcK2ra56Ya4ajcpgV3BJLGOAMUbKyLlcZxFAy2DpmD9IcNywnEhidO3iHUsvQc8fE3YMxrKHZVkxko59YvsY1MpHFyEsQzBhN+BYpyXCHrmGiahUUBUST/4Y/Qx9N6rLCrtuY+vK6HpbPT6gZWoMBuIKu6kRJqcXHHQRsMT7xY7gVaPbI6sW7zh6CaokZBsTBoOB+KYY+8T2MWL9OyvsmLAbcKwYLqDoRqf5CC6HTQftHAbV84WxPEA9jJxSz0InuoVtq6J+6YSNvJPGGFxQhfvqMSanFxwWmfZ22dtzSWGYkHSD6u1GVRdjGxbvOBgMxpLBSCki6dgTuY8xti66zSWxTNgNOizLwrrxSGV3BCvs0sElsYxBwcTm6HbgL95xZMTqsRIOmxqGY1s4+4gBVYMwGIgvIFaPMmG34HDIAm6Qd+2f/r7w96kvX9TD6CkoYTe+fvGOg8FgLBnUvUDdpmo7Rp8hRtjxRj6bmS0DrJso44F9YUIsl8Q2AS2P4c6B0c+gxup+ffGOIyMsy8KXrz4HtYbPZYKMgcYx6yKSiBV2iwCqxLIHeM/6Cc8HVh8DrNi22EfSO6w+Orpt83KGwWAAtcbS36RmZMDI6uh2idfkAzxbYUicQxQrT9raXfP5gQItjzniKYt2GAxGdyDKoI57zqIeRVZMjRQTnpsMxqDhpE2T6vbKUSanFxwbTlnsI1g4rD0eKA4v9lH0DnRjdYjntgwGAzh2PVsaDQSotc+aYxfvOJYIeEtqGeA152/D7kPzePL2NSg4zNGmYv1JwNlvBFZtj0txGYx+xMu/BvzP9cDT3rvYR8JgMAQmhgv4P884Bvtm69i0YoDJlKWK014JPHobcPgFi30kjG7gxZ8HfvU54IzXLfaRMBiMJYD3PvcEvO8bd+IV52xd7ENhdIKTrgAe+k/gpMvZpgpM2C0LDBdd/NXzTlzsw1j6sCzgae9e7KNgMLqDreeGPwwGY0nhtecfsdiHsHzhFoFnf2ixj4LRLRz11PCHwWAwAGyYHMI/XLmMlNSDitIY8Lx/WuyjWDJguRWDwWAwGAwGg8FgMBgMBoOxhMCEHYPBYDAYDAaDwWAwGAwGg7GEwIQdg8FgMBgMBoPBYDAYDAaDsYTAhB2DwWAwGAwGg8FgMBgMBoOxhMCEHYPBYDAYDAaDwWAwGAwGg7GEwIQdg8FgMBgMBoPBYDAYDAaDsYTAhB2DwWAwGAwGg8FgMBgMBoOxhMCEHYPBYDAYDAaDwWAwGAwGg7GEwIQdg8FgMBgMBoPBYDAYDAaDsYTAhB2DwWAwGAwGg8FgMBgMBoOxhMCEHYPBYDAYDAaDwWAwGAwGg7GEwIQdg8FgMBgMBoPBYDAYDAaDsYTAhB2DwWAwGAwGg8FgMBgMBoOxhOBmeVIQBACAQ4cO9fRgGP0B2Q5ku+gVuN0xKBaq3dH34LbHALjPYywOuN0xFgPc7hiLAZ7jMRYL3OcxFgN52l0mwm56ehoAsHnz5g4OizFomJ6exsTERE9fH+B2x4ij1+1OvgfAbY8RB/d5jMUAtzvGYoDbHWMxwHM8xmKB+zzGYiBLu7OCDLSe7/t45JFHMDY2BsuyunaAjP5EEASYnp7Ghg0bYNu9q6rmdsegWKh2B3DbY8TBfR5jMcDtjrEY4HbHWAzwHI+xWOA+j7EYyNPuMhF2DAaDwWAwGAwGg8FgMBgMBmNhwKETDAaDwWAwGAwGg8FgMBgMxhICE3YMBoPBYDAYDAaDwWAwGAzGEgITdgwGg8FgMBgMBoPBYDAYDMYSAhN2DAaDwWAwGAwGg8FgMBgMxhICE3YMBoPBYDAYDAaDwWAwGAzGEgITdgwGg8FgMBgMBoPBYDAYDMYSAhN2DAaDwWAwGAwGg8FgMBgMxhICE3YMBoPBYDAYDAaDwWAwGAzGEgITdgwGg8FgMBgMBoPBYDAYDMYSAhN2DAaDwWAwGAwGg8FgMBgMxhICE3YMBoPBYDAYDAaDwWAwGAzGEgITdgwGg8FgMBgMBoPBYDAYDMYSAhN2DAaDwWAwGAwGg8FgMBgMxhICE3YMBoPBYDAYDAaDwWAwGAzGEgITdgwGg8FgMBgMBoPBYDAYDMYSAhN2DAaDwWAwGAwGg8FgMBgMxhICE3YMBoPBYDAYDAaDwWAwGAzGEgITdgwGg8FgMBgMBoPBYDAYDMYSAhN2DAaDwWAwGAwGg8FgMBgMxhICE3YMBoPBYDAYDAaDwWAwGAzGEgITdgwGg8FgMBgMBoPBYDAYDMYSAhN2DAaDwWAwGAwGg8FgMBgMxhICE3YMBoPBYDAYDAaDwWAwGAzGEgITdgwGg8FgMBgMBoPBYDAYDMYSAhN2DAaDwWAwGAwGg8FgMBgMxhICE3YMBoPBYDAYDAaDwWAwGAzGEgITdgwGg8FgMBgMBoPBYDAYDMYSAhN2DAaDwWAwGAwGg8FgMBgMxhICE3YMBoPBYDAYDAaDwWAwGAzGEgITdgwGg8FgMBgMBoPBYDAYDMYSAhN2DAaDwWAwGAwGg8FgMBgMxhICE3YMBoPBYDAYDAaDwWAwGAzGEgITdgwGg8FgMBgMBoPBYDAYDMYSAhN2DAaDwWAwGAwGg8FgMBgMxhICE3YMBoPBYDAYDAaDwWAwGAzGEgITdgwGg8FgMBgMBoPBYDAYDMYSAhN2DAaDwWAwGAwGg8FgMBgMxhICE3YMBoPBYDAYDAaDwWAwGAzGEgITdgwGg8FgMBgMBoPBYDAYDMYSAhN2DAaDwWAwGAwGg8FgMBgMxhICE3YMBoPBYDAYDAaDwWAwGAzGEgITdgwGg8FgMBgMBoPBYDAYDMYSAhN2DAaDwWAwGAwGg8FgMBgMxhICE3YMBoPBYDAYDAaDwWAwGAzGEgITdgwGg8FgMBgMBoPBYDAYDMYSAhN2DAaDwWAwGAwGg8FgMBgMxhICE3YMBoPBYDAYDAaDwWAwGAzGEgITdgwGg8FgMBgMBoPBYDAYDMYSAhN2DAaDwWAwGAwGg8FgMBgMxhJC3xB2P//5z/GGN7wBxx9/PEZGRnDYYYfhRS96Ee6+++7Y817+8pfDsqzEzzHHHGN83XvvvRc7duzAmjVrMDQ0hKOOOgpvf/vbE88LggCf+cxncP7552NychLDw8M44YQT8J73vAdzc3NNj/3000+HZVn4yEc+Ynz8U5/6lDrOm2++2fjemzdvhmVZeOYzn9n0vRjZ8OEPfxiWZeGMM84wPi7Px6tf/Wrj429/+9vVc/bu3dvy/Xzfx6c//WmcccYZmJqawtjYGLZv346XvvSl+MlPfhJ77v33349XvOIVOOKII1Aul7Fu3Tqcf/75uOaaa2LPu+CCC2JtvFgsYtu2bXjta1+LBx98sOnxPPbYY7AsC29605sSj73pTW+CZVmJ9wOAl770pSgUCok2//3vfx/Pe97zsG7dOhSLRaxZswaXXXYZvvjFL7b8bpYrlnsbpLj55pvx9Kc/HRs3bkS5XMZhhx2Gyy67DNddd13iuZVKBf/3//5fnHHGGZiYmEC5XMb27dvxhje8ITEeMBa+ndE2Yds2xsfHcfTRR+P3f//38e1vf9v4P7VaDR/84AdxyimnYHx8HJOTkzj++OPx2te+Fnfeead6Hh0r5c+aNWtw4YUX4hvf+EbLY3vGM56BFStWIAiC2P3//d//DcuysGXLlsT/3HTTTbAsC//8z/8cu//RRx/FW97yFhxzzDEYHh7GyMgITj31VLznPe/BgQMHWh7LcgK3wST27NmDN73pTTjmmGMwNDSENWvW4PTTT8fb3vY2zMzMJJ7PY2x/wtRe5M+f/MmfAAC2bt0Ky7Jw8cUXG1/jYx/7mPqf//zP/1zIw2csMdx33314wxvegO3bt2N4eBjDw8M47rjjcPXVV+OXv/ylet473/lO1f+Z5mKHDh3C0NAQLMvCG97whthjWfuml7/85RgdHU289i9/+UusWrUKW7duxf3339+9D89YMPz617/GS17yEmzcuBGlUgkbNmzAi1/8Yvz617/O/PyXvOQluP322xPP1ftEOod/9NFHY8/NsxZ5whOekHiv7373uxgeHsYTn/hE7Nu3r4NvZPHhLvYBZMX73/9+3HLLLXjhC1+IE088Ebt378aHPvQhPPGJT8RPfvKT2IkqlUr4+Mc/Hvv/iYmJxGveeuutuOCCC7Bx40a8+c1vxsqVK/HAAw8kOjfP87Bjxw7827/9G8477zy8853vxPDwMH70ox/hmmuuwb/927/hO9/5DtasWZN4j9/85jf4+c9/jq1bt2Lnzp246qqrUj9juVzGddddh3PPPTd2/w9+8AM89NBDKJVKmb4rRmvs3LkTW7duxc9+9jPcc889OPLIIxPPKZfL+MIXvoAPf/jDKBaLsceuv/56lMtlVCqVTO/3xje+Ef/4j/+IZz/72Xjxi18M13Vx11134Rvf+AYOP/xwnHnmmQCAe+65B0960pMwNDSEV77yldi6dSt27dqF//qv/8L73/9+/MVf/EXsdTdt2oS/+qu/AhAuOG6//XZ89KMfxTe/+U3ccccdGB4eNh7PmjVrcNRRRxkJ4ltuuQWu6+KWW24xPnbKKafEXveaa67Bu971Lhx11FF43etehy1btuDxxx/Hv//7v+P5z38+du7ciR07dmT6npYTlnsblPjc5z6Hyy+/HCeffDLe9KY3YcWKFbjvvvvwwx/+EB/72MdibWfv3r245JJL8Itf/ALPfOYzsWPHDoyOjuKuu+7CDTfcgH/+539GrVbL9H0sFyx0OwPibWJ2dhb33HMPvvjFL+Laa6/Fi170Ilx77bUoFArq+c9//vPxjW98A1deeSVe85rXoF6v484778TXvvY1nH322YkNt3e9613Ytm0bgiDAo48+ik996lN4xjOegRtvvLHppta5556Lb3zjG7jttttwwgknqPtln/fAAw/goYcewqZNm2KPyf+V+PnPf45nPOMZmJmZwUte8hKceuqpAID//M//xPve9z788Ic/xLe+9a3M39egg9tgHPv27cNpp52GQ4cO4ZWvfCWOOeYYPP744/jlL3+Jj3zkI7jqqqtiC2EeY/sfsr1Q0HVLuVzG9773PezevRvr1q2LPW/nzp252z9j8PC1r30Nl19+OVzXxYtf/GKcdNJJsG0bd955J774xS/iIx/5CO67777YxlOpVML111+Pt771rbHXSiP68/ZNOm677TZcdNFFGBkZwfe+9z1s3bq1K5+dsXD44he/iCuvvBJTU1N41atehW3btuH+++/Hv/zLv+Dzn/88brjhBjz3uc/N/PzPfvazePazn514H9knVioV3HzzzfjIRz6Cf//3f8dtt92G4eHh3GsRHTfddBMuu+wyHH300fjOd76Dqamprn9XC4qgT3DLLbcE1Wo1dt/dd98dlEql4MUvfrG672Uve1kwMjLS8vU8zwue8IQnBGeccUYwNzfX9Ll/+Zd/GQAI3vKWtyQe++pXvxrYth084xnPMP7vO97xjmDNmjXBF77whcCyrOC+++5LPOeTn/xkACB43vOeF6xatSqo1+uxx1/zmtcEp556arBly5bg0ksvbfnZGM3x29/+NgAQfPGLXwxWr14dvPOd70w8B0DwnOc8J7BtO/jyl78ce+yWW24JAATPf/7zAwDBnj17mr7f7t27A8uygte85jWJx3zfDx599FH19+tf//rAdd3g/vvvTzyXPi8IguDJT35ycPzxxyee96EPfSgAEHzrW99qelyveMUrAsdxgunpaXXfzMxM4LpusGPHjmB0dDRoNBrqsUceeSQAEPzRH/2Ruu9zn/tcACB4wQteENRqtcR7/Md//Edw4403Nj2O5QhugxGOO+644Pjjj0/076b3u/TSSwPbtoPPf/7ziedWKpXgzW9+c8v3W05Y6HYWBOltotFoBK9//esDAMFb3/pWdf/PfvazAEDw3ve+1/g/e/fuVX/LsfLnP/957Hn79u0LCoVCsGPHjqbH9oMf/CAAEHz4wx+O3X/FFVcEz3rWs4LR0dHg+uuvjz32tKc9LVi5cmXg+34QBEGwf//+YOPGjcHatWuDO+64I/Eeu3fvDt797nc3PY7lBG6DSfz1X/91ACC45ZZbEo8dPHgwmJ+fV3/zGNvfSGsvFFu2bAkuuuiiYHx8PPj7v//72GMPPvhgYNu2av/NXocxuLjnnnuCkZGR4Nhjjw0eeeSRxOP1ej344Ac/GDzwwANBEATBNddco9aVJ598cuL5T33qU1Wbuvrqq9X9efomfb192223BatXrw42b94c3HvvvR19Xsbi4J577gmGh4eDY445Jnjsscdij+3Zsyc45phjgpGREXV+szx/dHQ0+O1vf6vuT+sT//iP/zgAEFx33XVBEHS2Fvn+978fDA8PByeddFJs/O5n9E1J7Nlnn53YdT3qqKNw/PHH44477kg83/M8HDp0KPX1vvWtb+G2227DNddcg6GhIczNzcHzvMTz5ufn8YEPfADbt29Xu7UUl112GV72spfh3//93/Gzn/0s8fh1112HF7zgBXjmM5+JiYkJY4mXxJVXXonHH388VrJRq9Xw+c9/nndPu4idO3dixYoVuPTSS/GCF7wAO3fuND5v48aNOP/88xPnbOfOnTjhhBOM8lsT7rvvPgRBgHPOOSfxmCynkbj33nuxadMmY2mWScFpgtyddd3mAtpzzz0XnufFyiF/+tOfotFo4C1veQtmZmZw6623qsdMSpM///M/x9TUFD7xiU/E1AoSv/d7v8dl3AZwG4xw77334klPelKif9ff76c//Sm+/vWv41WvehWe//znJ55bKpXwN3/zN5mOb7lgodtZMziOg3/4h3/Acccdhw996EM4ePAggPD8AzC2TcdxsHLlypavPTk5iaGhoZbt7fTTT0exWEyoh2+55Racf/75OP3002OP+b6Pn/zkJzj77LNhWRYA4J/+6Z/w8MMP4+/+7u+MVhtr167Fn/3Zn7U85uUCboNJ3HvvvXAcR6maKcbHx1Eul9XfPMYuD5TLZTzvec9LtP/rr78eK1aswO/93u8t0pExlgL++q//GrOzs/jkJz+J9evXJx53XRdvfOMbsXnz5tj9O3bswK233hor69+9ezduuukm47oyT99Ecccdd+Ciiy5CqVTC9773PRx++OF5PyJjCeADH/gA5ubm8M///M9YvXp17LFVq1bhn/7pnzA7O4u//uu/zvz8mZkZfOADH2j53k95ylMAhOsVoP21yI9+9CNceumlOPLII/Gd73wn0/jdD+gbws6EQJQirFq1Knb/3NwcxsfHMTExgampKVx99dUJT5DvfOc7AMJF3mmnnYaRkREMDw/jiiuuiNU533zzzdi/fz927NiROhF76UtfCgC48cYbY/f/9Kc/xT333IMrr7wSxWIRz3ve81Inq0DoY3HWWWfh+uuvV/d94xvfwMGDB3HFFVdk+EYYWbBz504873nPQ7FYxJVXXqnKlk3YsWMHbrzxRtV+Go0GPve5z+UiUGVn87nPfa6l3+GWLVvw4IMP4qabbsr02p7nYe/evdi7dy927dqFm266Cddccw2OPPJI4+KDQhJvtCz2lltuwfbt23HKKadg06ZNscWrTtj95je/wZ133onnPOc5GBsby3S8jBDcBuPv993vfhcPPfRQ0+d99atfBQD8/u//fqbjYix8O2sFx3Fw5ZVXYm5uTvU7sm3u3LkTjUYj0+scPHgQe/fuxZ49e/DrX/8aV111lSpPbYZyuYxTTz011uc9+OCDePDBB3H22Wfj7LPPjvV5v/rVr3Do0KHYJsVXv/pVDA0N4QUveEHmz72cwW0wiS1btsDzPHzmM59p+jweYwcHsr3QHx07duzAz372M0UgA9Gmv4msZSwffO1rX8ORRx6Z6gOahvPPPx+bNm2KEcGf/exnMTo6iksvvTTx/Kx9E8Vdd92FpzzlKXBdF9/73vdwxBFH5DpGxtLBjTfeiK1bt+K8884zPn7++edj69at+PrXv57r+To/YoLs9yTBlnctAoTr1Gc84xnYtm0bvvvd7yb4oX5GXxN2O3fuxMMPP4zLL79c3bd+/Xq89a1vxSc/+Ulcf/31eNaznoUPf/jDuOSSS2ITsd/85jcAgBe96EU45phj8PnPfx5ve9vb8IUvfAGXXXaZMqWWhoknnXRS6nHIx3RzxWuvvRabN29Wi9YrrrgCt99+e0y1pGPHjh348pe/jPn5efUZn/zkJ2PDhg1ZvxZGE/ziF7/AnXfeqQjQc889F5s2bUolUl/wghfA8zx8+ctfBhAqM/fu3Ysrr7wy83uuX78eL33pS/H1r38dmzZtwvOe9zz87d/+bWzHS+KNb3wjisUiLrroIpxyyin4wz/8Q3zlK19JJVnuvPNOrF69GqtXr8aGDRtw0UUXwfd9fOtb3zIqlii2b9+ONWvWJAg72V7PPvvs2GM333wzjjrqKLWzIZWt1AuK0RrcBuN429vehgcffBBHHHEEnvKUp+Ad73gHbr75Zvi+H3set7d8WIx2lgVSKSUnZ2eeeSae/OQn42Mf+xg2bdqEHTt24MMf/jAeeOCB1Ne4+OKLsXr1aqxZswZPeMIT8KlPfQqf+MQn8NSnPrXl+5977rn43e9+h4cffhhA2OdJIu/ss8/GL3/5S0xPTwOINjMoYXfHHXdg+/btmdr2cge3QTNe+cpXYvXq1Xj5y1+OY489FldddRWuv/56pfiT4D5vcCDbC/3R8ZSnPAXr1q1Tm/Z33HEHbr31Vq6wWeY4dOgQHnnkEaPK+MCBAzESWK4dJSzLwhVXXBETgshNFJMveta+SaJWq+HCCy+Ebdv43ve+Z/QnZfQHDh48iEceeaQp3wEAJ554Ih566KHcz5fzKvp+e/fuxUMPPYTPfvazeNe73oWhoSGlGM+7Ftm1axee/vSnY8uWLbjpppsGiqwD+piwu/POO3H11VfjrLPOwste9jJ1/1/91V/hfe97H170ohfhiiuuwKc+9Sm8973vxS233ILPf/7z6nlyB/dJT3oSrr32Wjz/+c/Hu971Lrz73e/Gj3/8Y3z3u98FANXAmu1uysdoY2w0GvjsZz+Lyy+/XJXSPOUpT8GaNWuaquxe9KIXYX5+Hl/72tcwPT2Nr33tazxYdxE7d+7E2rVrceGFFwIIB7PLL78cN9xwg7EkesWKFbjkkkvUYHfdddfh7LPPNkp0m+GTn/wkPvShD2Hbtm340pe+hLe85S049thjcdFFF6mFIwAcf/zxuPXWW/GSl7wE999/Pz74wQ/iOc95DtauXYuPfexjidfdunUrvv3tb+Pb3/42vvGNb+Dv//7vcfDgQTz96U/Hnj17Wh7XOeecg5/+9KfwPC9W/iUfk2qTubk53HrrrbGFqyw5553/fOA2GMcrX/lK/Md//AcuuOAC3HzzzXj3u9+N8847D0cddRR+/OMfq+dxe8uHxWpnrSANq+V4aVkWvvnNb+I973kPVqxYgeuvvx5XX301tmzZgssvv9yYuPqP//iPqs1de+21uPDCC/HqV786U2Km7MN+9KMfAQgJu1NPPRXFYhFnnXWW6gflY+VyGaeddpr6/0OHDnEbzAhug2asXbsW//M//4M/+IM/wP79+/HRj34UO3bswJo1a/Dud79bbRhznzc4oO1F/uhwHAcvetGLVPvfuXMnNm/enKpeYSwPyH7AFPZwwQUXxEjgf/zHf0w8Z8eOHbjnnnvw85//XP1OW1dm7ZskZIXF1NTUwBEkyw1Z+A76uBwXsz5fJ+zkJsbmzZtxxRVXYHR0FF/60pewceNGAPnXIrOzs5iensbatWsxPj7e+gP3GfqSsNu9ezcuvfRSTExM4POf/zwcx2n6/D/6oz+CbduqDBYAhoaGACCxcys7MblQTGtoFPIxWlP9rW99C3v27MHpp5+Oe+65B/fccw/uu+8+XHjhhbj++usT6hGJ1atX4+KLL8Z1112HL37xi/A8j0tvugTP83DDDTfgwgsvxH333afOyxlnnIFHH31UkbQ6duzYgW9/+9t44IEH8OUvfzl1oJuZmcHu3bvVDyUrbNvG1VdfjV/84hfYu3cvvvKVr+DpT386brrppkS58/bt2/GZz3wGe/fuxS9/+Uv85V/+JVzXxWtf+9pYGwaAkZERXHzxxbj44otxySWX4E1vehO++tWv4q677sL73vc+AOEOGD2u3bt3q8XSueeeq7zqbrvtNhw8eDCmsHvkkUdw//33K287StjJDrHZtcGIg9tgsg0CoQ/TN7/5TRw4cAA//OEPcfXVV+N3v/sdnvnMZ+Kxxx4DwO0tDxaznbWC3Cyjk7xSqYS3v/3tuOOOO/DII4/g+uuvx5lnnol/+7d/wxve8IbEa5x++umqzb34xS/G17/+dRx33HF4wxveoFKC9+zZEztG+b7nnHMOLMtSmxFUVTw5OYnjjjsu9pjurzg+Ps5tMAO4Daa3QSBUPX/kIx/Brl27cNddd+Ef/uEfsHr1arzjHe/Av/zLvwDgPm+QQNuL/DFhx44duP322/E///M/uO6663DFFVeoTX/G8oTsp3RrJyD0VJWbBmk45ZRTcMwxx+C6667Dzp07sW7dOuUXZkKWvkliaGgIn/70p3H77bfj0ksvxezsbJufkrHYyMJ30McnJyczP9+yrAShKzcxvve97+H222/Hb3/724RXZ561yJFHHon3v//9uOmmm3DllVcaNwX7GouZeNEODhw4EJx88snB1NRU8Otf/zrz/61evTp47nOfq/5+zWteEwAI/uM//iP2vPn5+QBA8Id/+IdBEATBt771rQBA8Bd/8Repr/39738/ABD8+Z//ubpvx44dAYDUn5tuukk9V09M+fSnPx2USqXgzDPPDJ797Ger53FKbGeQ5zLt56Uvfal6Lkhy0tzcXDA6OhpccMEFgeu6KqVOpjDpf8ufLVu2tDymJz/5yQEAYwoOxfe+970AQPDyl7889r+mJLwgCIKJiYngtNNOi/0v/ZFpxT/96U8DAMHf//3fBx/+8IeDqakplYZYr9eD4eHh4DOf+Uzwrne9KwAQ3HXXXeo97rrrrgBA8MpXvrLl52SE4DaYbINpkJ/lU5/6VBAEQfCnf/qnAYDghz/8YcvPtNyxmO2sWZsIgiB497vfHQAIvv71rzf9DLVaLTjqqKOCQqGgktObJS6+6U1vCgAEt912WxAE4XhJj/Gaa65Rzz322GODk08+OZieng4cx4klk77mNa8JLrroouDBBx8MAAR/+qd/Gnufs846KxgaGjKmGjMicBts3gZNuPfeewPbtoMLLrggCAIeYwcBWVNi6dz+iCOOCC644IIAQPDf//3fmV+HMbhYv359cOSRR6Y+ft999wUAgg984ANBECT7y3e9613B+vXrg+3btwdvetOb1P/RvrcZ9L4pCOIpsR/+8IcDAMHTnvY0Hhv7GOvXrw+2bdvW9Dlbt24NNm7cGARBEGzYsCHT8zdv3qz+7rQva7UWeetb3xoACF7xileo9ewgoHWc1RJCpVLBZZddhrvvvhvf+c53cNxxx2X6v+npaezduzfmGXHqqafiYx/7WKwUDAAeeeQRAFDPPeecczA5OYnrrrsOb3/7241qvk9/+tMAgBe+8IUAQlnmV77yFVx++eVGddwb3/hG7Ny5U5WJ6Hjuc5+L173udfjJT36Cz372s5k+I6M1du7ciTVr1hgl41/84hfxpS99CR/96EeV+lJiaGgIz3nOc3Dttdfi6U9/eqrs+6UvfWlMgaa/jgmnnXYafvCDH2DXrl1Ny35kSdauXbtaviYQqhvkbtxJJ52UKL+QKZ5PfOITMTw8jJtvvhmlUglnnXWW2s11XRdPetKTcMstt+C+++7DmjVrsH37dvUa27dvx9FHH42vfOUr+OAHP2iU6zPi4DYYQbbBrO932WWX4a/+6q9w7bXXcolQCyzFdgaEbeK6667D8PBw7P9NKBQKOPHEE/Gb3/wGe/fubdlepEetbHM7d+6M+fnQ1Lpzzz0Xn/jEJ/Ctb30LnucpGwAgVBZff/31+P73v6+eS3HZZZfh//2//4cvfOELXfdWGyRwG2zeBk04/PDDsWLFCtXn8Ri7PHHllVfiPe95D4499licfPLJi304jCWASy+9FB//+Mfxs5/9DKeffnru/9+xYwfe8Y53YNeuXbkCJST0vknHVVddhX379uHP/uzP8JKXvAQ33HADbLsvi/iWNZ75zGfiYx/7GG6++Wbj+PijH/0I999/P173utcBCOdD//RP/9Ty+X/8x3/ctWNstRZ5//vfj3379uHjH/84VqxYgb/927/t2nsvKhabMcyKRqMRPOtZzwpc103dFZ2fnw8OHTqUuP9//+//HQAIvvjFL6r7du3aFZRKpeDcc88NPM9T90sVx89+9jN131/+5V8GAIK3ve1tidf+2te+Fti2HVx22WXqvs985jNNlSCvec1rgsnJyaBSqQRBYGabP/WpTwXvfOc7g7m5OXUfK+zax9zcXDA2Npa6U33LLbcEAIIbbrghCILkrtOtt94aXHPNNcGPf/xjdZ++g5WGXbt2GdWg1Wo1OPnkkwPbttVr/PCHPwxqtVriuZ/97GcDAMEb3/hGdV+aiuCmm24KAASXX3550+OSuPDCC4P169cHW7duDd773vfGHvvTP/3T4LjjjgsmJiZiClWJG264Qb2XVCBQfPOb3wxuvPHGTMcx6OA2aMZ3vvMd4/1XXXVVot++5JJLAtu2gy996UvGz/LmN7+55fsNOhaznQVBeptoNBrB61//+gBA8Cd/8ifq/rvvvjv43e9+l3j+/v37gw0bNgT/P3vvHSbJUZ+Pv51mZnfv9qKkO+UsoUwQSOQgggEhDCYIZAwGB7D5GWzAOGCDMRYYDPgLNmCiACHABJOEBIggFAAhoZzudLrT5Xybd2a6u35/dFf1p6qru6tnd29n9+p9nntudndqOkx3ddVb7/t+VqxYwcIwZIwVr8xyJVSj0WAjIyOV+3jFFVcwAOzCCy9kp5xyivQ3rmq68MILmeu6bP/+/dLf9+3bx9auXcvWrl0rKY45du7cyd773vdW7sNihr0Gy6/BX/3qV2x8fDz3e654f9GLXiR+Z5+xCxu9KOw2btzI/vmf/5ldffXVtT7HYvHiwQcfZIODg+zMM89kO3bsyP19w4YNpQo7xhj76Ec/yi6//HKpndr31umbqMKO461vfSsDwN7whjf0dqAW84oHH3yQDQwMsDPOOIPt2bNH+tvevXvZGWecwQYHB9n69esZY4ytW7eODQ4Olr5/eHiYbdiwQfzetC+byVwkiiL2B3/wBwzAohmPLRiF3d/8zd/gu9/9Li6++GLs27cv59e/7LLLsGPHDjz60Y/GpZdeitNPPx0AcO211+Lqq6/G8573PFxyySXi/WvWrME//MM/4J/+6Z/wvOc9Dy9+8Ytxxx134NOf/jQuvfRSnH/++eK973jHO3D77bfjAx/4AG6++Wa89KUvxcDAAG644QZ8+ctfxplnnokvfOEL4v1XXnklVq1aJa3aU7zoRS/Cpz/9afzgBz/AS17yEu17aCENi5nju9/9LsbGxvCiF71I+/cLLrgAhx12GK688kqp6jDHueeeW1kJpwhbtmzB4x//eDzzmc/Es571LKxZswa7du3CVVddhTvuuANvectbhIrgAx/4AG699Va85CUvwTnnnAMAuO222/DFL34RK1euxFve8hbps0dGRsS9EIYhHnjgAXziE5/AwMAA3vnOdxrt35Of/GT87Gc/AwCR5cTxxCc+EZdffrl4n4pXvOIVuOuuu/C+970Pv/vd73DppZfiuOOOw969e3HNNdfguuuuk8rJH8qw16Ael1xyCU444QRcfPHFOOmkkzAxMYGf/OQn+N73vofzzz8fF198sXjvF7/4RTznOc/BS17yElx88cV41rOehaGhIaxbtw5f/epXsX37dnzoQx/q6RwtFszndcZBr4nJyUmsX78e3/rWt/DQQw/hla98Jd773veK995xxx141atehd/7vd/DU57yFKxcuRJbt27FFVdcgW3btuGjH/1oTtn+wx/+UFQ43rVrF77yla9g3bp1eOc732kUNsz7sptvvhmvfe1rpb+deuqpWL16NW6++WacffbZIqeFY8WKFfj2t7+N5z//+TjvvPNw2WWX4bGPfSyA5D656qqrcOGFF9Y6X4sN9hosvwa/9KUv4corr8Tv//7vi4In9913Hz73uc+h1Wrh7//+78V77TP20MNxxx2Hd7/73fO9GxZ9hFNOOQVf+cpXcOmll+K0007Dq1/9apx77rlgjOHhhx/GV77yFbiui6OPPrrwM/7qr/6qcjt1+iYd/uM//gP79+/HZz7zGaxcuRIf+MAHah+rxfzhlFNOwRVXXIFXv/rVOPvss/H6178eJ5xwAjZu3IjPfvaz2LNnD6666iqcdNJJAJLcuC9+8Yu49NJLte/fv38/vvrVr+KEE06ovS915yIUruviyiuvxMjICN71rndh5cqVeNOb3tTTOekbzDdjaAqes1T0j7FkNfSyyy5jJ598MhscHGTNZpOdeeaZ7N/+7d+0LG0cx+xjH/sYO/XUU1kQBOyYY45h//iP/1j43i984QvsSU96Elu6dKnY7kUXXST59Xfu3Ml832d/+Id/WHgsk5OTbHBwUCiWTNlmq7DrHRdffDFrtVpsYmKi8D2vfe1rWRAEbM+ePUa5DqYr/qOjo+w///M/2XOf+1x29NFHsyAI2NKlS9mFF17IPv3pT0se+xtvvJH9xV/8BTvrrLPYsmXLWBAE7Nhjj2Wvfe1r2UMPPSR9rnpPOI7DVq5cyV70ohexW2+91eCsJLj22msZAOb7fu787N27lzmOwwCwX//614Wfcd1117FLLrmEHX744cz3fXbYYYexiy++mH3nO98x3o/FDnsN6nHVVVexV77yleykk05iAwMDrNVqsTPOOIP9wz/8g1YxPTk5yT70oQ+x888/ny1ZsoQ1Gg12yimnsDe/+c1i1e9QxnxeZ4zlr4klS5awU045hV122WXsRz/6Ue79O3fuZO9///vZ0572NLZ27Vrm+z5bsWIFe+Yzn8m+8Y1vSO/lz0r6r9VqsfPOO4994hOfqJVXcuSRRzIA7H/+539yf3vRi17EALA3vvGNhe23bdvG3vrWt7JTTz2VtVotNjg4yB772Mey973vfUYqv8UMew2W484772Rvf/vb2WMe8xi2cuVK5vs+W7t2LXvZy17GbrvtNm0b+4xdmOhFYdfr51gsfqxfv5698Y1vZCeffDJrtVpsYGCAnX766ezP//zP2e233y7eZ9pfqn1vnb5Jp7BjLFEyv/jFL2YAcoo+i4WBO++8k1166aVs7dq1LAgCtmbNGnbppZeyu+66S/v+u+66i73qVa9ia9asYa7riueiztlj2pfVnYvoVPXj4+PsggsuYK7rsiuvvLLGGeg/OIwpNZotjNDtdnHxxRfjuuuuw/e+9z0873nPm+9dsrCwsLCwsLCwsLCwsLCwsDjo+OIXv4jXvva1uOyyy0TOv8XMYBMhe0QQBPjmN7+J8847Dy972ctw2223zfcuWVhYWFhYWFhYWFhYWFhYWBx0vOY1r8Hll1+OL33pS5U2agszWIWdhYWFhYWFhYWFhYWFhYWFhYVFH8Eq7CwsLCwsLCwsLCwsLCwsLCwsLPoIlrCzsLCwsLCwsLCwsLCwsLCwsLDoI1jCzsLCwsLCwsLCwsLCwsLCwsLCoo9gCTsLCwsLCwsLCwsLCwsLCwsLC4s+gm/ypjiOsW3bNixduhSO48z1Pln0ORhjGBsbw5FHHgnXnTvO1153FhQH67oD7LVnIcP2eRbzAXvdWcwH7HVnMR+wYzyL+YLt8yzmA3WuOyPCbtu2bTjmmGNmZecsFg82b96Mo48+es4+3153FjrM9XUH2GvPQg/b51nMB+x1ZzEfsNedxXzAjvEs5gu2z7OYD5hcd0aE3dKlS8UHDg8Pz3zPLBY0RkdHccwxx4jrYq5grzsLioN13QH22rOQYfs8i/mAve4s5gP2urOYD9gxnsV8wfZ5FvOBOtedEWHHZZvDw8P2ArMQmGs5r73uLHQ4GDJye+1Z6GD7PIv5gL3uLOYD9rqzmA/YMZ7FfMH2eRbzAZPrzhadsLCwsLCwsLCwsLCwsLCwsLCw6CNYws7CwsLCwsLCwsLCwsLCwsLCwqKPYAk7CwsLCwsLCwsLCwsLCwsLCwuLPoIl7CwsLCwsLCwsLCwsLCwsLCwsLPoIlrCzsLCwsLCwsLCwsLCwsLCwsLDoI1jCzsLCwsLCwsLCwsLCwsLCwsLCoo9gCTsLCwsLCwsLCwsLCwsLCwsLC4s+giXsLCwsLCwsLCwsLCwsLCwsLCws+giWsLOwsLCwsLCwsLCwsLCwsLCwsOgjWMLOwsLCwsLCwsLCwsLCwsLCwsKij2AJOwsLCwsLCwsLCwsLCwsLCwsLiz6CJewsLCwsLCwATLTD+d4FCwsLCwsLCwsLCwsLAIuFsJvcB3z+BcAvPzzfe2JhYUGwcc8Evv27LXjZJ2/CJR+/AZ/6xUPohPF875aFhYTbNx/A8e/8Ac7852vx8wd2zffuWPSIj/7kQVzy8RswOt2d712xsJhTfPhHD+DF/3UjxntYZLjipo249H9+1bf3yb9fcz/Ofc+P8PGfrpvvXbGwsJgBvnP7Vjz3I9fj7q0j870rFnMFxoDv/AXwv69LXlvMCRYHYffz9wObbgCue4+9WCws+gR7xtu4+OM34K1fuwO3bNyPO7aM4PIf3o/LPvNr+/C26Bvcumk/XvxfN4qf//e3W+Zxbyxmgo/+ZB3u2DKCb9jv0KIGNuwex4M7xw76dr/y60fwrv+7G3Fcb9zKGMP/++l63L75AL5z+9ba2/3n796DmzfsxZdu3lS77cFAGDOMTHUxMtWfhKKFhUU1pjoR/uqrt+OBnWP45m32mdzv6EY9iim23Qb87svAPd8CRrfN7k5ZCCwOwm7Hndnrid3ztx8WFhYAgJHJLl796V9jbDpZ/b/oUYfjzCOHAQC/2bgPl/zXjfjxvTvncxctDmFMdyN8/85t+Ptv34WXfuIm8fsnn7wa//Hyc+dxzyx6BVUL2Yn+oQfW42JtGMV45n/8As/5yPU9Kc5+eNd2XHHTxtrtGGP4+2/fhS/9ahN+uX5PrbZ7xjvidd1rfbobidc7R6drtT1YGGx4AICJTlTxTgsLi37FrrGsf6H9jkX/4Uf37MAZ/3QNvv7bzfUbP/zL7HVnfPZ2ykKCP987MCuY3Je93nUvsOTw+duXg4ROGOMPP/trHD7cwscuffR8746FhcB0N8Ir/udmPLBzDEtbPj7/2vPxuONXAgA27Z3Ae79/H35y306885t34uyjnoI1y1rzvMcWhxKimOE1n/sNfvPwPun333zjE/HY41bM015ZGIExYO96YPmxgN+U/rRpz6R4vWusfbD3zGIeEcUMr/yfmxF4Lq58wxPgOI5x260HpsTrh3dP4Nxjlhu3DaMYb7zyNgDAhSetwqlHLDVuu4OQZTtGpkremcdDu7NJ0bYD9dpu3pfdJ/1KbC9pJlOTSZspamGxYHFgMutf9pJFBov+w/t/eD+6EcM7vnEnXv64Y+o1piRd2xJ2c4XFobAb25G9Hj808odu33wAv354H753xzbsm7AdoUX/4APX3I/7d4xh1VADV/3JBYKsA4DjVg3hv1/9GJx8+BLsnejglf9zc9/m6FgsLoRRjK/fshlv/PKtObIOgCXrFgIeug74+OOA774596etBybJ63okhsXCxsa9E7hl437c9NBebB+ppxrbuHeSvJ6o1fYRQn5t3FOv7Ybd2fs376t3ve4gx7h1f722W8i9sf1AvyrsEsLOKuwsLBYuDpAFgb12ntrXOGI4E07UzhnvkmdQ5+BHSxwqWPiEXWcCaJM8rKn987cvBxHrdmU3xf07RudxTywsMrTDCF+/JZFU//sfnIOzjlqWe0/Dd/GF152Po5YPYOPeSbzhit9iyg7MLeYQWw9M4Zz3/Ajv+Oad+JHGiv2mp580D3tlURvXfyj5/86v5f7E7feArfa7UNEOI0Q189wAmSyj6jMTbCIk3Uai0jTB+l3Zth7aXY+w27I/29bm/fW2SwtNTLTrPTvpfdJLwYqDgaFmaont0/2zsLCoxoHJjKTbO25V7/2Mpa3McFm73+2S55dV2M0ZFj5hR9V1ADB1YF5242Bj3c5x7WsLi/nEB695ABOdCIcvbeIZpxVb049eMYgPvuwcAMBvHt6H119xS++BpxYWJWCM4Q1X/BaThBQeanj4/OvOx4rBAK970vF4x/NOn8c9tKD4+m83493fvUdP3LgkxaMrq4Mm2hWEXRQCv/oksOu+2dpVi1nEdDfCMz74c7yEZEqa4mFC2FESzQR7iH1630S9SeVmom6jajsTSMTZdL0JEr2+65Ju0n3S6U9CbMgq7CwsFjxGrMJuwYCOj6fq5g1KCrt6C1cW5lj4hN2EEtY7fWBeduNgg65c7J+0HaHF/GPPeBtf/FVSde5tzz0NrlueI/TEk1bjn154BgDgpof24o+/cEt9KbaFRQG2HpjCp6/fgKd+8Ge4b3umQn75447GD/6/p+AZpx2OW//x2fjni8+cx720oGAsyVD5wk0bcc3dO/JvoFkp+x+W/kQn91oS49bPA9f8LfCJJxVuv261TovZw51bRrBtZBp3bD5QW41BLaJ7arYdJwq1sZrk1/gM1GpUGTcT0m1GhF2fKtgGU4WdzbCzsFi4oBl21kXT36DRRLULhFCFXR9bYhlj2NWnhZZMsPAJu+kR+edDxBI7SgaKYzVXZy0s5gKfu+FhdMIY5x69DC977NFGbf74ySfgM695HAYCD79ctwfP/ej1aIf2wW4xMzDG8Pov3IL3XX2fyId63plrcNM7n4kPvPQcHL96CAAqSWWLg4vdRO2ktTbSBTrl2V9JRKy/Lvmf6fuXf/nevXjMv/7Y5t/NE2jxhHU1VXJUKVbXIjoTAkvebu9ta5NuZPJbd7vjMyD7Dha4wm7STvItLBYsRonCLoyZddH0MSiPUFth11kYltj//vlDePy/XYfv3L51vnelJywCwu6A/PMhYomlHeFon1b6sjh0sH7XGD75i4cAAH/61JNqVem76Iwj8K8vPgtAYm265OM34uq7ttuHu0UtRDHDbx7eh/F2iJsf2ov7d8grfZe/5GwcuXyg1rXZ99hxN3D7V+bHhtCewUoq0yvZNhBr4wYdYUe3qWxftvppBpwRUaJP5ouOfO7Gh3Fgsosrbtqo3+c5wt1bR3D51ff1LXlSB1HM8JdfuQ0f+fGDtdtumIGtVVLJ1VzAHJ8B2TcT8mtGROEMtktVgdPdGGEfPmd5hl2v98SvN+zF7/3nL3H75gOzuFcWFhZ1oBI/tYkgi4MGyiPUV9hRS2z/EnYfvPYBAMDffP2Oed6T3rDwCTtB0KWTsEPEEkvlq1ZhZzHf+OLNmxAz4BmnHYbnn72mdvsXP/ooXPSoIwAA9+8Yw5uuvA3/+9sts72bFosQe8fbCKMYX7hpI17+qZtx1j9fi1d95tfi764DfPONT8SKocY87mXvmGiHuGn9HtywTol/CDvAJ58E/N8bgd98+uDu1AM/BC4/Brj5v7V//uC19+MvrrxNn0O35VbgA8dr93kLyQQb0S1EUWJSIewoadMJ4zzhP7E7e63YaWnERO3BKoAf3Lkdr/v8b7C/h5yeF37sBnzq+g34f9etq92233DbI/vx/Tu34z+vW1e7+vfuscyqUvc8zhb5VdcSO3ukW+9EYVt3rZdtV8mt68ecuKFmmmHXI2H3p1+6FfdtH8XLPpnmITIGrP8JML6r1udI/dfUfmDfw8VvVrB53yT+++frMyvg7geBjz0OuPPrxp9xw7o9WLeT9HOP/Drpe2uA0cWR274I/OLfCxdMVKzfNYZPX78hI3W33Q5svNF42/dsG8F//Wx91n7rrcDD1xu3t1jYUAm66T7saywSSAq7Tt0qsdQS2/8ZduECjT7xq9/S5+AE3bJjgJFH+prdnU2MTtFBplXYWcwfxqa7+OatCbn2hqec2JOCyXMdfOaPHodbNu7DT+7diWvv2YGLz10727tqscjw3u/fi8/e8DCWDQQ5gqfpu/jem58MADj1iKXzsXuzgm0HpvCqz/waKwYD/O6fnpP9YZIQePvNJ5ISJvcBgyvrt/u/NwJgwLV/B1z4JulPnTDGf/0sUdv+4YXH4YITV8ltf/DW5Ll99duAx/+J9KdxQvLk1DVhG4jJd1yisOM/Lx8kJG2bVFNXlPjUfruzh4yTv/jKbQCA//fTdT1nIv7m4bzqb6Fh73hGtN26aX9p4SEVlLQar1kMYSaFFGaLdKtvTaUZdvXGcJXXuuF2k59DLBsIam1/rtHyE4VdGDOEUQzfq6ct4M+CbpROzB68BrjqlcDy44C33FnZPo4Z3nTlbfjpA7twxesejwtPWgVc9SrgkZuAP7seWHtu5We89Wu347eb9uOuLSP4xGWPBb75emDvOuBbfwKc8/LK9ndvHcFln00Wnja+/wXA6Hbgc2n//9f3AcNHlrZnjOFv/vcO/PyB3fj6n12Ik1c1ge++OfnjCU8Djn1CZfuLPpyQa8sGArz8cUcDn312olT+k58CRz228hhe8P9uAJA8i9/wpOOBL1wMdCeA110DHHdhZXuLhY12VyZ+rMKuPxHHDB2y6DOjohPhLFcD/vn7gUduBi79GhC0ZvezFxgWj8JuOJ3cdw+N/Jkxq7Cz6AGMMVz/4G584ucP4T3fuwcfvPb+GZdb/9otmzHRiXDy4UvwxJNWVTcowfnHr8TfPf9R+Nnbno6lrf6aRFj0D+KY4cM/fhCfvSEhqlSy7swjh/G5156PU49YuqDJOgBoBcnkdVoZ/Ep5rZN763/wHV8F/v0E4Lef0/75jV++Fa/41M16y1xUTDBs3p+ttmrJr5LYCqr2yT3X1GwUlbBTiJoc4UfbKwt7lGjaOVqvP6SFKjbuqbe6PNmnVTp7xfaRbPy1qea5oGTtQc2Do8RZXTvtLFli61pTVetunW3ryL5+QzPIpiadKE4UYYaqMCAhiET7MAbu/0Hyw4FNwPRoQasMm/dP4pp7dqATxvj1w3uBOErIOiBRqBngt5uS/vmHvHjO7geM9x9ICG+OXWPTwP3fz/64b0Nl+3u2jeJbt23FvokObt6wFxjZnP1xRzVpSSsvr9s1ljxjeKyAgUqQZhHfvXUkad9NP/Pub1S2t1DQHge+9ocHX00/A6hqdUvY9Sc60QyJVaqwi2aRsGMM+PnlwIafy/1fD+jH6Ie6WDwKu6UpYUfDDxcpwigun9gcghiZ6iKO2YK1vR0M7B1v413fuRtX3yVXX/yvnz2EP3vqiXjH806HVzOEP4oZvpBmPv3xk06YtXywRZUzZjGreHDnGJ7zEb2t5pXnH4N3PO90rFxE/QAn7Ka6ERhj2b1Bc9gmeiDsvv1nyf/ffyvwuD+W/nRgsiMmmvfvGMNZRy2T2zpe9np6FGgNix8f3k1z6DSkDb23lbalSim1+phCuuWJCGXQSQk+xbYxPgOl1HZCSuZI1QpQC/BiqPa+nVRrrTsuod9X/cIRvZNuMyocMZNKr6o1tR1h2aDZGrratk5xBnU/+5Gwa3gy4Tb4o3cA93wb+PMbgGVHlbZthxHapNr8yFQXhzFyX+68p1LdRUn7PeNtYJSElPfq4qEZmmEH8MufUZQwu2fbKA6ndt6R6tB0uliye3Qa2L8t++Oueyvb03t5vB0Co6S9wQLRup3ZeepGDBgn485DpDjgrOL6fwfu+27yT1Gm9yumlQJylZVix3YAzWGgMTiHe2WhQlVCzqhKbMlibm1Ifc7MHAgHlEV9aSzdK8Z3Az98O/DoPwROftbMPssAC19hx20uS9PcrO7iJ+zUwexYzayYxYbpboTf++j1OP99P8HP7q+XUXKoYNfoNJ770V8Ksu7xJ6zEa594PFYvSQaNn7p+Ay6/+r7an3v1XduxZf8Ulg8G+P1Hlw+kLSxmgjhm+P6d23Jk3UmHDeE/XnYufveuZ+P9Lz1nUZF1ADDQyMgxOhGVFXZKvt0MsWlv9hzdoFNKhUQ5p0y+aJXVbbqKq1TpNrZd+pOU61VTYaeSZVK16bAtr/wqn0XJpboEBj3GPTXVyvTZ/arHH1urbT+CVvmtm2E3NgO12kwIV+ma64SSYrJO27oquRxxVkNtKfUDSFVkPbZVf+4H+J4LvnYY7n4I+O1ngal9wPofV7alcTEAMDLVkRVpBmQRvY73jHWA/RuzPxoo9FTl7HQ3AjzyXBqtJtxoP7pjZDo5ftG+Ot+XqoZ3jbXlYzA4B1S1vvXAtNxXG0ye95Ecyk37JhIypkb7QwVhFOP2zQeq+51HfkUa9aBiuuOrwKeemmQpHiSoz+RS5dae9cBHzwa+8cfF77GYE7QjJWuwLmFHr8doFhce95Jc3wObZvRRKlk8K8+9n/xzspD05ZckKuw5xsIn7PhK+dBhyf+HgCW29qrFIsevNuzFtpFphDHD9+7cVt3gEEMcM7zrO3djz3gbywcDfOn1j8fX/+xCvPtFZ+JXf/csXPSoJGfoMzc8jNd+/jfGAdadMMa/fD9ZqX3NBcdJxIKFxWxgvB3i36+5H5/8xUM48e+vxl9+5XfS3xu+i2+98Ul46WOPXrTq2haxd0l9PZ3ATegJu7u3jiR2JBWqvUwZbGzalxF263cqyrawo5Bf8t/HynLo1PcrxNl4mWJJVbYo222HJQMylezrqAUrKsiiOAKu+5fEmqFgvIrsmx4BPvFk4Mf/nPsTJwrPWDuMP3vaSfm2Cwz03NVX2M1P1VS6AMpY3h5U2nYGBRxUVUOdCUT+Wq+z3TmYuMwBmmmOHXbenf2yxE7PoS5gj0x15YIzBmTVLlIAJVHYEbKqJuEHAKNjY3KfOa3pkxXQ4xid6srbHa0e5+6ZyLa3a6wtPy8MzuOByWz7O0emZZJxqppwo4Tf2HQoE3YG7Q8VfOhHD+LF/3UjvvzrCkLCIdN1A8I3h/97I7D9jiwH8SBAJX5KiaB7vpWQPQ/+sDfHgEXPUBd8anMKVFUXziJhR/s5aunvATl79mzwJuvIApKBanmmWHyEXdQ+KEznfEK90LhV6lAFDeu+a0v1QOhQw6d/uQHX3rMTgefgE69+LJ5yymHib77n4jN/dD5e+8TjAQA/f2A33vcDM6XdNffswO6xNg5b2sSbnnHyXOy6xSGOv/3mnfjvnz+E9//wfvG7NcMt/PCvnoI3P/Nk3PnPz8GywcWddeh7LgIvkZtIizV0Aje1P0fCTXUivPBjN+CFH7shX3E1R37JqpGtxKq5R63Yqbbt1CDdoq5C9snbpcRLN2IyEZEj3eSfc8ohSoiodtoShd14O8w/T3/7OeCX/wF88RKooMowbZXRO78O7LwLuPGjue+Ik0VLWgs/nQSQlUV1FXa9quQYY5IltI49lDFWTvRWoFTVWYGZkW4l13oF1MmZSuD1CxrpQkVMraAGRIVKFB+Y7MqqOB6jU4JdY4olVipYU002qf3e+IjSRlls0IEqBUenu7IqzUDlt09S2E3L2zQgDOkzY7wdKorueoTd+HQoq8AnrSWW45O/SAo0/dN37il/I/3OR6oVljlwW/hBtCPnCbuSfore55t/PUd7ZKFDjrCr+0ygqrrZVNiVxJjUhXpMM85THNsBTJBr9sAjM/s8AywCwi5VAgxlJMRit8XyC40H68Y1V4UXG2jWx0O7x40VYocCfrVhLz70oyTs+D0vOiupdqbBP198Bv7t988GAFxx80bct718QLhxzwTe9X/Jyvel5x8jcrYsLGYLY9Nd/ODO7bnfP//stXjU2mH8zXNOO2SuO5FjR8kIadLGcuryLaT4wy1qBVJ1wlimkstZU8vb0oqXozXb5gpH0PZdZcCm2II40cLJzQ61eajbzWXYZfscM83EYieZTCnnWVWG5cg+OkEak/ND+XaXNBcHYUfJWtWaWN22N5WcSrCFMUNkaGsNYwb1rTMi3WoQZzMi3dIxzmCqaq+nzpPb9uvYkRN2kjrOQFmmXjsHJrvy/W9AWFB12X61/fRIpShA7TMnRhTFkAFhN0b70alQJgoNcvT2koWWselQOYYDle0PTGXtJzqhvMhhcA4pYT/WVttbhR0gPzuWVi3aUNJ4fGFE//Dn6PJ0UbVU1bR3ffZ6zDqlDibUZ0CdiAXEMcDI9zqbRSfoNT9Twk659uos7Gmx9Vb5515I9JpYBIRd+hAYXAUgDb1Y5LZYvmqxYjCzgE13+nPQdTCwkeQtxSzN+7DAdDfCn33pVnQjhueccQQuffwxhe91HAevesKxeME5a8EY8C/fu7c0j+fDP34QI1NdnHv0Mquus5h1MMbwo3t25n5/6eOPxVuffco87NH8YoAUnhBQn3PKgGYLyUC6c8sB+b054qy4gEO+2qraVlXJ0QIAVco+hbArKxyh5vYox8+VQsNpdWmJAMkRdooqUJlg546Zkga775f/RN4bM83KLc2OUtpyNdBiIewmJUusucKuE8bSJKFO0QkdWWU64aBtef60KXGWqPNmYmtN3svv7Vpt033kk/xe7LTa+6SPwBekHXrvjeefCSpyltiJSSAkfYUB2USVopOdMN9/VCjU1IWHqbH6CjuqFBydViyxRu2z8zDZiRTS8kBl+1GikJtoh/LzpT1aGS5PFXadMEYoqWXGe8thW2SgOX/j7Yr8TLpA165WWEpQr5fZLAxQAnWuOlmmaqL31Gh+odZi7qA+L2uJXmLlWprNa4uOS3st9pNieqa233U/AT71NOCRVP2542757zO07JpgERB26UOkMQQEg/LvFin4hGBJyxdqgkO1XDZjDJv2yt/35v2LW2Fpiu/cvhUjU12sXtLER15xnlFFnHc89zS0Ahc3b9iLV33m11KWC8fdW0fw/TQr8N9ecvYho3KymHtMdkI8/YM/wwWXX4f3pUVQXnPhcThq+QCOWj6Af3jBo7C0tbgtsDrwfEjJYqIqyRUFGrW15iyxVQq7MsKugnRT7aWl281Vei2xCYZKX1SgsBseCKSfk+0o5yqnCqwg7ChRoEwmVAteTpFIw9oVZQQ/3qHFQtiRQXBOXVmCmdhVdIo4U5UctYMubdYjv7oREw7nVuDW2m4cM6FqGB7g2zVrS228vC+spwpUt9ufhB1X2LnUSmliJVWuu2hSIdcMyCraD3Ujhki1oFaQfmqf0B5XCbtywoUxJhN2U4rKz2DyKtnE26rCbiSfY6qAPjO056Diu1AVtuGUGmmwuOdpJqCVwRkrKTwTx/I1Y2CJljCmEN0G98BsYFosoiV9TelCCr2exixhdzChPgO6UY2ILZWgm00iviTvuC7yCrsaDoCoC1z5UmD77cDVb0t+x7NVlx6Z/G+g/p4pFhlhN5C8XuQKO74iOhB4mVXqECXsxtuhGJg87rgVAOSJ6qGK6W4kcr9e96TjjSeEx60awkdfcR5agYvfPLwPF/zbdVi/K+s07902ikv/51eIGfDsM47AmUcum5P9tzj0EEYxzvina7Fx7yR2jrbF6vOrnnAsrn/HM3DD3z5j0SiR6qLlc8KODKwqFHZUaZwjT1SFSKdY6VZtiS1R51VWepUnHmpBJWkgyQeCvNoiIfCo2mm4pSFAVLJPITtzFTvLiMYKVWApSakcL7fEVtqhFgjohLPOCvZs5LkNBB68tLSoKQnF39fwXEGKG5N95H1CrWa4XWpBqqt0ozbe4Z4Udvw+qU/2HUzwohPeNCHHDIgKlSxjal9noE6a6ipk06TSpoJsyilEVYKkYh8mO5Fk6x6dDuX+3oDskgi7bgRGzx2LKkk/9RiiaaXfr4geGlUWieJpZXuLPLrIBPsn5XNUWKinMw6AkCgGxLUElWA2sETPBqaVRbRS5Ra9Hg8C+WGRYUYKOzWzblYVdrOXYZcrOlGHM6FVxnfcmUSb8JiUE5+W/H8QKl8v7FFiHGeqgsaSTGG3yAk7fqG1AhetwMPYdHjIVorlpesHGx5OPnwJfrtpP7YeWNzfvwm+/but2D/ZxVHLB/CnTz2xVtvnnbUWnww8vPbztyBmwEUfvh4nH74ES1s+7tk6ik4U44jhJj74B+fM0d5bHCqY7kb492seQCeK8OVf5UNbT1+zFKcdsdRIHbqY0WpoMuzUCU+nmITK2RMrc+jqWGKL206kE09OpOSLPyiVXhXSQhpkcdKttSyxqJKVXIkA0SnsKtR5amZdOWGnkm4VhJ1kZVLPVaqwayzsoRgHPW8q+VqG/PcegzFmdN/z77kZuHCchKgwJb9EW98VBFFdsg9ICNddY23z7XYrrlfD7dZtyxgTk7Ne7LQHE1xh51DlsAFRoS4SxCrJZzA/UMmqWCX9Kj6DZmICQNQuV/iqyKl2J6flPsxAbUIVJIwBrD0G6W7qTgHNpYXt1QltlCPcys+BqhaL1H1e5PM0E+xXCjoVEnYqwVvbEquqTOe+8EQYxYJ0XlpXYTdpq8QeTMzMEqsWFptFhR0lcWe76EQdzmSXUojx3u9mJN7xTwHuuOqg3FMLe5RIcykkhd3illrzC60VePpso0MIe8aTzmH1kiaOWp58/4e6wu7BnWN47/eTEtN/9MTjEHj1hbRPP+1w3Px3z8TzPvpLjEx1sX5X1nE+/oSV+NAfnIvlJEPRwqIO4pjha7/djA//+EHsHss/4O9693Owae8kDh9uHvJkHQAMpJa7KR2BxZGzl1JLVT2VXGml16rCERoCa1lKLOSzoOSJB1f7uE6SB6dV2AnCbpq0q1As5Qg7+WeVtMgF8Zco7HKEXZkiseBcDTUXfqxAJ4wlK426ol0G/r37roMwneR1oliQaCZtm74LBylhV1Ml1wxckZnWC9nXCnpT57kOLRxh1rYjEYVB7ncm+wwQsq9fM+zScYsXErKrM5YUfHCLr4tJRR3nVhSc0X6GQjaxHNlU/hnjCuHHVEt+hVJQJbvinJq6niUW0CgNKxRu6v2bOwcV51GdENdtfyiAWmKBktzPimduJdT3HwRLLH0WcGdEYT8Vx/I1fZAUgBYJZmaJVRV2c1QltjuRXCdub8bQGRWd2LNO/vnG/wTAgCVHAKvTTO2DUEhnYRN2osN3ErLOTwmE2bxg+hB85ZoSdnUGx4sJe1KF3aolDRy1IiXsDmGF3chkF2+44reY7ER41NphXPr4Y3v+rLXLBnD1Xz0Fd205gCtu2oShpo+/eMZJOO+Y5ZZEsZgRvnjzRrz7e/fmfr+k6eN9v38WlrYCnHWUtVtzGBWdUCZgdNI3WlNhV2prVberkF8qgTXdjTLCTp24FhBnwwMBDkx2FVsrIezoz5BJB05+aS2xwVAy8Mttt6TaZxyXKuzUgV9u8ayEsGuTZ/lCh0pytENzlRxXOA4PBMIK3w5NCTtOnHlw4ADomltTSdtmzRw6nn+XqPN427pkn0fIPtO2yXYbnouWX3OfFVVgnbYHG/z7cHNK4vGsD9BgOr0fBxseJjsRmEpu9aCwY2p/WaWwy/WZat5oPbLM0Z0DxrJKKRrkFCQqQVZxDLkJbc3zqIa8193+oYCcJbaoOrZ6rupm2Knvn2GAvwnootdgqiAvVG6p+3OQMvYsEqgLlPUssWqG3RwRdkDSbzaXlLcpWNBRx2WlBVBU8MJHJzwNePgXwGhaEXbtecDAynQDB8w/r0cs7Aw7fpM3hpIHl9dMfp7NC6YPwR/EA4Gnt0odQtAp7LYcwgq7/7t9Kx7ZN4nDljZxxR+fP+OA/qOWD+B5Z63FVX96AT7zR4/Do49dYck6ixnj27/bKv182QXH4id//VTc9e7n4JLzjpqnvepfCLteWdEJZUJEJ505q42qEFFVY+T9nUiu4Ckp24FKtZqsdFNJRqXSa9qWE3zTOpVca3luu1RlpSVASsg+uo9Z8QBasKI8Pyifv0bJvki2AefaZiqthY6coodplIoF4OdhqOnVrtbK39f0XUHymC5gzoYlthl4PbTVKftMicI0d48cr7kqMNmG42SFTvrWEpsq7PxQ6asqyAreZ/DKlKKP4fMDAwcOJ5+5k9/hfavjyp9p2D6/uFJBdnWz7wnQEHYsriT9coRbrsp2eXt1TuHkCLvy8zittHfV73GRO6FMcCCnsCsg7NTvrrYl1swWvmt0Go9/309w+Q9TC+CvPgHc8JF62+KbkAi7Cfa7xgABAABJREFUiv5RV3k+0p+L8XaIy6++D3dvLa/UzHHH5gP4l+/dK+aKFnnMLMNOrRI7i/yLSvJXqXJ/92Xg8qOBh36a+5P6fDVVpQPILNonXwQMrsp+f+wFwMCKdAPVlbNnioU9SqQFJwDATx/Is+mh7kPwTq8VuHqr1CEEnmG3eklTKOx2jEyDVVTAWoyY7IT4zA2Jr/5Pn3IiDl/amuc9srCQcf+OpGjJHVuywdZ3//JJ+NcXn42TD7dZdUXgeU6SVYEPupvDyf85wk6pMkjRVS2i8gBetWRN65Ru4mf5s1SypLxt9jPNvNEG4gvSbTjXViZeknMlk4zpPg4s1+4z386yAc12K9SIpbl7FRV1p0Ue7cJX2IkCDoR8rEtgtXxPfH+mpNu0jvwy3S4lv3pWyVHizHCfu7NAFJK2psRoh7Rt+Rolah8hOacMfqSQCxVkBb8eVgyli5W8b+MTLQNlFye7DluazCkc3l/wz6iYOPLvaOVQI22fbpNP7ir2Yaojk45Z+5XZm1S1MkEcMzEn4NWPnYiojA32gd9/3M7ocmuyeN5UqATDTFgAAB4nCP2W0fYXPKZHErJr/6bCt+zLZdgVTPjVha7ahJ3yDFM/L8VP7tuFXWNtfOoXG7Bvy/3ANe8EfvJuYKJ+phwnfQLPIeOXCoUdv7aAfGGsFB/44f341PUb8MKP3VC88bu/Cfz8A5juhLjkv27E5258GP+nLBJbZFCfAbUssfEcEnYVsS85fOcvkoWI770l9yeVI+mJsFtyOHDGJclrNwBOf6Gs9p7jHLvFRdiJ6nGHhsKuMsNuYg9w1zeSVf5Fikxh1xAEVSeKcw/CQwFf+fUj2LxvCmuXtfDyxx0z37tjYQEAeHjPBJ72wZ/hU794CL/3n7/EzRuywd8d//QcnHP08vnbuQUCnkMpTcz5BKhgEjlBFA7jnVBexMhVTVUIrDISik+0RJEnfbXWwHPyn8W3K9Tw2cSBEhbLdPlatOiE0rZTpXbqKm0LjpcThZKyr4Kw4xNTcbxhWVs1s2/xKOxEMYOmL5RBxko3TmAFBQpJk7Y+/e7rZth5PSjdZscS29SpOk322XfFRLh+7p5XW513sNHwXDQQwmXp4gHv5yryu/j4WJBdXYWwqyCawigW50kQdpzs4oSZIdm1vIhwKyBM1PYrBpP+qMXSxYnGEtJ3TuuaApDnA6uWNAAwuHwizRct1EUbBZy05MSnx8/BoNk54N/D8vQYRBbh4Ork/4rvYcHjho8kZNf/PK3wLQcUS2zOSs2hLnTVPXe5wiv67953swXT/b/7Pml/oN72AIQp6RN4WT9VSJLwfMPWMqCxtHSbNz60p3rj3/hj4Of/htF7fix+tfcQnBOaYnarxM7ieVb7GNPP5uIt+lEKCdkTYTe4CnjOvwLPfBdw6VXAYacCnp9ds3WzJWtiYY8SqSUWyAi7Ra+wyw/YtBffNX8HfPP1wPf+v4O5ewcVeycyS2zDd7F6SXKjbh8pH4zM+n6Mt/Hp6zfgvd+/F5v3HfyByPpdY/jANfcDAN749JOwbHBmVlgLi9nCB6+9H5v2TuLyH94Pyhm9+Zkn2+vUEA0/GUh3JRKKT0T5JFDu86jCLmdPFO9NB+hkAhnHLKfYkYkzrnRbntsubadVq3VVpVteJQcAwwOJqkOuEqvYWqNOki8HaBV22gy7Ikssyc7Lta1QyfFzk9l466vzmotCYachsGpaNZtEYVebdOtpu7OhdJuBJbboejXZbtDDuZqBsu9go+G7GATp0zjRY5idlqnTVKJpEihxYEhk11AynnT5nEKo9CrsoArh5oZKX11FdnVl0nHA4YTdYKZQKyHsqB12xVADDRAiiPfbJZZYxlhuH8Q5EKSl2Tng/aIbp5Nt+j0sZmy9Nfl/ar94TqngRSfWLku+08J7USyScXVkzXOnKvIKCGMpQ29yd3F7A3SEws4V9vZCIohfy34rU6EWqJVyFdxVEIEK23GXeH2oxkaZgH8vld+TDty67KdFP+dSYacS1xSUxB46PPfnfGGNOoTdvuT/wZUJ3/TUtwGnPDv7O8/Vs4RdCfgXxDsxXnSi7EtdBKBByQ1uidB19Hd9Pfn/d18+WLt20LFnLCs6AWQPvh0HkbC76jeP4DkfuR7vu/o+fPaGh/GUf/8Z/uHbd+VKts8VGGN4z/fuRTdieNqph+FVMyg0YWExU3TCGHdvHUEcM9y9dQRX37VD+vsLzlmLje9/Af7mOafN0x4uPAS6gVRXsVkpzz21CICkGjMkzvgATkt+adrSbQyb5NB1qcKOhOlrc+gU0g0Qi3OS2knkmJmRjBEhKDOSUXOeC37mCjvt8VYU6BAFpBaBwo4SSfWrpmYxH5xImu6FdJuBWq1+20wV2DvpRogzw+PlY72G1wvJmN5jPRCFBxu+52IIZCLPJ0UlRBWQEUXcjpopw3j2ECv9DF1hjrrqMn7tcoWdlyP8yo+Bk2VLWj4818EA0vbBIBBUE3ZSzrXvoQmi5DKw5dJzsHywAQ8RXJZeJ/wcVFlipSxBBj/mhB/f/iIn7FaemL0e2659C1fYrUnnLYWK5FC5fnSW7A0/B770EuDO/83/jS86VWQwSgo/+v3WLXIBvSW20LovEXbp870gxH+yXdFfUSvt2DbxMlft3kKAq88G0qzBnqrEcuEUiwvzB+vvWHqdmpCBBRZq8VHKtWcaIwEgqwBLIwkoGumzaY6LuSy4UeJtj+zH13+7GXHMNJZYnmG3uKWv/EJr+NnKhfbiW9ajLZIx4Id/C1z7D6Urkf2APURhB2QPvh2jB4ew+94d2/B337oLeyc6OHxpU9iirvz1I3j2R36BB3bMLeMOAN+7czt+uW4PGp6Lf7nkTPjegrutLRYR/v2a+/HCj92AE//+am3OyF8/+9R52KuFjayf19hahWqsulprvu3y5H8NcQYYkm5hvq3jZNlJpmRfpfpHVdiRz6Or+Vr7sHquorZ4ttHFrmFeOVN3vAU/qwo7be4eh1pkYzEp7KTvT0OaGrXtRWE3A0usZrvmBSs0ZF/N420Qu9i04T4Lws53xXjDVC3AJ2INSfXSn2O8wHUwKJRlQ9mkrYLoaavKMFXdBhiRVbyAjYsYHrflGmbQ8e9yZboPflzPEsuPYbCRxN4MUsJOZMCVkY48Nie5NiXCjmeAlpxHqtBbPhAohF81aUkXQZYPBrLCb4Eo7O7YfAAX/Nt1+NZtW3r7AEp4FRwrj+6pVNgJlWgJ2fmjfwQeug741huK90WoVPXXzng7+54ZJQV7UA51Q2KJ5c/kquMLqhV29LmuzSon7ZyJzD5baDe2EM+PQUHY1SCzeIZdYzD73WxwMFEX4IsEBc4ICbRP5QQbAT8mHiNmbImNwux+K6pOLhR2c0vY+XP66bOMMIrxJ1f8FnsnOtg91sZfDCmWWO5bXuQKOxruzK1S2ouvV7Jt9/3Arz+ZvD7nFcDac3r7nDnCX37lNtyycR8++AfnYs9YlmEHHFyF3XQ3wuVXJ9WULrvgWLzrhWcgcF18785t+NhP12P9rnG845t34v/e9MQ5C9O/Yd0e/PXXbgcAvOEpJ+C4VUNzsh0LCxPsm+jgS7/Khyw//+w1+KcXnokjhpu2sEQPCNTogzgG4nQA2kzzM8ggiTGWI0u0hN3ACmD/wxIJxdt5roOhpoc940Vtl6c/50m3lu8JEsqc7KM5ZiXKvsaSRCnAYrFtPhhr+q5YsAh1hB3fZ77fQUtLUMo23plUtjWrqLsoMuwiXaXe+uRX/Qy7jJwQFWZ7KOCgVbGWbpePw+pbYrvSomuy06Ehccbb+p4j9rlu28BzEfj1yL6DDd8jlliqLDNUp4nsNa7saixJYnOiTrLYP6hXS6jZhC2Qyadh0QmhLktVfr5Q2NWzxLb8RK3a4rncwYCRJZaS2C3fQ4MTbn6LZI8W7wPffsN3Mdjw5HMgSMvic0CfF8sHVcLPjPScb7zuC7dg30QHf/31O/CSxxxd/wOo4kdDsE13I3Ge1wwPiN9pIZ5f6fUTdRIiwSNT+AObyYePZsQs3f7gKmBiVyFhTBf5HImw60FhF+sW0Qr6Kaqw42ODggy7pu+K63u8HWJpS4lVIco8Rq4xq7ArBn9+cDKrnsIuvbcDQtgxs+d+KWj/0FoGjO8ojzuj7+eZc/TP6XNuqOljqhuZR0FQ1RxX0qmwCrs8frtpvwiOvPaeHURhl54skWE3t6V15xvUElHuOSc3XZ3CE5tuyl6vu7aHPZxbHJjsYudoG9tHpjCarppwhd0Rw8lg5mBk2H3uxoexbWQaRy5r4R9fcAaavgfXdXDJeUfhK3/yBDR9F3dsPoAf37tzTrbfDiO853v3IIwZXnDOWqtcspg3XHP3drz7u/fgZZ+8SfsgfNPTT8aaZS1L1vWIHJlAK3M18lYxydaqUzuVVE1tE5tmq7SAQ9pWo84rtAmWWnFpjpmG7OOEpN/KTVo76Wq+77kIXA0BorPTppMWfmy+62BIqAJL1HnKgqCa1aSvbLtcPn7lmBdFlVhdxdWesuRqFn+QFjDrbZfatnolvxpefbIvJJNZv6bSjb8vcAvUpAb7TMm+/iXsHLQ40RMMJP8Ag4INyfHwAjKNmJJ+1WSVnBGoklXL030oH1/ya5cXXGgwskBSsX0gqxLbangYaBCFnN80ssRK/XDgounQ9tVKRVHYLiXQxfa9BvkeilU0lHgaVhV64nnV38KKGReukwi7aXzj1i246MO/wPpdiVqN22E918HqpcnctVphR1WihFCLQlkFt2ed3J7PlSss2WNEheaE5ProSWGnscQWLeB0CWFXobCjvaRatAMAME3akWt8zBJ2heDk6kAvCruILAaov5vRTvE+0skWpcsKitJrWmPh5mPEJc2ax8hJODfIYtdU8OrGizLD7oFrgN9+vnaze7dlX8KDO8cQtwsUdou86ERHM0DVK+xKbD1l2P1A9npsR/H75gl81XL9ruT7911HDM6Ewm50blfv9oy38YmfPQQAeNtzT8tNuA5f2sIrzk8syX/z9Tuwa2z2CcSP/Hgd1u0ax8qhBv7txWdbK6zFvKATxvjzL9+GL9y0EQ/tnkDDc/HDv3oK/vEFj8InL3ssfvTWp+Ksowqk5BZG4CSGGGRQy4FmMEMJC20xhBzpllfYJVlkGptgCYE1TRR2LROFXVejsJMslZrt+s1k8ASIrBQd8SJbYonKhuf4pL+bVhQ1yb6U2IcJYUCr4moVdiJnMN8WkG2kCx2Sqod/94YKu+w7qF81lVYjFCRUQci7Ck5++V4v9lJ6zXGS2LBtmN/n0HCfBdnnO/BrbjeUjrffLbEumg4n6ZvEEmuWYccL1zQYV6flif6y9tzqLAg7r0Hal88x+GfwDLwGUxR2VTl8YtEkscQ2qUKulsIu6dMywo0SdsVjZKnqduCi5dDFkup51jSZowwGPprQLbYsjHlao9e+WVHYve1/78D6XeP48y/fBiArOLFiMBDKpkKFHb/mm8PZ84tabke3yKqm/Q8r7bnCrtyOTFVoHn1W9ZRhp+mXKxV2zexZSTPsJvcJuyEd22hVc7QdVdhNL24hz0zAnws9WWIjov7lqCMQKtwpnl9n1udIY6twKucw7BCFHVDDEsvJ7maBuo7+bdEp7LbfCVz1CuD7b5ElvAbYeiD7Qqa7McbG0k6Ee6e5wm6BPAh6hZRh55cMbukFWzHIkTBOFGHju3rZxTkFr7y1LiXsVi1pwE1VFTzDbq4Vdu/4xp0Ya4c488hhvPi8o7Tv+etnn4rDlzYx1g7x5ZvzNsGZ4Cf37sSnf7kBAHD5S8621TYt5gW/e2Q//uhzv5F+9w8veBQetXYYb3jKiXjeWWtw6hFL52nvFg84ISBIKLqCKQi7vErOJVlyMvlVTCRRhZ3e1tpW2ua3W6iwM7DT0ueaNHDkA0MvyKxAqdJQViyVKOw0E15VUUP3JdkJVR2THW9lVVxVYUcq29JqvIuDsMsTn3ULRzR8WnTCbNAv2Txr2ktDQrr1qnTzTSxfats4U3X2mkPnu+R447qqQKe3ioAHEYFHyDJ/gFhiqxR2suK1KeW/VedcU7Kr4VGyaoC4eMrVV5yw4gvJAScNacGFskq1vGhEI1G4NXSEXWmGnXw/ye15dFC1Qo8XNpEIQ4N5lqzQUxR+XKWyQIQVseG9lQMh7BghyLjQgBN2ywcb1ZZ6kfE2oK8UO75bfr+qTusQSyz9PAW0AqsrKexmUnQiex5UZ9gN5BV247uB//do4AvPRxTF0jNX+3lkXx1ynNYSWwz+HBxoJOOqrimZBWTRLF4AuL78u5mA928B7XMMFXZArn/ix1SbsBPCsBLCrrFYM+yo3XJyL7DcvDDC1v1KdbaJUSwDNJbYRV50wjR3hTLO3UkAq/Lv0YGSdH1J2CXf87qdKWE31BR/O2ZFQt5u2T+FOGaCyJtN7Bydxs8eSM7LB//g3MJtLB9s4O+efzre+rU78LGfrcdxq4bw0sf2kIWh4PKr78Onrk/Iuqefdhiee+aaGX+mhYUpopjhX753D65QSOjnnbkGn7jsMdb2OgcQhAAfZHDCznEzm5em0muTZslpCzgsz7WlCju90m1KaZtX5xkr7PhKqONIhI+WeOGVx9wg96zniqVGkWJJ2DZSlUx3UgzwtMUSpHOlkpv54wUIYafLsJOy86aBxqA08VgMRScyVY6LZlhvpZ4SlxmBVZ/8ilxNfmFZW02xElOlW1ci+3pTugWeC9+tRxSGOjWpaXZeTMm+em0PNiRLLFXYGVpiebZVVmF1wJCson0nIQ2DlhHhl+yDTBo2WBdwoFjy2xkJmduHTGEnKeR8qvIrsfUqxVQkSy1vX3IM9F5u0XNgqJATmaKBuv2FobCj94QpGZ4DsayOjI4CGJY+f/9Eck5WDAZ6JTsFXXBqDAKdMTlHUSXo1AyvrkLYFZDelDD0I6pYqv9d6VTvhc8DqrBTM+zWXZu83n4Anc23Fu6vbl9FdWfIhVQsZPDnwkDgSj8bISIKZNdPyLrZIOyEwo7026UZdopqNJyS+ld+7S3hhJ2xJTa1uZYRdotWYUdPakVwq4otB+QvpDPFFXaHZtGJZpUllnbKdSyx48QGO9GPhF0yCOKKy9VLM8Ju7bIWfNdBJ4znrFLsD+7cDsaAxx63AmccOVz63hefdxRe9YRjwRjw9m/cgRvW7Sl9fxXu2HxAKOv+8ILj8J+vfPSMPs/Coi6+eduWHFl38blH4qOvPM+SdXOE3ICXD5LcQDuYoUq3Ad1kQLVq6nLoigoAzERhp2bYkWORq19qBo48t88LcpZYPviSs7ko2UfOl0L28WIJDVLtUyYoFXKTRYIApFVxl+iq4qrWY0CcL7qN1qJQ2HH1Vka6GRdhCPNqtbr20oYXo+EmbcyVbsn7Du9sxeHTG5PfGefQkSw5ThTWVLr5vdhpeVs3I/tMtxuS7fo1lX0HG4HnZJbYgCrsisd1jGWqVW5HbdVVl3VpH+bJZJWhKIBf97yITcD3gfYDJRlyqto4U6i1SIZd8TxHrWAsKdy86nmScPGoCjuJtKwm7BqekoFnuP35xpRC7vSksiNqoPFxOdtq24EpYomtobCTioaQ60etitkjYUfnkQEhu3pRQ1JLbOk8FciuBb9FLLEpCbk5c3DEj9xSuL+5zwLgEdKxX/u5fgB/LgxyhV0vGXbuwVDYlVlilT5deU7QohP050qYWGIXbdGJGRB2u9OKoCcdlhB00bSSYXeIKewaPimXrV58USifhzoVmSSF3e7i980TeIYdx5rhjLDzPRdHr0hWYjftnZuy8d+/cxsA4IXnrK18r+M4+NdLzsILzl6LmAF/9qXfYmePROKtm/bj5Z+6GTEDnn3GEXjvi88SK7gWFgcDn/nlBrzjG3dKv3vKKavxvt8/a1EE5/crMotoOnGgq5qahSq90q2EhKKkm5Rhp2nLnyW8bRwK4ky3XX0Bh+W5z6PqH2FPpG3pMXuB9DuqlNISEREh+3jblADMLIaZTVAiTwS5uSJ3HG1TRWFjSUYyduViF66DRZE/SpVJvRZhaBQRrhVtA4R4/Z2vxp/d91q4iGso3WL4CPGX97wcl936MgxjvIYlNk+6mRd/qJHvVNRWUqLWV/b1e4ad7yrKLKEkLh7LUuJyMEgmZnIOHie7zCyxTUqWBQNG1qxuFCNK92OYZ9jx46AZmmW2XBJ7I1tSaZafQeGMnCWWWlINFHappbUlnUMDwo8UHGjlMvj6n7Cb6MiEAy3GYAxCcnWm5In85v2TOEAIO1EVvVBhxwmtZjbfNVXYxRGJoliR2zcKibCLqeCj/pyaPpMFYVfUT/FrWSo6cSD5/0C2OBwpRKS2Cjm5rv2YfAd9qiTuB4gqsTzDrpYllo+tfMBN5wCzmmFHFXZlllilP1SeE3wRjxedMK4Sq9ZK0EHkgs5tFNfBt8TSk1qDjWSMiao9Zxy5DA/tngBTvcUL4EEwG8iqxHrF2QBqyXVTwi5sZ9/LqpOBVafky4fPM6gFFgCOWj4o/XzsqiFs3DuJR/ZN4MKTDG3AhtiyfxK3PXIAjgM8/+xqwg4AXNfBh152Ljbtm8DdW0fx9Vs2483POqXWdneMTOPPv3wr2mGMRx+7HO9/ydm97L6FRW1c/+BufPlXm/AjUu34iSetwudee74l6Q4ScnlTNDdEo1igSjdBnJVZNanNU5dFRgfGfNBEVxyjDuD5WfZRUcVOvo9qW2SDxMB30RDZXJR045ZYP0e68QFnwyNqJ0lhpyHsIk7Y5W2RXV3+HbWzdaeB5lLt8XZ0BCWvztjuit91CMG1GECVSYJgNlXYRTFcxHjBundhZ7wM38aLaxWOOM15BKumNgIATnG2IIxPNG57gpM5Cs50N6EbmVVb59fNU/d8DceMjAB4bi2iEABese0DOHXLBgzi7bXJzWcc+DbOvnk9mniZsaKwE2VESv9n2Dn6YgUlkyJ6LPyeDMD7SqruMrTE+q68D0IUUFJwQamQCgANvg9+I9mHcMqI8OKL8g1aNKIGYZazxErnoEyhl22/5XvKOTBX6HGypqkj/Po4w25SIexGp7v1cqKjUCr6152W52OJwi75TpYPBQYKu/RceQ29wm4yVdg1h5MMN0ps0ffx531BFU9KqInqykBP3xXta3y3Qs1LFXZ8MY+TkCNbxNviCVlJWKWwC8gxxCxdoFkEi2OzjcwS60k/G4GTc64/uwo7/j0GZn1OjuNQfhYKu0bdohMGlliDmILZwMG/cumqQA2F3eh0KAbRpx2RnDiXd0S8AztUFHZk9a1wJbuCbS6ECEp1gL+4BXjVV/uKrAOywhIcRy6Xfz5uZXI9cIXdLx7cjWvu3j4r2/7BncnnPP74lThiWJ8/osNAw8Mrzz8WAPCN27bkBgRluHfbKF76iZuwe6yN045Yii+//glYtaRZ3dDCYoZgjOE1n/uNRNY9/bTD8JU/ucCSdQcRvJ8XA3pagEFTNZDmsol8HKkYQtpeUyVWqMZIlViJdOPbpiuOapac7yJwdaQb328ycUx/JwpHuI6w+klEhFjJbeRIt45OYUe3G1PbhtxWrzrSKOyCATJwTH7XocerrU5LwrQVOx5VaC0GcFXQoNvFgCNblavQjRjOc9bjtN3X4ql7v54o3UJzpdsZbqbCOM99qMZ2Y5zmZMXPznIerlGwgmEJJvHcrR/DGRu/iPOch4zbdmOGJjo4f/8PsGzkPjzLva1W0QkHMV6y8z9x+CM/wIu8m2oThZfsvwKnfOvZWInRPibs3MzOGrSIiqHYOUGvGU5KSmSZAdkl20k90r6eOg0gVWIlws38Mxqc8KIKOX4eyjLspKITrl5hZ0r4BW6BrbjMEiv3qQtGYdeZAHbdh2jn/fKv694jCsEVKoTdjpE29k/kFXaFGXY0DoIXWaRVYjm5tTJdqJgkxBZ9XzON8Cm49ui16zMyR+nhu9I9Vwv7R34tB0RhN30gybcd2Zq9jx4XijLssrFMELcBZNvsVzXxfEMUnQjqZc8CyMg5ibCbhYq8gqQ267Ny/aGysMOv7fpVYtP7p1Rhx0n0xUbYSQo7c8Ju73jyRS1p+jh8aTJBEf70QyzDTlp9K6oSW+HnLgQn7JrDgNufKxEqQXfUigHp5+NWpYTdvklccdNG/NHnfoM///JtuGWjkvNQE1OdCF+4aSOAJLOrLp59xhEYbHjYtHcSf/21O4xyMX61YS9e+ombsPXAFE5YPYTP/NHjRIdjYTFX+NE9O/DyT96Ma+/ZIf3+qOUD+Lfft+rOg41cJUmdJZYMwqlKpKWruilItyXZz2nVwmlSIVBLYPHV+YAMYNJBm1z9UtNWUgbKg7AOHeD7GmsqJSldvUqOZtjJCjtqp1Uz7IgSQGenpav/Sn5UZuUk1WkpUcifu5KVjRN2mSpwMaDdjTGMCbz5jt/HGze/DQCrZS891c2UFGe6m4yLP4RRjBOdbEHuWGdnLYvo8URhd5SzpxZxdq77kPj5NHdzLaLwZGeb+Hmts7dW/h093mOcXeYZdjEDwPD8fV9Ea98D+CP/2r6dxPpShdZ8dWcd+Pl3HMBznWSMrFOnlSiG6IJF03cRIO03ad9RYhEUeZqpxd53IvhOel2YZsgpY3wpw64H0lFuz4tOmCv86irkuqR9opSkVWb7eJ72yK+A/74AR//0zdKv24bVrgUUQixqyyTzjtEsw26lSYYdVTGJKrEaS+zyY9MdJpl5VNhSYS3M+i+W5S6WvL8MQrnuu/DE4l0RYafJsAungdGtEhHjTBso7Mi+uogzwr3o/RbiGcCJY8Zq5DZqCbtZUNjx75GrkoGKohNqlVi9wm5J3Qw7uuhaBMMK5jPFPBB2VGFnbondm65GrFrSyGTmEWc+eZXYfGd0YLKD53zkF/i7b8m5SwsZRkUnIuWGKVmVlMAJO2r/6TMMNnwMNjJ1z0mHyVLV41clD7Qf37MT7/nePeL3X7hx44y2+5P7dmL7yDTWLmvhD3qo9nrEcAtfeN3j0fBcXHPPDrzuC7eIHAsdvnHrFrzyf36FqW6EJ5+8Gv/3pifhmJWDhe+3sJgNhFGMP/3SrfjNxn348y/fJn7/hdedjxvf+UwcubzkwWUxJ8gy7DhhR4gvTZC6XHFVY/PkK6B8tR5MTAq69PkiKmcW2Ev5AE1jaw18zXYp6eapSjdCuuksNCWWWNnWWtLW8zPFeDqo5MSe77nEJkgtsURhp+RHUaJQtKXKMGGJJaH5Yb7tYkA3inGu+xCGwv04cfIOnOlsMp4ghRGTlG6nOTXIr5hhObKx5DAmaxGFKxzS1pmsQdjFOJ3s86OcTTXUeTFOcTKC8hRna40qsQynKm2Nq8RGDEc7WeGrVX2tsHP0yqwyZRrpBxwnVdg5dRV2Wf8nqdNo/EDJPvD7n+/DEo8slBgSXrRqckNVyIkFh2IVS5ZD6uarzBoEuIsMvXTxJFMZmirsiELQU6vU9jFhJ9SL8uRfm5VWBoXQjVOVDn827RiZziyxg4G+2BFFVKGw4wTdsqPlnwGZsKu4dsTzG8p+zISwcw0K69CiGs1hwEnndzvult7mKll92u9Fua5E0Rj0oJQ8RMAXx6hrJmKmhB0nkz1C2M1Chp20KF29UFKlsFOLThhfCyJfsYywW6wKO9rJ1FDY7SPyYR6032Sqwi4vNf/izZvw4M5xXPWbzcarrv2ODsnN0dpwgLwk1bRKLC+l3ceEHSBPxg4nVWIB4PwTViLwHHSiGHSe+bMHds1oheWau5OV+Bc/+qie7YCPP2El3vbcJCPnFw/uxnn/8mNs2S+TqVfftR1/+Nlf423/ewcA4LQjluLTr3lcvQwNC4ua6EYxrrl7B256aG/ub595zePw9NMOn4e9sgAyFVZHtcTSKrFShl02AAt8hcCKoyxfJyALAKKAA59wZoozqd8sUatxYq/hufrcmrK2NIeurNJrWVs/q5xp2pZOLksVdlKBD1klV2inpWHhBZbYYJEo7LpRjKMIGfRod53xoLgTxVjhZJPMFc64ub00jLHMycaStUi3mEltl2GihlotxjJC9q10xoxVgd2IYZUzKrU132eZZKy33RgnE7LveGdH3xJ2vutmk21a8KGEqOoSKykAjcKuWqUnV7r2EHDCj04cS0nDbHwOAEt8cn69phFhllO4aQk7k8IZnlJ0wpD4VLbvC5WhPjM1116oq5yE8HPqqRznDSlh5yqTf+OAeg7l2KKUaDjl8KUAgO0j01nRiaEGKXZU0PfQSAddhh0XvyxNc7UpYScsfYOV14743qAIPnooOiHHVFRUs6aEpONkKrsdstDGb6uEXbnCDrCEnQn4dccziwGIwjmVmOsMO89QYadeo2rRCWGJ9aSfq/eDVKstgr9oFXa9WWJHp7LViOUpcdFivAKbUiWWPEge2Jl1XJv3z+3JPFigJddzygsOdVBjukKyABR2APAnT0myGs5YOwzHkRUKywYCvOL8Y8TPX379E7BiMMBkJ8K920fRC6KY4Yb1yWTkokfNjLj44yedgLc/9zTx80Uf/gXe/r934MM/fhDnv+8neNOVt+GX65JtLW36uOKPHy+q91hYzBU+e8PD+PMv34rXfO430u8vOHElLjrjiHnaKwsAebWaREDlFXZ8pb4pEVgK2QfIQbpcrRZnA+0cCcWYnKcjrKlyZpmf2tGktuR9cH0y+ZVz6HydNTW3XV/6PGprDXTW1JIMO52dVksySuoYmezzXUefnRcRwk5MllJlHyE3FwMSe2mWdbkCY8ZFJ8IoxjCyCegwJmoUYWBS22WYqEf2gZJ95tvthPntmhZ/6EYxhilR6EwYLyh3Qybvc43jDaMYy0nbFU5SFZeZqikOInxJYWdGdHVJPwCkGW40g87A0spJAF4wQajLqI2/lOzKFg8AYMhLPo85bqLurVE0gheWky2lcv9V1p4r9OTzaG6p5aKArHBHw4hw64TyMySg59CANJ03pGSYStjVXuhXFXacsEvz13eOTgvX2IrBhni+FxJKVCGuqxLbTuc1w2lUT9TOvl/uaguGSq8dxrIIgxxh1wO5KjLs/GzxrpKw48/mocOS/7fdnvy/OhE5uKEsbqjKsAOQKWxhLbFF4P1mkyrs+sYSa5hhp4qUcgq75Hh40QnjKAhOjJso7ApyReOY4ZaN+3Drpv0zEo7NQ5XY3otOAMBwK8CygQAeouwhpBJ25GG6bzx7vX7XOE5YXRIcuEBAH8ZNVXnBoV68JQ93CQuEsPub55yGo1YM4IIT9VVg/+VFZ+EFZx+JdhjhyaesxqOPXYGf3r8Lt23aj/OOWV57e3dvHcHIVBdLmz7OPbp+ewrfc/EXzzgZhy9t4u3fuBPT3Rj/e+sW6T3nHbMcb3z6SXjaqYfZcH+LOUUcM1x993a8/4dy0PLbn3samr6LP3ri8fOzYxYCgdrPS1lwMmkGEIUFrdgpyD7yLKC5HJzACjOLaC4Pjg7EpG3LRSeCWkq3trSNgFhTs+0Si4XrZ20VS6zvFgRcR7rzxdtqwrG1FmC60quo84h9WLbElij7wsVlie1EMdY4mTp3hTOOkRp5cLJKbqKWrXWZQn7VqbhKibM6dtpEYdcb6RZGMum2DObHG8YxDlO2W8c+rO4zkJz/ht9f12HgOSTDbsCMLFNUq3KF1YYRWRQq97REVgmyq3ofeH+wxIuACGBuAw7/HMPjyGfYmSrsMsLN95ysvWGAO51j+J6TkZYFim4Vcp/qKOfQwN42X/B5Prp8bPUVdh3tzyeuTgg7bocFgCOGm5hKF9gK+60qhV1bUdgBicrObxor7KQKsbOgsJOU6ylhF8XJ4oAqspCiMoCEsNt9P7D11uTnVacAex6EZ0KkKvtKycd+VRPPN/h4h841TZXmc0bYUYUdJ3LLrLYqx6FeK7woVqNmYY2ugcKuIsOuE8V42SdvBgDc857n9lypeB4IO3JANXzxXGE3POBj2UCAQZAOtaToxH6SEbZ7rA8l2DURxUzYPAOvRobdIiPsPNfBq59wXOHfXdfBhSdlZN6jj1mOn96/C7/bfKCn7f30/l0AgCeevGrWyoK/7HHH4AknrMKP7t2B0ekQ379jG7aPTOOiM47Av15ylrXA9jmimOFff3AvHnfcSrzgnLXVDfoM37h1C45dOYhNeyfw9m/I1oOPv+rReOE59QurWMwN6IA3eUGz4PKDcJ5h1CCZbpmdljwL/GaSF8MijUU0U6tl6jzS1g1yxBmt9KrNkpMqveqtqdRCo1UFSlVi89VphY23qGCFkn8n9pker2QB7ubbhrJ9uLDIBiUolbw/lVxY6AgjWXG23BmvlQcnK+zqZcmpirOucQEHRa3mTNYi3WSFXY3jjWMMO6RtDZIxt8+Y7F1RCE7YxWIs2S+Qq4uaVVelRBGQ9GFylde8GrnoM5L8NpVs4v2OmZ0VAJb4IdABYq+RWJrqKOxyVV5bhio/1VJLz0H9ohOSQs5AoacuZATUUrsAFHZ+PA0HMRh4Ub+amVzquU2fNYcPN9EKXEynz+ehhoelrUA812OWPON5kYbs8wwz7FrLEtV8ZzxR3Q2tLsiw0xB25Jk3Gwo7qrb3SQHDMGbiOStAFyABYEnqYhpPCwId/ijggR/Ai6aRVH1N2ustsfK+BrboRCX4M6/VkyWWEnae/LuZQFoolcdspe/nIAq7OGbieAbTDDtjpRsn/maQYUfJz9y9XQMLh7CbTgm7VoDBhoclTvJlMNeHwzshjc+ZZ9/Rz1jIoIM62cKj3FzqhW1aZnk6lVb3OWFXF485LikVftum/RXvzGOyE+JzNz4MAHjumWtmdb+OXTWIN6T23r9+9qmz+tkWc4ur79qOz9+4EZ+/cSNecM4L5nt3auGm9XtERiLFFX/8eDzt1MPmYY8sypBVINVZYmXSDKCh5R5RjSnkl+MlAyyvkQxKuOJMY4ntFBJnnISSba10MUlSyfHsPIloVLdLiDO+z/T5pbHEym01FWZLiELVvpV8XoEqULGDySRjSWafJiyeFrtYDOhGMZYSEmo5xoU90KTtTNRqw6o6z7gIQ5zLsDNVunW0+2xeOEJW2I3XOF6Z7FviTAOx2Vg6jNVzNQUPUV8qT3yXEEWGyjJh7Ur7ngGPwXXS76SgorYK2ocFnlIl1qA9VRYBwGBadCJ2m9nnVHxGO8w+Q7K0SqRhSZYfLRrhuWhC0w+VqQSlKq9JpVux/ZpFJ/KW2OrjnzcQxXkTXUwjOdbaVWKVc+uk31UrcLF22QAe3pPcg2uWJeQlXbTpRjE8V3HVSAo7TZVYnmHXXJr864xnJJ5E2KXXDouT5zHZDu33AkdV2NUn7CS1PSHowoghZxpSLbFLlAiWI84EADhgaKEjvhe9wk4l7DKy1WbY6SEWKXxKrBqeK0HYeblx2YxA40RMlHs5V2F2HdCYkkxhZ2qJnXmGXRTNDmF38EeKtJM2VX0BGJ1KLbEDARzHwepG8nMcDCUhlUCukghjTFLYjS0Cwo4ytXRSlFtpyEmy6yrshnvdxb7EWUclBOTWA1MYb9frTH7xwG6MTYc4esUALjnvqLnYPYsFiM2kWIhxCfQ+wKa9E3jVZ36d+/21b3mqJev6FFkGDCfONBZPPghHQS4bJ09oFhz9v8QSmxWsUC2x+uIP1BKrJ/tI23SArd0u32c6AHTz29XZWmOW3peUKHTzZB9/phZXmCUFPnKVbfM23uKquEXFLvrLitgrukqW3Apn3HiClOTQ9WhNDUMsRTZQHsaU8WQjUcll2x102iJvqrptrNlnMyWOShQ2nRBebKY46irbBYCBaMIoh05VIwKJyq4fJ7J5K2W1HbVLyHcgI8sAmCvsaIYdrTJLyX4WF05KxQJAajEecpP3RW4j2w+gQmGXWVolhZspcUn6NDkLsJVbdNBBRCrkLK2BUXspU9RXCD9N5mrfgBB2tFjBTItOuOkzt+V7UiyTjrDT3otShp2isIu62bnkhB2QEXY6SyyQu37KFXb1ydWQLPxJhJ2ub1bHJEPKODQl7ABggLjrTKrEWoVdBUa24gOj78AL3ZuT7yoda5rydcKm6nhzaImVF4a1KMntp2rBgZQt7kSxWXYrV9jRAm0q+N+itvbE0Yq7nmoHr4GZE3ZjO5NAaFNIhF1vCjsAWBkkbWOfnERFYTfRiaRB39j0LFxE8wy6cixbYtUy3Mqxmt5AC8QSWxfLBgKsHEoeVhv3mGcnAsC19ySy7N87a82M2HGLxQWqpjgwtTAWA667byee9sGf535/0aMOx2lrlh78HbIwgpeSX2KlTlLYEeu8xl5aaGsVynTZXsoH1A3PyWfJCfLKTxbKVJUc367OEltkp1W2GxB7qV4V6OYsElkenDw56MaxvF0dcRaSyaUgCosssfJkWy52UWGJVfeZTKoXA7qhqrAzLzrBum20nOx7qmMRdaJ2pqIC0HS6iEKz8U43ijAAeRzqxWZqkkStlh2v78QIlFD04u2yHHE2EI0VvFtpq6jkgFTdZ7BoFCpZgbytsdrgIML3SHabJi9TB1qdFAAGPbrAYFZwoavc01IGXgnhoe4D7zsHUtIw4uohE0sqUQo2fC8jDTX9pvYYSD6mRDpKRSfMFXYNXQYdWSAqas+fP1IGntS+zwgUrjgHpH6hviVWUdix5PhbgYezjszEECcflmTaUYuots8sy7CjFWEbSzLCjrulpKIT5PpV7gFKZuUz7HpQ2JEFKckSq+traDEqAFh1UvY31wdWHC/uGxqHpSXgrCW2Hu64CmdH9+LjjY+hGY6JOW59hZ1PxjhzZYk1yLBz0muN9G/02dgMatp+ucLON8iwA7SFJ/i5dJ0krqtXzGykeN17gf84Fbjrf83b0MFzDxl2S1vJDb0iSFe4PeIrVhR2+yfkzx9dIJPqMnBpp+Mk0ko+KMityuTkoYurSmwvOH5V8qDbtNdsUA0kHfx19yX5dc87a3btsBYLGzQTs9/zMae7Eb5x6xa8/orfSr//2p9egBvf+Ux8/FWPmac9szBBrsoaJc6kSaSs/OITLkCjdBMKO30BB7oynm/byLZPtisRhaolViXO/AKyj25XFNmoUAXS3D2X2ouYRtlXTJyJ7Dw6kDPO3cu+I7Fyqy06kScZFwPUHLohp21MugWR/EwewrRx2yTXSIaj+Z0WCtmXfJ7e1qKiE8ZyljKAIDZrG8YxBh2lmqHhPodRjCFlu4NoG9lxu4qdFuAZeP03kfVdp6A6qXmG3aCb2lGRVmhV7sGqz/CJuoxRdRlQSLh1FJVfKyXLYq6wq2lJbfhqhpy5JZYrjoUlVio6UZbjV7R9onYp2Qe6faoQjKlKGTCP6jmYSFV2Aw5Vcs3MEssVds3AxWOPXyl+z6N6HIcucGnuY5rxplaJ5YQd/26bw/LvJYUdXdyTzz2dQ+YVdvW/pw5RzHuuI4xwXR0RpI5JDs8UdVh9anLfpd+LKESDAjWiWnTCCcE5kn60/s87uJ0awND4pnxechXmLMNOZ4ktuQ753xpL5faQLakDgd4GXgihsCuzxBIeqpvvV/m5nKngp/eR4vY7gF9+KHl9+1fM2/VoiZ3oJBfAkpSwW+6nq/KSwk4eTE92ZDa27xR2YzuByX21mggLTjopyVUA5MjJQxdX0YlecEJaoWn9rvGKd2a46aE9GGuHOGxpE48+ZsVc7ZrFAsSO0axj7mfC7if37sTp77oml1n3iscdgyecuApHLR+wlYj7HBkZpFHJuflBeKnyS82LUSaAnTJLbBQqbQusqb4rnlGZnZasgBIlQ5YHl21XKPtihewTRKFC2MW8+IOalxMrNt58BpRcYbbEEus1cvlLocaKS49FXxV3cVpioygU2cJAYl0ytVr6CknWQtu4Sh0n7GJyH3iGdjv6vjhVHpkSdmHM0FKIM7W6ZBG6USxZuwCgwaYNba1MIhOA5HyZnOtuzHLbHaxBrB5M5IgiA4UdJYoAYIATdoIsqw4vz2fYpWSTE8hkVQHhRskuAGil+xA6XGFXbikNo1gUluMZdj4t2mCgsOP3TsNTqryqRScKrjfan0rnQF0gKjiPXWXBiO9/TFU4Fccwb0gVbFRhV1uZpXy3HrfEBh6eespqXPr4Y3HmkcN4+mmHZ5vVKbTF5xFSRFXY0fw6+n97VH5fMJgoPVz9fcSPkRLljBMRPRSdUO/FUiIoVsYkK0/I/rb2vHT/E6KSLpJoFymUvj9AhCVpoQGrsNNgYrd42eruFwow4yqxLO2baIZdmRLOFHSx061epBB/44S2RmHnOHJOn5Y8ViEUdiVFJ1w3Uy53J3N/ni3CrveiE4ednjDfex7MmP4qMGW1u0YnwMm3oUayy8vcdHLhkpPIT1jcBeIYkx2ZoOurohOT+4APPwpYcRzw5tuyHL4KZEHVyfv5xCZKq6CIC0JluA9xSywAnHHkML55G3DPthHjNtfesxMA8JwzjpiRlNVi8YEqePdO9B9hF0YxfnTvTvwtqQD73DOPwH+/+rHW2r3A4KmDKKr6ct3CSq++62psrUXkl2JNlQo4aKrT0s+IVfJLZ4lV1HlqpVdCMuYKOAiS0Zfb8kqvwgqXZbAk7RkgJl5OOqhUc+gyGx0/V4xW65MssUUKu6wt/33Dd+VVYlGgI21LJsWLAUFXHgcOoI1O12zgrqrkGk6EqGs2mecEW+wPgkVteNG0Mekm2roB4sZSuFNtBIbj0jjsoJFmczHXhxOHxgq7bsQEIcAcDw6L0EIH3Yih4Zf3zd0oFvlavO2A0zFSyYUaovBzrz4TrXQxs5/guw7imkSVWvBhwOP5cUEy2amlTnMkdVjk+kn+kNdM7usiSyzPf0snhk2qLgMqFXaUeM1XaTUjLjuKJVaqtktJxzjK+iUCERPgpxl2Tka4uSUqLXX7vOgEJwxDx4evUYT3FVJCszkTS6yqsEtJjZbvwXEcXP6Ss3NNkmdtpCfeY/L8Ewo7xRLbTO9hVWFHCTsguYbibp6wS7c71PQRtKPsM8Op5L2MGc9TATlaA0iec90oKrfEijGJB7zuh8ADPwQe/yfp/idz/UG04bkOopjpyU0+13VcgMUIEGJJ08fodNiXWZ3zjvFd4mWjfQC+m1xf5go7Ttj5s5thR8eLQrlXch/ybfL7gyrsxFhLcWCYELhdA4UdkFyfUVurXBaE3Qzy64CZKOz8JvAHn0te711n1kb9EmusrkymHQiv8DHsJ19GmxJ2Pn0QdDDV7WOF3YafJROsfRtqqew6yqoFZYs7utydop+LsIgJuzPT7Ih7to0avT+KGX58b5JfZ+2wFipoQZvRfupbAHzmlxtw8j/8EG+68jaMtUM0fRcffcV5+Nilj7Fk3QIEH2QwXkhBDGY4gaUQZyFROPhFtlZVJafYS32N4ixWyD6lSiy14gp7aRFRKDJn8wUcfDdryxirtMSGZEBG7UUhzbAT2y1QBbquZE/NE42aQhlEFahWwpOPWVMVl0yKFwOCWCbsfCcGMxzj+WnBhbCV2cVcQ4tokL6PBQNCEeIbFnAQ6jy/Vbst3b94YFWyL4ZtozDEALd2DSZtB5y2UW5QGDGhMnF4W0NFIiUK+fU4iE5fLkYGOaKKWGILlGEdkkcJAAMuJ4r0974OcpyAI0jZyFH7y3KFHR+jN93k55DrIyoUdl1SWTmxpDpZpUvXzNYrF9JRCDuDHD41T1SQlg6fPDul+6BmqHKFXYTUNsdzpvqRsOMKO2qJrVslVjwzku/aZ1mV2MLNlirsyHMkl2FXpLDTWGKBXBQFB9/uUMMTBCvjFWk1768CV+oLhZ1a6Z5CPN8JeXzcE4HnvBdYfqy0/wNOW9gatZ/F9zPd9wAhBq3CrhiUsOvsz/KSe7LEziZhRxc7q5XR4p4TCjuixEz7M8914LpOPmKmDKGBwg7ICtZoFHbhvFtiAWDZMcn/U/u1vt0ceq1cCgi13AAn7FwNYefJ+RLTCmGnWmTnFdtuz16PbjFuRtUPyf8FhJ16YZtmRSxiwu6MlLDbemAql2+ow62b9mPPeAfDLR8XnLhqrnfPYoFhhGRi9kM+5shkF+t3jYExhn/9wX3i9xc96gj8+u+fhRc/+iiJ4LdYOPCKCink1Grd7D1I1WpF1tQC8ktYYl2af6cSUApRmD7bOxplX7FKTt+WVlwF0sFOLjtP3mfVciCOOaRt+fHKg0pdgQ7tfks5WprcPTIYy5OjzdxEW32WL3Rw8isiMSWuYREGbomNm8Ng6WTeWCWXFolg/gBiTrrVJfv8ATHgNm3rp9k2zPHAmsl4KYjNbK0OJWsGE5JyIFXYVSGMIgxyMmFotWhrMhntRjFavO3g6vSX5pm+BxOSlTNXXKfciikssY5iRzVQ2NF+yCP2wNDhhFs5Ydcm+XMARMGHyFH6vYIgf6oC8hXCTGet10EunOGgkRbvYF4TJhlyatVtcQ6g77tzx0Aq5TqOgyavlGtIes4rUiVNCx0sTYme2hl2Ik8rIQ88ZEUnCjfLF8dCHaFFoigaKmGXChAaBpZYoPDc82tmoOFlFmgaOVUzbzCrVC9bYrVKYDWmQ4eUgBtAW/AAeoUdP/fJvgcIMcQJO6uwy4MIhoL2/lnKsJuF+ZDOEltGBApL7BL5Z1CFnUwe656ZjDH5Gc4/h+aX6iAIu/y4JY6zhd2ZYGatW8uyEzm5p/r9OcKuhsJOscQuSQcd0yAyRakCTke0GU5z71TF3bxicm/2eqQGYRfJFx4d7EudUS8Ku7CTBSwuQsJuuBXg2JVJJ37v9mqVHa8Oe9Gjjlg0lfwsZgeMMRyYzO6pflDvvuJ/bsZFH74eJ/zd1eJ3K4ca+PRrHovlg42Slhb9DkoGRTErIewU1ZiUQ1dka622xBZWmFWz5OhE0VdCtIsssSHPg8tsXDm1mlpFLldhNlPY8e0DKXFJA7ulfVbsw7qCFdIxU5VcW2obeMnENEdSSkUnCr6jRWKJddOV6KixVNj/jIkzTroFg4jSQmKmOXRcEcf8AbB0UmqssOPb9Vpg6YC7wUzVedyKOyAmhy10jCY6Lq0kJwg7wyw5iexLFhJbjpnCLozjTGE3lC5C9ith57oInKKCD0VEUTLG56rVppofZ5CFREl4x3HQdIi6DEBVpVm1Smym0FP7Lv0+0P7XcRz4TqJWFW1NSEdS+MInCrvQVTNP9eMW2id6bkacZsdQrnhRrclN9RwU5Kj1BdLvJ0CEwWYJMVQGfl55f8RMCLuCAoKAvFDGVW/dyaTKrpph11KLTqTKZ648KiDsMmWpJ74v3idK+2AI+mwEMrKiXGFXQtil938LnUxhV2Kv5fseIMJg+v7YlIQ6lECiLLzpffn4lSoIwm6WM+wkS6zs5NDvh5JhF1GFnbygG5Rci5+94WGc9q5rcNeWEflzyq5NIFPgaQg7vh133iyxQOJnT1f4MGFC2PVm0+yEsThgzqxzwm4K5CHuuuRB0MZUStitHEo6KFVxN6/gSjYAGNlq3EwtW+84jljJkzr6nP3Y4Fy3CYnFcxAWGc46Kjmuu7eW59gxxnDN3Qlh95wzrR3WQsZYO5Q6+/nOxxxvh7h/x1ju9794+9PhzPAhYTH/oDlnkuIsR2DJdkvfc0UmViHpVlIlVlhLVcVYrmCFXISh4bsGyj496dbw5AIOnSjWtJWrhkXE8sD3XexPbp8VpVuUbdd1nWzAqsveU/KnVEWPsP2oJKWfrxJLVSiLAQEhzmIvWUj1IjMySBBswSBin7c1U9hxlRyCQTFJM1bJxZmd1kkn10HcNlLJ8QITsZ+1NbWm+ilRGLsNOKkypuV0jCq9elqyzyzDrhuSDLtBTtiZneeDjcCj6jZClgMldtTsXgY0RFFNdRqQVXnNkVVF+8CtgIrCLlOnlZNdodKn8PZJW9/oGKgllmbYRU6QZp66NfeBE5+efAyGSkfevpsj/OZ/oTOH9Pw20BUCEaNqkhT8vHLSyOGEXZklVlPwSP08qrADEoGFsMTyDDvFEptT2Om/O5rzJbIfPULY1SRhQuVezBR2JTZWmq+oIiXsAicU0VjaCIH0XPGIg8AJxXk3JqEOJXSyZ7TXHRPjn8ikIAOgZNjN4n0tjZ0MrLacJOf3AcmRjHILusX283/9wX3ohDH+87p18n54vSvs1O33ipkv7Q7OhLAzW12hxSP4jTqQViObgOIr9rPVL66oW9GPhB0lx6YPGDdTq8QCQJOvzJRl2JlIVDmJ2FiaSVsXGc48MlEOVuXY3bNtFFsPTKEVuHjaqYcdjF2zWEA4MCHfT/NliZ1oh3j3d+/BH3/hFvG7p5yS9MkXPeoILG1VrApZLAjQB31CQlVYYkkF0rzCTrGf5NqWqfMKSLd0IGVkieVtlSwnGpQeSAq7WKPO45PWMDsnyFseupHOPiyv1naImiT5DJL5F0dZFbSSSq/8POVUEmJ1tpFTlfDJxmIpOiFIN7+FOJ0cNgyJswZLz1MwAJbasExJN6GICwbEKnfTUGEXEKKQT2gHDUm3RlpggvktMVgfQMfIduVTdZ5oa6awE23dhrDBDZpW5I3a8Jz02PqesMuKFUQIlOyz8oINvP/I5ccZZCGJ/M8cWaVm0BXtQ6S0j+X2FYRf1oemheVA5i09WmJ9QXyaZfnlsrL5OYCZUlGoDH25fQRO+PWxJTb9fptOVyjsTLIlJXBiQai8UsLOr1bY5foAxmSVOM3S6kySohMFGXacsONEn6IS56CqylZ638Res5LcLYJ6DflU9a5CHRvoIIjUUCgVyzLsuNo6QCiEPsY2z0MFcZy56gC43UliiTX9DJ3CbhYIO65g9ppmn6tm2FGFXaQq7PSW2O0j2blY0vSS8SXj6uaKuRQn7MJiwm7+qsRycFn9HFpiubWVrrwPseSkjDOlcgd5GE51kht8ZWoH60ZJVZm+sDdOE8KIS5oNECqTCyBdyWsrHb3auZoo7DhxuAjtsBxniMIT5Qo7bod9+qmHi87ewoJjrC3fT/Nhid2yfxJP/sDPpN/5roMvvf4JYIxZZd0igus6cJxk7B7GVHGmr/TajXWkW0HRiQKLKLXECjKgMP9OtrVSS2y+wizfZ06cpZNJss+OkwQDhzFLyELVEqvsc2GGXRQDXKFSUKAjpybxXLTDON0uuc9dn+RXtXPHSz+jK8i+Yitbl6gRFwN8Ymtl6WDbxJoaxwzNlLBzGkOIauTQMcYQCLJvMKmWDPPiD0E8DXgAggE4jZQ4c9oII4YS91qyf0JROAiXBKIbqeREsYsBMcEYNCTsaFs3nSS0TLdLbcacsOOWuT5DMsZNcyYdPwm/8ZrJhKjAjqoS6Jm6zUwZRj/Dp5/BgC6URYqCfcj6k7RPACe71L5LP2ZQ+yNeoVW0NTkGYon13KzKa5e5ZB+mK225fJ6RIy2VPjS3ffV7EBl4+udGX4FaYlOFncm9JUHkafHCBxH8NPC+CPw5kOsDKEnh+olC0h9I7oPuBNBJiTme3cXdUVyA0VEUdgUqKKoCajkRwJKqwHCD5HnXoyU2WwgrKGZAi0qVZdhxIhXdYkss+azYH4SHlODzubX5ECPsdt0HLDs6I3FVKHEIbjhJLLGmCjtdht0sFp2QFjtNLLFcYSdXiT3T2YgPhJ8Hfvgs+O5zk7co1+Kesaw/Gpnqyv3TDDLs+qPoBAAMpeqjObTEcsKOr3YAQCsl7MZyhF22+jWpWGKBPlLZtYl9rcaAqSs61eyra5Qp7JwaN9AiLjjBcVaqsNuwZ0JSblIwxvD9O7cDAJ571hEHbd8sFg7UfmQ+LLFfu2Vz7ncvfvRRAGDJukWIgA54Cyu9pqQbmbDlrDaFVVNrWGINsvP4M6oTxYnFsEjZl7Pi8swbst9F1WmFJZZJbfjkp7xgRZ6gpJ8hKft4e9XWqk6uqSWWTuhp24LjXejI1GpZllwQV6u3unGMQSRtnWAgyx4yaBvGWdVTp5GRbgEzs7U2iMKO21pbpio5aqdtZIHoJtZUn1S2FQo7p2Nop9Wp8zpGEyyRu+cG2cS+XxV2jlNS7MCMKGqm6rauYX4ckFfpcYVb13gf5IDxQtLQlOxK28dwkgmxicJOXfxAeh7EPpQrVlQ7I9+HLuPnoDxTSu3bBGFYgzidNxBL7GBZcYMyaBR2VUIRsTimFp2g54ifN66WkxR26f1cZYkVpIo8hqVzy5ZLqvqaVOjUQM0x5MqtPCFJFaTVCjuqmCv7LF4ww0ckxgPGNs/FgE03A/99AXDly4rfoxJ23UliiZ1JldjZyLDjxR6oJbbkc/kCiFDYZf1jGMd4tfcTnMXWAb/+JIY9eezHMUbmcdtHpmUVKo1k0CGN8tAWnWCzY4mducJOWGJ3V7+3Z4Vd8kUMkiXPVpxcaKOxwnp62eoVn1QvHwyEOmGqG/WHTYxaYtvmCjsxESOr8rwzausIu2AwWYExOdeHAGF32NImDl/axK6xNu7dNorHHb8y955frtuDh/dMYKjh4dln2Pw6izzUitMT7YOvsLt+XbZI8q03PRFb9k/hQlvNeNHCcx0gUi2x1eSXUH3x50OlSq4HS2yUr7hKK71GMYOvts0VrFDJLxfT3Ti1tRYRlKlKLqewo5ODCgtwnN8ukE7cqQrGC6AGzquKd7ltEdmnFLtYJJbYRjwNuAnpFneT82NiTe1GlHQbFJNcE3VeGDGRyeYEA8K+NYB2cs2VkKFRzNDk2w1acLnCzpB0C9LjRSATZyZkX8A4YZcdbwtto0qvorItsfEOoJ2f6Gsg1HleS6jz+rXohIsYSO27grDzG0AbheNZ3oc01fw4ls4dahadEJ/BdKShXmHHSYGA90Uq4VdRcCGnTOIKPeah4ThyP8JYkiVeeAzyZ0SG5yFvyyVZgkAlacmvY9VWbEp6zisIMZRl2PVK2GW2zLK+CCjJsJMUdun5D4YA7E3u3VyGnVp0gltiUyKjwF4YEVUl/75iqpoqUIQWQYwjfG6JLVDYxRpCUgdiiR0QGXbFnxXzftUNMcEX0g4lS+zNH0/+f+Tm4vcoYiGnO9FD0QmeYXcwLLEl/UXOEitn2C11sufcYe4I7sOS3L1GhRd7Jzqkf3LK8xWBjBDXKewUS26vmB9LrNdMJbbFDxxM7gPu/Dpwzssx2UkOdrCZ7W4zJexGIoWwI18sn1QPNHwMBB4mOxGmO33CsPdqiVUGA0BG2EmDPVraujNmaInlhN3iLDjB8ZhjV+Cae3bg+3dux7pd47hx/R4cs3IQf/mMkzHU9PHxn60HALz8/GOwpDnzW8Ri8YH3LZ7rIIoZJtpzr9zthDG+ePNGxIzhzi0juGPzAQDAz972dJywegiPOXbFnO+DxfzBpwOpQqWbTiWXkm58AFZYJVbOdEtsrWomm0J+lajV6ASlGzH4KlGo2CdUAkuq5FVoiVUUdnySLBGNRQRlvkCHtN2IWHUcL1W36I9XqAik7DxFOZDb7uKxxMYxQ8DS6yoYAIKEGPLi6oXCMIrRSouIucGAGPgakX1xLAL13aAFPgIKkBQFKomMQjeK0UjbOkELDgk1N8uwaxPCrp4lNoimAQfJqrwg3QwVdpywI9l5g07bSGEn8u8I2devCjs64eoYkmW0OiqQ2VG7aoZdWcEGxarOVX5dShoCUqg5RVcsHsh20Ly6rEDdpiwg8AqjXfho0PZgyWTZy49RVVutnxIwHcMMuVBRCQbqMVSQjjnlcU3Scl7hZ8TQYBExVAUqmEBCWDYqJuuFGXaxsmgEEIXdhEGG3YS0L0UVN4Uy1HUQpMrUyOm9kEAuw66o6IQUO1FtiW041BJbfK4iLzv3hXbcxYw966rfo/T9TncCfiNV2Jnah6WiEwbVXE1Bi070ZImlCjuGlchcjaswCmBJziI9SqKNJtohIQ0bep6KIkgVdprq9n2UYdeDJbYxBEy1s9/5Gqnhrz4BXP/vwE0fw+TzfwogKzgBAI2ogLAjg2JedGIg8DLCLuwDS2zYkQccdSyx4kFKMux0Hb14YKSrqCad7dSB5P/WcuP9WYh4wTlrcc09O/CFmzZKv//Ezx8SrwPPwZ8+9cSDvGcWCwW8AvWqoQZ2jbUL7dWzhTCK8earbsO19+yUfv+ic4/ECauH5nTbFv0B3udHMS2kUGCJ1arkKiyxSqabr7PT5qypekusr6n0OlBEMsa8cISaB0eCgQvbcoVd0pYPiBrU1uoUFcqQ2zaU7crKviL7sEwUNijZR6vTOk7+XImiEwvfEtuNs+qjTmMQaCfjMxPCrhNlpBslzlyDtt0wRiP9fl2/IWywDYToRrEIJ9chjBmaKRHh+E1JwVGldGOMwWfdrC2Z5Bvl0LFORtiRbCYTZZ84L35T2HAa6BoRhSJn0MvIvn5V2FEyx9yOqreT5tqXKDVUoiFH2JHYHe1uK2N0oZCrbYlN+xRXtZMq1XI1hF1WSMeV9qHL0r6mwhKrLkQEaaZZlyv0qtorTqAc4dfXllhCDM2SJRYAml75Z2ijjQBF5ZOeP0G2T2aCD5FhlxJ2UTtR3/F9EUUnyjPsPNcVFubY8Sqv1yJkC3CaiAvt8ZF908HLE6m5TDryWbzaeMuJxLjgkMqwoy6+Iih9v9OdhNdKx5kGkRIA5jDDjoy9TKpKC0tseh8QjiWKGVY62flY7YwCODL3vKXFAyc7EeKwk+TGVeXXAVkxGM3zlJ/L+SfsDKvExjHDx358D/4KQBQMwZval/wh6ugJu/U/Tv4f3YLuePJeStj5YUJy7Q+Vtm7WufBJ9WDDEwO3qU4fEHZdhaCrobBTByRAkcKOPzC4PLRG0YmB5cb7sxDxvLPW4PQ1S3H/jjEctXwATz11Na67bxd2jWU3+DueezrWLhso+RSLQxlcYbd6STMl7Ga3XxmZTBYcrvrNI+hEMR7ZOymRdQ3fxV896xT8mSWVDxl4opBCSR6cRmEnqrWGCmGXa5tXjfHcPMaSQY8nBlHqBFgm3RqE7BO/F9vVq+RUSyxfFQ9jonQrUMllCjvZftONGOAUFbuQc+hUZZ90nqusx77aNpYr+9Hta0jVhY6Q2FrdxiCcdEzHSa2qtg1CnHHCzqhtzIR6x/GbcJESdk63cnIWRpTsa8rEWYUSoxuxTJ3nN7NJPqq3C6REpqu0dbpGdlrelk5kGgiN2rrpJIb5jSxzp6B4wryDjFlDlayqKjrhy9lpHWZOFOUIs/R7NlX5qUR8kJKGHabv9/LbV/qy9D7owk+KSamEHQYrjyGz1dbcB1E4Iz2G3Dkot/U2FNJTnAMD4nTeoLNe1iV6FEssAAxWEHZ+kW1TffYBme2vM5ERM2qGHQCMkwXeigw7qWBUqrCLHaqaqkfCqEWV/KJstFhDSOpAM+xEldgyhR1XTEdk233isDsYoBbOIidjKhYaYwNY6kwBnYn6akRK2Inx0SzMhyRLrAERKBR26b2hKOxWOURhxw4A0GXYyZ8/NTWJIaCcSOYIip+n0Swtzs6Cwi4l7Cossb/ZuA+/fWgn0AAmWBPCdFkkiSbsrnNgCwCIij0A4IcJi7mvqxB2Xta5UIVdK0guwql+KDqhfqE1FHaq1B0AmmolP4Ao7NKLyOTBOLU/+X9gcVvrAs/FV//0AjyybxJnHbkMrutg73gb7//h/fjGbVvwkZefJ8L7LSx04Iq61UubwPYkPzKMYkEUAMDP7t+FL/1qE171+GNx0RnmxUtGprp4+od+hv2T8j3ruQ4+/PJzMd2NcOGJq3HsqvxA3WLxQhrwFhZSyGfYZSvbBZbYora+I2WldqMYXk6dJ5N9HTLRy1d6LWirkF9q4YiuAdlXlGGXDOgVO62af6eQbj4l3XLnSib71AU0vu8dXiWW7qtihVO3u5DRjWK0UmLUDQZqkW6JNZWTm02J7ItjVlpZsRNmtlYQwi5AWKlW65DtOn6DkG7VbcM4lgk7orCrsqbK6ryGorCrniS5qUUShGRsoItJk7Zcnedl+9yXtkQg61OYhy4/pZVEkVIsoVDZVVKwQfmMQktsAdmVFcBR1G2G6jJVacwtsR34CVFMFXWaz4hiJqZPDWUfOrxKbIVqSkTviPYKYVdJ+KWEnc8JQ160wvx7mDdQS2yQZtj1bInNFv1bXvlnFBIl6rMPkBV2aoad6yVCje4EMLo1+Z2X9RVFeWAhuW6Fwg5e4furkHs28gXHouOrIkVoldiUSC0+VwGiNG+x5YTFZOhiBiU/u5MZkUWRqsH2smEsdabgRJ2sInRtwm6WM+yoJZYXzyxaaGFkTCwy7IjCLoqwglhilyMhuTvKM1Ml7Kbb0ylhV0dhV5xhVzaWMcFBs8Ru2T8lHnyTrIFhOABY8Rdw4JFsJ8ceAbBGUth5qUptj0rYEYUdn1QPNDxxg/eHwk75Quso7DRMLV9NlNhilh4nv4hMVkcOEUssACwfbGD5YHbtrFrSxAdfdi4++LJz53GvLBYKeEGb1aQC9WQ3wnA6OJnqRHjDF3+LKGa4d9tojrCLY4Yb1u/BcasGcdwq+UH6qw17c2Rd4Dn42KWPxvPOWjsXh2OxACANOnOKs2pLLK/W6lRWic0UHlQl14litGoo+/j/YRwVkF/ySn9pVbnCfU4+U9jQuKpFsgFXVbaVc2EbpZZYxcYr8qbk7UqFQVxFHVSw3YWMbsTQEgUcBsSx+qybXHMl+S9UrQa/Ici+BrpJRl2J6iKMSVuvKRZ6TRRnYcTEmDRRunG1WrXSrUtUgS610zrdSvscbUttrYmyz1Bh5yFRWnEViQFRmLTtJlZcL9uuLnOnL5BOuDoIMiKzgmTM5WZBVdhVk21RnPWdyWcUqMsKVH6h0hf5OXVZlSVWn/8WMi8ht30/2Yeooz0P9PrzPRdgrJiwKyLcQpk0DFjBMVQUnVBtxZ2FZIlFFwMN3p/XtcTy/qwlftV0yz/DczXzOIAQIlRhp6sSS5R1reGUsNuW/1sBqUKv2wA8w87LPfNMUWSJzanc1JiNIog+NlPY5dTMZFwUpZWhfYcJd8IhlWEH8sxtj5cTdhjG8UjUmINpnqyxGlGXYTfbllh+LEWfSxV9QmFHCLvOlCChAYiq9Op9TavEAonCLtkHA4UdJ8Q1z4U+qhKbFp3ojAPd6UzRpWDfRFs8eCYjN/li425GLFGEHYBbZgE0xrdAIuzCDpx0pXBPVzmRUoZd8mUMBB6aafpwuy8y7JQBUo0qsTqFnU+tUhxCkp1+H0ZVYg8k/y9yS6yFxUzBLbDDA4FQEU22IwynFajv3T4qBge7x9u5SesHf/QAPvHzh7BmuIVf/u0zpPv567dslrb1jy94FC44cRXOOmrxVm+2qEYW2qzLsCuqEqup1lpRJVZniU22yzSkm6J0U61QnoOpboFFNNdWCTqn1tTcPssDQ1VhF1BVYS7DTsm/K6hml6gCy/dZnZg2KFFYYYlVg9n7Ebds3IfxdojHHLMCywaLB61dJYfOJaRbGDOJ+NW15Vlj8Jpw0zFL4IQII4ayuk9hFKPp0POcVgk1UKuFkUL20aITFW271E4b1LPEUnWeS6ypDXQxUVHpNYqZXtnnVOfuAYArsvMaZILRr4RdZgXlC9WVCrsCoqgdK8USWJRM8hQyWCa7FIWbaucssMSGpNombd81rNCqKo09ovAT12UJYUfJ5sBzpMmsabXcboFKMEe4FZCOat/m1SRO5xXpsQUIAUEM1SXsuGAiI6GabpXCrsAyKp71VGGXkhLdiXyGHZAQdGPbM4Vdk/ytiLAjhZs4uRHBr7xWipApTdXK7erxKQr4IgircpdYldU8vOyzovRa9Ykl9pBS2FHiqDMOQOPySW2j42wAIXPhOzEGwQk7w+3MRYZdTMdPTfDnOlikt/fS7XH1Kb1eFZEUP0b1vp5WnqHt6fTZaJJhx9W0oUZhN0tFJ2Y+Umwty27oElvs3olOprDjhB2g/2LbY9KPwVTyucISSxRpB6KWPFAhnztFFHYi0LMfQifVAVKNDBE1myJ5rSk6IR4Y3BJbQ2G3yC2xFhYzxSTJx+QLCROk8MSW/VnwaBQzjLVD0jbE5298GACwY3QaH/7xg+Jvz//PX+K6+3cBAE5fsxR///zT8YannGjJOgvxsK9TJbbhO0KBnfxeQ7rlFHaZJdZ1HXnlXwyi9Eq3XPaRRH6VF47oKM82/r82/07Z59zkQKd0KyLdFCVAadEJxR6kVraVLbGqjVe20y4ES+zb/vcOvO7zt2D97rHS98mkWwNOwHPZqskvmTgLCNlXXcChE8ViXAmqknOqFWfUEgu/IWVXVbVN9jnLzstsdJEB2UfVeS3RtulUK+yofVi28Vbn7gEQZD3Nziuqdjrv4H0K/Cx/07joRNoP5KqjEtJZ8xldieySFXZtQ7JJVdh5gvBTCjYUtVfsqJ6oEusR4rKYRKHXX+C60tjf1BKbO4+phVsQnzWLf3DSss3UvrAPrz0/67taohppj5ZYN0hy4FCtsKvMsNMp7KZHsvkkVdHx16UKO32Gne854r6J4PVMwuRiKugzmUKX0aeDn2XYNXlcRuG58hGDF0yJs7FTXeJ1IYPyDEWxW+l7OgjQTmpQo+XwMZWpwi69Lhyv8NqqDboY4jdkMld3HTKNwo5+hlIIopUq7FTyWHVgTk+n5FuV+hPISL3u3FWJnflI0XGyHLuJ3YVv2zfeEas005GXG7xKaI9IPwbtJFtNKOxSQm+aBYjgyao5XZXYhqcvzDBf4F8oXyWpscLZVVQIgDKx4RCEXVP+uQw8w+4QsMRaWMwEtKDNUCoBoZ39lv3yKsseUtDkVxv2Yrqb3auf/eXDGJnsYmSqi3u3J9kKF5y4Ete85an406eeNGfHYLGwwCc/SYadmSU2sbXK1VrLsuQYY7nQc3211rxajTEmJpRBTiVH2vKJh0pgKVY0ua2yz4J066Rtk+2qCruQVtR19QSlqloXttZYZ4mVA7j5PvOsJskSK6wiC9cS6wnVR/n7JFsrIewChBnJUACZOMuKTjRN1GrUXqpYRDsVarUwzlRyVGHXQLeybUKckWtSUtgZkG4OseJSS2ylOi+z8boBIfsMcvcYY/B4dp5Hi070q8IuVaLCz0iMCjtqRyxUpERROrnrqEQToCWr6PWWkU0pWcXJphLrE0DUaa5M+OXUZYaWWIcqDSOVuCy2xHpusuBCt9M2sMTSDLzATSy1nmrrrSDc+D5wYoWfw9z30JcKu3zRiao+LAdCHLE0f6tZkWFXaNtUVd5ApiIaI0UlSgm74exvBXPvkFy3vs4SW+O7isk1JO6DosIP6rigCCRjlDvm8gq7bFwUOlxhF1uFXVHsVnru2/AxLQg7PqbqoehEj3mHOdB99xTCTncd6hR2cZgo9YCcwq5VoLBTHZiddvpsNLLEcoVdGWE3M8ptdpZ2RaXYvYVv2TfREaz9dEyqweiIpGm5HHGzqxB26cU3gWTA0ZYUdrRKbGaJ7SvCjn+h3HrKIrOMOeQDaZPXGvUgv4DrKOyEJdYq7CwsyjCdduytgCjs2nqFHQDsJoTdzQ8l/eSljz8Wp69Zik4U413fuRvnvudH4j3vftGZc7bvFgsTXmmmm141FviulJuhJc6IJZYO0oSt1dURZ/kMO2miJ5RudJ9Vi2iWjRPrsqOorbXIxpu2jZXJgXgmhjrSrTp3DwC6Ic2hU8LWuSowlBV2WktsjihcOFVi5eIdxZAKR/iNRDmGhISKKkk3opLzmiTDrlphR+2lkJRu1Wq1MGJoSmSfucJOIuyUohOV+6xWmKVEYRXZF9JiF3Sfu5XukVxl2wriad7B7880uw2AgSVWvqfcHFlWrrALCdnluYmd1EvJi7y6TL8PkWKJ9Zii0DO1xPJ+my9KwJMtsQX70FHy5+jYv6tag6tUhr4LxJEo5pInHfXzCrVP5ZbYnEqxr6vEdrNqpL1WifV8sHSuW6mwK1KBqUptIFMRcctrY4l8bQvCbqv8M/2cnCU2u/YDSWFXrsbUISJFI1WFXaElllp+dSD9JC8iGbOEHBQgasQovdYCZMXgDpkMO8Zka2ahwi7p+9sI0EmLdPBoC+NzxdLr1a1wTtYB7ZdINfTks3WEHVXYkWJ8XGWnEnaMZ9jJxzitFCXtdjhhZ1J0ojhigtrNZ4LZGSkKhd2uwrccmOoKhd1U5ICVBVkqlthWN1HcCUtsmvk2iYTRlE4yVdilFrVBSWHXRxl2LWJzK8jDUKE+COlrqaNnqsKuorON44wotRl2Fhal4IPihu+KfmmSKOx2j8kD6R2jWSe+eV/y8Dh9zVK86RknAwC+e8c26f2nrxmGhQWFNOjMqdX0WXJBWq1VtnkWqfNk+yK30nLLZkiVfRoSSqdOadBBeqG9VFZh5e20ZURhRz85cMk+C7JPH/qu2r/EudIq7PTVafMko87GK4951KyqfoTrFOQqKaAFHOA1ZVtrFXEWMzS50s1vyKRbxUS5E7ICpVtdOy0hv0xsvDFV9gXZdp1qVaBKbvK2Jgq7bqyo82pXtk3bBqTohOHY86CDWGJ7Ljoh1HGcqPIAxy38DNWWT99jWjBBVSj7OUtsVZVYhcjn/RT8jNAts8QqfRIVA3RiR26vVRmSvth1pHMwHavHkD+HVKUdCNIyXeDgCr8zfx+46D3AsU/MtZ9vxFRhV1TcoAokS41bYhtVGXaFltgShR1X0KmuqOYy+e+UsPOKCLvsO+Nz9V6LTtDnhYiaKMro01l+dSBxB80gy56Uni+E/IuEwu4QzLCLw4xIA4qt57ywDwvQQRbNANQgqbWW2JkSdukzyWskLk7JEqvhcMT2HKnQCyckHYWwa6aEnbpAxl2ZYq2ky/fDQGEXVCvs3JLiWyaYHcJu+THJ//s3Fr5lqhOJTiBkrpAJ6wk7WWE3GHLCTlbYTTrJCWprMuwYtcQGNMOuB4Xdjrtl6fFMwS8eKlM2XOVU5faAkrnDUTfDrj0CEexoLbEWFqUQhJ3najPs9k8mD8ilqV12095MccfJuyOGW7j4nLV48smrpc8+6yhL1lnkIQ061cpqhDiLiOIsUBRncqZb3l7akSZrZZbYPIFFB845e6m2SmzWlg4OG7m2GqKQtNVODqT8OyV3T7HTqko3oQQI4/x5FmoDpbKtr5KMrLLohFoVtx+RVfarIM4KFWcGpBslsLymRJxVVnqN46z6m6SSM7XTFlhiq8i+ULHTku3WUueR7Zpk2OXVeVl12qrJaK6yLSe/+lZhRwg706ITCuHmxgpZJn1GsSU2I7uy7WT5a+WKIzWvyFUVdjXz46jS0ERhl1vU5wsEzEOHXyMlkUShuvAiWWr1eZwUUtELRaE3HaftTnse8OS3AEc/Ntd+vhE5WdEJUdygtiU2U1fH3BJb0c1XFp2QMuxShd1IWqBMFVlwgo7HVBll2GW2PUHY0Qw7QxcYIBNj/D4QDoGcJdYww44sTrT87H6OChV23JKeZdhVqb0XDRSCqtDOHGaxAx0k559Xe4+ZKWGnqxI7Q2EUfyZxZZvrQVSKLbPEur4ce8D7R4VEaxYq7JJrc9lAkG4q3Q+TohOcaynJsOsPhd2qU5L/b/go8NVXAxt+kXvLVDeTlofwRCemJZK40mvJGgDAYJQQdgMKYTfFCTuSB8Vv+jDsiEmLVHSiriV2/0bgU08BPn7+zC9CDn4xNoayC9wwR8TcElszw47n1wVDUmUjCwuLPGhWDs+wowq7/RPJg+LRxyX28of3ZJL0nSlht2ZZC47j4A1POQEAcOSyFl73pOPx8UsfM/cHYLHgkAUn6zLssklgztIE+owoyaGLOkrouqxW69JCCp4yeY26WTA8bSsVYVAJLKKwU1Ud5DO6Md1u3oqrmxxIdtqcBThTFAL5kHc+VpAUhbl9TifRiiVWUgWKQaRelaJWp+1HFOYqKQiVohOZ4iw0UudlZJ9MupnZWjVEoVGxCzk7T1armWfJ5S2xNdV5pEps1fhUUuflMvvMiUKande/GXY0u62aqALyJLirFksAcoR9WXs6OZyKiEoPKFwEV8fowhJrYEdN9kHJqdZm2FUfQ2aJTS1ucDWEX7HCznXS/pS8px3zDLxq0hNIz6NEevZvX8cRuVzJlVUj7dadN5LnFRenNNzyOZjnksUe6bM0llEeW8TPbU5ht1T5WZNhpxDGkaSw43N1v5Kg1iHSPpNnp+hEA100g+w6ks4XzbDjVWIRGUc7LBqoizBFhB1X2CFA28mU3kANNSJ387mzqbDTXBNlSk9K2DlO7jnhKpVbmzEvOiFfD9ytuXwwaR93lQXqMpQ8T8UizgzdFBWmcUOsTgm7qA3c//2E9f+z66W3SAo7eIjgJRvXEUncErvieGB8B5bGY3AQiwBTbomdTgm7aWpzTTuXsJs9JFozybDb8ttEWtoeATb8HDj5WfXa68AvnmAg+ZI748aDJrUKH30tF52gJZFRfQOJCrHLjfbDwuJQhmyJTQYGkyTDbl+qsHvssStw/YO7sSEl7KKYYVeaZ7dmOOngn37a4bj2LU/FcasGRVUyCwsVciGFItKtqyXdZCKpwBIbZ0SF7yZWWiALcJcJrLyyj+Z08LaySq7Yxsufa46TH+B3K4pd0FXzjOwjx+uqltgsMF0qsiEISkIy5my8Sv5drlCGpqKuaoktqE7bj+DDDBP11pIChZ1REQaqsPNJwYqK4g8dlcBKVQENhJg0sMQOOeR6rpV/V0ycmRWdoOeKWGJrqOSSc1Wzsq2jybBjqQq1KkPqYIMUnchl2BVUtuX3Mu+zcvlxQKmdNMt/kxV2XeZB6AJE+wLCLqew46ShWYXW3KI8rZaby/IrJsyECyfth0J4ecJPZ4mNVcKQngNO+JW0lxZuXKBDLLVR/49vonRa7CPOLLF1rZRRtlgTgxN2FZbYwqIMGoWdmjNepLDjGCIujgJShRYr4YVSQvRWdEIi7Bz5uZrr48S5qlLYZVViHaKw0857XR9hqkfyaJXYQ8USG6oKuwJLbMgJOx9d9JhhxzmcubDEUmWb6yfHoc2wU8dazeS93BKbno+uEyBgXTRYEWEnK+wY52VMCLugmLATz4S+sMQefb788+4HckRcorDLZLYRSlapuCV2xXHpTsYYxqSoDMMVdm038fHLCrvkC4tSws5zHQSemxF2dSWxI1uy1/sfNmpy9V3b8bVbHil+A5dM+q3awb+6DDsp6JojJqu/QHVnywtOWDushUUlOmQlfijNsJtIFXZRzDAyldxv5xyTZIlsO5A8MPaOtxHFDK4DrF6SPQROW7PUknUWpZDUTrkBSkGWnGJrlQop5GytHe3zJWsbF7eNM3WQL6m/SwpluHmFXeC6GVEoKd2KCjh0EUbZWMNTCLtSkjGWCRJBuvm06EQxUSiOCzpilH5HektsLquqD8En/XElkaQSWJRIMmlbkENXwyKqkm5mxR/0+1y1sNuJ4kzZR7frVGfJdZW8P4mwq1VkQ1Ej9pidl3xwH6rsQk4U0Qw7Pp4tyLBTCDc3zjLsGLd4lRQ8yOVK6siyCsWRel/nLLEldlIgvwggLK3w8tVyy1SCXOAQaQi7EpWfIAzd/DnIZ+gVbz9T6GVzPEFa9jEyZVYoxmRV92UOGktswyn/jOIMO43aSCXs1HmbSuANrspeF5AqtOgTd8NF6K2QAF88cB0klYpRICwB8s/YIqTXrI8IgefoSTiizIqIwo7fS4dM0Ymcwq6csGuzBroOf5bI45NKiKITs0jYhRplm1uyUCJsuWn/omSdcsJu3FsOAGjEKYFXUHSCE3axbj+KICyxU7k/xWQxeyaYvaITT3ijXNZWybOb6soZdiGXRuseerQoQyNZKVjhjBGFXaLA63jFCruom3wuH/T3rLCjJN3k/sq337VlBG+68jb87TfvwkZig5MQUsKuni1BN8iXJgkcouiEYYadVdhZWBiDKuy4bWIyzbAbmeqKaplnrk2sCLvH2miHkcivO2xpM1vBtrAwgE8tsTEZJAFahZ3nOmKwrLXE5qrEdvOh64Vt86qxsoJIHYmwyxd/yJ5rRDlOlW7qpEWEEDNE6QDOI8o+3lYu/qAo++IQXTJ24NvOiMIYOWuGmGynk2DleawtlKGSqnEIMKY9X/0GU2VCMelmQiQxBA4hkvws/LrKitaVCkc0JdKt2pqqElipgsOpJhkTtZq+cER1dl6cVaf1G2KM1nSqiUJpux6x8ToROmH5GK8oOy/54D7MsaMKu7iaKALyC9oO42QVtdWWkU2pQi9nR/U07QsIO14llmd3pX3XtIGdlB6DUMhpFXZ1LLGUsOPHUDyxFu19zTngiteSyXORQi9kLtrxzCasBwMZ0ROL7zBXjbQKpLJrJCyxFYRdZYadxhIrfl4u/7x0rfyzlrBTKmKKDDtH9KkheiNh1BxHAMWkWc2iEwGirIozlGeTpLDLvkcpTuRQgMonFFpiSYYdt8Sy5HdR3Qw7x+0p77BsvySirKTP0irsAPFcc6PkfEz6ywEAQVRliQ2k9kYxYYLLyT9L+TXq9gVhBwC/937g77YAq09NfublpJHcoJ0wJr54D13Iq0cSOEPpt4DBpGNaibHMt56qwaa8ZDKsy7CL0i+ct8mKTtTMoRvbkb2e2lf59uvuz4pT/G5zAcEnCLtsgGledCJvo5Eq03GoGXYgkzwdxtMKv0OHGe2HhcWhDFp0YqiZFp1oJ/ecKDjR8nHY0qYoQb9jZBo7RtL8uuGW+pEWFqWQi04UKey6RGWSV7qFpVViu9oFIV+nGstZYjO1WkND2EmWWFVhF2XFBSiJLarT6tqS1fgwzNT0+X0usdMC6JLoDFF0QrLEFisKxXsAUtmWWmJ5MQSFoAQKydF+g1c0iVTQlXLolCy5WvZSJUvOhCjUZOcFBhbRTknRiUp1Xqwnv8wswMp2yaSEVSzcyqRbIE8kCmyiHFGsKApdjxAv/UvYdeFn11/tohNl+W/FCjvVEivZcisIDBENkO4DJw2FHZT2IZpJcZElNtRm+ZlYYtNMKskSW6bQU9pzC7/OkqsRXPCIAqHQ030HfQxO9AROJD2PqtS+EsgzNhafV96XVWfYlSjsho+UfzYh7JRrJyJzS5o334slNozyhJ0oOqEeH6nsWop0v30nIewEmVpQdIKLgjySYWcVdvr3dRDkFHY5a3YR5iTDrsASCxRYYiP5PcqCBs+wm/ITzshLSUk6RuhGsei7hSVWHf+VQVSJncr165GGt+kFs7u06/nAwMrk9VRGVvFqrZ6TZdh1uTxcl2FHFWhpR7PcGc8ssakarO0n6ru2pLBLLbFhcqK5Kq9nhd30SPZ6cm/l2zfvy+SQd20Z1b9JsLb1FXa5KlZQVvU51CqxQPlNNJaW/1Y7fgsLixxo0YnB1BI7lVpiuR122UAAx3Fw5PKkI9+6f0oo7NYss4SdRT1kFTtJPhov3kSC1EPVUgXIKuycaqzcEtuQyL7iSq+VlthcZVuisIvz5FUgqeQKCEpkwcB0MBSIATo0xS4IYdfJnrsi/66MKFSsZHxyrVa2TcjNAoUdkHxPC8ASa6qwy1drJbZWI6umPv+uukpsEVFYXcChqOhE06DohJQlpyj7TM5VQ6OwAwCnYuE2UotdUFtrXE7YhTEj2XmN7DOA/rTEEqIoK5ZQHiETKuoubkftQldhtYSw88vy4yoUdgrhxUnDadUSCxQo3JR+Icoq3YY5wi1/HrgqVSjkdBl2JZbYrPBG2Tnwpb9R8L5ckDWSSnEhEHZZdVH6PKrqxyQQAiESVWJNFXZFGXbkumkMyYo0dd6m/kwJu4Lw/i6x7Xkkb76XohO8wqggfUGfycrx1VbYhYnCztEp7Pj17ZLvMSquULtYod7XRd9dRDLs0urIDVaz6ATNsCsrDFEHpZZYgww7JWrMTZ9vbS/hjDwWwUWMDsnI5eo6AFg+oCjs6HO2CJRcVPpF0W32FWEHZMz/ZKZG4xNZWiq6w+SHiQSe8RZkhN1KaolNFXZtv1hhx9IvnBN1PVeJlQi7aoXd5v2T4vWO0byXGYA8YRIXVvlgi0NfJVYj91Uz7IDyDpcrCZeuMdoPC4tDGV1iiR1KLbET3BI7mdxnXFZ9/KohAMCGPRPYmmbZWYWdRV1IK/CsYEWRVImlSjf+HJQVZ2qGXTc/YUVRhVnT/LsSi6hUYbaYZOzoyD4yeeGLc9JqPiU3c/ucDQJ5dEbgkUIZOjttjuxjiMJQVKLXWmLVQSSdkBScr36DVsWgQScsJt1M1HlNqvyi5FedSq8KURhXWHokAkvJv6vaZ4k4k/a52gKc2y4hkFmFikWuMCur85xaCrt0XFgzQ/mgghBFYc4SW0WWpeo2ThYxYqstrRKr9EMht3MSO2mlwk4mrJyYK+wc+RgKjqMoRy80JA359jPCLcwfQ6klVrW0dkX7To4wzLdXSVPpe1wAlkRhpXQiiXCKahF22bMuU9jNMMOOPj8cBxgmKrqlCkGnKvDovK6gynFEvneRN888Qs7WybDTKezSZ2OR5bcqw44UnfBdlzzj9ZbYbswVdjFZ7Oz/629WoM71i54raf/WRoCuw5+dybPA+HqfS4WdRNiViLziSH4Pf76lfY+XWmCnU84IyBeXahNuaJgTdrGyQF0GHgkH5HLsInURo0fMflmoQa6wy8gtzly2XC6zddGJSwg7obAbEIq9FRjLKew6QXLydRl2sVDYpfkBPhn810FNhd3W/dkXtXO0YBBEJxA9Kuz8ookNh5awK7mJRlOFnSqltrCwyEGnsJvUKOwA4KTDhvDT+4ENuyfw0O6kYM4pRyxVP9LCohRihTqKSNBvsSXWN82DI/YmMWElExXJElukdIvLLbGyso+TbtkATEQ9eBrSjbbl23WybcTp36SYCKoMYypRmA17wm47fX/RPquVbbPCMN1u9nzXW2JVws4D4ABgYJISsv8tsfWql8rE2UiVRTSM0KRVU0n+XbU1VdmuqBJbXXE1ZxElE8JqlZxa7CLZZ89h4nos3K5qiXUcRI4Hj0WVtrMoZuRcNQDXReT4STXUItuTtM9E2QcA/9/tcjRLP0FUJ/WNii0A2YRc2FGJuixT2BWrQHIkuij4YG6JpeH9dB+mYo3SVrOInlPeSpbS6vPQURR+fD8juLWKTugKb4hzWEJ6qqRpprDzpUlxvyJMlZABsVICMM/0AqTnFc/EC3rOsCuwjC47BjiQFjdUFXVqNcqAkAkF128oWWKTsWwXXqbiZxqipADiPtREN+WKTugsvxow14eDTDHHFXbS+WKZ2osTr4kllqjmDwWo93WhJTbhHTrMR+imzz9hFzU4V4xlY1HHKyfV6iAizziOsuraOYWd3D9ywq4dZIRdUxlf0JijZlpsRiyC+QYKOy8AH9+pC2A6ArsXHBSFHZ/ItrxkpyN4ZoRd0BIE4ApnPJdh120UK+z4oGnGRScoYZcWuygCYwy7x7MvatdYAQnHbx4/G+iZrnCqgbaAkhMkdkZniS25iYTCzhJ2FhZVaJPOfVBk2CV92YE0w275QPLQOOmwJQCAh3aP477tiU3+UWuHYWFRB/xhH9OVbj4p60nplq9eam6J1ajzdEShVCW2uOKqsHFJFhpe/IFm53HCzsnFX3ikrVxRl1s1g1xbQdhJ+1yiRiQqh24ne2arCrtQR246jvicbicbQPdz8RmvyMakQK5eqmS6VQz8JYKL5LKZFH+Iolgm+4RKLqxUU4SSvTQj7BLSrUqtFitFJ2gOXTVxFoCPz5J2sWOWJZcjKAHE6TXpVLSN1Nw9AGgNJ+dNneD3AwjRE+XItqIKq6odU2fnNKiwqpBlcv5bucqPhvcDgJuqNKZ5wQW3QmGnxgMQS2mmNCw+BuHC8XWEn3mGnXoOOjqFny7DTiVrouwcGudizSMo0eO6jrg1qjIxJbDsmROl0+yqKrGVGXaqZXTZ0frXHBe9J/n/CX8u/76QsMuuW18Ua3ELi1SUgc9F3aJFNAp1UawAsZNm2OWKTmiioNwsJ/+QzLBTeZWi51nEFXZZlVhO2FUp1AFkZB0wy1ViNVZUt3ihparoBCfsuv6QWOxtKAWiaCFB7uZ0VGdHGRxHzrEjiFiewO4Fc6iwy2fYNV0GRMmDR1QL0nUCoujEAKLWCngAloNYYqcSEi1sLAOgz7Dj1oJ80Yk6qyQh0Bkn+zVZ/F4A091YIgR3jrbBGBNWm+xzdQq7AvusglzJdiir+hzSJCVlfUsz7CxhZ2Fhio5kiU0z7NJ+7kCqsOOy6pMOTwi7Wzbuw2QnguMAp6+xCjuLehC2Domwy1dr1SndGqUFHLIQ6jJLbGkOXdQRxIxM9mmIQk3+napKASAXPFBDhfnrOESUVscsVtiFmrYBEIeI07YyuWliiQXCbpe0SfNyPKpk1CgHvAYQtQVRSLfXjzAtOtHpRmhK1UuzohOVk3S6WKkUnahqK5N9VGEXIqxYnI1KqqZWkm4FBSsAE+KM5YizyA0QxNOVOVFRTKriirYNBNEUnCqFnZq71++QqsRyZVdxFcI4ZiLrWy2YkJBdCumnU6epBXt0FVYrMr1ysTVcpcc8RDFLiBnHTSa7JkUjCHGZVWnVFw5I2vPFD3n7icJOtcQWE4Z+jjD0s/lNWeEOTpoqCr0OVUr2Mbqiumga5eQ66EasHtlDKmfyDDtedLEIUkat9FkFltFn/H0ijHnKX+sJ9yf+f8BRjwGOepz8+wLig6pTXa6wY36hhbYMsYag8HXCEsDYEhs5Pjwk1bSnHbKASU8XrRLLOPEa68m9xYycwq7IEptl2IVu+tyto7Cj/I3jzh5hV1Z0wijDTlHYxQlhF3kDCefSnUyq0FOFHem3W1xhp6tWWwa/mfBEXVmsFWkI7F4w+4QdV9iltlUAaKcTWb7CEDEvy3PQnXxSRZUTdito0YlUYRc3lwFgmNZl2BUq7GpINdtK0YgKwo5Xh+TohDHG2iGGW0pHRC+CijL1KnIPcxRZYkkQpOsnnX7RTdseAzqpetBm2FlYlIIxllliPReDDVlhxy2xPMOOK+y40vi4lYMYas5+12uxuMH7/FhL2GWWWKFW08UmhDGx2OSrxOqeLz5d7BKDa8VeGodEYUfbEuJMzeLh22eRmOR6RaSbOiAjr/n50FWkSwZKxW2jKJ9/J63Gl2TncdLNIZOHQFL2acLCeRV7TXXafkShKkKBpEgj2bzqKrYOjLZV1HmVFiZK9vlNAOnA2MCaGkYRGrxQhlLAwaT4Q5OSX64PBgdOancu3a6qzgNV2FXtMy2ywRV2yf9ORdGJSM3O63ekk7akSqxi5dRMCOk1Ksgmoi4Lcwo584IPdRR2qv2J5+hxhZrnesn5D/UEbVGVWCmHr8TW2yk4hq626ITmPOba0yxB1RJbrLALNFVqF4IlMWTJeecEm5cSdrX2nSi9hMXWLZ97FivQNM8RAFhxPHDZN4o/0HWBE56q+X1Bhl3M+04nsecDCOH0RNjpLIBBUY6c7jmpQUToCt8pIOGEPdNFN/0eXRYV5wMuVuQy7IoUdqR/TAk7PyXsjDLsqE1aUtiZFygp2y95sbOEDBTjQ55hlz7f0ue4nyrsYq8lSLVCS6yksKtL2A0A2J+LOJsthd3sjxSDJGAd3QnxK/EQdLIMu0xhpys6karNggF0GssBJEUnGr6bdIQpkZYQdorCLj2xmcIu7Sx7KTqREoMCnXLC7kAaNr96SVMQhWPTmuOTCLvi8FYdcvkSKFi5oBOc9Cb6o8/chL3jmoEoV9c1h4HmEqP9sLA4VBGSlfyG7wryTWTY8aITqcJu5VADKwazB4+1w1r0Aj5AZfRZoakS29E9I8rIL02VWCmHjtoiVXsOmUCHqrIDkLNjVMUZGaCLHDpdhp20XUq6JcceadpWk31eutt5dZ7nEdJNXWGldtrUihtIVlzddrPcOxHZQQghrx/tiClcQ4VdTKrt5qqmVg38U2ImRpqBk7ZtGthaJSUcHU+huoAD1LauBwZ+j5nYWok11XEQppYiM7JPVtjFZeoBpa1aOIITdm6dDLsFQdiVqON0RBeZuOvsmDmFXIklVs2wC+Flc4cKi2CuSjcnrJivIcyKFXYZYaYhvMqIy5wllivsNKSjTmEn+nGZsEssrUqGXkkGn86WvBAUTl1w62W6EKTLSqsCKQoVpRa8AOXtxbOjyBJrEnxvAtHX6C2xvpsVnegwQsIw8+8u0kQ3iUqtaoaduoBYgNDJnqMeCzOFHbVuEiV+prA7BDPs1L6p6LlC7s0ofY74cR2FnTIWna0MO60ltoywU4uwyVW0/VRhF/stZNXgFUtslCfsPN6/+YbPy0BfkyASBPbMKLfZJ+wag8n/hNwSmQxuViW2HZew9vzL8lvoBMsBJAo7z3WkTDnWStR8ksJOGfjwiUezl6ITnQnlM9ulF6LIrhoMsKSVtBnXEXbhzBV2kt1Ja4klk4V0Gxv3jOJjP12f/1BRcMKq6ywsqkDvs4bvYqBAYceLTgDAhSetEq8vetQRB2M3LRYZhPKrwhKbm/BBsdvkCLtsApqrUIgiEooWUkg3nT4bdUo3LYFVUenVpxMYHfnF4y/CEoVdHEtqB7VtlD6LC5V9qqIQyApbdTVEoafbrmKJBRClYxzXmblNYi4hrrmKPBvZmkoJu271JJ1X4uTnKVXYNZ1uPqBcRTogjwTZRwb4FYW8WKSo8wjpVjUek22tXOlGxoklkApW+Jx0S3PoKlRyUoXZXhR2qDkBmU9oix0UE5t0gukphF1ix1QVcmWEnazQCw1JQ8YYmZw5AGPCViUXjai2tPplGXLCGmxiiS3L4Ss+B5lKMVVbMdq+7HtQcwSzwh0LQeGUVReVn2e1ik7w55VDFHZOlcKOLBRRqJmzM0UB8RGL6zYhxIC0AIfTg8JOYwGUMmmlDZsdX+Rkz2APoZ7gJOOEMKU3XBYZRzssGphaYrkCmXlCYRewdAHN5HqPVYVdSc5cHQhLLK0SW6JsJvdb0q4pvdfni4L+QDa+KCk6wS2xLpOf8ZUoKCIqFKczXJydA4VdStgR+6iwyqQSY+ZkN5OesMsUdtNpTt0KpFlyPBsvGELQSE6irLCTv1SRYddL0QlOOg4dlv2uxBbLs6tWDAZYmhJ2Y9Oai2tGltj8hEpkDEnVcrIHO3OzTIYHd2oKZ9gKsRYWxqB9SMPLMuy4wu6AYokFgD+68HgEnoMLT1yFF55r7zOL+uATuExh55CiE6Raq0YlJwVa5wJ6swF8lmOjsbXq2lKVXGhKYCkkIzJFk7wiT4tOFGTYgSjsKonCYjuttq2uQAfZ7zgdBGoJSl1lW7rPXb7d/rXDAsALdn4SHwn+C0vGHyl/YzpATYgzl5Bu1VlyXJEWcbKsB5VcJGzWPmLw+6RiTEUVdml78TkVGXZR2IXn8MC0LEsOIEHVRW0lpVsa4SIsseUTnUhV9gGI08+op7BbQBl2zCfKruIJIbVwBUr+m6SwE31lsSU2I8sysiqnsKsgDQPXlSa0XXgZAV2Sgxfmik5kCreuSlxqBAS5BRuJcFNVhga2YKIyzCnsSs5B3lK7MCyxXaLMArJroV6GXTb/4kUn/IqiE5lt0zDDrlcU3EOckHQdBy7jVWJ7KzqhqxJbWHFcLUZV9JnEEuvFYaZ8pMQSqRLbZaTohLXE6t9HC/v0orCjqkuHqDFnTNhpiDIjS6y+6ESQKuyY1xKkmqr+75AomUxh15E/rwqcsFMy7GIxru63DLtGaonl6jTkLbFBo4GoWyKd5AfrtzCdnoDlzngSKMxtqgMrBAsqK+zkB2FzJlViua13YGVqG2UJidfUB8ZTZQ0PoNdbYkkHXDJ40IHKljlEVTt6bOQCjh0PHhLCTltWfXRL8r+u0pCFhYUE3oe4TnLv8SqxYczQCWPRDwwThd0TTlyFu9/z3CyH08KiJvjgV2TYaayWCNtZeC4pHCHnsinkF8kdCTUDbV9LnOVVclxlRWX/WrWaasVFucIuqiDdmMiwKyhYocuwU6rJSwSljuyjkwlO9oV5otC0LSeTvD5W1wHAmSPXY7W3BV9rv670fY4gzhpJZDsZaFdVXOWTCaFQkyqulqvVhMLOydpETgCXtSutqfw7CB0/U7e4DSCqLhwhqeg8WelWRfbJdlpFYVeVYUez89K2jFtiKxV28QIrOqHJjyuzkqZEh0NVq6UZdiUVVpWCCxHcfH6bjjSkKj/PkSbOXfiZw6eE8CqyxMpVXg0srbz/jzXnscxaXHAOJJVhia04Ui2xxBK8EAgTXl3UBQPiuNiqWgaWPSd51dmgirArUoGp1cZnigJSRSo6wQm72O0pw46TaNJYgFabl95sZomN4CJmDlyHwSWWWOl8UUtsxFVSEXku978le1aQU9iVE3YhPESekmFncq5yCru5rBJb8tlMGdMqRSf8mCrs0sgNp4MRci3yvrHpu2KexpWmxmR5lcKu/zLs8go7sWKUSoIbjYboxEoVdn4Lk/7ypC3CpDgCL2YxsFywoHqFXfK5uSqxvSjsGoPkuCYK384tcYMNH0ubyX6MtUsy7Pxm6YNPh9zDlLzWVol1vGTVG4nCcUK3PyNbk/+HjzLaBwuLQxltEk4KAINBRpxMdkKRZbl8QJZRW7LOYibIqqLplFt8AhbpC0dIRBJvr+TfxWE+fwiQ7aU50k2jsNOp5LTqvLRaIjIlla8b4Fdk2MUahZ1MMha3ZRqFnaSoKMmhC8M8UShvt5tvK1SBoXSM/QpmmK3GVKUbIYRiU9KNE15StdZyW6sgVKi92pULjxXB0ZF9htZUlit2kbWtUrrFYTdT2/icdPONtpuQbrKtlRN2JmTfgio6IaycRGFXMmnTqXqgtaOWEHbqxIpXeKWFLwzsrGI/yDakDDoTS6xi65UVesXnIWufVxlGOcJNR3wWK+xC9Rxoi3+o+58Vvai0uPcBQqpjibvFRFoZJEtsqrBDuUIty3jrrSiDMQyKTmRVYkkuGTNX2OkW/vj11KslNoyZqOCLqEvU+zrCzs2IVxaJZ7RRIYXFAPW+rMiw68BH6KSEXUpuGRHUQtHopisls5RhJzgSU0usspBcpLALBgSpVlp0IuWNOHlpvMBVlWHXd5ZYobDLCDt+IrzUEttsNBCxMktsdpKm0cA0S7+oqX2ZJbaVEXbaDDuusEsnyUJhV+eG5aRjMJhl8/GCGBpwS9xQ0xMZdnpLLGePqSXWrKqKLp9I2xGSSQqXEnuI9Io/boldZgk7C4sqZOW/007dc0X/Mt4OMTKV9F/LBg1XZSwsDMAXZliksYeSCVQuhwmGGXYsFkRSYFrAQVLY5cmvQGqryXRT1Gq9KOxKq8QWkW4lbasLVqSEUKix8ZZZgAHxPenIzX5EnGbCMKYZNxA4aRW2zNZKSLduOWHHLaSCsHOzRUZT0i1WFHb0b0XIkYyAqNbqGNppY2RFSEyz5CSrrieTbm6FnTaM4nzRifQzxOSiAJIVd0Eo7HRFJ0qIIs1ChVQhVZBNxYXeMtJPzo+L4GoKPuS/K0oeBJ4rbUNbpbWkaEPOUsr8LPamhLDL2ucVdmGOtNQQdmq1b9GenANPVrBI21ftX6LohbsgMsR4dVEAQBzCdXpQZ1GlV9qXeZUKuwLrLf+s2S46UUDYea4Dh1eJZfT9NSyxmgw7KWpCerOZ5TeKmSgIgrirLwZCLLGcKJUVdv1//c0K1Pu66LlC+obYlwk7o3uVCIMAzIHCjlpiS/LxcpZY3r8ln9NIc/lYMCCemw2E2qITAcmwyxR2NTPsFJ4oUheCesTcKuxSWazINEhZ+2azSRR2OrY0u4HbYYz9SC2ok/uIJXa5OKk6hZ2TfoF8Ip1Via3B/HJbb2MoO66SSrETHaKwE4RdlSW2LmFXnGEnqQcJ48yrFPmIMK5T2I1yhZ21xFpYVIHfZ3zBAACG0sITe8c74iGwfMASdhazB75KLDLsnDwBRW2tgZRhR1bvc9Vas8+JdfZSKcNOmTwQlZx5pVe637IaqjrDrph0q7Smasm+4vy7QqLQ4yq5Tu549YUyNASlxj7cj4h50HfV+ETYWrPrgpNucRVhFyptQUi3CnWeo6rz6OsKa6pOYSdItwrCTpB9TpAoC0jbKoUdNOo8VmJRpIijLlxHJl2YZ2aJDaN8oYy+Bs9e02W/lWSn6RR2oVS4oqTggqoOo/tgkKNHJ4CuQ7fvgsHN5+iVFY3QKNy6uRy9Ohl0br7wRlmGnqsSbjpLbDFpmZGefPt+Rpr2MXiRCABAHOqVXFUgzzqepRZUKOyKM+w0z/uZoMDSTUkFN80m6zC3t6ITWoVdAWmme7ZrEMUs4w2ibqUllp93l2TYLQTCeFYgOBRefKHIEpstBsRp0Qme22ZUZIUp352hIr8SNOefo8yarY7T+IJU+pwOYl7Eghad6BQr7Dhv1HPRCXncEqmLGD1iDgi7geR/FmUXAyeZUktsq9EUQZw51p4x6ctqhxEOsCXJz1P7gPHdyeuh1cQSm8+wc4TCbgZVYqnCzsASO8UVdg0Pw63UEltadCKrplY1UOPQTcYCXUdPbqTMEpsQdky9EUd4hp1V2FlYVIH3ZzTUfzAtPLHtQLKyEngOBhvWAmsxexAZdiXEV2JrVar0gazeRxEpSJQv/qC3l9ZVq2msuDpLLJBTnBVXiS0u4MB0CrsyRaF2n6vIPkq6cYVdBdlXUnQiDvMkYz+ClRADEoQ1NRvYZhVXy0k3TjTFtC2vxFtJumnIPkG6VZF9XGFHVKKGpFtG9pF7R4w9q5R9qSqQqPMYt9NWjAP5NQcgm5SkY0ivVrGLhUDYabLTSogmblmVJkW8wiozy7DjyqC8ukxjRy1R6AWeA8fJMuy4y8WkympuUZ7a1gxIw5wllRBmJoRbEeHXlYpOVLfPZdjBXRCWxA7Isy0qyEorA2MA0vcSpRd3mBWh0HqrkiIzRZHCjufOOURhF/dWdCJmyjUAJR5DerPmGauBaonVE3bZ+ISTew7Juzt0MuzS88D5mEJLLCk6kZJ7XjQLCrsa9mn9fmmsqCZVYtWiE1EHYAwNlrfENhy9wq5Bik6oBZ4qwc93KCvs+HXn9q0lFhAKNdUSO9BqEmmr8sCRQgx9tLsx9nPCbnIfML4zeb1kjb7oRPogdFMpY2MmRSdohp2BJXainez7YDNT2I3rFHYhYY/rVokllUw4RJVYXXlrkmHnOTGimImCGACS74irFoePNNoHC4tDGR0lww6AuN+3poTdsoEgGbBbWMwS+ASOaSum8oFsSCaNeeIsjqJ8G00OnY7sK86Sk4mzYpVcib1Uo1aTBtkmGXYapVsUo7Rtts+6ghVFqkBVJachRqWiE7rjzbftRzCHZ6tVWWLzxBkn3aqVbnnCjqveuNW2EOl5pNuNS+yG+rZEYeeZKewgyD5SIIO3rdiuo1HnMWWhuRB05Z4XnfBkZURh0ygSOdILyRIbMl32mo6oUoLuGQMl3ISd1KDCqZofJxdckGN3KLrqYgmZECefb1IlVrG0isIXXiY4KNmH3HmICGFmpBJUCcN0+8wzUuhx4jSz5EZi/7sLQOEUMQcxy8jO2hl2ShA/V3pxwUoRijPsZpuwy8YK0maowi6dq3cZzSWbocKuiDTTPWM1SBR2xBLLv5eCKrGdOCVKWQSfq6BZdpyLGvy+5ASSjmyNY3G+uvAQuwmR5dXKsMuqIUv/s1g4LHtC3aIT6jVEi05EXcE9OX4rKzpRkGEX+JklVqhijYtOyNl5HHwzM12gnX3Czguyh1GqUBM3b3rwA02qsFMJO/IASC2xu7E8+XlsBzC+K3m95HB90Qkx8NEXnYiZxkNfBK6mC4ZyIYY6TKaW2KGGhyXNMkssKWNdxhrrdkldPQMh7LSW2CxDgZ9/aZ94wYnGUqC1zGgfLCwOZegIO36/b9mfEXYWFrMJdRKprRIbh3mFAzLFGaOTek0Onc6aapolp6v0GngVbUW11mJ1XtV2+d/0VWJj/YRHkIwlBGXEoK3Ql8uh01iPeyAZ+xG8ciurIJJcXoVNIt24ErGcdBMKO7KKHZXYFrVtKelmWPyBt410bSvIr8yKS4lCM3UeJ6epOo9bYqtUclytGMPNiOC0rVuRMygVylgQCjtCtqnFGkqy33L9JAqqxJao09SiExJpWKIuE4slClkWpQqUTlj9GbkMuzKVn674hlAJqsdgWHgjt31uC66XYZcv3OEtCEuipOSKu/Kikwnod+J6oviBx8rnnQEtdiR9nqJimikKrn/6vXGFXYe5MgljiEi9j4BipaJa4bMAYRxnduUi5SN51oeE3vCc7D2HRI4d71e4RVNLcmV9TwhfPH+9njLs0nNNx1gzKTyhyzUs6ftzecGUryFqN6cxJPouH6HEBYmoI8+F7zpwHUKymxZ88VOCNJdhl78fesHcBKgoajQRYpoSRsODreIqsUogbzuMsIOtSH4e2w6M70heL80Udm1JYScPXlSFHVDDFksVdgXMKcVEaokdaPhYmlpiR8sIO59YYg0Ju9zDFNkARcqHIJMF3sl5grAj2xrbnvw/vNZo+xYWhzrakYawa3HCLukzLGFnMdvgE4dYq7DLBjM5hQMI+RWG+TauB4Ar8FLFmSaHLgxj/eDazSY3dFvJPmtUcl5+v8uqtfaWYWeq7NMcr84SSweOiipQS1AWWYBLrLj9CJZOEqsUdiLDrgfSjZNfTKOSc0zVedJ2DS2xYZ5kZIaFI4TCzskr7KqUbpkVl05G0u1WkG4iE00i+8wUdrrsvL4GIapEhdayYgtqThC57rq04EKJOi1S1W0k/y1XMAIsNykVhJ9oz9VtgfT3MtKQz0+yDLhMBZM7Bl2GXYElNin6UJ0FmCtapLXUFtskc8U/iEKwWyeSaJ4QRbFwJSEOIWp/GFtiyTlxvGz+ZaiwyxFKhoSWMQruoVhD2HVjp/SeK4Ku2nxhjpxwg5XTEXGc2MKTD+noLbZknNCNiQuNnPuFQBrPGDmFXQkPgeS8xinZxBecesqwo6TyTApP8Ge3zhKrVQsWKezagoeKmAPXb4jPaSCS1KxdMq9zHAdN38sqOxsTdpwnkhcpc4sYPWJuCDtFjSZk4pywGxoozrCjDyA3UdjtYCuTn0e3AWPcEnuEUM/pFHacsGsGcpVYoIYtVijsCGFXMgicbGcKO2GJbesy7HRFJ6otsYyx/KAE2bGJiy+OITIUyEqDn8pCx9vkfE3uTf4fOqxy+xYWFkQ6TUhzVWG3fHABKBgsFhSyiahmgEsy7PgCmS4/hkUawo68zhR2GjutohxQ2+rIvsoMu9x26yv7tBl2pm3jfFtTVSDf56CK7JOIGaVtnxedYG4xsUDhamytvHIrqyDdeG4bo6SbsMTWV9hlFVcriDPRlhCFooBDVXXafFtOnFXm0GmKXYhxa2WGXV6d5/hmVWJ11Wn7Glo7apkyTSWqZIVd14D0y9TJ+YIJmcKO9AXKfmRWQLnCK1fY5Y9Dp3BTCbMyS2xxjp5O4RbmlIrF5yDL8aOVcnsgToXCzzWz2c0zQqm4QdiDwk6OdaLWzDL4dHFL+jwzy6gxKjLsXMeBywk75vRUdCIrPJI9G7Nquyphp1xTBQjjWCpWKYZDOkus6yfqwBQeKfhxSOTY8WuQ8xY6kiuiCjtP8DYuC+EhMrveizLsgJnl2OmqxJYVtMhl2JHCU6nTcxoNeJ4rxmABQnTjWGT6q/O6VuBmhJ2pJVZk2MmEnS7TsRfMzWhRIbd4bgHvsFYsHShW2PGHrOMCrot2lxB2Bx4BxrYlr5cdg5ZvnmFHO476CrshI4XdZCfLsFtSWiU2/QyXEHYGnSFlg3UZdlHMklUSeqPQDIX04mt3NYTd4MrK7VtYWBBLLLkHRYadtcRazBHUyoValRsyYo2Sbjw/htHnDF0NzVlT82o1piym5V5r8uAqlW7KgpVW6VZF9onjrSIK6T7zDLsqVaDGfqyo8woz7HTW5RKSsS9hmF/EyTFGBrZcQValdMtIt2w1XRBwhmo1ut3YMGZERzKaVlyFRiVnrLAL85VthTOkMv8ub8XlEy2PlbflY9eQZOf1NWKe/2ZGNOVUDOT7j6id06BohGqrjeBm+Wv03Ku2wpwtl6vbeGXp3i2xXUbPg0kGXl7hlhWtKHb2CIV2jvDTKex051C1FWeVdheCuilmLLNT9pRhp1hiRdEJM4VdrjDHXGXYFVSJ9V0SxN9j0YlIQ1D4wiFQVHSiTpXYjEjVFp1wZEusTwp+LIRrcMYwscSm72FwEMEFI2q2FjqZGrcMuSqxs6Ww01RnLaukrt4jHuGgugl5NoVmci+nnxk4YVLjNL0eVOfUjBR2XUVhp6qOe8QcKezkh5FY8U8PftmSQUSpTDjsKoMbpZxvO4ywja1KfrfttsRH7w8kGXYlCjtPKOyS9ziOU7/wBK0SWzPDbriUsCMXY0kWhAq6MiDZnchrKTsHSMI3mZxhJ1XVndyX/D+4qnL7FhYWsnSaQ2RWpipbS9hZzDb44DcuIa8AINKRUDzDLpIXxNT2WqWbyL/r5t5PX/P90tlgYl11WiAjv+KyKrFRKenGn6fFCrtqO62+oi5tm8+w06kRZYWdZnVWJQr7PcPOsOiEIOwk0s2MOBO5bVRh53Gyz1CdJ5FuPA+uSmHH2xLSzTVT2OnIPhiSfU6cJ/tEpdcq0k1jxeWTBN+wLbXT9jUE0UPUbSXXVK7YDlfoOQEAh1ha66vDupLCjhJ28n7kCjZwdZqjFp0otuV2ckUfOOlHij4I0kVnSdXn8EkZciUKPyGwECrBzFKbJz2Lq8SqSsek8Ef/q5vCouIGxpZYcowOJezMMuzyCrRZzrArUE1HirAG4JbYmSjsCp6NFLrxjAZytmCBVbnAEuvSY1oAKs8ZI1YIO53aTeqbHMSkwEMDXTM1LCFIAcjf4Ywy7HSWWHm8J++Hco/4ZEEitcROo5Fcg0JhxyshJ8fZTfNFBWFHFXZ1M+wUhV2mejb7mCIcFEusWPlKO6zBZgNuOuidaisEmFiVTk5qO4yxgSnVS1ccDziOUNh1I5Z7mPJOh6pgml5Nwi6tcisr7IoDlHmG3SDJsBtvqwrCCMKuKhWdqCbsaEdDO0J6jF06yQAA18+t8ExrFXaWsLOwMIEIJ5WqxMqToNVLFoDlyGJBQVVcaItOAGAht6bmba2saHCsVk3VKN2YLv+O7oe2SixXDRTZaXnbKG2bH+DH0vNMo1bTKew8SpxVF6woJt10RGFxpVfZxsvHMjqCcqEo7Mzyi3S21lghY6vbUuLMsPhDul+6tlX7nBF2+euiMrMvzlenVeNYCrerqWwrxq2GWYER2WdHjHmrFHZ5O21fg6jbTKqT5iu0pscrKrSq6jQNYZez1dL8N5bYp+j1EulJj1x71RJrUKk2X3TCRSdSCLcSS6yaQSdlyJWcg8KiFdAU3gDLLI3K9n1l/yN4SeHePlc4RZFeYWdspRTPKwdw3cRWCpk00qG6KMMcW2L5PN0hQfyUsKtRdIKTPe4sFp2IYyZlC/o6hR05VyGp9uuwqL5SciGD90sGGXb8eeB5nuiXmugaFp3gCwjp/UJjWmZC2IWycCvZRnp96K7DnCWWcFDcEssayTVDLLFAtkDSiWTOqOn3YolNCVKVsBOK0wWgsOMnhKveHC9Aq5Wc0Om2MiBTgqnbYYwxDGIsIBlrq08GkKnnkvfJN72nZNgBGXMqLLH7NgA/eQ8wsUd/HDrCroRY4xl2gyTDTirwQI8PSDpCca5MLLEFCjvSKYZRnNtGR1hik/ayws4SdhYWddApUdhxrF6yAEK9LRYU+IDXKVGMAUU2z9TWGoa59yc/q0RSCdlXsO1YS2DJOUi5bXsyqaNT56kLUOprlg609BVmi6q1FltTpXDsSEO68X0Oi2283chsu36fE3YZcWZqiSVKN6ckc4bAYfIibdLWbFzkatry106VvbQkY7DqeDnpxnpoy691rl5M2qbqvKpKr6ItzbCTF6kL24oJ2iyF1881uCWWeXkrJouLiSKFLIs5WRap6rQyhZ1iRwUh3Bya66Uq7JT26fXL74WcpVW5NxhjhceRKA0VhV6Jwk3N4ZMVdgYqQ02l3JzCT/MZRe35Oex3lV0YM+EAQxzVV9gpC2o8w86vsMRqiwdKnzfLRSeKyGZkx9llbum1UgRdhp04j2oxA7XSaAGkbME4FGSgVmHneKmFlhCvYhGvv6+/WYGqsNNm2PHFhJQzcR3x/qbTrVd0gveHUt84E0tsSYad7lhUUpsWnQi5JZYr7FJLbErYcQeoiDpK53Ut382KlbiGhJ1fQNj1tcJOzbBLT4RL5IUDzeQ97U6FJTZVg+0eOjV7zzEXAEg8xhyiUixfbYScYQcgb4m95u+AGz4MfPml+uOgltiCL4KDMYbJLs+w8zDYSC6ubsRkRR99wNIMOxNLLJGaO47cEfIfO1Gck2SH6QOj6WossVOpJXbAZthZWJhAl2G3YkhV2FnCzmJ2UaqSI69jXq2VEEmq2iI3AFEmgLqKq5md1pMzsHJqtfxiEifVctsWOWclJGNFoQzddr2q7Dxl0l5MupVV5M1vl+bJlrXVqfP6EkJdUT74FvZTYqthyndbBEGcSSo5M6WbUNhRwtq0LePqPI3CrkKtplXnccKuUmHH9zlfOKJKJZe1pQo7QzutUAUuFMIuI6pyVkzyd44c2cYVemkbE3VakZ1URPhUEG7FCjtF5Sf2QU/4ScchLKWuJsOuRg6fjvjUEnbqOcgsrTFXyEnfg1J4I3cOk36QFxrsd4VTRK2XUReFVs4iKIqxugq7nApx1i2xBRl2vOgEIRa7MSVgZpphV5XRV94vRTFDxAgBV0bYuR4ihmpF3mIF75cMFHZ84ch3HcHdmCvsShaPZ1J0gvMhkiW2hDhW7xGhsMuKTkyhmYzz0r6z6aTPl/Q41XndAL0cTdWtnCcqyLDrU4Wd3hLrko5saCA5sLaBJRYAtqx+Uvaeky9KNuM6YiIyHcpMKF/NoCo8ibBjDHjwmuQP22/PPXi7UVyr6MR0NwYnpIcaPgaIsm+KWlDpxeYFGYNcsRos9gn53BvHcbL8g5wlNlPYLQn4vpK/t8eS/1vDldu3sLDI+iRa+OXoFYPSe1YvtYSdxeyCT+AE+UUH8GRlU1hiNavbwp6oDkBKiCTVGpVX5ynWVHJfeFX5d6Jqqi5LTtmu2laZeHga1XkcF2XnVReskKrEevl9zrLz9HZaplXnFVtx+xKGCrsshy5PulWNbQTB5VHSrSRgmoCTbo7OmmpI9vWksNOSwIG0T4WINGSfyF6uqBIby5MsgFpiqxR2GmVfPyPSKMNK8uOySZGqsOPqtmp1Wk4dRirVJn/nn6EnzLg6Su0zWdo3C4Wcp98HOkkOPJXwogq5MpWgfh9CePWqvBYQbmGOsNMrtXJZglxh1+cZYmHOesmfJaYKu+z5zBhDJ04+y61S2JHnpkQOiufXLBF2BWSvuDRJ1l6SYTe7CrviDLvy45MVdpGoOltUJTaSqsqG9YnXhYycwk5HcvGMz+T7dR2isDPNsNPZmXvIPMxBZ4ktU+6pCjuPKOx4hh2TFXbNVD3HiTreL3GeaMCnxUzrKuympF/zKrEzdVQcVEssJeyWDCQT2k63wDJKLLEA8PBRFwNnvgR48SeBw08Xb+cqO1Vh54LBRSzlTPEHSCeKgbEd8nb3bxIvr7tvJ878p2sxOTGaNqwuOjHRyS6igcBDw3fFlzPVKSDsXL9wpU4HkW2hGeTzik7dnMLOEYTdUJC8R1LYccKuubRy+xYWFvqiE8eohJ3NsLOYZfDniSA4VOJMIb90GXaFq9m8kEIcye8HIfu40k0dvIjJZzHpxgoz7LgaqrjYRbUltoygLMi/E0UNNBZgGv5dQsww3T7TAZlGOZYnN/tbYSfUahVkkLgm/bzCrjr/jp9jYqc1VMnp8u/49VilknNnoJLjikNZJSfHsRRBp87LbK2m6rz6bSEIuwWSYcdD0WmxAkquKmNmQVQpyjCmqttM1GlC3ZZVOAVQWa02ytlR+TlXyKqCe4Pa9XRFI3KVarUqwSJLrWtmLc7Zerti+2IfpUq5ct+Qq9ZLLLVA/yucZKKnB4UdUR2FxJZZpbCjzw5t5dM5zrAT94+UYQeIfLIaCrsceU5e95phF8VMkMbFCrv0mFJLbPb+LMPOiIha6ODflUGV2EirsOvUU9g5GoXdbBSdkCyxXO2vK6Ch2Kq5JTbsSEUnaJXYhiMXnVCFGIMeOX5TS6zIsJN5IiFam2F19rlZalMssaGOsBtMDqxTZYlNlXNuaxh42edzm2oFLsbbVGGXHVKAUEvYhREDxrbLH7R3vcjGu/quHehEMZzuJOAAaAxWKuwm27zghCe89QMND2PToagemxyfYisyrKQGZERB4GsIO98FOlFK2Mk3kaqwk6rqWsLOwqIW1KwDADhcUdStGW4d1H2yWPzgD3tWNMAVBFYHgKO1iPKqqEVtIey0OrKvYOJQaolNq7TTamIaO215dh5/NjrQVbYVCjutOq+C7KtU2JWo5LjCjtppyWsWdeEUbFdnPe5HOJz8qsyD0+TQ8bYVYxtXZBvnz1NV0Ql9294Vdo4hYcc/WyLODFVymeqKkm7c1lpBumlsrS63xFYoeKAh+/oahCjSK+wKMrgUso0r7LomGXaFFU6VCp4F43ZOegRK/8O/r9xxqKSJrrAcsbSaZNhlhJlatMLPK/T43wlZXpRBF9EcP9dFMjli+XNQULgjlyXYp6AkW0L01LRS0sIHUabWcyuKNtDnVzeOMUDUZABm0RJLLIssyWRkjEFcmqnCLmQuIqa83xCRaqsGea7mMuzI2KD0M2tk2Lku4jgj2mVrc39ff7MCQdg15J8pRBXt9FlLMuxadTPspHFZfQt10b6J/a/6XHUh2iM1B1LCbgrN5BpI38MJu64oOiHP6wYoYVdXYdeVFXbZs6mvFXbJYIuvKlFlwLKh5MC6XZWwUyyxXV6RUX8zFynsgMQWS9s1PKJCyynsHhYv1+8ag4MYA066b8FQjoRUwRV2PLsueZ1se1KnsBMXFpdumlSJVR6EBPyhIlWJVUJPh4Lke5jukg5LEHbWEmthYQIdYecq96Q/03RRCwsF/GHvxppBEiD6ex0Jlc+wKyLsivPgWJE6L0e6lajkClSBjiZ3zxNkX/l2dfvM70dJoVVmpy2w7miPWUzWi8k++tmyopBP1HmhjP4m7EQOXVX+ksbWmhV/qCC/SDEysd0SFZTUVqdi5NdUFenGNG0NyT5oCErH2E6bVwU66QTDr1TJ5ck+V1hiw6SKacU+LxhLLFG3CSKLhprniCK9nZW5ijrOIL9NJZtYIeGmEnbKxEyxxIYqYZYj/Jg4zJxCjZ4HI5WgautNFHaMsVLiM59hl20fIBlkhUot/j3IhGGsKh37FAkxlBGi9RV2GQEVxrEg/6r6IxqxIuW8zXrRiXzBEHponFiMuCKzF0usJsOOEmxSP6UrZKJBGMdaq7LePuyn78+uQSlfdrFDPBdT3kJL2MlVtFWFnRGxzr87KZ5lNiyxXGFnmGGXKzpBCTu1SixX2KXK5fQ4u6FK2FGnouF8ztcr7LKiE31J2JHAP2QnhGaVDA8mFrLQ0BJLs+go+O9FLpsrE3Z0Us0n0QlhpyjsxncCSIpHrNs1jgEQAs1EYScIu+zC5eTd/8/en8fa1m15YdiYq9n7nHPv1762mldFNVQVRRNwIICjOIViOygKkWNQbONEVjpLMUpQSGMRRQ6xLRJsxxhbkATiKIqCjIJtQGAMAlOhs7HLgsJA8ap51bxXr/26+917T7P3WnPN/LHmmHPMMceYc+1zzv2+td9bQ7q655y952rnWmuu3/w1qYcd83pRvCykwod1L4ABCRjJGXYI2PlVBYbdNG0Mu622OrFwJmbPrsPf8Zu+DwAA/rFf/e0f+TZt9c1f4WGvSWLx2ec97FrqJbeQJVdKTTXIdjoJ7EOWHDLn5bALI4F92Tbz9aYzrhI7L2EdicERuQRYBt2ktri/wnEGGg5CASEWdrFyDzsTmG4LQTfRJLo8tkFGmhFAtyrTzY91RA+7qjR1zNqeyrCTvA1rXnIxKCOuF0G3DpYFdCRtu+jbXHwXlbzz1lxEEpuwYqpAkeJhV/GfS5bBwK4oaWXgAkvajKBhw9pzH70UuMfKQysmAJ/amUpa9ZfibGKfMeTsQg86yQMPgKSYVliCvH1k2K0bMEkZdiORci5kZtHgA+KHV7UVII+dFIQSjP0fUk0O1iZSbMM8E+8ROpFdi+xnWfK7RBIbJwDxvEzSsswcOvEt62GHfQafx6KHXXpfSFJil4ZOSH3zoaET0xTHDOJ4oiSJZR52o54SGxl2PnQCGXb+voWAnTVdqgopFYZ8jDLDrl2lJJYa/kF8gBgi5Xnz6bxjkx1gtBPxS5AlsXtBBjr/3TPsxhyl78EySSyCWi4AdKFefgMAZjbczdHCJ4EAc91l1cMOWXQUsMPgiZRhp5gjnhA60Qu0SpTJcobdYCcYvHfEVee12siwG64BBwMbYLfVVstKYtgBAPyuf+QH4Vd955vwG773Ex/HZm31TV444DVcFoXFmG79SeBXCpwVk14V4MwI3nnot2qs8tIRGHY62AfTCNDq24wAptS2A/qir3vntUJKLAAQxn8OzIDgYZf4y0ptmZRt7Qw7BKRqABaGTiTSVD+2aaqAne8bAtPN2BpgJ4F9p4GMFHQzC/c3+tBR4GweI7ZQaSsA7kslsQiaSx52PVgYpwla5cXeBDntmXjYoSTWtenLY9vP7xasXyGgEoGiFKAcODNMkpNmHnRz33Te9y9KSk9l2DF2mQJm4xifJ7QC8NAJnW2SsTmIBx5uQ9fqgF0GOjLJYm0bNA87PA9rlyROSejEQAC7hQtIgg+ijLPGsDNmtrEYJ5ceo4UMtMUlgLV0de1jMOyEVEz6rLPORfBhoUcfBT/BWRmAI4z4CVNlDQD1sPvWYNidANgZCtjFlNhFh0n0sHsgw47eE+lz3bD7ES2VYXcI4aF3sPcedvMyg4cdSmLZe90Frs50sPjKU4hd62bYoe4YH7j+4qWA3WtXM2DXgoVvvCA7p6TEapLYC86wMyYMojoYk5fqnjLsrt+d//j6d87/ewDvvZfzgOjSzKjssbmYpUfhRKRxvVjXBwGw8z/fSh52+MA/SRLLPDpI4c0oCZ0wLRzGSMm+RMAOGXbIrmu6SOXcaqutinUUUmIB5pvxf/OXfxbeuDyTF6KtzqqCYa1LX6BCYejElINBQdaqedgxtkQnsPPEZEz6ewl0U1mBC3zonDKgL7adtz8w7BTvPBzoSb57dNkS6BYCKwjY1zQmrqYg15SO1SorhE4sZLolKbGnSWIbSZq6UNaKoNW8DbuT2kKbt60BZ3Lb05h9Kdg3r7er+NBJbVtk2Jmx/DLKQhhWXc6Fa3OENn0pD4BbepwHDWxDoAgRlxAYkR/rkHDKgytQVltll2mSWh5aIXvgxfXnL6cDZRoWvK+zlFZ8MXdElmuEexxrnzH0wnEss/wslxUjs5PLglda4+QCySEFek5k2LHgA7OAoRZAKEkS+9gedgDEHzGur/WhExMYz8a8R+hEACji3+hzNblPnRA6ITHmkvNC/QOV7w8r91B8lOKAHfoVJt9B5iyVxHqGnXkIw+6BHnYU7JIksZIXJA+doGOJwxweege9Z9jhBNe8/0cO2LXz9l8Eht0J112HDLu75HhnEzn3rFcsiaUMO5eETjT+odnCBF/9kIBgXBIbPOw0ht389yT5FOUFxsKuVQC7u2fzHz/1g/P/CNhdz9t85Rl2B+OBLKqJFgpBsMtEEusBu0QSywZ6yuBDqsxfg1Syb0HH38DdYMOsxGUz/z0w7BCw2z1dTvncaqtv8eLmpFtt9VFU8LDTJDLIdEOGnRAcUQPdZIadX44adpG+vEpyWt3/jnnYJW0xXa/MKCyx83rQ1ss97ASAEiYwwF6wyc/SNie/B3BUT1BbP8NuGQiFUk5DTKKXstXaALoRg+ngQ3cPdt5iOW3OzjsVdJM87KpgnxBkgvveuaHoQ2eEtgj29WCLL1m4zWfBsONAFQUwFP+4DGyjAW8AJGFVl2oPin9b5r+mhk7I7DQESS1nS2kJq0ySC+AZdpl/XP5SnO0DS3m11qWBdwxw09qDdgyy9hzwS4M31i6JTZhc9/Kwix6z4+RCOu4SxpHos7YQ0FpciYedl7+Sc9JQoNxO95I4RkYR9XmOn6esuGWA5IiMOd9GZD4S4CZlSo5hPPGtwbBDnIEAXvxekUliIzFpsSRWYtjdQ0KdFMVYkpTYkocdu6/S/fZYz63bz+NRlMR6wA4neriC8bL1961ThKhUwkvIXSGE5YE4y0cWOpHMHDZtOPgdWPjqh0Tvq0liNQ87LomFOKO2N1Mqz6GS2Ntn8x8/+QPz/y/fAQCA96/n9SNgdwv7ZHs0rzkpHEOWxLIB1wkMu5KHXZKASy6imWE3b0ff+NAJZNgdr+f/d0+q695qq63m0iSxW231KisyzsrgV8mHLrRtFQCr1FZKTKVtUZraUrCvIsVt00GYBJx1VdDNg1/CetGPR2f26R52upxWByiT30V2XpRaATx8xvVVlwlMt4r/0oQsOQF0q7yoBsBOkLW292DnLQbOJJZct8yHLm4zBc582wpLruE+xkBAN1MB3fx6aWAFHvOuAtip1+8aiwFVqYddGSxTpZiZf5wuJ40WPQgmMLCplV8ecR0tl8Q2Gtglp8xKKdcjtBF0VNYPEMEXvgzLPeiUF+CcoYdMRZTEVtoj05Ex/IB7Ca60xskFcJOGG5yeEtslDLslgJ0s81wmGV1cxmTnLmHYATLsmtTv8B6hExpzPfWdWyb55Qw7kflIJgatS70IxZCKb9biHnYA+fmzCNh5NUIDxMPuuDAlNpKDQt2jv6TbRbySxfRZSd7LgEO633cfAgD1sEsZdnjPPmSSWO8degojHT3sABhgt2pJbMpGG+wUbgLzWvtwUluw8NVnhGH3UEksxNmsJ136YOgkht3b3zP/f/sBgHNBEvu0mf+/cX5fCr4XABEEuyDAYmDYUcCOS5LobGHlAjmWPOz8345J6MTMsMObHL74HEe/HuxQmxx2q60WVzQn3QC7rT66CqmpKsMu9WXrBV82iaEz/+6fQ4IfXPbyWAG/0vAHz5JT14vbrANnrQrYoVwzb4vS1AC6qcy+HHRrGgONmS01sn0ECC/LyP7iE2iZ95MQiBD3d933kMUsOcilqUtlrXh+jSBNrUlxuxJLrgoU4nopKxBBt6VgX2wbwh9q7DyX94umj7P+pRdKidkXGXbltng8KNi32iLnbgTmYaewy4IcNUvE7v3n3MMuP09Z0mxgJZ7GsOsV0D73sOOAn8LQAxMBlKS94MOXsfzS4IuqB51lL5dBSj3vc+4FyNpXZMXD6hl2aRppcyrQQxhjqSyzzjiKoJIAQj2WJBYgB+zIvjXAPOzuwZiyvA8B6KEaJ3nYRRAZLUISYImMjRKmJAmpsCvvf49SU/58yoCuBQy7Yuo4XWbiYbeQkTkJMl0AOSGWLlcMnWC4StOGbXIesLuDNCW2Dww7L4llyqldG4HrxdV0UZY75IDdQ8d7r4hhl7LGRjsxhl0XLs6ZYUclsTj76CWxAbArM+wSwM4/TJNYXogv2DNgN59EeMsDdvYAMNzCs9t5m7/n9fnP144z7BRJrMSw8ymxKcNOAezoZ0qNBQ87kWHXtHAYoocdehOEh8HgmY0UFd5qq62KtTHstvo4Cun0DX+GhC/Mv7sCcFYD3YK8tOhhpwGFOXAWmSYVSazLgbMsOKLqYceBM0PAPmWbBYBy/r1hDDs9EOE0hh0OZuW2a6soES0PvrvAdMvBr6WS2KbL5S81llwreOctBt2mnNnXLGTYBTmtJImtMuxS25f5R2TJlX3oAugmrLfGsIv+d2fAsEsksR0Mlrw8tjJYpclR8do/WnYfEcbboyKJDYCbZRMAyjaEexGTxS/1sMtCJ05gCarBF8GHj3nQZYBb2YfP8vZZ6AQ/hgg4McBwpTVajcl1qiT2AQw7Cipxud9jFOu/iW9h8DZrGcPuYSmxxhgiY324h514XgiAZKdvYYYdvuNTMg5/ppHzDIAMuxkL2BsP8tcOFQ/RpD+X+vuLrwP8q98P8Md+OwBn3CLGQscDAKeFTgBE4phXU965/dz/mvi8BMglsYgTXSBecgrDzpjUx84X9rmHzs++WsBujJLYNgPsUBI7MUnskCzjMGBKbJlhRyWxOBt22aa9TZTEvvEd8eF3+wG8vJs7w3c8mds+t7t5oFAD7IQ0W2TYiZJYfGBTBLwii8UHocywox52cUbmbrTBbBYH1cF0c2PYbbXVyXWsTCJstdWrqAB+VT3dcrllBN1qbDWJYYdecgpQ2CALS/Chw/WqMt7Ud0+S09YYdo3AsAOY91ln2PH15gEy2ZglfJiCjHy9+Hw2AjBT8t1bZbVLgTOBYRcCHCo+dICA3elecoHZJ8haayCjJMU9nWEnBUeMqeRLbUvZefPLxZz0WpfESp59NYad6l+5xiJA1gTzNRJ2TWW3yd5rjjPsFA88AEkOmibNhuOL1zQHu7gKhgGsYyYn5R52Mkswl9Qi8D9lL7xBlpuFPjDQTwvO0KTFvv1QaW9VwJCtf6XFgR4EX0+XxDYZyFQr0cPusSWxAFn/Q5Za05jQnyY3J9Y6BEpO8rBjfdBXWfJbvi+NzJOuEQE7DpbmoRNrl2Q/SuExpaCX4mE3Kgw7gAV9nmANoQJgVzjOP/9XAW7fB/jJPwvwhb+UfhYYdgywKzLsWOgEQLw/oYcd7HxKbHxOAxCGHSNi7L3nf7h+l1bv8RQC2E1BIr5Ghh2N1IV5ZqvnHnZkNvIrHy6QxJ7gYYfUb86wC5LY0UZJ7MWbAJdvzT/ffgAvDvNJ/MzlvL3XbjcvW3k4YUlMQPSwS1JiM+omGXgpclssLZ1y/huRxIZBQeMZdshmnP8+oCR2Y9httdXJFaXpG2C31UdXAcBywuAEIDxTnAAGBRBJS1wNL6B5GAL+7CYBLCDrLYFupgL2RVmr5GFXBt00L7muae4lp8Xf45jFgOTRIslpk98LHnah7co97JqFDDs8zq0UOlF5Ue38smV23jLQjbLzcJurIKMg421xML+U2dflHnY10K0RgEIqa13CsJNYm52xRblXlKWfgySWgm3sRVsB3DJWDzIoA9hV9l4DoEmzFXaYwnCrgV25JJbtg+I/l0lq6SSAsg09Y1VPGcOu7GGX+fi1p0lqw72cA6crZzglwJAd7s+wM7P3oj0BsJMBrUcOnaDLQsk39ltjAgiDzMDJLN9+rICNK4FMk7R/FcmvnaY6Y27SwVIcl6yd4fkoFbyKd4D3T00Si8c0SYkFZNjVJLECs21Jf/nG3yc//730MwTsOJGoJLWVWKheUmuIJFb2sJv3UQPs7KmAXZcDdtlz4Z71kUlig4edaRPTyw4sfI0y7IgkdrRT2NF6Smw8iRGwSzsbUh3dcBs70/41Ati9Hxh2n+jn7biBC7g+jMCDNHhFYJFKYgWGneZhB1AF7DLKP6mOSmIJ6j3YCNjhoPq4Mey22uretUlit/o4KjzsK6ETTQDscvBLnc0OAFbOkkOwr9FeHNp0ICVJcWuy1kYAv4wxs6y1EhxRZtjVJMA5QAkwA2n3B/vQa1A41oGdJ7ddW8UABx04c86FwW/TnSaJdc6JwFlcb42dh8DZ6T50AeyTQicWylqp/13bLgTdCuy82cNOZyZIbeMLiC22xWv7rDzsyLbWPOgst4xhy8i81wSmhuWgn43vI/MyKqAhD4ab0GORJLQm7RWwjIFduM0ZWCZtA0+aZUDtcsCtBjqmATpx/bKkNsiCV85wspODwT2AmcVYXiOkwGmpAghFWYiST9hDi537BOxm3mbjCZJeLMv7gC+09ZBBthpgR8AT4kmXgH/k3de6NKE3eN59KwB2tM9oExQBsPPjKGMewLA7MXTinc/Hn9/7mfQzDZc4JXQCIA2eAIBbxxh2/nl4tBNMkwt9EnGinZfEhnvB0sLt9h520+SCVd+6AbtRSInFB5U/+K2Z4J0Xh3jREUnskdy0dEmsZ9gNdYZdYBkMBCDcPUkYdi89w46GTlwfbFUSix56F4Ik9pb462WS2CSxpwLYFUInEn8+gjYfR+JhFzTbDLDrN8Buq62W1hY6sdXHUTjY7cwyxlnKdPMgUtVLTmfYiT4hZFlNwcPuvuBXCrqVfeik2fy2AhTqHnYmHucqozCX0xqYwITncK+25b57a6sAuhUALDu5IC9JZa0oidUH7nZygcnYntgWIDLhaNsgTV3ICqRgX7tQ1irJaUPoRAU4kxh2AXQzNbAvD9mgnjxLPOzOgmHHJ7aBsstOY9hlQFEhQK4mSc3ArmpSrfXtPWhY2YYha58eh2AET8+hCvpVJK2LPejSPheBUzwPXNarsBRblMSuGzDhrDjRd61UpN9xGWetRBaY9tx9SLH+h+ubJbEpw86eADhixeAS9mwM+ycAklXAbmJS5TIbcWIhFSefx3MuOs6rAXYuZ9hdGE+2qh0rKeEXfy49f19+I/783hfSzzRcoiSJla4RJqnlDLuWSGIp1tRj6ETj8ZJ7M+xmnClJYF41YOfBraOd8llywrCbHMDzO//gIpJYCsJpbJYSw+6iSU9sGFgP13479/MJFgC7KzPTMm9hP/8tMOwUSSyGThCGnZgSKzEcKmAg1kBnEG+fxeAMoP58U4I2H218+CATITywMcWk2ySxW221tDaG3VYfR+XgF5e16t5qwcNOZeeljDMKQi31sJOCFHAbej5hFzaMgW5tCXSrgH1tCexTPOwEgHJeb11O25TAviSwIk9Q04DCtVWzwMNunOKEbCKJDQEO5bbIzkvb1gG7mZ2HoRPCeu/DsEvYagXATvDOo4Bd6aUwgH0UdAm+OrYIaDQslG3+mQKFS+S0ZwDYCanSeeBDDWhKz1HuYZf3jzylNd2OobIMLanWaIAfe/m03KdaOg40CAAgeSdxzgkswdMkrbkHHYKOCvCptOcsQ+AMvZXWNJGXdAoMLQUaCctrmlwARJZJYr1S6h4MtJMqgCroV0dAVr/9UwDscL2u7EtGKoanpH+P8mLyx4WhE+Pkgh87PS+JbJOBpVJIRVXm+c1QRBqsMtM81hI97HKGXWnSCgDkc7eEYXf7fvz5xVfTz6oMO8nDThibMobdwVyCMQSwc1ESSwG7wLBDDzt34nte8LCbMSQ6FnjoeO8VedhJKbEMiSWhEwAA7197sIow0A5jfHhpyCR621Fwz3pa5EXGsPMvHh75hN3V/D/1sPOS2EuYD/YN7OH6OFZBNSl0QkyJFWYOa2AgFgJt+8YC/MH/CsC/8asCizH48yWS2IZJYsf4HYCAAG8Mu622Wl4bYLfVx1ExhKEWOpFLYqsedg1O6uhgXz10wibrSrf5o5C1CimxKhuRgW5FsE8DRhU5LQ+sSNhQbH9X7mG3RF5qJwc7ZNj1cZC8tC0e50YE+/RZ+smByM5rF8h4AYCs9/6gGwX7WuJDtwQ4Sxl2URJbXq8HKAXW5n2kuKstcowC7lRht0WgiMlZtcCGaQAgL+/ORVlUBla1XE6qBV8w/zi+DZksV5bUauy0sA1NA5I31Zi8HPK0XH4cyj58avtMmsxYgtk+KOtfaSUMO+phtxToIQDbyQw7SX670OPtpGIgTtLv/PqQzWYpYLEweCJLS/YlyosXSn65J52cqJuCpUlIhSTHXVNNE8D1e8k96d5FgTQN6MLz7M9vm3jYzbhCtc9LfXNJ6MTNe/Hn63fTz4KHXQq4Fb3xpO3gDLvmMvk7svOPdgrvdABUEvtAhp1XctL+tlKGnT/Q4wHs5GBykA+6/f94UD64YQy7ticgmH7ApNAJ62dy9g33sPMvHsPN/If+yfy/wLC7mOaDfe0u5r+FB/RRvKCk0Ikrz7a7SSSxwqCJLrtQeOI/ad8FePn1OTjj3Z+ad4VKYskD4zASwM6laSiRYbcBdltttbRwNmZLid3qo6w2A+w46Mb80YSU2Ai6caabbyt4yfVtDShMwb62GByhSVMVplvbLFivAva1BbAv7K8C9iVtuSTWr1dJeu3ahoVs5bPP55ISGxl2+ovaaCnDLpem1hl2QtsFYN84TbIUl8haXeGFQwLdYtJrWdYa5bQ5O68zCxl2nQy6LQusIC8jSxl25wTYEaVN8GfOJLFp3xi4DG9C9iUy7IT7iCPvDRITwm9Hs5BdprH8ghw0C85YCpb12XckaTDdh5bLeo0GGipegJmPHwuNUJg7mX8Ze+c5h5RYiWF3cuhE0zKQqQ52FUGoVxI64dl0yLAzuSQ2Sclc6GMXUzFlD7twLOk9dgnDjkpcjcSwi9endTztV/C8W0vZEeBf/jTAv/q9ADfv179fK9HDjgN2nsCDoZSUYWdOZdidEDox2VkhiHV4HrEIgBiGyZV/i0InyDiOhWneNZ6g5Z+dDUzQwDQz7Ag5DNOHcVwiedh99cNb+FM//mV5fNHpDLuVAnaRjYassGzw608w+sR8gAw7KokVQDBeF55hd0dAMTRR1CSxZvSAncCww9CJnQfsbuBi/lsY5DjxxlsKnUhTYnOK+3JJ7LyOtyaCTn/jJwAgvlSN1MPONHAcp3CTa1iM8RY6sdVWp1cprXmrrV5VBQ87fJbyGWmWQEoHy3UPu1T6KIF9VaabAJyF4IhK27BeYUb+/h52RNbayuvVZK0tlbVW/f4EZl8FsJPAzTUWZZxpNU4TdAZBt5xhV/KSs5MLbWlK7BKwj7Lz6HpbktaqvWQ7JzP7Ytsa0w3BPgqcIcOuJqdNgaS07bL1ShO+nZnAWv1YR7DvEV/8X1URaVvHQQyF3ZYx7KYKw44tQ2RCINjlz0+U1coMuXwb8FxzOSoyuBTAjrEEDdnmkjR4IGBYBMxSGfXIfafYNgwa6MhlvQEwlD3seMqs4Sm1K60UGFLSSEtFWF58WbXqJQ+7hR5vJxUDVaKElUpiWegE3ZZKZUxRXy3fP7q8qoedwrATj1XD2I0r97BruzkAE2Am4zy07uFh11APOy+JrXvYSQy7iiT29hkA4HJ9/7ghLLuASzCGXWm50nbg8fR1bDzOQZ6dPYyzhx2qpsg7Xe+xqSMD7Jxz8E/+4b8Bv/OP/Tj8ib/15XxbECj0xLAEsDNrBOy6HLDLBuxNmsb1/o0giR3qgJ3MsJv/hrG8WPiC3QYpKAJ2b87/334ANx5c66f5YF+HlFgyMBPCIRAwTCWxUkqsBNgt0HwDAewsQeB9wgru29ESQBFDJ1zKRAgXISLZ/eZht9VWSwuvw00Su9VHWYElpwFJ3MOODD4iw24p6JZ72OlMN0wD1SWi3cKkVzk44iFy2ookFvT1InvrfnJaHHuY9EXkzFJimzAbXQbddqKnmwfdSiw5K7PkmgVprZSd1wjsvBLjTJPihtAJUwbdOoFhR5lutuB3FcA+qa2ZYFwAujWChx0AgB30Sd9mEsC+tRbZ1kxGVwmdyDzsOh6WQI4dGXPTF6vov4YSZA52yTY2OcsvTWgdssAGDviVGXp0P6XQB5ElyIIvqgy7zIMOAXWNZViT9aYswbWHTszAUDw2rT8OpWs6qSQldkpAplrhMcPwEXCOsIdeBcPOgzb02vF/m3zy5+jIM2ph8ETmo+gLxxKhn9LJnAWAnRUYc3JAxxw6UQ2pWFM9/fT8//U3yt9bUtT3UAXsUg87GjqBDLvFKbF04rEWOoH+dfs3AF77tvlnGkIRJLEnpMRKTD8C2L10F9C2KfYE4AG7KYZO0He6PqTEpu95f/fLz+EX3pvxoT/6n34x3xbElTxgh/dLYyCw9+5bHwHDzl+4iocdSi2e3TCGHZHEll6MpdAJ7IB7k3YYlMQGwG7HJbHP4M4Df51n4d2gJJYOcgQmXGQD1kInhJePhQw7fNC9Ob5DVvwSAOLDdWbYRbR5kEInENzcGHZbbXVSTZML97QtJXarj7KMMYs83SSpZl8LrCiAX4sZdppENAmOUBJXFQBrlqbWfOgUoNCUwD6UtWpgX1OQHpfZeWWwD+0pZFbg2sp03mu4wJIbCPhFx0lB1rpQEksnRQPoVmLYWUeYfbmXXFdgq9Gwi0aQtZbYeXSfWkHWWpfTCrJW0k+mUR8HhmPZ5ZJYAIBJSD4Nq5DSaddaRGmDY9uMncaZXajmYVJOE5hljBkGkPq/EUCGJ6RmLD1F0poz7FKAtRb4MHA5KgEMOw5QBIZchSXIWHo5Q05m+fFj4BrGMqyFVmThH7j+dUtiRxYU0Z7qfUYYcXaCkxh2CGgFKSLt4+YRx5ul0AmUyfr3RptIYpd62M3L5QAF/hqOZcKwq0tixxpjjjCtrEs97EQJ7ZoKAbuXjwDYUQCr4mE3JAy7mdWGDLvqscJrWfSwU/r74fn8/8XrAE8+Mf9MZcCat37JG09i2O2ehh+v4SLezzjDbnSiLzmODw6MYfcz77wIP3/twzvICnGl402yuY8xOfuKPeyO4SGKEbncw24eULsQ9iBLYgsedhg6QRh2ODvCGXbIOGgtZ9jNgJ27eS+cuHZEht0erg82fdEQBkXBb6+nHnbzdtwmHnapH8T8MwJ2+mALID7MX7PP4h+PCNj5mRkqifUMuyEAdtFkcf7yxrDbaqtTKkkT2hh2W33E1SbgF+t/hUCDALpVmW45kFQPjvDPF4WttkTW2qoMuyZPmGfrNTCF7+brfQjDLgeh5t8rQGFjgtVH1rYCUK6t2hZZclb1s7FWAez6OkvOJmBfPEdUiqv50M3ptAi65XLavsCSS+W0CktugZxW8pKry1qRsSSMAQHAlgA7AWSkY9MS2Nc5BLDOALAjMs7AOqpIYjMpJjLDkNnFmWEAKWBHXgQ52KQDbjxwoSwnzViCiqy34wmrTZczhATAbSSAnzFsGzhwKQBudnLBojsD3DKWYdnHL0vK7RjLcKVlqZTS3iNdlIAlKcOuDnY1/ByfwEA7qRiogv2uMRBBPA9+WMqwWxg6YXkfAvydA5Kk71RDJ6YUgCtIYidowDkI6rKUkbdoFz76evKIgJ3oYSdLYtGj7WEMO0kSqxzo4/X8/+4JwMWb8893z+LnGsOu5I0nKUcSht1l7ItNG5bV+8m1gwTYoSR2apIxyM+9cx1+/vrzu3xcFAC7GZsJ4PUD5bAArwqwC5LYQzRob9hNnpzgBhw8v/UPpiln2FEQjNeFB/Ooh90QGHayJLazDKjyncbdfRi3aZhPyo27mFNimyZuuwTYCfLd4GE3kEGnYCJbWi4tPPEXjho03iT7lkhiTQtHGz3s8CVh87Dbaqv7FZ0YKE0kbLXVq6iZNbYs+TQF3Sqy1rZP2lKwr2kMNAaqoFtMiU2f133b1FmBsEBeWmG65YEV5gRGoRA6UQE3cdliW5VhV5YPr60a6genAmdTkMTScU1DPN00sC9h2JG2LQl/0N4ZrNq2DpyNE2Xn5Uy3EmCXgH09bbss/KHz7AVJEgsAMI36OFAG+5a1FQMr1lo2Xj8Zs0yRxCY+XORzBCiDpNEY8eWPMssC2MUCFyJoKIMwGeCG/m0IlmXsNMX/TQhsiF5+uiQ1C71wLh6HkPLK7qdkGyho2bbGt2f7kAF+nOmI+5AyyzLAb6U1TpMYOrGcYRdZR/dNiRUZdq8wdCKyIpsE9Aqf1XzJWGXSbl/ZsTwhdMJOxE9vsvmxAghgI9piJSEV4T6y0v739DPz/4/tYacBXQGwoymxM9lqBwsBOynhtxY6kQB2b8w/J4DdfTzsondhqP3r4ceEYQcQJsh2Rveww2f8CG1y7f+cl8MCzP34vWs2SYbMPr+fmjz8PvWRSWIvGvawJRdnD2POsFvqYScx7DxivGOhE8hCC4BdkMS+CQAAhiSXmCF62GFybEm6iuu/IKETKIl1DuDO70tkEArxw4I3Hq3gneUDMQAgdIouCZ1AwK6Bo40zPPiSMDnfifDC2Bh2W221qHBioDFE9rLVVh9RdY0pMM5SIKkX01rvx5LrmiYCZwprTJN5totCJxRJ7CkediLYd7+2CcNOSePVfffqclo8VmsPrglecoXkU8p0Sxl2MUhBZ7pNctvAsBvVF/w5JVZi59WTXinYJ4FfpW1O5LRC21r4A8qLpZRYgLIPXSuBbsaEF9OynBZZgefAsIsAcBjbcmaXldltmhRzkMABQU4aAb8J0By9CXJSJu2vSlrT85WDXdz/TWfoZWCHAJhl/nMkBddlKa/5NiQ+fk2TLDsPzpDPg+ol2LD1r7SspSDbEPrfYqAnkcSm8tpa5YDWcgbaSaWETjREEuu8BNc6J/a1UmWgra9MxppIYsvPQjtNYAljrpGkykHOyxJupzGwF1fLsLt6e/7/MVNiSx52Fj3sCGDnsYA9AnZVSWyBYaexMUWGXSRLhcTYU1JiJWnunkhiKcMOIHnOH0dHPOxiexyXjNAm+NLXn6cyWP57ZNilgN1jTM6+WsAukcTKHnbzRkzw/M7f9E+VxGLoxBAPKKZ6aAy7nktifacxwzW0YGHfNWD8wQ6hE36bkm0kJYVOUPAOwyx4xHnyM1JBlcLBwD4B7GbaJSLDg51i520wJTZNDwzfGzaG3VZbnVJ4nV/0bZyF32qrj6ha6unGB/DoGeY/bwkIFWWtZSAJwYReGGjXgEIt/KErSVNRXhqAwlJK7Omy1tYo60UvOZC3OZUelwFKDtynYB9vWwZG11Yt8XRTAaxhhNbghKwQ4FBiulkb21J2HpG1lphuEsMOyDbrIOMkymlxOTM7rwT2oYed7EOnyVqTdFo6BjQmvFy6gtIC+2vCzoNoA+MKPsjRO+8cALs4cY8v/Uv94yK7LWUyJmEHwjKQgddz/zoQ5JwqWFUGDfPgjErgg40v3rmXX74NAw98IJ/lsl5BUss98MhnDQ/OONHHD/0w1x46MU5OZtgt3W4izxstCUqoKKgAIPishXtPIol9TIZdGgxgg4cd+RumxFpXZ02xigBg+vcMkNRCsIQaWYgEAqmJVBkBSGQHhu8PhKm7UsQO2WaHD8vfqxWZaHh2N4HTQiA82HZMJLEzq20P83NksSSW+ivWPOw8ZgG7pyTw81n8XGXYFaTlldCJZ/CEMewoG34SPexwgmtwLRyIgvPdFylOowN2836eD2Bnj+HC3CHDzuSAXQcTPL9FQEuQxBYYdheeYXdHQieOKsPOA3aTP8A7BOwidfJ1uIaLrgkH+9pdwMs7BrItDJ1oGxO2PSTFMk+L5OfKzTCAnxPpIMdUEjtMLgmdOI5TuMkZYuB8tBMxd9wYdltttaSQKUvB+K22+qgqDXCQAaxeYNjlslZZqokAV1sEoWTQLQCFmTS1uVfYRX1/McBBB936yv6WWHL3ZSMWQcY2Xe/aPeyol5w2eE9YXXQiFoEzU2C6UTYZYckhEFZjuknsvCT8QXnJTr3zcrCvNU5Na6Vy2kYLf1AAO0u2uWUvJAi6lYIjOkXWag221ceQYjrtWotIYjPARPOwKwQ2AMznLVjTCC+VA5fx0fE4ymoroRERNExBv0aTxLLzpbHToIlpucHSRgIdNUmtX0bSXjgG9HrpGpOCluEY6O3p8tsmldQ2Z8Kwm1zqYRdBtKWS2Pj+lfjhgQOoMJbalgFaiST2VXjYeXCOphv784UMu+keDLtEYksqk7dL78OFZU4EsAsMO3qPR7BRkMTi96ussY+rUMJ5eFH+Xq0IMPeP/IG/Dl985p9FWeiE97TH0AkTPewu4AgATrWhi8sQJoCrgJ0kiSUgZTUlVmLYxWsuFAHsvuo+kfZFlMRCKondE8VDQ4Br6l3+jgfsvuPNGTf58JY9r5kkNt7THw63vSIPOz8QmYYgDQiJrYIktgWbM+xawrAreNhJDDucHdkxs2N8iPbIUOufxG3yB/l1cwNv9jZQyW8kSawgXdXAxSviY5fsnzAjXAPscGarL0hih3FKaKrHcYLReaNr0tGHcWPYbbXVqYUMu8sNsNvqY6jG1H3ZWpVxRoAzRdaKzCEprbUq89Q83SjDTpXT6uCXDrqVwx+S/dWAQmWbl4BuESiUPOxyqSZdlra/a6s2sDYLbDU6gUnOL/WhU8E+CtgpHnYq6Kaw8+LseYnZ5+R+tUCaSpl9rRL+YAcZdBsJUMiBM3zJdAWlRWQFam1LDLtzlMRK6ajlsAMOdlEWZGkZGkMPAKANgBvex2QAI8py0+ALsxDwy5JuSeiEfhwow44HPlCGnbYNuYedMeDlkXH7kCGXsQzVlNhUUgv8GK60UobdcA8Pu+inZR1hhQFUAa8c0MLvm/mkPFaxcxcYdiauE1Nix8lFqtzi0AmZVZRLYgWgRVsmS4kNARYJww5tn/x6IG736kMnkDh09/xhyyHX4+0I8P7tlP2d/j5M3tu/aaLqEGbQruo36YTzF9iY9w2d0FJiC8QmiWH35neHH7/iPiEy7HoYYbAOjh6nSoIE/b1zgDbgS7dHCy88HvR9n54xoxywkyWxH7uH3Tee38H/7S9/Ad7npns08WqYBx8hNQ0HNU0DAOirM8XQCSqJDR52JUksetjFYIeD74A9S4lF2eiOM+wAAtL7BlzDm33cn1vYz6ETAPEhzWb2nHMquHi1m9vkDDuKSOtSW1r4MO4Tht3cKXoqiUXfCtPCYAnDboqJR+Pk4oWxAXZbbbWogvS9MImw1VavqlJ5qSJrLcg8dfALJaKaWXRTBc6CEb/kJWe0EAYE+zSgsA66tcWU2Mo2a4EVzQLQDeS2bZGdx/Z35T6YNHRCG7wnoBuVxPb1EAZLxzyJh10MrDiVnYfjqZ2xKjhQY9gBgBrgQL3zNIadJk1NvPO6lCUXGHbKeqcS2BcksXV2XnMOoRNUEouT0RMHy2pSTJTExr4R/dvyMbfG0MPtSNvLHnQaw61Z2D4m3eYedggkxmXkjJOM2UQ96AjTMNkGcgzCMcT2hAGIHnQl0NE5l+4D+aztmCR3pWWtg8nF4ydKL0uF719Nl4ZOAFRJGarH22PKYenyEOCizE6//c4DL9M9Qieya8lXBD8RRFouiZ3ZioRh539MAyzmn8cgiaUA38olsYFh91DAjtwPoElkxOn3PCCFoROtSdR2V3Co9/mSh90SSewpDLuSLFsCfj/zy5OvJGOthgJ2siQ2evxFDztk1+27psCw84Cdz0FYjST2D/3/vgD/5//w8/Df/UN/Pf2ADAgmf/AzDzuAZGY+sNhOlMQimDe5eOGiJBbZAlgIau0R8OopYPcmAHiGXev1290lTNDA9QEHdnLoxGBjFDqXyoWkWA7YCRKOqiQWH6Y297DrKZWaoM1zSmycLQppspRhx5HsrbbaSixkyl5sCbFbfQzVtgaaStJrBxYaZEiQKrLkSFuA3MNuSfhDBM5y0E31sPPbgZ93bb7epWmtooddTU4b1ls6Vop82CltS559gRWIwOjKgX/CsNPecxBgmsAk/cq0RNaqsOQ0OS2CMmUpLhkoS4oFALCKRHS0E/ShXyksOQU4U8E+Ev6gtVXTaSHKWjXQzTol7AIApiCJLfnf+bb9GQB2YeK+C9eIrUhiByrrAyBgWdzfHDCj/m0Kuw0MdG3L2ldCJ7iP3okedhng1koMOwF05C+H+JlpofXvUXnKbC6JzSS5phUAQ12SO++DLKkdzsDDjoIc2J8We9iRY2btFEEm+plSLQ9SkJhDj1EM/Ej6DabEGnK+7ymJ1Rh2AQgK+1d/Do4Jw26MDDt+rCCyAxNJ7Lcgw85Cq6cUMw+71vjntwfKLuEA7ngL8Bf+BYCf/ovyuiSGXTV0wqes9lcVDzuFYedsLi2XgMNuD/A9/xBMpoU/N/06MSW2N/PYREqJDdcGtAGL+uBmHq984skO3rya72fPbjSGnfewU9im96kHjRb/9N/+CgAA/MJ7N9EXASAB7JCi30uDbjIzHyWjfgBHJbELUmIBIvslMOxY6AQOrPcOGXZP4ocCw855yWyeEpueIOqfp0tiWehEMsBcBtgFujsF7IbUw+5IJbGmSTzsYLIB2Buohx1PY9lqq63Eih52K3/R3uqbspZ4q3VgM+BrblsHvzqwUQ5FKmWryUEKyBwqJ73Kiasa6NYWQbey/93DAisa6FVWIIJ9CiswCehQJMDKsVpd+e2d2WryANz6SdkRZBB4CTtvhDaVfDUkJVaTxI6yFHdJ+EMCqFF23gIfullOK/eNEP5QBPtQqsllrWXQjQKFnJ1XA/sAAHong32rLMK8wRCIPHSiwm6zKB8m/SEEJkhyUAa2kcn1AFYF0FB+CVYZdv58ZR52joTEQSE0gnj5DUXAjUti4z7kx1ECLRUPvKaLab0lD7xSaEXHPPBWWonvnJtyoLRWBDzIGHYVSWlMpGWS0Udn2KVBBBMFFUJKLGHYnRg6kQHHvoLCC6+DEz3sKPhUStQNQJ2hAN+JTMmPuh6LYUeSoS00YB0D/7FQEosMOzxXnmV3aQ7w+i/8eYC//gcA/uhvBXj2pXxdUv98qIedZtVFx46O3UM0YPuf/nfhL/+3fhR+0X1aSYm1cLRTwJpSSSwF7ObPEbB742oHb1zOy3h+LpJY2u0/oLLYpgknMDDspLQ2HPiaadYRjxMxm6UednVJLEAMftAYdkES6zzlkjLsPNL7urmGN5oUsAspsa08s0f983bsRQkZd0ESSx7AoU6UxCaA3XgH4FwA7GaGHUpiGziMUxhEwjSGDjlYtzHsttrqxMKZli10YquPoxoTwZ7M94WAbtLgoE083WTWmNa2X+JhZ3TQrcY4U9l5RdAtTXrNwy4WbHMB7KsBhapnX0ulx9o5ksG+1RUFvxTADoGtETg4WfeSm4LsRGaL7owFq1AidHbegvAHK3vnUZbcVJC1igw7iF5yGug2TpMqiUWWnDYOtA9g5znnYsLsOTDsiNImk9EpL4RaQisFKIOsVpCk5pJYyUePtWcMztxDzh/zwLBjgB3bD1x+LomNx8FmwGUpdEJgKhY87PL107RexUPP5usH8CQCsuzGf39YuSR2nKaEyRXCDZYCjST51E6nedg9xOPtpOKhE5jqakwE8Qz1sCsY/guFoJgmic0kv4s97CL4pB4rABg9CIX3Y3D29PP4URcy7MY7gIIXabUYcGk1SSw+ezPAbsY9LuEI+w9/Pn7/nZ/M1yUxJGt9ZUCG3aUiiV0A2ClswawfdXu43n8KAEBm2MEIo51CqIQmiUUyGMpf37rqA2BX87DD5wqfBL9P3Ruw+/BmSLzr3lN87FC2IJpOE0YAAMDNcUwlsegXVWDYGWPCQUbADhl2YVDlC0GtiwrD7nUvicXP7wbvjxeAtXRfqXTXMGNQZNhlHnaJ58pCSSwOKChgBwBgh5Q5R2Z4qIcdTGP0uhtHAIta8Y1ht9VWS2oLndjq46w5SIGxPLAQIDEy6FaWakaJqETdL7PVItjXNiZ7BqYMO5lx1qkMu2Z52EXmnbfES06X01ZDJ1S/P7K/nM2UtHWr97Cj+66BX8gms3ywTEA3zUtu0tqS9Y6KrNWSAbXEzgPQpamTxs6DupfcaKfckzm0nX/XwL5pIuNS5o2I7BHdO4+GXShgn7a/Lq73LBh2xMsax6yZFJS9EOb+b/MyDAGbsqRZQRIb2W0RLENQfiiAZXQbo6R13obMvy0B7HJJqwQa9qqHXc5wa7mkloCOZVmw1j5KYoOkVTgGlA3bNiaR5PbeRsSuWBI7TQ4mB7O8H2BmZnHWW3UhCELNoRPuBElsx0HVVyWJZWBt0u/I9gN4SR9j5NUK7/dq6IRjINs9GHYZgEy2zfptd4m0eeWS2N1r8eeHJMUiCOsMAJgkqCP9XmSQAeQMuys4wP4lYdVdvyOsK/rlhzIVwI561IXQiQ+jzDV8nqaop/dMtuzCdSImFvPQiRLDzrXB0gyJaW8WATufEjvcAExWBa/vUw9i2P3zv/mHws/vvWQDFP9AxIFRX/Cw2/s/XR8tkcTuFkliAQAu/Of4Mn2nAHZ4470AZJYRoIp42L3ezB3G7OcDPzn/kFI87ErbeaV52Al+LVL6LK15sOCgtXfpB/aYSmKJrvw4Eg87Gx8+w5EsY2PYbbXVooqS2A2w2+qjrzaRW+qyVlES29YTZjtjM/86AA8USix58rsG9iWpqZqM1+hyWo3NxNl5ooedeqyYd54QWFFn2E1gYBI87EoBHfG4z8dr5dJ6csw14AzBKWR5hUrYeVpbD9gpDDuAElBI5LTJeuPvGvhlNf87ABhr0tQE7GOgm6mBbhPpG4ydFyaE5ZTYRE7bKww7ZQw5rzeVZ666wsR9lIJmclJ2fiJDLgercpaeHriQSWKbNoI2lYRULTQi+rcJxAXRQy7fhgA4LAAdQ/AGUfRESSvfhweyDIX1h2WQ9kHSu1aGE0QgiYIcGchUK3J88FxZDTRh1XAPOymk8DGKnbskdGJKQyesPT10QgRJQAAkJe8xpcZpCmwwynzMwD+AIAN1Ybvj2GRaCrx+1NV2EWNAFtp9igFxNQ87/F645n0Y56U5wMXLL8bvS4CdBJTV+gpl0CHDztkYRhFSYhmRiIKCSxl2INgMADDAbqp62N35z595cO6Nyx082c/7eX1k1zQlgg03qjz8PnXv0eIbVz38z37k++A3fu8nAADgvWs2yGDyUXEA639+zX/15jCSWa2OAGHlixklsyhNvbMI2MmS2AtJEksYdk/M3KGafTzwd6NVZ9UQKJRe4vFvd8GjL84chgoDtYqH3TjBHoQBmT2GG+E4ueQmeFQYdvZAbggbw26rrRbV7ZYSu9XHWCn4xRlNEUg6mWFHQid4yisA+ITZsqdbBzb4JKXrbfRtrjDsUpBRByhxPXyba/tbktN26v7G3zsBpEwYdsW2MhNyVXUKw64AuiWJrrStB/vGDOyjLDmFrRbYeaytMTAEllxtmxvghuchcXVYANhx0G2JrBX7lRIc4bSgDC2dlrS9j5x2lSUyw5YFNkj+bz33oJM87DKwKpeDliS1dBs54NX5Yy4y7CwFvHywHAfMKEuwADqqoRGl9iLDjh9DKk3mDL8c9AxMa2H9a06JxW0TmVxLmYEExMBjNS30gMsSaV+VJJZtD4JekiR2Ztjl10upcL/5fBTKAsN1eAKDMGPYaX5/QAA7kzPstMTyVRRiEg8B7PD8+fd+PSXWn/uMYecBOzjA7vYb8fvX34CspP5ZY2NSBl1/GUFKDJ5YwrDjy3YCIcyX5fdkgPDc7sEmgN1ekMQO0MKdB+UwYOKtqx6eBPUkO67dRWCnwvE6rP9jD50AAHj76XywM4Zdyxh2oofd/PMT//y9PloQU2IrL8f7IIlNGXYtY9jhQ/sSBEks8bB7aiLDDpUWd0cC2GkMO2E7H1USOymA3XiAXUckscHDroVhdDA64mHnj8F0vI3rZrPEW221lVwlcH6rrV51NaaQEut/71UPu2Xglwj2LfGDK8lpNXYekYhqctolMl5cD29bYxRq4Q8J2Kcw+wDmSUEpUVff5rgslBCvuhLATvFHswpw1tRZciroljDstPV6Zh8HCqEuL0XQzXJ2HtR96FI5rcx00+W0FlrDGFKsraa0sEQSy/vV1JQ97FI57XlJYgMzrAAUzZ/rgQv5MgR2mcKOo+ywkv8bgMDyY8EXaWgFAwYhvly2JYZcITRiiYddfgxyD7teOAYZ6Cm0HzjgR1mKZwCYjAGwy73SFm83TYn1bdxCwC5jkzrlef3QYqCKpX2f+crZe4RO6Aw7xcNuiSTWuYT5GNiIyFoNyrImvPlPxMMOE3hXGzoBkPmf3asYc05ld05oKcE97Ahgd/de/P71u/m6RIZdpa9Qhp0xuY/dIg87vi868Csy3EhK7GCd7GEXGHZdCBZ9dhMlsYFhd2DbYkyUxR6vgwR7FYDda36jM5TRD7hwUNVLnh/+4D5NGHYI2O0CY64mid0zD7tbZNi5dJvwgXcJfsCVSGLnTvM63ASGndk9DV5Vd8OkS2LDduad5ZIz7ERJrJx6xWu0jgB2JjLjiCR2tC4xglQZdloSy1ZbbaUWBtDg7MpWW32UlYJBsoddq6bEUqabnPSqgUhLpKk9jOJ6+4UsORnsa6qgW7cEdFPXy17yfXWl9bYUdJsyRuJSdl57Dgw7Y8L4YRoVWasHp0Yj+/UB6Cy5APYJslb0kaoz7IRBepC1lhl2WdgFEIad5kOXJMwylhwuT22ry2kDw04F+/SwiyrDjrQ9D4YdZbfVwxIAqA9X6h8nsvQkdpllTAyi9sk98BRZrgL6oW9gYnhf8ICTJanacYjth+wYxHtYzxlJ4jHQAbecYSeEXhS2v8V3jxV72FkO2Dkh3KBWhB2aMex4uiWrTHY8xXe5R61S6ERIiSX9rVm2/VjWCSAJ+T2TsS5gEI7WJQEKMfUVwt9wWeFcEaDx5PP4cdRjMOzwnJ7KsMPJUo+LvGVeQjcS4PD2A2Fdqd8hANTZmJxBF3zsns3/a9iEMXE9yr5I/cjyezJAePZ2MPvrypLYyMJHSzOUxL55tYMnOwTshHERAV5Fht8968F3gUvOIMPy4JYLoRO61vmKMuzIjNJSSSyVnTrnAmDXMsBuBqsc7I1fB5WCXr4FAABvmpfwxHn22e5JWPbtQBl2LCWWhE7wuqTtadsEuFzGsBumCXYI2HUXAF0EEPEBfbQkJp572DkLfRjL+IvmHAyIt9pqJfX8dr5G0XB0q60+ykpYcienxJZYcpHpxmfFARDAup+HXTmwIrLkVBlv1TtPD46oAYWNcdAI+9w1puBDVwbdWur3l4Gb8bj358CwAwJgTRroNo8lpqw/tjFxVWPJ+b9PnGEHkSHgTpXiQnwJ0cCv6LsnMezKHnbRd69Jwy4WtLVHXU5bB90m6I0MuLvKGHIkybbNOTDsCNAUvM8K3m0AElhEAhMaMqENsEwOSsGyEPigA37z8mVJLHoOTg6ih5YkaVUBt27RcchSXgVJa/DRW7T+EyW5iiR4Du5YP8MOX+5Hl0tiF283IUwgm2upJDb3sHtVDLsUVEnk5A4Buy5+VmNNkZomF/IDsmejYaDZKQy7iTDsHGU+cnCzC8ufSADCWQB23j8Ojg/3sMNnr5oS64/XAC0YAzHF1INNnzNMAiuBiDy5G2BB6AQD5CjDzjmIYZgCmUgDAwvS6oz1DABREjvCUQud8BM2A3TBu/wDL4l987KHJ/uI7WR9CoHX43WUh5sVAHaZ5DMsGRl288HvJfNn/3Ng2PGU2AIQRosy7MbJweBvtg3TOe/aBnbU145qpK9mL7634QU8dc/nv12+nQZaBIYdB+x0I/qLJaET4cFX87CjYOMuYfylkthIDT6MhGEHABetn0FCT5mW6cS32mortZ7foenoGbz0bPVNV6k0lcsICWAn+ND1rQk+VrqcdhTbFkE3XK+aTkvAPm6/QNYrgn2L2HnyDGY5JTY+qyV2X9sWAivIbLIEuhXBPmMSgLMXGIlrqzHIS+XxCbLkJNANgTONJQdaYAXExFU16RVTYqX11kC3EtgXvOQU4GzQ2XkT9qvKegEgA3MRdHMa6LaAnQcKqDrLaWXvvFXW7inAa98GcPEm8arSgSKA6C+3zH8tH3PjS1e4JiWGXuaBp4VOpC/JLTlfOUONSlI5Qy/fhtJx0BlytH0dtJRkwXnKbA7iZPtPCBgZwLLCGkPgAvU+85MOpzLsTBvOh9OYQawia4wBWq/awy4JnfCAXUMksSeETlBgk7PP8fdwHZ3AIJw97HJPutCdCGiTS5FtAKRWDdj1npk1PEASizJnaOEzr+/BOgVsJQy7ZOy0fw0AAH6J+Xr6/eFWXVfqYVfpK5xh5+3I4PZZ/Ix+TksDvgtMzcwmACDxbB6nCQ4lSaxrA+HqQy+JfetJDJ0AIIQsrIRhJzD87lmPANjNG32bMexSNpooTfEH98r/KZPEFrzhaCED7zBOcDdYGAABu1wSm3jAUQQXATvzHK5GBOzeCoDb3WDjA5bJHVDuuohhJ3nYLZXEUg+77iKCbeMhnUEkM4uDnZKBJQJ2E6Lc7RnII7baaiWFEd6vb4DdVh9DtQnTTU96ldJHy6AbCZ1QPezKwNn9UmIps68ixS2w5IwY/gDVYzWvOwcaU+kxu9aNAUflx8XQCeFFqyIDXlsFPzgFhApMN36cIIJaGtOtCPaFxNWKnFYECsugW2DJCQN8ZGVobUNQhuB/N9XAPpoAy/qz9ZJis0SKmzHsysFlNCX2LMZ8v+l3A/yvPg/wX/tdOVCkgGU54Eb915jflSBHReaZGNgQGHY62DUvX5aEdiTV12aAVzyv5W04ATDjsuC2y/dBCN7I5FuJlyCTtLY54JgDhgVJ7gorBzOn0xl2CdMLAcCKTNBXBmidEMpwUrG+EySsRBKL8EAK2NVDJ+j5bQVPWrq+Uzz6uIedyrAzbQQ8iYfdOTA8H5th99k3LiNhhwc14ISXa1L21/51AAD4JeZr6felbZK846qhEwWG3UhAQZ4SCyDfd50DAHZPpKuTPOxo6MQ4yQw74vGHGA9l2O27Jizzhstig4fdCwKGP3xy9sFLQFbZDUcYGRstMOzo7J4/+JfdvEM3dweIB74resOl2+BZcEfrGWUesGOzjV3DADu6LU8+Of9nDvDa4OOLr96Gi26JJFb32rtSGXZCSmxNEks97Lp9IontOyKJJaj3LInNGXZhEHwOs61bbbWS+ttfegYAAK9fbNfNVh99tQaqAFYHNpqGk0p92RRpqtGBs8iS16W4EmOsLIn1DDtjs8E9ttVBt/j7vnFZYEWZYRd/780U5SCk7SLQzeR+gSnIKNwnaNtzAOwq3mqwBHTTvOT8oHgSXtgQ7FOBwgXr1UG3AthXkaZOngUgtZ0qwREIug3QZXLaKGvVgjII2Mc97Hxbo7UthF2svdoFclbnXJCKRrAoqnVUhp2QcCr5vy1hp83Ll4MvMHSCfkcCDQPoyCWpRNYbtkECzLLQiVxSO3JJbAJa6oDbEh/AuP054JidxxVWZMQ9wPvsISmxDwhlOKlwed6TbqKgBkpi/Xesc7p3mFCWhDqoHnYBZFvOIJw97PLzMrn5+qd9NZxHAkyeRejEo3jYzcfWQgPf/sZFIXQihiok45ALD9g1nmG3f0PfJpFhVwud0DzsPoyfmUbu85KXIt0vk48/M5sAgHDv7MGHTkgedpaETnjZKyqs3rzagTEm4DsvOWBHWIMBMHyEod6jSWJvK6ET4uDX/3zl/3R3SAckSyWxVyT44m6wAbAzrMMYY+BpO//NtRfpgGn/ehggvnH98/PfLt8OHn1J6MSkAXaCJFb1sKOSWJRR1AA7zrAjgB2dQSQRx3PoBH2x8TfoYOy4SWK32mpJ/Z/+w78/+2zCxrDb6uOpxB9N8aHTAxzqIQwzS04C3SizTw6daJcEVhSkqbsmH0gvYdjNbXOZVdcYcqz0tnulrSprBUjlx2LYhd7WEYDzPBh2XhKmAFg4HpIlsQj2lX3oiqBbJSVWbtsl39HWK0liayy52FZi2OG4txLQIbSt+dA9iGFXkNOuvfqMWZYDXRRLkTzs9IRTKbBBYpdx/zd5kj1jc6DCiAR9lIIr8vZ5Uu2Q7QOVxGops71wHJeAlpKkVW8fZMlFSe96ARMJkM2AyloVU2LLDLXcww79yF9V6MSYrG+WxPp3ZEMYmQzgKxUNFdE87O7j0WcnB6Mjkljy/m4nl0pi3ZlKYh8lJRZZkw18+rU9YSXKMtIRmnTCEhlvWG9+1/y/JIkVGXaRnSqWyrB7FtfRXWQTWsl6EoadzT+nqxNTYv1Y2VgYphrDroW7wcLz2yF4M6IlEgZPZJZwl2/P/9++T8DwFTDsVA87xkbrpYEzY9glgF3TLw6duPKg2LVn2A2QPwjDdz1gN3Ggyhh43swdZ3/8YP7b5VuBvXcYKcOOp8R6YFGQ7uaS2DjrF+qElNhd8LDbR8BuPIYZuckBTHZe1wRNqvuH+GLjNobdVludVL/mc2+Fn1+/OK+Xnq2+OaqjjDPB5B9gtp/opeCItiDVrLLz6sCZHnZRD6wAkIGzh7UtA4XOp5BKYF8iaxWekShxkmTAfdtEYFQCRwg4KgV8rK2iRFTxsPNjiUmSxFa85IrsPGTYVeS0Jaab3lb3zqultU4L1qsy7GwJKJQVHHnbBrjnE4J9fJI6fF4A+9ZeGSunEHYAIPmvUTkpXwZNOOVg0wL/N+aBhy90fdP4F1b/stbtwvtnDnhRhpzM0KP7EI9DiaGX70PLGXqneNi1fQH0zD34cobguXjY5XJjBDMCk6tWBMTIADtNJujrIZLRk4qdu4Rh5/9m/DGYTgydoOdX8oal66MM0vpyGcOOjFOscwlQiptAAbtzAIwfhWHnEIhr4dOvXxRCJ+LEU+ph93r6vbe+W98mJwDKJTbpZOOzEQE7ZKPdfRiBSpSU8pKk2XQ9wnWSTUIAJJJY5yI+s5c87KCB28HCB96/7um+C8De1V7Bv648YHfzPgEM5V06pR6eEssBKSwmiRUH3QGwm389Hu5I+36xhx2VnVKGndRhnjTIsMuZZe+bN9mCiST2WJfEXgjA4mUmiZUQ6YWSWO5hh6CjPQRJLADA5JczhYvIhAHdhWcxRMBuY9httdWS+pEf/FT4+TNvCAlGW231iqst+cG10VdNZ7qVwS+VnVf0sItAobreStgFAMC+lZluyxh2MjtP3Wbyt70wvOjbwrECCPvcQy7lbReut4cxM+VeYwXgTFMAFGStNTmtC2OVEktOA/tKbcvgV5TTCiy5ijS1CBRiWw3sG/V02hroFtqK7LzypG8S+nFmk7RZ4EMTX8KxxoTVIwUeLE+JjWAXldTO7ZGFJ/noJUBFa9iLZElSmodGSAw3NfRBZOjxlFchOEME3BQPPQlwk46hKqkVtn+FlfkLunQSahHYUwLsKu94LfcJPAHQOql46IQHCBtjokzW398Sht0SSWxIxYTMpiLrA0QNVqvJOeLHNkEL8VzYySV9Leuj7kwYdujb9iBJrH8uQgOfelpi2CEg1absL5Vht9TDrtBXpFAJlMTevA9wfDn/jExDXtKyE0nsUoYdjnfn5dx4hWiaEhvDpW6OFp7dohw2Pj+RTHbH8a8A2L0nA4b3rAfD9mroRJMa6IqeLgjYtYxhZxqApo3MtcWS2NTDTmXYWYBJAKq+bj4J3w9fiH947bNwsftw3rZSSuwCht1dJomlx6GcLAYQZ+9CSmy7h+D3Z4/JQwUZdoE+DDAf62kMTASHF845GBBvtdUK6qJv4Uf/1z8Cd4PdPOy2+liqNQaaBaCbnPRa8rCLslaJJdcnYJ8sxdXapj50Msg4r6PCdONtyazu3ghtK6Cba1ow0wA7qW3if6cDJL2xmf9d6venrBf0oI21VS2EAYEzV2LJqW2RnScxznC95dCJclst2da/qJZYclWmmwTYlYGzIrOPjZmzz0k6LR+1IdjXLJLTnhc7PA9LyCe4k2RKDha1fQDhliyjlTzstKRaAawCQIYdISB4wGuwjiTN6gy5HDBrc9BRDH1goRGUJaixDAUPuygLjuvPQiMKTMci4LdmD7spBauolHL+3EFF8JWw4sYTAbsM0CqkXz6oWDBA4n3o08BThp3AbFIqCz4hhZNb9/Hom/t2PA5hTIHrDOBfQ0InInCdsRfXWMg601LVF5S185TOCA186vU9vAPsfoaVAHbk75xhh4Dd5ENB2x6+8fwO/tOfex/+25OddQqSh53EJh3JPRH3FcGtWwrYKQw7SVpekcSKKbHEPgYA4Pow/79rSXt/fAZo4XC08AwTYq/i0zcqMNkY0oeYws37+T39AfXgJ/dlTRI7YUqs7mGHQQhHBOz8wTxVEosedkOIMc4HTU8aD9g1OWD3NfgEWegnAHZPSOgE8bDjkthC6EQI5eChE6IkVr+Zo3fGHvy6u328QY3HxOwbZ8KpFBZviEH+g/vQbYDdVlstre/5pDLzs9VWH0GljDPdw66auMpZNgHsk1lySwIcZqBQkOKWWHJkoLc3+UB6ZucpQKGZmeNmGk/3v4MIMO2bfGBZZAVCfAHTpLitNEGJbSvnaW1lK+BXBN3yfQ3AmfYCMhXAvirDTpfT1uSlpcCKIInVxmMFdt5SHzqJJYf9TAuOKCXbhglyV/fO6yRvoBVXZIbpzDTKmolgFU6OtwI7LH9HyF7sqIedyk7L2W0A/uVspAy7HvqmgTuYioBX5qNHQMecYadvQyd42On7IAGGXNJKWIZLWIptznLEv62Z4YTbZogENCFDnCKJJR52EitUqghosVCGR5fEptsjSWITD7tTQicKAEUmyz4BkLSTA5cAdvFYTpNLjhXeKhwBGhsOFq6xAmB3V/5eoe7uDvAEIsNOl8RGD7sEXEWJKtYnfmn8+XgNcPkm/PP/3n8BP/qT78Cv/eQ1fBsAU04W+joShZouspQJuBUksXtNEiuAgVRiLzHsOOsXIGA5O8+wu5YYdoF92sL1YYQPriWGnQ88zRh2uE/vPSpg92iS2JqHnThLjjJNBOyOvpO2OxjtFG7+pzPscn+JsL1eEjsJzLKvOALYvfG5+fs7ckKEByxAGVgMcl3uYZcchxMAu+Bhl4ZOtI2JqTl4E/b3pV3bhAfQPvOw2wC7rbbaaqtzqCWpqVJyKYD3sFMDKyLDTkp6LcpLsa1x0AmgW1HG2zThxWAvgG5FKS7UgLMCyAgxQa7qYVcA3cTAirYAqgKEQeW5hE7UACwEmJxwnGzwsCu3lcG+CmBXCrtocJsrYJ/YLypecgi6CetF4FED3UpyWlcZB6IkdhDm2V0N7PNtpbCLtVcediCw4/z4uDEQGVEEbMr91yR2muLf1nThhbboP2fjvaBvTfrC2nRB/p4z3HJJag64dSd52EkMu1bbB0FS2y/x8WuF7c8ksTQldv0edhLA1hCAe5Gcl7AicV+dyY+VVMGvEVdDWGOPWgxsDVg4SYnF70zuNIadyGjy1XGW5ikMO+bH3jp63RBJrGnjNfKQtN+Po1AmSqWjJ9b1HYYxtfD6RQ/WKQAaPotcm3Yvj32E+uT3x+PoQyF+9CffAQCAbzz3Mlk6zikFrPDACYAkoAEONUlsLXSikBIrSGJRCXGDDDtBEjtACy8PY/CwSxl28/ZkDDuyT8joXAVgl4Qy0PJAkMkYdhJgN+/sMCCI1MGRPPyWetjdHEc4DBaGoNnOBy+Xje+kAsPuZ6fPxl88DRQZdnejBZ1hp0t3Y8osSmKFG5QCBNLCwUT0sNtHdpydL27skDg4RknsrosRyfhSZOwmid1qq622OqeagyPK8tJFDLt7eNjp7Lx60qsadgEUdMsHeK2pyVo9c1yQtVY97JBhp7RdBvYJICMFCqXACsJ25x4/a6wJytLUwJITpamVsQ367RTAPjWt1SJQqANnKsOuAPbVPOzCi04ByDWVbZYBOy9rVVhypbYI3jQqYDeP98aHi2o+8sqYWcFCRghLaPIXrtR/rS7nzBh6LZGTZiw/Wc5qjCHLNgBNUwD9Sh52OWCWe9jlklbJwy6TtIqAG5e05sdgKByD/BgSWfEZACZWAIUTht2SbSeAV/CwWxjakIGyJ6SonlQMgEtADeabN1oSOlEJzQCI/ZNbRQCAkIKL64rXLQW+aU0uBewawrBLQiealjDscLuj/cQiluTHVY/AsLv1SkXTtLDvm0Uedsl9c3eVfu/170zCMN6/juOAoH5IJLELPOxo6Cey0W6fARye+21Y5mH3xfdu4Pf+B38v3wa6Siml1V/fOw/YId60o5PV5PhcH0Z4djPfC9+6L8PuEcZ6DwbsEJHMEMbAsJt3Orxk0AFsYH3NOzQcfUdoejgMBLCrSWKJLLfmYXdpcICYA1X/if2h+Mt3/4MAEBHUuyMB7NigCLcVv5usz/9tsG5+0EkzCoKBLa+cYbePgRF+9hQ7m/M3X7y59a2JHdS/FIVB8AbYbbXVVludRTWGgFBZSmxZmrpE1toaB70iTa2x8wDiACht25RBNw9AnOxhBxHs2wmBFW1JTgtR0ti3EuhW8Owj690L+9uXPPugvL9rrCBrVdgV6LkmMexiWxlIMgXQbTnYV2qrgIwFSexSlpzYtsJ0cwV2XpC1agw79L+TQDc/rtbAviCJlda78kLwqCTFDKyewAyLCa1zwikD3AoeduHeWQpMKMhZJXYZgBCeUfTRKzDkih548/5JDLl4HEuAmyLJJe3zlNmCJHcqgKYrLNy2IIkFBy15Hi5j2MXkzHCsSimxBEDKfP5I8umjVil0wm+/8d+xzpVZU6yKDDveh1zaF/+lP/MT8Gv+pb8Af+Wn3snacoYdTX6dL3cClLpc2tzwY7vGegSG3e0BcZQO9l0TjlnCcncuSZPlk7Qf9J+Jv7Rdsl1f/uA2fNRIDNAiYCcx7N7CjQL48BfnH3evyTvHgOZ/6o/8DfjTf+tL6WessmcDQLh38oleURILLVwfYkrsm0sYdujLd/dhsLJ4jICxBwN2CKYdxymNvA6Dj3knW5ei9vTnvR8wj8fI+rrzrLW+NVUqIQZf3GQpsRLDzqOmAmD3zngF/9fxt8Dhu38E4Nf8D+bvB4bclMl8sXBbJSYgBfHuBgs0eSpUxfcEIA4GLvAFod3lPoEhMhtDJ+bfKcMuMAIs8cLbaqutttpq9bU06fV0hl1LvicBdnWwD0CWlyZMN4FxhoCLxpIrA2f3Z9ghuCIy7NryNsfQCRns60GX+uCs/4Ww3jVWDThDgEkE7HD/VQ+7AmAXpKly2wD2mcJ6Vd+9kiS20rbAzqt52LlCsi32Mw3sw+RZyTsv+t9pYJ8elLH2ii/5Otg2aMwwAM/u4uy2nHWSBTYk/m+M5SeBZR4I6AWwjW5bCfTD5UuAmxr6IABmOeDX52BJCbBb4kFXlOTmHngdBxxXWNHDLl4nxk0QDufJklhk2Cn3BTsA/OEfAfgj/w2AacpDGZz+/HpQMcYcYridIIm107ToHRWr7GFXlsT+23/t5+DF3Qj/w//XjyXtJh+66CBaaCQg3DQxoNRLkQnAg8f2m4phJ+zLHWHYXfRtwEMsfX5TKT80Gfvrr376t8PX3ZvwJ3/49/vt8jiBPcCHt3E54uRxMXRCYNi1HcD+jfnnZ1+c/9cYdiadTPnys1tog9dwjWFHQydw3Jhu416RxB7tBN94MW/7Ig+7izcB5jgO6A4fzutfE8MOgMyAAWSS2JKH3c7vxzhGSewdstaqkTypJPZumKLHhzDguvAMNQ7Y2cmBnRz8vvGfgpv/3h8Ppod4Qm4HSwA7Jokd9NCJfdcAnqfbo5UpzhXPFIA4mLhoCGDHbqL4QHWiJNYzEfxLQkgiE15Gttpqq622Wl+1BqAx7IULqwbYtSX/u7gsHcCqJ73uTvWwg8hW68Wk10KyLWmr+dAtYfbJYF/Z/w5BkwspsKJ0rEjbc2PYaQBWCDoo+dBp7LwpgiJqWxU406W4TgAzkgrJtjrYpwJnBdAtSGI1ht2EKbFSYEWZJVeUxFYYdpHZd34edkvCFiLQJRisN330j1vALpPYbVEOyu+90TtrKCSkztvGPeh0SekiDzipvdUBtyWSXN0DL65/yII74rU9aB52JGl3zQy77/vUU/h9v/VXwj/7I8Ron/ifLdp2QRKrGvF/4S8BfPXHAb78nwPcfkA87Dig9cjXLdse7JNNIolFgDb+vEQSe5qHnawW4LLp5LiTfh9AuAlESew3tYfdX/v9AP/aDwC8+zPJn28P8/Vs2g52LWHY0RAces0LDLsf+9Rvg19/+IPws2/+V+c/oBJvPDLAThhPFkMnBIYdQGSk1QA7PPfOws0xVW8GIJeV2B8xdMKkz8uEdDXFoCYACMzCRR52bQdwMYOQF8cP5j+twcOOglSJjx3OFi4InUDjZjvElFhELPeCzJQXTaq9OVoYCymxl0b2sDuSA05ByMSDTgHWSqETxpiQYns72OQBGoox5aTCB+EeOxgF7CwD7DjDro0MOzRZDB4r7caw22qrrbY6h0o807jBbgDsppT+76vIsKOgmwJ+qawxMlASQxiSxFVdmnqvpNcGwT6hbSWwogSc1dY7FWW8TXjOykChLMdYay2WtUrsyYWy1qIkVltvgZ0XZa0ayKgz7KohYAVJbI3phmFfJYad5kO3BLCrMuzOURKbBUaksigAAWyj/a3pAustC64Q2G0dB/0S/zXhBTUY9yugIWPYDSVJ7BIPuwXHIU+ZlUIvJMBNAx1b6BHA4etPjiGT5Np8++2KQyc++8YF/BO/7rvgH/0V3xH/eCrYQ0Co0N80SemX/rP48+0HBUDrVYVOpAw7mhKL/SNl2NXPXQCdhTFI9LBDj75loRMJK44CdhTgJEDpxJmSzp4JYHcCw+4v/h6A628A/NV/LfnzwSsVm6abAVh/DKaEYUfuOQJgN/9uInBMGHbPbiNhqUHAjgKuxdAJgWEHEAG7D35u/n9fk8SO8LUP52OEgJ1V4CyRYdeiQiLtz6jWpNtv/He//GwG7CSG3YEz7ACCj93u+Cxf/z3r4Qw74pVDQa8448dDJ3IpKA56J5JcGgC7SkIsAMATIom9OY4xdEIYJF54wGs0KcOOgo10nTF0QpfElkInACLodzvYZMYs1ILI7+hhR2Q67IHfZ5JYZNi1sYP6zt1MG8Nuq6222uqcqqMUfgV0a8GmJsL4cdPozK9FslaFnWdMFcAqMd2mwHQTQicqfnBTgSWXrlf3obsfO09nBdakuBNLbF97IahVS4ktyY41sK+xkcGjtdXBPgTsJJZcZRLU6kChq3jJhcAKqW0A3cqswElg9qGXsakw7GSg0F/7TgP7Cv53K68l/nER6GJAlf++mpCayGoVdhllt/GUWfI9HexChh2XlAr7kQGPETBbkvJqM4YekbRySerJKbPIsKtLassMwRUDJlhN+uKeSVVLlTC9KpJYNNkHALh7lvsUOv0Z9KBi24OAGJXEIthlJ8g870pVMtmPoK3/QwDZmuKxTRl2NMGXrFMASh35biCdrloSu5BhR4FTl44j7o7zNd/g88Qfg8TDbhFgR87TSQy7gnxaZdj5kIa7D9PfeRErAwTsmsCwk8ldYkosC53AuqQEMX9fvdjN+477LTHsMkksAMDTT8+7cnwnX/8968GAXdOYABTRZFcuiW1citrTn3HAHJPViCS2khALkEpirw/Ew47Q1bH2MA9cBjZgQrCxMZAYdqehE/IgEBl2UugE/fvtYUweoKEWSWKRYSdJYud2OcNu/ph62OELVQDsNg+7rbbaaquzqIRJpklizQSSv23XgM78IjP4MgjVyJNuvqaHAFgVH7oSO89VWHKLGHYaO6/AkgusQAVkLKbEhvXW5UVrqJi4Kr+soQzTCQFW0YdOedFzJQ+78nqjd54OFKqyVgT77hEcUWL2Be9mBXSLPnR5W9OUwb4Sw874Y19ve76S2JKHXUgn5WEHpgFoGiF0Imen2WwZ1D9OAcsAwrgdx+i9IEcFoAw7XdKqe9j1QsqrztCT2uuhEaXgjQi4ZeyvkxmCDLBcc3HAjktVS+UiiBE98RTA63gdf759lgODr0oSywC4kOxqNIbd6SmxZQ87ZNjFZ+zLQ3psqF+gtcK4Z4rhWhNPicXzZGIfz8DQNdZShjNNetUAAQAASURBVN2Lr8af2XP36MM7m84/x/x1OikedhaaDEzKzhOug3nYBXuWh3jYAQBcvp3+rgJ28dy/59Nqqww7npwNEO7/dAy275q0z/pnyNOry2R5iySxAABvfOfc/u5r86avAbADiCw7muzKKfolSSyyvugLAbLWNBCM1hUJhnh5GNLoegaCoaR0MGmH0WStlztvKjjqktgaGxBR29sj8b47VRLrL5ydJIn1x7jjgN00/75viYedP8aRYbelxG611VZbnUMlgJiSEgsgs7f6pgD2GRNe5nV5ad2XTWa6mSLYhwBWp7R9nPWeyuxroF/UNj9WfeLZJ0mAcbB4Hgw7V2FXBGBLBCfL4FdDAIG8bXlcVAq7qIU/LGmrMeyWSWLLQKEoxa340JXCLvAFpOZ/J7ZdeWXeZ0TmhqbrUQpalqOW/Nsylh4JnVD94wDCy2/OLosEBLrcEmCmhmc0QsqqtA8TezkN+yB4yIkMPe0YUEmuLqnVU2Jb4iO4YsAEq2kATeMfIonNPew4w+5F/PnumeBh96pDJ7y6jfZdlAIiYOdcmTXFauLXIqmsD5MUXA7YXR9zQH7e9rgtQWJrXQKUBklsSxh2ZxE6sZBh9/wr8eeb95KPDkdMJfXPkyCJJeOc8DxoAcBkYFITgGO2XfYIz0WG3QNSYgFygO6KAXhYJHQCgUPchkmBs0QPO4FhhzjSvLAp9KfXnzDA7smC0AkAgDc+N/93nAG7VYROAETPt4RhF2YLOcMuB+waZ2HfNdEjp90Rht0SwC4u872XxyiJBcgGexfgkz8Yww4Bux0D3YIkdrBkVk7xsFPYgCiJPWqA3YKb4YDbhx2syz3sdv6BiIDd4B84lGGHL0WmMFDeaqutttpqfZWAPAVZqwQG7UptIYIreyFIoTUFdh4sYdjp0tToYScEOCwMf6iv95FlrQjYSccqkeLqbEQp3GONNZny+ARBNyNKU8uyVkMYQLxqwRElKW5guj2AJaex1UxBilsNfygEViATQpe16qBbE9YrM2Bi6MT5AXYZM0bwjxvVsANvBZP54EksPQZ2lQITmoa8POI26Ay9+e+MpSclzRaAxxwwy1mCI5d/BdCwJ9Li+3nYLQut4O3jRE3P17/2Ikyh9hR2IDlnOcjM9v34Mv4sethFQOtRiwGISbJrlhLrsnTOUi1h2E0CIPniLr3vUQAPAczGEF+6aQwy15lhV/IOHAOmtGqG51KG3UCYmS++lnx0HDzzzDPsmlYAi3HCyqSTCVjJcQVIJLEv7uJyWsnDblHohOJhF36vMezGDLAbFThrkPqjv/cigQmA+9fFfXzz6VX4+bV9B69dEMBuAcPu9cNX8/Xfsx4FsENWWuphhxR9f1CdABCRg/9k38UZ7bYjDLv6Jl70MYn13ZcHIomFbKC4C4Cd7GHHWXJ7GhgRaKEMsAspsfJNNTDs7ghqLh0HTTYC8SaYhE5kHnbpTXWcKGCXmiy2Dhl2myR2q6222uocqjU4m2ggC50gzxQJdOtKcloAmECXaqbsPJ01JgNYNaabXy/kg552oaxV9aG7J8iYeNi1p23zHFihm2lPgVF4JpJYPN8K6NZIY7vwYQXsc/pxqnnJlcG+WtsSYOdZcgpwVgrKqIN9x2T7kqrIWgMrosDOazV2XpDEnt8Ebc/ZTYJ/XM4MY2BZxk7L+7QqR237AFY5JzHkBnkbGKCc++DlYHbOUIvvRBngV/LyyxhuRJJaCL3I9yECbjlombdXfQAJQ3ByqdxxtSUAQ4vAHmL/FCSFGkuZSmIJwy6AmsTj7VGLgb0JyBYmYFASSxh2HHAUyhYAu46D7wQQpkAQACS/J0A2PS9UQkz6WmTYxe0+C0n2Uobd8Sb+TFmaAHD0DLuu89dn8JEl443gpTqf49zDjh0rEjpxe5yX88mnuxg6QceEi0InGMPuze9Kf+cSWSzCrn5+lwJ21mkMOzaRAhA9/ckY7DJh2MV7KgXsvv3NlG1XZNi9/b0AAPCpu1+YV7kWwA5ZaWlKbErRbySJCLmJXfYtGeSSlFgFBKNFk1jfecEAO3aD3HkPuyPIHnacYXcZTAUn0CSxNXARO8LhQC5COuhYlBLr05eADI7ZgKHjDDshJRYZdm2QsWyS2K222mqrcygEl5z06E4YdvkAIgHThJd+WwCh6ExkEewT2vZtmSVnQQfOukr4A663LqfNxxG2IE3tKwmztgC6LQ/KWPGLA6ng86awtzBYTALspgrTrQT21bzkcDLYCYBqlKaWwx9KLDkV7LMFsA/bagw7fFES2kaGnQLkLmDnNaCs94wlsTHsQLim/H4Nmv+c7xtt5mGHY+4l7LIuednLZLEYOqGy45Dlp8hqKUMOWXqCJDWTZS4C3HIPuyWhEdHDriSJJe09EydL2rU5YAiwcuN/LLJ/J4E9hBU3cuAok8QSht3xOso28ZH0qiSxDEBEJlVLPOwQsBsnlzHySlVm2M3/h+NIZKw3x/S+Rxl3CPA1DSTbgtd1mhIbPeyod+B5hE4sZdgRwG64TT8aELDzfUbqe2zSKQPsDAPnA8PuEM7TJ5/uFYbdEkksIwq99T2kfQ9w+VbeFiA59yjNfbrz2+pkQCxjX+M6gOApwCSxVgPsUqCx6GH32V8JAACfOH4ZnsDtGgE7nWEnS2Ljwb/atfElI5HELtvES09nfPflEQBial3mYecZdkdFEssZdrj+UujE3UKG3XCkgN3CDu4LO91OCp2wMsPumDDs/AuG76ABsOs2wG6rrbba6hwKgSnRPJ4ER+yafFBaBd0CgCV42JX87wCKAQ6tIYBacb0C6JYAZwVm37087HRGYVuV4urr7ZLQCQmgTCfP1l514MwzMiSGnSmDX00ABE73kkOwT5LiIoinr7fACqx6ydXBPk3WGsA+0Yeusl6f9DoJ6zU1hl3JO2/lpYYdAESGHTcWZ+y2fpGc0yXfpR52VDKWMf38eFsPrUAWi5ISi+dmchB2UQDccBuGzEMu7kOUf+UedllohfDeYTVpMUl5DQy5RJqcMrVywDB62CXbsOYiTCE8nIsSbonkeMqONXvWUEnseMgZdkTm+ajFzn3CikPAzt9Dp8mVWVOsRM8wX1nSMQHFD4ylRD3xZYYdS+8VvAONId89C4adB4SmoXysKTNzTAG7YwDs/LPXX6dOAOwC21+TxGYMuyPc+PP06dcvlJTYJaETjGHn2WgAMKertl2q2OTLJh52n3lt3k8tdELsj/4Z0pExcZIQS479L/n0G+Hn73wrgncAFYbdk08CvPbtAADwQ+aL6wHs9iXADhl2BQ87cNMM2AX2WBcOwMUChh0AwJO9l+X6h5nmf9K7GsOOh054ht1IADsCAjrnVDltWAaisF5bDk0HQA0IF0hi8SGNkl4pdCKkxDrGsKMedoCS2I1ht9VWW211TtUHg10JsDMhcKmHfADRleS0UAawkr8JIEdg5wmS2NR3T2K66eutMuwKgRVd05TltMjOAwmgLAdl2MDsUyTARSmuD4M6F0msUV42feFYwghjiZoPXWTYCeOQqg+dB85EKW7qoay1Lfnf3cfDLjDd7sHsw1S/VmHJlZJtcb1dRRJ7jgy7TEZHJiZ4ymUvAF0AkAMhBXZZ7r/WJi9bA/fSQ5ZfFlqhyHIVSSpl/mQprRLDTgCBEDTsM0ktYdhlgB+RtGYeeNTHjzHkkuCN1McvD95IQc9FwNfHXQQcwD64KLCAML0Cw05NiaWA3V0OTkvvzY9RLHRC9LDz94qRSmIXMOzKkljFw860GUuJ/o7XRtsY5ksnSWIjYOcIuyxL4F1jEebZ3d0N/M//nb8Ff/ivfCH/HmXVDSkbb/R+pX3vJ60ksDgAdl4JyQIRwnHNPOwOM3kJAD71dC9LYjVwGmCZh913/Ub44ns38Ot/71+E3/X//fH0e2TZz2/nffj0E99PFUls5k0KEJ4LXeJhJ0hiTQO//vs+Gf78X/+BTyXLLjLsAALL7oebXxAB7FPrcUMn6EYj1TIw7AS/EXITuNp1LCUWgxyWAXaX/HtBvsolsfP2HIB72CkMOw/gDdZFqS3znMDrX2PYXWDoxEExSV6UEusHJFQSy9rxh3TiYRc02xtgt9VWW211joVA0GTkR3fJl603BbAP4gxlL/jBJYCYMNsfwS8dKAQAGewLbe/hYYfbrLQtgX0loLBtTPALLAZlSOBmIgGWwE1k2J0JYOf3X2OrIatLZNjVmG7YtsvPj2vLgF1TWi+CfQqAFfzp7hEcUUqYNYvbSqDbPBbTWXK6nLbpygy7c5bEZmEJxgD3Txt52IGNL+8ARI7K/eMSwE6T1faRdQe6JDWTgzIWZ+6jl6qAaHqqBJj1mYddTiDIwzcED7uCB10uaSWyYAq4WSczHYMPoC6pndufAbuY9BHc9EUJt0QSG5heGohBJbHjIe8jjKX5aKWETjSEYYdhBZNzcYJPk+uTyq4juloOWhNAmjOqqMVWwpISPOymySXy2rg/0c6hMalse5VFmGd/4ye/An/6b38Ffu+f/Tz85z//fvo9Gjox3MS0bDvBOHoCTz8/T2hSbqgQOuHHXuxcBWCVS2LtADeDB8pe1ySxBfm0xrAzBuB3/BjAr/7vA/zI74bf/Sf+C/jgZoB//29+mX0vLhsl058MgJ0MiMV7GmXYIYEp3juT0AnCrv7k0z38cz/yffCP/wPfAT/ygylgV2TYAUTAzvxCBorepx7l6b1rBcAuDD64JFaWgqYMu11k2C2UxD7dcxCsAxhAZdgd3DIPO5pSe3DtfMDIMimyqqXEor/eEZFwPtBbMHsRUmLJMdIYdnjjGhCwIx52+PKzAXZbbbXVVudVHb6HaaCb6QDcQWarIWCnyGtKQQrI2JuggUZg59kiUFjzv2vy74VtNkU5bY2dV5TThvXKsta+EByBTEYNZCzKaQuefWssJ7zY08KxHYJG6YfL5LSyh11FTlsKu0AP5YokVvK/M8x/Ofu8xM6rSFNLYRc1wK7UtvHWJjo7TwcK115Z2ALAfOynIYZpZGENad/IpHiCqiUENgiy2qYxYMz8Xix6uEFkrkmBC3TbNA87mp5akqSWJK26JFUKjbhf+7CtPWXYDUl7yQeQMq7Oi2E3nsawI75z0QMsAkehnAOwxCZpvAsv9TElVn9+PahY30MmVUdCJ/A7o6WS2OWhExJA0fE+TEI1Sgy7BIhO0nvbuP0SUNrG4xbGTmv2sGu7+Vg7C19+94Pw57//tRfwa38JYaHR0Alws11Ct4cXd2OYCCwy7IIf6nx8MoYd97ATQycUhl1JPo39XcIdPvUDAP/YHwQAgG88j0CdnVy8dxAA9tpvx1uXnlRVYdilklh81sZtfOtJPgGB6/vf/uYfEpd9QTMOpPr2Xw0AAL+6+Rn4MQHAPrUeRxIr0QKDJNYm/2sedpe7NkmJjR52y25Ubz1JO4AR5KsAAL1Dhh33sJNlrfT3w8RmnQAS3b0qid2hhx2CZGzQRAfEys0Epb7RG6fkYTd/Fz3s9omH3dw+SCc4NXWrrbbaaqtVFj4jbY0lJ4BB6Lemt9VZcpgSW2sr+tBV0mlDgIMEfiVgn850qya9nhh2UQ2O8MdZluLS9eoSYOk4r7IqDLuuMPlXA92K7Lyahx2TPaYflpluKJWV/O9qbZGdJ0lxm8Cwk8+tKXj2GWTJaaCbRVaE1DZ/AUnbni/DLgOqADKwqQS2AVCGHQ+dKEli05e23AdPZinlctbUwy6XxKag47y9UmgD34f8RTy+nOYedktCI3JJqxwaMVouibVJewm0NMbI53KtRdlZnPlWqiQlljPsyLXNU7fHQ86CfFUedkbuu42JktiUYXe6JFb2sGNSSwJuJqGVwCSx9NqkHnb0vJBlheWTPtqY1GdxteXZZ19571n40y9+cJN+Z5B/f+/6GEC0Fp9FyHKnzzNka+OYL/Ow0yWxGDrx1lUfxzBLQyfsMqIQld+/dy14/08j3Bzm5b914e+rlZRYKXSCPuM//Rph/bHQIq1EOzhan/v1AADwg+YXYT++KC5rST2OJNY/DFOGnWd0ZQw7wcNusvCESWLvKr5wvN6+ih2gbUz0U2Ezu51n2N0pDDu+vqYxkfZoURJ7DJ/fEWaeUSiPCDoOg+94mSQ294LgFVNiSSJbxrCb1x887JLQCTwfCNjpyW5bbbXVVlutr9rAklMGJxjgIEpTPdinDP5LAFYACrX1FtuSZ5qwbgxhEL3zKIhXAN0ksK9bmvQqHSsaOiE8I8fCcaYyXonRFPf3m4Vh532KRYZdBTjDttIAviIvbYJ33unS1BI7LzDdaqzAezDsSh52+ILVVcA+iRWIQGGngH0l3721V+b9BpCBVaPqvcY97OTAB/qZ5kHX8u3gslzuYcdTYjWGHPPAA4BZgpkkX3Y501AMzsCXdd3DrhQakafMpj5++IozTm6WsTHgJwcMlWO4dtAEgIADNpcIliqAbA0B7ASZIHmPBACA8S6mGWcMtFfEsHPpeZ9DJ6Zkm5OU2AWS2LisfKyQMeyKktjcw64xhGE3jbFPTy45VnieGsKww3df52bv+dWWJ9G8++x5+NOXP0iDJZLQCYDgY/fey0McC/lrs+Rhh+NFfq5a3t/9NrnxALdDBOzCZKwWOsGPM/b5Cu5wc4zXyTeey4AdMuze9IDdoKXE8nsSAMGn4no+8zohL1l9Yo1W8LDTJLFPPw3f6L4dGuPgM8//TnFZS+pRALvorZAz7BAYMtIAiQBOl7sWeiNJYpfdqN5+Ggd8b131MUabedj1kwfseOiEjcAbL2TIHRyZvfMdEU9UCVgMKbGD0gkE81ZeeDOjsmE+Q4cPdIMpsRg60TZx4GI4YLcx7LbaaqutzqFwMHYfpltXY9gVvNW6wOyTZxyR6dZK4FfY5gaksIsY4CBscy3ZttTWlNNp47EStrmlDDsJZNRDJyjYJ4GjtsDOW2WhMbUCQuE5b6TE+YqHXQs6cIZ/0z3s5vXK3nnl8IcSO68qiZX8mHG5CNgpwFlTmLmvMexK3nl47FXWZkFOu/bKpKQAGVgVXspaDrahRxNjt0kJqWrKa0XSatk2KAy9EPqgBF9QsMwYk75gE4ZdyYMuBw0JQ25JaMRiH77KPmjHEPdhiRfcx13Uw+4UoJEyvYI0U5IlcsDuIABaryp0As+vt7oQJLHIzLInhk6IEsSwWtZ/SqETBARJwlQIAJVIiIMktslBbUjDpVbN8PQMu5vrCMp99cM0WCIJnQAISbHvvjxmMtVGkmOzlNiWDcsyYN3jBHY4BAzu7UvSJyWGHUD0FcQKgF2ZYff8Nj7z33lBATs891OQ5r6BgN1kRCBWDEERJhJfv9AlsVpVGXYA8NP7Xw4AAJ9+9uPFZS2pRwHs8OY+JDNgXBIrmGdmHnZxNggjnS/uwbB762pHHmbpYK9FD7spPRG4Pik4AoMnAsMOINxoYliFDiwi4DcOKU0/FB2AcZq0r5BARVPV2E10FzzsPGBnc4YdDuh6WEZN3Wqrrbbaah2FEy4a6DaWgKQq2KcHOHSV9RYZdtW2HsCS2GoV/7tiWmvCzpOkqf5F+h4edvFYCettDQHsCkChJn1cW7UoiZXBoK6QEltjybWBYScAZxV2XltkydVkrfW2mrwUQTcj+t8t9bDTmX1a0mtoK/SpGlBoUBJ7lgw7JhMEyMAqy1kUmZxVC3xY4GFXC41gwRcRNEzH+/ieZBXQMA+9IO8CxANuUDz06Lblx4GltFZCIyLLMN2HnGUoswQlDz7692GBF9rHXsSLKwPSSpWkxHq2mgjYcUls6mHnmC/bo5YiKW9ISiwys+zkYjKz8gygtSglFk8/uU65JPZIgklSD7u47UnqLAGRY+hEPG4NGSOsmuHp2WyHQwTlKIAFAIIkFgG7A1EqpoCdERh2EbBjDDsa5gEQrt9xiODZ21cUyyHthRTvUDa9p0rlnIPnd7Hdi0Ou0LDjEPrHGxf+b5D7IAIIkxhk/fMk2Pz5t795SbZ7mQIRCWVHO6n3hp/Zzf53b334+eKyltSjwPbhYUiTfzA2Fwdz0kwBoTde7dpI5ycX72KG3RMG2E2yh103zR0uk8Qiw45DzRCDL24m8pk9ArSdmi5L6yoAdmi4yCWxArLLChl2rRQ6ETzsfId06GE3/7ojHnaIvvduBDAAIM2Kb7XVVltttbrqKVtNqBJrrA6c+cGbCLqhh51i7BtAt/z5hUyyEVqQnjYBZJS88yjoJrHVCv53yTEQ02kLoBvxsHNNB/zVoxQ60TWmCHCinFZqu8YKnmlVhp0Eunm2msKSQ1DMSG1rLLkC2LcUKBTltJXE1RBY0eS9ual4ycWJawF0Cww7TRKL683btsiw0yRrZxw6EYEqwcPOj31zoCh94WorzLD5szI7LPegY7LcDPBL2ZRdAKu4h53mw0f6X9NB16SgWnh/IqBjxnAjTMNyaAQeR+5hx4HPBu6AvJyGcD+UVmrSZP9cagXwda2VpJES8KpW5JhlaaUVSSwFFSZH7iOvOHQCGXYtYXainNQmktj6MyvzgiSVXYc0dIIZ99PfE0CegIdNAFIhlcSOjNkI6QTeqoMnPMPueBdBued37PnJ+w6RxL7FvHejh50giYX03oQVjqtL71XTOG/HrmuAEuwmaOLIUPC2zLa7QBS6HWxynd0e0/sgAMAwxr+9tjNhG14exgwzEgFk8tz/4/+TXws/+8ER/kufe5M0Oo1hBzBjNEjOovXF7rsBAOD1l18oLmtJPRLDTqALM08NIw1UiEfA1a5jKbGnhU5825vRMPBzb1+pFN7WS2JvHGfYeWmrkPSK23BryQn3A4LDgjTbi5oktoRI+woJVNTgmT3wgyQ2MOzmjxOGnT8PG8Nuq6222uq8qjXLADvRl60C9pWAM/zbWAH7RABrIcgoSUQRvLBgQJbTory0xrDTmW6tyCg0RYAzgpuSJJYw7Nw3gSS2IhHFMYXoYefHF0YBkkoMu9p6A6Amgn25Rw2tJgB2Okuu0WStpbYPkLW2nlmhMS+LUtwex9sV/7szZNjhRHTKsOOm+WU5a88lsVLoBA9MsHwZigddkOVysColKcTAhbKkNgPL/PbqHnbxeyXAjXo4zaypUzzs/D5UkmaXyoLHs5DExvfTzIRfK+ciqGXackqsIIltOaj6qlJildCJ2cNOYNidIImdeB8glYWOkP5FGXUALCVWDJ0YAxNsPlaxr8XvtwB+uo1OhKwaMMYgyDGy2V7cseNOPpt/nxl2X39+iOMZTIAtAXaBYcdCJ3hacYOA3bzefdfABXn8HSg2UrL4WhA68fw2bYMhF35nAABgHOdrp28N7NAu0zVwc8iff9lEDNkfAIBf912vwT/x674rbcSYwVpRwO5O8bH7YvM5AAC4uvly7j14Yj2yJJZ62NFZSkdCJyQPO5tJYu8WAGG0ftV3vhl+/vTr+3igGcOuRYbdlJ6IQ5Fhh4AduWn6h/ndEklsH2mcAJC/PBgTj4sqifUPYlESO7cJyVKBYUc97PzgN0hiyXK22mqrrbZafUUAqyKJFYGzdJDGKybMSuBXbb3of1cC3ZS2C/zvRifPdJaBwrKcdiyBfQ15WZBYcgVwk7LzZA87bHsmktiQEqtIYgEBu9wPtyZNRWBLktMubSvKaYMlyz0YdhVZaymwIoQ/VIIyRCluVwuOSBlbtALDrtb2jBl2qUd2CrgNXPakhh0wX8oTUmJrHnRhG7iklSfVKmAXvhz3nB3nv5vJMgXQMSxDkPXSd/LBunkCxKTfyz3smKxXZSr69sh0zJJyU1nxqgETLGKen4GtWhEG2gRN8PsKPmLFlNiUYWdp8umjS2JTxlwC2IWUWA/YOQLuLpDElhh2qkefaXOG3ZgDbAlgR87LLImNy5rC9yFev+TcrLr/eYbdHmL/uDnaFF/JGHYzYPeVD2+zdHt8JiUpsWiRADJg1/HJCd8XnG+371q4aOIxvKPdgoLLfKJugST2BWMTSoAdkp+udh1hCzYhrDRZJZ9I4euXMJdJwWpYdW0Tlqv52H1o3oB33etgwAG8+9PF5dXqcUInxBSn6Mehesmw0Imove5ISuyyG9XTfQf/0A98CnZtA7/tv/ydoHrYBYYdA+zQw05k2M1/ux3pjStl2EntsJAmOY1IBxU6gfDwTbZvRIYdSVnhKbH+PBh/YzrQlFjmy7LbALutttpqq7Oq9iEsOZSmCqwv2lYGzhB001hyHvwSgAoEEUatrSuAX6a83iJwRv42Ce3DegX2F12etN1jwXfPGBMmH08F+1ZZFS+5CNjpoRM6cKZLYmuJq6Gt6Af3ANCtImttC+m0TQV0K4VdIOjWg83T9QBCaq0cOjH/bWcsOAFUKDH71l4dl6ICZEBRlkyZMey491oB7OJglT/PmZxT8dHLt6FP/q4FX6jsONMCGJNLg0WGnQ46GmMElqDmBVj2oNP2YQyAYYVhdw4edpTJRaWXpaL9iSinxKROgWGHHnbzulx2/B6tOEPVEYBLlMQKDEGlMrYrqXANCCmxCNC95qlbxwUMO1kS26TXYpOPa9YN2M0TX3sY4I3LeL9OWHacYef70lee3cb99Me66ZBhRzovMmp9H+WAXcMZdh4nQEnsvmugM/EYJqQ4gbnLt7OEOyQAHaSJsXjuRy+JfbJr475AI7LcRn5fBkifvxLmslASCxAJXRrDbpwm+Bn3HfMv7/xkdXmlelyGnTAD1sKoz3QnoRMdS4nVATSt/tA//Q/Aj/5vfgS+71NPZYadHQPT74aFTkQPu3yAfUlPSFiuD69Y4GFXZdjRv1Ukse0Uj1HmYdfJkth94mFnAcBtDLutttpqqzOr5bJWien2kLbzw2SoMPsk/7u4Xq1tk3yPVmDYPUSK68wsqdW2uQBQzu0ldl4ZdMNljkJAQFzvGby0AsSZelUSO+9r1wuebhXgDMchbcHDTgfsPFAorDe01c5PYJEIbStstabAzkOWodYvQlthf5NjIDBZTGG9HQFLp0Lbc2TYUcudkAKoAUVcEtsysCwLnYjvBzrYlbJQYuhD6iGHktpsG4J/W5khVwvO6DjLK5zLyC7KwBKFaagFV5QAP7ptuSw4XX9oH0IrWrYPKwZMsETArnLPJtcefc42C0MnMobdR+RhlwBcYkrs8tAJvMYo+IiVSS1J/8J3cEzrpIylBEgm10cMsSAMO+IdSBl2xk2BZbrq/ocMO3OEt676GZQCxjzjYK8dwDkHX/3wLpPEtmHSTPewyySxlLkIkCkA932TsElThl0DKENWAbvCxBEHvhIAz6RYyuWuDdfIDNjl12c2CYHbiIC6yLBbJokFqCfFWgfw0xMCdg8Lnngchh0CdiOdAfOzUkXALqL8T1RJ7PIb1dN9B9+BSR+iyWdEpW+mdLllhl3rv2OzjrskJfYiAHaFzioMIGgNdoIGpiBplTzs+uBhJzDs8IE9zeejQXR8C53YaquttjqLaisAVjH8oeJDh8w7CeToa6CbK4Bu/nk0qMw+nZ0XgC9o4su60Fba5paEXUgD9JhOqwOUdB3JegvHCiAGWVgntdXZeWssI6XMkeoDw073sKvKWoVxSFXWCgXgbCHYJwJnlZTYkpy2qXjYNQUfupYCj0JIR0Mna5X1AgCM3oA8bXu+HnbciB8AssnqMWOnMaAogH7+WhflpBxwS218MrBJAQ0jWLUQLGMedpqkVvWwE7ZB85BbCrhJoRX071UPO34MUSoe7JNWDJhgERnofRh2o5MAO/o+6t8HPUADw10CnIwJCPWqADvGDjVREmsoYHeCJLboYcf7D4I+JHQCGXYSYJcy7KYACibHyrSBMdgYI5/HVYdORIbdk30Hr3uWXeLthgw7gke8d32Em6ONtiT4HAuSWAmwS4F0rMxrUJDE0r7ALfZUAtICSewdA75ujzl+NPn70kUft2OqMuxYf8TnKAc/ARZLYgE8vgLMEo6UnSb4effZ+ZcPfq66vFI9EmAneUx4WQFMqYkuPVHkYcElsXixXiyUxGYlMewIjfTWagy7gofdYKOc1XfEmGZbT4mdxvThKW5vISU2O46Zhx1KYudtQiPIXdvGWQawbDkbYLfVVlttdQ7VFoAggAgkSb5sHQG/xLYIfglARQDOKnJaEXQzNaDQv9AWgDNbA90EZl9H2o5C26HAsDMJU0KXtaoMLqMfa/T709qurpj/bVLOhePc9bmHXVMBv7DtfRh2yOxrhcF/Lek1+t89LsOultZaZudRX538JSL43wnjx66PoWt2kMA+fFE6P4YdfdEKL0UqO00G2/pMjip42AV2GWNeBMCMgQ085TWT1KYsDR3w8/eKDHREsIsz7AqAXZY0m74g54AbsgQZaKiw/KIkVgEdtaTbjCW4YsAEi4ZOBGZYzcOOMrPjcwPlpSJgt3sSfjfGpCywV+Vhh8tzs/w+pNmaGJqRMuyWh06IEkRfCSOOLo+880dJLJk0o0Bywnycf7QuZSOmjDzJi3DF/Y942D3Zd/B0P+/viwNl2Hksg/Sdn3t3DjR4DR9pGDrhMZSUYeetBDzLjLMhtdAJN0VJLB7v0QneccL9FbdzXoGOOxQZdn65CNjR7dAksSLDjuyTLIlVAkKFwvu9yrCbAL7oPj3/8sHPV5dXqseRxDbCrAkZkFwAGXzQGw+XxCYpsXUgrFiSh904zzwOrg3sM6xySuz8t7thylDZIN1dEDoBpUETA994DdblQBt74O84w8733Zlh531oJhv963A5W2211VZbrb6awLAry1pFxhmUmW7lxNWFYF8hdKLaVtpmHBQqoFuJ6da4uF4rMDpCW2F/wwuwa2AUxvYDsuQkYMY5Il3Wwy7OBbBD/6VGGNi6aQxsfdnDruJ/FxJmhcCKrgz2BYadsN7IdCtLYkvS1GrbUuiE2rYka43HAL2CkmUXfPcoOy8oOUihJNY15zfe68kkup7QysISGNgWvdN0DzuVncZltZl/Gwtc0NhtnCHXpu8o2Yultg98/WRdgYmkpOVWWYLqPqTApybrzZNytfNwBnYAFBiSkoqlIvs1EhuG4LOZpMT6Y9N70MVLmxMWZAChXpGHHQCAm4L0kfqSNUlKLAH4KhX6sehhx+TtBJBEMB4BKplh16TnJZHExr6eMvIieJQBUWss/zzbwxGe7rtA+EmYZniP3782/z8N8LPvvAQAgNcwNjXcd/AZTAG7OJkJUGDYOXadU6CMescx3znV83BBSuxpgF0brrk5dCK9rzgCRucMu4KqsRDwxAuJUiWG3ZcCYPcL1eWV6pE87NisC0AyqLg0vnOZBiAx/qOAXUsAuz7QY0+RxCYVTgalkc6A3QH67OAuYdjdiZJYD/SVPOx2zGenKIlVGHa2wLDz27JjHnYpYOeT3twIT1o/eAPz+A+CrbbaaqutXknVZK0lIKmW1opAnsiwI+CXVGOx7Ri+I8ta6yCjhUZh2BXauri/0gtiZBQKAy0iGRkFsA/ZeSLrjJrAnxhYscYywbRamL0eIjjUloAzNbBCZ9g1QaVRadvrbbW01ijFPT04Ispp8/1F4Kw3VgyOaApgX9t1YJ1/URJAtxJg17VtbDsIbScECs9vvJfIBDOGXMpO08C2nr+jCBY0GdDAPOhUDzncBpTUKh54ncZOy+SsCjuNK5no2N2mgFnYhpost8pUVBh2nKEXjkHZB/A8GXYR6JEmjZKiEmsP2M2YUSF0YndF/jakLDB2/B6t6PKmMZ43MnnVehLKfVNiSx52AF7eTvoX9smrnQ8WIM/duH1AtmUMIHrKRoxjhSaR0FoSUrHi/tfOEzc9WLjatQE/SICrwLB76n8f4OfevQEAwrDzx6btkCFPQyf8/cJPKDYMzErCPAAy3GPfU++4tsCwY39njF+peFrw7UCew0wSu++bZKzGwT56njvO+FSCSee/FdSQrHb+OjmqDDsHX3Kf8jvzPsDd8+oytXqUp3cWVw6QIKiXgHprtjpy4V0RSewIbQDQSkBYsUSG3bwdM2CXXrB4sHfC+iJgN+WS2AXhGLgPgblwD0nsYKfo8Wfa+YJgbZDlZ2Det4PvP7uWzErYES6b+QPX7sEIN9Wtttpqq63WVzVJbJB5FlhyEogEUGG6YduKD50c4JCCbnzmPfjflTzsnCZr1b3zmjCeaMCdyM6LA9pGBvtKDLvkpU1g2KEEeAFbYRXV6KDbOBzDHna7giRWAr+cC1JmCXSrSmKDrFVPetVBNwTOJJAR25aZffJ6Wfoc+05k2Amy1sbACB20MIAdB+BLL8ppGwMH0jb7PIB958ewo+yPCFbJclTNwy4HmggDxDkAY0Jonh64sNS/TU6JzdunL8Ej94/L2s/LndzMKGrQON1NANMI0+SCx9/y0AgOuGnboHgBKmm9URacSpOz87DmIn0kSDlr3meEEZeEiEgSQQRdegLYTUPaT16VJDZhZ9rIQiL71/hzNlqX9ZNSqRJEIMxP/72WyFixTyBAdSSkGin1FZyF0E1dlPJC00bGYGMSnGHxefw4q8VJnxGe7rsA1CUMO5xoIJLYL70/A3ZPen9QkBlPATt/r6t52GXS5eBjSySxSTorGyNpAO8SSawH/7rGwDg5xrDzXnoB80glsQcG2NH7TMsZn5JtWtjO5ZLYXZVh5+AaLuHrv+yfgc9823cBwP373qMAdlESSza4acPDJEhi+c6TmwBNiX05xheKJ/t7bqLoYRcZdiM7uKXwCPTRmz3sUknsEq89Ywxc9i30JZplRRJ7HCfYGTboYm0yht2Yh07ANMIVMuzOcPC21VZbbfWtWlVJbAC/JODMJt/hNRQArBpgF9vqwNngZa38UYmgm8RWa8lgTGTYFZh9dFA6SYBdAPskD5PYVlpvkWFHxhzHKX9pGZwObq6xUBol7etImGBSSixKTkVgkxwnSU5bk7Vify611UA3BPIkZl/0oauAfSLDjspajxmoVwy7aAwM0MIeBplhN+nsPAAIbUty2nNk2BljoG0M2MlBJuW0y4Ai/Htg7bQpYDGZNhAi+8zDjvm/cUlq8G8rA34t34aMJVhmp/FAgh2yh+wxYUkBnOJhJwNuGcuvZYBbJguev1dNmeXHYM1FQLZmKdBIALbkfDI2JgDkoIv/W8ICIyDUoxYFAD3YC5B6wWK66OTuJ4nNJIiQAkMJK65pA2kGU1EpnpDI1QXG3MgksQnLL2z7dB6AMbKCYYQn+w4uD/N+3RypWtCDvfvIsPuiB+yu8Nbmz3HH08fbLt43cQzEGXaBUZpOkBgKlIWwB5N7xz0kdMIv682rHt59eUwZd36fXCKJxe3IgcOUYXcCYHeC52s1dMI/WL78G/+P8Jnvequ6vFI9TuhEp9yE/Um+NArDjsxgXPRNYJB9eIgX/P0ZdgIAhgw718NRYdhJ60MPOzklVve+o3W1a+PLjMSwawqdB5BhpwF2qSwXX+owannfNQkb76qZP9gAu6222mqr86kgTa2BbsLAuvGDfzU4opD0WvWhKwCFqTRVAL8WgH2jImsdCsy+yJJTQLewzbokdlC2uSQBTnyxxMCK8wLscNDaCPs6efnl6Bro2nxf2wJLbhrLctoacBZCJ0TAbpmcVgTdECg0LvGkCp8X5LRtktaag26RYZevd2bYeY8eITii5H8HEPuaJeFqWCU57TlUkHIq3mkZUFT1sKOA3SAzMTI5KPegkxl2IWWWh1bwbVA87HoFLMvADrof05C+nGZJt5XQiIWAW+Zhx95bLPewU4/BOXnY2ZxxpJXqoyYAGDwlFgDADqls+JVJYlP/wwBwkWeS8TNr4z1DJySGHZXJjtOU9M/IsJvXRQEQPO5tW/Ckoymxioddcw4edv7ZsPOA3ZVX+N0gKDZNEdcgktgvfTADdpd4avGa63KvSzxWQZGheNiFwySp+chk6m0G2D0kdGI+769fzOs8ciIYADiKedDwC86wIzhPBiAXJbEFNSSrWugE3uqk6+HUehzATrsJ+5NyGRh27KZDbgLGGNh5Gc8zP954smvvL9lkJonzBiLDbpehoSUvOqTo3o02e0gvCZ0AmGW1QZ4hetiVKcdHGjrRMcAu87CTQifiBXTRzMuZztCAeKutttrqW7WaCnCGIJRk8o9AgyaJXeRh5xrRh24osNUo6CaFP8RtLrPkpEH2WGKroWTDNTLoVkp6raz3GBh2wgsMeYZLwGpxf1dYJWnqOMyDtRFakVFhCiy5kTDBJNCt1BYmS8IuSj50ZVmrlDCbbIswmA9BGRLoRtpK0tQi2NcYGLzoxfqxqtRWB+y8XGgUrn0E+xZIfNZYAcRQUl4zoEjzsOOSWv9d+u6SLwPBKs3DzgN2PGVWTXmVffSGqQw6UiuBXJJqg6Q3WUY1dEL2sIug4/087DrOdGzT9qsGTLCIrG8xw44w4hKZtmHHA4AAdvsEPEiCOU4ADk4qJXSChkZhWME0neZhh/07kyBCClpME8T+adoAIgeGHUl7khl2Y7gmJgZuhv1hjLwIvFZ34+MrAtg93bd56ARNEPeA3d3hFp7dzPeLiy4F85NnHI45KpLYkN3DJgYwqXz2jitIYtXQCQTsCh52Hot57bJPfk+Wi8Ah2Y4J8rRael9vOZb0SJJYBOy4zRrfBsnT8dR6pNCJeTGctYYHRPWw4wffA3YfIGB3XzksgIye+hldSRJb9LDriIfdPUInAGbQL4ROSJ21LaC9fvt2wBJWWBvOsDt6E+LEw44y7M508LbVVltt9a1Yrfe/qMtaBbZahZ03FqSpMXFVY5zpIBT+bQbOBJZcka0WAUoRsIM62Dcz7PT1ltvKYN/gpa7yNg9h+dIYriQ9XmMhQCT1C5RfDtCJk6ttIcCBhiNIctpSWzrI7kSWXDTulsIfopy27EPnrMCSK7Rtuw6mEByRM926AsPOGMKwk8C+ABTK4zbrX6qtsM0NA7DOrTJmluJhl4cl4AupZ4ZJCas2ZdhpoQ8xsEGWg2ZglxoawcEyf39c6GFH10W3gU6G6Aw3xhJkwOdY8/FTPew4aLnQB3DNRYGhxQw7ZHk1qY+aBGBQeWCwWlIYdo/tYWcoiDhGKXQYN5go4T4xJTYGRAjPA+5HmYROpB52Q+JhR/olAYkDY8454h/I5MjEw67h95E1FpHEXu66wDgMXm6WPFe8JPbF9S0AAHziyQ66ABr7ycw+nZyg/4dxWwbYyWnQDcUaHJWiagw78vfJRkB7EcNu3u8kzCEw7HJJrAQchvARk+9jkTW6IBwDCzEjPXRi/l9KTT61HodhJ6XEAoSdvTAKqspOao+A3d18kBFZvlcF9JQMXpKU2PTGW/KwQ7nr7VH3sKsCdn0M1RDpzQsksTtgg67wEJgApil0HATsJn8xcg+7Cw/YTZskdqutttrqbKpx6UCLlnMOjgUQKvrQldl5EpMKwRqVcVYAoZoEOCtIUwvAjOoltyA4wmqgW5Gd59u6Nh/XAJDjLA324v4WJcCK1HNt1RQksQhKjYodcinAAdtaZ6CV5LSFthRIE0E36SUlNHbBfgWBPVod+ZsVpKklsK+jLDlJEltoCxCPYyk4QvK/o20nwf+uLbACz6G6lgNN3D8OJXMVsC0ATdTDyybSqRz0S/3fNHbakHnYKWBZxhJM9yGuP31foO+bEmiYyHoVpqEOuNV89LikVpYm5ymzXJrMgIA1Fzm2zakpsU2neNgJkth2lyi3Ug+7wjvjQ4sY+AdchjAE8VxNFLBbwLAL8lWJcW1M6Md8/3hK7FHwsGtNyphLE3X99w1h2JkULI1SzxX3PxI6cdE1AQcJgB29v/vAkpc3sxz2c29fJcEnAAB9IolFhl0cVwEIDDsuHWYedjsWOsHDHkRGJsViFnjYveEZdilgJ9iAOQrYcYYd3o+EMW/Rw265FH0XGHYaYOefC6th2PEHEZbveBcLJLEAEbB773bewacPYdiJkth5gHh0HRztlEh7FqXECpJY7Kj7vnxiL/s2hGqUJbHyID5JieUedr4dgo0NSeUL+0QGFyiJtZskdqutttrqbCqETgigm51cNBEWwC8cjI9KCENJqtlWGHZLZK33YedVmW4unaSS2upgny4fXuphJ24zgggqs+88JbGSlxyCUpJXHwAB7AoedgN0st9RIek1ZedJoNuOfpmvOK5DSKeljIRRAL9iYIXA7PPBEQAgBkfUgLPIsBPWW0i2rbVtv0k87LSwg+AflzHLlNCJ5MV/CACWQSaGc8DBKpWdxoMvFIZexhJkYFeUULLACN/eGBPIEVL4xkhkwcYY/1LL5HHacbQDOOfyF1wFdJQ89Oi+5SxBDx5wluGaC48BSYm1i1Ni2xS8FFNiCZGFEDZSht0rBOyQkUsk9I2JQG5LQcoTJLElD7v57+Q6mnLA7sleYNghmN0yxlziYaf5B0Y5cgT4qrvx8RUCdjDCvm8JYOf3Dxl27W6WUwPAze3MsPvOty4zVmbXSoAd97BLx5Mhdwf7OzLs/HNk3zaBLTeJHnYSQE2ew0sYdkESm4dOJF56AThsVYadBB5z8lXasIDVsKqGTpS24cR6JEksm73y5fxJu1ooid15QOpr1/P/iLTfq1o/iBMZdvOJooP4ElPuEgE7QRKLHeSiEjpxWQudYA9vXsdxioCfCtjhi0C8kIzhDwwLlx4Yncx5Dt622mqrrb4VC0EeyYdunFxMLxUAEgPIzpNBqMAak1hyxDtP9qGry0tr7LwHedjdR077AO+8Y7FtnPGV0hCLCbMrLEwWlSWxHnQz8litLXjJjUOU00qD2RD+AC57URyTwIp83UVZa0VO27VN6M8icIYsOQH8qslaS8m2AACjP46TMOsf/O9USSx62J3mnXcO1TcMqGpTpoWtSDmp91qYqCeT2DnYRvob86DLAxv8PTnzoKv5vzGWoCbrJee7zUC/uA0qO46sKwuNIO8d9DbXt2ZmLLkUXMwkrQpDr+PHUQu9WHNJTK5aui1NiaVebhJDLUhi94m9UdJPyPIevfz+WUJqCWxz0wYPOuucDMAoFQCKVn4nbiVAkqTq4vs2VcElfoCEMZcAqQJYytmNLU8/XWP5vrCDEXZtEyTCkWFHADuPBRyP83Pqk0/32TXXd22c4OWS2JASyzaBS8CZj23CsHOSh50goabPtAIQFjzsCpLYwLDrm0RJkXvYEaCX1yNJYnESQgudWB1g1/O4cyzfma7MIfk9rp0z7Ob/v/EyRdrvVYFhR/TeRBILkN4QljDsDkMuiUUK5kUldOKybwlDTmLYnZIS2+fLmYYA2GE09wQN7Npmnm0jg4ONYbfVVlttdX6FA2rrmowlN04uSByKwRFVxlnBh05La/W+XSIItZAlZwrg1+BaGfxawJLT0mmXAIVVZt892HnhWC14+VlDoSRW8kVE6aZVJLFtSGuVJLGRnSf53zUFlhyu9+jaaHBPqhT+UJPTtiStdeTg12Sh8awliWEHQKWpEmBXBs7w+nUF/7tG8PtL1iuBfRU57dqr5aSAjNnFXsx4YAR5YRPZaRnYRV8uFQ86zpCzNXaZxk7z91ZLAB6/Xcn3QJLVEg+74KHXpO3J97K0XcL8ogyRtjHpy7b/XsvtjxSm4+LQizUXBXqWMuwIWBJe1JmMMxSVxIb3vzFlMTJ546MWSl5JP4mkkjaVRT6Shx0AB+yIh92E7/3zvg4EAIlsxUY8LxNPifXnqUk87IgkdsV4XcqwawhhCNlxBAdA0NWHP33iyS6Tc+46E54r4fzhJIGTGXY5MI8MO+uXWZaiFhmlTRcpfELhfeg13w/GyeX3TIe4S8r049LcLIyI1iJJbP2662uSWOyLa5HEahuMoQYhdKLiYYeU/6+8nA/Wg0In0IeEngw/CAqAnT+Z0+SCXl5i2CF77nagklgMnUCGXQWw27Vx0Cp1gsoMxhw6UWLYWdh1DRgyqLZg4nZRDzsPjNqNYbfVVlttdTZlEuAsfXmw1gWgQQKSGjLAkkC346QDdmaKAzw5hMG3FWcrqf+d5Ad3f6ZblMSWpbgnt7V0vfk2HwrHivrDlGW858GwQ/mm5LlHZa1iW2TJGZe9JU1jWU5bSmuNUlyNnRfDH0bmJTcRRokYdmGirDVj2JHxpA6c+baC1AYZdm3Vh05nyWmgW2DYSUEZDlmB5zlJm0sxOVjGmV2ppCk1u+dgldUBv2QZNTmoIidt023I/efS9kHWKySEqiw9knQrMuyYh12edGuTe2TfNuwYIEOvzBLMU2ZlD7uzkMQKQE8VaAwAW5Mya0wBwGj75L2yEQGtV8ewm6gkNvGwi9vhpJRbpTIfQ1ZJHyaAJA+doB52Nkl9jdd4PFaQHKtg9M8ZdmcROkEAu64JVleBaUbl/v67mNb+1pNdklQMMN+PkEnHGXbBx5eBSQguZQw7mGX28/3BK/UkSWzJw67yDMJ+QPGfsO9+n9BLb99TSazJmH6ZzUCyk4WgT7scsKuHThRYfifW43rYsZsZSmKfgI+ozxh26U0MZx+/fp0i7fcqXNcoMOycB+z8AaY3hqKH3WCTmZDwN4jBFFpdJKETkiS2DNgN1hGGHQJ2LQDEB+O+a5NZcAtNlOqS2cAdAnZbSuxWW2211dlUE3zocpnnME0BLJDYak2BYeecq/jQUbDvNDlteCGFJgt7mrcb16vPdI4KyLjEO0+Tpi4BCkeQmX1LQydksK/A7FthmQ4Zdvn2Og9oWUUSS/3lOPiFoJQWWNESQMxlDLsI9kkvhl3TENAtbYsvN1rYRUMYdpkPHRnc66CbIol1riqJxeNYlNMqygirrRfqYN/aK8pRZf+4kTMpGFDUExZmzpAbIjuOtyfLyCWxLGG1wrDLwDLFwy4wRqecYad62E0x6TZLqRX3QW8P4IERkaHHJbXpe0sevMFCL86KYRfP72LAjviHaaywUEESSxl2iofdK5TETjbe1xNJLLmvTiYCu7WqSQBD4q6L+zeR8cyVmBJL/QCJVNmQa4oAVYnRP2EHnkXoRIehExb2XRtIREFySScCPBaA4Ugpwy7e+ywwwDXzsEvPVcYopfcgsPP9NGHYcUmsxChNfUW1il6GEmCHDDtCsCLjrSx0ggf5JDtZYtidkBJbDZ0oM05PqUeVxGYMuyCJ1QC79CYWE/Dmv7919YDBhXQyPHg3mJ3f3vlAUu2xBNglHna4D/6Eoma6yrDr21zSSqsiiT1Kklj68zTCrmsSwG6CSKels4nIsBs3ht1WW2211dkUgjwTNJk8x04uzKQaYeKHsvM4cGaJnLYEYA3Qij4+x4XS1NP94GoMu9I2e4DS3T90QgvKOAYZr9DWEq/Akoz3m0kSq7xQUuknD3CwFsE+uW1Hxjk8cZUy+yQ5bVsA3ShQKKbHgc50o8BhqzDsIujGwT7iFVVlyZ2WTltre+4Mu4wZw73TNCkm858DgHj/EhJWW8nDDpkqXBIbGBroo8c96NIJ+lzOSgA753LQUJBl6cdh1D3sTDunaZD9Exl65P2ta4zIMtQ97EZ2DBrPqE2/12r2SWssERhaLonVfNdCJSmxFQ+7Vxk6oUli6TWDHmgLJplqjKIk+CQAR/E+/MR7108uLktO3LWRYUfAPwqWNsy//ZxCJ3aeYbfjgB2djPD9xlnCsGMgbyKJDYBdHKMA5IBWw/s7eRZ33luPgq0H5h1XTkUu4w4Izl3tWrxtwcGm10Fg2HVt6JOTyz3syqETSySxp4RO5PcG51xMYF6Lh13HE5h8oST2SpXEkgPmXJBc4EDrzcsHDC6k0AnLATvPsKOAneCHguy5u9EG1mD0sNOltLSuktAJ4eZbkMRar+HOQieSdvONftfEczAz7HJJ7D4Aduc5eNtqq622+lashjwjOXA22ClMdknPERNAqJydN1Kwr8B0kzzsKDvPSDPwQX5RA78e4iVXYdgV2HkSuJm2PdGHjrQVAcqpsL8rrNbbi0hprSi/1DzsEi+5gYFfNYZd1wQmYwb2hbYK2JcAdoxhF8C+Vh1Eh7YZUEgCK1p5u6Mkll1HVE6rMezQw463dVFhISXbAkQWjBQ6UfPOW3vV/OMy/zYldAKA+uBFtUwm5USGBQG7MnYYk4PiC1vHPeQ0Dzz6HlCS5ZJ+pnvYkfaNvH66DxLgRl9uY8osJNuaAW6kfZIy25pUaubb9xxwXHMRkK3lzEatpJTYlso4JcCuT/pS7GdTsrxHL2TY+X5mDIBxEQhOGXbsuipUJs1mJXnYBUAQoiQWIL6jJ6EypM91FIAj1zyepo572FFG3lrL39uiJBYBu9R/bmbYecDO3/PfusoZdl1DGXYoifX3LJTEsnPVZUze+NzowXoPO39uoIHDotCJpZJYnyfQNgGPCcs36QTtnoZfCEy/cuhESRKL9876dYfPHCl0gt4v1gPYBW8GOSX2icawCwCeA7ADGD8bc/QDuDcfxLDDcAgqiZ1/HhsG2GEH6RpxthZBL+eI9INJYpd42PUGb77CfjFvPFqhA0sMOzbLd0Ft7aCZNd4ACbC32xh2W2211VZnV+hRKgFnlGFXmjXU2i5h2Ely2nm9daZbzcOuFDpR9bA7cZsByp59dAZalLVaXXoc2YhdEaAUmX0rrMbLRu8jiaVMMsuCFKYQWFEC3bypNme6VcC+pjHBVy9b7xDBPs1nCQFIDn6NfllH16opiIFhxwDKVE5bZudlgB150T+5LZSTbc+hgoed4v82cHYZk18ZYwTALQ9c0KSc82eMSaGBhhU5aGCysdC4zIdP8FHKQb8I9ASD9Qzw67P2NguNsHnKrQBa9g0DPISk3bCvgiT3rDzsSP9YLOUlPmq4j41JQaZQVBIb3lcH5sv26kMnnPewm89ZZGclrFQuqSxUTQKYyC3DczZn2AHEd/OErUjAwyR0goCbOL5pGMCXHNu1VuJh14Z3+ABaTeTe5r+LHsOvX3YZK7PvCGCHx4gd90wSa8g5AmAMO5t4XI4iw07wsBPuR1Lh/bUn7MIju1/huGvfU2luLol9MMNuiSQ2MOwEwM6tELBDhJHfhCd/M38ClZRYAIDhJvwYGHZXD2CAdfEGGBc8A4cYthAksQNBa4WiCbBhYHpi6MRFT0InipLYfBB/zAA7yrBLvTyekENqoZlTVACSm9YFIGD3Ch4CW2211VZbvZIyAcAyuYeddbn0gVaJYUcCK0SWXAhhyBlnczptQSJKWXIlD7sCW02Xphq/3rKc9r7Mvpr/nczOQyCqSWRmi9a7wmpC0qsDHhyBgJ02+de1TXgp4KBbAOw0sI+w5KZBltOOBW8nzUuO+t81yiB6FORidFklOa3V0loXyGnxOOZy2gXsvJIk9twZdgUpKEAEkJbISQcOmJUSVimzJAtsSD3shiz0IWVpqIERfhmRIcf3gYKGmoddQRJLWCIqw84OAQzN1i+AlhlL0AoeeJKkdilTbQ1FgR4OYGiFfcO0aZ+spcQSSWzS16ms+bELE0b9s70xJgnNoKmWiSS2cgyWethZa8P68DkOEEMeAaLPvOhh56awjYl82LThNCQJvc7Gda/Zwy5IYgfY903uYYcYQRslscigfrrvMlZm35owPnPYFqXICmCHz0XnZgXFTL/08lmw872QTKZm7LJiyMpyhl0WuNFwhl0tdKKQElsK+lzotwcQnxlS6MQqGXaqhx1KYo0iiaW/C4DdwzzspNAJZNjtk+0tJcQCzPsXHraBYXec02URsKtIYmcPu/ulxOJNK3rYRSNnPsv3pE9nRQK9mDwwUFo7wHkO3rbaaqutviWLssYcB85i6IQ4CAnyk9zDjrYtg265L5udXPBCkT3dIpOq5GFXWq91jch0GyYvTa3IacsMO329A3Ri28NU2uZo6CwChVMB7FthJawsts0IDk0LQLfMSw5BN01O28S0Vt42MPsUdh79jAN2tbCLua3MsKNgnyqnVdJaQyqua6ATwi4AACaTTsDGFRMprgK6YVvHVRrTBJ1n5mpA4dpLZ5aNyd87LoklctKeW/cQll7G0BO8w0oJrQAEVAjbkCpqcP2SzAxsDL5ouSxXkrQG0DH34SsDfgUPuwWgpy5NllJmqaQ2lSafh4ddzrCrMgMTSez8o5oSO0qSWBZw4QrvjA+tBu9TNm4nYfQlDDsKGLr8OUyr5mGHYNBIWFmoDOjbWY4dMQXvYUc9JpPUV/8j9bAjcmSeKhuP7Xopdvj8mEMnBEnsRJiZeG+BEYzx7EQG8vZNA9axCSj//1EJnUjOPbvWexihJ2EPFpocsKsB1IVCPKZvBbDSLxfDzbgk9qAy7AR8ZpGHXf262yn4F13/vA2rAexkDzscxF2pKbEUsLuNPz6KJFYKnZi3g0tiD8GHTh5EGWMCIIcvJmDHpJPWJbFNJSVW11PjTeuikSSxKePvygN2Exhw0ER2ILnJ7bxH0SaJ3WqrrbY6o0L6vxBoQFlyoi8HDY4QZK2BJVdg50l+cCOR05baaiy5AH7V2kpMtwXAWZVhV9nfQWyLzL4pY53VAMqYEjtW2QprqCQggQF2yCLTWHLGRFmrFuBQbqux5OqgW1wvB878xG0B7Is+dIzZ52WuwxI5LXsRGAcC9ikvs5MqiY3HXWPYTcyuJX5A2HlnGjrRZemkLGFVZZdJgQ26f1sEq/KUwDxhVd4GLak2Y/gpHnZ9o4OOOuB2moedlPKag545aKmnzI7J/TlNmY2gSXcGgEmoALJNqfSyVKTfjVSifC+GHQWhHuVVPS2/f5Pv6wkr0qTs45Ew4Gqy2CzAhVVIiSX3NGTZI5bQs+TNiV6fCWBH7guJJJYCdvj9iYQpFHfhYy3EP3ZcEpuFTkRJbA8jPN118zljMuq+awIgagPDLvoKAwihE/TcswmGzljY05RYl0tROfs42e6qJBYBOxMlsYxhh16LVBI7QR46kU1i0Aoy9GP+mXDv1aooiaWA3VpSYuOsS7rBU8aw44AdeWB5hp11Bia/Wd/x5tX9N0oKnfADtSkw7LxnHvGw0woBuYG8ENFOWguduOy7KIktMewEtBc7677BKRspdGJe9hO87/tjGOjFZPk7g+j6BthttdVWW51NFQINxslVGHYUwMpBtzAZVWDnDS5nnNnJheeiLBH1SY4CgOWcWwi6ySy5YWFgheidV1qvjT5nVpK1WvK85/tck/FOZOBWYSusoRo6aOVAsB9faQw7gDhmGgfuJVdOiQWIoJuW9KqBfQBR1sqlqYsYdkYGGZfIaXF/cqAQwb5OB/sMpv4VGHbKS8QUxnjpcV4SdrH2imCX7GGXhUYUJK2ZrNaOKbgCoLDLdHYaXa62jJ6Djom32ZCb9Qv+ZX1mBh/bn+JhJ4ZWqIBjDlraTJo8JM+UxMMuAQzPycMuB4aq2y0klc6ssIoJPwlgTMBBlvj5qNVgwM3ot9NkcsoArtHJjQozvO5hNx/LiUws4HMc1xdkhpKHHQGDwuWeMOy6mXGH3yfsxm4p8Pox1tEHh/Uwwo4w7I7jNMtT6WRCYL1ZeO0ivR+F+04bMZURfVX9MoKfruJhBwDhWCJ4FRl2UYqqMuzE/l4B7MZoT7DjclN/LttEEhvHW4N1yTjR8okcaRsfSRJ7RqET0YzVkRnjANgFhh3beWPiATnOgB0dRNG0mJNLDJ1IGXYjY9hJCbFYEbCLklhEc7vGxFkppS53RBIretgJMzC+8KZ1UUqJ9R3sMjDsELDLGXYorR02ht1WW2211fkUAbD4y4OlkljBC7XmYWeL7Dx9vaOdiIddGTjjs5A07OI+7LyivJR62JXYeUVwU06JvZsWAHZOYdgRg21RjrGySkIO2DkKktiCdESTptYYdklbq7QtSmJl0A1ZcyWgED/jwNkpYB8/t0vktBMDouJ657blsAvFB3lB2MXaq+Yfl4NdAlilJqxS/zce+FACq1L5chYawVgayKpMGLtJaIQGOi5jCeay3pKHXe4FuEQSW5LU5imzCwDDNZckvTxBEhtAJgN1xhEJHUzO8SuVxOK9Nb7HclYlAjkD0EmmpQw7DbCb/7fkPoU+p0ia4Qw7KwJ2NkpcrUvYgen3I3jU8OtnhUUBu7YxCRnoaCdIwmiITPUpAnYuvT/1TRPGhePIPexkhh09d1zC34fQCeJhpzLsHpAS2zUzgw4Ajja9DjB8jUpiEfOgARhlht0jSWIXMOwaA2Kg6an1qB52AOmFMPkBxKUWOgEQD5pn2Dn/+w9/2+sP2ygxdMIz7Dz7DoEwPMHU7JIXfjZQSeywLHACYPawKzLsipJYZNgJgB+TBlzh858Ddm0EBHsXZ3q32mqrrbY6kyJstYnJKefQCfaymLSNAJbsYcekUElbwjg7mdkXvfPktrheaeAUgRm+vwDLgiOqwFkl6bXkYUe/y3/XwL5i2xVWS/zWOPgVGXb65B968uSgW52dNypMt5oUl37GZa2ngG45YBdBN60mZX8pYKcFVkwa2GfjNmttHXpSZSzI2Mfa/jwnaXOgKnqnARTAspIHHRlzRzmqDnYFlp/g30aXqzHsxKRRIqsdOGgoeNBlHnYCYJZJahd52MVj0BZZhgpDz45CyuwCWfKai7DiTmbYNZxhJ7B5RIbdmMq/hX5435omB7fH3FcQ71ONIYCdSYGcyZH1VySxE78OWAWG3RiPBVpM4L4HX7ARPewIIE/ILSH11aWS2ITllzDyyPdXWjguwZBJqvw7jBNj2EVJ7GsXKRZAQVcEswKrET3s/HFvjA7YBeKsX1cHdiY3kcnUZaETyySx1MMOSVQhIRftBQAxmzYAlDj2pcETxQCURsdcJEsErYqhE66w/nvUI0li42LozInldEIJsMPveA+7/X4P/8t/+Afg3/rtv+ZhGyXpkxVJLHY2zcMOIAJfxyAbGgLDrgT0YV32LfSmJInV0d4QbIHtRUkspsTiDUln2OGNAJH8rbbaaqutzqD8AGgS0kvt5OKEUgE4k0A3uxR0q7Dk5LYR7JMTZpcw7JS0Vi8vvQ9L7lBsG8Mu7suwG6ATU2IPJTntCqttm9CvRh7+sIBhp/nQheThEmAX2qYyT7dAEov9igdHRDltnZ2nAXa2APYF0E3x3RugBW38rnnY4XqHov+dMob019/g2qoSZK2lsuMQyFTBsiUprzZ/sZM87DA0QpHl4rWuSUopYBeUSARMyBh2IkOu7mHXZutfIqktAH5Egq2mzE6jnjIrMPzOwsMuYXL5H6spsbkk9tSU2JaCso4Bsw+o3/fnPw8//H/4c/B3v/xh2EaAGDrRCZJYBLhGChUs9rCT71Oyh50H7Hz/7FEGyhh2XUniqoZOkPPYrl8Se/Dv5Tsze9xS5d9hmNL7CqbEGjsnxAIkTEMsDCRCH9UgifV+uhxcpZLYwMYlkthdFxm0kx9fJWMd31+/9N6L+LcTGXaJhx3z/cQ8AMqwc4YlypJtF8HjNn2GJGXzyQatdoENmvepzFv1gfVIkti4MQO5Edtmn35RQivxoHmGnWl6+J3/8C+F7/vU04dtVEiJFQC7lkliPfC2LzLsvCQWZ+XtEJDcEtCHdblrIsNOlMQKFFJfgSJaksT6dpeBYTefk8sMsBugg83Dbqutttrq7Kogax3sVAHOKIAleNgtAOx0hh2TkinrzYBCG/3voBIcUU5rLctpSymxMlCoMwoBAAZ6+PjxCnLNcjqt2HaFRZNeKSsCAOK+Fhh2Vgl/QCZYiWGnyVrdAlmrzuzD81MH3TLgDAGiwnpDWzZz7wLDrlPlMQh8mkkD+3T/OyexeCAeq5IUd+2lp5N60JdLnwpy0uiDFwFO3X9OYLcJclKAyLzLkmoDw44QG4T9wHF+UdarAW4kZbbkw5cHX8T3B3X9QvsAuJHt1yW1fdb+PBh2goddTcpLJKwBNKKhE+AiZYkyjgQPO0efpeZhr+p3g4X/+1/+WXAO4N/5z74YthGAMOyEwIIAcJ0gic2uRecAnn8lBCwFj76wfwZsYNil/w+ih108Lw1lzFGwVPSwsxGAXHH/OyRsxhGMMWlSLAXSfb/ZwQhP9gxDINctjgvz0InUOxCLetoFNiJOPKAk1qHag4FqAAHP+P/8xz8b+1vo7zXAbl7fTkyJ9axBmL+zJ2m1TYPhHEQSa1GSKgF2ggoT6x6SWIlhF7wUH0EOC/BokliFYddywI79DkAYdjf+O4/ksSEy7GYWn+OS2AXAG7LoEP0GewyhEyWgL7YnHnYnSmJxO/dGAPwyDzv/qz+1QddObnKdQ8Au347/51/7OfiX/8xPiC8aW2211VZbfYzlIoDFQTca/nAy6GZrLLkoxZW888ptkXEmMezu39Y5tyhhtipNrYRdSCy5caL2GHKip+a7N7ro2XMOgF1HADursLdKA9sQ/qB42N1HErukbY2tVvawk9u6BQw7S2SCyd8X+O45Zb12WOB/59uabH/jNaSBfWuvDChinmBLwC58Tyl52HWZh11BUssAuzxpFsfrHrAjLA8JcLMVwI9uQwDcEsBMYbgJDLkSw660/gCkhPZRcZSnzEqSWha8seYSgJ6qlJKwCpPzYYRJGnw37fYJ2yf2dSpfbeH6MMJv+bf+Gvyjv/8vw9ef3520K19452X4+c2rPiwTAMD5MQVPiQWAFOCSZI5C4bgkgCQ/+nsB/vVfBvD5/yBZ5kRYTLzvaB52SeKuIx52id+f7mG3OO33YyxMkQeA0EcS4EpJib3suxkUFXwPne9/Fifc/LFHcFACtOKxwj9ENl/qYcdkqwCRoQkT/O//5N/166zLTO0UQyP6tglg2IGFTnQwn8uOAIcYjkXluXRZWT2yJLbkYbcqhl3bmEDxp4Pb0TDwTWTYpZLYJTG6yzZKCp1Aht3F/Kt/SC8B3i4zSewY2l0sYNhd7bpA4xRlHMTL4l//Cz8F/8Kf+rvhpoLI7S4w9MhxZUDfJb5DIGCHqDu5eHfTfLM/uPR8/MRXnsO/+Gd+Av4ff+3n4M/93a9V92mrrbbaaquPsMggSfawU0Ak8jdJ5ln3sCsz7JZIcWeWXA4y4nqLoJvL204uPudk0I1us7Be9L+bxjD7z9sO0ImgW1FCXEjFBVgAUq6sGmPCcc5lrb5PFdLUAkuOecnBAtAtSlNlKe59JLFL2k5BLpauF5luixh23DtviKxNta0/jjnodghttdn6yLDj7Ly72PZMAbvIuOEedilY1mdgkQS4cbBr0NlhCeCnsdtGcM4JgF0KZtNjHxlu0Qdv4JLSYkqrLqnNPfBywCwDHe2QA34SSzGTBcftz+RfgqwsO49rroRhx467VoHlFZPJW5oGDBABlSR0wr/TTUM4Rglo33Twt7/0DP7Olz+En/r6S/iPv/DuSbvy/DY+Z96/xvOK98f5MyklNtnvQjAiLezaXWtmtOev/CvzH/76H4h/B8IgbFrgCcXcyF9M3J0YYEf6ezT7Zx52Z8DwvJMAO48/HAbuYRdZb1e76OcGAMm9DyenMoYdSpEFX9RwbP3YCJ8vPdj5/DApKgXKcOKpBRvl/wsksRT06rsGdh2TuRIPuxDG4bfD+M8o023g9/VkBwuhE6dIYrlsly5mjYAdQHwQ0ASknGEnedilktglMbrLNsiv203xBuNBwalDDzuUxJLEEaXwggneNXYI7ZZ62KEkFn13kvIX1+3dHfyb/9FPw//7P/kF+DveayBsXyOgvmyWj6fEPt336feAAHZs4PiXf+qd8POf/3sbYLfVVltttapKmF8l0K0MYEn+d/cG+6rsPJ1xNk4OrMZUS9pqICP635XltKW29Lt8vZKs1TlXlhAnnn3CIM5SCfH6U2K7xgTmJpeXIrDkSoBdALC4VHNBwqyR17sI7NNYcgsksaGtBvYt8bBj/QIBy7GwzZqsNQRluDaRK6VtPdjH2qZy2jP1sOPMLAI04fUIIPm35R50kWEXX/yz9gJzFIGwXE46JveXPPgi9bBL9oOkg9oMNEzBE7psieVX89Cj+zcyTyjKMmyz9RMPvJKH3QnBHeflYXcPwC5hjTHAjjPsktAJKoklzyTTwrPbeC/68Oa058bzu/j9968PYRsBACY/2dUaE+lUImAXQzhKlfTj62/ED976JckyU4ZdKueORv7zMYyJuzIANwN28zImAmtw/8DA7ltx6MSdbWBy6TW8p6AQBdJJSuzVrk2fG+S6c+H5jYDdvAxk80mPhcAqtQjYITg4eobdvCwE56gU9Q65RWaKkyihv+tjhQSwa03wh8sBuyniNR6kbLp8O/CeJjPs5Gdt8rdFDDuTbiOpKM1+nOfuoz29e/4gAIAx87ArpMQeH1sSSw40dhQ/0+i6mWGXA3YFSaz/7DDlktglKbH7rgmS2ESjzrb3/Rc34U8/9vPvAwBhAJZCJ/yFGD3sFEksAPTTDFweGcPuSx/Edf/MN17CVltttdVWKyoEsITk05n1VZgFT/zg0sHFYF1ZppmAfZL/XYmdV/Cwq3rn6R52adhFObDCCgBlCtjJ3myyBNiFz8S2hXMEwP0Cyy8/a6imMdEDhwFYARxaArpp7LyS/50KnHnD60WSWCUoowSchQAHBjKOddBtUgLElshpI+imJMzeA+yzIbCiO3uGXQkoot+T2GU52BRZejpDr8Buo3JUcn/pWjMzdtk20GMvAm5ZcIbEcNMlrXrwRh76kHvo2fBMyEMvCh52BDhFNkuWMtvmx3DNDKdQQUo5yQm/UlFZJk39bYRnTRI6kbP5pgR86eAZAekoeLekXtzFZb330q8XWcK2IIm9B8Mugt8NwN3z+MFh/jmXxLYELEZJbCr9FiWuHIBDTzUXYY2GypGnMb9+VlgHO8EAEWcAIJLYwabXlccC9maEy75Jz40QOhGewRNiEehht5xhF1JiGRuTprPe4CbCBIdxmsEsYQKBF2Xe9k0TVI8BhAthKA727F4dPewIw477eiY7WGDYLbD6wNoVJLGxX1cXs6gen2FHDvgiSWzmYffIkliAIIVFhp3rLudfQ0osSRxRCll0gWE3jUGzvQSwaxoDnfEA4SShvfNxOBzi4PKnvj4nrOB6MN1VDp2YP3ttxxl2uSS2tzNweceAwy+9HwG7L7zzctU3ta222mqrb7kq+LLNklh8PpXYajIIFcG+09hqVQ87An5xKVQCXjmrSlNlht0ykFFm2FUAuwLIOAbATlm3JdssSL+qIOUKC7eXs9VgmscrU2EQPimJq2GGvjAo1nzoTvOwk5l9RTmt36YsOGIR2CdLU5ek0zrFVycw7Er+d0pgRZDiuvP3sAuTBW18aU/YbRxwawV2mQQ2qXLOAthF2WlkAqSl5v3ke8aYuAwp+IL76BUAr1xSSzzoCrLejClG3h+yYyBKajngJ3jgFSS5i5lqayhyfpul202CD1IPO/qsWRY6MdH7VtPCs9v4bvihANhNk4M/+3e+Cj/zjRfZZy8ow+7mmOwfAoNVSawpTMqRCuCaMQAHsi3X7ybLDAxCcqwQVOe+YMmxpKETgiR24oxOAryeRejEOEV/eY9doDQ097CL1/aTHhjDLl53AbDDc+eXcfTjJ2kiJ9wK/bHCZ14PdgZUGbhLmW0H66W2nqT07Pa4SBKLLLWuMdA0EsMunlu0YsT+GBl2NCWW3ZNoSTkHWAvARawloROPxWx/PIYdQ8QBAIZ7pMQ+miSWdgo7zP/wZsQlsRg6scDD7o5QVe8WAH20dp4hh505KX9xWZKk9rXn88WK6+mRYdfpHnav7bx0wOmS2M4z7O6m9Fj/4ge34efDOMFXP7yFrbbaaqutVlKe/m+hzQyw7TQt8pKTEmaXe9gJbS0FoApAoeBDN1qyXmndif8d29+lUlwnp9PaZL0KSw46kMI98LP5DzIQJQGFANzDbv2SWACoM+xKRtIhrZUNjJekxCqAXWhbZPbdH+wLoJuSEluUxCqhE0ESC/qxwvVyWesSKa7GzqNgnyanXXv1miSWhB0AVBh26jLGKOMrscNaBWxjDLtZLkbOgbSMLDzDFlJWqQcc34d4/xsYS6l0DKTgjRxwyy14Op6WKgZ3cIZgfMnuuYfemosG9S0G7HIftRk0ahKm17wwyrCL73FdBmg1AMYkMlhJEvv7/vzn4Z/7o38Tfucf+/HsM8qwuzsyqbXfnk5KiZUksdXQCb/frQE4fBg/uJkBu+BhR44V9n1cH2ctWcrelMJAJhe2PchJcZ8ECe2qQyfGKYaHMUnsYWQedg0F7CLLEABSVqfvey5Lic3Zv1jchiB42Bk7f8Yk+xQoQ9uvBua/fXA9nCSJxfvEnoNh5F522flzGEJTmN8dxAmeXmLYFSWxaWBQqXqBrBbWj16Ka2PYZQ8CABgbhqT2V8IW+ANyvJ7/74Qk2fuUMWTW4hhDLQAAAsMulcSWwiOQRXc3xofZKZJYAAiS2Dsrob05YPf1Dz0Tzq9HZtil0prX9v4i86c2RD2TB0bn03K5h90HN+mA+kvvb4DdVltttdVqqiDzrIZOTDGlMmO6PcCHbpam3p/pZotMN913j0pxDUQPm+XrXQDYOckr0PnlKgBn4VhNk4PJQTnNd4UVAhwYCLXEw24K0ive9rigrQLYLWHYKSEMkWFXCn+Q2+I+lNh5GnC2ZL0qS25B2AWOpZusLcppl41T11gxHVWQs5LrM/ewy9ldYRmEHZYFPhQ87EpyVmOYtJAtIwO8kuALlLSi55ME2CnSYBtBx/ByWvKwywBDuv6Sh15JksuTerF9geG35qJMrqUpsYGh1qSsMIA0ZdW5FLAjbE/sZwHQ8u1qkth//29+GQAA/t5XnmefUYbd7ZCCcnhPbxJJrGdeUUCMpK2WaqL7TSWxN7PFUyNIYrkkPXjY+eskAYMlDzsqiSXP9YYGftCQihV72M2AnSKJHW16XyBYwNN2Al0S6/EF5mGHYxiZYZdeq7iMi8bfOxi4S1NiB5TaesDu/esjmQQpMOwYwLZXUmIBAK7wtoiSWH8vTSWx7J5G67EkscRf0Ll8vAcAalDUqfWIklj/MCSD5kwSKwJ26GHnAbvH8rADiOCfPQT/OgAAEzzs5oO5JCUWJbG3U3whuguS2GWHsfMMuVsxdGI+DpQG/bXnCNj5TlyUxM7Lfsoksa/t++y7HYZOTLEzOufgpZ+F+f5PPwWA1NNuq6222mqrj7lQ9iFIRFOppe4lNwgedsUQBYAE7LOCh92wYL3LvOQ4k4pKU3OmWxnsI+sV2jpowOJsfNY27m8esuFlOhqbkYROZOv1AzrrFLBvpRVS5sZ0Ug+BpfuBbveXxOIxdgX/u0lhycECkLHGsCuy8xq57RIprmvl4IglzD7nJ8jztnXvvLVXBIpyOStlwC5JeR2F0IglCav9gm3IAh8AUh88LiktMtQESWnG8stBw1zSWgLcaMprneEXQM9wDAjLUPXQEwBHwe9pdRUYcVPYpzrDLgILlnv6UcBrsgBAQFvihxhU3UyWTSWxz25yGR+Vu3N5Hk2J5YAdPoO6xsSUUS6JdS5htmmVBcBQSaxX0QUGIekfXI7dY0rsWPCwcwSAsy5s+0TGBC2VI08nhId8jHUYLAHsPMOukhILAPCki7JgME1C63IZwy6OBQFkwC70QxyzZIDd6FclSGIZw+76MC6SxCKJCkGwTG5KGXZ4mvE6Q0nsELcj3pd1GzJR5XCCJJYGWkiWLwDy8b1PPWLoRM6wOxrGltsJgF3LALvHYtjRZdshAnbdBXQsMnpR6ISYEouS2GUzl6jnvhM97PKB6Ye3M4sPAcUO8kFI5mFHGHZtY2LoBP2urxsSH30Yp9C5ftm3vQ4AAL/4/gbYbbXVVlutpgIIlUtEBztVQLcS42yq+N/F9YptF0hxH8R0W5T0KrfV9nderiKLSMC+HGTEbZq/K4OMIivQsrZnkBILACr7snF1SawGukWwb4m8VAmdKLZVwh+mOnA2NUq/sOjZd3+WXAnsg9CWS2KP1W1Gxlg4J2y941kDdpzdJie8GoOyPgZoAWWXCf5xgeHDPeyE9hlDzwr+c7I0LTLkGOBlJYabJElloKEQfFECLTOvcSm0oonvOMk2km3LJLk2Mh3z9oVzsOaSGHYnSGIzhh29p9hDbJOlxCLDLgXWbo6xT9GfsSi5h6ulro9EEjt4JpAHshA4a8K1E9eZAMxNHbCjh2f2sCMMu2lM989GcImzQ7PQCeoFRo5jxuYESMYTjYG43c4uP48fYx3GCY5OY9hNEfhqegBjwljisrXxODA2tePPYJwA8uM2yduUy+8jw86vw6V9JZXEIsNu/s7NYJdJYseUaUnZa/O64n5lkti2Tb8LkN8TaeH92+pj1iUpsbsEsEuB8mmtgF3HZ68AYOCzn0sksY/JsGs9+DceAIYI2HF9/LLQibkz3Nr4ML07IXQCAKBFwG4U1oMzq2xw+f71MaynC4NjPXTiKT6/oYG3rnZpR2Fo8R1h2L08xE77Q599DQAAvvTBJondaquttlpNkdCJ3MOu4iWH4Q+Sp1uVnRfXmzPOlrHzZP87DropHnbKNi8F+zTQTZXyJh52iiTWKPtMQjYkr8B5vecpibUK6FaaiZ6Eycj5gxMYdqw/RynuPdh5C9rWZa11hh0H3eAElhyXtWJKbsIo5RW2WWHnnbEkNvOPawVmFweqAFJ2V7Dt4XLQMfwtY6eJ/nMlsEuQ1BI5VAb6LdkGSVIrBl8wSW2B4Sb7+BHvsaQ9BRw1Se8Iugdf3n7NgEmo+3jY0ZRYztqkYC7186QedvaYM9AMpnDGZ+PtkD+jnxPZa0iC9XVgjLvDOIXzgsCgmBKL8lUK2BUksUn4SssYdgAAw01gbpUYdrmHHX4OSZ9HAI5ukyWsMWNMAjQuPo8fYx0LktgjlcR6wAm/e9VM4jUPAOBCwIg/Tv7+VGLYYXeN4515mXsmiTUtAnY5ww4xj9vjGAH8RZJY9LBj7D0Tx3tREuv7r/f2p9Lc7J5IqxQ6Idy7tNoR3IgzW3GM3q4tdAJvxAO5EAZzkX5JAuw4w+5RATs8IQOA922D/jIzCYwMuzpgd22pJJYBfc6lXnmsAtpcCJ0w7Gb4/vUxdNYOhMExMwK9wM2DZqahJutIO9+dI4Cdl8M+2bXwXW/P5+lLG8Nuq6222mo9VZCI1mWtEYSSPOxUiSdt62TwKwG+lKRXjWEHYHTgjIBf1aRX/iJBwU0FdBs1mQ/1ClRCJ6JfoMbsk2XLuD/0u2uvGODAGHYLZqKtkpqKwNISOS2fyAzptPcCzsZ6W1VOO6afi+stg31Fhp0/jo2TpbhjScYb2jJ23nj+kticHRf7lOUsikSOmktaY8JpnrAa5E2Ch1Ee+EC2QQutYC/O2TJK2yAl1WYMNwq4aYDZAg87OwRwpOOspYWAXy7JReN2af3rBUxCEYBqsZSSHDOdYWfzPppIYrEfpx6CdwSIuGUMu8NoE9bd+9dlwO72aBN2JAAUU2LHySXSUq3oo7LjklgAgOGWMOzisbIMWNE87NqmSQC4DNwGAAseLDL5cV+c9vsxVuphh6ETJNiBTZLhdy+6KTt/oZBNacf5JLl04lDyWAtgLZPE7pFhh4AdSmJJ/8RgzdYznW+OCxl2zMMuk8QaE5l+yLDz515m2JVCJx5HEts2JiTqHgW7mPk71cUsqkcMnVjAsJMkscHD7uX8/yuRxB4Jw24fHnp4cGNKbEkSOx+qmzEOCjKG3R//ZwD+Lz8E8O7PyJvjB1JhGbSQguxBvc+9PQdjfHBDGXa+E3W6h50JF2ITAyf4d33dkPALZNg9vejgcx6w+8WNYbfVVltttZ5yCNjlcsuBJq6KNH/d0y2Rl9ZCJ8TwhxJLTvfOy8EvzcOuAhQW1ltm2JVZctJxrjLs/O+DyxNmA1BYCulYYaEvEGerBWBpgR+cJom9Dzsvgn11hl0uWV7CsFOkqQvktIHpxoEzBOxKRtaqJNa3LYBuRmPYhcCK8wXscg+7CHCgn1rL2W0ADCzSQyM4w6fo32aFbRhxGzi7Le3beUpsfDHP90MH3KTwjWwfBMCvVz3wrJASm4PxuYcdBS056Cn4AC71gltDCdLLKtBIPMQsPx+JJJb4eSUBiQNJMk3PX4lh9yELoaB+dwCpr1doj/fWhGEnA3YTDZ0oSGIThl1jEu94AAAYbgUPuzYDi3uFYddRDzsC2DmyTaNjQQrUw25peMjHWIfR5gy7nkpiU6Yajr32xmbnD8sF+bNNxhwjtHP3Exl26bWKEz47g4Cd97ALDLs8JRZ9+08H7LwktmWhEwAweZYdkpOCJDZ42BEMit/TaAV8iI3BnAPJjqBUvL+GbeUs2wfWI0pi8w0+cA87kWHnO6Y3pHx1oRMefOouA1qND1lksF0UGHZPdvN2Xg9xUHDjfQGe7Nv5IvqJPwVw9wzgz//v8gU4B603YLyVGHa+Y6BP3be/MQN2718f4c5vXzulFyoAZJJYvGD7roN/85/8Nek62EDx2sXlIGD3ZN8Fht3XX9xlMzlbbbXVVlt9TBWYbopEtMiSKwQp1FhylspLpfCHujRVSqcNA3INOEuYbpIfnNHBr4qMFyACURpQKDL7LDO3Lq1XCNmYPzs3ht18jBH8wQoMu64OuvFjjIBWmWEnW4UYBRChFZbLB+RLGHZKSuySkA0V7FsiTUWWHG87LgAKFQ+7JTLetVcXgCLBOy0Diqh/XAEsIiBJxk4TPOxw+Zl/G0BIX8w98NJzHUMXBIac/1tfCL5QwzcIQy+TxJZAy6K0WGAZqgw/K4CepaTeMwidEJhcUzUlNjIXiymx3ICfpAVnDEmUxBLJ4R0H7G7S+xT3uOPMnzsC2IG/X3QUsDMpYGfdMkksfUZ3TTPbUdEabnOQjciHEVjpO99P/Dt6wt6setgxmSfZbuy/04oB48M4wZEBdhG4sgRM8pJYr5Tbw5idP6wgibVDBthpCaZdkx6rwLAzaehEI0hi7zzGgaETNwslsdXQCQBw/vxetMiw8/duD9gdLQFvEQgWGXbKhJ6b8u9Uase9QXH92G8fx8LuMSWx+QzEbfta+iURsPMn7/AqGXZDZNj1F1lU8N0Cht3Vbv7sBQJ2dgg3xatdB/DuT8cv376fL4BcJDeD3nk6mODJroVPPp2PwwfXxzA70gYPu33WLgJ28/8//B1vwz/4/Z9M19GlF8qNjQ9ylMS+tu/grasePvFkB84B/PQ3GKV5q6222mqrj6f8/X0SPOwGS9Nayyw5ntaa+NABpIMW0tZCk9hezOslEg5p3RWQEYCy1TRpag6cVcGviowX96fWVvOwi4EVsjfbIHrYpYPf8wHskI3BJLEOZ9n1QbhT9tUIL/RZWyX8YUlghRb+ENsWtjmktcqS2HJwhNI2JNvWGXYcdMO2UwHsMwrYF1Jiz9jDrkWwTPJOy5hl/ribVvSPGyQPuxPYZRlDDwDG4ZhuQ0USK7L8Mklp+mJO2+fA5bAMcCtJWvE4nuJhR8B4HhxQ8uA7L4ZdBOyq6bZEEms5Y5KmxAbwok8/s6MAaM2fUUnsYF0CenLGXSaZHdLtvh1slvraGF0SaxdKYumzsjGQ+4MlgF0EJHnfRQAkPC8poC4w5iibGZ/pgTRGgFf0vFuzJPs4TjC4eF0DEIbdMJHJgLnvILi3K3jYJX6F5Lk0QqsGIvBjhfYhOxY6YYT+efBfuWioJHaBh10tdALicwyXHRl28/FIPOxwEkRCzCg+REuxVCgVphrz+8PEnysPrEeUxC5IiRUBOwyG8Ay4hRTERYXLtseEYbfrCFpN/i952D3ZzyfuOZ5LSxh2uxbgnc/HL7/4Wr4AcpO7LnjYdcbCk30Hbz2Zj8P7N1F6204CpZQPaDUNO0By/A+uS9JqMUXo6UUHxhj4oW+bwdZ/8U//RDZ7s9VWW2211cdQId1UAqGmCF45q3rJjdBmoFuW1qoEBGjy0iLDjspLNQCrylbLmX3VAIeid54/jia+lEltSx52TgMZC/uLgIMqAV5pRUks97Cbt98UZa1llpwrjPk0plsIrCgBhVrSK4Le95DELgqsUIAzWMJ08/vDPewWseQa2cMO11sEGVdemf8c6Rd62EG6v9k7igBWZQmtAtgVXspIv40MO+aBx/p2BvqJHnYFDzlkuAmS1kWhFa0GWhLAreBhl3m5LfGwO9eUWAEYqm52AYRKUlaXMOzCu9zcp+4YCEdZdtyjjjPsKPsptGWpr11rsj7TUoA1fF8HLS3pA8aYnGE3RkmsIevi11/0sCsw7MBB49leURJrwjkKTNOEkYe7sN7+dxBDJwQPu7YHOzk4enBvZ0b13ueoBy0ZrwzQygmqwNiVADA6lMSmoRPoHUf7GKoIL/1m3D7Qw46CcJMfa3IPux4BO3ItFCWxSoq8ZqlQqp7ZrGFhv30kvO7xU2Ip6p/NorTCgIEz6trHZNj5m+F4iDcOgWG3JHQCAbsXx/hAv/Yw8tW+A7h+N375xVfVQTwAwLU0QUEksU/2Hbx9NW/7B9fHAAw2kiQWU1OYJJamqYTqL8OPd7BLztWLEDox7+dv+J5PAADA57/2QqaTbrXVVltt9dEWBaEyeSn3kuNARcHDLktrXS7zzMC+opecDH5Nqh+cLk0NbQNLTluvDrrVZa0lDztZ6lkCN9H7adLAvpVW2F62r8j6N90S4Iz73yGLqeBDpwyqmyXsPCMz3ZYw+wL4lfWL5cER3MNuCdiHxzGTxC7wv0OGXcvWG1JivylCJ5gU1E0wWgQc7g+WqUmzAtglMezsMCTr0EFDxYuPhD5kTEEJNFwC+AmyXhVws5Thhz6oucdk5sEnMB0zlmJJUrvmEj3sKgw7KSU2AEeSJNa/75J+gN5hk00BzzsGulFWXcagO6b3gDx0Ykq3BzyjiktifVcaE8BOZ9hZDtoWGHYTCdXgoHvwBBt5SqxJGZ8+1MAIYR8hQZY8azNJ+ArrMFAPuxm32FOSEbkuj2Mct/VgVcKOSfqefw6BAQeN6F8HwPwLgTDsgoedZ9gJzLa7ANjNba8XMuy4h92eAbcAcSyyxyEnAs4oiSV9vRg6QUDypGj/XsiwC8xnNlacHLseHliP9gSX4pLHycHkDDSmcHFwwO6VSWKJh12fpppEwE6XDDzxktjnRwewBwA3wd3hED+7IYDdNAJcvwPw2mfTv/m6rkli9y289WTu1O/fHOH6YKGBCYzXgyfHiBuBEg+FrAjD7hb2yU2Lhk4AAPyO3/T98Es/8xTeeXEIYOVWW2211VYfYxHgTGK6JaCbHdKXVnxxV2Sey8A+GXRz0MAEzexZovrQ5evFAVoEsOTBUynp1ZoWwEnbHEE3VwqOKLTVmIzpNp8OMp6fh908Bpg4w84zwUyRJSd7ySEoZQrSVC2EYUnCLAKBGUtuqoNfTglwiKzAe4B9eP2V9tcvl4Nu+OJbAgrxxall7LxFMt6Vl+qdBgB2JB5cACKziy4jMOSEhNU8sKEg5ySfoey45IFHlx9DI+J9QA19KKa8Sgw3Xdab70OJ4acfgwhaCrLidgHgeE4edm4i4EWlDZERL0qJxXOD9xPCsAv3HjM/gzgYcHckAAmTxOYMu+gNdhynJHQiAB5iSqz3Lp1cKulVyvJ9zjzsbkRQm/fdnhGAVMDO5Mqy+F0Iy8f1ha656tCJCY6QTlQlJKNwXXdJQMWOethlKbFoaWGz+0qVYRcsQDwwyEInGiF04tav4tL7zN0eKUi9wMMOAbs+97ALDLvW/82f+67vAWBImH5DYG6WQifk5+W8cws97Do5dCJJN36EekTAjnkrwHyii2AdgMCwe1WhEzElds8lsf5mh51DqisPWh1cPGSH49wBr3bdDNDRevl1FbC7GYRjQlJir3YdvP0kMuxeHkbogXSikiRWMZ2cF34Rt8Htw+wFQOphBwDQNAZ+86/4tnwZW2211VZbfTzlCGvMcRBqWhT+MAgedvXEVZ80WfB0m0wLjSOSDbbeUlprZLop0lRhvYs97KABrmXK16tvc+7ZV2MFIqNJYjKStk5Y70orpsyl+xoZdvWUWM50C7LPEsPORECBlhHAiGy9FbCvFFiBvjyGg1/Bh67QFiWxmQ+dB/sKwFkTZK1coYFtS+tFOa3Mzjvv0AlFzgoAdmT+cQJQBBDDHDKGnB2IdIqBCYqHnXNulvyZFsDZIIntCmDX/DkDzCSGWkESm8t6KWDGpcF66IPkoZd5AYoedlySS7ffg56GH8Nz9bCLx7bjQKlW+Llpc7ZZ8q6G59+/75JJjQiSxfNPAbknuxaujzZl2HFJLAPw8B339Yse3n15mAEQ7mEnpsSC32+XfV+qaLKvMezu4vEgIBtnQkUAxD/jKZhNAKbGpaANmDawmgLwTUInOGtsjXUYbRY6safhC4RhdyAMuxZISix//6cgfvBwZeEcrEKiLgPsAsMOveMKoRN7vxmJh10BBDsGzzlMiW3jfvvC8d4ePew4w46AZiOfiKHVEIadc9HvlN43lUAOXhxgDtuKDLtHEik+miS2Dd4KueFfueFHwbA7RoZdfxk7v00Zdhel0An/GTXXHgYE7NpUEgsAcPc8/d131qNr4XYQbvp+W3sY4cmuhbe8JPb96yNcH0fYA9VVF1Jiix52VBK7j9HskDPsttpqq622Wlklnm4MOLNOD39wLjwbRE83OwWWXNaW/D4KElG72EtOSGuthTBQhp3Cklskay2AjKW2JTltkBhqwKjrhGNVWe9KqyqJLXnJKUy3ZgHoZloZ7Aty06KsdSe3Dey8033olrSNwREy2Fdi9oEiaz1FittmYN+xvt6VVwaYkD6Dkt8MaFIlsZydZsO9JZPVCimzADnLbvKS2MiOk2W5Ie1WYPmpgFsrAW5C+wzwy6+RnrMM29L6ddByKDD8SoAjvifySZBVFtm3IFN1AK7EzqIgFAeBg32R4OdF5HlBQRvucW0C2L3p3w1TwK4cOoHvuq/597vBToQxN6+nFSSx2J8nmhJblMR6gCRoaTnD7lpMweX+h9TDzjmneNgBtCyxNJHEBobdeUli59CJFLBL0lLJveUwTDFojCbAZqEThGGHkz8esFIBOwbuYxBGDynDrhUZdnMbBNVmoHEBw84vo+cpsVYA7EJKrPVt/HYQfCVjDSc7SO7NFIReMKHHq1dSYiNov7bQCcFM1DoHv3/4rfMvv/XflhtmDLtXEToxEIbdRTRwHOabwRIPu6YxcLVrE9nQ8TjfjK72LcDNe2mDuw/T38nLA0/0mVfgpRAwwdWeMOxujnCdMewoYMeitksMu0QSu0teJhCw2+SvW2211VYrrQlBN9lLbgIyMKEDa/LzCE3GFCgCWM4Vwa/IOGP2DGzdUjrtwzzsPFC4oK0ma7XaNluyvwpQ6LQXGBsZdlrYhbreldakAKpLGHaUhZP8OYB9p7PkloB9ASh0vK0MpkjbnPnQBXbCAoZdBvbVPewabAtyn7qPh903Q+hEKaEV/eOywAfVP46z25YFV9AXW+4hh6Bh3j4dh2cMO9+P3DjkZvlFwE2XtJZkuUWGXQDcTvCgo+39e1QJ9JSsk1ZbBNClssHitpNjtiwlljPsjuHl3qHHm2ngjkhar7w90w3xqbtjJBD6GX3HfbonLCQpdIIRPhCoHC0B7HiCPCnEVWIf9IDd/o35//EYlklTcEcGmEcAZErI8UlKLMyKtHkfEEBuAnuuFT3s8Ovr7X9z6EQ6QZYAV+S6Pow2gnvTQM6fDNgZIol1DJTlhdc6MhZxMrhnHnZSOuuNZ9jtPGB3WArYKUzLlGHn5bIsJXbXC6ETFu/rUugEOUaUCbqACcirY56LYVFcnv3AesTQiRxhtNMEf8D+4/Cv/4o/AfArf5vS8CMKnSAMux3Rg9OTWwLsAGbpq4UGnH8p6v3A6MmuA7h9Nn8Jbw4HxrAjciTuNwAA4YbdGwsXbRM87L7+/ACDdRGwa/qUppl52C1j2N26XaD2A+SS2K222mqrrVZWCNg5QW45OQAwMlstAew61Q9OBuwIa74U4FBhq1knAIXBw67GsBNSYjNpqgwUWgmgxLZVOW3Jwy5K6tK2JaDQg31a25WWox44pFrAQbs+bkNgMwPdHBnTaIUsOcZWC+y1ewRHLJHEhrRWte19WHJ1WSuOhztNilsC+9DDTgX7HnEy/COuPgO6WgA/DrejB8sKYQsAkeUwcFntJCScFjzsAHIPt6Xb0DUccJvbT6Sf5dLe3INOAtyy0IhTPOzssCxllq+fsP+mSQMtc8DQkneP1ZaJZAhKQir6nxHCRBbCQdVQWkqsjfJbCmghY+6ia4ISjL67coYd9bAbrAuB8QjYDQSwM/6dcQ6dSM9Z1xDQZpEklvUhZNjtn/r9OxKPPp2NSCWG9NndtsZT5+bPW+/rbghQVZIih9TbFfc9KSV215JzThl2RBKbMuxSLANDJ1wiie2kr4ZqmQ0BgogRJJUlsc45uPE+/X0zxc+4b6NQ3MNOAuxGD1vtstCJPv9ukNhKDDsCHFIWviDlr9VOkcRm8uwH1uMBduFGTPXD8wvE9cVnlVbwakMnOiEltrtIPOxSwE6XxAIAPNnPgwScXcWOe9m3AIcX85fe+I75fy6JJS8AIsOOdI4nOxdSYrF2aK7J0WnVw66cEnsL83FGqun1cZPEbrXVVlutuqg0VZC1AihgEHkhFNl5FoEkAcBK2t5fXjpAp7YN67Vy21Fgqy1Neh1dwTuvJokV2uZAYUE+fAqTccWlSWIRWFrCsONstUUJs35cxIGzmDBbWq/CsFsA9qEUl/vBGSYnktvKHnZmwcx9o8hal0hxjSaJ9W2/GRh2ieQI5ageLOs5UKUw7LLQCUsDFwpgF5XEMtAPfQKz9qyfaEm10xgZHn0mKSWMIp7S2sT7Jr57xfYCw42/WJ6alItgkoM0iAAoy7DAECQvrqtn2SXhBrnMTiwx/MCEvwGAB+x46ASVxKLHW2RpIgix79v4/kpTOYdU8kolsRTMw/e74xglsQicddTDzt/vMWn11JTY0AfwvXuHgN0hMggJyIbXJPbPXWAsueR4B9YcKtIcAnZRXqsCdi4y7Nbc9yQPu53qYUcTZQfCNGT3+jYeA+6lqjLsGBt2mBRJLGO2He0Eg/Pn0V83qZRXf97nHnapNBqASmKnxOqlD9tBwGreH2klgWzCePc+klhlrKgl8Z5aj8iwyx+owReitLGcUfeYktjOA1Tj7fwPAKC/gIueMux8NLFRUFhST3Z+gOBP5M4McLVr55Nx9IDd6985/88lsUEm02YJPgCQXGBXrYPLXRu2EwDgtS737kjaBQ+7Ukos9bCbLxo8Xy/uCFtwq6222mqr9RW+fAuhE3gvF6WaBGiRmF9jYI2V2w4FxpkI9iVyWjnZVl0v+V3e5oXMvoJ3nrjNi9tqEuBB3+ZMPnwmgB0fZ/iKDLt6SmweOlGXxAawT5PEFhNXPYClediV1quAbsvAPplhhy+VJaZbAPtggiSSMnjY6W1Vhl0IyjjfsV2UYpJj4s/BOHIPO5nJUZKDDhm7TAhsIMqW6OE2r8NqPnqqLDd9saZhLosYbvieJYRWlNtzSauQUhtQDYEh17JjQD5z/vs54Ci3X7OPGAAk201DYMqS2IKHXYlhR5iOoZ+52Eco82jfR8IJFv785tW8nJsEsIvXTMKwCwzC+bw1SUpsk2y7peBsISU284/D/dy/FvYv97BrCNCXe9jRfsJBuMY/fwx578VxURPAvQggNyxIYY01+9Klk64lD7vAsJsIw45ZYhkqf8bUcAQ9l3rYebiow+cLprMyD7ubgw2gWmfuK4lNGXYAkVw0UjCQqD/6PvfS40BwUoSlnTDsHlESGxl2awPshPSfkJBR2liSXAoAic/agwsBquFu/gcA0F0mHnY4S7Hvmjn1qVBPfOSJ9SDjHoY5IRYA4PBy/h8Zdpkkdu4EA7RwJwJ2cXDxpJuPG2XZvY4/cgYifzkrethRSaxn2PkOtoVObLXVVlutuKYJMF1uFEIYMqlmYqRLXjigyWcCA/gl+I0xhh031s2AMzpbmchpcz+43P9uOXB2iv9dFShUmX0xwS7sx8S3WU+Y1TzsVBnvSitKYmm/sFGSVFJG4MtV5n/nX7YWsOQaFeyrS2Jzhp1vex+W3AKwDxmDPOl1iZw2YSqSfV7C7GtQxgsu7VcL/O/WXpkUEyCAVchuy8MWZP+4LGl2GnJzcgFsahoTpJHcww3BqoxdxvpnLstFhl0815EpmAOPizzoTvKwE1JqC4BfxpAj/dFy4FR48aUvrusH7KhXGmPY2TF/ZgAk71+B6YV9KryrCeAFDUZoUTIawRfq7RXeXxNJ7Pzz6xc5y+hA/O/2NH2VedIlDLsglyQAl2F9W6gp9EHGsENJ7HgIyzQ2rmtk7fqwnVPiN8fBT3yG4HOIHvdwPwjXyHQWKcUzQ41LYjUPOwbuKc+YkHo+jRnDrlVwD66aPDpFEuufWWj1dX0cg88cTugdKDOwJIkNoRPzuqlNGWIVIa22SZ9zu36XfA+ASmI13W8EykM9oiQ2ANgL02Zr9eiSWJo8mlFTxYYMbX1UwM4va7iJDLtun6TELkmIxUJwzvqXmh3MDDsYD/Hh+jpKYp+ljYP3kCaJjZ340gN26GMHAPDmDmfUNEnsEg+7eGw/MG8AQOzc1x6we21/vj4nW2211VbftEVn+QvSVNcIQFIiizO5D11REhvXK3nYRTlt2TtPZth5dp4mt1nAsHOggF/E/04LjtCYY6WQjeo2Wwr2yUBhPM7n4mHn/Y7oSyoZ5LbFpNcKcHYvplu9LYJfmZxWkDtq6+UsOQQOi+vFtozptgTsaxKZDr1+l3vY5W3rYN/aKwBNiSTW+7+hJDZjhqX7mwXjEXbaENhpuAyZZRFAP8ZQ00MnGMNOYbgh6GgMMp2cuAxV1jsNGeghyXr7bPvjy34I3uDApwAYhmWQ9ww3etCyICum7fmE0+qKAp1Anr2TA/j3/scA/8r3Arz8RtrGSSAUDz8YAUYtJXYkfSiy3ZBdREE3CtghWPLGZW68H+S0XROZayPxsJsIwy5LiRUYduz5Dz/9FwD+4K8H+PLfFLwgCwy75FilfS/1sJMYdh4QMgywo1LkLHRihN/wvW/DH/tnfwP8nv/OL4e1Vsqwq6TEjjYNqFDe/w0NYApp5WmwCC8O7muAXYfprL6f3R5tAOxw0uow0GTkOsNuxySxYd+BMOyaKRl7iaETPEyIFwl7CbVgO3nRkBRaWRDQA+vRQyfoAzV7gIgNXyXDzi97JAy7PjLs7OQCULVbEOOBDLvRzCdyB+MM2KF/HQDAa96v73idNraRYScCdsRz7tJfa28TwO5TeFhqktgSw+7ijfDje+bteTORYXe3Mey22mqrrVZbFfCrDJyhpK5Nvos1lEAofOEHA67EdJPALybF1TzdxG0mv1unA2d1Oa0OFNZ993RZqyMvu/I2F9J4NaBwpSUyIMkgt+kLDDvFhw7BsKbkf4esscz/zrPzFnjnZaDbArCv0Rh2DsGv0yWxzeSP11LQjTLsFnjYNYqJNnrnnbMkNkt4BYjsNC3sQJXESv5vCruMLSOGRqQWNRGs0gMj6DYEYkNgCXo5aQDbyDtCkSEXJytCaETBwy4LfcD9czamvGayYMI0o4CddR5h9FZB08ja50zHlGHHgJ+1FTluxk2BXTldvwfwE38S4PAhwM/8R2kbss9qSqwoiY3AK36fBinge1rfEsCOvEciSCEBdsi2SwA7SzzsUNqYSGLbZNstBWe5JPbf/R8BvPN5gD/ym/LrKDDsXp//t0eyf/FY8YCOHQmxpMQfwzzsGg/UBRCJhE40/Lg7C594uoff8L2fgF/2ba/DGmtO9KUedvM1uFc97CYYHZXEKoSdYC0RPezwma5ZgXH5fATsEGvw1zvzjrsmgB32raOlgJ3+3OUedk1jwnZESaxnYRqX9EVZEstk/rwIUB5KuXeXqif9lVbWFx9YryB0gkhiw8EqedgxFHP3KiSxNzNoBwDQXSS66Ge388m53NUZdujvNnjAbm8GeLLvImDXX0VzTUylxSJMgbthymOljYHRX6RX7dzhKGD36Su/zdzzL/OwSz0Iknr7+8KPH7QesLMWnHPw0odOICi51VZbbbXViiphurWZh93IQTfBSBeZUtX00kROm0ooNP+7WmBFOTV1Ceh2YoBDIfxhKIGb5PeSFFf3sNNZgXnb8wDsSqxNgLKHXUx6ZaAbIHCmz2QHaSpnyS1h2CnBETGwogBgqaDbkvWWgyNKLywawy4CdnUPO942XL8nSHzWVhnYBhCBIg+WxcAHmR2XJ81Shl3dwy7dDi6JXcawC158TBILmgceW0afyXrjPuSgYy7rpYBZAsJAlLu3HDRksmDETEbuw8eTcoVjYIxJQaA1Fw3um2zY7vbLPxb/ju+V5Htz2zYnrCzxsJuCI1l8lzPRhmIG7ARJ7JACdncUzAu2T22QGg5jDti1QkpsOFdJSix7ZpFjkEgAnQOwQugEdiACnOcpsRGgylh7dPu8nLc1sS9mvmELwjLWUuPkYHKgM+wslZZ2jI03itcsAEBDGXboYWdSUJZXy2wIDlMqcw0edsiw8/3s5jgGDztk2Dk6Fj3Bww6AgZUAMDhMiZ2YJDaXgwcPOw0wEyWxdekuryzMx1cEmxcvqlivIHSCoJuLJLGvkGHXUQ87DJ24THTRH1zPF8TlAknsEzTs9IPtPUpij96/bv9aBAk5w26KoRMAAHcshhsAwPoL6NIDdt/9djwWn7z0x7DKsIta/qw++UvDj7fNfAM9jBPcHG2I/d4ksVtttdVWKywy4JwEDzvJlyg28AMn/7zQ0qxiWms+gEFWmA5gleW0EvgVPOwkxtkUTYWL8lJVTmvDeutAIXseE1mrGnZRkdPKHnb8OK//JQIAQlCCEcyZrTPQFQA7ozDsOg+GleS0oIBu7SLA7v5yWi2tNSyrAJy13uaFS2KXtO26JjAZUsAuvqSp66WfJW3nMe45S2KzsAWACNhlYJf80hqTZnM5aeZ7pSwjB/1wGzQ5KAPsuBcfSmonDnaR64wm1WYsQcnDTpf1UqbJyDzo8Pt9AXADiCxAfgxwm2tpvRnoudYyJgGpQv+6fjd+58XX0jYh/KBJmGHz3wopsQkL0S+D9MGBSmJJaCIWvk++LjLsoiR2R6V7aHPg15NKYptk21NJLHtWknd4TDvuWpOOIagkFj36SLLryK4/KjEUwytNCghFSWyXgoYAkHgHrrzwXAUQbmQedlQS23BJ7DFec/z9n058cYbdwpTYo0+JDZNYfjm9f97R0AlkwSEYvKPPwkWAXTzXOwWwmxl28ZzudoKHHb+v8wpjZSF04gTAbleVxD4O1PZogF028wNRdlLU73Kz4t2Tx9okwrC7jQDa7gk0jQkJrO95wO5qAcMOv3P0Cat7GGbWHTLsdk/j9nOGnY0SG4A0djt8BRCwm4/h9336afjs7Qv03eAeduyFo+Rhd/WJ8ONXus/N+zJOIXCiJcdlq6222mqrFRXzksvAoFJKbMaS42y1kiTWg30KOy+TiIrsvGaW0ypBGSAxzphn38QZhVlghc50qye9KrJWScYrvPBr63UOEjY9tj03SSwepxSwm8dOI3TlSVkJOHMuyJhKslYNdIuAXZ2dx1ly7QLgrA721SWxPPxhiYdd2zRBaZHIWoMUtwz2HZzQ9pvAww5fuNLQCRb4kMlROdjGfPBowmoInSh72Gmgn9NkuSpYlUpiIYRWlBl22XGgHnQ8EVFgdGahD2TZOfApXyeZnyCTxNbaS2qs1Ra5TwdmGA0UfPHV9Ptkn7MQDyq/4ww7eo4wyIfIG5OU2OBhl7PokGF3HKOKC7+3I4DdkYROpJLYtF+ngJ0QOuFcQk4x/l24MSay6wCS0InQP8i76sgYrrsuXmd4rSThCLh9/hkSJbECUKoxA1dYAZSiIBww0IoASodxSp8XTp5oED3sTHqOebXsfnn03nFdAOz8sWfMtpshpsTic6s/EbCjKsgd82wMgB3zsNsTDzvnx4rZfT3bScJOxHpMSSxPLH5gPRo6I82afOwMOyqJRRbcbkb6kVH33sv5phLSXguFDDvUl+9ggKt9GxNi90/TddIKqLYH7AQfO0TVL7q5Y/7gZ18Ln/3gJ/1xylJiT/CwMwbgf/G3AP6nfwme7T4978s4wQvvX/dk11aTcrfaaquttvoYCuUF3ktOk4iCBEKhj1Uje9hF0E1i56Uvnzw1tRikwIBC1cOuADICyKDbUjmtdZI0dVnYxeD0wAr1RcAfaxQ3SWMiEaBccU0YHCEwLwdoi7YnInBG9rvoYdcogJ1/AWiKDDvZ/w5/L7XFbdL87xy3JknakhcScryWpNN2jQn9hr5ENAoARGsG+yR23jcBYCeBPEyOmjG7Mg87md0Gkw0viks97LKUWC4HrYGGmaSWM/RkD7uMaUg97Pj7VsHDDsDLcun+BQ86DlqytF0tqVZl6KXtM9BzzUX8z8Kxo4Ddy6+n3yfXac6wIwb33M+Lyp5xIgNBKNMEsCJJiR1ynzpk2AFEz68gie3bkL6ahE44yrBLzxmCZAnDjrCa4O5ZMrFmDh+G7Qz+dQBEEnsMy2wouMmAFQqAiCwpDEzw4GZDGHY4sZd5B3LvvRUWnsfJpGEICFqNdgSAqKSYU2LJPV+55pIJKEwNx2CRqoed70cTHvM0dIJ6xznn4OYwhm0ydmam7sDfS0xTZIkfxxxgo4DdaKfA3uvMlOAdFORD4Cy7r/OSGHb3kMRqoROT1HcfUI9mapFRtQHyG5ZUJAgBACLg9RiFyxrviGx1vnFc7Tr44GaA9156SewiDzt/o3TziZxDJzqAIzLsXgPokWHHAbsU1b4TADscbF0083H7oc++Dr/nt/wwfPubl/Dd9q/MX6pJYksMOwCAt7933tR2Xt7RRobdaxfnO6DbaquttvqmLu5DxwgKCKS5Vgfd8KVdTVyVJKKhbQ5AAUR5rZNYY1MKFNYDHGRQRwzZOMH/DjRZa9XDbgYKnXNhMitKcVN2TN6WSceStgo7b6XlgiQ2n4keoCtLPiS2GgWyOn3GHT/LWXLL2Xkqw24BO6+DdJy2xMMu9ZI7hvCzJem0bWPiC1jCkqvP+idgHzlPRvFjO6cSQR4MnbAMLFP2N7LTpqT9zE5jL4pC4EK6DC4HRZYSl4MqoGHmQccYenh9mBaATKKrDL1pBGv8PmQedHLowzBNceIA0MPOQMkDDyAybyz3sLPIsONpvVwWfE4Mu/g8DGEJFLDLrI/iPmepu9QvC88vEjBIP0FAxAiS2CR0ouBhh3+76NsA3NHQiSEJnSCgBiN8JAy7ThgbIFnFFx6btiGAXdPFd3ErhGq0fcawo+EYAXShLCnKfGxMEjqB15YoRV554XmccEIogOAeyEyYaj0cBgs9DahQQidiiJKFaBWSJgHz4iSsO/SwY5LYXb8DgCM4NwNlN0ebsP52bQO7qf7MBZA97Kgc+DBOYVzVw5TgHdTq7DBa2HVNfl/PdtJvT5ISex/ATp6EyOTZD6xXANidyLC7fCv9/TEZXh1hu+GNxUtW7yOJRYbdrQfs9sZ72AWGHfWwY4CdTQG722M+uzT6jrhv/v/t/XeYLNtdHoy+FXvCntmz9z5xn3yko6OIckAIISEZhARCZBtENGCTbMxnMPY1/rCx/fFcX/P5PjaO1+DPxgkwJpuMbYKIkghCCKGI4pHOOTvOdHel+8dav7V+K1TV6p6evbvnrPd59jO9Z7q6qqurq1a96w36b1/xSQ+IB2+WJz/HEruAwo5BNw21SBOx7JnJ5g7oIiIiIk41LJV2r8LOWzph2lrtDDs3j2jITtunVvMtS9cjf/7doOLMVtj12Gn9rbg6/65B5hB2TeO/4daPpaVCXpPbDqD7Lleh06POA+UFtti21HZe+/Aag/axajoFDCXhUOyJt3G1DSPsvNbUrlNNdYMKO1LJWaQbkX1Dyj7aphStOJZS82ZlyBJrNr0ylZxS2PUvayrsWAtvF0r2mWonvuwmK+yc7DhAff9UQ6siu/xEUeGQZTz/zbaT0o2grbCzXkN+Hr1NtdaNs9N2a51DhgobxPL976GCdb/lsXZR6UPTyvbNJBF/b4lEKlnLbJ/K0FIqqqbbntKJMaXjOoN9PrTdJmFnElb8c68ViRtgiWXHiVLYMTKiqn0ZdrwlVjw+M8nU5zutG5xFYbTElpxYoKZVUhwniWOpNEgb3/XOIizT2RUAW+IYIUtsNmHEyMzNsEu1Ar7wZNiRWqo0CDv2uSSJKp9AoqMzMqtRdiMIu5oR8S3UcUL368YEkrTEJr6WWOv+n65JKbPENsoSG5ZhpxR29Ll1psJObH+Dw3mtxk1oa0yKFEVN54KBNnn0ZdjJKLKGCDtJNCYsciLNLcKuxR7gntdtnLQl1i4COiZWWDpBFxJ9E9GGbOwqFXV9rz29rAeIpVbYAcCj18kSO07YHeyIk86RPHBLVEKCTBl2kzO65banJZbCmw/n7smD6pkniUvmOSd4gn0SHWqJZeCtM2SJPbMVCbuIiIiItYRFurlWTUs54lG60eDVJvtooOQn3cybz77sPAw1zKbHIPswrLBrfTcSzP5SI3VsvKFW3EYRba5zwGsfBjSRJa/nvBykUdlXmzPrDwBtRk2v7LOVY5I58sUtsdzuGUDYmXZaZsEaJN16FHaqnXZcnSfWx8gvWnZgvX3lD+pGZ2hZg3TzWGJHCLvaq86jZTd3fMeJA8onUkSRIrsWLDtgBEql8sbCMuz0uVZbvwCMkl2OUtBqKdQKPb/Ko1/hV6FpGuM5C+8H+R4Kext6FHKuLdciTntJx01S2OlrGh1elNMGwBVmMAKhUUovaonlCjvLEssKLrLEyiNnLbFlT0vslDXBcjEG/znJU3Xfx0snUp5h15r3j3SstIYlll0DKouwmwsyM88SVZiAvDSOc1IbmQpCc18ROdd12o1mWmL558IVdhnUJda2xG5AwZMiYdX+MksnDMJu0BJrZdgpcrZxJn6Lnmu3TaxPpRU1tRR2Bbt+T6sW1+eNEeswyVNdOjGiWuNZjQSe3zerG6WwE+SjfN1ExHlxNV7Xde553Ya3dML6bgagzxJL57h03Qg7J9AVXGE3sJqTzEyjPLyjx/XvJGFHGXaPqZbY8cHMwY74AK81klhDJSTIKh/vjF5ndR3gIdkNNXVJhZ03w04SgamPsKMLeJ/CjnzlAy2xDPxLQJbY3aiwi4iIiFhPBJY/eMsQLOKsr3FV33zxAcywnTZEnafy7/oUdoPKvgxA0pthhwEbLyBIt95tHlH20TWZLz9eOiEJu8QlOB1FYWMtu66gAT9X2JHluMsGLbFe4oxm+bsEedY/Vkl9Kjm2v7MAS2yOxhiL0XYMK+y4rZWtL6BhNs8yb/lD0LJpiqpzv4NpN25rNQg7b/7d5irs+KS/c75pWDMl0Et2DanbHCXEohl2rU12BdpBHUutrfDryY+zz0EAWm5tBPpJv77X6C2N8GfQ2a3kbg5f4PLrDBa3QOc4IqUAjFhirWMqY+SA736OzlekACbVWJYrW6thifVk2G0V+u/UHKtbYjNmNdWKObLEZgOW2LrtVHOsqbAzCcucCLs00Qq7fEsrq5q52o+6/Efn/RVkic31950KGg3hj2VV5hl2NAmoiKgNUthR6URiWWLTVFjVC4Owy2RLLBtL9JROGAo7anfHcOmEq7AjoszkGpIsN4pQjmxLbJ5qK++IJXbusbBOGAk3rbQlFm1jtDIDMOzifMzWR0raEybidcPIRY6ClaRwUOnE2insfDLnVcsBF4bdOJtvqVlGyqyjDLsghZ3MB7hea4XdwY6lsCPCrmstXzQRduKA9WXY0UCtTNy/9SvsbEusf6BggzPR1ynDLhJ2EREREesJJ8POT34l9iQOW1Yr7Pw5dH6LqHnj1ZfTMdhOO5JhN7Rerc7rW2+AnbYv/07Zhz0DNnCFnYd0825zC7tpz5dh1/ap89YUOsNO76dOjkmqkZZYpZLjNxvKThu4bE/+XWKXcDFkPmtq1yGjFsbBHDo2zjJIN3kzHap085VODNy0iGX7ba1DNzx5mnjJviSAKFx38Pwqp7CBws9HyLK+hlc0FcvJGiarcluYYH2Px0onlBOptZcPa2h1l2cZdKpptj/DTvy9R6XX2bZcvy246MmwS9TnMKywcwjDdQa7tiihHLfBVv2EnVs6wZRevvs5roICt4zmisgp8sRrieUKu63CLKXgllhF2NWNOi5ofVmaOhno9Fm1HVPY8euwbYmVee4iw469R3qfrCU2YeRS1TLSEKYi6lASdkYOGSNS00Q363KiVAmFMvM7ts4wLLGAwSGUeaqiIJAWQJJgVrWmqlodfya1k6ksWJZhpxR2fhrIVhNPG0nY2VxDolWd00rwCeo61FRC9UmlEwNqegDK+l14WmLnTYNpxdR77L3Q8cCFSHzMlvdl2HkVdj3iqAHQtcexxNp5isfE6hV27MtcW1/CUezftarNEdjaN/9PTTXQCjtSl4WUTpwlhV1N1tUKB9slK7TYNy2+/GRm5WrYCruu69RBXngJO8oDsEsn+iyxYQq7GSudiBl2EREREWsKaontJb/0jDwAkwyyrj+uWm3ITjtM9tWtewPcu94ey4BX2TdixdUtseOEXb8Vl94vJ5P4slZmFN/mzPN+2fYTKWeOiYhU9agC1xgdNa6y/drWuiW2dwYbmtxKuZWKN8wOqfPkeg2VHNvfeUBLrLGMUXYxZGvlCjv9nrMA0q2v/CFMnee3taqb+FGi0Ef2UfHLBhN27B7CbVi1yK6+DDsn/02f6+yWytHSCCcv1M6w8ytdXHWbeZyo9fcRfn1kG7T1OXNIQz/pZ6v8iIx3ii/6LLWNTZyGkY4bpbCjz6dr1Xkqqaf67yGlE16Fncd2J/djnpDCzi2dKLPMa4nlpBxXOwG8JTY1s7bocwcRdnA+M7KvGhl2A5bYRBZNGBl2+cRQMhEhzN+fEveollj9faf4KINYskonlI2Y5eGp/U7HX9eaZOMagj6zhIgtm7Cj9yn3p7DEsnO+PRaTSOVYJWMZdnSd6eNnbEXytLGyB9mxTvzJtGpwaJFqk4wpA4NLJ3iGnSbhjqoGLcvHs8em/NjnE8u9ojGfwo72+UIZduL15z0Ku1WVTqxQYedaYoMVdk/9TPHzlX9rVZsjUOyY1tCJJuxsRV2Ywk6q4yA+yBK1qbArz4gDgD5onmNHCjt5wNqlE/OmDbPE2jPKS5ZOqCDHWmfYRUtsRERExJrCUti5GXZEBg3I/BX5ZanVPCHm7rI9ttYAlVy/JdZvyzJep6fsQjfM+pR9Vv5djxrRmyWnHidIErpBd0k37zbzfe6xEKttVqTq+s/6A2DqD729TSVuyGpkwyo5X9OrJFVqZMP5dz5rqtxnbZcgy4fKHzwqOU6CDSndMo81NbDsYqz8YYx0q3y21oDSiTxNvWRfdooy7AA4hTGJIrvC8uNcsqtTKr0xsorUY2qCw2rk1nbQETuqlR+nyLZAdVpDWX7873KdYwq3vhw9V6HXtw126YT8HDqLWBlZfrMy7ISSCwCShhF2zdy6zorjqE1S1XOkjgkjw86j4qGiBzrHMELLUNj5WmLl461CK+xIdadbYrUSypdhlyaJ85nRubltO0PVpmAr7OS+MVpis4m+b21mirzg769uTK4gSRL1fSaFnTfDrmuQpalSTXOFnSJJMvc7sq4gclVdu9ixVWapJr5SIuwac3KIqd44dImSzrAbb4k1JzimVDqhroeaJN0uGGE3q/U1DMBO3qFM6HgPK50wMuwMS2yjsoHR1o5AiZN7/PyyEGG3xPWSFIF9E9Krcpmu7ArunMTZ41GF3ef8K+Cjfwjc8+JVbY5AkgiVHWXYTfbUn7Ysgm5va5xNLfMUu2WGeSt2W0kZdqolVhKC5Y4ouqiYv9+6gNulE3OjrngRS6w1Ux9aOuGxxMbSiYiIiIg1xZjSrTFvoPykmySResg+P4FlqkWWy7AjtVnPstaNr/gjKYNCyT6PnVbm33WduOlI2Q3v6DZnBfI0xbxpvbbWxLfN3DKa5AA6wyZBN/qJb71rDL/CTlti+2w1gCa3lJ0HsBR2A+o8h3Qr1XFRjZB9xrJEfgUq7EglV6BhRGFY2UWfSi6n7LxB0o2TfVpdkQUsa5J9i9lp1x2mwq6HaLLJsp6yA728/nuOBnOko4SbJrv854+xwoVsoOWVb2PfTSNXo9Zth4K9vrY2DhOXhXMOlFlmtq23RyXYS3xS8YajdOyxFW8EYefJsONRR4AgrbYP1PMAbTcE2P7gkzS++zmVYSedadD7v5prIkMp7KRLq+s6FbHkVdixhtmC3fchFeSJKp3IeOmEJGcS9p3xXWetDLu0OdKv1fhLJ+g7kjLLr6/Ns8hSVE2jLbH8ntZo7wUj7HwKO07Y1QCGSaObCfqsEkZwEoQllpRquXp+1bHrRd95R+XINup7qQi7nmuonWF3JC2xqsSInR+IJD6qxOdVM2ppO2v1tX+0dMKTYVdognpmZNi1jkCJq0/5uKuXgxosnVjAEjvSErvGpRNum9rQoAqAILrufcnJFFBsndWPd25RD3ctwm4/kKy6cGaCWSc+yAll2PHSCYAVT7CTmRxA0SDfzrDj0tbcR9jVHgk14FHYhZVO0JeAl07EDLuIiIiINQXZOHsy7DSR5COhzJvYPuJML+sJ+e+xtYYUR6DHxksDnOHcvR4L8AJlF8bzF1jW5xxwMrB81mP298a73s3KsFPqD66wU5bY4Rw6b3GEHBSPZdh5yx+YpWeo0CzPMjSdFcDP9vdQO61BfqmxFVfnjZN9YpspqkSr88ZaYr0quSCFnSb7iEwFwpR9644kSfqJItvKOabsssky6DH3WOlD0WMndQg7pdAby49bUGHH7qXqphMT8wk1SJIFc6T0wWmaldvQ2fvATxr2Zdg5OX6jKsH1ticCMBV2pP5iJAoAU2Um33PLFEaONbOpmcLOtcTSd52TUDyMn9+7AeJzpI9ykmeYWAq7GSPzDOseEbVyPV6FnfqsoEUg/Jplt8QqS2wCkHU4m4CXTtAxnjJCUivs9PmcvmtHZIllRRRG6UTCWmITTdgpa3jquYasKegzzXwKO17eQAq7ymqJ7YnEomtdxhR2RKr1RVLY59tDZYmV8RSKLEuVJfZoLgi7hlFLOzn0dg9kzgIwylXU+1ZFKcIS23BLbKe/IwCMfMealY8kfdySijXxuCSWsMRuUOmEO2tSq8C9la1mcUxYjt3OBfXw7Lb5Yexvh304d57dwlwe6LtZI3LfZlfMdRFhN3cJO2Jt7Qy7Wd0qqWfiG8Qr1rfPEmsr7IYJuy3JRE/rRllio8IuIiIiYk1h2R1s0q0aUm+NqOR8QezOekfIviFlHxGBysplLxtAutnL9uVA+ZY11gXPTXvPsk6rI3uceNeryc2cbBKtO4mZ+AaK6wxS2DFba1uJG7J5l4+o5GQeEtggnyyxIw2zmaGwI5Ucs9MOrNeb6UYNeSPttIa91Jt/N0T2eey0jIgeVvaxZT2W2OHcPU32EZnKl91kwg7wKbvM758my0asoHZeJxhhN5L/1k8aSnWbUuj5CxscsorspHaGXW/phEdpSORK4HtwLKkW8alJw8Uy7JRCzyZ2+qzJlhplLcGIIaUMCyDsakbYaYUdz7Aju6indIKIV66wI6ugoaBrjZ+AICz6FHaTPFXWvYoRdpkialPnupny45VEIB0jJRxL7Ey+51SLTHJ/6YSyxGa5141H3wVliTUUdvp7l6aJ1xLrZAcCaz9BpjPsNMFJKDOusBuxxNoTBTmzW1NDu6R/eltinQw7tv+byjhWtg2FXa1V4gB2shaTQIXdXKlB/Rl2bumE+X65c9BHAjvwKeyWscRmJolOoHHmGirs+sOZb1pLLGAp7Bhht2MOuGwCrw+CsBPPPVs2grm1LbFehZ344tGAy86wm9nMsY3gltiwDLvtkmYvGmWJjRl2EREREWsKsnkqxZm+hrRtpzL5VSB+j80T8MwEOg2z/aRbX+NqSDstX5dYlm5cfW2t5uDUXXaIdHMnroJz6NggMLNtdGzZxDMLzrOvfFlNg+tdY9B75ZbYTqopqqTon8GGRbpZKrk5cq2E8C2bpag7K4ifLzswtswzrpKz1XnDyxpkn1edN6aws4hC3to6kOPjXS8QVljBWmK7xrfsZo/vlJWzt6F12M7aq46DVn+ONc26pRFEVtn5cX0tsX7Cj/LftJ20r3SCWWItwoyC98dUen0ZdmkvaTiSYafeQ2W8x+Dl1xmJJuzopjttLUssL6GgBk6vwo6dEwZaYinDjhN2KsOOW2IlucPdWsISa5ZSaMIuU4RGVev8Q1LYmaUTZr5Z07Ht59d3ymmX5zTKsMvThJGSVumEfM2MW2J9ZQPy8XXVEuvJsGtr5Gli2IdpXKS+B0niz99bQ9BnlRasdEIO7CbcEivf/7RqzQiFHoedUth1rREpAfQ7IO2W2KOGPa/lar7czLCbi2KIDuL523mnFXbBpROelti6xdSwxNauJZbZZ53mb++bdMs9jmOJdSaz111hVxkD2wVbYk8CPQq7g2UVdgfbmEnCbi+X79W2xJYDlljJnPsUdr6gYnv5/pbY5RR2s7qJltiIiIiIdUdnDtYMmya77ibe9lK6aR+xpnpz2eSsb292nm2N8qy3z5rqWGI9RKFBurnLhpRd2NutsuRG8v4cCxt7nWGCsvC6DgYVhWsMsoByS2wrSycqDI+dEl/5Q6NtrUODWW+RQqNJt2GFXepaUwPz7wyyz1LYibKLBW2tnEAbIftovdTCi65TCpKxDDsi+xqvJXZzM+wAn0LOVqeFElVU2MDtpA3SRCohuk6fa+3SiFDCrUddpsgqi3Qkskyr0/zj+CxNVHKQrRQ0bL1tC8DKB1XbMJxhp99DT9OtvQ9UcUYf6em+B2P5dYZFDCVodeg+3e/VTHGnAv31rbWrsOuxxKpzrPwcfQq7jJVOVDYhlyJJEmxJ0oKIPNUgW6SK/OClE5nKPkyd4y5Tx0oLr5Kd3rvM8MvamV6O/paXRukEvSYn2bwKu9yyxPa0xKZpouzgSFP9WnwSyeccWEPQZ5kXW/qXcn8LS6yrsDOuU33ZmznLkbVI5b5rqJthx77HhsIuU50AXABE56WttF24dKKPsHMtsVbpRKYJO6f524cVWWIVEd4zEZ6tW0usXQHMH99Uhd3BPfrxznn96x3zwwhV2D1wyy7mMuTxTC4PFkdhty1+8pZY+UWiAdeRVToxq9sRhR2ryOZYWmGnv2DXYulERERExHrDKFIA2s5DXoHd1HMiiSaMem2tNoHVT3712VoHya8RlZxWBS5Cuo2TfcfNsHNusOHeqPrfr99OSwO6ZNNaYjO36ZUUdnUyPHbKPDl0HSPsxpRuzkQm2c664WU5+WWr5Mby77I0Mdvo2GuMFWXkaaJiU+xtBoYLK1JG9rV0w8tuMpMBK26epur9drVbWLHpltjcVshZ5ypFdvVYYrlCxybOc7RMoce+z04Gnb0NFllFrzGaYWeRjk5+XM8EPfoJtwxMIMHPK2OlDyrDzrYWD1tinQy7vtKLHlvvRmXYdSIrreTFOSQGaXyEnSa8lPpYZdjNexR21MIpiVNm8+REBlcRATAKJ8RPU2E355ZYo3SCLLj0ucG5bmb8WLM+ZwCalJNOtkwq7AqjdGJLv8+2RpZIm2DnEnacXHEssZx4SfR3NUsshR1FcfEJGW5HXmPQZ5YV7LiQ+7jMU+SJ+Z2a1S1TZNe9ZFMuXy9Ha1zHgKEMO60a67oO17nCjivSDEtsq8RInTw/b2UtU9j1X4O6rvOXTjASblo1Wr3ats7xapZOUKbnAP/ktcT2n3v7QOc0xxIbWrwaiJURdkMD25uqsLvlKfrxwb3q4Tlmic3SxCmh6MMrH74NM4hlb9uGGBzUkphTGXa74if39ytLrFh2Zn2ws6pxQ445msDSicCWWN7qQhl2u2Uk7CIiIiLWEpbiwUtAoYcMsuylfQ2zXtJNFSb12VqH1HnDCrsgso8Tdp1Lfg1l2CWjOXQegpLd8GeeZUlRmPr2Mxsw+7KaBte7xtCWGr2PW0XYDY8bMk+GUEN22hGVXDGgdBPE2Qjp1pNhF0K6aXXe3Fh2EZKxU6SbeA2Rnde/v8ziCNpmppYbUMmlCdiycr1to2/8RwK/1x25/X2y7KhjVkz+mdmEfZ7U2s7KVTg9GXb2uYe2wVWn2WSVZZ3KFnsPgE+lJ55TQOSsJbw8wPse/MvrttAwW7BuyiWiSdqCA0snNivDrkaWJpiAERVb8n6PvmtdxyYEPPlgzBbqJ+wo67NBkgB5wiyxcl+VzPJK7eWktKOyCVdhx1tiE7Us3SOm1EprKOzIZs2uf4mH0G5Mwi43Muy4JZbdb5MaVR5vXZp7iQ1VOlGRctOjmOtaZGmCLNHkpteGqBR2661oJzVkXrBztTxWyowr7HL5/NbMWlVkk3XuYwq7zm6JDVDYiWMo0fEUXIyUpIqwuzKtWJGYWOc2J+wGrkG8YbXsUdg50WHKAizJalbIUnvIPwf8O0noczMOoBhT2K0bYWf7nQGusLuJpRPn7tOP73+ZesgVdbecKQczWDhu3ZvgC1/yJPEaRQfMr+o/qpZYj8JOfknIm+5riXUGlxxWaYWCo7ALa4nljDhJWPeiwi4iIiJiPeFRuhF4c2s6VP7AyD6jwCEow65wns+3w28RlXZaNoDk2xq2XkbY+civEbLPW4g11NbKrB6OGmV0m/Vgzzcm0vl3m9USS9vrV9gNWy3zPMW8M8kvstPOUIySX5QZrG4OG032DeXf8Uw3TdiJZecLrXdu/JyjGCH7UuXCoPdJN68h61WWWGu9AICi/4YnSRJlT1YKO2bXS08LYWeXRtgKu5EMO/Ea5vc/R+sqw4BeO6it0COF3MJklU2Wjajb+DbYSt8MjZuB53kNlQWo8kPF8gV6FHJOaYSdBWi2zI7l8DnLrzN4G2maYAL5npIUKKUwQxF27N7XR4bwCS1FZrkZdpTzlhkZdlrBSUo6QJIY8m9E1DkZdkTo5ZlpiVWZefJz87TEmgo7pmwiUH4fKexa1hLbeEonABRUoAM3769gXIHKsJP3p3lPhl2amKUTmiTxW2jXGfRZ5UUBwPwelUaGHbXENupaI5SbflVrQRNuSYdOfi50bey7hvIJR2pvVeQgt4GnuXLsPXaNXatIYZd2QaUTnOwqfKUTTYup7UTstcTqlthBsswX47JUS2xPht2KCbuVMTS+0om1UNg9+ErgRX8JuP0Z+gQLQbwRBhlYDz7l6XcDbwaSZqrtsFkpTkwAy7DzKOwyIuxMJnZet2pWxntS4bMVHOpi2IkTaWCGHX3Brk0rNYNxJmbYRURERKwnrBsgn3IrTfqUbhTJYKrk7BvQIXWeQbp5iiOGiLMkzZEmQNv5icbB9aY5EhktxddbDZJu+jqYpwlm6CP7fGUXenDpU9g1Nulm5J8wO62H7HPIzTXP1CGQwi5HLT6IJEFXhVliSTVWonEIu6rLBsdfivxKoFsHG106MdYS65J9UmE30mybp6lra6UbnbHCikyr5Jp6Jm5x2LJDE9h5mqBWN2CUuxemzgNEAQgAtGpfsRurATvtJiDryY9Lg8sOmCXWUoflaNyyBaA3/82xk1JL7Ahp6LbMSlUV2VGdllmfwo5upE2Vn/ke2KRJj9LQ3o+qeCNL5PKdd/miL8fPKa3w34sohd5GEHZ6EipLE0zIkphNhNUT0N8xdtxUzBKrX4upeVS+G7ufY6RSlk5YLltuWAU5YTerG3UvSUSdssyqjDttmSVCo+0EUZYBqpU2TeEq7EYtsfI8Qwo7X4ado7CTalR5vLVMXMLJI9sSa2bYaeVjniWayEoytyUW2DhL7KTIxT5rZlphl2eoLeLLUNi1df95p9D/b+dHSKFVoEXP9Ygr7MjqWSHHFirtKgSANFOOvUevi8+8yBKlsJuk3BI7pLBjhB23xJKitG5xNG9Q0iRc1zjHKz/2VUtsUOkEJ+x63IwD0GUuJ6uwWxlD40jFwRR2QzvspJFmwGv/386v6QADgLsOthd7TTro6rlbOAHoltg5K50gyTwp7GqPwq7z3LQQxkonAPhaU/qwrb5gmhGPLbERERERawrrRpRn2FXqWpv67R8etUTddpBjIRVgrsk+N0uO21o5+TVYHGG1ps6b1ktgeXP3jCy5BFXTeYsj0iwbXHZI6TaYQ8fstD5VoF/JqK/TKu/KM4npzQpcYxiFBU0lyJ8mMMMuTTFHgV3M1A0eEUphijM6nsX6unqKJGDZPE1xjQi72la6hZB9ubUsbfM46Ta3lW7yJmAW1E5LGXamSm7s/QL6syAyNbTsYhNAN5bqpojsqLa6rSfDju+7ylKX5Whcwg/QNkD1Gn12Ups07CGr7Pw21dTZIUHLMuz6FSmOrVYRblwlyJRg1rGqJhJsSy1vmR3I8VMkjlU2lPZl2NnkQWYtv85g7aKGJTZnJFTtEnaNtA72kkYNex31d0bYJVvKMoo0U/fVkzxFnqXI0kRZFTkhB+hCQbrH5C2xnAiZtwm2oYmzPE0NdTnAPuuu8zetKoXdgXgNrrCrmcIuleOStlaEXW4o7Ny8MccS20PYpUmiSEekmc6w85Kla66w45+lTdhlKRJe1CHHUnXCJh372qUZYdfJqC4qz+y7pvBxExF2vQo7ySc8clX8/swkV8e7WTrRP2lEKr4kMY8DbvGeVg32DEus/DwTUthpu7jKRRxyePossQPn3j6oDDvL5k/27HSTSiduqsJuAP/1a1+CFz1wHv/X5z5rsQVZ4w1m0hI72dN/J8LO0xJLhN3MUtjN6sZtNOPoqxrmX0yPRLQPxER//KoOtCzzlR0OERERERGrhMqhczPsaJBapEkPCSWW5S2TdH1u2w7E/aUDBJapsPPYPAfaaZH15MEtbGvV662sG85e0s0Oqwcn+3w2Xh0Yz4OX7WW9SkZmp/A3zA4su8YwQrBbsziiGbPEGiUMM/kS4kZvjmKwQY2TXzQGIhJs3g1bU7MswdzJoeO21hHSrSO1mmnFnXXjJOOMsuQ8ltihCewkSdDIm4/OUvbNkY9OfpPCrqMb6ZptczY8Jlx3OLYj6zuk1W3+G64kSTyFDTLDDg0rrWCWKOvYLBzCzSQNxyytTv4cO6cWBmk4YIntsdVShp2xDzy2rtw+pylLbav/PpCB55zXKIdPqQSHlY6F57y4tjBUb8wSm29phZ2HsKtUhp3HltlwS2yfwi4xFHZEmNB3gDfFksKORCiuwq5Vv+ekVyVJxVSSxUOlE3XDFHZG3muPwi5LNJlH71EVFxFhJ7arYeISg7DLrdIJXyZd2zr7yuvs840v1hC8IESTSaSwS4XCHQCyQhFc+to67z33FVxdLYVEZIkteq4p3CFA26Xsy0aGXaYKKz9yWXzmZ7ZyrXpLG6fddui9F1lqRJTRcT2tG0wNJ6LrKOTHviqdGLpm+konjmGJtTPsvGrPY2B1pRO0wevWEjuAFz94AT/4lz4RD956ZvzJHETY1X2EnS/DTnzpKEzSq7AbbIkNJOwWVNhdlyfDvaiui4iIiFhfWEo3o32U53UM5HKYWXKdsSwwrBpL0mGLqJ/80jPCPgLLtcT2Kd18pBuRfcMqOW+G3ZAqkG2zbyKSiMLUZ7Nhoc/+wgp7m9fbokMw8s8aU/lVjwxs80yTX6S66FjpRBpIftGyjSL7htVqPrKPK+yG8u8E2ddHug0TZ1nCFXZm6cS8G95mQKvk/Aq74SF73ZO7NxtRFG4CKNeospVdZMW01WUessstjdCE3Vj+nLG83RLbMZWS8Rr+hlSnpRpC6eQu747j6TUqK8svSxjhN5SBZ2fYyXUUqJEkPoWdP4POKe4gpWOaygKGU5RhJ1tiNWE30RZzVvBCoIZpr8KunmqiwbDE6utYnqVmhp1qiRWvpwi7uvEo7KQiSf7ebIllKtNOPxbqzNQ59ul4bzueYedR2G0fiO3rpCWSl07QfpL3rrllieUZdvzcSBl2R2SJzT3kp9MSm6nj2k/wrff1VheEZEwYJM7hkzzVRSRZqQhZwxLbQzalnLCTUV2Ufdd3TaHfVzzDjgqmlMIuAdJU8QeksNubFOp4n6QtSv696QGNqyZWRIYqyJw3OJrzlljOd4hlyJo6bxpmiR1S2HncKMewxNYWYdeua+mEr4ktKPRvE5Exws5riZWEHZ3MAPVFyvsUdlXD6pl9llgmL+ZwFHZ0ER7+aLetVtxoh42IiIhYY1g3QLUnfqLIUv/AWj5OPSo5fs32K+y0ss+5YWWvk9C1qY84s9Up4PZSnzVBD8L9pJtc7yDplnnHJmGFFYV3vXpZer++htmC3Zx73u+GhGATuDJTvUc5aG9GLbGuwk4XVgSQfVYOHRFoY9bULE3UTYlNnI210xptrZW77NCYNuXLWkq3scIKAGjopsgqypiNqBEBtj8dC/C4nXbdoVUM/rIDdWM2QFY5WduMsBuzcgKe+xybNBxRyLn5c3odhkKuJzxevIZd+qAz7BzCz5N5qElLcz9m3JLb9BN2ziQGIwwBqa5iBQy9+2AjCDuWYZclKFXbJVPYORl2CRpJhnltmdx51VM6IVRjmrAjgplIK14sQSSPVtjJv1kZdmUulEsqb6vT584MraBBOr1OAOp8U/OWWP7ZWhl2Bc+wU8SHpbCjRmT5/ji5yZVVOsPOIuQBx6rM95USr/blB64xZl6FnS6dKNj7pOd2CXteT4Yd0hQtEbTy+CNLbN/1SGVVNq2rsKMMO3mc2Pn3QmHHCTs6Hw1YYmvzGCcohV0l7N9m6YQ58eJT2JWLKuyOYYmtbEvsJhB21D63Fi2xJwGvwo4RdnQi91hilcLO0xJbKfvGAGFnH/A8Y6NlIYyBCjsCb82NiIiIiFgzWDdh/H6HBidCYTeQQ5cVUPdk8gX4IGNc6Ub5Qx6F3Zg1dYD8Gram5j0TgkPLjijsHHWeZ8BmrNcl3bLcZwHmLbH9RVy6JXYzMuwKT9OrKkNIxyyxKVOrmbZWajXtAyfd3Py7cIUdkW4dt4iOZtjZltiwllhAK926yl52XGFHIewtHVe0r7psfNnUVvaFZfZtAlSGnVW2kDlWzP7CBudcQBl2iad0wqtuswk/Ko2wcras+ILe9VsKuyxA5adKGzwqQbeh1f1+FXZEgFq+9jTlJs7kv2GTNJaXN9yOpdbaBx7V8tqCTX5lSYJJ4mk+tS2xzJZpKHHp+XTPCAxk2PHm0wxVLV6PyDZFTNQNZpWpsOPqO8BsiQU0EVO1FmGXcJI1M7a/5aUT/JplZdiV3QyALLOyizUcS6xU2Ml7WFu1TMcpHSaGUooVYGSplWHnU9htiCVWfZZFqo8XlmGXM2spfb5pzsYwPfmdAHQWLGXYdeZnbINHEBA5qCaTpMqdjhOyxBL2Jrna52XSsNKJ/rGCJtgswo4UozLDTikKu8Y5V3Mim1SBg1Ff1j4Wj8fz9mwUStnXKv4LWGvCjnnj5Ylczyavai1rAiPDTirsvBl2TGFHswqlWHZmtYnMjLpizyC+l7DjFqjwDDtbUXewEwm7iIiIiLWFamsV52pDucVa5PhMvV7WtZfS9dmvsOsvf3DWPahW43lw1o0eWzYdU+f5lnXspSMkI9vmQaKw8WzzYP7dcIadPztvM2b8CaIMwXQAJJIMGiPsOPnVyBs8It3GG2ZTRpyJZbsqTK3GCytaRfaFEVh5miorbmer1RawtXYeW+vYBHbrKOwYUTiSYVcn1nHF8v42XmFnW2IdO6qlbvMoJApb9coz7Bw7ab/CrnYy7CzSsEfl55JlqZp0z9HogPSA0onGIh29GXie5ftIyyJ0/T37gMgEoa5i57UxleE6g5FUuZNhx4QbgHHN8d6o0zVudkX+IjH3jZ1hl7gKu9Im5arWVGVBK5KcDDv5d1Iwzdjuz9FoMohtS8oVdj7lvpVhBwATVKbCjvaTfP8pFTBKglAr7Mzzot0ebpz7eOmEnWFHkRVeS+yaE3asIMQmhI0Mu7RQzzWcDQN2zkpeVxLHEuu/LvCJgblN2BFR26Ow22MZdmXSokzGCbuZUtiZ20NuwGnV4Khq0HKexIoeoO/HnClPbQLQwJAldoEMO74OY6zYrSthx75MTdsZQdanTmFHEt+2BqaXxWPDEkthpNwSKw6ColdhN2KJrXsIO8A8GQUq7GxFXVTYRURERKwxBjLsjKDl0Ew3NbEmSaSEkVB9ZJ91s9iMFlbwDDu3wIFu2vzZeT7SzbXi6pbYcLKvUtl5gdvsIQoVydg1UDuBqSD9mX3yc9qw0okiS10HgBzTtGMZdqkvD06MjaoAO21lEWctI7+G8u9MZd/UWP+YRTRN4CmdCCusADyEXaMz+8YG72Qx7lqbsAtYlsjTxlTYVSP24U2AUjHUJtmWElnm5L8NKOyUOkyq9Lz5cQEKPbIOOgo7v6XVydBjzykMW66eNLDhlk6wpltbYTdEuNlKRbRM4TeQgWdbk1nTLiBJ0QGFHe3naiMUdiaJ5i2dsC2xaa6uTcakAD1f/X9ilpoYGXamzdMtnRiwxDKFXdvq/DFF2NH3qNXHVuoo7CSRLT+rtu30PWXnUdjJDDsAmGAuW2KtYo2MCLu5aAIlS2ziV3qVFnFD7bfiRXQzfJZoOzaSzJ+dvyGWWH/phMcSmxWKkM2MfDqyqnoIOznxlcoYr5kk7GxilMCLFOgYah3CTnwOe5bCjltiTYVd//Ve2b77MuyqBtPKyvpvzPMkP/bntUlyezFoiQ2PCeMkY+1xn6w1YVe1rTFI3fSZPQdcxnz4qPjJFXY5lU5wS6w4CMqJWLZuO2OGaV63qrVlIUsssJTCrshS7LIcu0jYRURERKwxrIEEv8YaM/BqMOsj3QpHIaHCedMU3ploZbNwFWdcaZfmQ6QbL6zwZLp5l9U3LKm1zcayXrKPZ9j1F1YMteIKW2u/ndbIdaNluMLOk9mn8u/yzSLszBw6MRZJSLUWorAj8ksSZ0RkjeXfcbKvqayyCwwPqH22Vm6nHSKwRFurJAqt0okQ0k0RdnQzr5Ru49ZUssR2NankwvPvdIbd3PgZQvatO5yWWIuwU/lxA7YwZ9JAkV2tWzrhuWFTCjmLrErRo/JzGlI9hQsqL4wXX9D5y6ew8ysNC9Q6QH5AJeiSjnL5pGakZb+tOM9sws+05CZJYiqWezLwNkJhl2hyIEsTMzzfscTy4gO6UWfnGDtw3/6/lWEXWjoxtSyxPPNrzvYxZdupDDtDYdf6FXZy82vDEstLJ+R5pjyj9tUWKnEc2bnrzH6Ys/dXyyy9MYUd2YD59onPJWX2Yd4Sy56/ISVPPG9QEZ0+S2yaq+dmOfuOS/Wc79xFE1+pajuXRH1vhp2erOxV2MlrlZNhNynU514mTWDphF8Rt82O52nVoOk0WWufp+g7MGeqwDIf4EJslSwwzLX0vQw71vh3To0zR7JnQ3Eilti66YwL0qZnZzigUgkAuPZR8dNXOlH1K+wAYMpsscISyw5EGwMzZny2QZ1MRxR2gEnSRUtsRERExBqDml7l4KTroFqoVIU9z7BrfMRZxogkK2s2S/xZLz5LbOPaab2qMUOd5yrd1I1NsK3Vo3QbsfEOFUeMKfuKAdItKzyEnS/DzqeEVAPqDmjX/8a1yJgllo7DNizDrsi00s22l441zJqkG6nkxM9xO22iVAS0XtVOG2BrrRTpZmbnhTSuqvdlqfNmAeUPjW1rpRy6AFsrfRZJ41EFjthp1x2FTVQpws4qnRiwczrfZ26JXUBh524DkYYjGXYqP4wRdvI5QmE3XpzhnAszTbg5pRchlloiDI3SiYHijr6WWF9xR5LCzkRyykPWGbx0Ik0wSWi/TgYtsSrDzshRs8gK5/9sXQmzeWauJVbZXpnCbuJR2PHoJfo9vUbVtPr4tQk7Ur2Rwq7r9OfIr1dE3OQTJVTZSuZmhp2lsEM9R5YmSi1GltjCOj85hJ2hsOOfCwxLbNv5FHYe6+MawiydsDLs8hRFwhR28rlGg/uAws6+XtK1cax0gltiO+IVKssSaynsDnYKtf0FqoVKJ2xFHBG1U0lOG6UT1rmeW8XnPQSggaEMuwUssUb7MiPsaotoPy5WRtiJmRXxuG5bYyZ802f2HKSZVtERYTfxEHbUpAJowq7UX64Zs8XOKlY6MdgS62GoDUusKXMfwj4n7LbD2eSIiIiIiBsMK8MO0BkZxoDeN5vccALLvOEyCyuGChy44qw1XkO89BDp5ra1dl3nqtXGbK1eS2xY6YS3sCL3kZvDGXa03ozfjCtyRS87ZONN+Kz4ms/6A+LGzXYAKFJoYNYckPZSRbrJ0okmXGGnSDdVHBGWf5emCWpSyZEaMDD/jr++z4qbjQzA68RS3zBb6xhx1qnvoFU6gWxQFQhwws604p4mhZ1tic0C1W0AJ9xcO2dIhp0im6yG1n5LrD+/zauw86n8BlSCehv0ewgpnXAssSzDzrHkeklPrWJxtj/gM3AUgusMq9xgwpVCuamAMjLsKPrAsMQGKuxaU2HXIFPFC6p0ghETpLDbUvl2ZqsmIJy39LnTMTavW03ModHFDYxkpcPZq7DrOm0HzrdUFNQW5jLDzl86gWZulGpUkoboK50gTDiRw8tADDViqmMnNj7DzrXE8gw7+twLPnFIrj5fhp1V8DRtyYo8ZontMG/EuvossZM8ww5z7N22N2GEXR2UYddbOiGJ6K4DrhzVmrDrGuc8U3oVdgPXTJ/CbglLbJIkTDnMnC8rLl5daagFn30/1Qo7QBN0Vz4k/88tsdQSywg7eRCkeaEOIFNhx9pPbEssPzH6DnhWcR1qiQWiwi4iIiJiY0DXEDaQsJtei8ydmeXLInPLEIzMl5GmVzs0nbfFepVuA0RhE0z2afui19Y6aMVdRmHnZtgZ66UbAp4doxR2LrlZefLvjGXXPFcHMLPkaJCcBoYzJ4lW57VWa+oihRWdRfaNEXaAvknRCjtxozFHPph/x19fLUtkX5cjG7G4tEol55ZOjLfE+ksnQtR5nbNeuWxXjG7zusNRZpEdVSnsbLKrn2yyM+yM/LcBssyxc1JLLKxt6FGo8XOvahNUGXaellbPTaNjtWeWWOc9DJROOKQjmCV3wBbWa4lNPNsf8hmsMyxiyMiwI+UYkRdjCjs7w87et06GnVnKALAMO6Ml1lTYbfn+lqfCqgyLcGV27Kwz7YWAtpU2nLCj5/HxRVZqhZ2TYSffZ84Iu1Rn9NFEUGGRGqVF4BmEXaJdZWlilk54c8M2xRLrbYkV+3GS85bYHFP1ueuCh2GFnXkumcmYij5+Rn3PW6awS23CTr/mHfv6+L5tb0sTdl0d1BI7s3IaCWSJBcQxW8PjKLRbYhlZPRki7LwKu8UtsXy7K48ldu0UdgCMwe2pzrADtAX28gfET1lrDYC1xLoKO2SlUVNMmNX8QLRmAfj/vZbYxUsnAJOku/+W3dHnR0RERETcJFDpBLuJs1VyRZawmdlhAosUEgbZ5yXs9CSQTX5VpBhLxu2lNlFojBFG1Hk+0q1qhkg3n7KP599Zba2LtNM6tla2jJcY9WXYccKODRbXFKJ0wsqwk5bYzrZ2eVBZ5FdCltgR0s3IkrPttMn4gNoh3RYg+2yVXKvIvnHiTFlilZ1W21rHZtsdhR1X541aYsV6E6t04jQp7Gw7amaXTjTmTRyHrRBW6rSk8Vhq+zPs7G0ge1/hZMCZx5kRHeSzpI4o9MRr+FWCBbf1DrRFalvwkEIvhLS0VYqtawke2v4NiAIwstISK8NOqnOuHx7iW/7rW/HIZZkfZmTYcdLIOl85Cjst2BC5bJLQYrfp/tIJk5jwFVJwO6lBmLJjj2fmqU1O2LFit89zVZKjsEv13x2FXYU8S90MO5ugK7L+/zPyME8TrQ5khR9ehd2aT44ZBSG5ZYnNWOlEWujPvUj1eUZ9793vnX3NO2opO3A4w65iGXZqIoq4jUQfm7dzwm6fK+wqTdgNZtiJ74ytiCuy1PgsW8MSa55nFy6dyH0FoYtbYgG9H3mGneFeWQHCNX8hL5YlQCU2smxJUpsoZv9UgRR2NNvAWnL8LbEkMS/FiWdahxN2xkzGkCW2WUhhd/FAZ/E9+dYzA8+MiIiIiLipkDfwiVdhx2Yn7cEbWxZppgYwdMNlLusZ2DLbQV+GnaHO8zXMZlxx1hrLApyw47ZWpnSTg/nWq5IbXnZIYady6Az7sL5W2wUd/HXyXO4vnqXCSyfQv15hY0kAdGt/EwGIcdyR5QBQCrt8ceIstGEW4GSfafNchHRT6rwqnLBrkgLooFRqnbKmBhBniXmz1dWMOBtT56UWibyIOo8ssa15U30aMuxKR9lF6jgrJyggv00r7HT+Wpgd1SLLbFuu07JqjsP5Z9C0HYoMLMPOo5Dzlk7YGXRL2notS6zYB3QzvIwl1mfJ9bTcbqTCrkGWsQw7Rti97f2P4EeufRDVe9+PfwoYpJHxnUulaqpPwcNz2RLWomoQduL1NDHRMqWVqbCbVo1XZVSyz79LUyQYIOw4ucuz0gGTsGMKu0lSifdtv0+mGMsSUUYAAPPOzMsjbNuEnWGJ1URqmpqNuv6WWE9sxpqh6zpFsJZGhh1vidVKNfrct4pMPJdHcHkVdubxRqUTfdcFrng8nIv9NqSw4x/fbXsTNS7IUbMMu/7rrt2EzLFTZLg6E6+hW2IbR8msLLE1s8QOZdgpS6zfjbIIjGxIiZpPhq8AJ2OJZQq7TZ/V60W5Z/6fK+wo366e6kw5dmBpyXKPJdYm7OwTow0m215EYfeaZ9yhHp/bjRl2EREREWsLeW5P2WBMEXb1mCVWD2htW5dXnedtmNWW2MpqmM3SvmX1jZtaLyns2A2bUqv5yL4e0o22e0wlZ5ds8NdJfWpEVvCk85bc9Wa84MNR2Gk7rVedlyb+z2lN4SudSNtw6wiRbq1F2DUhKjnL1orAdloAntbUcLKvsYhvg3QLVbrV5rIV8tH8u04qCp0cum6cdCOLsSJTm3CScd2RK6LIIqpkPpJrx+wn3NR5hGfYBTSsqskOZUclws+62ey56ePHjaMUDCx96M+gC7XU2ipBbQvWhNuQJdZvKy68hJ+7vFMess4wSDQrw06KJ6qZIC8euXRdLeNtiQVMW6ytNmLXzzxNkSXy+izFL0WmxS86w84l5UhN13aaaOENq0XOlECGws7NPzcVdvpad21W49HLV+WTSsHWMIWdYYlVCjudyVYk7Hramdl6hO3SvIfd8ins2tponEWS+bmHDbDEVk0HcsmLDDu3dEJbYguzHdj+nnvIpsayxB618rPvUXzza811SZYpwm4uj3V2DL/o/gsAgHM7BQ52SrX9eVcFWWIrri60YJRa8Agw61zP1aWqdCLIEutriV2MsPNZ/Y1CtxVgxQo7vcGU87Lpg4ReTCxFmqGwYy2y9RQod4wL2JYKBdVs/7xudVaBPeOu/p/4lXM8W6Cjk+44F/viBy/g+77iBYaUNSIiIiJiDaEssQXSRAzI6caRCDSTdOMklL4BsxUSc66wG8z0YARWbZJ9ZZb6rbiNHqjZyg5uiRq2xOaD9tKxZTMPcUbjk5Ra2w2Fnc5m8+WS0OuUPkUiV9h1rvWLbrJzIuya2UYQdiJLzrTEZmpMM26JrZPSUKslzQKkW0oqOdPmOVZYoZ7T6WW6ZnE7rSbsJPmVFKOuESIiyZq6SNlF4yjsdOnEqMIuI4WdlZ3X5b03ZpuCPjuqQ5Y1A+o0WzErz1llYP6bKnyobYUetcQOE25caVE7xGPj5vANqAQdS2zCCLMh0tG2tHKFXogltsdWnBkKvyFLrrX96wxGDuSFlWEnyQpS3WWJnhTzZtgBJmFhZ9px+62R8Sb2F1cKTVhLrKG0gknOXT4U2+azxFZNZ5ROeBV2dN3teOlEha/6/t/G5Q++HT+bQZ//c7t0Ym78no8tylR/9nNqK7VUSDvlkMJOE+NZkSKDJo+1wo4/3yxwWEcQ8QoQCWdef8osZeUNhconFAq7ngITBvuap0onRiyxAHB9rolCACwrT6/nK156P/a3c7z+2RflczVhR9+ROil6SSdj4tjCmYleqizlWIJn2GWmws60g4co7OTYousGz51DcJTH0GO/9bTEshO510d+mlBahJ2RYccIu+pI/J9dwFQld8UVdgGW2KwEfAPFJTPsAOBTn3p70PMiIiIiIm4iLMVZy8qdKm4nsAZ64jGzeVo3TIZsf1BxVjo3W2b+nW+9mvzqW2+eJkjJVmkUVvS3tZoNs6EZdh6lG8+J6TpxffWQm7VHYSfes2UTYlayAtbNPbQ6yNjXa95cB4jtVROKVH7SMbXJCJokBzpNeinCLmAWW1tTibCTg/+AAXUtl+2sZcPIPnP2nV6jxviy9L5Uzp9cdhaSJSfHc2Rr7eo5EhDZN0y6tY7CTrxGCFG47ihtZVamiSIAHjupOwa2S3N4k6FbWuFb3iLhmaVWxf+0LQCTDCOkiTjFdJ2bYZcHZtA55zNFuNWa1AlQyNmWVjPHb9xWbNuCC18G3sD21xuWYZem/gw7+p22ZWb+plLAJOnse0iuGst0iypZALlSaGIQE7bCTj/vylTaKRn5wonvLs2QAEjR6tIJdu9I2991QJvkSAF0bY3feu9jeEoyBzLo87+8791K5uI4tksnGGE3yRipISe27PNTmCVWNCtzslRFZfBTpW+MsGbgjrsJt8TWWmFnWGIPZTtwkfarNRlai8Q7Ui2xfYSd/v3h3FLYEWHHzi9ndwp85Sc9wLZB/C1jCrsqyXtJp9lA5tweU9hNJiUwhWyJNScW6JiZVqEZdhZh1zZQ5+4FFXb2ZLYoFhJ/swtVlsVqLbHM8uL1kZ8m2Aq7rbP6cZrpC3V9ZJ4kssLIGCBMqwbVGGHXNzDmhN0CGXYRERERERsCTwnDcEusJ5ctzZ0sKEVA5X2kmybsaOCvlH0LqPP61ptnTDnuI92ywrGXGi30Kodu8Qy7ZKjpNSsc+xYnCr0WYrafC2tf8ce9+2tNkbOWWCKfMklGJUGEHY2HZOkEKc/S8WWJhOqsIoWQ/Ls+W6vdmOdfL+X1mGq1ELJPKQcbTboBwtYammGXyGXbRqvzRltiqTmVFHanunRCWzEBbontJ5uc5mZuiXUKH0Ly3yinibfMsvOuNQ5PkkTdvOnX4IRdgCXVLm1gpRNODt9AcYZbGhFmiXUsrSzDrrAJx01vic20qixPWYZdxgk7aclmxQeG8pyDnytLq+hPqbVr2XwqM94kscIVTzxc31YSJUmiSIorR1Jhx1R3PMNOK+xa1bbsU9gBUIKSthbv17AHs58TVMgSaJuhp3SiTPQ1ca4ssVaGna2w67HEcjViv8Ju/Qk7TjAlSaJVcz2WWKNQxFFreiyxlpr9qBlW2CVJoj7/azOrRKeSltihOAwi7FpN2M27/munMZa0cGZLL7dd0uSua4mlY6ZuO2UHH7bE0j4mwo6duxfNsLMnpNm4b1WW2JUSdgUbVDddj4f/tIATdFtnXYJMNcVOzRuntDB81oRZ3aKxQp0VxjzVfJZ/QYVdRERERMQGgNmUeCM7wG2tiWvTBAYtsWqg1Jer5rHEzmsP6TaUJZeV2k7mZOcxa6nPmpqVDunGyTelsPORjB47bdd16mY3L0t3GfZ+3X3FiEJfqy4n+6ySDYArITcrwy5PdUts01RA26p2TmUrHkCdmmo1Up4lIQo7Nflp22nH19ul1j6mxtcAKy69vlLJUcNsAFHYKaWbpc5LCqSBxRFEunVVuDqvk9ucWpbY2SlQ2LnKLq2wU/leI5YmO7+TnlMmtfq+DuXH9ZFdhh2Vn/8GWlZday8jDYcUaqQSdFpia7b8+D7wZdgFWWKdfSAVdknjIU19Cj+WobbuUIS/UNj5MuwmEN81XnxgXBc5hgg7dv0UuWwysqKjDDtO2GmXFgk/eMbbliQpLh9Jco2RFgW7hnfyPjEzLLGZ81wAaKgRVH62pUPYbcn9wTLLAK/CziDsepReg5ZYZlUustRqifWoGzfCEisJOPqcM3ObJ07pxGIKO3uiaUpW5AGOhj7/w5l1PlIKu4GJr5yuRZX63lQDps6h0gmusNuaMDeGNbnCVZmXDrWVeGwb0bXinGdxNYugL98ZGN7Hi2ClbJoaVDetYXc5lTijCxuwd9H9OzXFVofmgDwrvQq7WcUtsX2EXc8gMyrsIiIiIk43PI2rtVLYjSi32A2UbWs1bZoD9lJGYNWWss/MsPOTfUVurtdY1jcD7lGr0fusDYWdJ4eOW1Ot92tYFfhA1wrq91liOflWchuwpyXWfr8AULWefb3GNxGEPEuUA6Ct5s6YZgx2a6pSjwUs20u6hay3h+xrApZtreOZVHIhRRl2lly3QNkFEQGKmJSNfPOugC/fx0CuVQ18vXPkTkbUpmGI6NJE0bClyVHbGpZYi3DzFjZYZFOqyTInv65nG5zzgjdDrl+hphV25ntYtOXVu/4QS6yj8OPrt/aBbx8qYccGEHZGEYSdYSfeN+WKZR7SyLlRD1HYtRWyNNE2QqlAMyyxrLjQl9VFajSyxPIMO058k8UxT/wKO779lYxESOTzDLUh7RMIArMA+w7YpRP1DGUqJ8+SFHVLllhLYVeYx05fS6xQ2Gny2evuyzwTgmsGZW0mNaRdOpFlum01LZgVOnMJOw/RbijSkwwkmhuaBCIR1vW5pTqm0olBhZ2+fm5JUnuG5Uon9g3CjsZ7jGCTfEeZp+pzv3Sk23X7t5FP2M5Gz91DKCxLrEHYraPCLmeD+cbHcp8m7N/JHvsIO94Ua1piJ8xnTZjV3BJrVU83/bNVAKwMO3niigq7iIiIiNMDTwlDbeXBGYSdoVbTN1D2ja9SffHcFC/pVpp2GuibrlErbla66zUssXJw1LVwmtXZsrW1XrE7aL1jTa8+ss+nsOu3xPJBWMGtvLRMq/dzbinsuq6zFImbo7DLmCW2rWfgrWppMV5aVVvWVKUAC7HTEmFXW8sGzICTWi1RpRPhZRdKYbeEOo8+27QxCbuQZTtSJtA2V7p0YjQLR948p50YC7aqdGK8YXbdUebmuYcTdmq/GJamoYZT006aw1P4EKQuk6SNj/ADegi3AUusU9rQr1Crrf1gkobjGXhehV+IJdb5HDwttQP3LGXuRhSsLZhaPU14ht2WoSgDzAw7Q0nNEZhhlzGFHbXEGqUTXkts5vxdWWINhR3LsJOquUnaMbFHzp7LLLFS6SeIva5fYZdUKDr+PXQtsYUi7DIWE2Fl2DkKO26JlY+7FoXVEuvlHljb77qCMu3V+xxpidWlEx6Fnee6alhiy121n3yKNvUy8jO5TuwejbXm18TPoWtwpp+byVbgIcJuSGHHSye2DYWde8zScaMLV4YUduz7WM/09SNJFxY9ORnN3BK7Ih5stYSdUTqx2jrbtcP+Xfrx2bvcv+eSsKuO2GxZDiSJbolllthpNWCJtcM7bXAL1MDsYERExApx+Bjww38R+J3vv9lbEvFEAMuwcxpXeYW9T7nlVY0RgUV5O0kP6caLI0xL7Nwg3XzrZSq5QUssGxzRjUPLSTd7MOQh3XwEZVroqA7LPgwARc7yZlUOnbuvtBpRL5ulCRxlIGuotAkGruzrVSSuKYosZRlGlc51A5AFWGLbxFS6KdItROlmkW4qFy6gnbaz1GqLtNN2inRbPDsPlsJO5d8tYqdVVlyxbBVgpwXPZGzmqp22Qj5sDdoAKHs6lbjI81yWtC7RBQzmv2mFHbOTOqUVAXZSRvgVjjout5LvBZzyDK9SMCCDzn4PRkvseA6f3ZTrVch5W2J7bMGGJXdIIegqj9cWlk1VqcryUhFRRFzxltWqjwyhqCQAKHfMv7EMuywRnycATCVhV+T6u89jlQxrpMSWrbBjVkF+/HUyy7NIOy9RzXPMeO5njmY4w67zfAd46URChF1u5u8ycEtsniYmoWeQmylT2J0CSywRTLlL2BVSzdmkBaY1s0LbGXb2/8GU6gC6Yse/nyzQZ6IUdoqEI4VdAGE3vaJ+NR0obCKnh08Rt88y7Ha2mMLO06ZNx81j0hI7KQaItywX5BwgrtFj4qgBOJPZbP+OtcqHYsUKOx3oevoVdkxVt3+3+3dliT1yDgIlZ670zPusbpTkeGFLLLcxDcwORkRErBA//k3AH/4w8JPffLO3JOKJAK6ws276FHHWm0PnWmLnliU2T9Me0m3cEjteOlGqGw5/wyy7Xinyi2fJ+ZVuWZogGbMA5/5le7fb22xrEaMZBUNbZB8nGa0bU04ymutd3yBsQpoA885V2M26MKslEVVEui2isGutGxdFZAVYVrSttTLWH2R3oaZXpbxcwMarArfNYyqIsJNjx0zZaWV2XoAVN+EkZjMzLbEbPhbvU4YVRvbbsKUpT22yi1liU+s1PGNoh2xakKwCBiyxSRPU8uqShse1xOriASeHz5uh51+/v/Sif/mNsMQyoifrscROpE3RII36Mux2zuvHAxl2Rcqaxb0ZdvoeUhE9hU9hJ7bN1xI7Zwq7Mm2NCUEO9b3r9GtkaNX7dlpiMdcKO34+UufxCqUkI9sk691XPJNvf7swSQ9WUpVniZFhR1m1piXWuk6vIZxWU4/CjiyxNXJMK0bw8fNENhFV1BaMRnZGFg9dF+hYOZQKO1UwNcZJ8L/NBGHXdglmA6UTQwq7B2/VatQ7z++JB22lP0+usJPHDU2O7pYjXAgvnhg5dw+h10GywuvuSgm7ggVh174vzWnC2XuAF30t8KRXAZ/whe7faSalZoSdPAi0wk58Ceq2Q9uBZdj1tMT2lk6wQannAI6IiDgBXHq/fnz42M3bjognBhhhZzdSeTPs2lqPWgby4BaxxLo5HawNj1txab2MOLOtYNpOm5jXK8eaWjoqOWN8wcsu1Pulbc5715smckLRViQyO62thtHWYzmusdttubKvh1QFNs8SmyQJGqmw6JpKKcbmKLwDbBtaJUekGx3LATPZRPZJAitVn22Iwo6UbtROu4AlltR5VJBRL6CwU4Hb8n3KZbuA9Sac7Ou6hey0RutxPWeE3XjD7LqDbmSVMoyVTniz3zw3rfSdbByFXVjDqrZzWmRV0kAJQ0ZUGkOW1CKAsHMstV5L7ADp6Cj8SKFXu+sfVOi5pKUqGRy4Z3GadtcZjOjJ0tRUlTELKNAhS9zSCefcuH1OP+61xFYoEp57KvO5OGEnRR9HVaOIji2mTCKy67KnJVYRxnWnSifKtPPaC/l7qBlhV6DGJKFJiFLvE0iFnZqQ4UQSK52QhGTHFHG23Z/bIJ1TF7O45kZLbJ/CTqsX1xU6k44IO1OBz0snauTq+Y7Crieigpc0dTkj7AZckHQ+uT6zyFnC0MQXPVcq7GYo1OSwD4ZLxMJT79xTj++7dV88aGovybxtEXR2eYm7nSxyY4xrGYAvKxlYLQe2UlYnYxcirbDbbBl+L5IEeO0/6v87fYGqqXMQ2KUTNEOiCDv7pEKWWMrFs6FORnORAcR/FxERcTKgpiQAePRd5uxpRMSqwaxaTgkDtxPY5FdeWqSbDLO2ml4Lo+nVl0PnrtewxGaWSi4rjOw8fcNtN9uOKOxSTw6doewrzGWzwrCE6fw7c71KEWPbgLk6r/VbYtWyyk5LNl49gFTv18oZBOTNyQZZYgGolrmu0jPRFbLxIgS4hB3d0KXFOAnVWVlySmGXB5B9VpZc0oar5Ig4U2rANrydVi0rs+TomGoWyLBLIBtPF7DTFnmGWZdjktRCYUfKvqRYmS3nZkGde2qfum08uw0w71EAGGSVk0E3pLCjOBtuxcrs7M0ehZ1NWGU+wq5/G8q8bz94mmo920DEj53Dl/sIPy/hZk7aaEuup2l3wJa8EZZYblNNYWbYsfdWojaKDyp7YodgEHZ9pRMNilRnrc1bT+mEFH1cnerrtFdhJ//uU9jVbYuWLLFJ23vcq2sv9OtnaJXaq0Ih/sIz7JT6jpFHjLDLlcKuv1GXE27XZtY9MZsoy9IEGbXOpikjShj34Cu1WjM4WYTWuIQTk7MuYwo7i7Dz2GEBoMo1Qdwxa/ZQgymdE8kSmyxC2NHfppfFNqNQ79G7fWry171O3X9hFxfPbuGoavCkO+R9VjNnJLNriSXYWYgO8i0Al4XCjl4vQPlvw42poVi41XFgK2V1cjZ7VZ8Au7hRIHKtOnTk6VuqdKKVP6XSrq8llgi7voOIbpToeUAk7CIiThrXP6YfP/5e4J4X3rRNiXgCgGfYWTbPuUG6mTlWyEuThMoozNpU5xkqua4Vg5c0M65furp+wBJL6zUIu1KNBea1Z0DDbTitm2Fnh70bs+icyFDr1QQlDZjmNtlHY5M+S2xWIm/NQZgOyCbCrl+dRwPhuRrAtWqbU77da5yrw1FJS2ZXzxdW2BFRlbRzoKm1hSkbL6wgYo6IM/qZBJBudh6cIu4WyL8jcpEIwxArrnHT1My0wi6EKLSXJVVgQMNskYlykAlqsc7KUsFsMArre8yJKm0lDSPLbLLKn2HnyW/LzfMfP/dsZfK8NWIXs4l8rrAjBd8yllg/cdlfWmHn8JWBhJ8iLR1bceOWTgwVd7T9N+9rA1thlzAikn1Pt5LKyLDTCvABhd3Wgfk3di3hCrsZZdh5LLHUhAmYCjv6OwXvcxLDzLATz5sMEXbq89avzzPsqqTEFqD2xxbmWmFnWDX1BFUp31+XZObkWw/oXlmBShVbccz6GnozTvxsgCV2rCU2SRJMJNE571LFG0zs0ok+wq7QBHHLHg8p7OicqE93NmE3ZImVz5WW2ClKNfbzwbEE85dKE/z0X/1ktB2w3XxcvonKe56xCbtgS2w91/nJSxF21qRyT5nKcbBS+RtvrmtYxswTErwltrEJO5k/UJsKu5RbezjqqVy+5yCiQUPNFD+RsIuIODnUc2B6Sf//6PGbtikRTxAw1YUtv1fkV2oRZ61NJHkssYo4S8wbNEVCcfLLb4kVKrmBZdPCuVGr+Yxq4itw4ITdwGDIt82t+35r2z5MA8Ne0s3XqGspJ+xrdutT9klS1W4O3CBLLABUKRF22jUw7/Igwo4UbUkzB2+YdWbsfbBUchl9tkHLkq1VZtgtkH9Hn21Ky4bk9kgY76ueqWVDiLPUWnaRdto8SzGHdlxQYUWIOm/dMURUlaRKGfmMVIC+1xIbkB9nK/TYc7ZI5TNCGqqJC0vl58+g8xF2FnGplq9d4nLA0urbj2GWWCuDjrXEqpvtgO2vN0JhxzPsYGbYsfd2+45py3SuE4SEnSvveKa1Ln39KxNNbEylwo6/FqmwLh1qBR1X8pAo5KpUpm0z9R0vb2kl8ZUbpRMm4aE+7xYmuSz3RS0nEihCYIIKOZVO8HMZt8SyDLtqID7rRfcLNdVnPPMO8w9Woy7f9y0RdkbmnSebd80wt0snaH+xgqdSlk7Mu1zxBlt5FkTY1YW2lbbMrZcNKK/twobUVrUPXVdomyR/Me1KIxbEhuG48OBgp8T53VLvl7b2RoBtFYsq7Gg/T1nB53EUdqajYpUc2IoVdsTEt0ENJKcayhJ76MjDVcOPnDWYVRToSBeHHsKuV2Enl6um+neRsIuIODkcftz8/1HMsIs4YbAZcKdxlefQ8QG3h3Qr8iNjmaqXdJuLPBR281dKFYnb9NpH9rE8OMvKpYsyGHHGi5O4Om9oMMS32dPWWqibdIug9LTX2fuqbM2bS2dQaWfY+dSIlipQLbthltg6KYEOIgqAKeyGZugJLVe6MSeAcwPggWprbSugbYXNFIFkn6XOy5RKbnxZIs7SrgHaRr1GiJ02zc3vkVLnBZBuWcZsrTVT2AWst0gTzMGOqwXIvnVHnzouT1pspTZZ1pMfZ5NNRv5aiB1UbEPXCSdRlmbokCBBh63UVtgFWmIVCcJKH9ikQd/yej+QrdGnkPMtb1lSmSVWEW4B+8BXvOGWZgSUVqwzWK6ck2GXpqiRI0eNW7eBbKo/z6ovQH+iSRNDbQcYKrCCWlSRgMRlipSGmUkHuKTEJO//Oz/+WqnZKZO2N8NOfV5tq67RpsJObHeTTZACmGCO1Fc6YVhixZtqmcLOZx385298Hn70LR/E5z3PKnakbexE9iSpG7sk9XMPat82WFf0W2L1+KCQ73PaZZjKBnBHYdeTYVczS2wrM+zSBIPN41vWcZTaZODQxJcV4XUchZ21EfoxcR7sPLc3MY/f0Qw7XjpBkWIhcRsWdJkQTSp7rNnHxEpZHR7oeupbYsegLLFTZ7bKzrAjuW+WF0CNAUtsj32EbliqQ/a7SNhFRJwY7JKJWDoRcdJgNiWn+bS11GqZzK1rZAGEWrZ0yT7DEjtMuhWZVKmpHDpGQiWSPOPtXUbpRE8Ona10ay2S0UO6GYOhNBUWma7x21qZosDZV/I55nrZNre2ndZSyTmqQJ8K0kOMGutd31wdDtVSylpi5yiMfKReyDFKSsckRGtclg8M+AmqwGFukpsBhB3lwZEqj24kk5ABOX/9Zr5Q2UXOSbdmrnPwAkg3oZIrpK11ulBRRpGlos03gRGifZoIO9vKCQDbuVWuM6Ju87XEFo6d1P2cOTldNS2yIkOb5sjaCpPUtvKHWWK7NEcCypAbV/mVzn7wWWLHFXYOaZk0ri14gZZYbwafj/Czm3bXGaqQqEaWJGaGHYS6LO8EYZc/ziyxfSTUMz8P+NBbgCe/2l1XymyeTIHmKLPhEnI2KTGkMuLEglLYJVxh57fE1k2njtUsaXG2bIFORyWQwm4rqZAPlk5oQrJNcveaynDLmQm++pMfdH5vKuxSlR9ImXxiuz0Ku3W2xFYWYeUl7MRnNGsyS2HHM+z8Wfdt4RJ2Y/lq9nGUlQtk2DmEXaFchT70FrXY4OdE4jzYMbu/rbepzNLx1+OlE0TYLaOwc8a3a26JzdiJ+NS3xI5h0BJrtsTSQawGr05LbGiGHVfYjbDKERERy2N+zfx/tMRGnDR4hp0ioSjDzlJvpUxlw20gnEjy5dClmbbt2MTZmCUWcFVjTGnhrtciztgNi1i2v+yiofGFYy+1iUJmTW1N4kyXTvTn0LnL9uxnj8LOvrGt7AHchlliayJ96qma2T5CuZAlVpBuRPblyMdm0wGkPEuu4eq8AJUc2VqlSk5nK4Wo8yxb6wKkW5EzpRuzxIZk2JVZgpln2XBLLH0HZ0iaBZpt1xz0vZlbRBEAbDvqtr6GVis/jVli8wUaTgH9faZswW1H5Rdmie1SIk3aMEtrHmCpDWiZnVsKuzLYEkv70FTYTZIa6v5+YPncOqeuNdT5vUKWdIKAB9S5gciqW7bActQy91xPyCeirPApnz6wrpoRWpk5oSYxyS1CrhhW2PVl2LWgltihDDumSmWNxGcLOfaQ55smJUtsz+RGryV2CSUSPbcVCjvKRK0ZpWFk2G1AXmx/S6zeZiLsjtpMCX62CisGpee62E721eMmE/zEGD9jH0eprd4bup6xYgsAmI0p7AZaYs11snMKFf+xY/YsI+x2JgE8CJGdzWycaxmAHVVwEi7TlRJ2BftiP+EVdsRyV4eaSJMknmOJlQdxxvNwOjb7NKqwkwcrP3g3vBEsImKt4RB2UWEXccJglhX7pokItNwhziqTEMpKrc6rbQLLQyS1rQ7izQpH3eGSUNYgkykt7HZBtd40hPzqy+zryZLzkH11YxOUI6UTvI23tvLvxkonUtcS61pxN8sSSzdkaGZqrHHUlUGW2E6VTlQqkye0sIJIrgQdMNcugpDSCaPUgp2zQ+y0GVeHNHOl0gsh3YrUzJJbpNnWzKHTRGHIskXmJwrbJRQD6wbXSsoUdqqhdZiw4y4g/hp54lGnDeSvie0Qr0FkKAXCj2+DeT4iVVCOWp2bwyypRDoSidLoc9qAJZaKLTRpybMAbUts/z5o2k7khbFtnEgFdkiGXdV06Lo1V9mx61nRMbJHEXbi7+e3OjPDzj7Xh8AonZCEHTJ3Mg7DllfAzR7zZtg1OsPObIk1l83ZRFsntzFDizO5LEBwCLtKT4wYCjt9vcsZYVfb448Q9GTYtazJ1iCjMksJv4aY2Rl2dI1i4wN6n9M2VfzBpMjMxuHCr7DrSq2wq7ZENuAYYeco7JzSiSGFnUXYdSMtsXKMNarYNyyxxHno7TAIuyKAsONZgXX4pJyNwlJOh5SpLIqVEnZ65iS2xBqWWCuDjvIHplbpRM6/DPzEMpZhp0on5POiHTYi4mQxswi7aImNOGmwgN0+4sxr8+Q2kKwcIN1sdZ69rKuSc24mbKXbQOlE1WuJrc1ls9IJOm/sWfk0N5dhxFluKXOcgVTfNmelc3PsEpTWNrMb5VLdmFuf0cAM+jqDFHZJPVVWlCnKIEtsy62pchZ7htxVoHiQ8HGRJN3mXYYiYDCeFmzgPeOEXRhxNuu0e2GR7LyCK93qGbPEhthpE8w6jzov1BLLiEI6toJKNtYcTnZamiqyS+fH9beTAqYLSPxioHDBc9OWpQnolkadi4iwS93zlvd9WFlHTaJJkKDiCydDzvce+hV6qvWTbp5ZBl0I4WfYgtvW2Ea3eKM/Qw9gxOm6ghdBgNvxxUQAfdfOT4AsYZbYZRoieYadJGYarrDjLbBWhp1jiXUIPWYVzfTnb1pi/Rl2/NrbyWN1O+uUqpXOkXVKlti5/3zHiBFOSNb2BFoI1OcibNyZR2GX+kon1piwU6UTdF1T4xKtKs+lJfuoSdV4ZitPga2z+oV6FXb6OdfueYV46qgl1vx7XlqioSHltkXYTVEOE3ahlliKXgF00SYjmU2FXQAXwssxjqOwsy2xtgtkBTgRS2zd8Ay7la5ic6AssTqgWdVeS4UdZdeRtDXL2cFlEHaBlliPPDQiIuIEQGoNkplHS2zESYOXThAJ5SuOAEz1lmGJzZwbPvpZOsu66rxRSyy34nadobTgM/vmNi+SB2cuG2aJ9RNnub1etaxHFWgXVtgKO1vZZxCFPe93Qy2xSTPTzW+YaMJ1AKSG46UTFfIgBYpRTDG7AkCq8wImgw0V3uyqfhysdJPH8/y6/kNQDl2CqpM3EfVUWHKBIMKu7CX7xkm3PEs0YceWbdPToLBzywpaRSAsprCz1Wklt5OqpsAeS6s1aUHbMLEtsT3jcPvGrpGqIGHLTazzprsNTobdYMusz1Jrbr+RgWfbgn2WWPadrZvOeI5DnPosuR6V4tqCXQszqbBrkKrPdi6J9YNJp3LUhMIukHzgUNeh2lCgzT0FFvYkCSfkAFdh12+JFa9TJM2oJbZiirwzRYetROwPmlzgCjt9z+rLsNOlE02SL2mJ1dfdPE0VYdcySsPMsFv/yTFHYWdP6LWtep+XK/3etooM2DrQL9STYZdMzuDvVV+KHzn/tbh28FSxilFLrEUEb5kk3LAl1tyOa9getMTOQksn+HpHLLG374e30KOZsXP/Ego767ysi9HWVGGn5eYtmwF/girsVEvskaOQs0snvAo7fmJRy4+UTkSFXUTEjQGpNQ7uFT+jJTbipKEG1P0WUZewq8yb2CRxstXmQ0SSQfZxlVwfCcWsqXzSiWW61WoGUm6zUsnJwWHjKlXsbXbGF44V15dD12Nr7W2J7bfEljZhN0QU9rbTrv9NBAeRPkk9Uwq7o64MGuOROixFq5add0UQ2ZflJepOPk+SbnPkQTfDRc5UcnKSpe5S5AFlFyUnvwyyL0Rhl2AKeVxNL7NlA8i+lGfYTVUeVEizbZGmmHY6azCVY8JTaYkF0Mjv33agHbW01G3DDak9r8EUSgDQJLYldnh5e/KhkSRImbRIksQ5b/Ytr25+JemYJ8wSO0Aa8ugivp0ig27cFswVI3VjWWLtz8Gr8LMUeusMlmFXduI9VdCRQzN5fjgoW91UmmZsYmcRhZ1WxXMFmqOehyA9+X60rX+OZdZjia2aVpPFQ6UT7DpGhN1uAZXnN5XnV7IHT8DGHPyelduL4VpiF1LYJTrvNks7pIm0ITJLrL8ldn2vtZRhV/aNS9i2Pz7VRPckT4HtA/1CPdenMkvxfc1n4Cf3vxDEk49NetkKu8n2Ii2xJrl3rdvWuZse9OY++qBESjIig52nzu7obbrzrJ+8NEDHKCtpWkphl9N52Sw3C5lYDMWKFXY0G80UdiuUA24U6GA1CDupsJMnTyLqZqSwK9jBv5DCjlpiI2EXEXFDMJc3cETYTS9roiEi4iSgLCuZc/M6qDizbr6cZWkG357ZbdmySOR67SKFPqLQavT05N8p5QDlNtlqNU5+pSZRqCI3HKWbmyWnQtZra5tTa2DsKdkYt8RaNwKNJlXtzD51Y+K0wK3vTQQHKSgSlmE3DSyd6PjYRaqRjzAJGszmWYojyOVl9MAU5aidBxDHpSK/ppcAhGfn5caymnTLgrLk+DY/qn7f9agf7PWqZWdXlRW3DVi2yBO97Pw6skZ8TnW+M7DUZkCTbfpmlcgypewaaDcF9M2wJruGWmJ7iius0gSytIZm2OXWOaWRpE9pF2f0vEZfS2vps8QOWGrbTk58cMLN2Y8eSyz7zs6bFkgS1LQPMrspd7i4o94YhV2tctnm0PuUFHb7RasUdg0yV3m+0LrmyEFkrlbr2cojTsot1BLLM+yUwq7tJey0JbZTatLdvBPEHDRhV6fy/hZzrXwy2kt1Jhu14Dbg5OYiCjv5froGJTQJ1MiJnSxNBPmtnq/Vi+sKnUk3EtUBTdjlaSL2G1fY7Vzwvr7KLm5atc/H+Bn7ONqaWNegIcIuTY3Pf0xhR2SeTTZ7YZ/X2P/vPqe3cbccj83QxyVX2C1fOkHXBT1GXVPCjltPYoYdsbaeDLvcVNhNlRR2jLAbKZ2ooyU2IuKGgBR2Z+/Wv+NKiojl0FTAB99slu4sgq4z8wTrGfCH/w34168A/ujHRIkC/X12Ffjw74vHf/DDwI//FeBj7zjW5p8omGqitNRqrvLLY4mV1wVNnJnkV+FTflnqPFvdMahW40RUpgkW2yLqKM58xRG5eZOq7QY9lliPSk6TfRZR6LTEeiyxFkGpyz0o/4TUedoK1NeKWzjbvBmWWFJppbx0ApNAwo6NXeT3L7Rh1lCrSfLrqJsEzcTnWYqpIs6IKAxTBeZZgqPOJN0OuwnyfPwmQKzX3OZpV5ixJz0os5StV5/L2iyA7EtTHNF6j/iyPWPHDQIvOyBBgFK3BebHEemhGlLlebJIGn2jSOeBHmJWnwPlNhDh5ijs+kjDHkusnf/Gts+3/sp6Dzm3tA4QZkYGXdMurJBLksRpz6Z94KoM3eV9OYBrCzYRVEiF3TzR74nIqr28UQq7qkvdYqNF1tXUBqE181hiAWCX5XPZpRPcFggMKOxkI3w+VDqR8udLhV0uCGIAOJKkJUUmbCWVn7DjlliysCaZzvpahCvglthEH0OksHOsnhuQYactsXaGnZXLC+AxSSmocxZX2J1/wPv6fOzmax72gRN2kzxFbrfEFiMTQcwWe7XbUSpCH6qe49wL+7zEztVcVbeQvbZmhF3ApJwNe6xY246KFWClzI6qf247NPJLGFtiD90MO1LYUUusJO4mZSYOREPZgHGFnWqJjQq7iIgbAsqw2zoAJmeB2WVxg7TLZrc++Gbg938Q+NT/FzDZuymbuZa4+hHgD34IeMFfBC69T5Bk8+tiYmN+Hfj57wAefAVw5g7gFd8OnL1HkCrVFPjlfyD25cu/VZwjf/NfArc+DNz7icBb/oPY53/4w8Dr/xnw3l8Ffv+/6PX+4JcBe3cCVz8MPPTpwMf/BHj8PcDzvgx4878Xz3nz/wN823uAnfM3ZdcMwsiwIzvrgpZY8Bl2i3RTSjdG9lk3fn2W2NxWnDW1deOZo7BIRnqNsrd0QqtE6Cl2oK/bTjs3X4NbYm3SzVbYOZbYEkVnk5vWQHdgWa6E6brOLeiw7bRrjoZy6AzCrgy6Kc2yDNOuEDdzjHQLmX0ushRHXQkkAK5/XK43jCgss0QvS+sNXpaRbmq9ZdAAvEhdsk8oCkOUfYkm3Q7FetsuCbqJKLIEV2m917myb/MJO5toytJMqdt02cFw3p++aW2M54WWTgDMUuoo7AJLJ+wJE2hLrFjeLPqx4WTYZTrDrrRbZgcIP3qNLVbM4pKOPSrBNEXVNOqmtElyoAu3BedZKoiDdS+dMDLsXIXdtCuABNhOG5Qyw3Depe5kVNC6tNI7o4w3pkCzz1kHOwUeuSruDc9Y4foHO+bnvrel/65agpklNqh0ou0UMbuddyjlJNVRI16jTjx5oUWPJVa9v3y5Nk0iFdsaRcoIO1LYJdZ1ZSMssXaGHSOSuk59p5ouweNT8VxFqHGF3e5t3tfn5w1fLqIPjorTvgaNEna7SlF/NVBhF0ayWec16zzzL77kefhPv/V+fP0rnjz+Wqp0YgaAcj2XV9jN656x8QpwMoRdE1ti/S2xJmE3b0TWn/FFzQq32Y+W7zuI6OAlhZ1Hxh4REbFCUAh5uStmt2aXTWVX1wH/5pXicZYDn/b3b/gmrhTXHxXv8fyD5u+nV4Cf+CvA098APOMN4n3bg6X5deD6x4Dt88C7fhH4oa8Qv/9f/0i8pg/v/p/i5+//F+CWpwB3PluQfIQrHxQ30X/8k/7lf/wb/b+/+mHx850/q39HZB3hfb8OPO0z/cvfTLT6JrPIxfWht+nV1xJLeU0WgeUM3rx2WiLs/LOIfmUfU2kkSb8lVpU/6EG4EbyeFiiy2lifE+jbp85jeX/j5Q+VZ73+bVaDsNwi7Gp9s07vt5PWs35L7GYo7Dqp0kpbbXmadWEquSwVVs0tMMIusGFWEFg2+VUGDYRNO60k3ULVealvvRNNbA9AWGJdsi9kWWOb5bKHmKAIUfalXFEotnnWFchOwZiQHytKLasKH1yS3/saKmfIZ4kNI+xsS2udaJWeufxIaYVqiSXCzqNus6+lgKM2pvUYltgBS6tjSZ1whZ3bdu1DkSU4qvg+sFWG9B76izfmYE216wq6nnUNilaQY3N22zztMiABClTYSuX1pU21an1JS2wh1WttkrqRFRJcRXd+1zxWD7YZCZulBqHHCePGWzrhV9gJgk883sk6FJX4rh224vkVb7GW8QNGAQIL96fyhCZJlyM2uMKOW2Kp9dbmHTYgL5bUZ9oSS5+vJFMbnaF46VA8VoQdJ0YvPtf7+gWLFOizWdvg5SU7ZS4IOI4yXGF3rdtGW/m/713X9RLTXowQdp/xrDvxGc+6c/x1AMOqrZw9SynsTEtss0yZyghWS9ix2ffmBBoyNgr0Bap4S6xZOgGILykRdltFZtRVK4wq7CjDLlpiIyJuCCjstNgRaqxL7zObYj/8e/oxkU+bjP/wBuAjvw8kKfA33guUZ4Bf/R7g7T8h3uvb/jvA+DR85j8Rs6zv+3Xgfb+m2h0N9JF1Nj7+J+Ifx+/+u6XeBu57GfC+XxWPb3s68Mgfuc9536+tKWGnB9SFvEG1CTulsPC1xFIjYk/j6kLqvJoUfj3ZeV6ikAb+plpNDWi44swKXidFISkyGmXjtVWBvhw6S9nnNNuy9VrqlgJaXeAdVA4q7EyC4bRYYrNmqiYHQ22tgvwqcQ5gOXQTTAKVbrbiTJBuYet17LSh20zKPrbstCsXUMmZttajbhI0eC+zBNe65ba5yPm+WmzZdYehDKtbYALUMmNwK5Ass899pjrNssT2qvR0ayagLa1kERzP0bMmPTpGmgCDdlax/j5LbOO2vHpIR7Kktp3chiRBhRwFaj9pGLANtbIF2/tgiPRs1DVgbcEIy6IWk7Qz+f2qm1ZZYsuuwiTrgMZU2C1liQWQy0bampVO2OfKs4yUcwg7prC7cKY08ty4wp6O3Qz9GXY5O97pc97JO+Qyw+56K0snuhxtl4gCCBoL83tWNTaoUYAadzMm7llEYcc+F+ixQtOJbXWy2TKuolpPqJbUzLLEAsYEaIVcKSuN7MJv/gMxOb53u/f1+YRpsCWWEXq7kwyYnDGfYBN4zgucVQ+vYRtp5bfEzhhxb+fmeTGQYbcwslUp7Kz4lBMQra2U2clSPTB+wivsaGah9pROsJnSw3mjLbGksAPMQfxYS6xqTImEXUTEDQHZz4ttYLIvHnNSiqvBHnuPX3m2Dvjg7wL7d4vsrZ/8a8Bz3wg88CnA9jngF/8u8Kv/t/n8rgW++97x1/3Jb17dNt75HODDb/X/7bP+v8BPf5vY/ue8EXjozwGPvB34X98NXHiyGIQ+/l7gz/8nMfO4fxF45y+Igce9LwEee7ewLT/1MwXp+pYfAC4+b3XbvkoYllhbYTfQQNpDuml7qZW34yP7KOupxxKrCSwP+SV/R6+vrLi1ZYllA3q7sCKn90vZeXbkRq8lNne2mZR2uY9048r2rETOYn6rpnPJPj7Ya1u9fG6quOYs6NkhRtc4V4ejkQq7rJ2jm11DArKXBlhiU5nLxq2pXYkzgUo3WzUWut4yT3HYmWq1I0yCAs7LzFWrHSLcxnvdJvsC7cN5muLQWu+0mwSNpYs0wWEnx4mHTJ13Cgg7h2gCV3bZdtQessxR2Gl1mrp5pRzKUUvriLos1BIrl3cy7EZJR1MlmCctyqwzX6OHcLMtqRUKQdgR+TFqabVIRyfDbsyabJKeawu2/4pGTNLOZGbbrG4xB1mqK0zSFmiAWZuo4yvI3kfgWYIQ+69BplvcLXWuTcpx8KbMXcsuy49fKp0YyrDjyqGKLLFZi0KWcBzW0hLbATMU2MZc5zkXXGHH3l83U+9vOXJTbyORmw1S1CSQss+VvFhgTeFYYjnZ2czV51MhwyNXxPswPtuD4XE5n2x14jl6wLMRd8pcbBPFdgHm5+vD3h3q4dVuB1s9itopI/K2Qr4zNsexRKurXlYrP1ehsKNxbb2McnQEK2V2DK87tcQ+UQk7wxJrKuTSNMFOmeFw3uBo3phhk76ZgCZQYVfHDLuIiBsCsp8X23oWiZdOfOgt+vH8GnDp/cC5+8zXmF1zZ6xWidk14P1vErls2+dF+cLurYI4nF0VNlVA/I4e/+kviJ9ZuTrlz8XniZm/j78DuOclwGf/M+CWh4Df+X7gN/458Np/BNz/cuCdPwf85y8Sy3zJfwP+4+cBz/pC4PP+jSDd/se3A5/0V8V+/uW/D7zk64HnfDHw/K8Qf9+7KC60z3iDIB7LXXEevfR+4N4X6+156NX68fkHRU4eANzxTOCpr1vNez4JKKtmbtgbALBB/ZCtlQg782ar1xLLs1RDLbG+0gmLKKx7rakeolAuX6Sy7dKyG/SSX0whQoN3ep+1s17+fs2GxhJ6/FK37cA2WzEWrNmW3nN/k++GKOxY02h3+CgSSMVZwAC78Npaw4ikIudKN6lWC1b2uQ2z4YUViUOcBW9z5rbEhi7bbwEOUwVqRSFT9q3wpuFmgogmRfr3lh2EkW3cEqsVdmGEmzqPEWkTmGHnWGpthV2wuo3eA1NmYbzlFXAtqbXMoHNVfv7lc6u1mz6HIrB4w96Hawu2/aSwm8rPe1o1qiU2ayuVQThv0iUJO328aEIr7c0bO2CW2Au75r3hHiNyjuamqkkRvnWLupMWUrS9GXZ0/RQKO/H8naxBJomy6zLDrmkCYBDuAABaGUlEQVQ7TFEKwu7oklyYZ9jpbSzbqXx/S7bEJqxEoyNyM3XLqNSb2ACFHQl3yIHHPwc28Vohx5F8rp1dOAQ+Ydpns7bBlZu7E7nPJ2e0gnLMEntGq/0ewx7O9yjs6P2o1tsxOAq7gbba0ddix0Ynz6lj2Xwe2NnQzhh1BVhxhp0+iVfLNL+cJtAHXh16G3N2yhyH8wbX57X2ruepm4kDLNASGwm7iIgbAv6d9hF2dtvoI283Cbsf+wbg9/4r8Dn/EnjW569mm970vcCVDwGf8EWCpHvfr7uWTyrL4CCyjsNHItz1fKHIA4D7Pxl476+Ix/e9DPjKnxKzU2//cVHu8MCnAG/8b+Jc1KcsfMFXin+Eh18DfO3/FI8vPhf4TrY/z90PfPF/MZ/Lce5+8/8H9+jH+4FZFuuMttWDCU+2mkNC+Vpiyf41Zok1LKI96rwxSyxf1lLnuZaBAbJPbo9tp63sgbljidU37na2yHArLl9vhhz6hrKqPcURPP+E3wxkE6RpgixN0Eg7rGND2TTCLpug6RJkSQdc+ygAqd4KKWHIlrdqFqmb6XbUTXAuaL3J0uvNsxSHPktsINlnr/ewC1f2KYKSZdiVQco+l+ybnhJLLCD2jWg57LFiBmbY0SR5mwgNbZZ0KBJLndabQWery8gSG0pW+ZcvnOX7CENNoHRdh4QRe05xRR/pl6fAXFtSiXBzFHY9y5e5df2xbcGjCj/5HtbeEqs/g5wssdIGO61blWeXtnOUMsNu1iVu42cI+OcoCbu6y9zrhsQ5RqbYllhugX3B/eeMv+kMxE61xIoMux7CjpcVyPe7lbXIpMLuaiN+VzctZpLM1JZYT+kEgEkrxs9VkqMm8miZllgwhV2X9ueGGaTMerpdaCyljpkk0RPnzcwg7Ag7ZfjxxcdfquBh5Jpy257JWYiFGGE3Zollisb3dHdgp1dhx2LBQuBk2B1DYUfiqnqqvwNLlDTZzdnOGHUFWHGGnbbEkiwwZPb1VKKkA9nv56cv2vVZYx6sPoWdssSOlE4QImEXEXGyUJZYD2F3+JiyI+Hh1wLv+GlBnBHJ9LF3COslAPzUtwBPfpWwoHK0rWhAffRPgVf/n3od9Qx41y8BFx4Sy/zSd4kChgsPAb/xveI5b/pny7+ve14sWlzveBbwrC8Abn+mWPdH/xC4+Bzg575DnI8+518Bf/IzwFv/E/C67xHLJgnw9M82ibZF0ROY+4RHx2Ym08zIQWraDlS2p8kgpjiziDPbUtWfy8Zz6CzSrc8Sq8g+lyh0LbEDJQxW8Lq9LLXQu+20czno0hlVtppDKRa8eX+MoEwS8OHLvGk9llhaduaoAuk9a8LO3s+b1RJb5BmuYwv7OEJy9SMAgKvYCSKwRNOrTSQF2ktzH+k2we2B5Q9Tu3QCYfbSMkvwqE0UIjSHjr3fI8rsK4NIt9xjxZ0G2ngLTvbJnNVQ+/AmwMkJUoTdYhl2dB6ZIwPdmoUq5GxLK21DHmgnJbJLTT6QyinQEsvvqaqmQ8nW476HHsIsJXscbYNUyAWShlp1ZX4OKk+sHSEdU3PiZ23BSJO8Es2nZImdVo2yxKKeYZKKfTdtlrTEpqnICO5alFI1ViN11fMSn/UJF/GLb/8otssMdx241sRf+JZPwb/4n+/CV37S/cbvuRKIjr2hDLsJI2fn8vnbSaMIu2u1HhPMZGuutsQy4iPNhDKuazBpxbmpQqnjsxaZVDAIO20fptdyTtHK4tiJ93kcRdYJYVZ5jhlF2OnxFH1mwGIKu8kSpRO37mnO4fZ9+ZgfH2OW2DPaElsjVypCG2SJ5fn+g7A5juNk2JG4an54LIWdVq6althVXntPRGFXNZ1iGRdizU8Tyl2IM1enBl28MYcIO2GJZVJY7qcmjJZO5MP/j4iIWC2UJXZHk2mUYXftEfFz+xxw9ws0YUd4/2/ox9PLwH/+C8Dn/huhCiOV2lt+QFhEATHQec4XAx/5A+BDbwV+59+620PPtXHLUwT5dvQ48NCnAb/6T4Qd9nP/tcjZ+7TvAn78rwjl3Ne/CTh7t/91zrxS/PxsRgY+9XXrbSE9TeA5Z0xxNq/14AvguWycwLKsqVbLYJA1dcQS69ppa3e9PaUThZND108U2gq73F7Wzr9Lc0UK0Y2PU3YxYB9OZLvtvGl7LLETtuxMrZPuGIo0xRStMUjeVEtsniY4JMJOfj7Xuu2gGeQiY+UP8jx51AW2xKYprhD5Jdd7hDKIOMuzBFc9KrndgBtp0bgql5Wkm2hrDVmWvV+J0Ow8w4orifqjLrQVly1L6+3C9tUmQKhPKkWI9CrDeskyKw4AuSLsQlV6jpIiscmuYUurIssU2WUr7MJIR3ofWZ6CbuGLbrHiC3oPc7UN9j4YbrpVkyDo2Qd9lloWn7T2kKRJJgm7I1LYVY1WlDVzpW48ajKmllrwe5eVQD1F2YkJ4brLdNarde6498IOfuTrP6n3pZ582xn84y98tvN7rrYlAq5A3Zthx3Mf5/K9b6eNaAsHI+zqVp/zmh5XWFYC9ZEi7OpkFRl22hLbdj0KO74d9XQ9CTs7ww7wqv+5ws7OJxwCd0f02axt7G/p11fNwwlbRgmTevDSbwQuvR/vuP21wE+aWXUcmrALVdixczMbby0FFV92qDPsxohID5yogxOIhVsxYSc2rGk9s8lPNCSJkI7Or+obeDbbQF+06/NaMeuidIIUdouUTkSFXUTEDUXFvpOOwk4S9DsXgNueIR4/8na9LFlJ73kJ8Ge/KXLmfujLga/5JeBX/rFQzXH81r8W/xbBc94IfMZ3A5M98/dPe70YmJ27Tzehful/F4OBJYJWI24QLIuoz94AeHLZvKSbbYntyYPjBJZta61DyD7zxtO2xDr20ozZSx0br3mDqbNqSNnXY2vNSpSZuYx+vx6i0HOjmmcJ5o2YOa2c7Dy5n+sZfMqcIk+BmdnM1tswu+bIswTXuy2wWD/M0x3DftWHMk8dIim8wIEp7GjZbmvxLDk5e36ICc6GNr125jaLltgwldyRlzgLUfYxlRwtu5D12NrmwP28CaB8J7rBm3eWsmtEHUcNjIrwa3kWFincwhR26jUU6WHb8cMssVrlZOfHDavb6DWyNEHTZSiTxs2QGyidEMubKsEyqcxt6LmXcJtu5T5QpOdIS2xqXgvWGvI9ZDJOZIZS5LVV2iKKeqoI36uV/nwWUtgB8vOaomgF4VUhda8bxwQnxmateM0cda8ltmTH+0x+zpO0RSq/J1eodKJlllhCD2FXygKPOQp30i8ESaLUiFlD+yrrz7Djlsl6DhzDQXlSMKKxCMaYiFSXSxJ2RLz61P498FqrOWGXjhBs2+eAz/s3mH/gMoBfVW5CGwtbYo0yk2N+mEQ6GoTdMhl2IxPDK8DJWGJbPpv8BCXsABHOOL8KXJeEXakD5klhdzivzbwDX5vNqMLO9nNHwi4i4kQh7UZGSywRdlKNge3zwG1PE48/9g4xiE5S4J0/L3736u8Ur/MDnysUbo++S7eyXnwu8Kl/G/jFvwd8+Pf6t+PBVwjC8JP/OnDnJ4hG2rf8APCCr3LJOgA4e5f7uySJZN26w1LYcZUHD+52c9lqlzizbpZ6iSRewmBn2FmNqy7ZN2c3bTbpJrKXhi2xfqJQFUe01mx0X/5dViDP5sYyro3XQzLydsAsBdAYYc2KAFGK+EpPsvHcI2Ydq3uJws1oiTXaSyWmWdjA1rDESixS4HAd5ox3aOOqj+w7CiSwSp67x5Y9G5hDd60zb1avYzvoBl6o5Mxlg/dVmuJqZ34mV7ATpGTcBEysDLq5bcVU39+esgVbXdylKpcx7YhwGymN6ClcyENJwx5LrKsS9JNtWZogScS95VwSdilylGiQK4XdYqThvMuBBMi6xRR2laWwc/ZBb3EGxSdtgMKOygLnQmE373JUTYsZK51APVef3xVG2C2usJPHc0sZdtoSuzD51wN+Hpk2RNg1vZbYkhE9RNhtJXMkHb1f+nvnTBY4SiVqZaYMO+Sa2Fh0UiHNgWaOopmq11KZujZhl6bi+W2NdW2KVTwAJ63UhKAe18yh/767UIad/s4vYtn+0W/4JLzjI1fwKU+5VfxijKTzgKyu03pFltiebMSlwC2xRFAWy2TYWQ4Se7y3AqyYsNM3Aifh3904MIIOgHEDzTPsjvjBymfsAXFVHiudiAq7iIgbi9qnsJOWWK6wO3uPVNpeE4RcuQNML4nv+d0vFAM0KnD4p8/Tr//VvygujJOzwL/9cwA6Qco983NF4+oHfgd4/pe7kvTzDwCv+o6TfOcRNwMtG+ikmZGXUbFBauqUMMxd0q3HElt6CSy/0s0tu7CJMzc7j98oeGMzDKWbtc3WTfLcUfbJa17L7LRJKoojWFRH13VqIJU72+zuK77d3BLrFkf0KOzYje38FCjsbCJplo5YYiSKLMUV62buSrcTpBrLsxRXPCRUaEvsoUWcHXWTMCuuhyi8hi3cEmhNvQJz31zudnFHyPtNU1zp3GVDLbGXPes9LQo7UmBohd1ihQ0l+z62bScKLJAjg1TXto3OMeqzk9q22o7IqjBLq22JnSXy/AiLMOwhu5IkQcHKN/K0QwZq+2zM9zDSNKstrX2W2GGVn7LUqrbRwAw7u+l2nSHfQ1qRwq5A3XaY1g1mdAvdzBRhd5mdzhcmyuW6ctmiWnW8JXY132FOZh02Pkusn7CbVS2mUpG63R2pv1+txO+quhUKbGNlE+//lcKuK1i8xRL7qpkjleRf3WUqI81rQ8y3xDicxu5rhu943dMwq1uj/dcXbbKsJZaOxbbTrawhx+dz7jnAc+450L942uuBj/0x8InfGLxu+7xtQxF2oSUtnFDrEzKFQhWEHmn3wDIZdnYRj7LErqnCTsuku2iJBYTCjoMReLuyceVo3uBQ1m5vl7km5YikayroAO0eFYz9+0jYRUScHLpOt8QWO8CWpbDjhF2aCpXdB34beORtwK6cpTq4V5MML/oabZMFgNuermex7nkh8I2/DezfZVao3/Oik3lvEesJPpiWN2yAuOmb26ovwCKhTKUbJ5G6zpetxpRfllKDBnhdB1WmIF5znCjkg8O6bT3qPLbNbY86j1QptbWszxJrlWyI9bLAZfv9trU3+0nNTA9ZYqnJDTAGkFpN0/bn/W0IYVdmqXFD1nQJ6jws66XIElyBTbrt6uKPkWWXJaEEUWiu9zLCyS+HKOx2A1WBCS5bpNsV7ODuQGWf/X6vYAc7ge/Xt97Tk2HnV9jlNtk1om4DREPpvBGE3RbkJIHR9Dxm5ySFnSSrnPy4sZZXIrvkeVkp/IbJLoC15dYtijRBK/dD1tWOwti/DVY8gVTYOYRbn1LRJvyIOHUUesMZdtWmZNgBSGX25gwl6qaVllhdOkH77tJMvLcyT4PiAgzIa1YuVWOk5gOWIP96wHNZj1qxfUMKO/WdazRhRxl0AHC1ycT1rW1x3ZrQcYgPGoMoS2y2vLhHbmcu86TnyNV5wUvYcbXaGuJLP/F+95eeycS605/P2W3/99sHft26Pqvl75YggV/x7cCz/zxw4UnBi+gog1Y0W1vfC1LeBVti+bjjOIUTgL6vqq5ru+8yGXapZYk9AdHaSq/i/CLg3AQ8EeEo7PT/t0lhN69xNBdfnp0yYxYbeVLhswF9CjubYY6EXUTEyaGZQ5HovCWWSicOpSV2R2Y+kC32kbcDj79XPD53v369h18HnJcXv72LwGf+E3N9tzxkknURTzxYg2mudPNm3Ay0xNpKt/6WWJd0y41lfc2nfEbYT7oBgvyqe4nC/vy7edMaJKO32dZa1lgv22ZvQceQSq71WGI9lhUj/44N4lxyc8NaYrPUUNiFWjwBSULZRFK3G0QkFR6F3eXuTNANrJc468IIrD7iLCSHrvAse7nbDVT2udt8eQGi0KfsW5Wd7mbDVmrMWosoGrWC6v0wl+HrRLgZ5w4gWB2m1WU2aTjc8kpk11QRdnO9HcBgtI1hb5Oko1p3O07Y8etH03a6qTbQEmvnNSmVobP88D6ka8Bag+6vZrIlFkIVZrTENnOlkHxccr6TZQg2+ZnnjSChZl2mrler/A7T53dY8wy78dKJIyLsmusAgLZLUCPDUdVg3nSuwo7iYgikmFfvr1Ck7cLxWfLYTCVhVyMbJux8cVPrDh65Ib9TLftO3rYfri7j9uzrcyLsljim0mwhsg4wibi55zuvM+wCt4cr7I5L2KnSiSMtxOjjWoZexrouqON6bRV27Iu96qDMjYSdIcUVdlLKesgVdkWmAxRppo/P+PVJP+0Ddg0bcCIiTg0qPbuIfNtTOkGE3QXxk4onPvpHmoDnhF2WA1/506Kc5s5POLHNjthgWIqHkg0O5r4Z+AESis/4HTGLQuklsPwtsYBNQlnLcqKQiLPUv6xrL3XbWvl6ubJP3cQYltgBorAxLcTmel2ikC9f+cY1fFm6VrMQZK5E2XRLbJmnuNLpmedr2Aq+yfIpvy4HZquJZc3JzyvYCVq3jzi7gl1laxxCr8IuKIcuxSVrmxdS9tlqxG43sGE2RYUch90EO4k4HoUV93RMnDsKO9uKGWiJBfR9iiK7WruwZix/TVpaHbJqpLTCyhBdVCUotkGr/PKmQ9dlws7VWgq7EUssnQ8rpdCrhHx6rPjCUtjN5Poz25rc25S7QRl21BhOCrtO5K5NqxYzlWE3U/l/j8sh3iSUfPCsK6sP5bqy4EbPRVDkKTBvcJ0y7Lqw0okj+XxdGpEDSDCtxGTW3IoQUO4TAl3Pa0H4TVumsFv0HEXKR0bYEZHvnVTJrXvrTYDiA6bqO5Wy7+Ste+GEXZ6loqCm7XB1Ko7VGzWRw62u06qVbd9gv1tQYceVm8cm7FjpBHlij2WJFee0Rk0Mr2mGHWcYa2UdOR0DhaVgE3aeDLvDeY0jSdiZCjsi7OTZP5voQEQbTk7A4uxwREREIKghNknFoJ5mEeupGAxwSyzAFHZ/BFz/mHh81/PN19y7Q/yLiPDBGkxzlcbM17A1YC/lA//DuS48UPZEg3Szyh/YbGHdeCyx3nZaecOTJCiyROXXKXWeXRxRz9h6SVFo2lqdDDvDEmspCo1tblXukib7eEGHqyzhuVc0rlE3/rnv/XrstMwS62bnbY7C7mM4UP//eHc2eHxX5h7irNsJI7BSl8ASirNQ0m05hV2e+hV2YW2t/m0OUhSmKa5jC3WXIk/EsXoZu2HttPI5l7GLHczkNoeRfZsACmSnrKppx4gmYJTsStMEeZpIa7xJVjmTGz3jbbtlm1R+uZOjF6ZOO5KkT04k2QhZZm5Di6JJ0CmVIC/dSXoD4nlp0bzRbadZxyY8gAFLrJlhN1MKPfs9jJRWtJupsKuVwk4fO0TYPjazrhGLQF6zMklozdrcnehZAei1DmvxOWbcEpsMKezEYyLcZrKUZ1o1qJoWU8MSm2gyhECTaLXIA5x2OcgVvfA5Sh6bqZxArxhh57fEbiBhR0qyeqrOTUmuv1O3nlksv22SpzicN7g6Fd/PGyWoKrJEkYVH88ax8i7cEss5juMW5hn2187zuzDQ971pOzGp3FoTwyvACVliuxOZFdg4bJ/Tj7OJcfGiDLvrswaHFRF2OTupkDxe/hwi4RyFXWx8jIg4MdQsvy5JJGEnT8rTKx7C7uni5+PvAT7wW+LxvS+5YZsbcQpgWWK5RVS3jPsUdh6LKBtAXJ9phZ0iEwZy6NI0UYPhYUssJ870TZ8aI9Q+pZsbsKysuGyb/ev1qfMKzzZrC7D//bo3y9wS6+QFjmTY+WJC3Oy8zSDsyjzFx7oD9f+PdueDx3e2wq7tElxFGGHXl8sW2jDrJd0Cli0zf/lDUDttmqJGbjTFXg5U9gkC2yT8Lgcq7Oh9XWLbLay4p2PinM5xU/k91GRZmJUTMAmIed0qO6iv7MYHu3hn3pFKKYw0dC2x8pxuW2IHom14wLkg3Pg5jJ2HRkjHeS0mEpTCzlbojViL57Ww1JLS0SVOe4o71HVgAwg7eg9SPDFHIcipujEy7Khl+EgWOUxCyQdjXZKEkmPMI5ZXtsqmZ3qta0TYdXXvcUvfuXnT4qiW3zdJ2FWJ2L5Z3aBuO7PgZ7InMpw55H1sIomR67X++8JKJNpORdjlirDznt9tMcwmgLLaqkNtiU30d+rczmL3+kSIXZMZdjeqPTxJEkOkZIMy9YJbbzmhli1GWrqv5VHTLUHYcUUtnVeBJYjoAaz00+LS2foE/Lsbh51b9GOrzZEy7C4dztHIfbVdZky2OzV/DrHIPU08ERERJwBS2BGJnqZaZTe9DBxJS+z2efHzzK26bAIA7n4RcP7BG7OtEacDDmGnbxpnMrDXsDfQIMZDulHoNACl7uav6VfJuaoxI/qC1u0rf2A3AES8Ve2QvdQlGZ3cPXtCcMASa6zXlyXns8QyKxe3xNZO6QS7XitLbOku68sK5Nf6bv2tYYKwO6v+/9HuwCSJB5dNcBnaInoNW+iQBqvVHodpL72G7XDCzpOdF6zO8xRlhFlTxevzEPaPdQeByj6x7OOddmRcRtg2Z2mCNAEe6fRk8Xu720+Nwm5LKezEd3hKRFEbRhQB5mSHmf/mkv1Dy9O5QG1DaP6bZYmdtWSpncs2nxCFnVbp1U2nlV71XE/2D9zI5qx1m6sM0zYsx69v+axrpKV2uHhDlQhtROmEuR+PMBEtsVXL9vtMHYP0u6XIENVIKwkxZoILKegJBZELV+dE2PUf+zSuuD6r1bFOjbmVJCynlSC/jdIJ22EGOMKTw0bvo5BrgQHazrnYV3WXq4gPP2FnFTpuAlS+2lRN7N1z61mUWYrPeOYdSBdUb9H1+kZbYgEtUjpkY04CEYhntgJNn/nIcbYI0tQk7dJ8KdET/77P6kbxOqtU2J1Ihp2wf5Dt5HTM7C2F3Qv6seXl352IE9+j1/XFcafM3Fyb2iIHfLAvzFFhFxFxclANsWwWZmsfmF0WhJ2tsAOAu14A/Mn/EI+f/UU3ZjsjTg8s1QVXs9PNqzGjz8mgxkNgZQnmjQ4fztNEN3cNtMTSuqdVazSuFr48OM+y5hjBCtMeIAqJiGg7YWsdzr9zSbcySzGThJvb1uqxAFvvV2yzxwJcsJsAuhFg12p/EZdF2HWtWO9xrR0njDJLDIXdR7rzwQP+Ikvx8U6PgR7v9sRnGljgcGS3DyIJttNedUi3sPy7PEtQW0PkS6EKO/n6KTQhcRlnghWFgCAlCe/rbg9WM+ZZikPoMeHHcG6lNw03E1phJy2xbQakQIaw/DjAVdjVfZbYHvAJC7UN4NswnN9GxAudD7iKKnwb7HMSnbNnTGE3tA9YaUVt5fgZltgehRzfh43ehyknfoBeleCF3QnuOtgWrqJ1hyWAOOomYqLMKJ2YIZHXO9qXS2XYyf2dMJsnYStfQrHXA8oQm0qL65DCrsxIXFJpYpcIxUQ890haYo3SCbtwAnCUS1ePpbCT+57tq6P5QDNnzuylmwLaX/WR+l7ec8s+3v6Vr/HbfkdgE3Y3shR0R3IepKbjUITdJDB/3773Oi62zups8q2z/fFjA+AZgbP6ZIpXV2yJ1bM+c9t28kQEV9jtXTT/JC9UH78qLq5FloiLsD0LENJaYl+Yo8IuIuLkUHu+k1Q8cfioLp/ghN39n6QfP/zak92+iNMHlWEnWxGZpchrieXXER+BZQ3czPy7sNbUadWo/Bmv0s2jdvGVMHgtsZ6bXp17xDLsaEJwTNlntSry3/mtuG6GXc0ssVolRwPqqfe8wN+vQ/blbNC5ATcRZZ7i3d2dSlXxtu5+Jzy6D0WW4nHogfV2Mg/Ov7OJqqNOBpeHNL3mKVprmDtDGbRun0Lm2gJWXAD4360oEboqbbkhqhsip7nCboYymHQrsxTfU38BurTET535fGN7Nh10vNEkBVlitcIuwBLLFHZV02FutMS6KtnebSBbbkOkR6Al1srAO2oZacXzOwdbYvX5f960qqXVmDgIUNgR4TdXtmB2zk8y19IoMWGEXcUIv6ytrJZa/z74O5/1dPzat38qvvjF9/Zu49rAeg9HKHWGHdvvKRF23TEUdvJeLpmTgk2/1qJqqiHQ50eEYNo1vdmJNFa4dDRX25PMxPY1ic6wq9vOnBwJUNgZlthF3x9d8+faEjuosCMV1fzQ/du6gvZXNTXGRMuQdYAe510+Eq+1vYxte0nYCrur0wofvybOVdemCyrsOGHnI4YXxdZZ9vhg6ZdRpUhVqxR2CytHB7Biws5V2N1IBnftsMsIu7N3GX8iP/fH5AGrvji2z54Iu3KgtcRR2EXCLiLixECWWGOWR57wL71P/iIBtg/035/3ZcBLvwn4ip8G9k3yPiJiFCrLVJzb+eQYWWJNwk5eA6oj7w0kPZcGbltcDWAo3Vx1Hq2bWxuc4oimYsu6xJm3YZa2uSdLiuce9bfTVt4b3twzNvE3vZKifcKW1YoaxxLLJ8eIqC84YWda13qX3QDCrshSXMIe/spt34efe9kP4pfb5wRbYuk9/zJeAAD4V/XrggeytP+/bv5X0U328VXVt8rXDC9h+FAn4gkek82tIQQWHTN/0N4PQN/chlpTkwT4O9VX4PoLvgFfW3638Zoh6/679Zeh3r8X/2z3G8R6A/d1niV4Z3c33vU1f4x/f+ar5DafDsKOzlPTukHbdtqi19mE3bjCTpD3jVbYGeeOsAw8ADhSpGFYU61tiZ3ahF1Q6YRZZuMtzhhQ2JnK3860BdcsA68HJcs146RnwtvBgcH9uDFwCLuJbomFO7lF+3I7NI/LWJfY54ksuCBCcGsZtd4AFGGnSlv86nJAf9aGBXgutq9OTUvsh7t+VxkAR2F3uUrVOpJFVU1Whh1vifWe7yiWSlpoNwJEMlaH+nu5RL4agT53IpOCSx5WAHIVXp/X+OClI7zkH/4iXvQPfgF/8IHLSmG3Nwm1xK5aYXfAHp/tfdoYdIt5g0ru42XJVR9WehbgtbaOZeWJiDO368elmcFCCjuaZVPScLt0gk4uQzXD9oV9za01EREbjdpjiaVZnsfeI35uH5gNbVtngU/7+6bSLiIiFJbyQ6u+Oqaw45ZYprDzZLrRQO3S4dxddiTTja7zPDw491liPctyZYhrTfXZaTnpppsJB8suWj0TrbaZKd2cBnvVTjsfsbX6LLHsHHD0uFx221m2Zso+tc1JwmbQj7DuoH34EVzAR3cfBpAEW2Jp2W9rvxEf/Ix/h+9rPiOYgKL99T/aF+MjX/8neFP7DABhA2EiyL5q/m1o7nsZvnT+N43XHFxWvv43VH8V9YOvxpd23yV/H77d17GNxz/pb+PduGi85uiyaYL3dHfig1/+G/iJ/DXyd4GEHRFCKCCFaKdm4pwr7Hj+XOpk2A0Qdixru6o7U522wPI0UXLYEmkoz4cjDamkCqbzX9V2mNE2NH5FtPMahkqwNcoPQhR2yhIrJz8Mwi+EsOP7sGlRd5wwHG+Z3ShY91PTrkTVdJjWjSbs5oeqSIFIrTOh5IOxLtrn9Fri9VdNrFB8Rk0Ku9Y/SQaY9/BVZ76nJjVbYv+sYyIV38S0pbCj1wud+DFAYwPDEkuEned8R6KXapMIO2bjDfhejsFWxK+aCB6CLtqs8XNv+wiuz4VD48fe+kFF2O2GfmeMe6/lCTYFLq44FmGn1dcnIVpbLWHHam3pJuK0hN0uBR4sz0PnodlmgpKCKpWBpbAbIuzS1LwwDtlnIyIijgefTZ1O8o+9W/zkdtiIiOPCmv0u2LWWlG5GZg7PayH1FhuIUx7OFamwG12WDRInatma/c4i3Wpup3WJsxkvpnKsqX2FFQMTgotYYh1bq+/96u82nzVVeYE08M0KYR0DGGHntsTOmxZ168nX2aBcnYIpk7w27MFlxXu+3Gzh0j2fig5pOHnF9hcd62UWpsig4+OPu3tx9Yv+O97WPQAgbBBNn937u9tx5fP+M97cPCjfS+B7TjUxU9l5jWPLsn1dtYsN/EuuvrLJ6Q0H3WDO6qaHsAsojch5dI9fJTVoiS00WdV1HabSEhtKGtJ5bN6I5aum09tQz1hpxDhhR+fC2YIKO35jaRJ23BY8rrCb1b7iDrl8WiyVBbV28JVOkCVWEXZX1d9pXyyVz2eRMcdS6w1gS1liKXtwIMOOnbMq+Am7o6pB3XS4whu5AzLsiNwMjVYwQNvpscR6eQcSzWySwk61xB6F5dmPwM5VvJEKu50JEXYN3vSuR9Xvf/1dj7IMu8DvzME9+vExFIcKXGHHybsFMWHXJ8eNsQKs1hLLvtgULHhaBgpLIUmAr/5F4LlfCrz0G40/7RTmgXluR574+Q0PoGcDxg5KflGJpRMRESeHvtIJIBJ2EScDazDNb97pWuu1xHLFBbNq0o2vssTyAbNRpNBPYNGyhp1FhSQz8ot9T2hmn7LzjO1WCjuW42So5AZItzFLrGqJ7dwGez6LbTdAw7y59dqP6f0dXXLfrxVwL96HZ9kNIOwmTFXjVXUOwGjmtD+7wGUB3WocSl7lHrIPCFOrUZYcIBSSykodSDTSTWPNGpFDSUpOTmsl6mLrrZpu4X297lBh+ZXITiN13LIKu3nN1WlTL9nfu7xlJw0lDQ3FkszyNBRyjavytcEtrbN6GYWdbWnlCrtxwq/k1q+m1TmALbfUnhLhQGG+jyOUqKQlVqkzu1b9vVIKuyXIkB7CbpWFE4CrsEsG7OBchcVLMACgScX2zqTCDkjwsb2nij8++8+7K7YVdjiGwo7GBmSJ7TJF2HmdfRtpiWUK/BNR2N3IDDuxrsN5jXd/XH8G7/rYNTVxvBeaYXeWZV8ePtr/vFCsTGEnz4uVHi+s0hK7Ur0yH1AMhj8+kXD3C8Q/C3a44tlteXHk7X4Ay7DbxSDyUpN7sXQiIuLk4CEi1En+cWmJjYRdxCph3Yjy6+o1Rdj5LLFTpgh1ibNLvgw7btNUxzon+6TCbirVeV6i0E9+bVlkH389s9nWVZnklqpE7AePOs9jiS0YeeI02Bvvl/aVvoYqVU/VQ1TlE2B+DZhect9voQkGtWzh+Zyq9SfsChZ5Qu9lkZZYApFuoctykktPBC++rEHYLUB+EUFJBSuhrhFFUtaeZuLRZbk6bzHSTVnHmcLutJS/9SnsEiIbuLqrB3Zzs6FuW6Bllmy5c0XYyWU95y4OrnKZO9vgVzW726AnL2Z1gtaw1I7f2BulEU2rrY7NPExhZ9mK6wUttRsFK87oqPMo7BiI1Aq293E4hJZ4rZPKsJtzslmeZ+zjdpcpBacwvxddRpZYHfnws8//N3jjMybArQ+7K7bIT2qzXs4S67bEUoadd2JEEXbXFl/XzQJviSVSeJUKuxUTwUMgxenVWY33P6aLP2Z1i0dk+Wawwo5fz255ygo2jt2vbZ9b+mUMS+wJqNtXS9ixnehkzEQYONgukCZQg8ADW2FHF31qtFlIYXdKLpQREesIDwGiCDv63m6fv7HbFHG6YSk/+HWV1Gr9CjuXdLNVcg4BRcsq0s1VjenCih6i0KfOs1rK0oQNrn3Nth5ba92wDDt6z4Yltr/ZtmLLKhJDbV8HyPY7UyUnSbe6UTcEJsFJCjuyxPrttLSsv813czLs5n1KwwHw513xHa8DSBKRlTevW0W6hQ6CkyRBkSUic6rShF3orHcpCbujanGyrzAyF5dTFc59x+vYsimR0x0rWDkdTheeYVfVVtkC4FUT2ygt1eus44TduKWWtmHeCJXfTLYWJ41N2PlJP67+IWXSvMuBBJbCLURh1yFJWnSK8GPLBzTlkkKu5k25AQo5Yx/2WWJPDWFniiWmKFE3LaY1K2GQEP8X37WlCDvr3k2XTqxYYSc/v5qXhYAIO/O43WFKwaPO3L5Wbu9UWmLFxp4Fbr3Pv+LcvI897MQxFjp5Y4CO7zmVTuQ6w873esUGKuyUJXYKdDRjtPz3yiboVm21HgKp59750WuY1y3yNMGDt+7iTz6qCdTb9xcgI7/u14H3/irwrC84/sZx0u8YBKAe7y1+3Q7BStm0NE2cgcHCVc1PEKRpgnM7+sR4dluefPhNC6BmD9TJpg9cvh5LJyIiTg7KEssz7A7M5+zdjoiIlcG6CczSRJEOSmHXl0PnyVzcsogzLwHVm2Fnk33LE4VbRabttD6yjxFnvGjDybCjm4zellhtiVX2RF9xhFLJsfcr9831Wa0m2CY+C/GR2xLLB3CkSjP2tbK8bIDCjpFIKssvUPnBSQqdmxh+szBIMI+ABsw8piW0kZCOkSNDnbcY6caz5Ba18tZ92YdD62UZbadt4pwr7GZ1YxJ2XReU82Sry/x20qH8N5OsInVcUk9F4ULnJz4IaZoYWZ5V3WFGyqVAhZ1hia0aZmmdhSnkrBtLf+lEwD5QpResuOO0K+wwEUUhVeMozppEk6S7y5Ah1j47qdIJer2687T7WkTvJM/UuefIfr+5yFY/UpbYkfNUn8JumfenWmIFAccz7LyxBUphd+j+bV1ReMZEK82wu3HXhfO74vN68/vFxOY953fw1Dt0zuHBTrEYgXj7M4AX/yVjnLc07niW+bpLgmfYzevFnAQhWPmnZQ8MVrmxpw10AANCcQdAXyQbm7CLCruIiLVA7VHY7d9pPmcVMu2ICIJnMG3bS70kUk8OnSLsDn0qOWZN9RBnLtnHlx0OSQ6z0868Kg8iMegmEeAZdkzhQa243BJLqiNfYUVWglQRKofOsPGa7xewyVH5nj2WWLoRmVWtW1jBl92ADDtbVQOEE2ecpPB+9iOYWJ9BKFHIn3t9vpidlj+X22kXLctYNDuPP0+o5IjsC7UBu8f6qWuJrWWGmKHsmusnBpJdc6PwYTqqjgPM/LZ53WNnBYJIw1ndYmYQXmGWUnoP2pbrUdgFEG4zleO3oCXWIj21SnHqPXdvNBhh1yBFhQxV3QpVGXK07DpTJ5o8WM4S21M6cUIKO/W5t8OFK/RejmAp7HJBgnFL7OD51VbYYcvYnoVARYvyes8tsd5t2MgMO2q2PVwJEW4r7G6kJZb4jktyzHnfhR08dJv+bt15dgXlEcvi3APAnc8Bbnu6+Lck+PWJvg+r5MBW3rktviiLz0Y+EWEQdsoSSzctVDohCTuqpO4Dn7k4LTNbERHriMolMbB/l/mcCw/duO2JOP3whKFvlxmuzxtcPhTXCr/VkinsOOk2pJLzFUd4FHZXxhR2Vf+yg2RfjypQ3WgztZrOsBsm+7TqqGFKN7nuJBHPrY96SDc3d8/7nmdX3GXl86Z1g2nta/O1MmvXGFxZROTjIoPRSZFi3rT+Yy5w3VeWUNjpZcWN3SJqFSIZScWapUkwcUbbaBSsBBKNdpMpsLgV12yJPR3jcNp/00p8n6qOlx2EkWWlRVaZGXYhllhuDbcJuxnbhoEMuSLF1Rk1T7MsNCODLkAl2DRouxTJwgq7jL0HplRckPBThN2CKsWNwkSTCrNkC0CCeSMIYwDo8m1gLo6bOtPX2OA8Lo6+0omVZ9hZpROsNMNL2JU5Lh1WmHZWhp0klKaSvOav7QW7Tz3qSrRSM7Rchp25LTWyYUssEa90nd4E8IzbxI7wWBx2dv6NtMRe2DU/r/sv7OJpd2qF3cWzN5HgT1PgL/2vY78MV057S8aOiRNX2N1IyeWm4cIZfQDffV4ScnTCpouuyrAbIey4JS8SdhERJwdS2HGSfP+ifpxk/sDdiIhl4bkJIuLhMUnYeVVy6IDZVfk7V+l2yUucjWXYDSnsfBYOT/7d4QDZV7EbX4+91Kuw41ESnpnoLeMG1UM20XM9CjubLDJacQFX/e5pxb02rVUEjamEZIrENYdhiV0ww048V6orfcfN2LLF8dV5Sy1bmJ/9cZYFwgfvRlbbgvl3dFxXMmNtkWXXHVtMwXA050TTzCTLBsginv9mWGKbxUonvBl4dM5LCyDtP7755ztzXmOc8NoqzOXnHVfYhVtayao/95VOhGTYNS3mvZbe06ewO8wEwTCvWzUB07J7s45d6y6cWeI+zM6wwwll2BWksPMQ0x6yelfm2NkKO0XYzfVE2OA5ku9L8GvsMpZYczurTltivSro3VvEz+sfW3xdNwu8dCLAKj+GPYtEXoooXRLnz5jno/su7OATn6TLHl70wPkbti0nBWWJrTiBvcYKO3vjlvoiPkHwwC06l+7Jt8oTGV2klcKOyIExwo5VEUfCLiLi5OArnZjomSJ82ncZs7IREceGR/lBNplHr4lrhZGZw2+WSDVm2FrFdbqRChwv6dZjax0kMWgdbaWtJ4bCziRPvOttZlpZnruD+mmlZy+VYsln4/Vs8/VZo96zs93TS4NNr4qgtAdg9o2pj+yb9qnzGMG55uDHDCkZllG6LaOw21Jk32KFFfy5S5FuxyD7bAtwmaVIA+20tJ7rM030htqXbDIIOD0T54bCjmeI2d/7gYzCfsKNv0aIJZYy7DzbMBJhwycfjAy6HoVw3/LTukHZgSnsuLUxxNLamFlsXCU4RFpmegKkt2n3tGRps9KJw1zcZ1VNq0tsWL54lerP7Fl3sXuyUNgKu45aYk/GEjvzEnZDlljrb3LfTOvGPxFmgzVwmoTdMSyxEhUylTHr3QaaVL/2UZE1uYrss5MGn9Cj97sihd3Enng8YZy3FHYP3baH3UmOv/v6Z+D3P3AZX/7S+2/YtpwUfJnFa22J5V+8IkuC27ieiHjBfecBvAsAcNeB/GLaFhkZqLmQwm7nlpVtY0REhAVf6USSAF/w/wCP/inw4r98c7Yr4vTCo/wgOwNlZO3w2VM+6KZMNw/5pf/vIZHQaftIMUBgeZV9AKZUwuAShZd9xQN8WWUv1b+jgc/h3FP+MKKws4kXY1n+XKWw89l4qdzDunmy4yoG9hV/PbEs5eroprR1Bf+cLzO1YfjyNmG3uMLOe8wFLqvbaZe30y62zRbJuABpVvqI3sDlaZuPqmbhrMF1h6Gw40QTV+WOTFiXLMPOtXO6qmAbE6bWNSy1gD7njW0D3diRws5HmI1Yamn5rgNSrhIMWd66sVTvoToKWp6TntOq6SE9T4nCbrKnHh7mBwB0hiIA4/y/v38WeBR4yYPnl7Mb9pRO2GTHcUEEXI0MDVJkYJbY1CXxyN5rl2wk8r1Pq0DVNSPspskxCTuPJZbgbebcvVW4X7oGuP6I6YpZV/BMYJqsPcb3ao8RdjfSDgsAt+xOkCZQY7en3CFEDaeBqCMYGXabQNjxgdRpGSScFF7x8K34P/7cU3DfLbt65pVOQo2lsBvLsOO86JnYUBkRcWLoG9Q/4w03fFMiniDwEHY2abHD/58kYua/YgHLhmrMUsL7lG4AuwHtb3o1Bttc1eFrXLXLA7xEIV+va6e94iO/xhR21jYDtiWW1iNHk9zW6lg5rQEYu6ETL6z/79tXxqw2KePJtrzG4J/V477cxNHliTRdnMCylYpLKd36Pr8F1rtQZp+zzcsThcAidlrxvKvTnmN9g2Er7DRR5FcD+8DtnDObsPNNxvUsP5MqKz9hN7wNqoymFu/DKH0IsL7xG8MOQMZLJ5TCLZRwa5nCbvGW2amdA3jaMuyYwm5WCCcFZVoCQML+vr1zBr/27Z+qSwQXhXXcXJcqtFUTdvtbtH0JKuTIII+ZNBd5XhZ2S3F8dkjRZhOk8hhJJ1Q60bDm8IHz3La2Pdap28S+EKzji5OJ3rzPNBP3xlc/BPzo1wFf9mOLr/NGw2iJlfvrGA46nqt4fufGfj/TNMFDt+3hHR8VY51bl7GMrzmU8rlqVH7sWmfY8cHQaZHhnxSSJME3veohvP7ZjOnnSgGAZdiNNKjw/I6BwUZERMQx4SudiIg4SZAlltmM7Oa4nYmt/No1/8+uCzulOVdnZJv4BoQe8otmSg3iMMu1dUPZWnmm24BSKivgtrX6VHIsxF8RdsxOO1iUQU2hlvrffs88/67QN/h8OxRKi7Db0vZ4V6HVQ/ZNr2DdkSSJOuYeuy5u8HYWmKU/Vh6c0xK7CPll21qXUcktX5RxdbqMjdfc5jJfxE478D3ZcJDCru3EflU36W3tteD7QDdQ81pk/C2qsOPLH3GyDQhW2DkKN65QCyDc9PKNZes98kd2OMtrwm9WN7pMoD5ipRMDhB0LV59x0vI0tsQyAcT5+UcAmJNGKb/OFju462B7uYZYwCGhDjuxD+3A/uNif1tvX5Ww1/ao6wDgrnPsWGJur1RGv5hq3oFzDYtuKhN+flpC3GPd55qEXc823Pls8ZNyBtYdtK97irgWBVfYrZoEDsG3v/apeMrtZ/CfvubFN9SOe6NAY5yTmixbucKOyyyjwm4J0EWyrYC21Tc9xW7/MsBGZOBERJwKVIEkekTEquCzxNqEnUXCodwFmMCO38DZbWHGDYZqTWXXFMPWOmCnpfXMmWLMKH8Qz9UFDGzZJBHrqQ69uXs24WOUPxQ+dZ5rTe0lbezvsqdkQ/9/RGE34YSdDOuuqCHWWi8tuwEKO0CM746qBo/L0pBFbDVbFum2kK31GAo7myQ+lrJvoWUtsm+J9V5dQVFGmvSEsG8g+D68clSZFr1AddsWU+k5ZJmajBvIj2PbIMjYBHOUKDEPV9ixjMK67TBPmUIuQCmoSidqsjJya/D4e+AKu5lNWqrSiXFL7lwqBGc+hd5pydJOM2HlPHocH9l7BvCoJsPTBEgmzP00Fl00BuszP5QlDyensJOEHfFXParIW/f0Z5mUO8D0cfH0LUHYTStB3AIj5yqWGzdNdc7zUqSGRUir7zEGCLvP/z7gT3/encxcV/DjwRMTsijOTPQ+OncTCLtXPnwbXvnwbTd8vTcKvmb4VRJ2K5924zcRS8lcn+jgJ8xmHk4OPPRp4ieTHEdERJwATltGS8T6QxF2rHTCIkt2bfKENbIhSY1l7bYwm8BzixS4fWWMsLMGlJ7WVIJD2gRkyXlJG6+d1l22lwCxb7QYCWePY5xtdgi7PfZce1mb7JPkHg3G1xx24cauTRIPwCHOFsq/W0XpxCqWPU6z7TJqxGPk7rH1nhY1A//sLh1Vph3Vc87wgY6lo6rBkaEOm+kG+AF1Gi//uCSt4VUqx+3BhJ2pgjQVauOlEdx6ZWTgVYdeZXPf8rO6EQo7tTxT2AW01E6lpdbMsDtlhB0AfN2bgFf+bfzGfSKf+CorTUq4mOK4k7gWkUTFDAcrti+eZZbdmivsPA2xAPD6Z19EkgDPv+8cEvYe8y1xrZtVgaUTDG/d/UT1+MwyikTr+OLkfe6zxAIiWurpnw08+dWLr+9mwHc8lcsX2vFx3tllbdsRvbBV9cBqLbGrL51gg9nQVqsIBn4SalimxtiMwHO+RNwo3P2ik9u2iIgIlnMTFXYRNwiqJbY/w85RO/FrxmTPaE60CTqbwMNkT6vcAOPmzyYGt23Sxia/hrLzehtXO2e99uylQWKkuSAlu9afuzdG+AyQbraScTjDLjEG1K46b7MVdlvWZ7+QJZbZAMX/j9Mwe4MsscdoiT0eUXic9Vrfk1M0cZ4kCSZ5ilnd4rHrc3RIUScF8q7yNjz7QOfJoznlx/kUdv3XdrLTN22HS1JpqkiPwG2wVZBqG4Iz7PR3KUGCtmMZniEqQa6wq1qLMKTxTb9ajM6J87rF4ZwRfuj0uWyAcNw47N8JfMq3IvmldwLgeZiZmS9+XOUWi1Po0hxZUSIDcM/51Y41uTWyTktAFt72HXMXD7bxm3/zVdjbKoD/cEGUqwFI9+8AcFUQ36Hn9S/+QeDPfgu/+sFPBz7yMQDAvj1hGALrO8rJe2+G3SYizYRNudUWy+MQdrczpeR7P3594JkRy8CeGC6z1TbxRoXduoHPatUzncsxRg6kGfCMzwHO3nVy2xYREcEsJ5Gwi7hBUEHg/ZZYR+00YQO7yVnjT/aMtpO5wweF5Z4RRG0vu2cPtifWgJIRWrZt134PQ1lydumEY6elm2SPdcS1No6p5PR7sN/f3sSamebLTvaNfWWTqL1E4bVHsAmwP6+FLLFjyswB2GPJpWytSyj77LbW4yx7nLKLG/V+NwF0/vn4NXFOVOH1SmE3QthxhR0nmwyyqv/azrMcqXyldhR2YRl29Pkqwq86CrSkSkts1WLetJgaLa/jhJtSyFWiNEJn2E1Zbnb/fuTngcu20jFwH2wi9HdakOFbeQpsHegnHHdMyK4lSbmLN337q/C/v/WVbtzFMcGv4XNuKx84Zm7b3xLn+1Qvm++LfD+jCGrsXPWUTwde9R3Ynuj1nt1ZQu1lfc9n7H2cKrEQ/0zSwsgxXhR5luKLXnAPAOAvvuyB425ZhAU6L9Nk2arLnk62dOI0fWluFJJEqwqmV0QFNXD8bISIiIjVIMByEhGxUjSsxU1iuzQv34MKOzZzD7gklGNJMci+vcHnuoQde36+vaAV1/pOsRsg+2ap14o7YKclhZZjU5iY+4cTlvb7dbbZIOyG95VDjFII92PvAv7FJ619GPZobuIA7M9rmTw4wiJjS21NPUY77VLWVLuwYpllj2PFPZmbhpsN+v59/Jo4Jzak5PK0UvuwrcgqYYk9InXa/FCr00Zz8MRrXJKfbbMgaahKVA5peXmOJLILGCR/uKX1aN7gSGadoToKeg/cFmxk0HWtnvAYuOcwrMmHc6t449Lo9m8q3MbpDNi7Qz/h2IQduw6lBc7tlrhtf/XRK3mW4japttrZXdTSqxVDW4U4bq/PG/W70AkCXpLFM/WCYSvsWIbdIqVEaw9OnNuToUvgH37us/Cz3/xyvOaZd4w/OWIh0PnhpAi71ZdORIXd8VHuilmy62zWPRJ2ERHrgQDLSUTESkG5QGyQerDNMlvSxB0oc5WcRUidsVRiDulmLGsOEm3CyiX7+gksm7AaJAoBbzstL53wPnfAEttrE+TbWZ4RivXgbWbLbtn7ecR6vMMzZxPDtryOsFVyi1liRxShg+s9PtnXyFrjY+XQLUH20c3sUsURx7LELk4UbgLouHnkirgON5n8nh+JIPxRsq1k6rKqUcH+qK4HKewAPVlCGXaKsFuQNCTCr80mQMveAxCkkJvVLdoOqI0MOnoPAwo59r11FHKHj8nl+/dBmmprslAZJqjTCfJ2Bhw+Prr9m4rStqoXmdEiizPHJEH4dbpr+p+3AvzLL30+Pnp5ilt/dx+4JH8Z8pnd+2Lgfb8KANgq3fNSaGYXn+xZKk9tSGF3mrgH/j7tRvolkKUJHr7j+K8T4cJuiV1lfh1wAoTdVsywOz7KHeAQwHXh70eaH0sGGxERsSK0LbOsnL4Z5Ig1hSc3kbd8nd8t3awMQ2FnWWKHWmKBhRR2ixB2TnbeEFFoLa9y6PpsreomubP+71F3DWXYWds8yVMUWYKq6fzbvM9iKPbuNP60VaRIE0ByRa467+A+tv3rf43n47skWYxI4ooKwHPMDcB+rl1+MYRVKPu8rcYLr3eJ4oglbK3Hyc7bBNB3iBSEHRF2RDSN5IhtG+qylhF2Yeo0/hqPX5eWVhoL0DaMLE9E92PXBeHXpqUk7Njyaf/xoksnWtRNh0ZZWvl76B+fGJbWQ7u8gwi3MdIyw6xumcqwlITdo0HLbyJKtt8B+Tlwwu7Wh4+3Ataiirbtf94K8Lx7z4kHv8eO1ZDP7JP/D3FCfPrrHYW10dw+Aj55tb8MYWdt65Qdw07UxiaDk7grUNhFnBxovECTdBtgiY0Ku2ODblqIsDuFM1URERsJyq8DosIu4saBCDt2E3aO5b5cOONRdHDyy1J+7VgDWpc4sxRnDKMW0SF1nm0RHcrds16LblKJOOsvrHD/H1z+YD+GyKzi2+0QlGfvYes0P4fRZflNOb/xW1NwZc5umS8UqGyrC3cn4TdV7jEXfoM3+tkPLmsTvYuo846R2SfXQ0TvQmSfHHfPG0YqnCI43yH6zimiaHi8rAi7ubDETskSyxtWx8gqUsiRwi6Tz6cx+xhpWJoZeCqb9ChMnaYssVWDw3mNKZGOvHRnYHySMUU2KeS0rZcUdmH7kYo3WkVaflz8PG4BwxrCvgHfKlJg54L+xS0PrW5lbT3+nFWAX7NC7jXLXeDV/ydw8bnYKTJDFL7Iueb5959Tj5dT2JnXWlNhd4oIu+0D/fgYhRMRJw/7+F97wo4z20tVNUfoC93Vj8r/xy9pRMRagAb0QCTSI24cRhR2t5zxqLN4to5liU1Tk2gpnEy3AYXdaAnDvv8xQsg+tq5ix1AcjKrkhgorxtppBwg7ezudbWYlE9i/6C47GVgWAN7wL4HbngG85rvdv60ZeEPwIoUTQIAyc3C9yy9rZz0uU/5AWGQAPnq8ntiyyxOUmwBbbZnQOZEIu0Cy7Mq0QtN2WmEHBGfQESHwOGXQ5XIsQOUxI9tACruPX7WiDgJVgqRsOpQ5fFNeHBBKuMlteJRUfrmlVBwhLfU+kKQl7YNTLDSwLW5bRQZceDLw8GuB534psH2uZ8klcP8nre61hpAvqLBjSNPEODcvcq554f3n8dBtZ/DgLbu4sLuEutxSkKriFJxmwu70keCnCce5bodg5YwaH0jdujec4xDRA7rQXf2Q+GnZmSIiIm4S5tfEz3x70LISEbFSeLKVzu9wws5zrT17t3686DVkIP9uu8iGbZ4D5NdOKWbkyWLoZLoNEIWjRERhDWbZDaNTluCsl71HrpiQ4DclXrLos78XePN/AF7+be6y7PnO+wWA5/wF8W8DcMCOOe97GcBoFuACyzqK0BNar235WiSzzyYZF7EAjxLMQ8sewwK8CbA/v6S0iKKRm9otlfEnFExHnOyakTpt3A4KCFstAHREVlFcxsgkOx1HZJ1q6dwVUPgAaHVq03YQr5ChSzIkXaOVWWO23CLDJVQq27ErdoD55eCiOyJF6Fze2uffU0gu2N+t3TIXEzZ/4T+vbiWv+8fA238CeMO/WN1rDuEYhB0gvo/XZuKYsydHhlBkKX7im16GIkuRpUtktxZ2hp2eODxVGXacBI6W2LWGrYRfJKc3BCs/qu880F+iSNgtCbrYX/mw+GnZmSIiIm4S5lJhV56+2eOINcaIwu5gx2Mp4VbNO57p/PnrX/EkAMBXfdID7rJb/bkpSZIYRMYiDbNJkuAMW9YhMfiNrnXTa1so3eKIfjutq+6yiJfzbB+cux82OEHkJXye+0bgL/4ssOfaWvl7XIS0WUeYNuzFVBGjzcQDOI46b9SGPQD7mFssd2/5wbtNMC+iGLGfe/osseb7S+kcQ5NpY0STRSqkaYbOJrc8KlsO+/Pp7HWOqvws0tE5d40Qds6xlLhky5hCziKfO5tkHLUFm/uxG5gwOS2wFbaL2PqD8cKvBr7sx4DdW1b/2j7wz3mJz4xP2Dlq+xFsFdlyZB3gKuy4JfY0qYq3DvTj7fO9T4u4+bCvtYu6EMaw8tHjXQf6S+Sd9Y8YB12sr0rCbhIJu4iItQBZYk/h7HHEGsOTYXd2u8BXvPR+/OZ7HsPnPPcud5kDRtjd82Lnz9/86qfgZU++Bc+7z2PjOf+gfuwhsDgcOy5vytu91Xn+/naBq3JGfpGyC1vttGsPhpzCCv1/ez3ODe85Tlq6NxB3HWzjtyHype46t5gKYZTs2yCcYwq7C7uLje/sZuLjkF9ea3HfssdQuq2UKFzg5n6VasRNJ4lt7Fv5hdm2Ra4Flk7w/yfFjplPuyBhl0wWI+zsDNHEXp9NfllI0wQ7ZYZDqdBLEwjihUhLYJRws9WiiUPYhSns1PILko6bCHufnYrvFldwLamwU48XOC8fG5bCroL4bMo8dSI/Nhr88+GuiYi1g31OXDWhv/Jv10VG2OWn6UtzI0EX+ysfFD+jJTYiYj2gZvEjYRdxA6EUduYg9Ttf/4z+ZbbPAZ/5T8RjT7Zamad46ZN7ZvFvYW13tz7V+XPNGuyc4oHb2PNve5qzLCewLh5Yypay3047qnaybxjZd3R02TQFLjwEPPpO4Omf7Wwzb7F78JbFbCnnDSXk+jfBDuHsMRR2/DNIksXspbY6bxE77irJr4UIuxUqChcr6LDIzdNAKjDcvm+eM4pta0J7hCwTZSnayrldZmIZyn5L0gCVnrmPs8lidlCHLLMJuwCya3eSK8Jup8zFa5AtGBi15Tqk45ZNGoYVbxDSrf7z72nBcdS6awuDsFtCYcfbXm8oYWcfX2IcskiD+EaAfz77nonZiLWBfX7YLtbcErtVZHjw1l1kaYLn+2buI8ZBF1pqe4qW2JPF/FDcEHcd8OHfE1bk5gY1NEVsFqIlNuJGo211NtKiA+oXfKX4tyi4ws5Dun3jK58MAPisZ7tEIC6wpryDe50/U3sl4KrmzPw787o3WjxgN9uyMoggpdRX/QzwVT/nDfvmY5lFm7/uu6BvLJ5062bfxBoKuwUdFJx0W7Rh9jiqMZvsO0477UKqQPt4PUbu3mJqxNOtsLttXx93e5McmUM0DZ8j09Rsbj67XZjk1GQPGDk27WMqd1R+I2SZRdjl24up2wDz2NwqMnNiv9wbzdi1bbnOfhzJwLOP52wJ0nHTYGefnorv1g6zWR5XYXcj90fqvw6fqsIJALjr+fqxx7EQsT44zlgjBCfy7frpv/LJOJo3Gz+bfNNgX+yjwm61eNcvA7/yj4EPvllcoA4/LgZIF54MfOT3xXMmZ4FX/A3g2X/BvKBFPLERLbERNxpUOAGM3kStDHkJfOmPiuPdo8772pc/Cc+46yxeeL/n3FhsAS/7a8Cjfwrc+1Lnzy990gW8+2PX/YN7buM9Yw5OR4mISX/+nV2U4b3R2r2lNzfo9c++iKN5g0+4+8D79yHwXJN7z2/2TextLJd40YxibmU8t7tY1tGeZYNcqPxhhbbW46nkFiH7llfJHef9bgJu29PnwLvP77jX4oBr8/5WoUon9rdyoOATBePj7bPb5vFY2OqywJZXQr6gShAwP9ed0iLsAib5uS23zFKdBUgYieKxrcnFEqTjpuGMM2l0CsghruBaIjdvsEH9JmDVuWE3HXc8S7TIX3o/cPG5N3trIgYwyVPkaYJaDjTXPsMOEAz3qWO5byRsgihm2K0Ob/3PwI9+HQB551Zdlz8PNVkHiLawn/1b4t9TXiP+PesLVtPS89h7hHXh0vvFDfgf/jBw+QNC4be1Dzz+PqCeiRnSvTuAh/6cCB7tWuDuFwAXnwfMr4tB3QIqhYgVYC6Pl1No94hYU1QsW2mJGfCl8aRX9v6pzFO88uHb+pd99Xf2/ulbP/2p2Nsq/Ll7F57MHj9k/GnU1mo027pFGbtlzrLzFhufJEmCP/8iVy0Ygtc/+yL+0c++Ay+6/zzybLPtOvdd2MHfeu1T8aePXMPrferKAXCCj+yIoXCaQRdS5x2nOOLm2GlHMxeHlh3Letxw3G4p7Jy8uQCiaH+7wAcviYkQobBjY+6R/DrAJavKBXP0bMLZsfXyoPke8ON6d5KbhF3APQMvKtqdZJa6+SyQDR9znLTM0sRV6I2oDDcRO8c4l6wteJGBR00/hgss8sGeWLkZKDf8GusgSYT6v545k5gR64UkSXBmK8elwwrA6i3zp+BscwphN8HcqLag0443fa8g4ADgSa8Cbn1YEGdtI8I8t/aBhz5NEGN/+ovAL32XeO6f/Iz491PfArzgq4CXfD1w4Unh6/3A7wC//4PAn/wPQdItgkvvA/7sN83f5VsiIPnM7WJ7b3mKeC87F4CjS8CTPrVXLr4Q2gY4fAx41y8Cb/tR8bvdW8S6n/+VwH0vXT1h2FTCnryuNnAi7E6h3SNiTUGqzqwctTltAs5uF/gbr3Fz8QCIc5p6oknolZk5e+moGwYUdoC4uSLC7kaqju45v4Pf+Juv8jf5bhiSJMHXvnyBa5+1LGFetwPPXC2Oo3Q7TpZcmaco81S910UG7ztlZuSsLbLNWZpgu8hwVDULL7sJ4JmQD9yy637Xtw9GX4Nnbe1vF0C5GGFnK+wmZ6wx+whZxRu+AWB3qxSTgDSBvDMeJ8SPzQu7pUnSBYyfuANqd5Kb58+Afcj3wZlJjoSTlJN9odI+ZSgy8zvtRDpsIvgkIM+uDQTPlLzhat67ng988HfRPulVwNvEr5ZunV1nrOv9UISDMxNN2C3iBAjBKTjbnELYCrvdASXDExXv+BlBgD3jc4EHP8X829El4C3/AfiDHwZmV4SMeHYNeOfPir+/+C8Df+67hgcUF58LPOdLgEf+CPihrxCv07XAb///gN/+t8D9LxODsovPBZ7/5WJGdbInSK4PvVXY2H7/B4E//G9mcxfHhScDbQ1cfxR4xhvEhfPoEnDto4LYm+yJx/t3Ac1c/P8Dv63bzK59VLxPH/It4I5PAJ71+aLl8c7niEFYbtmYuk6QbtUR8JYfEHbhR98JXPoz04pn4w9+SPzcvQ3ICk0cPvvPL2Yh/sDvAO/5X8CH3gL82W+J94REqHte8beAe14Y/lo3AjSgjpbYiBsF+r7fSHXdzUKSAJ/2D4AP/i7w1M+0/pRgd5Lj8lHP7KWdYWfBUaTcQNxx9gZZmdccn/2ci/ixt34I3/ipTx5/cg9ssmQMdjj+IjeVW0VqWKkXvSE9M8nxWD1feFlShF5bkmDenWjC7rRZYpMkwc//tZfjX/3vd+MbXvlk4KPvMZ+wMz7BzZVAZ5cg7PatY3Dr3B3mE0Ym2XfLzCB+DnYKsV5F2F0Y3Yaz2zxPslxYYXd+1yTcjHPm9jhhaBN2xnsOWH5TsVtm6nM7Fd+t254OPPPzgIP7lpqI5te287s3mKT9ov8IvPUHkD7vK4C3/RaAU5hhF7FRENcWce+8akL/FJxtTiFswiPKYE0cXQJ+5GsEifa7/w744h8CnvJp4m/1HPh3rwM++of6+Y+9Wz9+2bcAr/o7Ycqw/TvFv2/5IyFH/vDvAb/5rwTx995fEc/5k/8B/M9/KB4XOzIT71H3tc7eAzzl04F7XiK25xO/YTl77eFj4vW3DsR2PPZu4P2/CTzyNuDocf28egp84LfEP46LzwMeeDlw7RGh3HnnzwFJBsyvjq/73k8UA0EiPgHg+iPi5+9+v/j5s39TEIQH9wH3vEiogi69D7j6UdEeefkDghRsGxGk38w9K+qAd/2S+KzWDUeXxM9oU4+4Uci3xMTEjcqvu9l46Tf2/mm3zBRh59ws8RtGj0KF32DedfAEID/XEN/9uZ+AL3nxfUsVkv3LNz4f3/njb8P3fNGzF1rOts8uosBIkkSRdYDZkhuCItPruv3sYpl/O2WmCLtFLdy7kxwfvzZXj08bHrp9D/+fL5DHwSWLYAuYMNzf5s2WBbDFCLIgskwfBztlhmyPTapn5ShhlSQJLuyW+PBlMRlz294EOHMbcO0jwdvArcHnd0vTRrugwu62/S1zvwUQbvs2YcfV0QHbv6nYneR4XCpoFp08WEukKfD537f04twS+7x7bzBRu38n8PJvNX5lT9BERNxI8Ab7qLB7IsC+2PEL4RMdXQf8xF8VZB3hp74FuO83BAH2S39Pk3Wv/k4xa/meXxGDoae/wdsAOIrJnvj35FeJfx97h1DPvf3HgekVPciqDrV9jbB9HviUvwG8+C+txj66c14PrJ77Rv37thEk3QffDPzaPxEKva4Vwe8cH3qz+OdDvi228daHgVf/XXHcza4Adz4bSHNtx2sq4J0/Dzz+XqE0+9NfkDbiXxDb8Ph7xb/3/C/z9f/05911pgXw4CvEZ3flw4J4ffh1ggi9/2UL754Tx5UPiZ+eIP6IiBPBwT3AF3z/zd6KtcD+doEPyZtch4jgMQXnHnCW5c+/GAm7m4LtMsOLHliuxOk1z7wDr3nmHeNPPEFM8sUG4Dyrb9Flz+2UeOSqaIdelBjgGWt2c92pwx67Fm+dFYr/EXCS4WCnALYY0XDuvtHluaX2/G5ptjeWZ4LGeucZYXf7/paIZaEcZTsWxwNeAHNht7QIt/HleePznftbYlJZLb+Ywu7iwRZwhhGnp5iw4yVCi5LwpxEP37GHJBH75aHbbn5u4f23RPdLxM0DL17hjearwCm/km8obEl/rHLWqGeCHEpz4I3/DfjxbxLk1M9/h7B9/vo/Fc/7oh8AnvZZ4vELv3q123Drw8CrvkP86zqRg/eRPxCDtHouchW2DwR5FWCvWAnSTJBnD3yy+EeYXxcqtsPHgPf9ulCuXf2IKK9AB9z/ycImO78usu9CbHdZATz1tfr/z/9y8XN2DZheEqUZH3qzsO9e+jPxWX3gt8S6zj8A7N0p7LpJCtz5CWKgauO2noyrm4muA972I+JxJOwiIm447ji7hT/+iFAD8+wcAMA+O494zmO8XfJU5txE9OLrXvEk/Iv/+S589ctcIvck8Ql3H+AX3v7RpZbdYrPzd59bzKrGyZz7LpzyG1iedZmF3SA95XY9LnvqHftAcyd7vXs8S5i486w+v+yWuRmREZgzygtobt2bLKxQ4+e/87sTYW1Uf3zG6PLcEnv7/sR83wG52fde0Mfk7ftbwBluiT0YXX5Twa8dt+xGwu5gp8SvfNsrMckzpDfxuvrPv+R5+MHf+TN866cvnsMXEbEqXDzQ5+V7FrxujyESdusIO0fAzh17IqPYAr7w34uZyDufDbzu/wb+4+cBv8Mk3Xe/0Mk/OjEkiVDvPflV7t8CZnpPHOUugF0xY3rhScDzvvTk1jU5I/6dvXs5JeO64+f+tn6872m4jIiIOFFUjS4ruN2evUxT4NanAh/7Y6GmtvDNr34Iv/6uj+ONLxlX0EScLvy1Vz8FL3/oVjzvvoOFl/2eL3w2vuUHfw9//dOesvCy3/WGZ2BSpPjKl96/8LIdk+eVTNUTAi7wuuG5UjcafFK0ngUt8hAj7J5xcR/I2CTnmfHM6G1GptatPCeduUO4LR58RdA23Ht+B7/3Z5cAyNwtnkF3fpxYvo0Rdi964Dxwlqnibh2f8Hz6nXp9u5McOGDq1YvPHV2exwqcs1WGAaTnpoJbiW8mQbVOWHRC4STw2mfdidc+687xJ0ZEnCDOMxJ/1dnFkbBbVzz51cJieKOIp01CkgiyDgAeerWwvv7yP9R5aJ/3b1ffXhoR8dTXAW/6Z+Lxwb03d1siIp6A+MQHL+DX/vRRlHnqZJMBAL7qZ4SC+LanOX+65/wO3vQ3PRMrEaceZZ7iE5+0nE3vc557F170wPmlcg/vPLuN7/3i5y213tc+6078/gcu497zi98Mv+TBC/iFtz+y1Ho3EkTU85iQATzrrrP4rGdfxIXdUja2lsDrvkeU3Twp7Bzxt177VPzDn/5jfNcbnil+8dW/IPJ9H37t8IISf/+zn4k0AZ57z4H4xYu+RjgTXvINQU6H59xzgC9+8b146h17eDJZET/lb4ic4HteNLr8dpnhe79YqJK+6IX3AGUJPPTpwrHy9M8Oeg///Euehx958wfwl1/+JDFB/ervFMu//K8HLb+JePXTbsNvveexm70ZERERawh1PodolV4lko5P4/XgypUrOHv2LC5fvoz9/Ri2fkNw7WOiAfSFX712lc436nhYaD2PvRv4458Cnvdl5kxlxKnBjTwP9a7rHT8jWn+f9fknuv6I9cJanvOegJhWDb7/196LVz/tNkMlc1oRj7snLuZ1i//+lg/gZQ/dujBZOK9b/NtffQ9e8fCteNqdi3+eG3fcfeitomX+BV95w5wNXddhVrexlXKFWIsx3giqRny3PvmhW/CMi/Fe47Rg4855EWuJruvw79/0Pjz1jj28+MHxScJFjoeosFtXnLkV+OQ1bMlcV5x/EHjpN93srYg47Xj4NTd7CyIinrDYKjJ83SueNP7EiIgNR5mn+KIXLqfkLvP0ifU9ufgc8e8GIkmSSNY9AVFkKf7ypzyBvlsRERHBSJIEX75EBEYIVqvXi4iIiIiIiIiIiIiIiIiIiIiIiDgWImEXERERERERERERERERERERERGxRoiEXURERERERERERERERERERERExBohEnYRERERERERERERERERERERERFrhEjYRURERERERERERERERERERERErBEiYRcREREREREREREREREREREREbFGiIRdRERERERERERERERERERERETEGiESdhEREREREREREREREREREREREWuESNhFRERERERERERERERERERERESsESJhFxERERERERERERERERERERERsUaIhF1ERERERERERERERERERERERMQaIRJ2ERERERERERERERERERERERERa4RI2EVERERERERERERERERERERERKwR8pAndV0HALhy5cqJbkzEZoCOAzouTgrxuIvguFHHHV9HPPYigHjOi7g5iMddxM1APO4ibgbiGC/iZiGe8yJuBhY57oIIu6tXrwIA7rnnnmNsVsRpw9WrV3H27NkTfX0gHncRJk76uKN1APHYizARz3kRNwPxuIu4GYjHXcTNQBzjRdwsxHNexM1AyHGXdAG0Xtu2+NCHPoS9vT0kSbKyDYzYTHRdh6tXr+LixYtI05NzVcfjLoLjRh13QDz2IkzEc17EzUA87iJuBuJxF3EzEMd4ETcL8ZwXcTOwyHEXRNhFRERERERERERERERERERERERE3BjE0omIiIiIiIiIiIiIiIiIiIiIiIg1QiTsIiIiIiIiIiIiIiIiIiIiIiIi1giRsIuIiIiIiIiIiIiIiIiIiIiIiFgjRMIuIiIiIiIiIiIiIiIiIiIiIiJijRAJu4iIiIiIiIiIiIiIiIiIiIiIiDVCJOwiIiIiIiIiIiIiIiIiIiIiIiLWCJGwi4iIiIiIiIiIiIiIiIiIiIiIWCP8/wEXq8SwLKnx/gAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "myDataReshaped = myData.reshape(24,26,4096,1024,2) #(modulation,SNR,frame,I,Q)\n", + "plt.rcParams['figure.figsize'] = [16, 16]\n", + "plt.rcParams['figure.dpi'] = 100\n", + "for x in range(len(myDataReshaped)):\n", + " plt.subplot(3, 8, x+1)\n", + " plt.title(modulation_classes[x], fontsize=12, fontweight='bold')\n", + " plt.plot(myDataReshaped[x,25,0,:256,0], linewidth=1.5)\n", + " plt.plot(myDataReshaped[x,25,0,:256,1], linewidth=1.5)\n", + " plt.xticks([])\n", + " plt.yticks([])\n", + "plt.tight_layout()\n", + "plt.savefig('images/modulation_timedomain.png', dpi=300, bbox_inches='tight')" + ] + }, + { + "cell_type": "markdown", + "id": "6b9daad3", + "metadata": {}, + "source": [ + "### Split training and test data" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "9170a762", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(511181, 1024, 2)\n", + "(511181, 24)\n", + "(511181, 1)\n", + "(2044723, 1024, 2)\n", + "(2044723, 24)\n", + "(2044723, 1)\n" + ] + } + ], + "source": [ + "X_train ,X_test ,Y_train ,Y_test, Z_train, Z_test =train_test_split(myData, myMods, mySNRs, test_size=0.2, random_state=0)\n", + "print (np.shape(X_test))\n", + "print (np.shape(Y_test))\n", + "print (np.shape(Z_test))\n", + "print (np.shape(X_train))\n", + "print (np.shape(Y_train))\n", + "print (np.shape(Z_train))" + ] + }, + { + "cell_type": "markdown", + "id": "f9b6b8cb", + "metadata": {}, + "source": [ + "### Build CNN Model" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "2d918a19", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-08-14 14:53:54.633186: E external/local_xla/xla/stream_executor/cuda/cuda_platform.cc:51] failed call to cuInit: INTERNAL: CUDA error: Failed call to cuInit: UNKNOWN ERROR (303)\n" + ] + }, + { + "data": { + "text/html": [ + "
Model: \"functional\"\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1mModel: \"functional\"\u001b[0m\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ input (InputLayer)              │ (None, 1024, 2)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w1 (Conv1D)              │ (None, 1024, 64)       │           960 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w2 (MaxPooling1D)    │ (None, 512, 64)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w3 (Conv1D)              │ (None, 512, 64)        │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w4 (MaxPooling1D)    │ (None, 256, 64)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w5 (Conv1D)              │ (None, 256, 64)        │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w6 (MaxPooling1D)    │ (None, 128, 64)        │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w7 (Conv1D)              │ (None, 128, 64)        │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w8 (MaxPooling1D)    │ (None, 64, 64)         │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w9 (Conv1D)              │ (None, 64, 64)         │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w10 (MaxPooling1D)   │ (None, 32, 64)         │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w11 (Conv1D)             │ (None, 32, 64)         │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pool1d_w12 (MaxPooling1D)   │ (None, 16, 64)         │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1D_w13 (Conv1D)             │ (None, 16, 64)         │        28,736 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ MaxPool1D_w14 (MaxPooling1D)    │ (None, 8, 64)          │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ flatten_w15 (Flatten)           │ (None, 512)            │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_w16 (Dense)               │ (None, 128)            │        65,664 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_w17 (Dense)               │ (None, 128)            │        16,512 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_w18 (Dense)               │ (None, 24)             │         3,096 │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
+       "
\n" + ], + "text/plain": [ + "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n", + "┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\n", + "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n", + "│ input (\u001b[38;5;33mInputLayer\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1024\u001b[0m, \u001b[38;5;34m2\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w1 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1024\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m960\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w2 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w3 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w4 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w5 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w6 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w7 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w8 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w9 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w10 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w11 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pool1d_w12 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv1D_w13 (\u001b[38;5;33mConv1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m28,736\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ MaxPool1D_w14 (\u001b[38;5;33mMaxPooling1D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ flatten_w15 (\u001b[38;5;33mFlatten\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dense_w16 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m65,664\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dense_w17 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m16,512\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dense_w18 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m24\u001b[0m) │ \u001b[38;5;34m3,096\u001b[0m │\n", + "└─────────────────────────────────┴────────────────────────┴───────────────┘\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Total params: 258,648 (1010.34 KB)\n",
+       "
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 Trainable params: 258,648 (1010.34 KB)\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m258,648\u001b[0m (1010.34 KB)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Non-trainable params: 0 (0.00 B)\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "inputs = keras.Input(shape=(1024,2),name=\"input\")\n", + "x1 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w1\",activation='relu')(inputs)\n", + "x2 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w2\")(x1)\n", + "x3 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w3\",activation='relu')(x2)\n", + "x4 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w4\")(x3)\n", + "x5 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w5\",activation='relu')(x4)\n", + "x6 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w6\")(x5)\n", + "x7 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w7\",activation='relu')(x6)\n", + "x8 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w8\")(x7)\n", + "x9 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w9\",activation='relu')(x8)\n", + "x10 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w10\")(x9)\n", + "x11 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w11\",activation='relu')(x10)\n", + "x12 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"max_pool1d_w12\")(x11)\n", + "x13 = Conv1D(filters=64,kernel_size=7,strides=1,padding=\"same\",name=\"conv1D_w13\",activation='relu')(x12)\n", + "x14 = MaxPooling1D(pool_size=2,strides=2,padding=\"valid\",name=\"MaxPool1D_w14\")(x13)\n", + "x15 = Flatten(name=\"flatten_w15\")(x14)\n", + "x16 = Dense(128, activation=\"selu\",name=\"dense_w16\")(x15)\n", + "x18 = Dense(128, activation=\"selu\",name=\"dense_w17\")(x16)\n", + "outputs = Dense(24,activation=\"softmax\",name=\"dense_w18\")(x18)\n", + "model = keras.Model(inputs=inputs,outputs=outputs)\n", + "optimizer = keras.optimizers.RMSprop(learning_rate=0.0005)\n", + "model.compile(optimizer=optimizer,\n", + " loss=\"categorical_crossentropy\",\n", + " metrics=[\"accuracy\"])\n", + "model.summary()\n" + ] + }, + { + "cell_type": "markdown", + "id": "7b1a82d9", + "metadata": {}, + "source": [ + "### Training Model" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "4b17a38b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1280s\u001b[0m 640ms/step - accuracy: 0.2170 - loss: 2.3478 - val_accuracy: 0.3456 - val_loss: 1.7990\n", + "Epoch 2/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1260s\u001b[0m 631ms/step - accuracy: 0.3627 - loss: 1.7594 - val_accuracy: 0.4005 - val_loss: 1.6480\n", + "Epoch 3/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1264s\u001b[0m 633ms/step - accuracy: 0.3937 - loss: 1.6701 - val_accuracy: 0.4252 - val_loss: 1.6038\n", + "Epoch 4/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1260s\u001b[0m 631ms/step - accuracy: 0.4294 - loss: 1.5949 - val_accuracy: 0.4523 - val_loss: 1.5864\n", + "Epoch 5/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1255s\u001b[0m 629ms/step - accuracy: 0.4808 - loss: 1.4845 - val_accuracy: 0.5163 - val_loss: 1.3972\n", + "Epoch 6/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1280s\u001b[0m 641ms/step - accuracy: 0.5110 - loss: 1.4106 - val_accuracy: 0.5323 - val_loss: 1.3527\n", + "Epoch 7/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m 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val_loss: 1.2666\n", + "Epoch 12/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1306s\u001b[0m 654ms/step - accuracy: 0.5776 - loss: 1.2464 - val_accuracy: 0.5788 - val_loss: 1.2383\n", + "Epoch 13/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1280s\u001b[0m 641ms/step - accuracy: 0.5811 - loss: 1.2369 - val_accuracy: 0.5744 - val_loss: 1.2627\n", + "Epoch 14/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1267s\u001b[0m 635ms/step - accuracy: 0.5845 - loss: 1.2291 - val_accuracy: 0.5801 - val_loss: 1.2445\n", + "Epoch 15/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1271s\u001b[0m 636ms/step - accuracy: 0.5875 - loss: 1.2231 - val_accuracy: 0.5868 - val_loss: 1.2210\n", + "Epoch 16/100\n", + "\u001b[1m1997/1997\u001b[0m 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accuracy: 0.5986 - loss: 1.1961 - val_accuracy: 0.5838 - val_loss: 1.2289\n", + "Epoch 21/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1301s\u001b[0m 652ms/step - accuracy: 0.6008 - loss: 1.1917 - val_accuracy: 0.5961 - val_loss: 1.2125\n", + "Epoch 22/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1298s\u001b[0m 650ms/step - accuracy: 0.6029 - loss: 1.1870 - val_accuracy: 0.5967 - val_loss: 1.2028\n", + "Epoch 23/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1303s\u001b[0m 653ms/step - accuracy: 0.6031 - loss: 1.1853 - val_accuracy: 0.5953 - val_loss: 1.2081\n", + "Epoch 24/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1295s\u001b[0m 648ms/step - accuracy: 0.6052 - loss: 1.1809 - val_accuracy: 0.5898 - val_loss: 1.2205\n", + "Epoch 25/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1274s\u001b[0m 638ms/step - accuracy: 0.6064 - loss: 1.1778 - val_accuracy: 0.5940 - val_loss: 1.2117\n", + "Epoch 26/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1275s\u001b[0m 639ms/step - accuracy: 0.6072 - loss: 1.1756 - val_accuracy: 0.5914 - val_loss: 1.2203\n", + "Epoch 27/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1281s\u001b[0m 641ms/step - accuracy: 0.6094 - loss: 1.1713 - val_accuracy: 0.5995 - val_loss: 1.1966\n", + "Epoch 28/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1289s\u001b[0m 645ms/step - accuracy: 0.6098 - loss: 1.1691 - val_accuracy: 0.5983 - val_loss: 1.1990\n", + "Epoch 29/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m 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accuracy: 0.6205 - loss: 1.1432 - val_accuracy: 0.5907 - val_loss: 1.2402\n", + "Epoch 43/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1491s\u001b[0m 747ms/step - accuracy: 0.6218 - loss: 1.1399 - val_accuracy: 0.5955 - val_loss: 1.2242\n", + "Epoch 44/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1386s\u001b[0m 694ms/step - accuracy: 0.6212 - loss: 1.1413 - val_accuracy: 0.5957 - val_loss: 1.2284\n", + "Epoch 45/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1458s\u001b[0m 730ms/step - accuracy: 0.6235 - loss: 1.1366 - val_accuracy: 0.6004 - val_loss: 1.2046\n", + "Epoch 46/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1434s\u001b[0m 718ms/step - accuracy: 0.6236 - loss: 1.1367 - val_accuracy: 0.6005 - val_loss: 1.2076\n", + "Epoch 47/100\n", + "\u001b[1m1997/1997\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1297s\u001b[0m 650ms/step - accuracy: 0.6239 - loss: 1.1355 - val_accuracy: 0.5987 - val_loss: 1.2131\n" + ] + }, + { + "data": { + "image/png": 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169dn1qxZ+cQnPpHBgwfnvvvuO09/CgAAvBnPoAQA4Ly65pprugTIJBk4cGDnj5uamrqca2pqyo4dO5Iku3btysSJEzvjZJJcddVVaW9vz549e1KpVLJv375Mnz79TWeYMGFC54/79OmThoaGHDhwIEnyxS9+MXPnzs327dtz3XXXZc6cOfngBz/4//q9AgDwfydQAgBwXvXp0+d1t1yfK/X19Wf1uR49enT5vlKppL29PUkye/bs/OMf/8hjjz2WTZs2Zfr06Wlpacl3v/vdcz4vAACv5xmUAAAU9eSTT77u+/HjxydJxo8fn2effTZtbW2d5x9//PHU1NRk3Lhx6devXy655JJs3rz5bc0wZMiQNDc358EHH8zKlSvz4x//+G39fAAAnD1XUAIAcF6dPHky+/fv73Kstra280U0a9euzZQpU3L11VfnZz/7WZ5++un89Kc/TZLMnz8/y5cvT3Nzc+64444cPHgwixcvzuc+97k0NjYmSe64447cdNNNGTp0aGbPnp2jR4/m8ccfz+LFi89qvmXLlmXy5Mm5/PLLc/LkyTz66KOdgRQAgPNPoAQA4LzasGFDhg8f3uXYuHHjsnv37iSn37C9Zs2afOlLX8rw4cPz85//PJdddlmSpHfv3tm4cWNuvvnmTJ06Nb17987cuXPzve99r/Pnam5uzokTJ3L33XfnlltuyeDBgzNv3ryznq9nz5659dZb8/e//z319fX50Ic+lDVr1pyD3zkAAGfDW7wBACimUqlk3bp1mTNnTulRAAAoxDMoAQAAAIBiBEoAAAAAoBjPoAQAoBhPGwIAwBWUAAAAAEAxAiUAAAAAUIxACQAAAAAUI1ACAAAAAMUIlAAAAABAMQIlAAAAAFCMQAkAAAAAFCNQAgAAAADFCJQAAAAAQDH/C4fxktkD3W8ZAAAAAElFTkSuQmCC", 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "callback = keras.callbacks.EarlyStopping(monitor='val_loss',\n", + " restore_best_weights=True,\n", + " patience=10)\n", + "\n", + "history = model.fit(X_train,Y_train,epochs=100,validation_data=(X_test, Y_test),batch_size=1024,callbacks=[callback])\n", + "\n", + "plt.figure(figsize=(10, 6))\n", + "plt.plot(history.history['accuracy'], linewidth=2.5, label='accuracy')\n", + "plt.plot(history.history['val_accuracy'], linewidth=2.5, label='val_accuracy')\n", + "plt.legend(fontsize=12, frameon=True, shadow=True)\n", + "plt.grid(alpha=0.3)\n", + "plt.xlabel('Epochs', fontsize=14, fontweight='bold')\n", + "plt.ylabel('Accuracy', fontsize=14, fontweight='bold')\n", + "plt.tick_params(axis='both', labelsize=11)\n", + "plt.tight_layout()\n", + "plt.savefig('images/training_accuracy.png', dpi=300, bbox_inches='tight')\n", + "plt.show()\n", + "\n", + "plt.figure(figsize=(10, 6))\n", + "plt.plot(history.history['loss'], linewidth=2.5, label='loss')\n", + "plt.plot(history.history['val_loss'], linewidth=2.5, label='val_loss')\n", + "plt.legend(fontsize=12, frameon=True, shadow=True)\n", + "plt.grid(alpha=0.3)\n", + "plt.xlabel('Epochs', fontsize=14, fontweight='bold')\n", + "plt.ylabel('Loss', fontsize=14, fontweight='bold')\n", + "plt.tick_params(axis='both', labelsize=11)\n", + "plt.tight_layout()\n", + "plt.savefig('images/training_loss.png', dpi=300, bbox_inches='tight')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "f9ea7cc2", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m15975/15975\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m139s\u001b[0m 9ms/step - accuracy: 0.6004 - loss: 1.1973\n", + "Test accuracy 0.6012117266654968\n", + "Test loss 1.1940562725067139\n" + ] + } + ], + "source": [ + "test_loss, test_acc = model.evaluate(X_test, Y_test)\n", + "\n", + "print(\"Test accuracy\", test_acc)\n", + "print(\"Test loss\", test_loss)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "813480fe", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m615/615\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 8ms/step\n", + "SNR: -20 accuracy 0.04334349593495935\n", + "\u001b[1m614/614\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 7ms/step\n", + "SNR: -18 accuracy 0.0463302752293578\n", + "\u001b[1m618/618\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 8ms/step\n", + "SNR: -16 accuracy 0.04974696356275304\n", + "\u001b[1m613/613\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 8ms/step\n", + "SNR: -14 accuracy 0.05818107583954272\n", + "\u001b[1m617/617\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 8ms/step\n", + "SNR: -12 accuracy 0.08337982451691434\n", + "\u001b[1m615/615\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 8ms/step\n", + "SNR: -10 accuracy 0.1315186975324345\n", + "\u001b[1m619/619\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 6ms/step\n", + "SNR: -8 accuracy 0.1850729687421098\n", + "\u001b[1m613/613\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 5ms/step\n", + "SNR: -6 accuracy 0.26047674952784444\n", + "\u001b[1m615/615\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 8ms/step\n", + "SNR: -4 accuracy 0.3364163024697632\n", + "\u001b[1m611/611\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 8ms/step\n", + "SNR: -2 accuracy 0.41535705144612234\n", + "\u001b[1m610/610\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 5ms/step\n", + "SNR: 0 accuracy 0.5281440812766176\n", + "\u001b[1m611/611\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 8ms/step\n", + "SNR: 2 accuracy 0.6248145305704784\n", + "\u001b[1m619/619\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 8ms/step\n", + "SNR: 4 accuracy 0.7374747474747475\n", + "\u001b[1m614/614\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 8ms/step\n", + "SNR: 6 accuracy 0.8447774889126778\n", + "\u001b[1m617/617\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 8ms/step\n", + "SNR: 8 accuracy 0.8990923381167284\n", + "\u001b[1m626/626\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 8ms/step\n", + "SNR: 10 accuracy 0.927009485771343\n", + "\u001b[1m607/607\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 8ms/step\n", + "SNR: 12 accuracy 0.940218511647083\n", + "\u001b[1m611/611\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 6ms/step\n", + "SNR: 14 accuracy 0.9425646275915024\n", + "\u001b[1m617/617\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 8ms/step\n", + "SNR: 16 accuracy 0.9455254890037499\n", + "\u001b[1m612/612\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 8ms/step\n", + "SNR: 18 accuracy 0.9457621920049075\n", + "\u001b[1m614/614\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 7ms/step\n", + "SNR: 20 accuracy 0.94831013916501\n", + "\u001b[1m621/621\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 7ms/step\n", + "SNR: 22 accuracy 0.9477739726027398\n", + "\u001b[1m614/614\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 8ms/step\n", + "SNR: 24 accuracy 0.9477300488599348\n", + "\u001b[1m621/621\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 8ms/step\n", + "SNR: 26 accuracy 0.9490987815929917\n", + "\u001b[1m611/611\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 8ms/step\n", + "SNR: 28 accuracy 0.9460924713584288\n", + "\u001b[1m612/612\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 7ms/step\n", + "SNR: 30 accuracy 0.9463118103800572\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "snrlist = np.unique(Z_test)\n", + "acc_arr = []\n", + "\n", + "# interate over SNRs\n", + "for snr in snrlist:\n", + " i_SNR = np.where(Z_test==snr)\n", + " X_SNR = X_test[i_SNR[0],:,:]\n", + " Y_SNR = Y_test[i_SNR[0],:]\n", + " X_SNR_len = np.shape(X_SNR)[0]\n", + "\n", + " # model prediction\n", + " pred = model.predict(X_SNR)\n", + "\n", + " #Pediction values are onehote, corresponding to indices representing different modulation types\n", + " pred_ind = np.argmax(pred, axis=1)\n", + " expected_ind = np.argmax(Y_SNR, axis=1)\n", + " matches = sum(np.equal(pred_ind, expected_ind))\n", + " acc = matches/X_SNR_len\n", + " acc_arr.append(acc)\n", + " print(\"SNR: \", snr, \"accuracy\", acc)\n", + "\n", + "plt.figure(figsize=(10, 10))\n", + "plt.plot(snrlist, acc_arr, linewidth=2.5, color='#2E86AB')\n", + "plt.ylabel('Correct Classification Probability', fontsize=14, fontweight='bold')\n", + "plt.xlabel('SNR', fontsize=14, fontweight='bold')\n", + "plt.grid(alpha=0.3)\n", + "plt.xlim([-20, 30]) \n", + "plt.ylim([0, 1])\n", + "plt.tick_params(axis='both', labelsize=11)\n", + "plt.tight_layout()\n", + "plt.savefig('images/SNR_Accuracy.png', dpi=300, bbox_inches='tight')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "39c37fc0", + "metadata": {}, + "outputs": [], + "source": [ + "def plot_confusion_matrix(cm, title='Confusion matrix >= 0dB SNR', cmap=plt.cm.Blues, labels=[]):\n", + " plt.figure(figsize = (15,10))\n", + " plt.imshow(cm, interpolation='nearest', cmap=cmap)\n", + " plt.title(title, fontsize=16, fontweight='bold', pad=20)\n", + " plt.colorbar()\n", + " label_len = np.shape(labels)[0]\n", + " tick_marks = np.arange(label_len)\n", + " plt.xticks(tick_marks, labels, rotation=45, fontsize=11)\n", + " plt.yticks(tick_marks, labels, fontsize=11)\n", + " plt.tight_layout() \n", + " plt.ylabel('True label', fontsize=14, fontweight='bold')\n", + " plt.xlabel('Predicted label', fontsize=14, fontweight='bold')\n", + " plt.savefig('images/confusion_matrix.png', dpi=300, bbox_inches='tight')" + ] + }, + { + "cell_type": "markdown", + "id": "7718e4f4", + "metadata": {}, + "source": [ + "### Plot confusion matrix for SNR>=0" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "38a45e5d", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m308/308\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m53s\u001b[0m 170ms/step\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "X_test_SNR = X_test[(Z_test>=0)[:,0],:,:]\n", + "Y_test_SNR = Y_test[(Z_test>=0)[:,0],:]\n", + "\n", + "test_Y_hat = model.predict(X_test_SNR, batch_size=1024)\n", + "conf = np.zeros([24,24])\n", + "confnorm = np.zeros([24,24])\n", + "for i in range(0,X_test_SNR.shape[0]):\n", + " j = list(Y_test_SNR[i,:]).index(1)\n", + " k = int(np.argmax(test_Y_hat[i,:]))\n", + " conf[j,k] = conf[j,k] + 1\n", + "for i in range(0,24):\n", + " confnorm[i,:] = conf[i,:] / np.sum(conf[i,:])\n", + "\n", + "plot_confusion_matrix(confnorm, labels=modulation_classes)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "444053f4", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "conv1 weights shape: (7, 2, 64) \t\t# bias: 64 \t# params: 960\n", + "conv2 weights shape: (7, 64, 64) \t\t# bias: 64 \t# params: 28736\n", + "conv3 weights shape: (7, 64, 64) \t\t# bias: 64 \t# params: 28736\n", + "conv4 weights shape: (7, 64, 64) \t\t# bias: 64 \t# params: 28736\n", + "conv5 weights shape: (7, 64, 64) \t\t# bias: 64 \t# params: 28736\n", + "conv6 weights shape: (7, 64, 64) \t\t# bias: 64 \t# params: 28736\n", + "conv7 weights shape: (7, 64, 64) \t\t# bias: 64 \t# params: 28736\n", + "dense1 weights shape: (512, 128) \t\t# bias: 128 \t# params: 65664\n", + "dense2 weights shape: (128, 128) \t\t# bias: 128 \t# params: 16512\n", + "dense3 weights shape: (128, 24) \t\t# bias: 24 \t# params: 3096\n" + ] + } + ], + "source": [ + "# Get the model weights from each layer:\n", + "w1 = model.get_layer(index=1).get_weights()\n", + "w2 = model.get_layer(index=3).get_weights()\n", + "w3 = model.get_layer(index=5).get_weights()\n", + "w4 = model.get_layer(index=7).get_weights()\n", + "w5 = model.get_layer(index=9).get_weights()\n", + "w6 = model.get_layer(index=11).get_weights()\n", + "w7 = model.get_layer(index=13).get_weights()\n", + "w8 = model.get_layer(index=16).get_weights()\n", + "w9 = model.get_layer(index=17).get_weights()\n", + "w10 = model.get_layer(index=18).get_weights()\n", + "\n", + "# Dump dimensions of weights and bias:\n", + "print(\"conv1 weights shape: \",w1[0].shape, \"\\t\\t# bias: \",len(w1[1]), \"\\t# params: \",np.prod(w1[0].shape)+len(w1[1]))\n", + "print(\"conv2 weights shape: \",w2[0].shape, \"\\t\\t# bias: \",len(w2[1]), \"\\t# params: \",np.prod(w2[0].shape)+len(w2[1]))\n", + "print(\"conv3 weights shape: \",w3[0].shape, \"\\t\\t# bias: \",len(w3[1]), \"\\t# params: \",np.prod(w3[0].shape)+len(w3[1]))\n", + "print(\"conv4 weights shape: \",w4[0].shape, \"\\t\\t# bias: \",len(w4[1]), \"\\t# params: \",np.prod(w4[0].shape)+len(w4[1]))\n", + "print(\"conv5 weights shape: \",w5[0].shape, \"\\t\\t# bias: \",len(w5[1]), \"\\t# params: \",np.prod(w5[0].shape)+len(w5[1]))\n", + "print(\"conv6 weights shape: \",w6[0].shape, \"\\t\\t# bias: \",len(w6[1]), \"\\t# params: \",np.prod(w6[0].shape)+len(w6[1]))\n", + "print(\"conv7 weights shape: \",w7[0].shape, \"\\t\\t# bias: \",len(w7[1]), \"\\t# params: \",np.prod(w7[0].shape)+len(w7[1]))\n", + "print(\"dense1 weights shape: \",w8[0].shape, \"\\t\\t# bias: \",len(w8[1]), \"\\t# params: \",np.prod(w8[0].shape)+len(w8[1]))\n", + "print(\"dense2 weights shape: \",w9[0].shape, \"\\t\\t# bias: \",len(w9[1]), \"\\t# params: \",np.prod(w9[0].shape)+len(w9[1]))\n", + "print(\"dense3 weights shape: \",w10[0].shape, \"\\t\\t# bias: \",len(w10[1]), \"\\t# params: \",np.prod(w10[0].shape)+len(w10[1]))\n", + "\n", + "np.savetxt('aie/conv1d_w1/w1_weights_trained.txt',np.reshape(w1[0].astype(\"bfloat16\"),(-1,1)),fmt=\"%.12f\")\n", + "np.savetxt('aie/conv1d_w1/w1_bias_trained.txt',np.reshape(w1[1].astype(\"bfloat16\"),(-1,1)),fmt=\"%.12f\")\n", + "np.savetxt('aie/conv1d_template/w3_weights_trained.txt',np.reshape(w2[0].astype(\"bfloat16\"),(-1,1)),fmt=\"%.12f\")\n", + "np.savetxt('aie/conv1d_template/w3_bias_trained.txt',np.reshape(w2[1].astype(\"bfloat16\"),(-1,1)),fmt=\"%.12f\")\n", + "np.savetxt('aie/conv1d_template/w5_weights_trained.txt',np.reshape(w3[0].astype(\"bfloat16\"),(-1,1)),fmt=\"%.12f\")\n", + "np.savetxt('aie/conv1d_template/w5_bias_trained.txt',np.reshape(w3[1].astype(\"bfloat16\"),(-1,1)),fmt=\"%.12f\")\n", + "np.savetxt('aie/conv1d_template/w7_weights_trained.txt',np.reshape(w4[0].astype(\"bfloat16\"),(-1,1)),fmt=\"%.12f\")\n", + "np.savetxt('aie/conv1d_template/w7_bias_trained.txt',np.reshape(w4[1].astype(\"bfloat16\"),(-1,1)),fmt=\"%.12f\")\n", + "np.savetxt('aie/conv1d_template/w9_weights_trained.txt',np.reshape(w5[0].astype(\"bfloat16\"),(-1,1)),fmt=\"%.12f\")\n", + "np.savetxt('aie/conv1d_template/w9_bias_trained.txt',np.reshape(w5[1].astype(\"bfloat16\"),(-1,1)),fmt=\"%.12f\")\n", + "np.savetxt('aie/conv1d_template/w11_weights_trained.txt',np.reshape(w6[0].astype(\"bfloat16\"),(-1,1)),fmt=\"%.12f\")\n", + "np.savetxt('aie/conv1d_template/w11_bias_trained.txt',np.reshape(w6[1].astype(\"bfloat16\"),(-1,1)),fmt=\"%.12f\")\n", + "np.savetxt('aie/conv1d_template/w13_weights_trained.txt',np.reshape(w7[0].astype(\"bfloat16\"),(-1,1)),fmt=\"%.12f\")\n", + "np.savetxt('aie/conv1d_template/w13_bias_trained.txt',np.reshape(w7[1].astype(\"bfloat16\"),(-1,1)),fmt=\"%.12f\")\n", + "np.savetxt('aie/dense_w16/w16_weights_trained.txt',np.reshape(w8[0].astype(\"bfloat16\"),(-1,1)),fmt=\"%.12f\")\n", + "np.savetxt('aie/dense_w16/w16_bias_trained.txt',np.reshape(w8[1].astype(\"bfloat16\"),(-1,1)),fmt=\"%.12f\")\n", + "np.savetxt('aie/dense_w17/w17_weights_trained.txt',np.reshape(w9[0].astype(\"bfloat16\"),(-1,1)),fmt=\"%.12f\")\n", + "np.savetxt('aie/dense_w17/w17_bias_trained.txt',np.reshape(w9[1].astype(\"bfloat16\"),(-1,1)),fmt=\"%.12f\")\n", + "np.savetxt('aie/dense_w18/w18_weights_trained.txt',np.reshape(w10[0].astype(\"bfloat16\"),(-1,1)),fmt=\"%.12f\")\n", + "np.savetxt('aie/dense_w18/w18_bias_trained.txt',np.reshape(w10[1].astype(\"bfloat16\"),(-1,1)),fmt=\"%.12f\")\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "my-venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.6" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/vitis/Makefile b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/vitis/Makefile new file mode 100755 index 0000000000..f9acf25218 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/vitis/Makefile @@ -0,0 +1,100 @@ +# +# Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +QEMU_PREBUILT := amd-cortexa78-mali-common_vek385_qemu_prebuilt +export QEMU_COMBINED := base_camp_images +export WIC_PARTITION := edf-linux-disk-image-amd-cortexa78-mali-common.rootfs.wic.ufs:2 + +export DUT = dut +export XCLBIN = ${DUT}.xclbin + +TARGET ?= hw +export IP_DIR := $(abspath ../aie/radioml_top) +GRAPH_O := ${IP_DIR}/libadf.a +export XSA := my.xsa +export STIMULUS_DIR := ${IP_DIR}/data + +export APP_EXE := ../ps_apps/host.exe + +export SD_CARD := $(abspath ../package) +export BUILD_DIR := build_${TARGET} + +export EMBD_EXC := embedded_exec.sh +SYSTEM_CFG := system.cfg + +.PHONY: help all clean + +help:: + @echo "Makefile Usage:" + @echo " make all" + @echo " Command to generate the sd_card in this design, including platform/petalinux/ip/ps_apps" + @echo "" + @echo " make clean" + @echo " Command to remove all the generated files." + +ifeq (${TARGET},hw) + all: ${SD_CARD} +else + all: ${SD_CARD} qemu_combined copy_wic +endif + +${BUILD_DIR}: + mkdir ${BUILD_DIR} + +${BUILD_DIR}/${XSA}: ${GRAPH_O} ${SYSTEM_CFG} ${BUILD_DIR} + cd ${BUILD_DIR} && \ + v++ --link --debug --save-temps \ + --target ${TARGET} \ + --platform ${PLATFORM} \ + $(addprefix --config ../, ${SYSTEM_CFG}) \ + ${GRAPH_O} \ + --output ${XSA} \ + 2>&1 | tee vpp_link.log + +${EMBD_EXC}: + @echo "#!/bin/bash" >> ${EMBD_EXC} + @echo "#" >> ${EMBD_EXC} + @echo "# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved." >> ${EMBD_EXC} + @echo "# SPDX-License-Identifier: MIT" >> ${EMBD_EXC} + @echo "#" >> ${EMBD_EXC} + @echo "" >> ${EMBD_EXC} +ifeq ("$(TARGET)","hw_emu") + @echo "export XCL_EMULATION_MODE=hw_emu" >> ${EMBD_EXC} +endif + @echo 'echo "INFO: Load the pdi and dtbo using fpgautil"' >> ${EMBD_EXC} + @echo "fpgautil -b ${DUT}.pdi -o ${DUT}.dtbo" >> ${EMBD_EXC} + @echo "" >> ${EMBD_EXC} + @echo "./host.exe ${DUT}.xclbin" >> ${EMBD_EXC} + @echo 'return_code=$$?' >> ${EMBD_EXC} + @echo 'if [ $$return_code -ne 0 ]; then' >> ${EMBD_EXC} + @echo ' echo "ERROR: Embedded host run failed, RC=$$return_code"' >> ${EMBD_EXC} + @echo 'fi' >> ${EMBD_EXC} + @echo echo '"INFO: Embedded host run completed."' >> ${EMBD_EXC} + chmod 755 ${EMBD_EXC} + +${SD_CARD}: ${BUILD_DIR}/${XSA} ${APP_EXE} ${EMBD_EXC} + cd ${BUILD_DIR} && v++ -p -s -t ${TARGET} -f ${XSA} --package.out_dir ${SD_CARD} --package.defer_aie_run ${GRAPH_O} -o ${XCLBIN} 2>&1 | tee vpp_pack.log +ifeq (${TARGET},hw) + cp -rf ${BUILD_DIR}/${DUT}.xclbin ${SD_CARD}/. + cp -rf ${STIMULUS_DIR}/* ${SD_CARD}/. + cp -rf ${EMBD_EXC} ${SD_CARD}/. + cp -rf ${APP_EXE} ${SD_CARD}/. +endif + +qemu_combined: + rm -rf ${QEMU_COMBINED}; \ + mkdir -p ${QEMU_COMBINED}; \ + cp -prf ${YOCTO_ARTIFACTS}/${QEMU_PREBUILT}/* ${QEMU_COMBINED}/.; \ + +copy_wic: + ./run_copy_wic.sh + +run_emu: + cd ../package && ./launch_hw_emu.sh -qemu-config ../vitis/${QEMU_COMBINED}/combined.qemuboot.conf -login "amd-edf" -password "amd-edf" -run-app " mount /dev/sda2 /media; cd /media; ./${EMBD_EXC}" + +clean: + /bin/rm -rf ${SD_CARD} ${BUILD_DIR} *.o ${QEMU_COMBINED} .Xil ${EMBD_EXC} .ipcache + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/vitis/run_copy_wic.sh b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/vitis/run_copy_wic.sh new file mode 100755 index 0000000000..6494880a13 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/vitis/run_copy_wic.sh @@ -0,0 +1,45 @@ +#!/bin/bash +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani +unset LD_LIBRARY_PATH +source ${YOCTO_ARTIFACTS}/amd-cortexa78-mali-common_meta-edf-app-sdk/sdk/environment-setup-cortexa72-cortexa53-amd-linux +echo "sourced" +wic cp --sector-size=4096 ${EMBD_EXC} ./${QEMU_COMBINED}/${WIC_PARTITION} +echo "copied embedded_exec.sh" +wic cp --sector-size=4096 ${APP_EXE} ./${QEMU_COMBINED}/${WIC_PARTITION} +echo "copied host.exe" +wic cp --sector-size=4096 ${BUILD_DIR}/${XCLBIN} ./${QEMU_COMBINED}/${WIC_PARTITION} +echo "copied xclbin" +wic cp --sector-size=4096 ${SD_CARD}/${DUT}.dtbo ./${QEMU_COMBINED}/${WIC_PARTITION} +echo "copied dtbo" +wic cp --sector-size=4096 ${SD_CARD}/${DUT}.pdi ./${QEMU_COMBINED}/${WIC_PARTITION} +echo "copied pdi" +wic cp --sector-size=4096 ${STIMULUS_DIR}/data_iq.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/data_o.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/w1_weights-rtp.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/w1_biases-rtp.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/w3_weights-rtp.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/w3_biases-rtp.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/w5_weights-rtp.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/w5_biases-rtp.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/w7_weights-rtp.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/w7_biases-rtp.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/w9_weights-rtp.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/w9_biases-rtp.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/w11_weights-rtp.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/w11_biases-rtp.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/w13_weights-rtp.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/w13_biases-rtp.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/w16_0_weights-rtp.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/w16_1_weights-rtp.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/w16_biases-rtp.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/w17_weights-rtp.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/w17_biases-rtp.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/w18_weights-rtp.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/w18_biases-rtp.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +wic cp --sector-size=4096 ${STIMULUS_DIR}/modulation_classes.txt ./${QEMU_COMBINED}/${WIC_PARTITION} +echo "copied Stimulus IO files" + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/vitis/system.cfg b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/vitis/system.cfg new file mode 100755 index 0000000000..a7c8410879 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/vitis/system.cfg @@ -0,0 +1,33 @@ +# +# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Faisal El-Shabani + +# ------------------------------------------------------------ +# Clocks +# ------------------------------------------------------------ + +[connectivity] + +# ------------------------------------------------------------ +# HLS PL Kernels: +# ------------------------------------------------------------ + +# ------------------------------------------------------------ +# AXI Stream Connections (PL to AIE) +# ------------------------------------------------------------ + +# ------------------------------------------------------------ +# Vivado PAR +# ------------------------------------------------------------ + +[vivado] +#impl.strategies=Performance_Explore,Performance_ExplorePostRoutePhysOpt,Performance_WLBlockPlacement,Performance_WLBlockPlacementFanoutOpt,Performance_EarlyBlockPlacement,Performance_NetDelay_high,Performance_NetDelay_low,Performance_Retiming,Performance_ExtraTimingOpt,Performance_RefinePlacement,Congestion_SpreadLogic_high,Congestion_SpreadLogic_medium,Congestion_SpreadLogic_low,Area_Explore,Area_ExploreSequential,Area_ExploreWithRemap +#impl.jobs=8 +prop=run.impl_1.steps.phys_opt_design.is_enabled=1 +prop=run.impl_1.steps.post_route_phys_opt_design.is_enabled=1 + +# This enabled unified AIE flow to show AIE resource in Vivado: +param=project.enableUnifiedAIEFlow=true + diff --git a/AI_Engine_Development/AIE-MLv2/Design_Tutorials/README.md b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/README.md new file mode 100644 index 0000000000..4473363563 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Design_Tutorials/README.md @@ -0,0 +1,34 @@ + + + + +
+ + + AMD logo + +

AMD Vitis™ AI Engine Tutorials

+ See Vitis™ Development Environment on amd.com +
+ See Vitis™ AI Development Environment on amd.com +
+ +# Design Tutorials + +The AI Engine Development Design Tutorials showcase the two major phases of AI Engine-MLv2 application development: architecting the application and developing the kernels. Both phases are demonstrated in these tutorials. + + + + + + + + +
Tutorial + Description +
Radio-ML on AIE-ML v2This tutorial implements a Convolutional Neural Network classifier on AMD Versal™ AI Edge Series Gen 2 for radio signal classification. +
+ +

Copyright © 2020–2025 Advanced Micro Devices, Inc.

+ +

Terms and Conditions

diff --git a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/01-using_code_analyzer.rst b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/01-aie-mlv2_a_to_z-sourcelink.rst similarity index 57% rename from Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/01-using_code_analyzer.rst rename to AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/01-aie-mlv2_a_to_z-sourcelink.rst index 22c44fdc3f..34b35a6e54 100644 --- a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/01-using_code_analyzer.rst +++ b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/01-aie-mlv2_a_to_z-sourcelink.rst @@ -1,5 +1,5 @@ ####################################################### -Version: Vitis 2024.1 +Version: Vitis 2025.2 ####################################################### -To view the source files for this tutorial, click `here `_. +To view the source files for this tutorial, click `here `_. diff --git a/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/01-custom_base_platform_creation.md b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/01-custom_base_platform_creation.md new file mode 100644 index 0000000000..8c50417722 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/01-custom_base_platform_creation.md @@ -0,0 +1,116 @@ + + + + +
+ + + AMD logo + +

AMD Vitis™ AI Engine Tutorials

+ See Vitis™ Development Environment on amd.com +
+ See Vitis™ AI Development Environment on amd.com +
+ +# Custom Platform Creation + +## Platforms + +A platform is the starting point of your design and will be used to build Vitis software platform applications. + +>**NOTE**: AMD recommends using the VEK385 base platform provided on the Versal AI Edge Series Gen 2 VEK385 HeadStart Board Early Access Secure Site as a starting point for designs. This page is intended for users who would like to understand how the base platform is generated. Other users can start directly from [AI Engine Development](./02-aie_application_creation.md). + +In this first section of the tutorial, an example of how to create a new platform is shown. This starts with building the hardware system using the AI Engine in the AMD Vivado™ Design Suite. + +This is in most ways a traditional AMD Vivado™ design. You are building the platform, that is, the part of the design that you do not want the Vitis tools to configure or modify. This can include completely unrelated logic, any hierarchy you want to have in the design, but there are some rules that you must follow: + +- Your design must contain an IP integrator block diagram containing the CIPS, NOC, and other infrastructure IP. +- Your design must have at least one clock that you will expose to Vitis for use with any kernels that it adds. +This clock must have an associated `proc_sys_reset` block. + +This tutorial targets the VEK385 board + +### Step 1: Build the AMD Versal™ Extensible Embedded Platform Example Design in Vivado + +1. Launch Vivado IDE, and select ***Open Example Project*** from the Welcome window. You can also do it by clicking ***File*** from the menu, and select ***Project*** and then ***Open Example***. + +2. Click ***Next*** to skip the first page of the wizard. In the template selection page, select the ***Versal Embedded Common Platform*** template. Click ***Next***. + +3. Name this project as ***custom_pfm_vek385*** and click ***Next***. + +4. In the part selection page, select the **VEK385 Evaluation Platform**. Click ***Next***. + +5. In the design preset page, change the **Design Type** to **Extensible** and keep the default settings for the clocks: + + ![missing image](images/252_design_preset_config_VEK385.jpg) + + +6. Click **Next** and ***Finish*** to complete the example design creation phase, and this will open up the Vivado project with the template design you just created. You can open the block design to view the details of the platform design. By using the pre-built template, you can easily get a validated hardware design of the platform to move on to the next step. In your real design development procedure, you can use this as a baseline design and make further modifications on top of it. + + ![missing image](images/251_block_design_complete.jpg) + + +7. Click ***Generate Block Design*** from the Flow Navigator panel on the left, click ***Generate***, and wait for the process to complete. + +>**NOTE**: A critical warning is displayed by Vivado when generating the Block Design. This is due to the fact that the Interrupt Controller IP has an unconnected input. This can be ignored as this input will be connected automatically by Vitis later in the flow. + +8. Click ***File*** from the menu, and select ***Export*** > ***Export Platform***. + + a. On the second page, select ***Hardware and hardware emulation*** as the platform type. + + ![missing image](images/221_export_xsa_pg1.png) + + b. On the third page select ***Pre-synthesis***. + + ![missing image](images/export_xsa_pg2.png) + + c. On the fourth page, add the name of the platform. + + ![missing image](images/251_platform_properties_vek385.jpg) + + d. On the fourth page, set the name of the XSA, and click ***Finish***. + + ![missing image](images/251_platform_properties_vek385_2.jpg) + +9. Close the Vivado project after platform export process finishes. + +> Note: The vivado platform creation can be automated by running "make vivado_platform" + +### Step 2: Build the Platform in the Vitis Software Platform + +1. Open the Vitis Unified IDE, and select a workspace. + +2. On the Welcome Page, select ***Create Platform Component***, or select ***File → New Component → Platform***. + +3. Set the platform component name to ***base_pfm_vek385*** and click ***Next***. + + ![missing image](images/251_create_platform_pg1_vek385.jpg) + +4. Select ***Hardware Design*** and use the XSA generated during the previous step and click ***Next*** + + ![missing image](images/251_create_platform_pg2_vek385.jpg) + +5. Set the Operating System to ***aie_runtime*** and the Processor to ***ai_engine*** and click ***Next***. Then click ***Finish*** to create the platform component. + + ![missing image](images/232_create_platform_pg3.jpg) + +6. Then build the platform by clicking on ***Build*** In the flow navigator with the base_pfm_vek385 component selected. + + ![missing image](images/251_build_platform_vek385.jpg) + + >**NOTE**: If you modify the XSA file later, go to vitis-comp.json located in the Settings folder of the platform component and click ***switch xsa*** + +7. The generated platform can be found in `workspace/base_pfm_vek385/export`. + +In this step, you created the platform starting with building the hardware platform in the Vivado Design Suite. Then, you built the platform in the Vitis software platform, based on the exported XSA file. + +> Note: The vivado platform creation can be automated by running "make vitis_platform" + +In the next step, you will build an AI Engine application using this platform. + +

Return to Start of Tutorial — Go to AI Engine Development

+ +

Copyright © 2025 Advanced Micro Devices, Inc.

+ +

Terms and Conditions

diff --git a/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/02-aie_application_creation.md b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/02-aie_application_creation.md new file mode 100644 index 0000000000..d2b9c3d93b --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/02-aie_application_creation.md @@ -0,0 +1,109 @@ + + + + +
+ + + AMD logo + +

AMD Vitis™ AI Engine Tutorials

+ See Vitis™ Development Environment on amd.com +
+ See Vitis™ AI Development Environment on amd.com +
+ +# Introduction - AI Engine Development + +In this section of the tutorial, you will learn how to create a new AI Engine application project from a template, and run through the ***Emulation-AIE*** process. + +## Step 1: Create a new AI Engine Application Project + +1. Open the Vitis Unified IDE if you have closed it. You can use the same workspace as the previous stage or create a new one. + +2. Click on ***View > Examples*** to view the application examples installed with Vitis + +3. Under **AI Engine Examples > Installed AI Engine Examples** select the ***Simple*** example + + ![missing image](images/232_aie_simple_ex.jpg) + +4. Click ***Create AI Engine Component from Template*** + + ![missing image](images/232_aie_simple_ex2.jpg) + + >**NOTE:** In the description of the template, it says that the template works only for AI Engine Emulation and software (x86) simulation. In the following steps, you will learn how to make it work on hardware. + +5. Set the component name as ***simple_aie_application*** and click ***Next*** + + ![missing image](images/232_aie_app_pg1.jpg) + +6. On the platform page, select the platform you want to use: + + * If you have created the platform following step 1, select the **base_pfm_vek385** platform you just created. If you do not use the same workspace from last step, click **Add**, and select the folder `base_pfm_vek385/export` to add the platform into this workspace. + * If you have skipped step 1, select the VEK385 base platform (xilinx_vek385_base_202510_1) which is part of the Vitis installation. + + >**NOTE 1:** There is a current limitation in the Vitis IDE when using the base platform (vek385_base). Recommendation is to follow step 1 to create a custom platform from vivado + + ![missing image](images/251_aie_app_pg2_vek385.jpg) + +7. Click ***Finish***. + +8. The template imports two folders: + + * `src` contains the sources for the kernels and the graph. + * `data` contains the data for the simulation input (`input.txt`) and the golden reference for the output (`golden.txt`). + + ![missing image](images/232_aie_app_folder.jpg) + +9. Open the file `project.h` to see the graph. You can see that the graph (simpleGraph) has one input and one output and implements two kernels with the same function. The output of the first kernel feeds the second one. + + ``` + first = kernel::create(simple); + second = kernel::create(simple); + adf::connect(in.out[0], first.in[0]); + connect(first.out[0], second.in[0]); + connect(second.out[0], out.in[0]); + ``` + + This is the representation of the graph. + + ![missing image](images/aie_app_graph.png) + +10. Open the file `kernels/kernels.cc` to see what function will be implemented in the kernels. +You can see that this is a simple operation which is doing the sum of the real and imaginary parts of the input to create the real part of the output and the subtraction the real and imaginary part of the input to create the imaginary part of the output. + + ``` + void simple(adf::input_buffer & in, adf::output_buffer & out) { + cint16 c1, c2; + cint16* inItr = in.data(); + cint16* outItr = out.data(); + for (unsigned i=0; i Note: The ai engine application creation can be automated by running "make aie_app" + +

Go to System Integration

+ +

Copyright © 2025 Advanced Micro Devices, Inc.

+ +

Terms and Conditions

diff --git a/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/03-pl_application_creation.md b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/03-pl_application_creation.md new file mode 100644 index 0000000000..2a9c2da77b --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/03-pl_application_creation.md @@ -0,0 +1,122 @@ + + + + +
+ + + AMD logo + +

AMD Vitis™ AI Engine Tutorials

+ See Vitis™ Development Environment on amd.com +
+ See Vitis™ AI Development Environment on amd.com +
+ +# Introduction: System Integration + +In this section of the tutorial, you will learn how to add programmable logic (PL) kernels in HLS into the system project, and build the whole system. + +## Step 1: Add PL Kernels + +In this example, HLS kernels are used which bridge between memory and the AXI4-Stream interface to input and output data from memory. + +* The `mm2s` kernel reads data from memory and inputs it to the AI Engine array. +* The `s2mm` kernel receives output data from the AI Engine array and writes it to memory. + +1. In the Vitis Unified IDE click ***File > New Component > HLS*** + +2. Name the first component **mm2s** and click ***Next***. + +3. In the **Configuration File** page, keep the default settings (**Empty File**) and click ***Next*** + +4. In the **Add Source Files** page, add the file **mm2s.cpp** from the src folder + + ![missing image](images/232_mm2s_comp.jpg) + +5. In the same page, set the mm2s function as the top function (click ***Browse*** and select ***mm2s***) + + ![missing image](images/232_mm2s_comp2.jpg) + + ![missing image](images/232_mm2s_comp3.jpg) + +6. In the **Select Platform** Page: +* If you have created the platform following step 1, select the **base_pfm_vek385** platform you just created. +* If you have skipped step 1, select the VEK385 base platform (xilinx_vek385_base_202510_1) . + + Click ***Next*** + +7. In the **Edit Settings** page select ***Vitis Kernel Flow Target*** under **flow_target** and ***Generate a Vitis XO*** under **package.output_format** and click ***Next*** + + ![missing image](images/232_mm2s_comp4.jpg) + +8. Click ***Finish*** + +9. In the flow navigator, click on ***Run*** under **C SYNTHESIS**. + +10. In the flow navigator, click on ***Run*** under **PACKAGE**. + +11. Repeat steps 1 to 10 to create another HLS component called **s2mm** with the **s2mm.cpp** source file + +## Step 3: Configure the Hardware Linking Project + +Now that you have imported the kernels, you need to tell the Vitis linker how to connect everything together. + +1. Create a new System Project component by clicking ***File > New Component > System Project*** + +2. Call this system component **simple_aie_application_system_project** and click ***Next*** + +3. In the **Select Platform** Page: +* If you have created the platform following step 1, select the **base_pfm_vek385** platform you just created. +* If you have skipped step 1, select the select the VEK385 base platform (vek385_base) . + +4. Skip the **Embedded Component Paths** page (click ***Next***). This page is used for system running Linux. Our system will be Baremetal. + +5. Click ***Finish*** + +6. Open the settings file called **vitis-sys.json** under **simple_aie_application_system_project > Settings** and click on ***Add Existing Components*** in the **Components** section at the bottom of the file. Click ***HLS*** and select the ***mm2s*** and ***s2mm*** components. + + ![missing image](images/251_sys_proj_vek385.jpg) + +7. Click again on ***Add Existing Components*** in the **Components** section at the bottom of the file. Click ***AI Engine*** and select the **simple_aie_application*** components. + +8. Now you need to tell the Vitis compiler about the connectivity of the system. This step is done using a configuration file. Still in the settings file **vitis-sys.json**, under **Hardware Link Settings** expend **binary_container_1** and click on ***hw_link/binary_container_1-link.cfg*** + + ![missing image](images/251_cfg_file_vek385.jpg) + +In **binary_container_1-link.cfg** change the view to **Source editor** and add the following lines under **[connectivity]** + + ``` + stream_connect=mm2s_1.s:ai_engine_0.mygraph_in + stream_connect=ai_engine_0.mygraph_out:s2mm_1.s + ``` +![missing image](images/232_cfg_file1.jpg) + +Note that as per the [Vitis Unified Software Platform Documentation: Application Acceleration Development (UG1393)](https://docs.amd.com/r/en-US/ug1393-vitis-application-acceleration/connectivity-Options), the naming convention for the compute units (or kernel instances) are `_#`, where `#` indicates the CU instance. Thus, the CU names built corresponding to the kernels `mm2s` and `s2mm` in your project are respectively `mm2s_1` and `s2mm_1`. The `stream_connect` option is defined as `.:.`. For example, to connect the AXI4-Stream interface of the `mm2s_1` (compute unit name) called `s` (kernel interface name) to the `mygraph_in` (interface name) input of the graph in the `ai_engine_0` (compute unit name) IP you need the following option: `stream_connect=mm2s_1.s:ai_engine_0.mygraph_in`. + +9. In the **binary_container_1-link.cfg** page, change back the view to **Settings Forms** and enable **Export hardware (XSA)**. + + ![missing image](images/232_cfg_file2.jpg) + +## Step 4. Build the System + +1. In the flow navigator, make sure **simple_aie_application_system_project** is selected and click on ***Build Binary Container*** under **HARDWARE > LINK - binary_container_1**. Click ***OK*** when asked to build the HLS components (mm2s and s2mm) +The compilation process takes some time to finish. The underlying AI Engine application project, hardware kernel project, and hardware linking project are compiled one after another. The system should build successfully with no error. + + ![missing image](images/232_system_build.jpg) + +2. You can open the generated the AMD Vivado™ project in `/simple_aie_application_system_project/build/hw/hw_link/binary_container_1/binary_container_1/vivado/vpl/prj/prj.xpr` to take a look at the compilation result. You can see that the Vitis compiler added the two HLS IP (`mm2s` and `s2mm`) and connected them to the memory (NOC) and AI Engine IP. + + ![missing image](images/232_vivado_prj.jpg) + + ![missing image](images/232_vivado_prj2.jpg) + +> Note: Creation of thr PL can be automated by running "make pl_app" + +In the next step, you will create a processing system (PS) bare-metal application, and run the system with it. + +

Go to PS Application and Run

+ +

Copyright © 2025 Advanced Micro Devices, Inc.

+ +

Terms and Conditions

diff --git a/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/04-ps_application_creation_run_all.md b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/04-ps_application_creation_run_all.md new file mode 100644 index 0000000000..4d632ac78f --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/04-ps_application_creation_run_all.md @@ -0,0 +1,141 @@ + + + + +
+ + + AMD logo + +

AMD Vitis™ AI Engine Tutorials

+ See Vitis™ Development Environment on amd.com +
+ See Vitis™ AI Development Environment on amd.com +
+ +# Introduction: PS Application Creation and Run + +In this section of the tutorial, you will learn how to build a PS bare-metal application using the XSA created in the previous step, and then build, as well as run the complete system. + +## Step 1: Create a New Platform in the Bare-metal Domain + +1. In the Vitis Unified IDE with the same workspace directory as the previous step. Click ***File → New Component → Platform***. + +2. Set the Platform Project Name to **AIE_A-to-Z_pfm_vek385**, and click **Next**. + +3. Use the XSA generated in the previous step that you can find in `simple_aie_application_system_project/build/hw/hw_link/binary_container_1.xsa` + + ![missing image](images/232_ps_pfm.jpg) + +4. Set **standalone** as the **Operating system**, **psv_cortexa78_0** as the **Processor** and click **Finish**. + + ![missing image](images/251_ps_os_vek385.jpg) + +5. Open the platform setting file (vitis_comp.json) and open the Board Support Package for the cortexa78_0 and enable the **aiebaremetal** library + + ![missing image](images/252_vek385_bsp.jpg) + +6. Build the platform. + +## Step 2. Build the Baremetal AI Engine Control Application + +1. Create a new application by clicking ***File → New Component → Application***. + +2. Set the name for the application to `A-to-Z_app` and click ***Next***. + +3. Select **AIE_A-to-Z_pfm_vek385** as the platform and click ***Next***. + +4. Select the A78_0 processor domain (`standalone_psv_cortexa78_0`), and click ***Next*** and then ***Finish***. + +5. Right-click the `src` folder under the **A-to-Z_app** project, and click ***Import → Files***. + +6. Import the `baremetal_metadata_compile.cpp` file from the output of the AI Engine application project (`simple_application/build/hw/Work/baremetal_metadata_compile.cpp`). + +7. Import `main.cpp` from the `src` folder from the git repository. + + Go through the `main.cpp` file. You can see that the code is initializing the input data and the memory space for the output data. One thing to note is the use of the `.run()` API to control the AI Engine. + + ``` + printf("Running Graph for 4 iterations\n"); + gr.run(4); + ``` + + There are two options to enable an AI Engine graph from a system: + + * Enable the graph in the PDI. This means that the graph will be started during BOOT and will run forever. + * Enable the AI Engine graph from the PS program using the `.init()` and `.run()` APIs. This is what you are using in this case. + +8. Modify the Linker Script to increase the heap size for AIE library. + + * In the Project Explorer, expand the A-to-z_app component. + + * In the src directory, double-click `lscript.ld` to open the linker script for this project. + + * In the linker script modify the Heap size to `0x100000` (1MB). + + ![missing image](images/232_heapsize.jpg) + +12. Build the A72 PS component (`A-to-Z_app`). + +> Note: The creation of the Vitis fixed platform and the ps application can be automated running "make ps_app" + +## Step 3: Package the Full System + +1. Open the settings file **vitis-sys.json** for the **simple_aie_application_system_project** and click on the **package.cfg** config file under **Package Settings** + + ![missing image](images/252_package_option_vek385_1.jpg) + +2. In the **General** Section, in the Baremetal Elf setting add the following to tell the packager to add the application executable and run it on the A72 processor + + `../../../../A-to-Z_app/build/A-to-Z_app.elf,a78-0` + + ![missing image](images/252_package_option_vek385_2.jpg) + +3. In the **AI Engine section** select the option **Do not enable cores** + + ![missing image](images/232_package_option_3.jpg) + + >**NOTE:** The option will add the line --package.defer_aie_run in the package + configuration file. This is required when running the AI Engine graph from th + e PS (see the [AI Engine Tools and Flows User Guide (UG1076)](https://docs.amd.com/r/en-US/ug1076-ai-engine-environment/Integrating-the-Application-Using-the-Vitis-Tools-Flow)). + If the user is looking for a free running graph, this option should be disabled + +4. In the **AI Engine section** deselect the option **Enable debug** + + ![missing image](images/232_package_option_4.jpg) + + >**NOTE:** This option is used when running the debugger. In our case, we will just run the system without using the debugger + +5. Build the **simple_aie_application_system_project** project for Hardware (Click ***Build All*** under **HARDWARE** in the Flow navigator). + +## Step 4: Run or Debug the System in Hardware using JTAG +We will now test our system first by booting it through JTAG. As discussed previously, the segmented flow will use two PDI files; boot and PLD. The AIE binaries are applied to the PLD PDI. We have to tell the IDE to use both of them + +1. In the flow navigator, select the A-to-Z_app component and click on the configuration icon which appear on the right of the Run option when you hover it with you mouse + ![missing image](images/251_jtag_config.jpg) + +2. Click on New Launch Configuration + +3. Set up you target connection (local or remote) + +4. Select **Load PL PDI** and set the path to **${workspaceFolder}/simple_aie_application_system_project/build/hw/package/package/binary_container_1.pdi** + +5. Power up the board + +The output will be send to UART0. + +6. If you are using a Rev B. board, open a serial terminal to get the UART0. If you are using a RevA, the UART0 is not available through the serial interfaces but is routed to the System Controller for remote UART functionality. To access it, log in to the system controller and set an IP address for the PS ethernet inteface and an IP address of the same network group to your PC (for example 192.168.1.2 and 192.168.1.1). Then open a Telnet Terminal (for example in tera term) and connect to 192.168.1.2:4001 to get the UART0 terminal + + ![missing image](images/Telnet_tera_term.jpg) + +7. Click on Run. You should see the application running successfully + + ![missing image](images/UART_out.jpg) + +## Summary + +In this tutorial, you have performed an end-to-end flow to create a platform based on the VEK385 board, added an AI Engine kernel and PL kernels into the system, and built a PS bare-metal application to control the system. Then you have run the system is hardware emulation and hardware. + +

Copyright © 2025 Advanced Micro Devices, Inc.

+ +

Terms and Conditions

diff --git a/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/Makefile b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/Makefile new file mode 100644 index 0000000000..f96bcd9035 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/Makefile @@ -0,0 +1,73 @@ +# +# Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# + +################################################################################ +# Variables needed for AMD tools version checking, PLEASE DO NOT MODIFY # +################################################################################ +REQUIRED_VERSION = 2025.2 +VIVADO_VERSION := $(shell vivado -version 2>/dev/null | grep "vivado ") +VITIS_VERSION := $(shell vitis -version 2>/dev/null | grep "Vitis " | sed 's/\*//g') + +############################################### +# Variables that may be changed to your needs # +############################################### + +# TARGET = hw or hw_emu +export TARGET := hw + +############## +# Build Flow # +############## +.PHONY: clean help all vivado vitis_platform vitis_ip vitis ps_apps linux + +help:: + $(ECHO) "Makefile Usage:" + $(ECHO) " make vivado_platform" + $(ECHO) " Builds a Vivado custom base HW platform using Pre-Synth flow" + $(ECHO) " To run full implementation platform, override using environment variable" + $(ECHO) "" + $(ECHO) " make vitis_platform" + $(ECHO) " Builds the Vitis platform" + $(ECHO) " * Depends on vivado_platform rule to be completed" + $(ECHO) "" + $(ECHO) " make aie_app" + $(ECHO) " Creates and Builds the AI Engine component" + $(ECHO) " * Depends on vivado_platform and vitis_platform rule to be completed" + $(ECHO) "" + $(ECHO) " make all" + $(ECHO) " Generate the full project + $(ECHO) "" + $(ECHO) " make clean" + $(ECHO) " Command to remove all the generated files." + +vivado_platform: + $(MAKE) platform_vivado -C vivado + +vitis_platform: + $(MAKE) pfm -C vitis + +aie_app: + $(MAKE) aie_app -C vitis + +pl_app: + $(MAKE) pl_app -C vitis + +ps_app: + $(MAKE) ps_app -C vitis + +vitis: + $(MAKE) vitis -C vitis + +run_emu: + $(MAKE) run_hw_emu -C vitis + +all: vivado_platform vitis + +run: all run_emu + + +clean: + $(MAKE) clean -C vivado + $(MAKE) clean -C vitis diff --git a/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/README.md b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/README.md new file mode 100644 index 0000000000..a5325d407f --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/README.md @@ -0,0 +1,38 @@ + + + + +
+ + + AMD logo + +

AMD Vitis™ AI Engine Tutorials

+ See Vitis™ Development Environment on amd.com +
+ See Vitis™ AI Development Environment on amd.com +
+ +# A to Z AI Engine Bare-metal Flow for VEK385 + +***Version: Vivado / Vitis 2025.2*** + +***Supported Boards: VEK385 Rev. A, VEK385 Rev.B*** + +This tutorial introduces a complete end-to-end flow for a bare-metal host application using AI Engines and PL kernels. The tutorial is based on the 2025.2 Vivado and Vitis unified software platform. + +In this tutorial, you will learn how to create an HW extensible platform for the VEK385 in Vivado using a Configurable Example Design. You will then use this platform in the Vitis Unified IDE to create a simple AIE-MLv2 application that will be connected to the HW extensible platform using HLS kernels. +You will then run this design on the VEK385 board by booting from JTAG using the Vitis Unified IDE. + +>Note: The AI Engine application shown in this tutorial is targeting DSP design. For ML application, please contact your FAE for availability for the Vitis AI tools. + +The flow is broken into four different steps shown in the following diagram. + +![missing image](images/diagram_22.1.png) + +[Start with Custom Platform Creation](./01-custom_base_platform_creation.md) + + +

Copyright © 2025 Advanced Micro Devices, Inc.

+ +

Terms and Conditions

diff --git a/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/description.json b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/description.json new file mode 100644 index 0000000000..481e9b4e0d --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/description.json @@ -0,0 +1,34 @@ +{ + "name": "AI_Engine_Development-01-aie-mlv2_a_to_z", + "description": "01-aie-mlv2_a_to_z", + "flow": "versal", + + "platform_allowlist": [ "vek385_base_reva"], + "platform_blocklist": [], + + "testinfo": { + "test_name": "AIE-MLv2_F_01-aie-mlv2_a_to_z", + "disable": false, + "jobs": [ + { + "index": 0, + "dependency": [], + "env": "", + "cmd": "", + "max_memory_MB": 32768, + "max_time_min": { + "vitis_hw_build": 470 + } + } + ], + "targets": [ + "vitis_hw_build" + ], + "category": "canary", + "custom_build_target": + { + "all": "all", + "hw":"all" + } + } +} diff --git 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All rights reserved. +SPDX-License-Identifier: MIT +*/ +/* + * main.cpp : AI Engine A-to-Z Application + * + * Created on: Jun 2, 2020 + * Author: florentw + */ + +#include +#include +#include "xil_printf.h" +#include "xil_cache.h" +#include "xil_io.h" + +#include "xparameters.h" +#include "xaiengine.h" +#include "aeg_baremetal_api.h" + +#define MM2S_BASE XPAR_XMM2S_0_BASEADDR +#define S2MM_BASE XPAR_XS2MM_0_BASEADDR + +#define MEM_OFFSET 0x10 +#define SIZE_OFFSET 0x1C +#define CTRL_OFFSET 0x0 + +#define INPUT_SIZE 128 +#define OUTPUT_SIZE 128 + +BaremetalGraph gr("mygraph"); + +int InitInputData(int32_t** in, int size) +{ + int i; + int data = 0x00010000; + *in = (int32_t*)malloc(sizeof(int32_t) * size); + + if(!in) { + printf("Allocation of memory failed \n"); + return -1; + } + + for(i = 0; i < size; i++) { + (*in)[i] = data; + data += 0x00020002; + usleep(50); + } + + return 0; +} + +int InitOutputData(int32_t** out, int size) +{ + int i; + *out = (int32_t*)malloc(sizeof(int32_t) * size); + + if(!out) { + printf("Allocation of memory failed \n"); + return -1; + } + + for(i = 0; i < size; i++) { + (*out)[i] = 0xABCDEF00; + usleep(50); + } + + return 0; +} + +void AIE_systemConfig(int32_t* in, int32_t* out, int input_size, int output_size) +{ + uint64_t memAddr = (uint64_t)in; + uint64_t mem_outAddr = (uint64_t)out; + + printf("Configuring MM2S IP\n"); + Xil_Out32(MM2S_BASE + MEM_OFFSET, (uint32_t) memAddr); + Xil_Out32(MM2S_BASE + MEM_OFFSET + 4, 0); + Xil_Out32(MM2S_BASE + SIZE_OFFSET, input_size); + Xil_Out32(MM2S_BASE + CTRL_OFFSET, 1); + printf("Done \n"); + printf("- \n"); + + printf("Configuring S2MM IP\n"); + Xil_Out32(S2MM_BASE + MEM_OFFSET, (uint32_t) mem_outAddr); + Xil_Out32(S2MM_BASE + MEM_OFFSET + 4, 0); + Xil_Out32(S2MM_BASE + SIZE_OFFSET, output_size); + Xil_Out32(S2MM_BASE + CTRL_OFFSET, 1); + printf("Done \n"); + printf("- \n"); +} + + +int main() +{ + int32_t* in; + int32_t* out; + int status; + + print("Starting AI Engine A to Z Application\n\r"); + printf("------------------------------------\n\n"); + printf("Beginning test\n"); + printf("- \n"); + + printf("Initializing input data in memory\n"); + Xil_DCacheDisable(); + status = InitInputData(&in, INPUT_SIZE); + if(status != 0) + { + printf("Error Initializing Input data memory \n"); + return -1; + } + printf("Done \n"); + printf("- \n"); + + printf("Initializing output memory space\n"); + status = InitOutputData(&out, OUTPUT_SIZE); + if(status != 0) + { + printf("Error Initializing output memory space\n"); + return -1; + } + printf("Done \n"); + printf("- \n"); + + printf("System Configuration\n"); + AIE_systemConfig(in, out, INPUT_SIZE, OUTPUT_SIZE); + printf("Done \n"); + printf("- \n"); + + printf("Running Graph for 4 iterations\n"); + gr.run(4); + + int checks = 1; + + while(1) { + printf("Checking output, check #%d\n",checks); + uint32_t v = Xil_In32(S2MM_BASE + CTRL_OFFSET); + checks++; + if(v & 6) { + break; + } + sleep(2); + } + printf("Done \n"); + printf("- \n"); + + gr.end(); + + printf("Checking Output Data: \n"); + int err = 0; + int32_t golden, dataIn, realTemp, imTemp; + + for(int i = 0; i < OUTPUT_SIZE; i++) { + dataIn = ((int32_t*)in)[i]; + realTemp = (dataIn & 0xFFFF) + ((dataIn & 0xFFFF0000)>>16); + imTemp = (dataIn & 0xFFFF) - ((dataIn & 0xFFFF0000)>>16); + golden = ((realTemp - imTemp) << 16) + realTemp + imTemp; + + if(golden != ((int32_t*)out)[i]) + { + err++; + printf("Output Error: Golden = %x Output = %x\n ",golden,((int32_t*)out)[i]); + } + } + + if(err > 0) + { + printf("The AI Engine A to Z Application failed with %d errors", err); + } + else + { + print("Successfully ran AI Engine A to Z Application with no error"); + } + + return 0; +} \ No newline at end of file diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ip/mm2s_aie/src/mm2s.cpp b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/src/mm2s.cpp similarity index 62% rename from Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ip/mm2s_aie/src/mm2s.cpp rename to AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/src/mm2s.cpp index 85f8db7bff..ea4f60c67a 100644 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ip/mm2s_aie/src/mm2s.cpp +++ b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/src/mm2s.cpp @@ -1,5 +1,8 @@ -// Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -// SPDX-License-Identifier: MIT +/* +Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +SPDX-License-Identifier: MIT +*/ + #include #include @@ -8,8 +11,7 @@ extern "C" { -//void mm2s(ap_int<32>* mem, hls::stream >& s, int size) { -void mm2s(ap_int<32>* mem, hls::stream >& s, int size) { +void mm2s(ap_int<32>* mem, hls::stream > &s, int size) { #pragma HLS INTERFACE m_axi port=mem offset=slave bundle=gmem #pragma HLS interface axis port=s @@ -20,10 +22,8 @@ void mm2s(ap_int<32>* mem, hls::stream >& s, int size) { for(int i = 0; i < size; i++) { #pragma HLS PIPELINE II=1 - //qdma_axis<32, 0, 0, 0> x; ap_axis<32, 0, 0, 0> x; x.data = mem[i]; - //x.keep_all(); s.write(x); } diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ip/s2mm_aie/src/s2mm.cpp b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/src/s2mm.cpp similarity index 71% rename from Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ip/s2mm_aie/src/s2mm.cpp rename to AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/src/s2mm.cpp index 6eb4fa5d00..fef6cdddba 100644 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ip/s2mm_aie/src/s2mm.cpp +++ b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/src/s2mm.cpp @@ -1,5 +1,8 @@ -// Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -// SPDX-License-Identifier: MIT +/* +Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +SPDX-License-Identifier: MIT +*/ + #include #include @@ -8,7 +11,6 @@ extern "C" { -//void s2mm(ap_int<32>* mem, hls::stream >& s, int size) { void s2mm(ap_int<32>* mem, hls::stream >& s, int size) { #pragma HLS INTERFACE m_axi port=mem offset=slave bundle=gmem @@ -20,7 +22,6 @@ void s2mm(ap_int<32>* mem, hls::stream >& s, int size) { for(int i = 0; i < size; i++) { #pragma HLS PIPELINE II=1 - //qdma_axis<32, 0, 0, 0> x = s.read(); ap_axis<32, 0, 0, 0> x = s.read(); mem[i] = x.data; } diff --git a/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/Makefile b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/Makefile new file mode 100755 index 0000000000..21f0a72a11 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/Makefile @@ -0,0 +1,62 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# + +ECHO = @echo +WORKSPACE := workspace +HW_EMU_PKG := simple_aie_application_system_project/build/hw_emu/package/package + +# Makefile input options +TARGET := hw +XSA := custom_platform_vek385.xsa +VITIS_PLATFORM := base_pfm_vek385 + +.PHONY: clean all vitis + +help:: + $(ECHO) "Makefile Usage:" + $(ECHO) " make all" + $(ECHO) " Command to generate the full Vitis workspace" + $(ECHO) "" + $(ECHO) " make clean" + $(ECHO) " Command to remove all the generated files." + +pfm:../vivado/build/xsa_platform/${XSA} + mkdir workspace + vitis -s vitis_pfm.py ${VITIS_PLATFORM} ${XSA} + +pl_app: hls_comp vpp_link + +aie_app: + vitis -s aie_app.py ${VITIS_PLATFORM} + +hls_comp: + vitis -s hls_comp.py ${VITIS_PLATFORM} + +vpp_link: + vitis -s vpp_link.py ${VITIS_PLATFORM} ${TARGET} + +ps_app: create_ps_app ps_config build_ps + +create_ps_app: + $(ECHO) "Creating PS platform and PS application" + vitis -s ps_app.py ${TARGET} + +ps_config:./workspace/A-to-Z_app/src/lscript.ld + $(ECHO) "Editing Heap Size in Linker script" + $(shell sed -i 's/_HEAP_SIZE :.*;/_HEAP_SIZE : 0x100000;/g' ./workspace/A-to-Z_app/src/lscript.ld) + +build_ps: + vitis -s build_ps_app.py + +package: + vitis -s package.py ${TARGET} + +vitis: pfm aie_app hls_comp vpp_link ps_app package + +run_hw_emu: ${WORKSPACE}/${HW_EMU_PKG}/launch_hw_emu.sh + ./${WORKSPACE}/${HW_EMU_PKG}/launch_hw_emu.sh + +clean: + rm -rf ${WORKSPACE} .Xil package diff --git a/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/aie_app.py b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/aie_app.py new file mode 100755 index 0000000000..aa20ef85eb --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/aie_app.py @@ -0,0 +1,28 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# + +import vitis +import sys +import os + +app_path= os.getcwd() +cmd_args=len(sys.argv) +args=str(sys.argv) + +client = vitis.create_client() +client.update_workspace(path="./workspace") + +if cmd_args == 1: + platform_name=base_pfm_vek385 +else: + platform_name=sys.argv[1] + +platform_path=app_path+"/workspace/"+platform_name+"/export/"+platform_name+"/"+platform_name+".xpfm" + +if (not os.path.isdir("./workspace/simple_aie_application")): + comp = client.create_aie_component(name="simple_aie_application", platform = platform_path, template = "installed_aie_examples/simple") + +comp = client.get_component(name="simple_aie_application") +comp.build(target="hw") diff --git a/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/build_ps_app.py b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/build_ps_app.py new file mode 100755 index 0000000000..7fa26bb965 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/build_ps_app.py @@ -0,0 +1,16 @@ +# +# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# + +import vitis + +client = vitis.create_client() +client.update_workspace(path="./workspace") + + +comp = client.get_component(name="A-to-Z_app") +comp.build() + +vitis.dispose() + diff --git a/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/hls_comp.py b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/hls_comp.py new file mode 100755 index 0000000000..45f95481ce --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/hls_comp.py @@ -0,0 +1,75 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# + +import vitis +import sys +import os + +app_path= os.getcwd() +cmd_args=len(sys.argv) +args=str(sys.argv) + + +client = vitis.create_client() +client.update_workspace(path="./workspace") + +if cmd_args == 1: + platform_name="base_pfm_vck190" +else: + platform_name=sys.argv[1] + +if "vck190" in platform_name: + part="xcvc1902-vsva2197-2MP-e-S" +else: + part="xc2ve3858-ssva2112-2MP-e-S" + +hls_src_loc=app_path+"/../src/" + + +# +# Create MM2S HLS PL Kernel Component +# + +if (not os.path.isdir("./workspace/mm2s")): + comp = client.create_hls_component(name="mm2s", cfg_file = ["mm2s_config.cfg"], template = "empty_hls_component") + +comp = client.get_component(name="mm2s") + +hls_comp_cfg = client.get_config_file(comp.component_location+'/mm2s_config.cfg') +hls_comp_cfg.set_value(key='part', value=part) +hls_comp_cfg.set_value(section='hls', key='flow_target', value='vitis') +hls_comp_cfg.set_value(section='hls', key='package.output.format', value='xo') +hls_comp_cfg.set_value(section='hls', key='package.output.syn', value='true') +hls_comp_cfg.set_values(section='hls', key='syn.file', values=[hls_src_loc+'mm2s.cpp']) +hls_comp_cfg.set_value(section='hls', key='syn.top', value='mm2s') + + +comp.run(operation="SYNTHESIS") +comp.run(operation="PACKAGE") + +# +# Create S2MM HLS PL Kernel Component +# + +if (not os.path.isdir("./workspace/s2mm")): + comp = client.create_hls_component(name="s2mm", cfg_file = ["s2mm_config.cfg"], template = "empty_hls_component") + +comp = client.get_component(name="s2mm") + +hls_comp_cfg = client.get_config_file(comp.component_location+'/s2mm_config.cfg') +hls_comp_cfg.set_value(key='part', value=part) +hls_comp_cfg.set_value(section='hls', key='flow_target', value='vitis') +hls_comp_cfg.set_value(section='hls', key='package.output.format', value='xo') +hls_comp_cfg.set_value(section='hls', key='package.output.syn', value='true') +hls_comp_cfg.set_values(section='hls', key='syn.file', values=[hls_src_loc+'s2mm.cpp']) +hls_comp_cfg.set_value(section='hls', key='syn.top', value='s2mm') + +comp.run(operation="SYNTHESIS") +comp.run(operation="PACKAGE") + +vitis.dispose() + + + diff --git a/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/package.py b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/package.py new file mode 100755 index 0000000000..a95f1d91c9 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/package.py @@ -0,0 +1,29 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# + +import vitis +import sys + +cmd_args=len(sys.argv) + +client = vitis.create_client() +client.update_workspace(path="./workspace") + +if cmd_args == 1: + target_sys="hw" +else: + target_sys=sys.argv[1] + + +proj = client.get_sys_project(name="simple_aie_application_system_project") + +proj_cfg = client.get_config_file(proj.project_location+'/package/package.cfg') +proj_cfg.set_value(section='package', key='ps_elf', value='../../../../A-to-Z_app/build/A-to-Z_app.elf,a72-0') +proj_cfg.set_value(section='package', key='defer_aie_run', value='true') +proj_cfg.set_value(section='package', key='enable_aie_debug', value='false') + +proj.build(target=target_sys) + +vitis.dispose() diff --git a/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/ps_app.py b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/ps_app.py new file mode 100755 index 0000000000..57a0f82593 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/ps_app.py @@ -0,0 +1,79 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# + +import vitis +import sys +import os +from hsi import * +import glob + +def get_metadata(*args): + xsa = "binary_container_1.xsa" + + ret_metadata = {'arch' : '', 'target_proc' : '', 'part' : ''} + xsa = glob.glob("./workspace/simple_aie_application_system_project/build/hw/hw_link/"+xsa, recursive=True) + if len(xsa) == 0: + print("Error: "+xsa+" not found at ../vivado/build/xsa_platform") + return "" + + xsa = xsa[0] + print("Info: Using XSA file: " + xsa + " to extract HW metadata using HSI Python API") + + HwDesign = HwManager.open_hw_design(xsa) + arch = HwDesign.FAMILY + part = HwDesign.PART + board = HwDesign.BOARD + for proc in HwDesign.get_cells(hierarchical='true',filter='IP_TYPE==PROCESSOR'): + if proc.IP_NAME == "psu_cortexa53" or proc.IP_NAME == "psv_cortexa72" or proc.IP_NAME == "cortexa78": + target_proc = proc.IP_NAME+"_0" + break + + if board == "" and part == "xc2ve3858-ssva2112-2MP-e-S": + board = "vek385" + elif board == "": + board = "custom" + else: + board = board.split(":")[1] + + print("Info: ARCH: "+arch) + print("Info: BOARD: "+board) + print("Info: PART: "+part) + print("Info: TARGET PROC: "+target_proc) + + ret_metadata['arch'] = arch + ret_metadata['part'] = part + ret_metadata['board'] = board + ret_metadata['target_proc'] = target_proc + + return ret_metadata + +app_path= os.getcwd() +Vitis_dir = os.environ.get('XILINX_VITIS') + +client = vitis.create_client() +client.update_workspace(path="./workspace") + +ret_metadata = get_metadata() + +platform_name="AIE_A-to-Z_pfm_"+ret_metadata['board'] + +platform_path=app_path+"/workspace/"+platform_name+"/export/"+platform_name+"/"+platform_name+".xpfm" + +if (not os.path.isdir("./workspace/"+platform_name)): + platform = client.create_platform_component(name = platform_name,hw_design = "./workspace/simple_aie_application_system_project/build/hw/hw_link/binary_container_1.xsa",os = "standalone",cpu = ret_metadata['target_proc'],domain_name = "standalone_"+ret_metadata['target_proc']) + platform = client.get_component(name=platform_name) + domain = platform.get_domain(name="standalone_"+ret_metadata['target_proc']) + status = domain.set_lib(lib_name="aiebaremetal", path=Vitis_dir+"/data/embeddedsw/XilinxProcessorIPLib/drivers/aiebaremetal_v1_0") + status = platform.build() + +if (not os.path.isdir("./workspace/A-to-Z_app")): + comp = client.create_app_component(name="A-to-Z_app",platform = platform_path ,domain = "standalone_"+ret_metadata['target_proc']) + comp = client.get_component(name="A-to-Z_app") + status = comp.import_files(from_loc="../src", files=["main.cpp"], dest_dir_in_cmp = "src") + status = comp.import_files(from_loc="./workspace/simple_aie_application/build/hw/Work", files=["baremetal_metadata_compile.cpp"], dest_dir_in_cmp = "src") + comp.set_app_config(key = 'USER_COMPILE_DEFINITIONS', values = "__PS_BARE_METAL__") + + +vitis.dispose() diff --git a/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/vitis_pfm.py b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/vitis_pfm.py new file mode 100755 index 0000000000..0f40e7a331 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/vitis_pfm.py @@ -0,0 +1,32 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# + +import vitis +import sys +import os +from hsi import * +import glob + +cmd_args=len(sys.argv) +args=str(sys.argv) + +client = vitis.create_client() +client.set_workspace(path="./workspace") + +if cmd_args == 1: + component_name=base_pfm_vek385 + xsa="custom_platform_vek385.xsa" +else: + component_name=sys.argv[1] + xsa=sys.argv[2] + + +if (not os.path.isdir("./workspace/"+component_name)): + platform = client.create_platform_component(name = component_name,hw_design = "../vivado/build/xsa_platform/"+xsa,os = "aie_runtime",cpu = "ai_engine") + +platform = client.get_component(name=component_name) +status = platform.build() + +vitis.dispose() \ No newline at end of file diff --git a/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/vpp_link.py b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/vpp_link.py new file mode 100755 index 0000000000..b2564067d5 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vitis/vpp_link.py @@ -0,0 +1,56 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# + +import vitis +import sys +import os + +app_path= os.getcwd() +cmd_args=len(sys.argv) +args=str(sys.argv) + +client = vitis.create_client() +#client.set_workspace(path="./workspace") +client.update_workspace(path="./workspace") + +if cmd_args == 1: + platform_name="base_pfm_vek385" +else: + platform_name=sys.argv[1] + if cmd_args == 2: + target_sys="hw" + else: + target_sys=sys.argv[2] + + +platform_path=app_path+"/workspace/"+platform_name+"/export/"+platform_name+"/"+platform_name+".xpfm" + +# +# Create System Project +# + +if (not os.path.isdir("./workspace/simple_aie_application_system_project")): + proj = client.create_sys_project(name="simple_aie_application_system_project", platform=platform_path, template="empty_accelerated_application") + proj = client.get_sys_project(name="simple_aie_application_system_project") + status = proj.add_container(name="binary_container_1") + + proj = proj.add_component(name="s2mm", container_name=["binary_container_1"]) + proj = proj.add_component(name="mm2s", container_name=["binary_container_1"]) + proj = proj.add_component(name="simple_aie_application", container_name=["binary_container_1"]) + + cfg = client.get_config_file(proj.project_location+'/hw_link/binary_container_1-link.cfg') + cfg.set_value(section='advanced', key='param', value='compiler.addOutputTypes=hw_export') + cfg.add_values(section='connectivity', key='sc', values=['mm2s_1.s:ai_engine_0.mygraph_in']) + cfg.add_values(section='connectivity', key='sc', values=['ai_engine_0.mygraph_out:s2mm_1.s']) +else: + proj = client.get_sys_project(name="simple_aie_application_system_project") + +# To create the PS Application Vitis needs the XSA of HW. Thus when HW emu is select HW target is also built +if target_sys=="hw_emu": + proj.build(target = "hw_emu") + +proj.build(target = "hw") + + diff --git a/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vivado/Makefile b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vivado/Makefile new file mode 100755 index 0000000000..61106e32b5 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vivado/Makefile @@ -0,0 +1,53 @@ +# +# Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# DEVICE SELECTION +# ========================================================= +DEVICE_NAME ?= xc2ve3858-ssva2112-2MP-e-S + +# ========================================================= +# PLATFORM NAME +# ========================================================= +PLATFORM_CUSTOM ?= custom_platform_vek385 +PRE_SYNTH := true + +# ========================================================= +# XSA NAME +# ========================================================= +XSA_PLATFORM := xsa_platform/${PLATFORM_CUSTOM}.xsa + +# ========================================================= +# BUILD PRODUCTS +# ======================================================== +BUILD_DIR := build + +# ========================================================= +# SOURCE DIRECTORIES +# ========================================================= +SRC_DIR := src + +# ========================================================= +# XSA CREATION SCRIPT +# ========================================================= +XSA_PLATFORM_TCL := $(SRC_DIR)/xsa_platform_classic.tcl + +# ========================================================= +# BOARD PART SELECTION +# ========================================================= + BOARD_LABEL:=vek385 + BOARD_VER:=1.1 + +# ========================================================= +# DEPENDENCIES +# ========================================================= +DEPS_PLATFORM := $(XSA_PLATFORM_TCL) + +platform_vivado: $(BUILD_DIR)/$(XSA_PLATFORM) + +$(BUILD_DIR)/$(XSA_PLATFORM): $(DEPS_PLATFORM) + vivado -mode batch -source $(XSA_PLATFORM_TCL) -tclargs $(PLATFORM_CUSTOM) $(DEVICE_NAME) $(PRE_SYNTH) $(BOARD_LABEL) $(BOARD_VER) $(XSA_PLATFORM) + +clean: + rm -rf $(BUILD_DIR) + rm -rf .Xil vivado* .crash* diff --git a/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vivado/src/xsa_platform_classic.tcl b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vivado/src/xsa_platform_classic.tcl new file mode 100755 index 0000000000..c7c89c039b --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/vivado/src/xsa_platform_classic.tcl @@ -0,0 +1,90 @@ +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# + +## =================================================================================== +## Create Platform Vivado Project +## This script takes in two argument: +## PLATFORM_NAME +## DEVICE_NAME (e.g. xcvc1902-vsva2197-1LP-e-S) +## =================================================================================== +namespace eval _tcl { + proc get_script_folder {} { + set script_path [file normalize [info script]] + set script_folder [file dirname $script_path] + return $script_folder + } +} + +variable script_folder +set script_folder [_tcl::get_script_folder] + + +set PLATFORM_NAME [lindex $argv 0] +set VER "1.0" +puts "Creating HW Platform project for : \"$PLATFORM_NAME\"" +set DEVICE_NAME [lindex $argv 1] +puts "Using : \"$DEVICE_NAME\"" +set BOARD_LABEL [lindex $argv 3] +set BOARD_VER [lindex $argv 4] +set BUILD_DIR build +set XSA_PLATFORM [lindex $argv 5] +set BD_NAME versal_comn_platform + +create_project -f ${PLATFORM_NAME} ${BUILD_DIR}/${PLATFORM_NAME}_vivado -part $DEVICE_NAME + +# set board part +set_property BOARD_PART xilinx.com:${BOARD_LABEL}:part0:${BOARD_VER} [current_project] + +set_property coreContainer.enable 1 [current_project] +create_bd_design ${BD_NAME} -mode batch + +## =================================================================================== +## Load Board example design +## =================================================================================== + +instantiate_example_design -template xilinx.com:design:versal_comn_platform:2.0 -design versal_comn_platform -options { Design_type.VALUE Extensible Include_AIE.VALUE true} + +set_property preferred_sim_model "tlm" [current_project] + +update_compile_order -fileset sources_1 + +## =================================================================================== +## Generate Block Design +## =================================================================================== + +generate_target all [get_files ${BUILD_DIR}/${PLATFORM_NAME}_vivado/${PLATFORM_NAME}.srcs/sources_1/bd/${BD_NAME}/${BD_NAME}.bd] + +## =================================================================================== +## Set output type to hw_export +## =================================================================================== +set_property platform.default_output_type "sd_card" [current_project] +# Help by explicitly categorizing intended platform +set_property platform.design_intent.server_managed "false" [current_project] +set_property platform.design_intent.external_host "false" [current_project] +set_property platform.design_intent.embedded "true" [current_project] +set_property platform.design_intent.datacenter "false" [current_project] +set_property platform.extensible "true" [current_project] + +## =================================================================================== +## Add hardware emulation support +## =================================================================================== +set_property PLATFORM.LINK_XP_SWITCHES_DEFAULT [list param:hw_emu.enableProfiling=false] [current_project] +#set_property SELECTED_SIM_MODEL tlm [get_bd_cells /Cips] +#set_property SELECTED_SIM_MODEL tlm [get_bd_cells /CipsNoc] +#set_property SELECTED_SIM_MODEL tlm [get_bd_cells /MemoryNoc] +#set_property SELECTED_SIM_MODEL tlm [get_bd_cells /ExtensibleRegion/ControlNoc] +#set_property SELECTED_SIM_MODEL tlm [get_bd_cells /ExtensibleRegion/DDR] + + +## =================================================================================== +## Export Platform XSA +## =================================================================================== +set_property platform.name $PLATFORM_NAME [current_project] +set_property platform.board_id {board} [current_project] +set_property platform.uses_pr {false} [current_project] + + +set_property pfm_name xilinx:${PLATFORM_NAME}:${PLATFORM_NAME}_custom:0.0 [get_files ${BUILD_DIR}/${PLATFORM_NAME}_vivado/${PLATFORM_NAME}.srcs/sources_1/bd/${BD_NAME}/${BD_NAME}.bd] +write_hw_platform -force -file ${BUILD_DIR}/${XSA_PLATFORM} diff --git a/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/README.md b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/README.md new file mode 100644 index 0000000000..9d7cb53374 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/Feature_Tutorials/README.md @@ -0,0 +1,34 @@ + + + + +
+ + + AMD logo + +

AMD Vitis™ AI Engine Tutorials

+ See Vitis™ Development Environment on amd.com +
+ See Vitis™ AI Development Environment on amd.com +
+ +# Feature Tutorials + +The AIE-MLv2 Development Feature Tutorials highlight specific features and flows that help develop AIE-MLv2 applications. + + + + + + + + +
Tutorial + Description +
A to Z AI Engine Bare-metal Flow for VEK385This tutorial introduces a complete end-to-end flow for a bare-metal host application using AI Engines and PL kernels. +
+ +

Copyright © 2020–2025 Advanced Micro Devices, Inc.

+ +

Terms and Conditions

diff --git a/AI_Engine_Development/AIE-MLv2/README.md b/AI_Engine_Development/AIE-MLv2/README.md new file mode 100644 index 0000000000..e992cd2085 --- /dev/null +++ b/AI_Engine_Development/AIE-MLv2/README.md @@ -0,0 +1,29 @@ + + + + +
+ + + AMD logo + +

AMD Vitis™ AI Engine Tutorials

+ See Vitis™ Development Environment on amd.com +
+ See Vitis™ AI Development Environment on amd.com +
+ +# AI Engine for Machine Learning v2 (AIE-MLv2) Development + +## Introduction + +The tutorials under the AI Engine for Machine Learning v2 (AIE-MLv2) Development help you learn how to target, develop, and deploy advanced algorithms using a Versal AIE-ML array in conjunction with PL IP/kernels and software applications running on the embedded processors. + +- The AIE-MLv2 Development [**Feature Tutorials**](./Feature_Tutorials/) highlight specific features and flows that help develop AI Engine-MLv2 applications. + +- The AIE-MLv2 Development [**Design Tutorials**](./Design_Tutorials/) showcase the two major phases of AI Engine-ML application development: architecting the application and developing the kernels. Both phases are demonstrated in these tutorials. + + +

Copyright © 2020–2025 Advanced Micro Devices, Inc.

+ +

Terms and Conditions

diff --git a/AI_Engine_Development/AIE/AIE.rst b/AI_Engine_Development/AIE/AIE.rst index 3c5080a169..9b0b5a1036 100644 --- a/AI_Engine_Development/AIE/AIE.rst +++ b/AI_Engine_Development/AIE/AIE.rst @@ -30,7 +30,7 @@ To easily find the right documentation corresponding to the development stage yo The major documentation for AI Engine includes: -* *Versal ACAP AI Engine Architecture Manual* (`AM009 `_) +* *Versal adaptive SoC AI Engine Architecture Manual* (`AM009 `_) * *AI Engine Tools and Flows* (`UG1076 `_) * *AI Engine Kernel and Graph Programming Guide* (`UG1079 `_) @@ -53,16 +53,16 @@ Environment Settings .. important:: - Before beginning a tutorial, read and follow the *Vitis Release Notes And Installation Guide* (`UG1742 `_) for setting up software and installing the VCK190 base platform. + Before beginning a tutorial, read and follow the *Vitis Release Notes And Installation Guide* (`UG1742 `_) for setting up software and installing the VCK190 base platform. Run the following steps to set up the environment (do **NOT** apply to tutorials that do not use the VCK190 base platform): -1. Set up your platform by running the ``xilinx-versal-common-v2024.2/environment-setup-cortexa72-cortexa53-amd-linux`` script as provided in the platform download. - This script sets up the ``SYSROOT`` and ``CXX`` variables. If the script is not present, you **must** run the ``xilinx-versal-common-v2024.2/sdk.sh`` command. -2. Set up your ``ROOTFS`` to point to the ``xilinx-versal-common-v2024.2/rootfs.ext4``. -3. Set up your ``IMAGE`` to point to ``xilinx-versal-common-v2024.2/Image``. +1. Set up your platform by running the ``xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux`` script as provided in the platform download. + This script sets up the ``SYSROOT`` and ``CXX`` variables. If the script is not present, you **must** run the ``xilinx-versal-common-v2025.2/sdk.sh`` command. +2. Set up your ``ROOTFS`` to point to the ``xilinx-versal-common-v2025.2/rootfs.ext4``. +3. Set up your ``IMAGE`` to point to ``xilinx-versal-common-v2025.2/Image``. 4. Set up your ``PLATFORM_REPO_PATHS`` environment variable based upon where you downloaded the platform. diff --git a/AI_Engine_Development/AIE/Design_Tutorials/01-aie_lenet_tutorial/README.md b/AI_Engine_Development/AIE/Design_Tutorials/01-aie_lenet_tutorial/README.md index 36c7dd1b26..1c6f9b7063 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/01-aie_lenet_tutorial/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/01-aie_lenet_tutorial/README.md @@ -15,7 +15,7 @@ # AMD Versal™ AI Engine LeNet Tutorial -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents @@ -39,7 +39,7 @@ Versal™ adaptive SoCs combine programmable logic (PL), processing system (PS), This tutorial uses the LeNet algorithm to implement a system-level design to perform image classification using the AI Engine and PL, including block RAM. The design demonstrates functional partitioning between the AI Engine and PL. It also highlights memory partitioning and hierarchy among DDR memory, PL (block RAM) and AI Engine memory. -The tutorial takes you through hardware emulation and hardware flow in the context of a complete Versal ACAP system integration. A Makefile is provided that you can modify to suit your own needs in a different context. +The tutorial takes you through hardware emulation and hardware flow in the context of a complete Versal adaptive SoC system integration. A Makefile is provided that you can modify to suit your own needs in a different context.
Objectives @@ -110,7 +110,7 @@ Note: This tutorial targets the [VCK190 Production board](https://www.xilinx.com * [AM009 AI Engine Architecture Manual](https://docs.amd.com/r/en-US/am009-versal-ai-engine/Revision-History) -* [Versal ACAP AI Engines for Dummies](https://forums.xilinx.com/t5/Design-and-Debug-Techniques-Blog/Versal-ACAP-AI-Engines-for-Dummies/ba-p/1132493) +* [Versal adaptive SoC AI Engines for Dummies](https://forums.xilinx.com/t5/Design-and-Debug-Techniques-Blog/Versal-ACAP-AI-Engines-for-Dummies/ba-p/1132493)
@@ -124,9 +124,9 @@ Tools Documentation: To build and run the LeNet tutorial, you will need the following tools downloaded/installed: -* Install the [Vitis Software Platform 2025.1](https://docs.amd.com/r/en-US/ug1701-vitis-accelerated-embedded/Vitis-Software-Platform-Installation) +* Install the [Vitis Software Platform 2025.2](https://docs.amd.com/r/en-US/ug1701-vitis-accelerated-embedded/Vitis-Software-Platform-Installation) -* Obtain a license to enable Beta Devices in AMD tools (to use the `xilinx_vck190_base_202510_1` platform) +* Obtain a license to enable Beta Devices in AMD tools (to use the `xilinx_vck190_base_202520_1` platform) * Obtain licenses for AI Engine tools @@ -174,7 +174,7 @@ platforminfo --list | grep -m 1 -A 9 vck190_base Output of the above command should be as follows: ```bash -"baseName": "xilinx_vck190_base_202510_1", +"baseName": "xilinx_vck190_base_202520_1", "version": "1.0", "type": "sdsoc", "dataCenter": "false", @@ -244,7 +244,7 @@ make run TARGET=hw_emu ### make kernels: Compile PL Kernels -In this step, the Vitis compiler takes any Vitis compiler kernels (RTL or HLS C) in the PL region of the target platform (`xilinx_vck190_base_202510_1`) and the AI Engine kernels and graph and compiles them into their respective XO files. In this design, the `dma_hls` kernel is compiled as an XO file and the `Lenet_kernel` has already been pre-compiled as an XO file. You can access the source code by unzipping the XO file. +In this step, the Vitis compiler takes any Vitis compiler kernels (RTL or HLS C) in the PL region of the target platform (`xilinx_vck190_base_202520_1`) and the AI Engine kernels and graph and compiles them into their respective XO files. In this design, the `dma_hls` kernel is compiled as an XO file and the `Lenet_kernel` has already been pre-compiled as an XO file. You can access the source code by unzipping the XO file. `unzip lenet_kernel.xo` @@ -264,7 +264,7 @@ mkdir -p ./build/hw_emu cd ./build/hw_emu v++ --target hw_emu \ - --platform xilinx_vck190_base_202510_1 \ + --platform xilinx_vck190_base_202520_1 \ --save-temps \ --temp_dir _x \ --verbose \ @@ -375,7 +375,7 @@ The expanded command is as follow: cd ./build/hw_emu; v++ -l \ - --platform xilinx_vck190_base_202510_1 \ + --platform xilinx_vck190_base_202520_1 \ --save-temps \ --temp_dir _x \ --verbose \ @@ -396,7 +396,7 @@ If EN_TRACE=1, the command is expanded as follow: cd ./build/hw; v++ -l \ - --platform xilinx_vck190_base_202510_1 \ + --platform xilinx_vck190_base_202520_1 \ --save-temps \ --temp_dir _x \ --verbose \ @@ -474,31 +474,31 @@ or aarch64-linux-gnu-g++ -O \ -c \ -D__linux__ \ - --sysroot=$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-xilinx-linux \ + --sysroot=$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-xilinx-linux \ -DXAIE_DEBUG \ - -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-xilinx-linux/usr/include/xrt \ + -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-xilinx-linux/usr/include/xrt \ -I $(XILINX_VITIS_AIETOOLS)/include \ - -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-xilinx-linux/usr/include \ - -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-xilinx-linux/usr/lib \ + -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-xilinx-linux/usr/include \ + -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-xilinx-linux/usr/lib \ ../build//Work/ps/c_rts/aie_control_xrt.cpp \ -o ../build/app_control.o aarch64-linux-gnu-g++ -O \ -c \ -D__linux__ \ - --sysroot=$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-xilinx-linux \ + --sysroot=$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-xilinx-linux \ -DXAIE_DEBUG \ - -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-xilinx-linux/usr/include/xrt \ + -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-xilinx-linux/usr/include/xrt \ -I $(XILINX_VITIS_AIETOOLS)/include \ - -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-xilinx-linux/usr/include \ - -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-xilinx-linux/usr/lib \ + -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-xilinx-linux/usr/include \ + -I $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-xilinx-linux/usr/lib \ ../design/aie_src/main.cpp \ -o ../build/lenet_app.o aarch64-linux-gnu-g++ ./build/app_control.o \ ./build/lenet_app.o \ - --sysroot=$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-xilinx-linux \ - -L$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/sysroots/aarch64-xilinx-linux/usr/lib\ + --sysroot=$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-xilinx-linux \ + -L$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/sysroots/aarch64-xilinx-linux/usr/lib\ -L$(XILINX_VITIS_AIETOOLS)/lib/aarch64.o \ -L$(XILINX_VITIS_AIETOOLS)/lib/lnx64.o \ -ladf_api_xrt \ @@ -557,10 +557,10 @@ v++ -p \ -t hw_emu \ --save-temps \ --temp_dir ./build/hw_emu/_x \ - -f xilinx_vck190_base_202510_1 \ + -f xilinx_vck190_base_202520_1 \ --package.sd_dir $(PLATFORM_REPO_PATHS)/sw/versal/xrt \ - --package.rootfs $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/rootfs.ext4 \ - --package.kernel_image $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/Image \ + --package.rootfs $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/rootfs.ext4 \ + --package.kernel_image $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/Image \ --package.boot_mode=sd \ --package.out_dir ./build/hw_emu/package \ --package.sd_dir ./design/aie_src/aiesim_data \ @@ -586,10 +586,10 @@ v++ -p \ -t hw_emu \ --save-temps \ --temp_dir ./build/hw_emu/_x \ - -f xilinx_vck190_base_202510_1 \ + -f xilinx_vck190_base_202520_1 \ --package.sd_dir $(PLATFORM_REPO_PATHS)/sw/versal/xrt \ - --package.rootfs $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/rootfs.ext4 \ - --package.kernel_image $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/Image \ + --package.rootfs $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/rootfs.ext4 \ + --package.kernel_image $(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/Image \ --package.boot_mode=sd \ --package.out_dir ./build/hw_emu/package \ --package.sd_dir ./design/aie_src/aiesim_data \ @@ -616,8 +616,8 @@ cd ../../; |Inputs Sources|Description| | --- | --- | |$(PLATFORM_REPO_PATHS)/sw/versal/xrt|The PS host application needs the XRT headers in this folder to execute.| -|$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/rootfs.ext4|The root filesystem file for Petalinux.| -|$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.1/Image|The pre-built Petalinux Image the processor boots from.| +|$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/rootfs.ext4|The root filesystem file for Petalinux.| +|$(PLATFORM_REPO_PATHS)/sw/versal/xilinx-versal-common-v2025.2/Image|The pre-built Petalinux Image the processor boots from.| |design/aie_src/aiesim_data|The data folder that contains the input data stored in DDR memory. It also contains the output golden refernece data the PS host application uses to verify the output data from the AI Engine.| |build/hw_emu/lenet_aie_xrt.elf|The PS host application executabled created in the `make application` step.| |build/hw_emu/vck190_aie_lenet.hw_emu.xsa|The XSA file created in the `make xsa` step.| @@ -652,13 +652,13 @@ cd ./build/hw_emu/package When launched, you will see the QEMU simulator load. Wait for the autoboot countdown to go to zero, and after a few minutes, you will see the root Linux prompt display: ```bash -root@versal-rootfs-common-2025_1:~# +root@versal-rootfs-common-2025_2:~# ``` In some cases, the following error might display: ``` -root@versal-rootfs-common-2025_1:~## xinit: giving up +root@versal-rootfs-common-2025_2:~## xinit: giving up xinit: unable to connect to X server: Connection refused xinit: server error Enabling notebook extension jupyter-js-widgets/extension... @@ -724,7 +724,7 @@ Transmit delay: 0 msec/char 0 msec/line **Step 7.** Power on the board. -**Step 8.** Wait until you see the `root@versal-rootfs-common-2025_1` Linux command prompt. Press enter a few times to get past any `xinit` errors. +**Step 8.** Wait until you see the `root@versal-rootfs-common-2025_2` Linux command prompt. Press enter a few times to get past any `xinit` errors. **Step 9.** Run the following commands into the TeraTerm terminal: @@ -1041,7 +1041,7 @@ Additionally, the `memcpy` and `memset` functions are used to initialize the dat #### 5. Open Graph, Obtain Handle, and Execute Graph -The following registration function was added in 2025.1 for XRT to use ADF API callbacks: +The following registration function was added in 2025.2 for XRT to use ADF API callbacks: `adf::registerXRT(dhdl, top->m_header.uuid);` @@ -1122,7 +1122,7 @@ Throughput = (no of images / Processing time) ## Power Measurement Details -Resource utilization and power are measured using vcdanalyze, and Xilinx Power Estimator (XPE) for Versal (2025.1 version) tools. +Resource utilization and power are measured using vcdanalyze, and Xilinx Power Estimator (XPE) for Versal (2025.2 version) tools. The registers and CLB LUT utilization information can be found in the Vivado project if you perform the following steps: @@ -1159,7 +1159,7 @@ The vcdanalyze tool is used to generate a `graph.xpe` file which can be input to vcdanalyze --vcd x$(VCD_FILE_NAME).vcd --xpe ``` -2. If you do not already have it installed, download and install [XPE for Versal Version 2025.1](https://www.xilinx.com/products/technology/power/xpe.html). +2. If you do not already have it installed, download and install [XPE for Versal Version 2025.2](https://www.xilinx.com/products/technology/power/xpe.html). 3. Load the `graph.xpe` into XPE to see the AI Engine power comsumption and resource utilization for lenet design: @@ -1169,7 +1169,7 @@ A summary of resource utilization and power is given in the following table. | Number of Compute Cores | Vector Load | Number of Active Memory Banks | Mem R/W Rate | Active AI Engine Tiles | Interconnect Load | Dynamic Power
(in mW) | |:-----------------------:|:-----------:|:-----------------------------:|:------------:|:----------------:|:-----------------:|:-------------------------------:| -| 5 | 30.36% | 52 | 7.72% | 13 | 6.83% | 1331 | +| 5 | 30.36% | 50 | 7.72% | 13 | 6.83% | 1331 | ## References diff --git a/AI_Engine_Development/AIE/Design_Tutorials/01-aie_lenet_tutorial/description.json b/AI_Engine_Development/AIE/Design_Tutorials/01-aie_lenet_tutorial/description.json index 78cfdb887a..b433d8e460 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/01-aie_lenet_tutorial/description.json +++ b/AI_Engine_Development/AIE/Design_Tutorials/01-aie_lenet_tutorial/description.json @@ -13,8 +13,7 @@ "pre_exec": "./env_setup_versal.sh" }, "board": { - "pre_exec": "./env_setup_versal.sh", - "post_exec": "./addon/copy_perf_files.sh" + "pre_exec": "./env_setup_versal.sh" } }, "user": { @@ -51,7 +50,6 @@ "all": "run", "hw": "sd_card" }, - "custom_board_target": "run_test", - "customized_params": "multi_params.json" + "custom_board_target": "run_test" } } diff --git a/AI_Engine_Development/AIE/Design_Tutorials/01-aie_lenet_tutorial/sample_env_setup.sh b/AI_Engine_Development/AIE/Design_Tutorials/01-aie_lenet_tutorial/sample_env_setup.sh index caa8da3778..1624f5b985 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/01-aie_lenet_tutorial/sample_env_setup.sh +++ b/AI_Engine_Development/AIE/Design_Tutorials/01-aie_lenet_tutorial/sample_env_setup.sh @@ -6,9 +6,9 @@ # ======================================================= # Set Platform ,Vitis and Versal Image repo # ======================================================= -export PLATFORM_REPO_PATHS= -export XILINX_VITIS = /2025.1 -export COMMON_IMAGE_VERSAL= +export PLATFORM_REPO_PATHS= +export XILINX_VITIS = /2025.2 +export COMMON_IMAGE_VERSAL= # ==================================================== # Source Versal Image ,Vitis and Aietools @@ -20,7 +20,7 @@ source $XILINX_VITIS/settings64.sh # ========================================================= # Platform Selection... # ========================================================= -tgt_plat=xilinx_vck190_base_202510_1 +tgt_plat=xilinx_vck190_base_202520_1 export PLATFORM=$PLATFORM_REPO_PATHS/$tgt_plat/$tgt_plat\.xpfm # ========================================================== diff --git a/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/DualSSR16_hw/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/DualSSR16_hw/Makefile index dac460cc7a..4b1e075deb 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/DualSSR16_hw/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/DualSSR16_hw/Makefile @@ -24,7 +24,7 @@ ADDON_DIR := ./addon_files # hw_emu|hw TARGET ?= hw -PFM_NAME := xilinx_vck190_base_202510_1 +PFM_NAME := xilinx_vck190_base_202520_1 PFM_NAME := $(strip $(PFM_NAME)) PLATFORM := ${PLATFORM_REPO_PATHS}/${PFM_NAME}/${PFM_NAME}.xpfm PNAME := vck190_aie_base_graph_${TARGET} diff --git a/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/DualSSR16_hw/README.md b/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/DualSSR16_hw/README.md index 5ac644db6c..dc8456f475 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/DualSSR16_hw/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/DualSSR16_hw/README.md @@ -15,7 +15,7 @@ # Dual Implementation of a Super Sampling Rate FIR Filter with Dual-Stream Input -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** The purpose of this fith part of the tutorial is to implement and run in hardware two instances of SSR with dual-stream I/Os. @@ -38,10 +38,10 @@ The first step is to compile, simulate and visualize the graph with: make clean data aie aiesim aiesimviz ``` -The output display of the average throughput gives different values for the 2 instances just because the reference time taken for G1 and G2 is the same while G1 starts before G2: +The output display (in the console or log section of Vitis Analyzer) of the average throughput gives different values for the 2 instances just because the reference time taken for G1 and G2 is the same while G1 starts before G2: -- G1 (filenames finishing with 15) output throughput is around 3900MB/s -- G2 (filenames finishing with 25) output throughput is around 4000MB/s +- G1 (filenames PhaseOut_N_K_15 finishing with 15) output throughput is around 3900MB/s +- G2 (filenames PhaseOut_N_K_25 finishing with 25) output throughput is around 4000MB/s In the 'Array view' one can see clearly the 2 instances with all input and output filenames. diff --git a/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/DualStreamSSR/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/DualStreamSSR/Makefile index 0e56a43683..43346aaaf8 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/DualStreamSSR/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/DualStreamSSR/Makefile @@ -18,7 +18,7 @@ AIE_HW_DIR = ${AIE_BUILD_DIR}/hw RM = rm -f RMDIR = rm -rf -PFM_NAME ?= xilinx_vck190_base_202510_1 +PFM_NAME ?= xilinx_vck190_base_202520_1 PLATFORM ?= $(PLATFORM_REPO_PATHS)/$(PFM_NAME)/$(PFM_NAME).xpfm # AIE compiler settings @@ -39,10 +39,12 @@ all: clean data aie aiesim aieviz throughput waveform run: clean data aie aiesim NUM_SAMPLES ?= 512 -NFRAMES ?= 16 +NFRAMES ?= 4 SYSTEM_VAR_D := -DNUM_SAMPLES=$(NUM_SAMPLES) -DNFRAMES=$(NFRAMES) -AIE_FLAGS += --aie.Xpreproc "$(SYSTEM_VAR_D)" +SYSTEM_VAR_D_Preproc := $(foreach word,$(SYSTEM_VAR_D),--aie.Xpreproc $(word)) + +AIE_FLAGS += $(SYSTEM_VAR_D_Preproc) NSamples := $(shell echo " $(NUM_SAMPLES) / 2" | bc) NFrames := $(shell echo " $(NFRAMES) + 1" | bc) diff --git a/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/DualStreamSSR/README.md b/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/DualStreamSSR/README.md index c314c12e06..26b07b235a 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/DualStreamSSR/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/DualStreamSSR/README.md @@ -15,7 +15,7 @@ # Super Sampling Rate FIR Filter with Dual-Stream Input -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** The purpose of this fourth part of the tutorial is to understand how to improve upon the performance already achieved using the two input and output stream connections to the AI Engine. diff --git a/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/DualStreamSSR/aie/SSRgraph.h b/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/DualStreamSSR/aie/SSRgraph.h index e6ac13192d..41afde795c 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/DualStreamSSR/aie/SSRgraph.h +++ b/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/DualStreamSSR/aie/SSRgraph.h @@ -121,12 +121,24 @@ std::vector taps8p[8] = { PHASE(0,8), PHASE(1,8), PHASE(2,8), PHASE(3,8) } // Constraints: location of the first kernel in the cascade + // for(int i=0;i(k[i][0]) = tile(j,i); + // } for(int i=0;i(k[i][0]) = tile(j,i); + int j0 = (i%2?LastCol:FirstCol); // 23 on even rows and 230on odd rows + int step = (i%2?-1:+1); // 23 on even rows and 230on odd rows + for(int l=0;l(k[i][l]) = tile(j,i); + location(k[i][l]) = adf::bank(j,i,2); + } } + // Cascade Connections for(int row=0;row 293.24 Msps diff --git a/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/SingleStreamSSR/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/SingleStreamSSR/Makefile index b76570f434..f9f9719bf3 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/SingleStreamSSR/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/SingleStreamSSR/Makefile @@ -18,7 +18,7 @@ AIE_HW_DIR = ${AIE_BUILD_DIR}/hw RM = rm -f RMDIR = rm -rf -PFM_NAME ?= xilinx_vck190_base_202510_1 +PFM_NAME ?= xilinx_vck190_base_202520_1 PLATFORM ?= $(PLATFORM_REPO_PATHS)/$(PFM_NAME)/$(PFM_NAME).xpfm # AIE compiler settings diff --git a/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/SingleStreamSSR/README.md b/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/SingleStreamSSR/README.md index 3f815dd399..cf5c5a64c9 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/SingleStreamSSR/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/02-super_sampling_rate_fir/SingleStreamSSR/README.md @@ -15,7 +15,7 @@ # Single-Stream Interface -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Super Sampling Rate FIR Filter diff --git a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Makefile index 053486f68b..07baa4cdbe 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Makefile @@ -47,11 +47,11 @@ step2: $(MAKE) -C Module_03_PL_Design kernels step3: - $(MAKE) -C Module_04_AI_Engine_and_PL_Integration xsa TARGET=hw REV=rev1 + $(MAKE) -C Module_04_AI_Engine_and_PL_Integration xsa sdt TARGET=hw REV=rev1 SHELL := /bin/bash step3b: - $(MAKE) -C Module_04_AI_Engine_and_PL_Integration xsa TARGET=hw_emu REV=rev1 + $(MAKE) -C Module_04_AI_Engine_and_PL_Integration xsa sdt TARGET=hw_emu REV=rev1 step4: $(MAKE) -C Module_05_Baremetal_Host_Application application MAIN=main_partial diff --git a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_01_Custom_Platform/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_01_Custom_Platform/Makefile index df651ce8b4..edab03d93c 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_01_Custom_Platform/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_01_Custom_Platform/Makefile @@ -5,7 +5,7 @@ MK_PATH := $(abspath $(lastword $(MAKEFILE_LIST))) XF_PROJ_ROOT ?= $(shell bash -c 'export MK_PATH=$(MK_PATH); echo $${MK_PATH%/AI_Engine_Development/*}') -PLATFORM ?= xilinx_vck190_base_202510_1 +PLATFORM ?= xilinx_vck190_base_202520_1 DEVICE_NAME := xcvc1902-vsva2197-2MP-e-S diff --git a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_01_Custom_Platform/README.md b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_01_Custom_Platform/README.md index a6c067b952..b148a9c5cc 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_01_Custom_Platform/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_01_Custom_Platform/README.md @@ -110,7 +110,7 @@ The first thing this `vck_190_v1_0_xsa.tcl` script does is call the `create_proj The `vck_190_v1_0_xsa.tcl` script then calls the `dr.bd.tcl` script, which generates the platform block design. Open the block design in the Vivado project located at `hw/build/vck190_v1_0_vivado/vck190_v1_0.xpr`. Note that there are five major components to the hardware platform: the AI Engine, CIPS, NoC (Network-on-Chip), Clocking Wizard IP, Clock Reset IPs, 16 AXI4-LITE SmartConnect interfaces, and a top-level AXI4-Lite SmartConnect (called ``ctrl_sm``). -![Platform Block Design](images/Beamforming_custom_BlockDiagram_2025_1.PNG) +![Platform Block Design](images/Beamforming_custom_BlockDiagram_2025_2.PNG) Open the `dr.bd.tcl` file and review the comments. After the `Setup and Error Checking` commands, note that the main function of this file is called `create_root_design`. @@ -314,7 +314,7 @@ Lastly, the `vck_190_v1_0_xsa.tcl` script generates the files necessary to suppo ### Software Platform -After creating the hardware platform (XSA) with the AI Engine IP through Vivado, import this XSA into the Vitis environment and create the software platform. Then add the aie_runtime, Linux, and standalone (bare-metal) domains into the software platform. The domains are configured with prebuilt Petalinux software components. Review Steps 2 and 3 of the [Versal Custom Platform Creation Tutorial](https://github.com/Xilinx/Vitis-Tutorials/blob/2025.1/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/README.md) if you want to learn how to create the Petalinux software components from scratch. +After creating the hardware platform (XSA) with the AI Engine IP through Vivado, import this XSA into the Vitis environment and create the software platform. Then add the aie_runtime, Linux, and standalone (bare-metal) domains into the software platform. The domains are configured with prebuilt Petalinux software components. Review Steps 2 and 3 of the [Versal Custom Platform Creation Tutorial](https://github.com/Xilinx/Vitis-Tutorials/blob/2025.2/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/README.md) if you want to learn how to create the Petalinux software components from scratch. Certain software components distributed with this tutorial are licensed under open source licenses, such as the GPL and BSD, source files for these materials are located at the following locations: @@ -401,7 +401,7 @@ Finally, software platform is generated with the `platform generate` command. Th * [Clocking Wizard IP](https://www.xilinx.com/products/intellectual-property/clocking_wizard.html) * [Processor Reset System Module IP](https://www.xilinx.com/products/intellectual-property/proc_sys_reset.html) * [CIPS Product Guide](https://docs.amd.com/access/sources/dita/map?url=pg352-cips&ft:locale=en-US) -* [Versal ACAP Programmable Network on Chip and Integrated Memory Controller Product Guide](https://docs.amd.com/access/sources/dita/map?url=pg313-network-on-chip&ft:locale=en-US) +* [Versal adaptive SoC Programmable Network on Chip and Integrated Memory Controller Product Guide](https://docs.amd.com/access/sources/dita/map?url=pg313-network-on-chip&ft:locale=en-US) ### Support diff --git a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_01_Custom_Platform/images/Beamforming_custom_BlockDiagram_2025_1.PNG b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_01_Custom_Platform/images/Beamforming_custom_BlockDiagram_2025_2.PNG similarity index 100% rename from AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_01_Custom_Platform/images/Beamforming_custom_BlockDiagram_2025_1.PNG rename to AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_01_Custom_Platform/images/Beamforming_custom_BlockDiagram_2025_2.PNG diff --git a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_02_AI_Engine_Design/README.md b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_02_AI_Engine_Design/README.md index a0f2d974d2..bbd8a7a09c 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_02_AI_Engine_Design/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_02_AI_Engine_Design/README.md @@ -42,9 +42,9 @@ aiecompiler -v \ | --- | --- | |-v | Verbose output. | |--pl-freq=400| Sets the PLIO interface to the AI Engine to 400 MHz. All the AXI4-Stream interfaces from the PL kernels to the AI Engine operate at this frequency. | -|-include=\ | Includes the src directory, the src/kernels directory, and the src/inc directory.| +|-include=\ | Includes the ``src`` directory, the ``src/kernels`` directory, and the ``src/inc`` directory.| |--platform=\.xpfm| The custom platform created in Module 01.| -|-workdir=Work| Specifies the Work directory name.| +|-workdir=Work| Specifies the work directory name.| ### Dependencies @@ -71,56 +71,56 @@ aiecompiler -v \ ### AI Engine Kernels, Graphs, and Applications -AI Engine kernels are computation functions that work together to build data flow graphs. Multiple subgraphs can be stitched together into larger high-level graphs. This beamforming tutorial uses three beamforming kernels that implement matrix multiplication functions. These kernels are strung together to form the downlink and uplink subgraphs. Three uplink and three downlink subgraphs are instantiated in a high-level data flow graph `TEST_BF` defined in `test_bf.h`. The AI Engine application contains an instance of the `TEST_BF` graph and can be compiled and simulated using the AI Engine tool chain. +AI Engine kernels are computation functions that work together to build dataflow graphs. Multiple subgraphs can be stitched into larger high-level graphs. This beamforming tutorial uses three beamforming kernels that implement matrix multiplication functions. These kernels are strung together to form the downlink and uplink subgraphs. Three uplink and three downlink subgraphs are instantiated in a high-level data flow graph `TEST_BF` defined in `test_bf.h`. The AI Engine application contains an instance of the `TEST_BF` graph and can be compiled and simulated using the AI Engine tool chain. ## AI Engine Kernels and Graphs -The fundamental beamforming kernel computes a complex matrix multiplication on a (8x8) coefficient matrix times a (8x1) input data matrix which results in a (8x1) output data matrix. The beamforming kernel repeats the matrix multiplication computation on as many (8x1) input data matrices as are fed into it. +The fundamental beamforming kernel computes a complex matrix multiplication on an (8x8) coefficient matrix times an (8x1) input data matrix, which results in an (8x1) output data matrix. The beamforming kernel repeats the matrix multiplication computation on as many (8x1) input data matrices as are provided. -When the beamforming kernel computes the matrix multiplication, the results are only partial summations. The beamforming kernel then sends the partial results to identical kernels in a cascade chain for further accumulation and multiplication into a final accumulated (8x1) output data matrix. A real 5G system is determined by the number of layers (M) and number of antennas (N). For this beamforming tutorial, M is determined by the number of inputs into the chain (that is, the length of the input data matrix (8) times the number of kernels in a cascade chain). N is determined by the number of final accumulated outputs at the end of the chain (8) times the number of chains in your design.  +When the beamforming kernel computes the matrix multiplication, the results are only partial summations. It then sends the partial results to identical kernels in a cascade chain for further accumulation and multiplication into a final accumulated (8x1) output data matrix. A real 5G system is determined by the number of layers (M) and number of antennas (N). In this tutorial, M is determined by the number of inputs into the chain (that is, the length of the input data matrix (8) times the number of kernels in a cascade chain). N is determined by the number of final accumulated outputs at the end of the chain (8) times the number of chains in the design.  -This beamforming kernel comes in three flavors: `bf8x8_fst`, `bf8x8_mid`, and `bf8x8_lst`. Review the source files defined in the `src/kernels/` folder. +This beamforming kernel comes in three variants: `bf8x8_fst`, `bf8x8_mid`, and `bf8x8_lst`. Review the source files in the `src/kernels/` folder. ![Beamforming Kernels](images/beamforming_kernels.PNG) -The kernels are strung together into a cascading chain, and they are named first, middle, and last depending on their location in the cascading chain. All three of these kernels implement the matrix multiplication function and only differ in the input and output interfaces. The first kernel in the cascading chain does not have a cascading input because it is the first kernel in a chain. The middle kernel has both a cascading input and a cascading output. The last kernel has both a cascading input and output, but writes the output to local memory instead of the cascading bus. +The kernels are connected into a cascading chain, and named first, middle, and last based on their location in the cascading chain. All three kernels implement the matrix multiplication function and differ only in the input and output interfaces. The first kernel in the cascading chain does not have a cascading input because it is the first kernel in a chain. The middle kernel has both a cascading input and a cascading output. The last kernel has both, but writes the output to local memory instead of the cascading bus. -All three beamforming kernel types start by loading the input data and input coefficient data from PL kernels. The first beamforming kernel computes the matrix multiplication, computes the first partial summation, and sends it to a middle kernel using an output cascade. The middle kernel reads the partial summation from the previous kernel, computes its own matrix multiplication on the accumulated data, and generates its own output cascade. This output cascade becomes the input cascade to either another middle kernel or the last kernel. The last kernel does the final matrix multiplication on the accumulated data and writes the final results to a PL kernel. The entire chain of beamforming kernels repeats these calculations on new input data for 12 subcarriers in total. +All three beamforming kernel types start by loading the input data and coefficient data from PL kernels. The first beamforming kernel computes the matrix multiplication, produces the first partial summation, and sends it to a middle kernel using an output cascade. The middle kernel reads the partial summation from the previous kernel, computes its own matrix multiplication on the accumulated data, and generates its own output cascade. This output cascade becomes the input cascade to either another middle kernel or the last kernel. The last kernel does the final matrix multiplication on the accumulated data and writes the final results to a PL kernel. The entire chain of beamforming kernels repeats these calculations on new input data for 12 subcarriers. ### Cascading Chain Subgraph -The subgraph `bfCascadingChain` is used to create a cascading chain of beamforming kernels. Review the graph definition in the `src/inc/subsys.h`. It is a templated subgraph with parameters `xoff`, `yoff`, and `len`. The `xoff` and `yoff` parameters define the coordinate of the leftmost AI Engine. The `len` parameter specifies the length of the cascading chain (`len-2` = the number of middle kernels in a chain). The port arrays `din[len]` and `cin[len]` are the data input and coefficient input ports. The size of these arrays is determined by the `len` parameter (so we need one data input port and one coefficient input port for each kernel in the cascade chain). Additionally, there is one output port `out` for the final output in the last kernel. +The subgraph `bfCascadingChain` creates a cascading chain of beamforming kernels. Review the graph definition in the `src/inc/subsys.h`. It is a templated subgraph with parameters `xoff`, `yoff`, and `len`. The `xoff` and `yoff` parameters define the coordinate of the leftmost AI Engine. The `len` parameter specifies the length of the cascading chain (`len-2` = the number of middle kernels in a chain). The port arrays `din[len]` and `cin[len]` are the data input and coefficient input ports. Their sizes are determined by the `len` parameter (so you need one data input port and one coefficient input port for each kernel in the cascade chain). Additionally, there is one output port `out`, for the final output in the last kernel. -You can create subgraphs that contains multiple cascading chains where each chain can be customized to contain any number of beamforming kernels. +You can create subgraphs that contains multiple cascading chains. Each chain can be customized to contain any number of beamforming kernels. ![Multiple cascading chains in a subgraph](images/cascading_chains.PNG) ### Downlink Subgraph -The subgraph DL64A32L is a 64-antenna-32-layer downlink subgraph. Review the graph definition in the `src/inc/subsys.h`. It consists of eight `bfCascadingChain` subgraphs of length four beamforming kernels. This subgraph has four data input ports and 32 coefficient input ports. All eight chains get the same input data. Each chain gets four of the coefficient input ports each. There are eight output data ports for the output of each chain. +The DL64A32L subgraph is a 64-antenna-32-layer downlink subgraph. Review the graph definition in the `src/inc/subsys.h`. It consists of eight `bfCascadingChain` subgraphs of length four beamforming kernels. This subgraph has four data input ports and 32 coefficient input ports. All eight chains get the same input data. Each chain gets four of the coefficient input ports each. There are eight output data ports, one for each chain. ### Uplink Subgraph -The uplink subgraph UL64A32L is the reverse of the downlink subgraph. Review the graph definition in the `src/inc/subsys.h` It consists of four `bfCascadingChain` subgraphs each of the length of eight beamforming kernels. This subgraph has eight data input ports and 32 coefficient input ports. All four chains get the same input data. Each chain gets eight of the coefficient input ports each. There are four output data ports for the output of each chain.   +The UL64A32L uplink subgraph is the reverse of the downlink subgraph. Review the graph definition in the `src/inc/subsys.h` It consists of four `bfCascadingChain` subgraphs each of the length of eight beamforming kernels. This subgraph has eight data input ports and 32 coefficient input ports. All four chains receive the same input data. Each chain receives eight of the coefficient input ports each. There are four output data ports, one for each chain.   ### Test Beamforming Graph -The test beamforming `TEST_BF` graph is the high-level AI Engine graph that contains three instances of the `DL64A32L` subgraph and three instances of the `UL64A32L` subgraph. Review the graph definition in the `src/test_bf.h`. +The `TEST_BF` test beamforming graph is the high-level AI Engine graph that contains three instances of the `DL64A32L` subgraph and three instances of the `UL64A32L` subgraph. Review the graph definition in the `src/test_bf.h`. ## AI Engine Application -Review the `test_bf_3x.cpp` AI Engine application. Note that all the input and output PLIO ports for the `TEST_BF` graph are instantiated. Next, instantiate the virtual platform and connect the virtual platform's `src` and `sink` arrays to PLIOs. +Review the `test_bf_3x.cpp` AI Engine application. All input and output PLIO ports for the `TEST_BF` graph are instantiated. Next, instantiate the virtual platform and connect the virtual platform's `src` and `sink` arrays to PLIOs. -Each input PLIO port has a `*.txt` file relative to the current directory that sources the input platform data. Each output PLIO port specifies a `.*txt` file to sink the output platform data. The beamforming kernels expect `cint16` data inputs, so the input data `*.txt` files are organized as four columns per row where each column represents a 16-bit real or imaginary value. +Each input PLIO port has a `*.txt` file relative to the current directory that sources the input platform data. Each output PLIO port specifies a `.*txt` file to sink the output platform data. The beamforming kernels expect `cint16` data inputs, so the input data `*.txt` files are organized as four columns per row, each column represents a 16-bit real or imaginary value. -Lastly, the AI Engine application uses the Run Time Graph Control API with an infinite graph execution. The graph `dut` is declared from the `TEST_BF` graph class. In the `main` function, this graph object is initialized and run. The `init()` method loads the graph to the AI Engine array at specific AI Engine tiles. This includes loading the ELF binaries for each AI Engine, configuring the stream switching for routing, and configuring the DMAs for I/O. It leaves the processors in a disabled state. The `run()` method starts the graph execution by enabling the processors. This graph runs for one iteration. The run-time event API for performance profiling is used to calculate the throughput of two of the output ports. +Lastly, the AI Engine application uses the Run Time Graph Control API with an infinite graph execution. The graph `dut` is declared from the `TEST_BF` graph class. In the `main` function, this graph object is initialized and run. The `init()` method loads the graph to the AI Engine array at specific AI Engine tiles. This includes loading the ELF binaries for each AI Engine, configuring the stream switching for routing, and configuring the DMAs for I/O. It leaves the processors disabled. The `run()` method starts the graph execution by enabling the processors. This graph runs for one iteration. The run-time event API for performance profiling is used to calculate the throughput of two of the output ports. ## Sending Data to the Beamforming Kernels -AI Engine kernels consume input blocks of data and produce output blocks of data. There are two data access mechanisms kernels can do: window-based access or stream-based access. The beamforming kernels access data with the window-based access mechanism. +AI Engine kernels consume input blocks of data and produce output blocks of data. There are two data access mechanisms that kernels can use: window-based access or stream-based access. The beamforming kernels use the window-based access mechanism. ### AI Engine Kernels Parameters -The view that a kernel has of incoming blocks of data is called an input window. Input windows are defined by type, to define the type of data contained within that window. The beamforming kernels expect an input window carrying complex integers where both the real and imaginary parts are 16 bits wide for the input data (`x_input`) and input coefficient (`c_input`) parameters. +An input window defines the kernel’s view of incoming blocks of data. Input windows are defined by type, to define the type of data contained within that window. The beamforming kernels expect input windows carrying complex integers where both the real and imaginary parts are 16 bits wide for the input data (`x_input`) and input coefficient (`c_input`) parameters. ``` void bf8x8_fst( \ @@ -130,7 +130,7 @@ void bf8x8_fst( \ ); ``` -The view that a kernel has of outgoing blocks of data is called an output window. The last beamforming kernel (bf8x8_lst) shows a declaration of an output window carrying complex integers where both the real and imaginary parts are 16 bits for the output data (data_out) parameter. +An output window defines the kernel’s view of outgoing blocks of data. The last beamforming kernel (bf8x8_lst) shows a declaration of an output window carrying complex integers where both the real and imaginary parts are 16 bits for the output data (data_out) parameter. ``` void bf8x8_lst( \ @@ -144,7 +144,7 @@ void bf8x8_lst( \ ### AI Engine Subgraph Window Connections -The size of the window (in bytes) is declared with the ``connect>`` construct. The ``bfCascadeChain`` data flow graph establishes the window connections between the input and output ports of the graph and the input ports of the beamforming kernels. +The window size (in bytes) is declared with the ``connect>`` construct. The ``bfCascadeChain`` dataflow graph establishes the window connections between the input and output ports of the graph and the input ports of the beamforming kernels. ```C++ // Make connections for input data and coefficient @@ -167,7 +167,7 @@ The window sizes of the coefficient, data, and output ports are as follows: ### AI Engine Application Data Files -Lastly, send the actual input data to the beamforming kernels and receive the output data from the beamforming kernels. This is accomplished through the PLIOs instantiated in the AI Engine application. Each PLIO specifies a 64-bit PL interface with an associated input or output data file. This means each row in the data files can store two (32-bit) complex data samples. An AI Engine kernel that is expecting a cint16 with a 64-bit PLIO needs a data file organized as four columns per row, where each column represents a 16-bit real or imaginary value. +Send the actual input data to the beamforming kernels and receive the output data through the PLIOs instantiated in the AI Engine application. Each PLIO specifies a 64-bit PL interface with an associated input or output data file. Each row in the data files stores two (32-bit) complex data samples. An AI Engine kernel expecting cint16 with a 64-bit PLIO needs a data file organized as four columns per row, where each column represents a 16-bit real or imaginary value. ``` <16-bit real> <16-bit imaginary> <16-bit real> <16-bit imaginary> @@ -175,7 +175,7 @@ Lastly, send the actual input data to the beamforming kernels and receive the ou ## Simulating the AI Engine Graph Application -Next, conduct a System C simulation of your AI Engine application using the AI Engine System C Simulator (`aiesimulator`). This simulator can model the AI Engine array, global memory (DDR memory), and network-on-chip (NoC). Invoke the AI Engine System C simulator with the following ``make`` command: +Next, conduct a System C simulation of your AI Engine application using the AI Engine System C Simulator (`aiesimulator`). This simulator models the AI Engine array, global memory (DDR memory), and network-on-chip (NoC). Invoke the AI Engine System C simulator with the following ``make`` command: ``` make sim @@ -188,13 +188,13 @@ cd build; aiesimulator –pkg-dir Work –output-dir aiesimulator-output |& tee aiesimulator-output/aiesim.log ``` -The `aiesimulator` executes the AI Engine application where the AI Engine graph is initialized, run, and terminated by the control thread expressed in the `main` function. By default, the `dut.run()` option specifies a graph that runs forever. In our AI Engine application, dut.run(NITER) is specified, where NITER = 1. This runs the graph for one iteration. This means the simulation has the AI Engine receiving “one block” of data samples through the input ports, and the AI Engine outputs “one block” of data samples through the output ports. The block size of the data input, coefficient input, and data output ports is specified by the `IN_DATA_WINSZ`, `IN_COEF_WINSZ`, and `OUT_DATA_WINSZ` global variables. +The `aiesimulator` executes the AI Engine application where the AI Engine graph is initialized, run, and terminated by the control thread expressed in the `main` function. By default, the `dut.run()` option specifies a graph that runs forever. In our AI Engine application, dut.run(NITER) is specified, where NITER = 1. This runs the graph for one iteration. This means the simulation has the AI Engine receiving one block of data samples through the input ports, and outputs one block through the output ports. The block sizes for the data input, coefficient input, and data output ports are specified by the `IN_DATA_WINSZ`, `IN_COEF_WINSZ`, and `OUT_DATA_WINSZ` global variables. ### Run-Time Event API for Performance Profiling -Additionally, in the AI Engine application, the `event::start_profiling` and `event::read_profiling` API calls are specified. These calls configure the AI Engine to count the accumulated number of clock cycles. Because we know how much data is coming out of the AI Engine (`OUT_DATA_WINSZ`), and using this API gets us the number of clock cycles its takes to receive all the output data, we can calculate the port throughput (bytes per second). This calculation is done in the AI Engine application and printed to the console during simulation. Note that the longer the data is simulated, the higher the throughput accuracy. Currently, the number of iterations is chosen as 20. +Additionally, in the AI Engine application, the `event::start_profiling` and `event::read_profiling` API calls are specified to configure the AI Engine to count the accumulated number of clock cycles. Because you know how much data is coming out of the AI Engine (`OUT_DATA_WINSZ`), and this API reports the number of clock cycles it takes to receive the output data, you can calculate the port throughput (bytes per second). The AI engine application does this calculation and prints to the console during simulation. The longer the data is simulated, the higher the throughput accuracy. Currently, the number of iterations is chosen as 20. -Open the `build/aiesim.log` file to view the following throughput calculations for two of the output PLIOs: +Open the `build/aiesim.log` file to view the following throughput calculations for two output PLIOs: ``` DLBF Output0: Throughput 6.56944e+08 Samples/s, i.e. 2.62777e+09 Bytes/s @@ -203,7 +203,7 @@ ULBF Output0: Throughput 6.59284e+08 Samples/s, i.e. 2.63714e+09 Bytes/s ## Conclusion -5G NR massive MIMO systems require intensive computation for matrix multiplication. It is shown that three 100 MHz 32-layer-64-antenna 5G NR beamforming systems can be implemented on 192 AI Engines with three kernels with slight differences. The proposed matrix multiplication implementation on AI Engine has a flexible and scalable architecture applicable to a wide range of use cases including but not limited to 5G wireless. +5G NR massive MIMO systems require intensive computation for matrix multiplication. Three 100 MHz 32-layer-64-antenna 5G NR beamforming systems can be implemented on 192 AI Engines with three kernels with slight differences. The proposed matrix multiplication implementation on AI Engine has a flexible and scalable architecture applicable to many use cases, including but not limited to 5G wireless. ## References @@ -223,6 +223,6 @@ ULBF Output0: Throughput 6.59284e+08 Samples/s, i.e. 2.63714e+09 Bytes/s GitHub issues will be used for tracking requests and bugs. For questions go to [forums.xilinx.com](http://forums.xilinx.com/). -

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diff --git a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_03_PL_Design/dlbf_slave/sim/Readme.md b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_03_PL_Design/dlbf_slave/sim/Readme.md index ef46e93530..f6be534750 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_03_PL_Design/dlbf_slave/sim/Readme.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_03_PL_Design/dlbf_slave/sim/Readme.md @@ -15,7 +15,7 @@ # Summary -This simulation design builds on the IP that was generated by using the Makefile in the parent directory, that is, `dlbf_slave`. The design is built using the following blocks: +This simulation design builds on the IP generated by using the Makefile in the parent directory, that is, `dlbf_slave`. The design uses the following blocks: 1. AXI4 LITE VIP 2. AXI4 Stream Master VIP @@ -34,6 +34,6 @@ This simulation design builds on the IP that was generated by using the Makefile
-

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diff --git a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_04_AI_Engine_and_PL_Integration/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_04_AI_Engine_and_PL_Integration/Makefile index c514cf7248..8baf1bb18d 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_04_AI_Engine_and_PL_Integration/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_04_AI_Engine_and_PL_Integration/Makefile @@ -1,4 +1,4 @@ -#Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +#Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT @@ -103,9 +103,9 @@ $(BUILD_DIR)/README.md: unzip $(BUILD_DIR)/rev1/hw_emu/xsa.zip -d $(BUILD_DIR)/rev1/hw_emu xsa_all: - $(MAKE) xsa TARGET=hw REV=rev0 - $(MAKE) xsa TARGET=hw REV=rev1 - $(MAKE) xsa TARGET=hw_emu REV=rev1 + $(MAKE) xsa sdt TARGET=hw REV=rev0 + $(MAKE) xsa sdt TARGET=hw REV=rev1 + $(MAKE) xsa sdt TARGET=hw_emu REV=rev1 xsa: $(BUILD_DIR)/$(REV)/$(TARGET)/$(XSA) @@ -121,7 +121,18 @@ $(BUILD_DIR)/$(REV)/$(TARGET)/$(XSA): $(DEPS) $(XOS) \ --config $(CONFIG_INI) \ -o $(XSA) - + +sdt: $(BUILD_DIR)/$(REV)/$(TARGET)/sdt/system.dts + +$(BUILD_DIR)/$(REV)/$(TARGET)/sdt/system.dts: $(BUILD_DIR)/$(REV)/$(TARGET)/$(XSA) + xsct -eval " \ + sdtgen set_dt_param -debug enable; \ + sdtgen set_dt_param -zocl enable; \ + sdtgen set_dt_param -dir $(BUILD_DIR)/$(REV)/$(TARGET)/sdt; \ + sdtgen set_dt_param -xsa $(abspath $<); \ + sdtgen set_dt_param -board_dts versal-vck190-rev1.1-x-ebm-01-reva; \ + sdtgen generate_sdt; \ + " clean: rm -rf $(BUILD_DIR)/$(REV)/$(TARGET)/$(XSA) rm -rf $(BUILD_DIR)/$(REV)/$(TARGET) diff --git a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_04_AI_Engine_and_PL_Integration/README.md b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_04_AI_Engine_and_PL_Integration/README.md index c8c9f73ed2..c85faa4d43 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_04_AI_Engine_and_PL_Integration/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_04_AI_Engine_and_PL_Integration/README.md @@ -15,9 +15,9 @@ # Recap -In _Module 01 - Creating a Custom Platform_, you created your custom embedded platform with the base components (CIPS, AI Engine, NoC, clocking infrastructure, and boot software) to create an AI Engine design that is stitched together. +In _Module 01 - Creating a Custom Platform_, you created a custom embedded platform with base components (CIPS, AI Engine, NoC, clocking infrastructure, and boot software) to create an AI Engine design that is stitched together. -In _Module 02 - Creating an AI Engine Application_, you introduced the beamforming kernel and created your downlink and uplink subgraphs, the data flow specification graph, and your top-level AI Engine application. +In _Module 02 - Creating an AI Engine Application_, you introduced the beamforming kernel and created downlink and uplink subgraphs, the data flow specification graph, and the top-level AI Engine application. In _Module 03 - Creating the PL Kernels_, you solved the data storage problem by creating PL kernels to send reference input data to the AI Engine and store output data generated by the AI Engine. @@ -25,7 +25,7 @@ In this module, you stitch together the custom platform (``.xpfm``), the AI Engi ## Building the Design -The Vitis compiler linker step for this large design takes ~16 hours to complete. +The Vitis compiler linker step for this large design takes about 16 hours to complete. ### Build XCLBIN from Scratch @@ -106,11 +106,11 @@ v++ -l \ | --- | --- | |-l | Runs Vitis compiler in link mode to link XO, O, and XPFM input files and generate an XCLBIN output file.| |-t hw_emu | Specifies the hardware emulation build target.| -|-f | Specifies the platform (.xpfm) file to which Vitis links input files.| -|--save-temps | Saves intermediate files/directories created during the link process.| +|-f | Specifies the platform (`.xpfm`) file to which Vitis links input files.| +|--save-temps | Saves intermediate files or directories created during the link process.| |-g | Generates code for debugging the kernel.| -|--config \.ini| Specifies a configuration file containing more Vitis compiler switches. This file also describes how many of each PL kernel to instantiate and how to connect the PL kernels to the PLIOs in the AI Engine. The rev0 build uses the config.ini. The rev1 build uses config_2regslice.ini, which contains timing closure techniques. | -|-o beamforming.rev\<0\|1\>.\.xclbin | Specifies the name of the output file generated by the v++ command. During the linking process, the output files must end with the .xclbin extension.| +|--config \.ini| Specifies a configuration file containing more Vitis compiler switches. This file also describes how many of each PL kernel to instantiate and how to connect the PL kernels to the PLIOs in the AI Engine. The rev0 build uses the `config.ini`. The rev1 build uses `config_2regslice.ini`, which contains timing closure techniques. | +|-o beamforming.rev\<0\|1\>.\.xclbin | Specifies the name of the output file generated by the v++ command. During the linking process, the output files must end with the `.xclbin` extension.| ### Dependencies @@ -129,7 +129,7 @@ v++ -l \ ### Build Products -Notice that the Vitis compiler linker step was invoked three times producing the following build directories: +The Vitis compiler linker step was invoked three times, producing the following build directories: |FileName|Description| | --- | --- | @@ -137,11 +137,11 @@ Notice that the Vitis compiler linker step was invoked three times producing the |build/rev1/hw/|Vitis compiler linker build with timing closure strategies applied that meets timing. | |build/rev1/hw_emu/|Vitis compiler linker build that meets timing for hardware emulation run.| -The rev0 build contains the first revision of the Vitis compiler linker step that naively links the AI Engine graph design to the PL kernels and PL platform. However, because the beamforming design makes full use of PL resources, the straightforward implementation does not meet timing. The rev1 build is the second revision of the Vitis compiler linker step with timing closure techniques applied. In Module 06, you will be working through hardware emulation, and you will need to invoke the Vitis compiler linker step again with rev1 and TARGET=hw_emu. +The rev0 build contains the first revision of the Vitis compiler linker step that naively links the AI Engine graph design to the PL kernels and PL platform. However, because the beamforming design uses PL resources, the straightforward implementation does not meet timing. The rev1 build is the second revision of the Vitis compiler linker step with timing closure techniques. In Module 06, you work through hardware emulation, and invoke the Vitis compiler linker step again with rev1 and TARGET=hw_emu. ## Introduction: Linking the System -After the AI Engine graph is created and the RTL kernels are packaged, the `v++ --link` command links them with the target platform to build the device binary (XCLBIN). This XCLBIN is used to program the hardware and includes the PDI, debug data, memory topology, IP layout, and metadata. +After the AI Engine graph is created and the RTL kernels are packaged, the `v++ --link` command links them with the target platform to build the device binary (XCLBIN). This XCLBIN programs the hardware and includes the PDI, debug data, memory topology, IP layout, and metadata. ## Timing Summary @@ -154,7 +154,7 @@ build/rev1/hw/_x/link/vivado/vpl/prj/prj.runs/impl_1/vck190_v1_0_wrapper_timing_ ### REV0: vck190_v1_0_wrapper_timing_summary_routed.rpt -Scroll down to the Design Timing Summary section in the timing summary report. You will see that rev1 has a WNS and TNS, which are both zero. This indicates that the rev0 build meets timing. +Scroll down to the Design Timing Summary section in the timing summary report. You see that rev1 has a WNS and TNS, which are both zero. This indicates that the rev0 build meets timing. ``` ... @@ -171,7 +171,7 @@ Scroll down to the Design Timing Summary section in the timing summary report. Y ### REV1: vck190_v1_0_wrapper_timing_summary_routed.rpt -Scroll down to the Design Timing Summary section in the timing summary report. You will see that rev1 has a WNS and TNS, which are both zero. This indicates that the rev1 build meets timing. +Scroll down to the Design Timing Summary section in the timing summary report. You see that rev1 has a WNS and TNS, which are both zero. This indicates that the rev1 build meets timing. ``` ... @@ -186,7 +186,7 @@ Scroll down to the Design Timing Summary section in the timing summary report. Y ... ``` -The rev0 build has a negative slack and fails timing while the rev1 build does not. During the Vitis compiler linker step, the rev0 and rev1 builds used different configuration files. A configuration file is used to specify more Vitis compiler options. The rev0 build used the ``config.ini`` file with no timing closure technique options. The rev1 build used the ``config_2regslice.ini`` file, which is similar to the ``config.ini`` but contains additional timing closure techniques. Both the ``*.ini`` files are located in `Module_04_AI_Engine_and_PL_Integration/` folder. The next sections detail the ``config.ini`` file for the rev0 build, and then the changes made in the ``config_2regslice.ini`` for a successful rev1 build, which meets timing. +The rev0 build has negative slack and fails timing while the rev1 build does not. During the Vitis compiler linker step, the rev0 and rev1 builds used different configuration files. A configuration file is used to specify additional Vitis compiler options. The rev0 build used the ``config.ini`` file with no timing closure technique options. The rev1 build used the ``config_2regslice.ini`` file, which is similar to ``config.ini`` but contains additional timing closure techniques. Both the ``*.ini`` files are located in `Module_04_AI_Engine_and_PL_Integration/` folder. The next sections detail the ``config.ini`` file for the rev0 build, and then the changes made in the ``config_2regslice.ini`` for a successful rev1 build, which meets timing. ## REV0 Configuration File (config.ini) @@ -210,7 +210,7 @@ nk=dlbf_slave:8:dlbf_o00.dlbf_o01.dlbf_o02.dlbf_o03.dlbf_o04.dlbf_o05.dlbf_o06.d The first line specifies there is one `dlbf_data` PL kernel named `dlbf_data_00`. The second line specifies there are eight `dlbf_coeffs` PL kernels named `dlbf_coeffs_00 ... dlbf_coeffs_07`. The last line specifies that there are eight `dlbf_slave` PL kernels named `dlbf_o00 ... dlbd_o07`. The ``config.ini`` file repeats this three times because there are three instances of the downlink subgraph. -The config.ini file also repeats this connection scheme for the ULBF PL kernels: +The ``config.ini`` file also repeats this connection scheme for the ULBF PL kernels: ``` #PL Kernel Instances for Uplink Subgraph 0 @@ -223,51 +223,51 @@ The ``config.ini`` file repeats this three times because there are three instanc #### Streaming Connections -The `sc` switch defines connections between the ports of the AI Engine graph and the streaming ports of PL kernels. The first set of `sc` connections are between the `dlbf_data` PL kernel instances and the AI Engine `dlbfid` (input data) ports. The next set of connections are between the `dlbf_coeffs` PL kernels and the AI Engine `dlbfic` (input coefficient) ports. The AI Engine ports are connected to the PL kernels’ `M00_AXIS` (master AXI4-Stream) ports. +The `sc` switch defines connections between the ports of the AI Engine graph and the streaming ports of PL kernels. The first set of `sc` connections is between the `dlbf_data` PL kernel instances and the AI Engine `dlbfid` (input data) ports. The next set connects the `dlbf_coeffs` PL kernels and the AI Engine `dlbfic` (input coefficient) ports. The AI Engine ports connect to the PL kernels’ `M00_AXIS` (master AXI4-Stream) ports. The next connections are between the AI Engine `dlbfo` (output) ports and the `dlbf_slave` instances. The AI Engine ports are connected to the PL kernels’ `S_AXIS` (slave AXI4-Stream) ports. -The `config.ini` file repeats this connection scheme for all three instances of the DLBF system and for all three ULBF systems as well. +The `config.ini` file repeats this connection scheme for all three DLBF and ULBF instances. ### \[clock\] Section The next section of the `config.ini` is the `[clock]` section. It only uses two clocks (`id=0` and `id=3`). The clock `id=0` is a 100 MHz clock. Clock `id=3` is a 400 MHz clock. These clocks were created by the clocking wizard in the custom platform (_Module 01 - Creating a Custom Platform_). They are available for the Vitis compiler linker to use in this step. This is possible because they were exposed using the `PFM.clock` function when creating the custom platform (XPFM). -All of the PL kernels’ `s_axi_aclk` are connected to the 100 MHz clock (`id=0`). This clock is for the AXI4-Lite port of the PL kernels. It clocks the control path in the PL kernels which allows the CIPS to send/receive control and status signals from the PL kernels. The `dlbf_data`, `ulbf_data`, `dlbf_coeff`, and `ulbf_coeff` PL kernels have an `m_axis_clk`. The `dlbf_slave` and `ulbf_slave` PL kernels have an `s_axis_clk`. These clocks are connected to the 400 MHz clock (`id=3`). This clock is for the AXI4-Stream port on these PL kernels. It clocks the data path in the PL kernels, which allows the AI Engine to receive or send data to/from the PL kernels. +All PL kernels’ `s_axi_aclk` connect to the 100 MHz clock (`id=0`). This clock is for the AXI4-Lite port of the PL kernels. It clocks the control path in the PL kernels, which allows the CIPS to send/receive control and status signals from the PL kernels. The `dlbf_data`, `ulbf_data`, `dlbf_coeff`, and `ulbf_coeff` PL kernels have an `m_axis_clk`. The `dlbf_slave` and `ulbf_slave` PL kernels have an `s_axis_clk`. These clocks are connected to the 400 MHz clock (`id=3`). This clock is for the AXI4-Stream port on these PL kernels. It clocks the data path in the PL kernels, which allows the AI Engine to receive or send data to/from the PL kernels. ### \[advanced\] Section -* **`param=compiler.addOutputTypes=hw_export`:** This switch specifies the creation of a new XSA for the target platform. The exported XSA has the name of the output file specified by the `-o` option in the (``v++``) command, with the extension `.xsa`. This advanced option should only be set when creating a new XSA. This option is required for building the fixed platform in the bare-metal flow. -* **`param=hw_emu.enableProfiling=false`:** This switch sets the hardware emulation profiling feature off. -* **`param=compiler.maxComputeUnits=1000`:** This switch sets the maximum number of compute units allowed in the system. Without this switch, the default number of maxComputeUnits is 60. +* **`param=compiler.addOutputTypes=hw_export`:** Specifies the creation of a new XSA for the target platform. The exported XSA name is based on the `-o` option in the (``v++``) command, with the extension `.xsa`. Set this advanced option only when creating a new XSA. This option is required for building the fixed platform in the bare-metal flow. +* **`param=hw_emu.enableProfiling=false`:** Sets the hardware emulation profiling feature off. +* **`param=compiler.maxComputeUnits=1000`:** Sets the maximum number of compute units allowed in the system. Without this switch, the default number of maxComputeUnits is 60. ### New XSA Platform: rev0 If you built from scratch, you can open the block design in the AMD Vivado™ project to view the new hardware platform at `build/rev0/hw/_x/link/vivado/vpl/prj/prj.xpr`. -![Linked Hardware Platform](images/Beamforming_new_xsa_2025_1.PNG) +![Linked Hardware Platform](images/Beamforming_new_xsa_2025_2.PNG) -Notice the new XSA hardware platform built on top of the custom platform you built in Module 01 (Creating a Custom Platform). It still contains the original building blocks: CIPS, NoC, AI Engine, Clocking Wizard, Processor Reset Systems, ``ctrl_sm``, and 16 AXI4-Lite SmartConnect interfaces. However, you will also notice that only six of these are being used, and ten of them remain unused. +Notice the new XSA hardware platform built on top of the custom platform you built in Module 01 (Creating a Custom Platform). It still contains the original building blocks: CIPS, NoC, AI Engine, Clocking Wizard, Processor Reset Systems, ``ctrl_sm``, and 16 AXI4-Lite SmartConnect interfaces. However, you also notice that only six of these are being used, and ten of them remain unused. -Each AXI4-Lite SmartConnect interface can have up to 15 AXI4-Lite master interfaces. Four of the AXI4-Lite SmartConnect interfaces have 15 AXI4-Lite master interfaces instantiated, one of them has 14, and one of them has four. This is total of 78 AXI4-Lite master interfaces which are connected to the newly linked PL kernels (three ``dlbf_data``, 24 ``dlbf_coeff``, three ``ulbf_data``, 12 ``ulbf_coeff``, 24 ``dlbf_slave``, and 12 ``ulbf_slave`` kernels). The AI Engine is also connected to all the PL kernels through their AXI4-Stream interfaces. +Each AXI4-Lite SmartConnect interface can have up to 15 AXI4-Lite master interfaces. Four of the AXI4-Lite SmartConnect interfaces have 15 AXI4-Lite master interfaces instantiated, one has 14, and one has four. This is total of 78 AXI4-Lite master interfaces connected to the newly linked PL kernels (three ``dlbf_data``, 24 ``dlbf_coeff``, three ``ulbf_data``, 12 ``ulbf_coeff``, 24 ``dlbf_slave``, and 12 ``ulbf_slave`` kernels). The AI Engine is also connected to all the PL kernels through their AXI4-Stream interfaces. ## Timing Closure -We know that the straightforward configuration file for the Vitis compiler linker did not meet timing. This was because this design is a high resource utilization design, running at a high frequency clock rate (400 MHz). The Vivado tool cannot perform timing closure without user intervention. This is solved by adding two ``axi4s-register slice`` IPs between the PL kernels and the AI Engine, updating the connections in the configuration file, and applying timing closure strategies during placement and routing. +You know that the straightforward configuration file for the Vitis compiler linker did not meet timing. This design is a high resource utilization design, running at a high frequency clock rate (400 MHz). The Vivado tool cannot perform timing closure without user intervention. You can solve this by adding two ``axi4s-register slice`` IPs between the PL kernels and the AI Engine, updating the connections in the configuration file, and applying timing closure strategies during placement and routing. ### Timing Closure Strategy -There are many different ways to close timing. This section details how timing closure been approached in the beamforming design. +There are many different ways to close timing. This section explains how timing closure is approached in the beamforming design. -First, find the problematic paths that resulted in the negative slack. The longest paths in the design are between the PL kernels and AI Engine, which cannot operate at 400 MHz clock frequency without negative slack. +Identify the problematic paths causing negative slack. The longest paths in the design are between the PL kernels and AI Engine, which cannot operate at 400 MHz clock frequency without negative slack. -The first thing to do is try to break up these paths and reduce the amount of time it takes to get from the PL kernel to the AI Engine. This was done by introducing two AXI register slice IPs in the paths to pipeline the data flow. +Break up these paths and reduce the amount of time it takes to get from the PL kernel to the AI Engine. You can do this by introducing two AXI register slice IPs in the paths to pipeline the data flow. -In addition to adding the AXI register slices, we also explored timing closure strategies that could be applied during each stage of implementation: placement, routing, and physical optimization. The full list of strategies available for each stage is documented in _Vivado Design Suite User Guide Implementation Chapter 2: Implementing the Design_ ([UG904](https://www.xilinx.com/search/support-keyword-search.html#q=ug904)). +In addition, apply timing closure strategies during each stage of implementation: placement, routing, and physical optimization. The full list of strategies available for each stage is documented in _Vivado Design Suite User Guide Implementation Chapter 2: Implementing the Design_ ([UG904](https://www.xilinx.com/search/support-keyword-search.html#q=ug904)). ## REV1: Configuration File (config_2regslice.ini) -The next step is to review the configuration file that contains the timing closure strategy that created rev1, which met timing. Open the `config_2regslice.ini` file, review the comments, and follow the next sections of this module. +Review the configuration file that contains the timing closure strategy that created rev1, which met timing. Open the `config_2regslice.ini` file, review the comments, and follow the next sections of this module. ### `[connectivity]` Section @@ -277,7 +277,7 @@ An additional ``nk`` switch is added, which creates 528 ``axi4s_regslice`` PL ke nk=axi4s_regslice_64b:528 ``` -The ``sc`` switches are also altered so that there are two ``axi4s_regslice_64b`` kernels between the PL kernels and AI Engine. The following snippet is an example of how this is done. +The ``sc`` switches are also altered so that there are two ``axi4s_regslice_64b`` kernels between the PL kernels and AI Engine. See the following example: ``` sc=dlbf_data_00.M00_AXIS:axi4s_regslice_64b_1.S_AXIS @@ -287,11 +287,11 @@ sc=axi4s_regslice_64b_2.M_AXIS:ai_engine_0.dlbfid0 ### `[clock]` Section -All the ``axi4s_regslice-64b`` kernels are clocked by id=3 (400 MHz). +All ``axi4s_regslice-64b`` kernels are clocked by id=3 (400 MHz). ### `[vivado]` Section -At the end of the ``config_2regslice.ini`` file, there are additional Vivado options given to the Vitis compiler linker. +At the end of the ``config_2regslice.ini`` file, additional Vivado options are given to the Vitis compiler linker. `prop=run.impl_1.STEPS.ROUTE_DESIGN.ARGS.MORE OPTIONS=-tns_cleanup` @@ -303,11 +303,11 @@ At the end of the ``config_2regslice.ini`` file, there are additional Vivado opt `prop=run.impl_1.STEPS.ROUTE_DESIGN.ARGS.DIRECTIVE=AggressiveExplore` -These are the combination timing closure strategies applied during placement, route, and physical optimization that resulted in timing closure. +These are the combination timing closure strategies applied during placement, route, and physical optimization, resulted in timing closure. ### New XSA Platform: rev1 -If you built from scratch, you can open the block design in the Vivado project to view the new hardware platform at `build/rev1/hw/_x/link/vivado/vpl/prj/prj.xpr`. Notice how the ``axi4s_regslice_64b`` PL kernels are inserted between the AI Engine and original PL kernels. +If you built from scratch, open the block design in the Vivado project to view the new hardware platform at `build/rev1/hw/_x/link/vivado/vpl/prj/prj.xpr`. Notice how the ``axi4s_regslice_64b`` PL kernels are inserted between the AI Engine and original PL kernels. ## References @@ -320,6 +320,6 @@ If you built from scratch, you can open the block design in the Vivado project t GitHub issues will be used for tracking requests and bugs. For questions go to [forums.xilinx.com](http://forums.xilinx.com/). -

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diff --git a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_04_AI_Engine_and_PL_Integration/images/Beamforming_new_xsa_2025_1.PNG b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_04_AI_Engine_and_PL_Integration/images/Beamforming_new_xsa_2025_2.PNG similarity index 100% rename from AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_04_AI_Engine_and_PL_Integration/images/Beamforming_new_xsa_2025_1.PNG rename to AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_04_AI_Engine_and_PL_Integration/images/Beamforming_new_xsa_2025_2.PNG diff --git a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_05_Baremetal_Host_Application/README.md b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_05_Baremetal_Host_Application/README.md index dfc195c0c0..2e41f7fdec 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_05_Baremetal_Host_Application/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_05_Baremetal_Host_Application/README.md @@ -1,4 +1,4 @@ - +
@@ -15,32 +15,32 @@ # Building the Design -Next, we will create two bare-metal PS host applications: +Next, you create two bare-metal PS host applications: ``` make application MAIN=main_partial make application MAIN=main_full ``` -The individual commands are explained later on in this module. +The individual commands are explained later in this module. ## Introduction: Building a Bare-Metal System -The AMD Vitis™ unified software platform provides a variety of AMD software packages, including drivers, libraries, board support packages, and complete operating systems to help you develop a software platform. In this module, you will create a standalone platform (a single-threaded, simple operating system (OS) platform) that provides the lowest layer of software modules used to access processor-specific functions. You will then compile a bare-metal application that orchestrates the data flow between the PL kernels and AI Engine graph. In Module 07 and 08, you will create a PetaLinux software platform to run Linux applications which conduct functional and performance tests. Bare-metal systems are often first created because they are simpler, easy to validate, and can help get the entire system design up and running quickly. When the bare-metal system is stable, this indicates the hardware is stable. System designers can then move on to build complex Linux-based embedded software to run on the hardware. +The AMD Vitis™ unified software platform provides AMD software packages, including drivers, libraries, board support packages, and complete operating systems to develop a software platform. In this module, you create a standalone platform (a single-threaded, simple operating system (OS) platform) that provides the lowest layer of software modules used to access processor-specific functions. You then compile a bare-metal application that orchestrates the data flow between the PL kernels and AI Engine graph. In Module 07 and 08, you create a PetaLinux software platform to run Linux applications that conduct functional and performance tests. Bare-metal systems are often created first because they are simpler, easy to validate, and can help get the entire system design up and running quickly. When the bare-metal system is stable, it indicates the hardware is stable. System designers can then move build complex Linux-based embedded software to run on the hardware. ## Building the Design -The process of building bare-metal applications can be broken down into three parts: generating the platform, compiling the PS application source code, and linking the PS application source code. These steps are repeated to create two bare-metal PS host applications (``main_partial.elf`` and ``main_full.elf``). +The process of building bare-metal applications has three parts: generating the platform, compiling the PS application source code, and linking the PS application source code. These steps are repeated to create two bare-metal PS host applications (``main_partial.elf`` and ``main_full.elf``). ### Difference between main_partial.cpp and main_full.cpp -There are two main files: ``main_partial.cpp`` and ``main_full.cpp``. The only difference between them is that the ``main_partial.cpp`` file runs through 10 complex data samples (``TDATA``) for each kernel. The ``main_partial.cpp`` file is created to run through hardware emulation in a timely manner. In Module 06, you will run the ``main_partial.elf`` file for hardware emulation. +There are two main files: ``main_partial.cpp`` and ``main_full.cpp``. The only difference is that the ``main_partial.cpp`` file runs through 10 complex data samples (``TDATA``) for each kernel. The ``main_partial.cpp`` file is created to run through hardware emulation in a timely manner. In Module 06, you run the ``main_partial.elf`` file for hardware emulation. -The ``main_full.cpp`` file runs through the full set of data. For the ``dlbf_data`` kernels, ``main_full.cpp`` runs through NITER=4 and BLOCK_SIZE=384 for a total of 1536 64-bit data packets (``TDATA``). For the ``dlbf_coeffs`` kernels, ``main_full.cpp`` runs through NITER=4 and BLOCK_SIZE=256 for a total of 1024 64-bit data packets (``TDATA``). In Module 06, you will run the ``main_full.elf`` file on the hardware run on the VCK190 board. +The ``main_full.cpp`` file runs through the full set of data. For the ``dlbf_data`` kernels, ``main_full.cpp`` runs through NITER=4 and BLOCK_SIZE=384 for a total of 1536 64-bit data packets (``TDATA``). For the ``dlbf_coeffs`` kernels, ``main_full.cpp`` runs through NITER=4 and BLOCK_SIZE=256 for a total of 1024 64-bit data packets (``TDATA``). In Module 06, you run the ``main_full.elf`` file on the hardware run on the VCK190 board. ### Generating the Platform -Building bare-metal applications requires a bare-metal domain in the platform. In Module 01, you created a custom platform with a bare-metal domain. In Module 04, you built on top of your custom platform and added PL kernels (and subsequently their PS drivers) to the design. The first step of building the bare-metal PS host application is to use the XSA generated during the link process to create a new software platform using the following command. +Building bare-metal applications requires a bare-metal domain in the platform. In Module 01, you created a custom platform with a bare-metal domain. In Module 04, you built on thatcustom platform and added PL kernels (and subsequently their PS drivers) to the design. The first step of building the bare-metal PS host application is to use the XSA generated during the link process to create a new software platform using the following command. ``` generate-platform.sh -name vck190_baremetal \ @@ -53,7 +53,7 @@ generate-platform.sh -name vck190_baremetal \ ### Compiling the PS Application Source Code -You now need to compile your PS host application (``main_partial.cpp`` or ``main_full.cpp``) and the additional source code your PS host applications need. The source code is stored in the ``baremetal_src/`` folder. This bare-metal PS host application only controls the PL kernels, so you do not need to compile the ``aie_control.cpp`` file in this design. +Compile your PS host application (``main_partial.cpp`` or ``main_full.cpp``) and the additional source code your PS host applications need. The source code is stored in the ``baremetal_src/`` folder. This bare-metal PS host application only controls the PL kernels, so you do not need to compile the ``aie_control.cpp`` file in this design. Compile the ``main_partial.cpp`` file using the following command: @@ -64,9 +64,9 @@ aarch64-none-elf-g++ -c -Wall -O0 -g -mcpu=cortex-a72 -MMD -MP \ ``` -In this step, you need to include the BSP include files from the generated platform. This command creates a `build/main_partial.o` object. The same options are used when compiling the ``main_full.cpp`` file. +In this step, include the BSP include files from the generated platform. This command creates a `build/main_partial.o` object. Use the same options to compile the ``main_full.cpp`` file. -Next, compile the helper source code stored in the ``baremetal_src/*.cpp`` files. Below is an example of how to compile the ``dlbf_din.cpp`` file. The rest of the ``baremetal_src/*.cpp`` files are compiled the same way. +Next, compile the helper source code stored in the ``baremetal_src/*.cpp`` files. Below is an example of compiling the ``dlbf_din.cpp`` file. Compile the other ``baremetal_src/*.cpp`` files are the same way. ``` aarch64-none-elf-g++ -c -Wall -O0 -g -mcpu=cortex-a72 -MMD -MP \ @@ -101,7 +101,7 @@ During this step, the board support package (BSP) ``libxil.a`` is required. It i ## Bare-Metal Source Code -This section dives into the ``baremetal_src`` code and describes the purpose of each file. Open the ``baremetal_src/*.cpp`` files to get a sense of what the source code does. A summary of the files is given below. +This section describes the ``baremetal_src`` code and the purpose of each file. Open the ``baremetal_src/*.cpp`` files to see what the source code does. A summary of the files is given below. * ``dlbf_din.cpp`` * ``ulbf_din.cpp`` @@ -110,17 +110,17 @@ This section dives into the ``baremetal_src`` code and describes the purpose of These files contain the data input for the ``dlbf_data``, ``ulbf_data``, ``dlbf_coeffs``, and ``ulbf_coeffs`` PL kernels. These PL kernels were already initialized with the input data from the ``*_hex.mem`` data files. The PS host application checks that the PL kernels were initialized correctly by comparing the BRAM content in the PL kernels with the data in these files. -The ``dlbf_gold0.cpp`` and ``ulbf_gold0.cpp`` files contain the golden data output expected from the AI Engine. The AI Engine generates the output data and stores it in the 1``dlbf_slave`` and ``ulbf_slave`` PL kernels. The PS host applications check the URAM content in these PL kernels and compare it to the expected golden output in these files. +The ``dlbf_gold0.cpp`` and ``ulbf_gold0.cpp`` files contain the golden data output expected from the AI Engine. The AI Engine generates the output data and stores it in the 1``dlbf_slave`` and ``ulbf_slave`` PL kernels. The PS host applications check the URAM content in these PL kernels and compare them to the golden output in these files. The ``dlbf_utils.cpp``, ``ulbf_utils.cpp``, ``dlbf_utils.h``, and ``ulbf_utils.h`` files contain utility functions that help the main PS host application check the input data, verify the output data, reset the PL IPs, and more. -Open the ``dlbf_utils.cpp`` file. There are three global variable arrays: `dlbfDataAddr`, `dlbfCoeffsAddr`, and `dlbfSlaveAddr`. These are arrays that contain variables that start with `XPAR_*`. The definitions of these variables are located in the `build/vck190_baremetal/psv_corexa72_0/standalone_domain/bsp/psv_cortexa72_0/include/xparameters.h` file. The xparameters are the base addresses the PS host application uses to access the control and status registers of the PL kernels. +Open the ``dlbf_utils.cpp`` file. There are three global variable arrays: `dlbfDataAddr`, `dlbfCoeffsAddr`, and `dlbfSlaveAddr`. These are arrays that contain variables that start with `XPAR_*`. The definitions of these variables are located in the `build/vck190_baremetal/psv_corexa72_0/standalone_domain/bsp/psv_cortexa72_0/include/xparameters.h` file. The xparameters provide the base addresses the PS host application uses to access the control and status registers of the PL kernels. -The ``utils.h`` and ``utils.cpp`` files contain functions that are common to the ``dlbf`` and ``ulbf`` operations. For now, it contains one function, `extractIQ`, which returns the imaginary and real parts of a given integer. +The ``utils.h`` and ``utils.cpp`` files contain functions that are common to the ``dlbf`` and ``ulbf`` operations. Currently, they contain one function, `extractIQ`, which returns the imaginary and real parts of a given integer. -The ``params.h`` file contains all the global variables that are used in the PS host application. Note that each PL kernel has its own set of global defines in this file. +The ``params.h`` file contains all the global variables used in the PS host application. Each PL kernel has its own set of global defines in this file. -In Module 03, you learned that the PL kernels contain a control status register (CSR) module. The PL kernels have been designed so that the CIPS block can access the registers in the CSR block to control the data masters or the RAM slave in the PL kernels. The CIPS block contains the A72 processor on which the PS host application runs. These global defines are the addresses the host application uses to directly access the CSR registers in the PL kernels. Below is a table of the ``dlbf_data`` CSR registers. +In Module 03, you learned that the PL kernels contain a control status register (CSR) module. The PL kernels are designed so that the CIPS block can access the registers in the CSR block to control the data masters or the RAM slave in the PL kernels. The CIPS block contains the A72 processor on which the PS host application runs. These global defines are the addresses the host application uses to directly access the CSR registers in the PL kernels. Below is a table of the ``dlbf_data`` CSR registers. **Control and Status Register Address Map** @@ -130,11 +130,11 @@ In Module 03, you learned that the PL kernels contain a control status register | 0x4 | \[0\] RESET | W | DLBF_DATA_REG_OFFSET_RESET | 1:assert, 0:deassert. Also assigned to the `m_axis_rst_bram` input in the CRS module. | | 0x4 | \[4\] GO | W | DLBF_DATA_REG_OFFSET_START | 1: start PL traffic, 0: stop PL traffic. Also assigned to the `go_bram` input in the CRS module. | | 0x8 | \[11:0\] BLOCK_SIZE | W | DLBF_DATA_REG_OFFSET_BLOCK_SIZE | Sets the block size of the stream frame. TLAST is asserted for every number of cycles. Also assigned to the `block_size_bram` input in the CRS module. | -| 0xC | \[11:0\] NITER | W| DLBF_DATA_REG_OFFSET_NITER | Sets the number of iterations of the data to go through. If this set to 0, data will be transmitted to the AI Engine forever. Also assigned to the `niter_bram` input in the CRS module. The bare-metal host applications set this register to 4.| -| 0x10 | \[15:0\] ROLLOVER_ADDR | W | DLBF_DATA_REG_OFFSET_ROLLOVER | When the BRAM address reaches the rollover address, it will reset to 0. Also assigned to the `rollover_addr_bram` input in the CRS module. | +| 0xC | \[11:0\] NITER | W| DLBF_DATA_REG_OFFSET_NITER | Sets the number of iterations of the data to go through. If this set to 0, data is transmitted to the AI Engine forever. Also assigned to the `niter_bram` input in the CRS module. The bare-metal host applications set this register to 4.| +| 0x10 | \[15:0\] ROLLOVER_ADDR | W | DLBF_DATA_REG_OFFSET_ROLLOVER | When the BRAM address reaches the rollover address, it resets to 0. Also assigned to the `rollover_addr_bram` input in the CRS module. | | 0x20 | \[0\] MASTER_DONE | R | DLBF_DATA_REG_OFFSET_DONE | When this status register is 1'b, the data master is done sending data to the AI Engine. Also assigned to the `m0_done_bram` input in the CRS module. | -All the PL master kernels (``dlbf_data``, ``dlfbf_coeffs``, ``ulbf_data``, and ``ulbf_coeffs``) also contain multiple PL data masters (BRAMs). The ``dlbf_data`` and ``dlbf_coeffs`` have four data masters. The ``ulbf_data`` and ``ulbf_coeffs`` have eight data masters. Each of these data masters also has its own set of CRS registers. The PS host application can access each PL data master register by adding the ``dlbf_data`` xparameter + the data master’s offset + the CRS offset + the CRS register offset. +All the PL master kernels (``dlbf_data``, ``dlfbf_coeffs``, ``ulbf_data``, and ``ulbf_coeffs``) also contain multiple PL data masters (BRAMs). The ``dlbf_data`` and ``dlbf_coeffs`` have four data masters. The ``ulbf_data`` and ``ulbf_coeffs`` have eight data masters. Each data master has its own set of CRS registers. The PS host application accesses each PL data master register by adding the ``dlbf_data`` xparameter + the data master’s offset + the CRS offset + the CRS register offset. The following table is a list of the ``dlbf_data`` data masters’ offsets and the CRS offset: @@ -164,34 +164,34 @@ The control and status registers of the ``dlbf_slave`` PL kernel are shown in th | --- | --- | --- | --- | --- | | 0x0 | \[31:0\] ID | R | DLBF_SLAVE_REG_OFFSET_ID | 32-bit ID register.| | 0x4 | \[0\] RESET | W | DLBF_SLAVE_REG_OFFSET_RESET | 1:assert, 0:de-assert. Also assigned to the `slave_rst_bram` input in the CRS module. | -| 0xC | \[11:0\] NITER | W | DLBF_SLAVE_REG_OFFSET_NITER | Sets the number of iterations of the data to go through. If this set to 0m, data will be transmitted to the AI Engine forever. Also assigned to the niter_bram input in the CRS module. The ``main_partial.cpp`` sets this to 4. The ``main_full.cpp`` sets this is TODO. | +| 0xC | \[11:0\] NITER | W | DLBF_SLAVE_REG_OFFSET_NITER | Sets the number of iterations of the data to go through. If this set to 0m, data is transmitted to the AI Engine forever. Also assigned to the niter_bram input in the CRS module. The ``main_partial.cpp`` sets this to 4. The ``main_full.cpp`` sets this is TODO. | | 0x20 | \[0\] SLAVE_DONE | R | DLBF_SLAVE_REG_OFFSET_DONE | When this status register is 1'b, the RAM slave is done receiving data from the AI Engine. Also assigned to the `rxdone_bram` input in the CRS module. | -Each data slave PL kernel (``dlbf_slave`` and ``ulbf_slave``) contain only one RAM slave (URAM). The PS host application can access each RAM slave module by adding the CRS offset (0x0008_0000) to the CRS register offset. For example, to access the NITER register, write to the following address: +Each data slave PL kernel (``dlbf_slave`` and ``ulbf_slave``) contains only one RAM slave (URAM). The PS host application accesses each RAM slave module by adding the CRS offset (0x0008_0000) to the CRS register offset. For example, to access the NITER register, write to the following address: ``` NITER_ADDR = DLBF_SLAVE_CSR_OFFSET + DLBF_SLAVE_REG_OFFSET_NITER ``` -The ``ulbf_slave`` PL kernel also has the same register address mapping, and its CSR registers are accessed in the same way. +The ``ulbf_slave`` PL kernel also has the same register address mapping, and its CSR registers are accessed the same way. ## PS Host Application -The next step is to review the PS host application and understand how it orchestrates the data flow between the PL kernels and the AI Engine. The PS host application also verifies the output data stored in the ``dlbf_slave`` and ``ulbf_slave`` PL kernels by comparing it to golden reference data. +Next, review the PS host application and understand how it orchestrates the data flow between the PL kernels and the AI Engine. The PS host application also verifies the output data stored in the ``dlbf_slave`` and ``ulbf_slave`` PL kernels by comparing it to golden reference data. ### Main Function -Open the ``main_partial.cpp`` source code and review the main function. It calls two functions: ``test_dlbf`` and ``test_ulbf``. If either of them returns 0, the test has failed. If both of them return 1, the test has passed. The ``test_ulbf`` function is structured in the same way as the ``test_dlbf`` function. +Open the ``main_partial.cpp`` source code and review the main function. It calls two functions: ``test_dlbf`` and ``test_ulbf``. If either of them returns 0, the test fails. If both return 1, the test passes. The ``test_ulbf`` function is structured in the same way as the ``test_dlbf`` function. ### test_dlbf/test_ulbf Functions -This section details the ``test_dlbf`` function (it is left to you to review the ``test_ulbf`` function). The diagram below shows the execution flow of the ``test_dlbf`` and ``test_ulbf`` functions. +This section details the ``test_dlbf`` function (you can review the ``test_ulbf`` function). The following diagram shows the execution flow of the ``test_dlbf`` and ``test_ulbf`` functions. ![PS Host Application Execution Flow](images/Mod5_application_execution_flow.PNG) ### Reset -The first thing the `test_dlbf` function does is call the `dlbf_reset` function (defined in the `utils_dlbf.cpp` file). This function resets the ``dlbf_data``, ``dlbf_coeff``, and ``dlbf_slave`` PL kernels. This is done by asserting and deasserting the DLBF_DATA_REG_OFFSET_RESET register using the `Xil_Out32` function. The `Xil_Out32` function is part of the AMD Hardware Abstraction Layer API in the standalone library. This API is used throughout this PS host application. See the OS and Libraries Document Collection ([UG643](https://www.xilinx.com/search/support-keyword-search.html#q=ug643)) for the full API documentation. +The first action the `test_dlbf` function does is a call to the `dlbf_reset` function (defined in the `utils_dlbf.cpp` file). This function resets the ``dlbf_data``, ``dlbf_coeff``, and ``dlbf_slave`` PL kernels. It asserts and deasserts the DLBF_DATA_REG_OFFSET_RESET register using the `Xil_Out32` function. The `Xil_Out32` function is part of the AMD Hardware Abstraction Layer API in the standalone library. This API is used throughout this PS host application. See the OS and Libraries Document Collection ([UG643](https://www.xilinx.com/search/support-keyword-search.html#q=ug643)) for the full API documentation. ### Configuration @@ -205,7 +205,7 @@ The `test_dlbf` function calls the `dlbf_data_config_ips`, `dlbf_coeffs_config_i ### Check RAM -The `dlbf_data_check_ram` and `dlbf_coeffs_check_ram` functions are called. These functions are optional, but they are useful for debugging. In Module 03, the BRAMs in the ``dlbf_data`` and ``dlbf_coeffs`` PL kernels were initialized to input data stored in ``*_hex.mem`` data files. These `check_ram` functions ensure that the ``dlbf_data`` and ``dlbf_coeffs`` RAMs have been initialized to the correct values. The golden input data is stored in the `dlbf_din.cpp` and `dlbf_coeffs.cpp` files. +The `dlbf_data_check_ram` and `dlbf_coeffs_check_ram` functions are called. These functions are optional, but useful for debugging. In Module 03, the BRAMs in the ``dlbf_data`` and ``dlbf_coeffs`` PL kernels were initialized to input data stored in ``*_hex.mem`` data files. These `check_ram` functions ensure that the ``dlbf_data`` and ``dlbf_coeffs`` RAMs were initialized to the correct values. The golden input data is stored in the `dlbf_din.cpp` and `dlbf_coeffs.cpp` files. ### Start @@ -213,9 +213,9 @@ The `dlbf_start` function is called. This function asserts the `GO` register bit ### Wait for Done: Inputs -The `dlbf_data_wait_for_done` is called continuously in a while loop. This function reads the MASTER_DONE register on each ``dlbf_data`` PL kernel. When all four data masters in the ``dlbf_data`` PL kernels have a status of DONE, the function returns a 1'b, which breaks the while loop. The while loop only calls the function 100 times maximum, and times out if the ``dlbf_data`` kernels are not done by then. +The `dlbf_data_wait_for_done` is called continuously in a while loop. This function reads the MASTER_DONE register on each ``dlbf_data`` PL kernel. When all four data masters in the ``dlbf_data`` PL kernels reports DONE, the function returns a 1'b, which breaks the while loop. The while loop only calls the function up to 100 times, and times out if the ``dlbf_data`` kernels are not done by then. -After the ``dlbf_data`` kernels are done sending their data to the AI Engine, wait for the ``dlbf_coeffs`` to send their data to the AI Engine. If the ``dlbf_data`` or ``dlbf_coeffs`` kernels time out, the test fails. +After the ``dlbf_data`` kernels finish sending their data to the AI Engine, wait for the ``dlbf_coeffs`` to send their data to the AI Engine. If the ``dlbf_data`` or ``dlbf_coeffs`` kernels time out, the test fails. ### Wait for Done: Outputs @@ -223,11 +223,11 @@ Wait for the ``dlbf_slave`` kernels to finish receiving output data from the AI ### Verify Output -If the ``dlbf_slave`` does not time out, the `test_dlbf` function calls the `dlbf_slave_read_and_verify` function. This function compares the data in the ``dlbf_slave`` to the golden output data in the `dlbf_gold0.cpp` file. If there are any mismatches, the test fails. If all the output data matches the golden output data, then the `test_dlbf` passes and returns a 1'b to the main function. +If the ``dlbf_slave`` does not time out, the `test_dlbf` function calls the `dlbf_slave_read_and_verify` function. This function compares the data in the ``dlbf_slave`` to the golden output data in the `dlbf_gold0.cpp` file. If there are any mismatches, the test fails. If all the output data matches the golden output data, `test_dlbf` passes and returns a 1'b to the main function. ## Test ULBF -The main function then calls the `test_ulbf` function. It starts the ULBF kernels and verifies the output of the AI Engine using the same execution flow as the `test_dlbf` function. +The main function then calls the `test_ulbf` function. It starts the ULBF kernels and verifies the output of the AI Engine using the same execution flow as `test_dlbf`. ## References @@ -237,6 +237,6 @@ The main function then calls the `test_ulbf` function. It starts the ULBF kernel GitHub issues will be used for tracking requests and bugs. For questions go to [forums.xilinx.com](http://forums.xilinx.com/). -

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diff --git a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_07_Petalinux/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_07_Petalinux/Makefile index d1caea21fa..4b23802b10 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_07_Petalinux/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_07_Petalinux/Makefile @@ -9,27 +9,29 @@ RELATIVE_PROJECT_DIR := ../ PROJECT_DIR := $(shell readlink -f $(RELATIVE_PROJECT_DIR)) MODULE_04_DIR := $(PROJECT_DIR)/Module_04_AI_Engine_and_PL_Integration +MODULE_07_DIR := $(PROJECT_DIR)/Module_07_Petalinux # ========================================================= # BSP # ========================================================= -BSP := xilinx-vck190-xsct-v2025.1-final.bsp +BSP := xilinx-vck190-v2025.2-final.bsp # ========================================================= # XSA SELECTION # ========================================================= XSA := $(MODULE_04_DIR)/build/rev1/hw/beamforming.rev1.hw.xsa - +SDT_DIR :=$(MODULE_04_DIR)/build/rev1/hw/sdt/ # ========================================================= # BSP SELECTION # ========================================================= -BSP := xilinx-vck190-xsct-v2025.1-final.bsp +BSP := xilinx-vck190-v2025.2-final.bsp # ========================================================= # BUILD PRODUCTS # ========================================================= BUILD_DIR := build PETALINUX_DIR := vck190_linux +VITIS_BOOT_DIR := $(MODULE_07_DIR)/build/vitis_workspace/platform/export/platform/sw/boot/ # Edit the vck190_linux/project-spec/configs/config # PetaLinux Config: Use EXT4 as rootfs format @@ -87,12 +89,13 @@ update_boot: petalinux_create: mkdir $(BUILD_DIR) -p; \ cd $(BUILD_DIR); \ - petalinux-create -t project -s $(BSP_DIR)/$(BSP) -n $(PETALINUX_DIR) + petalinux-create project -s $(BSP_DIR)/$(BSP) -n $(PETALINUX_DIR) echo "CONFIG_YOCTO_BUILDTOOLS_EXTENDED=y" >> $(BUILD_DIR)/$(PETALINUX_DIR)/project-spec/configs/config + echo "CONFIG_SYS_INIT_SP_BSS_OFFSET=5242880" >> $(BUILD_DIR)/$(PETALINUX_DIR)/project-spec/meta-user/recipes-bsp/u-boot/files/bsp.cfg @sed -i -E 's/.*CONFIG_SUBSYSTEM_INITRAMFS_IMAGE_NAME.+/CONFIG_SUBSYSTEM_INITRAMFS_IMAGE_NAME="petalinux-image-minimal"/' $(BUILD_DIR)/$(PETALINUX_DIR)/project-spec/configs/config petalinux_config: - petalinux-config -p $(BUILD_DIR)/$(PETALINUX_DIR) --get-hw-description=$(XSA) --silentconfig + petalinux-config -p $(BUILD_DIR)/$(PETALINUX_DIR) --get-hw-description=$(SDT_DIR) --silentconfig $(MAKE) -f $(lastword $(MAKEFILE_LIST)) update_config $(MAKE) -f $(lastword $(MAKEFILE_LIST)) update_rootfs_config $(MAKE) -f $(lastword $(MAKEFILE_LIST)) update_dtsi @@ -107,16 +110,27 @@ petalinux_build: $(MAKE) -f $(lastword $(MAKEFILE_LIST)) update_linux.bif platform: - xsct xsct_create_pfm.tcl vck190_custom $(XSA) + mkdir -p build/vitis_workspace + vitis -s run_sdt.py vck190_custom $(XSA) + +copy_dtb_elf_to_vitis_boot_folder: + cd $(VITIS_BOOT_DIR); \ + rm system.dtb; \ + rm bl31.elf; \ + rm u-boot.elf; \ + cp -f $(MODULE_07_DIR)/build/vck190_linux/images/linux/system.dtb $(VITIS_BOOT_DIR); \ + cp -f $(MODULE_07_DIR)/build/vck190_linux/images/linux/bl31.elf $(VITIS_BOOT_DIR); \ + cp -f $(MODULE_07_DIR)/build/vck190_linux/images/linux/u-boot.elf $(VITIS_BOOT_DIR); petalinux: $(BUILD_DIR)/$(PETALINUX_DIR)/images/linux/Image -$(BUILD_DIR)/$(PETALINUX_DIR)/images/linux/Image: $(XSA) +$(BUILD_DIR)/$(PETALINUX_DIR)/images/linux/Image: $(SDT_DIR) $(MAKE) petalinux_create $(MAKE) petalinux_config $(MAKE) petalinux_build $(MAKE) update_boot $(MAKE) platform + $(MAKE) copy_dtb_elf_to_vitis_boot_folder clean: rm -rf $(BUILD_DIR) diff --git a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_07_Petalinux/README.md b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_07_Petalinux/README.md index 7951664ec7..20be101256 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_07_Petalinux/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_07_Petalinux/README.md @@ -39,12 +39,12 @@ Creation of the PetaLinux software platform can be broken down into the followin ### Create PetaLinux: Creating the PetaLinux Project with a BSP -First, create the PetaLinux project from a board support package (BSP) with the `petalinux-create` command. A BSP is a collection of software drivers and an operating system on which your Linux applications are built. It is the support code for a given hardware platform or board that helps in basic initialization at power-up and helps software applications to be run on top of it. Because you use a VCK190 board, the ``xilinx-vck190-v2025.1-final.bsp`` package is required. +First, create the PetaLinux project from a board support package (BSP) with the `petalinux-create` command. A BSP is a collection of software drivers and an operating system on which your Linux applications are built. It is the support code for a given hardware platform or board that helps in basic initialization at power-up and helps software applications to be run on top of it. Because you use a VCK190 board, the ``xilinx-vck190-v2025.2-final.bsp`` package is required. ``` mkdir -p build; cd build; -petalinux-create -t project -s /xilinx-vck190-v2025.1-final.bsp -n vck190_linux +petalinux-create -t project -s /xilinx-vck190-v2025.2-final.bsp -n vck190_linux ``` These commands create a new PetaLinux project directory structure under `build/vck190_linux`. diff --git a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_07_Petalinux/run_sdt.py b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_07_Petalinux/run_sdt.py new file mode 100755 index 0000000000..fd9ab7afd0 --- /dev/null +++ b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_07_Petalinux/run_sdt.py @@ -0,0 +1,69 @@ +import vitis +import sys +import os + +board = sys.argv[1] # index vck190_custom +xsa = sys.argv[2] # index for xsa path +#sdt = sys.argv[3] # index for sdt path + +print("board:", board) +print("xsa:", xsa) +#print("sdt:", sdt) +workspace = "./build/vitis_workspace" +sdt_repo = os.path.join(os.environ["XILINX_VITIS"], "data", "system-device-tree-xlnx") +client = vitis.create_client() +client.update_workspace(path=workspace) + +advanced_options = client.create_advanced_options_dict(sdt_repo=sdt_repo) + +platform = client.create_platform_component( + name="platform", + hw_design=xsa, + os="standalone", + cpu="psv_cortexa72_0", + domain_name="standalone_cpu", + advanced_options=advanced_options, + compiler="gcc" +) + + +aie_domain = platform.add_domain( + name="aiengine", + os="aie_runtime", + cpu="ai_engine" +) + +aie_domain.set_qemu_args(qemu_option="PMC", path="./src/qemu/aie/pmc_args.txt") +aie_domain.set_qemu_args(qemu_option="PS", path="./src/qemu/aie/qemu_args.txt") +aie_domain.set_qemu_data(path="./src/boot") + +# Create Linux domain +linux_domain = platform.add_domain( + name="xrt", + cpu="psv_cortexa72", + os="linux", + architecture="64-bit", + #runtime="ocl", + sd_dir="./build/image", + #bootmode="sd" +) +#linux_domain.set_active() +linux_domain.set_qemu_data(path="./src/boot") +linux_domain.set_boot_dir(path="./build/vck190_linux/images/linux") +linux_domain.set_bif(path="./build/vck190_linux/images/linux/linux.bif") + +platform.build() + + + + + + + + + + + + + + diff --git a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_08_Linux_SW_Application/README.md b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_08_Linux_SW_Application/README.md index 3347c44a97..3f05914c3d 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_08_Linux_SW_Application/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_08_Linux_SW_Application/README.md @@ -45,11 +45,11 @@ One of the first things the host application does is bind the UIO drivers to the These functions call the `mmap` function to bind the physical address of the PL kernels to a memory pointer. The host application uses the memory pointer to access the register maps of the PL kernels. -### Changes from 2025.1 +### Changes from 2025.2 All AI Engine related APIs are handled through XRT APIs. XRT APIs provide this flexibility by parsing the metadata in aie.xclbin and corresponding binding code in compiled `aie_control_xrt.cpp`. Hence, it is no longer necessary to include graph.h or graph.cpp into host application compilation. Instead, only the PLIOs needed for performance measurements need to be included in `host_app.cpp`. These changes are implemented in the source code in this module. -Thus, host application is agnostic to AI Engine source code starting 2025.1. +Thus, host application is agnostic to AI Engine source code starting 2025.2. ## Load AIE XCLBIN diff --git a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_08_Linux_SW_Application/src/test_bf_app.h b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_08_Linux_SW_Application/src/test_bf_app.h index ef923e8754..5248ef448d 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_08_Linux_SW_Application/src/test_bf_app.h +++ b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_08_Linux_SW_Application/src/test_bf_app.h @@ -8,7 +8,7 @@ #define __TEST_BF_APP_H__ #include -#include "xrt.h" +//#include "xrt.h" #include "xrt/xrt_aie.h" #include "xrt/xrt_kernel.h" diff --git a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_09_Running_the_Linux_System/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_09_Running_the_Linux_System/Makefile index 8eac288def..310035fac2 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_09_Running_the_Linux_System/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_09_Running_the_Linux_System/Makefile @@ -60,7 +60,7 @@ package: aie.xclbin $(BUILD_DIR)/package_$(TARGET)/sd_card.img $(BUILD_DIR)/package_$(TARGET)/sd_card.img: cd $(BUILD_DIR); \ v++ -p -t $(TARGET) --save-temps \ - -f $(MODULE_07_DIR)/build/platform_repo/vck190_custom/export/vck190_custom/vck190_custom.xpfm \ + -f $(MODULE_07_DIR)/build/vitis_workspace/platform/export/platform/platform.xpfm \ --package.rootfs $(MODULE_07_DIR)/build/vck190_linux/images/linux/rootfs.ext4 \ --package.kernel_image ${MODULE_07_DIR}/build/vck190_linux/images/linux/Image \ --package.boot_mode=sd \ diff --git a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_09_Running_the_Linux_System/README.md b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_09_Running_the_Linux_System/README.md index 1b3630a6a6..e8d1b92079 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_09_Running_the_Linux_System/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/Module_09_Running_the_Linux_System/README.md @@ -43,7 +43,7 @@ For the hardware build, the ``–-package`` command creates an ``sd_card.img`` f ``` 7. Power on the board. -8. Wait until you see the `root@versal-rootfs-common-2025_1` Linux command prompt. Press enter a few times to get past any `xinit` errors. +8. Wait until you see the `root@versal-rootfs-common-2025_2` Linux command prompt. Press enter a few times to get past any `xinit` errors. 9. Run the following commands into the TeraTerm terminal: ``` diff --git a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/README.md b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/README.md index bd5585d03d..617d52df10 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/README.md @@ -15,7 +15,7 @@ # Beamforming Tutorial -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction @@ -56,7 +56,7 @@ This tutorial targets the [VCK190 ES board](https://www.xilinx.com/products/boar * [AM009 AI Engine Architecture Manual](https://docs.amd.com/r/en-US/am009-versal-ai-engine/Revision-History) -* [Versal ACAP AI Engines for Dummies](https://forums.xilinx.com/t5/Design-and-Debug-Techniques-Blog/Versal-ACAP-AI-Engines-for-Dummies/ba-p/1132493) +* [Versal adaptive SoC AI Engines for Dummies](https://forums.xilinx.com/t5/Design-and-Debug-Techniques-Blog/Versal-ACAP-AI-Engines-for-Dummies/ba-p/1132493) * [AI Engine Documentation](https://docs.amd.com/r/en-US/ug1076-ai-engine-environment/Overview) @@ -64,13 +64,13 @@ This tutorial targets the [VCK190 ES board](https://www.xilinx.com/products/boar 1. Obtain a license to enable beta devices in AMD tools (to use the VCK190 platform). 2. Obtain licenses for AI Engine tools. -3. Download and set up the [VCK190 Vitis Platform for 2025.1](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). +3. Download and set up the [VCK190 Vitis Platform for 2025.2](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). 4. Follow the instructions to install PetaLinux tools in the PetaLinux Tools Documentation ([UG1144](https://docs.amd.com/r/en-US/ug1144-petalinux-tools-reference-guide)). -5. Download the [VCK190 PetaLinux 2025.1 BSP](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-design-tools.html) from the Versal AI Core Series VCK190 HeadStart Early Access Site. +5. Download the [VCK190 PetaLinux 2025.2 BSP](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-design-tools.html) from the Versal AI Core Series VCK190 HeadStart Early Access Site. To build and run the Beamforming tutorial, download and install the following tools: -* [Vitis™ Unified Software Development Platform 2025.1](https://docs.amd.com/v/u/en-US/ug1416-vitis-documentation) +* [Vitis™ Unified Software Development Platform 2025.2](https://docs.amd.com/v/u/en-US/ug1416-vitis-documentation) * [The Xilinx RunTime (XRT)](https://docs.amd.com/r/en-US/ug1700-vitis-accelerated-data-center/Installing-Xilinx-Runtime-and-Platforms) * [PetaLinux Tools](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-design-tools.html) @@ -81,9 +81,9 @@ When the elements of the Vitis software platform are installed, update the shell 1. Edit the `sample_env_setup.sh` script with your file paths: ```bash - export PATH_TO_BSP= #(the folder that contains xilinx-vck190-v2025.1-final.bsp) + export PATH_TO_BSP= #(the folder that contains xilinx-vck190-v2025.2-final.bsp) - source /Vitis/2025.1/settings64.sh + source /Vitis/2025.2/settings64.sh source /settings.sh ``` @@ -104,7 +104,7 @@ When the elements of the Vitis software platform are installed, update the shell ### *Validation*: Confirming Tool Installation -Make sure you are using the 2025.1 version of the Xilinx tools. +Make sure you are using the 2025.2 version of the Xilinx tools. ```bash which vitis @@ -121,7 +121,7 @@ If you are a novice user, review the following tutorials to understand the basic ### System Design Overview -This tutorial showcases a beamforming system with 32 layers and 64 antennas implemented on an XCVC1902 Versal ACAP device in the VCK190 board. The beamforming system consists of a downlink subsystem which contains the DL64A32L AI Engine subgraph and the `dlbf_data`, `dlbf_coeff`, and `dlbf_slave` PL RTL kernels. The beamforming system also consists of the uplink subsystem, which contains the UL64A32L AI Engine subgraph and the `ulbf_data`, `ulbf_coeff`, and `ulbf_slave` PL RTL kernels. Together, the downlink and uplink subsystems implement the uplink and downlink matrix multiplication equations for M=32 layers and N=64 antennas and compute sample data. The results are compared to reference downlink and uplink result data for verification. The entire beamforming system is copied three times to make full use of the available AI Engine and PL resources. +This tutorial showcases a beamforming system with 32 layers and 64 antennas implemented on an XCVC1902 Versal adaptive SoC device in the VCK190 board. The beamforming system consists of a downlink subsystem which contains the DL64A32L AI Engine subgraph and the `dlbf_data`, `dlbf_coeff`, and `dlbf_slave` PL RTL kernels. The beamforming system also consists of the uplink subsystem, which contains the UL64A32L AI Engine subgraph and the `ulbf_data`, `ulbf_coeff`, and `ulbf_slave` PL RTL kernels. Together, the downlink and uplink subsystems implement the uplink and downlink matrix multiplication equations for M=32 layers and N=64 antennas and compute sample data. The results are compared to reference downlink and uplink result data for verification. The entire beamforming system is copied three times to make full use of the available AI Engine and PL resources. #### Block Diagram diff --git a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/sample_env_setup.sh b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/sample_env_setup.sh index bd1388a6e7..dd3e6ee46c 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/sample_env_setup.sh +++ b/AI_Engine_Development/AIE/Design_Tutorials/03-beamforming/sample_env_setup.sh @@ -10,10 +10,10 @@ unset LD_LIBRARY_PATH export PLATFORM_REPO_PATH= -export XILINX_VITIS=/Vitis/2025.1 -export COMMON_IMAGE_VERSAL= +export XILINX_VITIS=/Vitis/2025.2 +export COMMON_IMAGE_VERSAL= export BSP_DIR=/bsp/release -export BSP=xilinx-vck190-v2025.1-final.bsp +export BSP=xilinx-vck190-v2025.2-final.bsp # Setup SDKTARGETSYSROOT and CXX... source $COMMON_IMAGE_VERSAL/environment-setup-cortexa72-cortexa53-amd-linux @@ -22,12 +22,12 @@ source $COMMON_IMAGE_VERSAL/environment-setup-cortexa72-cortexa53-amd-linux source $XILINX_VITIS/settings64.sh #To source petalinux: -source /settings.sh +source /settings.sh # ========================================================= # Platform Selection... # ========================================================= -tgt_plat=xilinx_vck190_base_202510_1 +tgt_plat=xilinx_vck190_base_202520_1 export PLATFORM=$PLATFORM_REPO_PATHS/$tgt_plat/$tgt_plat\.xpfm echo "" diff --git a/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/Makefile index 8febcd9795..aa7d4b88fc 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/Makefile @@ -8,10 +8,10 @@ ECHO = @echo export TARGET = hw -RELEASE=2025.1 +RELEASE=2025.2 TOP_DIR ?= $(shell readlink -f .) -PLATFORM_NAME = xilinx_vck190_base_202510_1 +PLATFORM_NAME = xilinx_vck190_base_202520_1 PLATFORM_PATH = ${PLATFORM_REPO_PATHS} export PLATFORM = ${PLATFORM_PATH}/${PLATFORM_NAME}/${PLATFORM_NAME}.xpfm diff --git a/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/README.md b/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/README.md index 2014d7d541..e7c600685f 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/README.md @@ -15,7 +15,7 @@ # Polyphase Channelizer -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents @@ -180,17 +180,17 @@ The polyphase channelizer design can be built easily from the command line. ### Setup & Initialization -IMPORTANT: Before beginning the tutorial ensure you have installed Vitis™ 2025.1 software. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). +IMPORTANT: Before beginning the tutorial ensure you have installed Vitis™ 2025.2 software. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). Set the environment variable ```COMMON_IMAGE_VERSAL``` to the full path where you have downloaded the Common Images. Then set the environment variable ```PLATFORM_REPO_PATHS``` to the value ```$XILINX_VITIS/base_platforms```. Additional information on this process may be found [here](../../../AIE#environment-settings). The remaining environment variables are configured in the top level Makefile ```/04-Polyphase-Channelizer/Makefile``` file. ``` -RELEASE=2025.1 +RELEASE=2025.2 TOP_DIR ?= $(shell readlink -f .) -PLATFORM_NAME = xilinx_vck190_base_202510_1 +PLATFORM_NAME = xilinx_vck190_base_202520_1 PLATFORM_PATH = ${PLATFORM_REPO_PATHS} export PLATFORM = ${PLATFORM_PATH}/${PLATFORM_NAME}/${PLATFORM_NAME}.xpfm diff --git a/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/aie/m16_ssr8/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/aie/m16_ssr8/Makefile index ff905793d5..b5e412ae0f 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/aie/m16_ssr8/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/aie/m16_ssr8/Makefile @@ -18,9 +18,8 @@ SOURCES := ../m16_ssr8_filterbank/m16_ssr8_filterbank_graph.h \ ../m16_ssr8_dft/twiddle_m16_ssr8_dft.h \ m16_ssr8_graph.h +PART_USE := xcvc1902-vsva2197-2MP-e-S PL_FREQ := --aie.pl-freq=625.0 -PLATFORM_USE := xilinx_vck190_base_202510_1 -PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm LOG_FILE := log @@ -33,7 +32,7 @@ ALL_INCLUDE := --include=${PWD} --include=../m16_ssr8_filterbank --include AIE_OUTPUT := libadf.a -AIE_FLAGS := --aie.verbose ${ALL_INCLUDE} ${MY_APP}.cpp ${OTHER_OPTS} ${MAP_OPT} ${PL_FREQ} --platform=${PLATFORM} +AIE_FLAGS := --aie.verbose ${ALL_INCLUDE} ${MY_APP}.cpp ${OTHER_OPTS} ${MAP_OPT} ${PL_FREQ} --part=${PART_USE} XPE_FILE_NAME := ${MY_APP}.xpe VCD_FILE_NAME := ${MY_APP} diff --git a/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/aie/m16_ssr8_dft/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/aie/m16_ssr8_dft/Makefile index 3e7db3ca06..f2ec0d4cc0 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/aie/m16_ssr8_dft/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/aie/m16_ssr8_dft/Makefile @@ -10,11 +10,9 @@ MY_APP := m16_ssr8_dft_app SOURCES := m16_ssr8_dft_graph.h dft_1xN_widget_graph.h dft_1xN_widget.h dft_1xN_widget.cpp \ twiddle_m16_ssr8_dft.h -PLATFORM_USE := xilinx_vck190_base_202510_1 +PART_USE := xcvc1902-vsva2197-2MP-e-S PL_FREQ := --aie.pl-freq=625 -PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm - LOG_FILE := log MAP_OPT := --aie.Xmapper=BufferOptLevel9 @@ -25,7 +23,7 @@ ALL_INCLUDE := --include=${PWD} AIE_OUTPUT := libadf.a -AIE_FLAGS := --aie.verbose ${ALL_INCLUDE} ${MY_APP}.cpp ${OTHER_OPTS} ${MAP_OPT} ${PL_FREQ} --platform=${PLATFORM} +AIE_FLAGS := --aie.verbose ${ALL_INCLUDE} ${MY_APP}.cpp ${OTHER_OPTS} ${MAP_OPT} ${PL_FREQ} --part=${PART_USE} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} diff --git a/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/aie/m16_ssr8_filterbank/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/aie/m16_ssr8_filterbank/Makefile index 2303e35cbb..d74bcf5621 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/aie/m16_ssr8_filterbank/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/aie/m16_ssr8_filterbank/Makefile @@ -9,11 +9,9 @@ SIM_FIFO := false MY_APP := m16_ssr8_filterbank_app SOURCES := m16_ssr8_filterbank_graph.h polyphase_fir_graph.h polyphase_fir.h polyphase_fir.cpp -PLATFORM_USE := xilinx_vck190_base_202510_1 +PART_USE := xcvc1902-vsva2197-2MP-e-S PL_FREQ := --aie.pl-freq=625 -PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm - LOG_FILE := log MAP_OPT := --aie.Xmapper=BufferOptLevel9 @@ -24,7 +22,7 @@ ALL_INCLUDE := --include=${PWD} AIE_OUTPUT := libadf.a -AIE_FLAGS := --aie.verbose ${ALL_INCLUDE} ${MY_APP}.cpp ${OTHER_OPTS} ${MAP_OPT} ${PL_FREQ} --platform=${PLATFORM} +AIE_FLAGS := --aie.verbose ${ALL_INCLUDE} ${MY_APP}.cpp ${OTHER_OPTS} ${MAP_OPT} ${PL_FREQ} --part=${PART_USE} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} diff --git a/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/hls/m16_ssr8_permute_fb_i/m16_ssr8_permute_fb_i.cpp b/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/hls/m16_ssr8_permute_fb_i/m16_ssr8_permute_fb_i.cpp index 191e942ceb..721c4cf37d 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/hls/m16_ssr8_permute_fb_i/m16_ssr8_permute_fb_i.cpp +++ b/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/hls/m16_ssr8_permute_fb_i/m16_ssr8_permute_fb_i.cpp @@ -70,7 +70,7 @@ void m16_ssr8_permute_fb_i::align_latency( TT_DATA (&data_i_0)[M], TT_DATA (&dat static TT_DATA buff0[M][LATENCY] = { TT_DATA(0) }; static TT_DATA buff1[M][LATENCY] = { TT_DATA(0) }; static ap_uint<2> cnt = 0; -#pragma HLS reset variable=cnt; +#pragma HLS reset variable=cnt #pragma HLS array_partition variable=buff0 dim=0 #pragma HLS array_partition variable=buff1 dim=0 DELAY: for (unsigned mm=0; mm < M; mm++) { diff --git a/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/ps_apps/hw_emu/host.cpp b/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/ps_apps/hw_emu/host.cpp index b3e1ef1c49..bc600cae1f 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/ps_apps/hw_emu/host.cpp +++ b/AI_Engine_Development/AIE/Design_Tutorials/04-Polyphase-Channelizer/ps_apps/hw_emu/host.cpp @@ -4,11 +4,6 @@ // // Author: Mark Rollins -#include "m16_ssr8_graph.h" - -// Instantiate AIE graph: -m16_ssr8_graph aie_dut; - #include #include #include diff --git a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/Makefile index 0c3c21cdad..4c0085c4fd 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/Makefile @@ -7,10 +7,10 @@ ECHO = @echo export TARGET ?= hw -RELEASE=2025.1 +RELEASE=2025.2 TOP_DIR ?= $(shell readlink -f .) -PLATFORM_NAME = xilinx_vck190_base_202510_1 +PLATFORM_NAME = xilinx_vck190_base_202520_1 PLATFORM_PATH = ${PLATFORM_REPO_PATHS} export PLATFORM = ${PLATFORM_PATH}/${PLATFORM_NAME}/${PLATFORM_NAME}.xpfm diff --git a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/README.md b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/README.md index b7f42eb4e4..c2b5014bbf 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/README.md @@ -15,7 +15,7 @@ # Prime Factor FFT-1008 -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents @@ -39,9 +39,9 @@ A second advantage of the PFA approach is that unlike the popular Cooley-Tukey F This tutorial illustrates these concepts by designing a PFA-1008 transform in Versal using both AI Engine and PL elements working cooperatively. The PFA approach may be applied here since $1008 = 7 \times 9 \times 16$. This illustrates a PFA implementation in three dimensions. The transforms for each of these three relatively prime factors are implemented on AI Engine using vector-matrix DFT's. RTL implementations for the I/O permutations and intermediate "memory transpose" operations are obtained using Vitis High Level Synthesis (HLS) from untimed C++ models. -## Matlab Models +## MATLAB Models -The figure below shows a block diagram of a 2D PFA transform. It's corresponding Matlab model is shown immediately below. The algorithm consists of the following five steps: +The figure below shows a block diagram of a 2D PFA transform. It's corresponding MATLAB® model is shown immediately below. The algorithm consists of the following five steps: * An input permutation is applied to the input data. The specific input permutation depends on the values of the relative prime factors $N_1$ and $N_2$ as outlined below. * The data is organized into an $N_2 \times N_1$ matrix and 1D FFT's are performed along the rows of that matrix. @@ -49,7 +49,7 @@ The figure below shows a block diagram of a 2D PFA transform. It's corresponding * A second set of 1D FFT's are performed along the columns of the original matrix. * An output permutation is applied to the output data after being read column-wise out of its 2D matrix form. The specific output permutation depends on the values of $N_1$ and $N_2$ as outlined below. -The Matlab code below shows all of these five steps clearly. The routine `compute_perm_2d()` computes the input permutation `P_i` and output permutation `P_o` applied based on the values of $N_1$ and $N_2$. +The MATLAB code below shows all of these five steps clearly. The routine `compute_perm_2d()` computes the input permutation `P_i` and output permutation `P_o` applied based on the values of $N_1$ and $N_2$. ![figure1](images/pfa-2d-block-diagram.png) @@ -72,11 +72,11 @@ function [sig_o] = fft_pfa_2d( sig_i, N1, N2 ) end ``` -The figure below shows a block diagram of a 3D PFA transform. It's corresponding Matlab model is shown immediately below. The algorithm consists of the same steps similar to the 2D case above with the following differences: +The figure below shows a block diagram of a 3D PFA transform. It's corresponding MATLAB model is shown immediately below. The algorithm consists of the same steps similar to the 2D case above with the following differences: * The I/O permutations now depend on three relatively prime factors $N_1$, $N_2$ and $N_3$. The mathematics specific to these 2D and 3D permutations is given in detail below. * The data is now organized in a $N_1 \times N_2 \times N_3$ cube instead of an $N_1 \times N_2$ rectangle. Transforms are taken in 1D along each of these dimensions in order, first along $N_1$, then along $N_2$ and finally along $N_3$. -* The "matrix transpose" operations required to extract data in the $N_2$ and $N_3$ dimensions involve slightly more complicated "stride" patterns. These patterns are computed by the Matlab routine `compute_addr_3d.m`. +* The "matrix transpose" operations required to extract data in the $N_2$ and $N_3$ dimensions involve slightly more complicated "stride" patterns. These patterns are computed by the MATLAB routine `compute_addr_3d.m`. ![figure2](images/pfa-3d-block-diagram.png) @@ -107,7 +107,7 @@ function [sig_o] = fft_pfa_3d( sig_i, N1, N2, N3 ) end ``` -The full suite of Matlab models illustrating the operation of the PFA transforms is given in the `matlab` folder of the repo. +The full suite of MATLAB models illustrating the operation of the PFA transforms is given in the `matlab` folder of the repo. ### I/O Permutations (2D Case) @@ -176,17 +176,17 @@ The figure below summarizes the AI Engine and PL resources required to implement ### Setup & Initialization -IMPORTANT: Before beginning the tutorial ensure you have installed Vitis™ 2025.1 software. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). +IMPORTANT: Before beginning the tutorial ensure you have installed Vitis™ 2025.2 software. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). Set the environment variable ```COMMON_IMAGE_VERSAL``` to the full path where you have downloaded the Common Images. Then set the environment variable ```PLATFORM_REPO_PATHS``` to the value ```$XILINX_VITIS/base_platforms```. Additional information on this process may be found [here](../../../AIE#environment-settings). The remaining environment variables are configured in the top level Makefile ```/05-Prime-Factor-FFT/Makefile``` file. ``` -RELEASE=2025.1 +RELEASE=2025.2 TOP_DIR ?= $(shell readlink -f .) -PLATFORM_NAME = xilinx_vck190_base_202510_1 +PLATFORM_NAME = xilinx_vck190_base_202520_1 PLATFORM_PATH = ${PLATFORM_REPO_PATHS} export PLATFORM = ${PLATFORM_PATH}/${PLATFORM_NAME}/${PLATFORM_NAME}.xpfm diff --git a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/aie/dft16/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/aie/dft16/Makefile index 4413500c50..b5b6a2c15d 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/aie/dft16/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/aie/dft16/Makefile @@ -10,8 +10,7 @@ MY_APP := dft16_app MY_SOURCES := ${MY_APP}.cpp dft16_graph.h dft16_compute.h dft16_compute.cpp dft16_combine.h \ dft16_combine.cpp dft16_twiddle.h -PLATFORM_USE := xilinx_vck190_base_202510_1 -PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcvc1902-vsva2197-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing @@ -21,7 +20,7 @@ DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ AIE_OUTPUT := libadf.a -AIE_FLAGS := ${DSPLIB_OPTS} --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} +AIE_FLAGS := ${DSPLIB_OPTS} --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} diff --git a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/aie/dft7w/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/aie/dft7w/Makefile index 5e6a66c273..1187b76df7 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/aie/dft7w/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/aie/dft7w/Makefile @@ -10,8 +10,7 @@ MY_APP := dft7_app MY_SOURCES := ${MY_APP}.cpp dft7_graph.h dft7_compute.h dft7_compute.cpp dft7_combine.h \ dft7_combine.cpp dft7_twiddle.h -PLATFORM_USE := xilinx_vck190_base_202510_1 -PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcvc1902-vsva2197-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing @@ -21,7 +20,7 @@ DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ AIE_OUTPUT := libadf.a -AIE_FLAGS := ${DSPLIB_OPTS} --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} +AIE_FLAGS := ${DSPLIB_OPTS} --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} diff --git a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/aie/dft9w/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/aie/dft9w/Makefile index 86c4320e5c..247ce147ec 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/aie/dft9w/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/aie/dft9w/Makefile @@ -10,8 +10,7 @@ MY_APP := dft9_app MY_SOURCES := ${MY_APP}.cpp dft9_graph.h dft9_compute.h dft9_compute.cpp dft9_combine.h \ dft9_combine.cpp dft9_twiddle.h -PLATFORM_USE := xilinx_vck190_base_202510_1 -PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcvc1902-vsva2197-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing @@ -21,7 +20,7 @@ DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ AIE_OUTPUT := libadf.a -AIE_FLAGS := ${DSPLIB_OPTS} --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} +AIE_FLAGS := ${DSPLIB_OPTS} --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} diff --git a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/aie/pfa1008/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/aie/pfa1008/Makefile index d7dff9cef0..6617323750 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/aie/pfa1008/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/aie/pfa1008/Makefile @@ -21,8 +21,7 @@ DFT16_SOURCE := dft16_graph.h dft16_compute.h dft16_compute.cpp dft16_combi MY_SOURCES := ${MY_APP}.cpp pfa1008_graph.h ${DFT7_SOURCE:%=../dft7w/%} ${DFT9_SOURCE:%=../dft9w/%} \ ${DFT16_SOURCE:%=../dft16/%} -PLATFORM_USE := xilinx_vck190_base_202510_1 -PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcvc1902-vsva2197-2MP-e-S PL_FREQ := --aie.pl-freq=625 OTHER_OPTS := --aie.kernel-linting --aie.Xchess="-std=c++17" --aie.xlopt=1 @@ -37,7 +36,7 @@ DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ AIE_OUTPUT := libadf.a -AIE_FLAGS := ${OTHER_OPTS} ${DSPLIB_OPTS} ${MAP_OPT} ${PL_FREQ} --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} +AIE_FLAGS := ${OTHER_OPTS} ${DSPLIB_OPTS} ${MAP_OPT} ${PL_FREQ} --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} diff --git a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_dma_snk/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_dma_snk/Makefile index 17fd7503b6..d76f46d59d 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_dma_snk/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_dma_snk/Makefile @@ -5,6 +5,7 @@ # Author: Mark Rollins DO_COSIM := false +DO_OOCPAR := false ECHO := @echo KERNEL := pfa1008_dma_snk_wrapper @@ -28,6 +29,8 @@ ${XO}: ${KERNEL_SRC} ifeq (${DO_COSIM},true) vitis-run --mode hls --config hls.cfg --csim --work_dir ${KERNEL} vitis-run --mode hls --config hls.cfg --cosim --work_dir ${KERNEL} +endif +ifeq (${DO_OOCPAR},true) vitis-run --mode hls --config hls.cfg --impl --work_dir ${KERNEL} endif diff --git a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_dma_snk/pfa1008_dma_snk.cpp b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_dma_snk/pfa1008_dma_snk.cpp index 42d6d337cc..5fe7e7a579 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_dma_snk/pfa1008_dma_snk.cpp +++ b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_dma_snk/pfa1008_dma_snk.cpp @@ -11,8 +11,8 @@ using namespace pfa1008_dma_snk; // Stream Capture // ------------------------------------------------------------ -void capture_streams( TT_DATA (&buff)[NSTREAM][DEPTH], TT_STREAM sig_i[NSTREAM], - const int& loop_sel, const int& loop_cnt ) +unsigned capture_streams( TT_DATA (&buff)[NSTREAM][DEPTH], TT_STREAM sig_i[NSTREAM], + unsigned word_count ) { // Streams incoming in polyphase order, need to store into DDR in linear order: // --> ss0: s0 s2 s4 s6 s8 s10 s12 s14 @@ -20,21 +20,33 @@ void capture_streams( TT_DATA (&buff)[NSTREAM][DEPTH], TT_STREAM sig_i[NSTREAM], // // --> buff[0]: s0 s1 s2 s3 s8 s9 s10 s11 // --> buff[1]: s4 s5 s6 s7 s12 s13 s14 s15 - CAPTURE: for (int ll=0; ll < loop_cnt; ll++) { -#pragma HLS LOOP_TRIPCOUNT min=1 max=8 - SAMPLE_IN: for (int dd=0; dd < DEPTH; dd++) { + unsigned cnt_smp = 0; + unsigned cnt_cyc = 0; + bool saw_first = 0; + TT_ADDR dd = 0; + unsigned base = word_count - DEPTH; + while (cnt_smp < word_count) { #pragma HLS pipeline II=1 + bool full = (sig_i[0].empty()==0) && (sig_i[1].empty()==0); + bool capture = (cnt_smp < base) ? 0 : 1; + if (full == 1) { + saw_first = 1; TT_SAMPLE val0[4], val1[4]; #pragma HLS array_partition variable=val0 dim=1 #pragma HLS array_partition variable=val1 dim=1 ( val0[3], val0[2], val0[1], val0[0] ) = sig_i[0].read(); ( val1[3], val1[2], val1[1], val1[0] ) = sig_i[1].read(); - if ( ll == loop_sel ) { + if (capture == 1) { buff[0][dd] = ( val1[1], val0[1], val1[0], val0[0] ); buff[1][dd] = ( val1[3], val0[3], val1[2], val0[2] ); + dd = dd + 1; } - } //dd - } // ll + cnt_smp++; + } + if (saw_first == 1) + cnt_cyc++; + } + return(cnt_cyc); } // ------------------------------------------------------------ @@ -63,16 +75,14 @@ void read_buffer( TT_DATA mem[NSTREAM*DEPTH], TT_DATA (&buff)[NSTREAM][DEPTH] ) // Wrapper // ------------------------------------------------------------ -void +unsigned pfa1008_dma_snk_wrapper( pfa1008_dma_snk::TT_DATA mem[pfa1008_dma_snk::DEPTH*pfa1008_dma_snk::NSTREAM], - int loop_sel, - int loop_cnt, + unsigned int word_count, pfa1008_dma_snk::TT_STREAM sig_i[pfa1008_dma_snk::NSTREAM] ) { #pragma HLS interface m_axi port=mem bundle=gmem offset=slave depth=DEPTH*NSTREAM #pragma HLS interface axis port=sig_i -#pragma HLS interface s_axilite port=loop_sel bundle=control -#pragma HLS interface s_axilite port=loop_cnt bundle=control +#pragma HLS interface s_axilite port=word_count bundle=control #pragma HLS interface s_axilite port=mem bundle=control #pragma HLS interface s_axilite port=return bundle=control #pragma HLS DATAFLOW @@ -80,12 +90,15 @@ pfa1008_dma_snk_wrapper( pfa1008_dma_snk::TT_DATA mem[pfa1008_dma_snk::DEPTH*pfa // Internal buffer: TT_DATA buff[NSTREAM][DEPTH]; #pragma HLS array_partition variable=buff dim=1 + unsigned cycle_count; // Front end load from DDR4 to PL BRAM: - capture_streams( buff, sig_i, loop_sel, loop_cnt ); + cycle_count = capture_streams( buff, sig_i, word_count ); // Back end transmit from PL BRAM to AIE: read_buffer( mem, buff ); + + return(cycle_count); } diff --git a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_dma_snk/pfa1008_dma_snk.h b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_dma_snk/pfa1008_dma_snk.h index 81e10d6167..0dfd8ab85f 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_dma_snk/pfa1008_dma_snk.h +++ b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_dma_snk/pfa1008_dma_snk.h @@ -23,7 +23,6 @@ namespace pfa1008_dma_snk { // Run: // Assume 312.5 MHz clock. // We have 32-bit I/O's @ 1250 MHz AIE clock or 128-bit I/O's @ 312.5 MHz -void pfa1008_dma_snk_wrapper( pfa1008_dma_snk::TT_DATA mem[pfa1008_dma_snk::NSTREAM*pfa1008_dma_snk::DEPTH], - int loop_sel, - int loop_cnt, - pfa1008_dma_snk::TT_STREAM sig_i[pfa1008_dma_snk::NSTREAM] ); +unsigned pfa1008_dma_snk_wrapper( pfa1008_dma_snk::TT_DATA mem[pfa1008_dma_snk::NSTREAM*pfa1008_dma_snk::DEPTH], + unsigned int word_count, + pfa1008_dma_snk::TT_STREAM sig_i[pfa1008_dma_snk::NSTREAM] ); diff --git a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_dma_snk/tb_wrapper.cpp b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_dma_snk/tb_wrapper.cpp index ba5cd6adc8..01d5c81213 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_dma_snk/tb_wrapper.cpp +++ b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_dma_snk/tb_wrapper.cpp @@ -26,38 +26,45 @@ int main( void ) TT_STREAM sig_i[NSTREAM]; // Configure the same as 'host.cpp' for top level application: - int loop_cnt = 4; - int loop_sel = 1; + unsigned word_count = 8*1008; // Load stimulus (in order produced by DFT): - std::minstd_rand gen; - for (int ll=0; ll < loop_cnt; ll++) { - for (int mm=0,ss=0; mm < NSTREAM*DEPTH; mm+=2) { - TT_DATA data0 = TT_DATA( gen() ); - TT_DATA data1 = TT_DATA( gen() ); - TT_SAMPLE val0[4], val1[4]; - ( val0[3], val0[2], val0[1], val0[0] ) = data0; - ( val1[3], val1[2], val1[1], val1[0] ) = data1; - if ( ll == loop_sel ) { - ddr4_g[mm+0] = ( val1[1], val0[1], val1[0], val0[0] ); - ddr4_g[mm+1] = ( val1[3], val0[3], val1[2], val0[2] ); - } - sig_i[0].write( data0 ); - sig_i[1].write( data1 ); + std::mt19937 engine(std::random_device{}()); + std::independent_bits_engine bit_engine(engine); + bit_engine.seed(1); + TT_SAMPLE val0[4]; + TT_SAMPLE val1[4]; + for (unsigned ww=0,mm=0; ww < word_count; ww++) { + TT_DATA data0; + TT_DATA data1; + for (unsigned ii=0; ii < 4; ii++) { + val0[ii] = TT_SAMPLE(bit_engine()); + val1[ii] = TT_SAMPLE(bit_engine()); } + data0 = ( val0[3], val0[2], val0[1], val0[0] ); + data1 = ( val1[3], val1[2], val1[1], val1[0] ); + if (ww >= (word_count-DEPTH)) { + ddr4_g[mm++] = ( val1[1], val0[1], val1[0], val0[0] ); + ddr4_g[mm++] = ( val1[3], val0[3], val1[2], val0[2] ); + } + sig_i[0].write( data0 ); + sig_i[1].write( data1 ); } // Run DUT: TT_DATA ddr4_o[NSTREAM*DEPTH]; - pfa1008_dma_snk_wrapper( ddr4_o, loop_sel, loop_cnt, sig_i ); + unsigned cycle_count = pfa1008_dma_snk_wrapper( ddr4_o, word_count, sig_i ); + std::cout << "cycle_count: " << cycle_count << std::endl; // Check output streams: bool flag = 0; for (int mm=0; mm < NSTREAM*DEPTH; mm++) { TT_DATA act_g = ddr4_g[mm]; TT_DATA act_o = ddr4_o[mm]; - flag |= (act_o != act_g); - cout << "mm: " << mm << " act_o: " << act_o << " act_g: " << act_g << endl; + bool flag_this = (act_o != act_g); + flag |= flag_this; + if (flag_this) + cout << "mm: " << mm << " act_o: " << act_o << " act_g: " << act_g << endl; } if ( flag == 0 ) cout << "--- PASSED ---" << endl; else cout << "*** FAILED ***" << endl; diff --git a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_dma_src/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_dma_src/Makefile index 40b20abcda..2d8dbc7129 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_dma_src/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_dma_src/Makefile @@ -5,6 +5,7 @@ # Author: Mark Rollins DO_COSIM := false +DO_OOCPAR := false ECHO := @echo KERNEL := pfa1008_dma_src_wrapper @@ -28,6 +29,8 @@ ${XO}: ${KERNEL_SRC} ifeq (${DO_COSIM},true) vitis-run --mode hls --config hls.cfg --csim --work_dir ${KERNEL} vitis-run --mode hls --config hls.cfg --cosim --work_dir ${KERNEL} +endif +ifeq (${DO_OOCPAR},true) vitis-run --mode hls --config hls.cfg --impl --work_dir ${KERNEL} endif diff --git a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_permute_i/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_permute_i/Makefile index da520f89a0..1d75eb700d 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_permute_i/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_permute_i/Makefile @@ -5,6 +5,7 @@ # Author: Mark Rollins DO_COSIM := false +DO_OOCPAR := false ECHO := @echo KERNEL := pfa1008_permute_i_wrapper @@ -28,6 +29,8 @@ ${XO}: ${KERNEL_SRC} ifeq (${DO_COSIM},true) vitis-run --mode hls --config hls.cfg --csim --work_dir ${KERNEL} vitis-run --mode hls --config hls.cfg --cosim --work_dir ${KERNEL} +endif +ifeq (${DO_OOCPAR},true) vitis-run --mode hls --config hls.cfg --impl --work_dir ${KERNEL} endif diff --git a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_permute_o/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_permute_o/Makefile index 47aef1f165..0c054bacde 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_permute_o/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/hls/pfa1008_permute_o/Makefile @@ -5,6 +5,7 @@ # Author: Mark Rollins DO_COSIM := false +DO_OOCPAR := false ECHO := @echo KERNEL := pfa1008_permute_o_wrapper @@ -28,6 +29,8 @@ ${XO}: ${KERNEL_SRC} ifeq (${DO_COSIM},true) vitis-run --mode hls --config hls.cfg --csim --work_dir ${KERNEL} vitis-run --mode hls --config hls.cfg --cosim --work_dir ${KERNEL} +endif +ifeq (${DO_OOCPAR},true) vitis-run --mode hls --config hls.cfg --impl --work_dir ${KERNEL} endif diff --git a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/ps_apps/host.cpp b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/ps_apps/host.cpp index ac14f13b54..baccb545fc 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/ps_apps/host.cpp +++ b/AI_Engine_Development/AIE/Design_Tutorials/05-Prime-Factor-FFT/ps_apps/host.cpp @@ -4,11 +4,6 @@ // // Author: Mark Rollins -#include "pfa1008_graph.h" - -// Instantiate AIE graph: -pfa1008_graph aie_dut; - #include #include #include @@ -33,8 +28,7 @@ typedef int TT_DATA; // Assume cint16 data static constexpr int32_t NUM_ITER = -1; // Let the graph run and have DMA_SNK terminate things static constexpr int32_t LOOP_CNT_I = 8; -static constexpr int32_t LOOP_CNT_O = 8; // Try to stop it early -static constexpr int32_t LOOP_SEL = 0; // ID of loop to capture by DDR SNK PL HLS block +static constexpr int32_t LOOP_CNT_O = 1; static constexpr unsigned NSTREAM_I = 2; static constexpr unsigned NSTREAM_O = 2; static constexpr unsigned DEPTH = 1008; // 8 transform x 1008-pt / 2 stream / 4 samples @ 128-bit @@ -45,6 +39,10 @@ static constexpr unsigned NUM_SAMPLES_O = DDR_WORD_DEPTH_O * 4; // 32-bit (ci static constexpr unsigned DDR_BUFFSIZE_I_BYTES = NUM_SAMPLES_I * 4; // Each sample is 4 bytes (32-bits) static constexpr unsigned DDR_BUFFSIZE_O_BYTES = NUM_SAMPLES_O * 4; // Each sample is 4 bytes (32-bits) +static constexpr double THROUGHPUT_TARGET = 2000; +static constexpr double THROUGHPUT_ERROR_LIMIT = 5; + +static unsigned int word_count = LOOP_CNT_O * DEPTH; // # of 128-bit words on each stream // ------------------------------------------------------------ // Main @@ -90,6 +88,9 @@ int main(int argc, char* argv[]) auto dma_snk = xrt::kernel(my_device, xclbin_uuid, "pfa1008_dma_snk_wrapper:{dma_snk}"); std::cout << STR_PASSED << "auto dma_snk = xrt::kernel(my_device, xclbin_uuid, \"pfa1008_dma_snk_wrapper:{dma_snk}\")" << std::endl; + auto dma_snk_ip = xrt::ip(my_device, xclbin_uuid, "pfa1008_dma_snk_wrapper:{dma_snk}"); + std::cout << STR_PASSED << "auto dma_snk_ip = xrt::ip(my_device, xclbin_uuid, \"pfa1008_dma_snk_wrapper:{dma_snk}\")" << std::endl; + xrt::run dma_src_run = xrt::run(dma_src); std::cout << STR_PASSED << "xrt::run dma_src_run = xrt::run(dma_src)" << std::endl; @@ -144,11 +145,8 @@ int main(int argc, char* argv[]) dma_snk_run.set_arg( 0, dma_snk_bo ); std::cout << STR_PASSED << "dma_snk.run.set_arg( 0, dma_snk_bo )" << std::endl; - dma_snk_run.set_arg( 1, LOOP_SEL ); - std::cout << STR_PASSED << "dma_snk_run.set_arg( 1, LOOP_SEL=" << LOOP_SEL << " )" << std::endl; - - dma_snk_run.set_arg( 2, LOOP_CNT_O ); - std::cout << STR_PASSED << "dma_snk_run.set_arg( 2, LOOP_CNT_O=" << LOOP_CNT_O << " )" << std::endl; + dma_snk_run.set_arg( 1, word_count ); + std::cout << STR_PASSED << "dma_snk_run.set_arg( 1, word_count=" << word_count << " )" << std::endl; // ------------------------------------------------------------ // Run Application @@ -168,6 +166,18 @@ int main(int argc, char* argv[]) dma_snk_run.wait(); std::cout << STR_PASSED << "dma_snk_run.wait()" << std::endl; + // ------------------------------------------------------------ + // Throughput + // ------------------------------------------------------------ + + unsigned cycle_count = dma_snk_ip.read_register(0x10); + std::cout << "cycle_count: " << cycle_count << std::endl; + double throughput_MSPS = 2.0*(4.0*word_count)/(1.0*cycle_count)*312.5; + std::cout << "Throughput (Msps): " << throughput_MSPS << " vs. Target (Msps): " << THROUGHPUT_TARGET << std::endl; + double tp_err = 100.0*abs(throughput_MSPS-THROUGHPUT_TARGET)/THROUGHPUT_TARGET; + std::cout << "Througput Error (%): " << tp_err << " vs. Error Limit (%): " << THROUGHPUT_ERROR_LIMIT << std::endl; + bool flag_t = (tp_err > THROUGHPUT_ERROR_LIMIT); + // ------------------------------------------------------------ // Retrieve Results // ------------------------------------------------------------ @@ -211,8 +221,16 @@ int main(int argc, char* argv[]) // Done: if ( flag == 0 ) + std::cout << STR_INFO << "--- REGRESSION PASSED ---" << std::endl; + else + std::cout << STR_ERROR << "*** REGRESSION FAILED ***" << std::endl; + if ( flag_t == 0 ) + std::cout << STR_INFO << "--- THROUGHPUT PASSED ---" << std::endl; + else + std::cout << STR_ERROR << "*** THROUGHPUT FAILED ***" << std::endl; + if (flag == 0 && flag_t == 0) std::cout << STR_INFO << "--- PASSED ---" << std::endl; else - std::cout << STR_INFO << "*** FAILED ***" << std::endl; - return(flag); + std::cout << STR_ERROR <<"*** FAILED ***" << std::endl; + return(flag || flag_t); } diff --git a/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/AIE/README.md b/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/AIE/README.md index 06d2a89a65..09122b127f 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/AIE/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/AIE/README.md @@ -13,7 +13,7 @@
-# 2025.1 Versal 2D-FFT Implementation Using Vitis Acceleration Library Tutorial (XD073) +# 2025.2 Versal 2D-FFT Implementation Using Vitis Acceleration Library Tutorial (XD073) ## AI Engine Implementation @@ -124,7 +124,7 @@ Each `make` step to build the design is specified in the following sections. The ### make kernels: Compiling PL Kernels -In this step, the Vitis compiler takes any Vitis compiler kernels (RTL or HLS C) in the PL region of the target platform (`xilinx_vck190_base_202510_1`) and the AI Engine kernels and graphs and compiles them into their respective XO files. The following commands compile the kernels (default `TARGET=hw_emu`, `FFT_2D_INSTS=1`, `ITER_CNT=16`, `FFT_2D_DT=0` and `FFT_2D_PT=2048`). +In this step, the Vitis compiler takes any Vitis compiler kernels (RTL or HLS C) in the PL region of the target platform (`xilinx_vck190_base_202520_1`) and the AI Engine kernels and graphs and compiles them into their respective XO files. The following commands compile the kernels (default `TARGET=hw_emu`, `FFT_2D_INSTS=1`, `ITER_CNT=16`, `FFT_2D_DT=0` and `FFT_2D_PT=2048`). ``` make kernels @@ -137,7 +137,7 @@ mkdir -p $(BUILD_TARGET_DIR); \ cd $(BUILD_TARGET_DIR); \ -v++ --target hw_emu --hls.clock 312500000:dma_hls --platform xilinx_vck190_base_202510_1 \ +v++ --target hw_emu --hls.clock 312500000:dma_hls --platform xilinx_vck190_base_202520_1 \ --save-temps --temp_dir $(BUILD_TARGET_DIR)/_x --verbose -g -c -k dma_hls -D FFT_2D_DT=0 \ $(DESIGN_REPO)/pl_src/dma_hls.cpp -o $(BUILD_TARGET_DIR)/dma_hls.hw_emu.xo ``` @@ -194,7 +194,7 @@ aiecompiler -include=$(AIE_SRC_REPO) -include=/L1/include/aie \ -include=/L2/include/aie \ -include=/L2/tests/aie/common/inc \ --verbose --Xpreproc="-DFFT2D_INSTS=1" --Xpreproc="-DMAT_ROWS=1024" --Xpreproc="-DMAT_COLS=2048" --Xpreproc="-DFFT_2D_DT=0" \ - --platform=/xilinx_vck190_base_202510_1.xpfm \ + --platform=/xilinx_vck190_base_202520_1.xpfm \ --log-level=5 --test-iterations=2 --dataflow --heapsize=7000 \ --Xchess="main:bridge.llibs=softfloat m" --workdir=Work $(AIE_SRC_REPO)/graph.cpp 2>&1 | tee -a aiecompiler.log @@ -246,7 +246,7 @@ The expanded command is as follows: ``` cd $(BUILD_TARGET_DIR); \ -v++ -l --platform xilinx_vck190_base_202510_1 --save-temps \ +v++ -l --platform xilinx_vck190_base_202520_1 --save-temps \ --temp_dir $(BUILD_TARGET_DIR)/_x --verbose -g --clock.freqHz 312500000:dma_hls_0 \ --clock.defaultTolerance 0.001 --config $(SYSTEM_CONFIGS_REPO)/x1.cfg \ --vivado.prop fileset.sim_1.xsim.simulate.log_all_signals=true \ @@ -403,7 +403,7 @@ or cp $(PROJECT_REPO)/run_script.sh $(BUILD_TARGET_DIR)/ cd$(BUILD_TARGET_DIR); \ -v++ -p -t hw --save-temps --temp_dir $(BUILD_TARGET_DIR)/_x -f xilinx_vck190_base_202510_1\ +v++ -p -t hw --save-temps --temp_dir $(BUILD_TARGET_DIR)/_x -f xilinx_vck190_base_202520_1\ --package.rootfs $(XLNX_VERSAL)/rootfs.ext4\ --package.kernel_image $(XLNX_VERSAL)/Image --package.boot_mode=sd\ --package.out_dir $(BUILD_TARGET_DIR)/package --package.image_format=ext4\ @@ -480,7 +480,7 @@ and do: When hardware emulation is launched, you see the QEMU simulator load. Wait for the autoboot countdown to go to zero. After a few minutes, the root Linux prompt comes up: ```bash -root@versal-rootfs-common-2025_1:~# +root@versal-rootfs-common-2025_2:~# ``` After the root prompt comes up, run the following commands to run the design: @@ -560,7 +560,7 @@ Transmit delay: 0 msec/char 0 msec/line **Step 7.** Power on the board. -**Step 8.** Wait until you see the `root@versal-rootfs-common-2025_1` Linux command prompt. Press **Enter** a few times to get past any `xinit` errors. +**Step 8.** Wait until you see the `root@versal-rootfs-common-2025_2` Linux command prompt. Press **Enter** a few times to get past any `xinit` errors. **Step 9.** Run the following commands in the TeraTerm terminal: @@ -1140,7 +1140,7 @@ For all applications, designers must work to predefined specifications and build #### Resource Utilization and Power -Resource utilization and power are measured using Vivado, vcdanalyze, and Xilinx Power Estimator (XPE) for AMD Versal™ (2025.1 version) tools. +Resource utilization and power are measured using Vivado, vcdanalyze, and Xilinx Power Estimator (XPE) for AMD Versal™ (2025.2 version) tools. The registers and CLB LUT utilization information can be found in the Vivado project if you perform the following steps: @@ -1179,7 +1179,7 @@ cd $(BUILD_TARGET_DIR); \ vcdanalyze --vcd x$(FFT_2D_INSTS).vcd --xpe ``` -2. If you do not already have it installed, download and install [PDM for Versal Version 2025.1](https://www.xilinx.com/products/design-tools/power-design-manager.html). For full documentation of XPE, see [this page](https://www.xilinx.com/products/design-tools/power-design-manager.html). +2. If you do not already have it installed, download and install [PDM for Versal Version 2025.2](https://www.xilinx.com/products/design-tools/power-design-manager.html). For full documentation of XPE, see [this page](https://www.xilinx.com/products/design-tools/power-design-manager.html). 3. AI Engine power comsumption and resource utilization shown in below images for the 32 x 64 point 1-instance design: ![Image of 2D-FFT AIE XPE](images/fft_2d_aie_xpe_pow.PNG) @@ -1187,39 +1187,39 @@ A summary of resource utilization and power for all variations is given in the f ##### cint16 Design | Number of Instances | FFT Configuration | Number of Compute Cores | Vector Load | Number of Active Memory Banks | Mem R/W Rate | Active AI Engine Tiles | Interconnect Load | FF (Regs) | CLB LUTS | Dynamic Power
(in W) | |:----------------:|:----------------------------:|:-----------------------:|:-----------:|:-----------------------------:|:------------:|:----------------------:|:-----------------:|:---------:|:---------:|:-------------------------:| -| 1 | 64 point
(32 x 64) | 2 | 18.81% | 28 | 9.26% | 4 | 11% | 1144 | 370 | 0.699 | -| 1 | 128 point
(64 x 128) | 2 | 34.00% | 28 | 16.49% | 4 | 11% | 1144 | 370 | 0.765 | -| 1 | 256 point
(128 x 256) | 2 | 44.09% | 28 | 20.67% | 4 | 9% | 1144 | 370 | 0.804 | -| 1 | 512 point
(256 x 512) | 2 | 58.85% | 30 | 25.30% | 4 | 9% | 1144 | 370 | 0.865 | -| 1 | 2048 point
(1024 x 2048) | 2 | 78.68% | 42 | 23.48% | 6 | 8% | 1144 | 370 | 0.985 | -| 5 | 64 point
(32 x 64) | 10 | 18.65% | 140 | 9.19% | 20 | 7% | 5691 | 1823 | 1.573 | -| 5 | 128 point
(64 x 128) | 10 | 34.00% | 140 | 16.49% | 20 | 7% | 5691 | 1823 | 1.905 | -| 5 | 256 point
(128 x 256) | 10 | 43.82% | 140 | 20.51% | 20 | 7% | 5691 | 1823 | 2.105 | -| 5 | 512 point
(256 x 512) | 10 | 58.71% | 150 | 25.19% | 20 | 7% | 5691 | 1823 | 2.412 | -| 5 | 2048 point
(1024 x 2048) | 10 | 78.55% | 210 | 23.44% | 30 | 7% | 5691 | 1823 | 3.017 | -| 10 | 64 point
(32 x 64) | 20 | 18.65% | 280 | 9.18% | 40 | 6% | 11361 | 3606 | 2.670 | -| 10 | 128 point
(64 x 128) | 20 | 34.01% | 280 | 16.49% | 40 | 7% | 11361 | 3606 | 3.333 | -| 10 | 256 point
(128 x 256) | 20 | 43.87% | 280 | 20.55% | 40 | 7% | 11361 | 3606 | 3.729 | -| 10 | 512 point
(256 x 512) | 20 | 58.64% | 300 | 25.17% | 40 | 7% | 11361 | 3606 | 4.343 | -| 10 | 2048 point
(1024 x 2048) | 20 | 78.47% | 420 | 23.43% | 60 | 6% | 11361 | 3606 | 5.542 | +| 1 | 64 point
(32 x 64) | 2 | 18.83% | 28 | 9.27% | 4 | 11% | 1144 | 370 | 0.699 | +| 1 | 128 point
(64 x 128) | 2 | 34.54% | 28 | 16.62% | 4 | 11% | 1144 | 370 | 0.768 | +| 1 | 256 point
(128 x 256) | 2 | 44.20% | 28 | 20.62% | 4 | 9% | 1144 | 370 | 0.807 | +| 1 | 512 point
(256 x 512) | 2 | 58.92% | 30 | 25.41% | 4 | 9% | 1144 | 370 | 0.865 | +| 1 | 2048 point
(1024 x 2048) | 2 | 79.00% | 42 | 23.53% | 6 | 8% | 1144 | 370 | 0.988 | +| 5 | 64 point
(32 x 64) | 10 | 18.67% | 140 | 9.47% | 20 | 7% | 5691 | 1823 | 1.574 | +| 5 | 128 point
(64 x 128) | 10 | 34.56% | 140 | 16.60% | 20 | 7% | 5691 | 1823 | 1.914 | +| 5 | 256 point
(128 x 256) | 10 | 44.25% | 140 | 20.61% | 20 | 7% | 5691 | 1823 | 2.314 | +| 5 | 512 point
(256 x 512) | 10 | 58.72% | 150 | 25.31% | 20 | 7% | 5691 | 1823 | 2.408 | +| 5 | 2048 point
(1024 x 2048) | 10 | 79.06% | 210 | 23.53% | 30 | 7% | 5691 | 1823 | 3.013 | +| 10 | 64 point
(32 x 64) | 20 | 18.67% | 280 | 9.20% | 40 | 6% | 11361 | 3606 | 2.675 | +| 10 | 128 point
(64 x 128) | 20 | 34.55% | 280 | 16.62% | 40 | 7% | 11361 | 3606 | 3.333 | +| 10 | 256 point
(128 x 256) | 20 | 44.18% | 280 | 20.59% | 40 | 7% | 11361 | 3606 | 3.740 | +| 10 | 512 point
(256 x 512) | 20 | 58.71% | 300 | 25.28% | 40 | 7% | 11361 | 3606 | 4.337 | +| 10 | 2048 point
(1024 x 2048) | 20 | 79.00% | 420 | 23.53% | 60 | 6% | 11361 | 3606 | 5.547 | ##### cfloat Design | Number of Instances | FFT Configuration | Number of Compute Cores | Vector Load | Number of Active Memory Banks | Mem R/W Rate | Active AI Engine Tiles | Interconnect Load | FF (Regs) | CLB LUTS | Dynamic Power
(in W) | |:----------------:|:----------------------------:|:-----------------------:|:-----------:|:-----------------------------:|:------------:|:----------------------:|:-----------------:|:---------:|:---------:|:-------------------------:| -| 1 | 64 point
(32 x 64) | 4 | 43.560% | 40 | 14.61% | 5 | 6% | 1136 | 363 | 0.840 | -| 1 | 128 point
(64 x 128) | 6 | 55.390% | 88 | 12.46% | 14 | 5% | 1136 | 363 | 1.170 | -| 1 | 256 point
(128 x 256) | 6 | 63.640% | 88 | 14.15% | 13 | 5% | 1136 | 363 | 1.190 | -| 1 | 512 point
(256 x 512) | 8 | 54.210% | 74 | 19.05% | 12 | 6% | 1136 | 363 | 1.252 | -| 1 | 2048 point
(1024 x 2048) | 8 | 65.840% | 130 | 12.93% | 22 | 5% | 1136 | 363 | 1.521 | -| 5 | 64 point
(32 x 64) | 20 | 43.560% | 200 | 14.61% | 36 | 6% | 5680 | 1838 | 2.422 | -| 5 | 128 point
(64 x 128) | 30 | 55.370% | 440 | 12.45% | 65 | 5% | 5680 | 1838 | 3.825 | -| 5 | 256 point
(128 x 256) | 30 | 63.610% | 440 | 14.14% | 64 | 5% | 5680 | 1838 | 4.032 | -| 5 | 512 point
(256 x 512) | 40 | 54.290% | 370 | 19.05% | 59 | 5% | 5680 | 1838 | 4.330 | -| 5 | 2048 point
(1024 x 2048) | 40 | 65.810% | 648 | 12.96% | 110 | 5% | 5680 | 1828 | 5.750 | -| 10 | 64 point
(32 x 64) | 40 | 43.560% | 400 | 14.61% | 63 | 6% | 11379 | 3657 | 4.187 | -| 10 | 128 point
(64 x 128) | 60 | 55.280% | 880 | 12.46% | 119 | 5% | 11379 | 3657 | 7.003 | -| 10 | 256 point
(128 x 256) | 60 | 63.510% | 880 | 14.13% | 123 | 5% | 11379 | 3657 | 7.492 | -| 10 | 512 point
(256 x 512) | 80 | 54.200% | 740 | 19.04% | 122 | 6% | 11379 | 3657 | 8.272 | -| 10 | 2048 point
(1024 x 2048) | 80 | 65.720% | 1278 | 13.14% | 273 | 9% | 11379 | 3657 | 12.268 | +| 1 | 64 point
(32 x 64) | 4 | 42.380% | 34 | 16.70% | 5 | 6% | 1136 | 363 | 0.836 | +| 1 | 128 point
(64 x 128) | 6 | 55.390% | 86 | 12.75% | 14 | 5% | 1136 | 363 | 1.150 | +| 1 | 256 point
(128 x 256) | 6 | 63.640% | 82 | 15.19% | 13 | 5% | 1136 | 363 | 1.192 | +| 1 | 512 point
(256 x 512) | 8 | 54.210% | 72 | 19.58% | 12 | 6% | 1136 | 363 | 1.274 | +| 1 | 2048 point
(1024 x 2048) | 8 | 65.290% | 108 | 15.55% | 22 | 5% | 1136 | 363 | 1.403 | +| 5 | 64 point
(32 x 64) | 20 | 43.370% | 170 | 16.70% | 36 | 6% | 5680 | 1838 | 2.215 | +| 5 | 128 point
(64 x 128) | 30 | 55.390% | 430 | 12.75% | 65 | 5% | 5680 | 1838 | 3.806 | +| 5 | 256 point
(128 x 256) | 30 | 63.620% | 410 | 15.18% | 64 | 5% | 5680 | 1838 | 3.990 | +| 5 | 512 point
(256 x 512) | 40 | 54.200% | 360 | 19.57% | 59 | 5% | 5680 | 1838 | 4.314 | +| 5 | 2048 point
(1024 x 2048) | 40 | 65.390% | 536 | 15.67% | 110 | 5% | 5680 | 1828 | 4.241 | +| 10 | 64 point
(32 x 64) | 40 | 42.370% | 340 | 16.70% | 63 | 6% | 11379 | 3657 | 3.916 | +| 10 | 128 point
(64 x 128) | 60 | 54.930% | 860 | 12.63% | 119 | 5% | 11379 | 3657 | 7.034 | +| 10 | 256 point
(128 x 256) | 60 | 63.500% | 820 | 15.15% | 123 | 5% | 11379 | 3657 | 7.410 | +| 10 | 512 point
(256 x 512) | 80 | 54.430% | 720 | 19.66% | 122 | 6% | 11379 | 3657 | 8.088 | +| 10 | 2048 point
(1024 x 2048) | 80 | 65.130% | 1070 | 15.69% | 273 | 9% | 11379 | 3657 | 11.202 | *Note: The vector load, Number of memory banks and Memory R/w Rate are measured from script based method and then imported the values manually in pdm to get the power. @@ -1227,14 +1227,14 @@ A summary of resource utilization and power for all variations is given in the f **cint16** | Number of Instances | FFT Configurations | XPE Load(in W) | HW Load(in W) | |:-----------------:|:--------------------------:|:--------------:|:-------------:| -| 10 | 512 point (256x512) | 5.384 | 4.0791 | -| 10 | 2048 point (1024x2048) | 6.612 | 4.484 | +| 10 | 512 point (256x512) | 4.337 | 4.084 | +| 10 | 2048 point (1024x2048) | 5.547 | 4.496 | **cfloat** | Number of Instances | FFT Configurations | XPE Load(in W) | HW Load(in W) | |:-----------------:|:--------------------------:|:--------------:|:-------------:| -| 10 | 512 point (256x512) | 9.32 | 6.946 | -| 10 | 2048 point (1024x2048) | 13.315 | 11.869 | +| 10 | 512 point (256x512) | 8.088 | 6.979 | +| 10 | 2048 point (1024x2048) | 11.202 | 11.768 |
@@ -1365,21 +1365,21 @@ A summary of performance per Watt for all variations is shown in the following t ##### cint16 Design | Number of Instances | FFT Configuration | Performance per Watt (in MSPS/Watt) | |:----------------:|:------------------------:|:-----------------------------------: | -| 1 | 64 point (32 x 64) | 808.141 | +| 1 | 64 point (32 x 64) | 809.2974 | | 1 | 128 point (64 x 128) | 648.626 | -| 1 | 256 point (128 x 256) | 604.805 | +| 1 | 256 point (128 x 256) | 604.056 | | 1 | 512 point (256 x 512) | 665.431 | -| 1 | 2048 point (1024 x 2048) | 630.524 | -| 5 | 64 point (32 x 64) | 1798.153 | +| 1 | 2048 point (1024 x 2048) | 629.248 | +| 5 | 64 point (32 x 64) | 1797.01 | | 5 | 128 point (64 x 128) | 1301.320 | -| 5 | 256 point (128 x 256) | 1154.164 | -| 5 | 512 point (256 x 512) | 1195.675 | -| 5 | 2048 point (1024 x 2048) | 1032.377 | -| 10 | 64 point (32 x 64) | 2118.722 | +| 5 | 256 point (128 x 256) | 1054.164 | +| 5 | 512 point (256 x 512) | 1195.178 | +| 5 | 2048 point (1024 x 2048) | 1031.692 | +| 10 | 64 point (32 x 64) | 2114.762 | | 10 | 128 point (64 x 128) | 1494.585 | | 10 | 256 point (128 x 256) | 1305.021 | -| 10 | 512 point (256 x 512) | 1328.405 | -| 10 | 2048 point (1024 x 2048) | 1121.185 | +| 10 | 512 point (256 x 512) | 1327.180 | +| 10 | 2048 point (1024 x 2048) | 1120.781 | ##### cfloat Design | Number of Instances | FFT Configuration | Performance per Watt (in MSPS/Watt) | |:----------------:|:------------------------:|:------------------------------------:| @@ -1388,12 +1388,12 @@ A summary of performance per Watt for all variations is shown in the following t | 1 | 256 point (128 x 256) | 432.856 | | 1 | 512 point (256 x 512) | 402.856 | | 1 | 2048 point (1024 x 2048) | 367.337 | -| 5 | 64 point (32 x 64) | 1171.093 | +| 5 | 64 point (32 x 64) | 1170.564 | | 5 | 128 point (64 x 128) | 680.154 | | 5 | 256 point (128 x 256) | 646.572 | | 5 | 512 point (256 x 512) | 594.852 | | 5 | 2048 point (1024 x 2048) | 607.610 | -| 10 | 64 point (32 x 64) | 1324.54 | +| 10 | 64 point (32 x 64) | 1324.208 | | 10 | 128 point (64 x 128) | 736.0448 | | 10 | 256 point (128 x 256) | 696.308 | | 10 | 512 point (256 x 512) | 634.567 | @@ -1412,39 +1412,39 @@ A consolidated summary of observations for all the point sizes and all the corre | FFT Configuration - Number of Instances | Aggregate Throughput
(in MSPS)| Average Latency
(in μs) | Number of Compute Cores | Vector Load | Number of Active Memory Banks | Mem R/W Rate | FF (Regs)| CLB LUTs | Dynamic Power
(in mW) | Performance per Watt
(in MSPS/Watt) | |:---------------------------------------:|:---------------------------------:|:---------------------------:|:-----------------------:|:-----------:|:-----------------------------:|:------------:|:--------:|:--------:|:-------------------------:|:---------------------------------------:| -| 64 point
(32 x 64)
- x1 | 565.698 | 12.656 | 2 | 18.81% | 28 | 9.23% | 1144 | 370 | 0.700 | 808.141 | -| 128 point
(64 x 128)
- x1 | 498.1453 | 23.020 | 2 | 34.55% | 28 | 16.61% | 1144 | 370 | 0.768 | 648.626 | -| 256 point
(128 x 256)
- x1 | 488.078 | 63.488 | 2 | 44.24% | 28 | 20.65% | 1144 | 370 | 0.807 | 604.805 | -| 512 point
(256 x 512)
- x1 | 575.579 | 228.675 | 2 | 58.60% | 30 | 25.29% | 1144 | 370 | 0.865 | 665.431 | -| 2048 point
(1024 x 2048)
- x1 | 621.697 | 3544.131 | 2 | 78.49% | 42 | 23.42% | 1144 | 370 | 0.986 | 630.524 | -| 64 point
(32 x 64)
- x5 | 2828.495 | 12.656 | 10 | 18.65% | 140 | 9.17% | 5691 | 1823 | 1.573 | 1798.153 | -| 128 point
(64 x 128)
- x5 | 2490.727 | 23.020 | 10 | 34.54% | 140 | 16.60% | 5691 | 1823 | 1.914 | 1301.320 | +| 64 point
(32 x 64)
- x1 | 565.698 | 12.656 | 2 | 18.83% | 28 | 9.27% | 1144 | 370 | 0.699 | 808.141 | +| 128 point
(64 x 128)
- x1 | 498.1453 | 23.020 | 2 | 34.54% | 28 | 16.62% | 1144 | 370 | 0.768 | 648.626 | +| 256 point
(128 x 256)
- x1 | 488.078 | 63.488 | 2 | 44.20% | 28 | 20.62% | 1144 | 370 | 0.808 | 604.805 | +| 512 point
(256 x 512)
- x1 | 575.579 | 228.675 | 2 | 58.92% | 30 | 25.41% | 1144 | 370 | 0.868 | 665.431 | +| 2048 point
(1024 x 2048)
- x1 | 621.697 | 3544.131 | 2 | 79.00% | 42 | 23.53% | 1144 | 370 | 0.988 | 630.524 | +| 64 point
(32 x 64)
- x5 | 2828.495 | 12.656 | 10 | 18.67% | 140 | 9.20% | 5691 | 1823 | 1.574 | 1798.153 | +| 128 point
(64 x 128)
- x5 | 2490.727 | 23.020 | 10 | 34.56% | 140 | 16.60% | 5691 | 1823 | 1.914 | 1301.320 | | 256 point
(128 x 256)
- x5 | 2440.390 | 63.488 | 10 | 44.25% | 140 | 20.61% | 5691 | 1823 | 2.315 | 1054.164 | -| 512 point
(256 x 512)
- x5 | 2877.990 | 228.675 | 10 | 58.32% | 150 | 25.16% | 5691 | 1823 | 2.407 | 1195.675 | -| 2048 point
(1024 x 2048)
- x5 | 3108.487 | 3544.131 | 10 | 78.58% | 210 | 23.44% | 5691 | 1823 | 3.011 | 1032.377 | -| 64 point
(32 x 64)
- x10 | 5656.989 | 12.656 | 20 | 18.64% | 280 | 9.16% | 11361 | 3606 | 2.670 | 2118.722 | -| 128 point
(64 x 128)
- x10 | 4981.453 | 23.020 | 20 | 34.54% | 280 | 16.62% | 11361 | 3606 | 3.333 | 1494.585 | -| 256 point
(128 x 256)
- x10 | 4880.780 | 63.488 | 20 | 44.19% | 280 | 20.60% | 11361 | 3606 | 3.740 | 1305.021 | -| 512 point
(256 x 512)
- x10 | 5755.979 | 228.675 | 20 | 58.34% | 300 | 25.15% | 11361 | 3606 | 4.333 | 1328.405 | -| 2048 point
(1024 x 2048)
- x10 | 6216.973 | 3544.131 | 20 | 78.50% | 420 | 23.42% | 11361 | 3606 | 5.545 | 1121.185 | +| 512 point
(256 x 512)
- x5 | 2877.990 | 228.675 | 10 | 58.72% | 150 | 25.31% | 5691 | 1823 | 2.408 | 1195.675 | +| 2048 point
(1024 x 2048)
- x5 | 3108.487 | 3544.131 | 10 | 79.06% | 210 | 23.53% | 5691 | 1823 | 3.013 | 1032.377 | +| 64 point
(32 x 64)
- x10 | 5656.989 | 12.656 | 20 | 18.67% | 280 | 9.20% | 11361 | 3606 | 2.675 | 2118.722 | +| 128 point
(64 x 128)
- x10 | 4981.453 | 23.020 | 20 | 34.55% | 280 | 16.62% | 11361 | 3606 | 3.333 | 1494.585 | +| 256 point
(128 x 256)
- x10 | 4880.780 | 63.488 | 20 | 44.17% | 280 | 20.59% | 11361 | 3606 | 3.740 | 1305.021 | +| 512 point
(256 x 512)
- x10 | 5755.979 | 228.675 | 20 | 58.71% | 300 | 25.28% | 11361 | 3606 | 4.337 | 1328.405 | +| 2048 point
(1024 x 2048)
- x10 | 6216.973 | 3544.131 | 20 | 79.00% | 420 | 23.53% | 11361 | 3606 | 5.547 | 1121.185 | ##### cfloat Design | FFT Configuration - Number of Instances | Aggregate Throughput
(in MSPS) | Average Latency
(in μs) | Number of Compute Cores | Vector Load | Number of Active Memory Banks | Mem R/W Rate | FF (Regs)| CLB LUTs | Dynamic Power
(in mW) | Performance per Watt
(in MSPS/Watt) | |:---------------------------------------:|:----------------------------------:|:---------------------------:|:--------------------:|:-----------:|:--------------------------:|:------------:|:--------:|:--------:|:-------------------------:|:---------------------------------------:| -| 64 point
(32 x 64)
- x1 | 518.559 | 22.208 | 4 | 42.00% | 34 | 16.55% |1136 | 363 | 0.835 |621.029 | +| 64 point
(32 x 64)
- x1 | 518.559 | 22.208 | 4 | 42.38% | 34 | 16.70% |1136 | 363 | 0.836 |621.029 | | 128 point
(64 x 128)
- x1 | 517.733 | 45.328 | 6 | 55.390% | 86 | 12.75% |1136 | 363 | 1.150 |450.203 | | 256 point
(128 x 256)
- x1 | 515.964 | 94.608 | 6 | 63.640% | 82 | 15.19% |1136 | 363 | 1.192 |432.856 | | 512 point
(256 x 512)
- x1 | 513.238 | 272.108 | 8 | 54.210% | 72 | 19.58% |1136 | 363 | 1.274 |402.856 | | 2048 point
(1024 x 2048)
- x1 | 515.375 | 4235.414 | 8 | 65.290% | 108 | 15.55% |1136 | 363 | 1.403 |367.337 | -| 64 point
(32 x 64)
- x5 | 2592.799 | 22.208 | 20 | 42.00% | 170 | 16.55% |5680 | 1826 | 2.214 |1171.093 | +| 64 point
(32 x 64)
- x5 | 2592.799 | 22.208 | 20 | 42.37% | 170 | 16.70% |5680 | 1826 | 2.215 |1171.093 | | 128 point
(64 x 128)
- x5 | 2588.670 | 45.328 | 30 | 55.390% | 430 | 12.75% |5680 | 1826 | 3.806 |680.154 | | 256 point
(128 x 256)
- x5 | 2579.824 | 94.608 | 30 | 63.620% | 410 | 15.18% |5680 | 1826 | 3.990 |646.572 | | 512 point
(256 x 512)
- x5 | 2566.193 | 272.108 | 40 | 54.200% | 360 | 19.57% |5680 | 1826 | 4.314 |594.852 | -| 2048 point
(1024 x 2048)
- x5 | 2576.876 | 4235.414 | 40 | 65.330% | 536 | 15.67% |5680 | 1826 | 4.241 |607.610 | -| 64 point
(32 x 64)
- x10 | 5185.597 | 22.208 | 40 | 42.00% | 340 | 16.55% |11379 | 3657 | 3.915 |1324.54 | +| 2048 point
(1024 x 2048)
- x5 | 2576.876 | 4235.414 | 40 | 65.390% | 536 | 15.67% |5680 | 1826 | 4.241 |607.610 | +| 64 point
(32 x 64)
- x10 | 5185.597 | 22.208 | 40 | 42.37% | 340 | 16.70% |11379 | 3657 | 3.916 |1324.54 | | 128 point
(64 x 128)
- x10 | 5177.339 | 45.328 | 60 | 54.930% | 860 | 12.63% |11379 | 3657 | 7.034 |736.044 | -| 256 point
(128 x 256)
- x10 | 5159.648 | 94.608 | 60 | 63.520% | 820 | 15.16% |11379 | 3657 | 7.410 |696.308 | -| 512 point
(256 x 512)
- x10 | 5132.385 | 272.108 | 80 | 54.210% | 720 | 19.58% |11379 | 3657 | 8.088 |634.567 | +| 256 point
(128 x 256)
- x10 | 5159.648 | 94.608 | 60 | 63.500% | 820 | 15.15% |11379 | 3657 | 7.410 |696.308 | +| 512 point
(256 x 512)
- x10 | 5132.385 | 272.108 | 80 | 54.430% | 720 | 19.66% |11379 | 3657 | 8.088 |634.567 | | 2048 point
(1024 x 2048)
- x10 | 5153.751 | 4235.414 | 80 | 65.130% | 1070 | 15.69% |11379 | 3657 | 11.202 |460.074 | These observations show that with the increase in the FFT point size, the window buffer size used in the AI Engines increases, and with that, the throughput increases. Increasing the `TP_WINDOW_VSIZE` parameter in the FFT AI Engine graph can further increase the throughput, especially for the lower point sizes. Still, the AI Engine mapper/router could encounter issues due to the higher memory requirement. diff --git a/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/AIE/description.json b/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/AIE/description.json index 9718c0e0f2..436adb86d6 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/AIE/description.json +++ b/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/AIE/description.json @@ -13,8 +13,7 @@ "pre_exec": "./env_setup_versal.sh" }, "board": { - "pre_exec": "./env_setup_versal.sh", - "post_exec": "./addon/copy_perf_files.sh" + "pre_exec": "./env_setup_versal.sh" } }, "user": { @@ -51,7 +50,6 @@ "all": "run", "hw": "sd_card" }, - "custom_board_target": "run_test", - "customized_params": "multi_params.json" + "custom_board_target": "run_test" } } diff --git a/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/AIE/sample_env_setup.sh b/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/AIE/sample_env_setup.sh index a60aada818..ea3ba579d6 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/AIE/sample_env_setup.sh +++ b/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/AIE/sample_env_setup.sh @@ -6,9 +6,9 @@ # ======================================================= # Set Platform ,Vitis and Versal Image repo # ======================================================= -export PLATFORM_REPO_PATHS= -export XILINX_VITIS = /2025.1 -export COMMON_IMAGE_VERSAL= +export PLATFORM_REPO_PATHS= +export XILINX_VITIS = /2025.2 +export COMMON_IMAGE_VERSAL= # ==================================================== # Source Versal Image ,Vitis and Aietools # ==================================================== @@ -22,7 +22,7 @@ export DSPLIB_VITIS= # ========================================================= # Platform Selection... # ========================================================= -tgt_plat=xilinx_vck190_base_202510_1 +tgt_plat=xilinx_vck190_base_202520_1 export PLATFORM=$PLATFORM_REPO_PATHS/$tgt_plat/$tgt_plat\.xpfm # ========================================================== # Validating Tool Installation diff --git a/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/HLS/README.md b/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/HLS/README.md index 7dea65c448..5edea15ffb 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/HLS/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/HLS/README.md @@ -13,7 +13,7 @@ -# 2025.1 Versal 2D-FFT Implementation Using Vitis Acceleration Library Tutorial (XD073) +# 2025.2 Versal 2D-FFT Implementation Using Vitis Acceleration Library Tutorial (XD073) ## HLS Implementation @@ -123,7 +123,7 @@ Each `make` step to build the design is specified in the following sections. The ### make kernels: Compile PL Kernels -In this step, the Vitis compiler takes any V++ kernels (RTL or HLS C) in the PL region of the target platform (`xilinx_vck190_base_202510_1`) and the HLS kernels and compiles them into their respective XO files. The following commands compile the kernels ( `TARGET=hw_emu`, `FFT_2D_INSTS=1`, `ITER_CNT=16`, `FFT_2D_DT=0`, and `FFT_2D_PT=2048`). +In this step, the Vitis compiler takes any V++ kernels (RTL or HLS C) in the PL region of the target platform (`xilinx_vck190_base_202520_1`) and the HLS kernels and compiles them into their respective XO files. The following commands compile the kernels ( `TARGET=hw_emu`, `FFT_2D_INSTS=1`, `ITER_CNT=16`, `FFT_2D_DT=0`, and `FFT_2D_PT=2048`). ``` make kernels @@ -138,7 +138,7 @@ cd $(BUILD_TARGET_DIR); \ v++ --target hw_emu --hls.pre_tcl $$(DIRECTIVES_REPO)/hls_pre.tcl \ --hls.clock 500000000:fft_2d -D MAT_ROWS=1024 -D MAT_COLS=2048 -D FFT_2D_DT=0 \ - --platform xilinx_vck190_base_202510_1 --save-temps --temp_dir $(BUILD_TARGET_DIR)/_x \ + --platform xilinx_vck190_base_202520_1 --save-temps --temp_dir $(BUILD_TARGET_DIR)/_x \ --verbose -g -c -k fft_2d $(DESIGN_REPO)/pl_src/fft_2d.cpp -o $(BUILD_TARGET_DIR)/fft_2d.hw_emu.xo ``` @@ -149,7 +149,7 @@ mkdir -p $(BUILD_TARGET_DIR); \ cd $(BUILD_TARGET_DIR); \ -v++ --target hw_emu --hls.clock 250000000:dma_hls --platform xilinx_vck190_base_202510_1 \ +v++ --target hw_emu --hls.clock 250000000:dma_hls --platform xilinx_vck190_base_202520_1 \ --save-temps --temp_dir $(BUILD_TARGET_DIR)/_x --verbose -g -c -k dma_hls -D FFT_2D_DT=0 \ $(DESIGN_REPO)/pl_src/dma_hls.cpp -o $(BUILD_TARGET_DIR)/dma_hls.hw_emu.xo ``` @@ -203,7 +203,7 @@ The expanded command is as follows: ``` cd $(BUILD_TARGET_DIR); \ -v++ -l --platform xilinx_vck190_base_202510_1 --save-temps --temp_dir $(BUILD_TARGET_DIR)/_x \ +v++ -l --platform xilinx_vck190_base_202520_1 --save-temps --temp_dir $(BUILD_TARGET_DIR)/_x \ --verbose -g --clock.freqHz 500000000:fft_2d_0 --clock.freqHz 250000000:dma_hls_0 --clock.defaultTolerance 0.001 \ --advanced.param compiler.userPostSysLinkOverlayTcl=$(DIRECTIVES_REPO)/cdc_async.tcl \ --config $(SYSTEM_CONFIGS_REPO)/x1.cfg --vivado.prop fileset.sim_1.xsim.simulate.log_all_signals=true \ @@ -369,7 +369,7 @@ or cp $(PROJECT_REPO)/run_script.sh $(BUILD_TARGET_DIR)/ cd $(BUILD_TARGET_DIR); \ -v++ -p -t hw --save-temps --temp_dir $(BUILD_TARGET_DIR)/_x -f xilinx_vck190_base_202510_1 \ +v++ -p -t hw --save-temps --temp_dir $(BUILD_TARGET_DIR)/_x -f xilinx_vck190_base_202520_1 \ --package.rootfs $(XLNX_VERSAL)/rootfs.ext4 --package.kernel_image $(XLNX_VERSAL)/Image --package.boot_mode=sd \ --package.out_dir $(BUILD_TARGET_DIR)/package --package.image_format=ext4 --package.sd_file $(BUILD_TARGET_DIR)/fft_2d_hls_xrt.elf \ $(BUILD_TARGET_DIR)/vck190_hls_fft_2d.hw.xsa @@ -441,7 +441,7 @@ and do: When hardware emulation is launched, you see the QEMU simulator load. Wait for the autoboot countdown to go to zero. After a few minutes, the root Linux prompt comes up: ```bash -root@versal-rootfs-common-2025_1:~# +root@versal-rootfs-common-2025_2:~# ``` After the root prompt comes up, run the following commands to run the design: @@ -520,7 +520,7 @@ Transmit delay: 0 msec/char 0 msec/line **Step 7.** Power on the board. -**Step 8.** Wait until you see the `root@versal-rootfs-common-2025.1` Linux command prompt. Press enter a few times to get past any `xinit` errors. +**Step 8.** Wait until you see the `root@versal-rootfs-common-2025.2` Linux command prompt. Press enter a few times to get past any `xinit` errors. **Step 9.** Run the following commands in the TeraTerm terminal: diff --git a/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/HLS/description.json b/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/HLS/description.json index 93e8604cfb..8467444eef 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/HLS/description.json +++ b/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/HLS/description.json @@ -13,8 +13,7 @@ "pre_exec": "./env_setup_versal.sh" }, "board": { - "pre_exec": "./env_setup_versal.sh", - "post_exec": "./addon/copy_perf_files.sh" + "pre_exec": "./env_setup_versal.sh" } }, "user": { @@ -51,7 +50,6 @@ "all": "run", "hw": "sd_card" }, - "custom_board_target": "run_test", - "customized_params": "multi_params.json" + "custom_board_target": "run_test" } } diff --git a/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/HLS/sample_env_setup.sh b/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/HLS/sample_env_setup.sh index c3ecfde2d6..8a3fc02cac 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/HLS/sample_env_setup.sh +++ b/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/HLS/sample_env_setup.sh @@ -6,9 +6,9 @@ # ======================================================= # Set Platform ,Vitis and Versal Image repo # ======================================================= -export PLATFORM_REPO_PATHS= -export XILINX_VITIS = /2025.1 -export COMMON_IMAGE_VERSAL= +export PLATFORM_REPO_PATHS= +export XILINX_VITIS = /2025.2 +export COMMON_IMAGE_VERSAL= # ==================================================== # Source Versal Image ,Vitis and Aietools # ==================================================== @@ -19,7 +19,7 @@ source $XILINX_VITIS/settings64.sh # ========================================================= # Platform Selection... # ========================================================= -tgt_plat=xilinx_vck190_base_202510_1 +tgt_plat=xilinx_vck190_base_202520_1 export PLATFORM=$PLATFORM_REPO_PATHS/$tgt_plat/$tgt_plat\.xpfm # ========================================================== # Validating Tool Installation diff --git a/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/README.md b/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/README.md index 583285c35d..78bc36cceb 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/06-fft2d_AIEvsHLS/README.md @@ -15,7 +15,7 @@ # Versal 2D-FFT Implementation Using Vitis Acceleration Library Tutorial (XD073) -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents @@ -146,7 +146,7 @@ fft2d_AIEvsHLS * [AM011 AI Engine Architecture Manual](https://docs.amd.com/r/en-US/am011-versal-acap-trm) -* [Versal ACAP AI Engines for Dummies](https://forums.xilinx.com/t5/Design-and-Debug-Techniques-Blog/Versal-ACAP-AI-Engines-for-Dummies/ba-p/1132493) +* [Versal adaptive SoC AI Engines for Dummies](https://forums.xilinx.com/t5/Design-and-Debug-Techniques-Blog/Versal-ACAP-AI-Engines-for-Dummies/ba-p/1132493) @@ -203,8 +203,8 @@ The script sets up the environment variables and sources scripts explained below 1. The `PLATFORM_REPO_PATHS` environment variable is based on where you downloaded the platform. 2. The `XILINX_TOOLS_LOCATION` path to the Xilinx tools is used to source the `settings64.sh` script. -3. The `XLNX_VERSAL` path to the `xilinx-versal-common-v2025.1` directory is used in the step below. -4. The platform is set up by running the `xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux` script as provided in the platform download. This script sets up the `SDKTARGETSYSROOT` and `CXX` variables. If the script is not present, you _must_ run the `xilinx-versal-common-v2025.1/sdk.sh` script. +3. The `XLNX_VERSAL` path to the `xilinx-versal-common-v2025.2` directory is used in the step below. +4. The platform is set up by running the `xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux` script as provided in the platform download. This script sets up the `SDKTARGETSYSROOT` and `CXX` variables. If the script is not present, you _must_ run the `xilinx-versal-common-v2025.2/sdk.sh` script. 5. `DSPLIB_ROOT` is the path to the downloaded Vitis DSP Libraries. This is only required for the AI Engine implementation. 6. In the script, you can optionally set up an `XRT_ROOT` environment variable, pointing to XRT - RPMs, which can be packaged in the Vitis compiler packaging step. If not set up, this environment variable is automatically excluded from packaging. 7. The script also sets up the `PLATFORM` variable pointing to the required `.xpfm` file of the target platform set by the variable `tgt_plat`. @@ -232,7 +232,7 @@ platforminfo --list | grep -m 1 -A 9 vck190 The output of the above command should be as follows: ```bash - "baseName": "xilinx_vck190_base_202510_1", + "baseName": "xilinx_vck190_base_202520_1", "version": "1.0", "type": "sdsoc", "dataCenter": "false", @@ -258,7 +258,7 @@ The following table compares a 1024 x 2048 point 10-instance FFT-2D design imple | Design Target | Aggregate Throughput
(in MSPS) | Average Latency (in μs) | AIE Vector Cores | AIE Vector Load | Active Mem Banks /
Mem R/W Rate | Active AIE Tiles | FF (Regs) /
CLB LUTs | BRAMs | DSPs | Dynamic Power
(in W) | Performance per Watt
(in MSPS/Watt) | |:-------------:|:----------------------------------:|:-----------------------:|:----------------:|:---------------:|:------------------------------------:|:----------------:|:-------------------------:|:-----:|:----:|:-------------------------:|:---------------------------------------:| -| AIE | 6216.973 | 3537.296 | 20 | 78.47% | 420 /
44% | 60 | 11360 /
3647 | 0 | 0 | 5.545 | 1121.185 | +| AIE | 6216.973 | 3537.296 | 20 | 79.00% | 420 /
44% | 60 | 11360 /
3647 | 0 | 0 | 5.547 | 1121.185 | | HLS | 6277.483 | 4211.296 | NA | NA | NA | NA | 88447 /
56429 | 250 | 180 | 6.819 | 920.587051 | These observations give a clear indication of where the AI Engines in Versal can offer improvements: diff --git a/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/AIE/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/AIE/Makefile index 8bc03be46e..464ab3a898 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/AIE/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/AIE/Makefile @@ -326,8 +326,8 @@ ifeq ($(EN_TRACE),1) ifeq ($(TARGET),hw) VPP_LINK_FLAGS += --profile.trace_memory DDR VPP_LINK_FLAGS += --profile.data $(DATAMOVER_KERNEL_NAME):$(DATAMOVER_KERNEL_NAME)_0:all - VPP_LINK_FLAGS += --profile.data ai_engine_0.DataIn - VPP_LINK_FLAGS += --profile.data ai_engine_0.DataOut + VPP_LINK_FLAGS += --profile.aie ai_engine_0.DataIn + VPP_LINK_FLAGS += --profile.aie ai_engine_0.DataOut endif endif @@ -439,7 +439,7 @@ aiesim: graph aiesim_profile: graph cd $(BUILD_TARGET_DIR); \ - aiesimulator $(AIE_SIM_FLAGS)--profile 2>&1 | tee -a aiesim.log + aiesimulator $(AIE_SIM_FLAGS) --profile 2>&1 | tee -a aiesim.log @echo "" @echo "AIE Simulation, With Profiling, Complete..." @echo "####################################" diff --git a/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/AIE/README.md b/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/AIE/README.md index f601c1ea50..a7ac70c1e2 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/AIE/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/AIE/README.md @@ -139,7 +139,7 @@ The individual make steps to build the design with the options applied to them a make kernels: Compile PL Kernels ### make kernels: Compile PL Kernels -In this step, the Vitis compiler uses any kernels (RTL or HLS C) in the PL region of the target platform (`xilinx_vck190_base_202510_1`) and compiles them into their respective XO files. +In this step, the Vitis compiler uses any kernels (RTL or HLS C) in the PL region of the target platform (`xilinx_vck190_base_202520_1`) and compiles them into their respective XO files. The following command compiles the kernels (default TARGET=hw_emu, N_FIR_FILTERS=1, N_FIR_TAPS=15, FIR_WINDOW_SIZE=256, EN_TRACE=0): @@ -157,7 +157,7 @@ v++ --target hw_emu \ --hls.clock 300000000:datamover \ -D N_FIR_TAPS=$(N_FIR_TAPS) \ -D N_FIR_FILTERS=$(N_FIR_FILTERS) \ - --platform xilinx_vck190_base_202510_1 \ + --platform xilinx_vck190_base_202520_1 \ --save-temps \ --temp_dir build/fir_$(N_FIR_TAPS)_taps/x$(N_FIR_FILTERS)_firs/winSz_$(FIR_WINDOW_SIZE)/x$(N_AIE_PER_FIR)_aie_per_fir/hw_emu/_x \ --verbose \ @@ -215,7 +215,7 @@ aiecompiler -include=$(DSPLIB_ROOT)/L1/src/aie \ -include=$(DSPLIB_ROOT)/L1/include/aie \ -include=$(DSPLIB_ROOT)/L2/include/aie \ -include=design/aie_src \ - --platform=$(PLATFORM_REPO_PATHS)/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm \ + --platform=$(PLATFORM_REPO_PATHS)/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm \ --workdir=Work \ --Xpreproc="-DITER_CNT=$(ITER_CNT)" \ --Xpreproc="-DN_FIR_FILTERS=$(N_FIR_FILTERS)" \ @@ -277,7 +277,7 @@ The expanded command is as follows: cd build/fir_$(N_FIR_TAPS)_taps/x$(N_FIR_FILTERS)_firs/winSz_$(FIR_WINDOW_SIZE)/x$(N_AIE_PER_FIR)_aie_per_fir/hw_emu v++ -l \ - --platform xilinx_vck190_base_202510_1 \ + --platform xilinx_vck190_base_202520_1 \ --save-temps \ --temp_dir build/fir_$(N_FIR_TAPS)_taps/x$(N_FIR_FILTERS)_firs/winSz_$(FIR_WINDOW_SIZE)/x$(N_AIE_PER_FIR)_aie_per_fir/hw_emu/_x \ --verbose \ @@ -461,7 +461,7 @@ v++ -p \ -t hw_emu \ --save-temps \ --temp_dir build/fir_$(N_FIR_TAPS)_taps/x$(N_FIR_FILTERS)_firs/winSz_$(FIR_WINDOW_SIZE)/x$(N_AIE_PER_FIR)_aie_per_fir/hw_emu/_x \ - -f xilinx_vck190_base_202510_1 \ + -f xilinx_vck190_base_202520_1 \ --package.sd_dir $(XRT_ROOT) \ --package.rootfs $(COMMON_IMAGE_VERSAL)/rootfs.ext4 \ --package.kernel_image $(COMMON_IMAGE_VERSAL)/Image \ @@ -530,12 +530,12 @@ cd build/fir_$(N_FIR_TAPS)_taps/x$(N_FIR_FILTERS)_firs/winSz_$(FIR_WINDOW_SIZE)/ ``` When launched, the QEMU simulator loads. Wait for the autoboot countdown to go to zero, and after a few minutes, you will see the root Linux prompt comes up. ```bash -root@versal-rootfs-common-2025_1:~# +root@versal-rootfs-common-2025_2:~# ``` In some cases, the following error might come up on the screen: ``` -root@versal-rootfs-common-2025_1:~## xinit: giving up +root@versal-rootfs-common-2025_2:~## xinit: giving up xinit: unable to connect to X server: Connection refused xinit: server error Enabling notebook extension jupyter-js-widgets/extension... @@ -619,7 +619,7 @@ Transmit delay: 0 msec/char 0 msec/line **Step 7.** Power ON the board. -**Step 8.** Wait until you see the `root@versal-rootfs-common-2025_1` Linux command prompt. Press enter a few times to get past any `xinit` errors. +**Step 8.** Wait until you see the `root@versal-rootfs-common-2025_2` Linux command prompt. Press enter a few times to get past any `xinit` errors. **Step 9.** Run the following commands into the TeraTerm terminal: ``` diff --git a/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/AIE/description.json b/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/AIE/description.json index db2306901f..1bacfbdd10 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/AIE/description.json +++ b/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/AIE/description.json @@ -13,8 +13,7 @@ "pre_exec": "./env_setup_versal.sh" }, "board": { - "pre_exec": "./env_setup_versal.sh", - "post_exec": "./addon/copy_perf_files.sh" + "pre_exec": "./env_setup_versal.sh" } }, "user": { @@ -51,7 +50,6 @@ "all": "run", "hw": "sd_card" }, - "custom_board_target": "run_test", - "customized_params": "multi_params.json" + "custom_board_target": "run_test" } } diff --git a/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/AIE/sample_env_setup.sh b/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/AIE/sample_env_setup.sh index 3eac35cbef..887ad5548c 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/AIE/sample_env_setup.sh +++ b/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/AIE/sample_env_setup.sh @@ -5,9 +5,9 @@ # Set Platform ,Vitis and Versal Image repo # ======================================================= -export PLATFORM_REPO_PATHS= -export XILINX_VITIS = /2025.1 -export COMMON_IMAGE_VERSAL= +export PLATFORM_REPO_PATHS= +export XILINX_VITIS = /2025.2 +export COMMON_IMAGE_VERSAL= # ==================================================== # Source Versal Image ,Vitis and Aietools # ==================================================== @@ -21,7 +21,7 @@ export DSPLIB_VITIS= # ========================================================= # Platform Selection... # ========================================================= -tgt_plat=xilinx_vck190_base_202510_1 +tgt_plat=xilinx_vck190_base_202520_1 export PLATFORM=$PLATFORM_REPO_PATHS/$tgt_plat/$tgt_plat\.xpfm # ========================================================== # Validating Tool Installation diff --git a/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/HLS/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/HLS/Makefile index 0d3d2db468..33337b9925 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/HLS/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/HLS/Makefile @@ -360,7 +360,7 @@ VPP_LINK_FLAGS += --advanced.param compiler.userPostSysLinkOverlayTcl=$(DIRECTIV ##VPP_LINK_FLAGS += --vivado.impl.lsf '{bsub -R "select[type=X86_64] rusage[mem=65536]" -N -q medium}' #VPP_LINK_FLAGS += --advanced.param "compiler.enableMultiStrategies=1" #VPP_LINK_FLAGS += --advanced.param "compiler.multiStrategiesWaitOnAllRuns=1" -VPP_LINK_FLAGS += --vivado.synth.jobs 32 +VPP_LINK_FLAGS += --vivado.synth.jobs 8 VPP_LINK_FLAGS += --vivado.impl.jobs 8 # ========================================================= diff --git a/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/HLS/README.md b/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/HLS/README.md index d76b8bf5ba..84c6949361 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/HLS/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/HLS/README.md @@ -118,7 +118,7 @@ The individual make steps to build the design with the options that applied to t make kernels: Compile PL Kernels ### make kernels: Compile PL Kernels -In this step, the Vitis compiler takes any kernels (RTL or HLS C) in the PL region of the target platform (`xilinx_vck190_base_202510_1`) and compiles them into their respective XO files. +In this step, the Vitis compiler takes any kernels (RTL or HLS C) in the PL region of the target platform (`xilinx_vck190_base_202520_1`) and compiles them into their respective XO files. The following commands compiles the kernels (default TARGET=hw_emu, N_FIR_FILTERS=1, N_FIR_TAPS=15, EN_TRACE=0): @@ -137,7 +137,7 @@ v++ --target hw_emu \ --hls.clock 500000000:fir_hls \ -D N_FIR_FILTERS=$(N_FIR_FILTERS) \ -D N_FIR_TAPS=$(N_FIR_TAPS) \ - --platform xilinx_vck190_base_202510_1 \ + --platform xilinx_vck190_base_202520_1 \ --include design/pl_src \ --save-temps \ --temp_dir build/fir_$(N_FIR_TAPS)_taps/x$(N_FIR_FILTERS)_firs/hw_emu/_x \ @@ -151,7 +151,7 @@ v++ --target hw_emu \ --hls.clock 300000000:datamover \ -D N_FIR_FILTERS=$(N_FIR_FILTERS) \ -D N_FIR_TAPS=$(N_FIR_TAPS) \ - --platform xilinx_vck190_base_202510_1 \ + --platform xilinx_vck190_base_202520_1 \ --include design/pl_src \ --save-temps \ --temp_dir build/fir_$(N_FIR_TAPS)_taps/x$(N_FIR_FILTERS)_firs/hw_emu/_x \ @@ -210,7 +210,7 @@ The expanded command is as follows: cd build/fir_$(N_FIR_TAPS)_taps/x$(N_FIR_FILTERS)_firs/hw_emu v++ -l \ - --platform xilinx_vck190_base_202510_1 \ + --platform xilinx_vck190_base_202520_1 \ --include design/pl_src \ --save-temps \ --temp_dir build/fir_$(N_FIR_TAPS)_taps/x$(N_FIR_FILTERS)_firs/hw_emu/_x \ @@ -356,7 +356,7 @@ v++ -p \ -t hw_emu \ --save-temps \ --temp_dir build/fir_$(N_FIR_TAPS)_taps/x$(N_FIR_FILTERS)_firs/hw_emu/_x \ - -f xilinx_vck190_base_202510_1 \ + -f xilinx_vck190_base_202520_1 \ --package.rootfs $(COMMON_IMAGE_VERSAL)/rootfs.ext4 \ --package.kernel_image $(COMMON_IMAGE_VERSAL)/Image \ --package.boot_mode=sd \ @@ -421,12 +421,12 @@ cd build/fir_$(N_FIR_TAPS)_taps/x$(N_FIR_FILTERS)_firs/hw_emu/package ``` When launched, you will see the QEMU simulator load. Wait for the autoboot countdown to go to zero, and after a few minutes, you will see the root Linux prompt come up: ```bash -root@versal-rootfs-common-2025_1:~# +root@versal-rootfs-common-2025_2:~# ``` In some cases, the following error might come up on the screen: ``` -root@versal-rootfs-common-2025_1:~## xinit: giving up +root@versal-rootfs-common-2025_2:~## xinit: giving up xinit: unable to connect to X server: Connection refused xinit: server error Enabling notebook extension jupyter-js-widgets/extension... @@ -502,7 +502,7 @@ Transmit delay: 0 msec/char 0 msec/line **Step 7.** Power ON the board. -**Step 8.** Wait until you see the `root@versal-rootfs-common-2025_1` Linux command prompt. Press enter a few times to get past any `xinit` errors. +**Step 8.** Wait until you see the `root@versal-rootfs-common-2025_2` Linux command prompt. Press enter a few times to get past any `xinit` errors. **Step 9.** Run the following commands into the TeraTerm terminal: ``` diff --git a/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/HLS/description.json b/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/HLS/description.json index a01804a759..997d2ceccb 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/HLS/description.json +++ b/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/HLS/description.json @@ -10,11 +10,11 @@ "test_name": "AIE_D_07-FIR_HLS", "tasks": { "build": { - "pre_exec": "./env_setup_versal.sh" + "pre_exec": "./env_setup_versal.sh", + "level": 14 }, "board": { - "pre_exec": "./env_setup_versal.sh", - "post_exec": "./addon/copy_perf_files.sh" + "pre_exec": "./env_setup_versal.sh" } }, "user": { @@ -31,9 +31,9 @@ "max_time_min": { "vitis_aie_sim": 50, "vitis_aie_x86sim": 50, - "vitis_hw_build": 500, + "vitis_hw_build": 900, "vitis_hw_emu": 200, - "vitis_hw_run": 90 + "vitis_hw_run": 600 } } ], @@ -51,7 +51,6 @@ "all": "run", "hw": "sd_card" }, - "custom_board_target": "run_test", - "customized_params": "multi_params.json" + "custom_board_target": "run_test" } } diff --git a/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/HLS/sample_env_setup.sh b/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/HLS/sample_env_setup.sh index 1a793dbb49..7547d2030b 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/HLS/sample_env_setup.sh +++ b/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/HLS/sample_env_setup.sh @@ -6,10 +6,10 @@ # ======================================================= # Set Platform ,Vitis and Versal Image repo # ======================================================= -export PLATFORM_REPO_PATHS= -export XILINX_VITIS = /2025.1 -export COMMON_IMAGE_VERSAL= -export DSPLIBS_VITIS= +export PLATFORM_REPO_PATHS= +export XILINX_VITIS = /2025.2 +export COMMON_IMAGE_VERSAL= +export DSPLIBS_VITIS= # ==================================================== # Source Versal Image ,Vitis and Aietools # ==================================================== @@ -19,7 +19,7 @@ source $XILINX_VITIS/settings64.sh # ========================================================= # Platform Selection... # ========================================================= -tgt_plat=xilinx_vck190_base_202510_1 +tgt_plat=xilinx_vck190_base_202520_1 export PLATFORM=$PLATFORM_REPO_PATHS/$tgt_plat/$tgt_plat\.xpfm # ========================================================== # Validating Tool Installation diff --git a/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/README.md b/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/README.md index d8f8c50b12..df8780e027 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/07-firFilter_AIEvsHLS/README.md @@ -15,7 +15,7 @@ # Versal AI Engine/HLS FIR Filter Tutorial -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents [Introduction](#introduction) @@ -36,7 +36,7 @@ Versal™ adaptive SoCs combine programmable logic (PL), processing system (PS), and AI Engines with leading-edge memory and interfacing technologies to deliver powerful heterogeneous acceleration for any application. The hardware and software are targeted for programming and optimization by data scientists and software and hardware developers. A host of tools, software, libraries, IP, middleware, and frameworks enable Versal adaptive SoCs to support all industry-standard design flows. -This tutorial is one of the several to perform two implementations of a system-level design using AI Engines and HLS with DSP Engines in the Versal device plus PL including LUTs, flip-flops (FFs), and block RAMs. In each implementation, the tutorial takes you through hardware emulation and hardware flow in the context of a complete Versal ACAP system design. A Makefile is provided with each tutorial for additional customisation. +This tutorial is one of the several to perform two implementations of a system-level design using AI Engines and HLS with DSP Engines in the Versal device plus PL including LUTs, flip-flops (FFs), and block RAMs. In each implementation, the tutorial takes you through hardware emulation and hardware flow in the context of a complete Versal adaptive SoC system design. A Makefile is provided with each tutorial for additional customisation. An important goal and criteria of this tutorial is the use of C++ based kernels for AI Engine and HLS library kernels for DSP Engine and data movers. The use of AMD Vitis™ application acceleration development flow and library kernels is illustrated throughout the tutorial to demonstrate the ease of kernel integration and scalability in a system design. In the Vitis application acceleration development flow, the Vitis HLS tool automates much of the code modifications required to implement and optimize the C/C++ code in PL, including the ease of data mover kernel coding. The inference of required pragmas to produce the right interface for user's function arguments and to pipeline loops and functions is the foundation of the Vitis HLS in the application acceleration flow. Vitis HLS also supports customization of your code to implement different interface standards or specific optimizations to achieve design objectives, enable scaling, and leverage automation.Note: Alternative design methods to Vitis HLS may increase PL based performance. For example, using LogiCORE™ FIR Compiler IP and RTL based data movers could increase raw performance but will increase dynamic power and design time. @@ -126,7 +126,7 @@ filter_AIEvsHLS * [AM009 AI Engine Architecture Manual](https://docs.amd.com/r/en-US/am009-versal-ai-engine/Revision-History) -* [Versal ACAP AI Engines for Dummies](https://forums.xilinx.com/t5/Design-and-Debug-Techniques-Blog/Versal-ACAP-AI-Engines-for-Dummies/ba-p/1132493) +* [Versal adaptive SoC AI Engines for Dummies](https://forums.xilinx.com/t5/Design-and-Debug-Techniques-Blog/Versal-ACAP-AI-Engines-for-Dummies/ba-p/1132493) ### *Tools Documentation: @@ -141,11 +141,11 @@ filter_AIEvsHLS To build and run the FIR filter tutorial (AI Engine and DSP implementations), install the following tools. -* Install the [Vitis Software Platform 2025.1](https://docs.amd.com/r/en-US/ug1701-vitis-accelerated-embedded/Vitis-Software-Platform-Installation) +* Install the [Vitis Software Platform 2025.2](https://docs.amd.com/r/en-US/ug1701-vitis-accelerated-embedded/Vitis-Software-Platform-Installation) * Obtain licenses for AI Engine tools -* Download and set up the [VCK190 Vitis Platform for 2025.1](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html) +* Download and set up the [VCK190 Vitis Platform for 2025.2](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html) * [DSP Library (DSPLib) Documentation](https://docs.amd.com/r/en-US/Vitis_Libraries/dsp/index.html) @@ -161,10 +161,10 @@ When the elements of the Vitis software platform are installed, update the shell Edit `sample_env_setup.sh` script with your file paths: ```bash -export PLATFORM_REPO_PATHS= -export XILINX_VITIS = /2025.1 -export COMMON_IMAGE_VERSAL= -export DSPLIBS_VITIS= +export PLATFORM_REPO_PATHS= +export XILINX_VITIS = /2025.2 +export COMMON_IMAGE_VERSAL= +export DSPLIBS_VITIS= source $COMMON_IMAGE_VERSAL/environment-setup-cortexa72-cortexa53-amd-linux source $XILINX_VITIS/settings64.sh diff --git a/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/Module_04_full_system_design/README.md b/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/Module_04_full_system_design/README.md index 43faf501a0..9192c6f37f 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/Module_04_full_system_design/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/Module_04_full_system_design/README.md @@ -24,21 +24,21 @@ or ``` v++ -l \ -t hw \ - --platform xilinx_vck190_base_202510_1 \ + --platform xilinx_vck190_base_202520_1 \ --save-temps \ -g \ --optimize 2 \ --hls.jobs 8 \ --config ./conn.cfg \ --clock.defaultFreqHz 150000000 \ - --temp_dir ./build/_x_temp.hw.xilinx_vck190_base_202510_1 \ - --report_dir ./build/reports/_build.hw.xilinx_vck190_base_202510_1/hpc \ + --temp_dir ./build/_x_temp.hw.xilinx_vck190_base_202520_1 \ + --report_dir ./build/reports/_build.hw.xilinx_vck190_base_202520_1/hpc \ --advanced.param compiler.userPostSysLinkOverlayTcl=./post_sys_link.tcl \ - -o './build/build_dir.hw.xilinx_vck190_base_202510_1/hpc.xclbin' \ - ../Module_03_pl_kernels/build/_x_temp.hw.xilinx_vck190_base_202510_1/packet_sender.xo \ - ../Module_03_pl_kernels/build/_x_temp.hw.xilinx_vck190_base_202510_1/mm2s_mp.xo \ - ../Module_03_pl_kernels/build/_x_temp.hw.xilinx_vck190_base_202510_1/packet_receiver.xo \ - ../Module_03_pl_kernels/build/_x_temp.hw.xilinx_vck190_base_202510_1/s2mm_mp.xo \ + -o './build/build_dir.hw.xilinx_vck190_base_202520_1/hpc.xclbin' \ + ../Module_03_pl_kernels/build/_x_temp.hw.xilinx_vck190_base_202520_1/packet_sender.xo \ + ../Module_03_pl_kernels/build/_x_temp.hw.xilinx_vck190_base_202520_1/mm2s_mp.xo \ + ../Module_03_pl_kernels/build/_x_temp.hw.xilinx_vck190_base_202520_1/packet_receiver.xo \ + ../Module_03_pl_kernels/build/_x_temp.hw.xilinx_vck190_base_202520_1/s2mm_mp.xo \ ../Module_02_aie/build/libadf.a ``` diff --git a/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/Module_06_sd_card_and_hw_run/README.md b/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/Module_06_sd_card_and_hw_run/README.md index 5ee99bd705..867f873def 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/Module_06_sd_card_and_hw_run/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/Module_06_sd_card_and_hw_run/README.md @@ -25,9 +25,9 @@ or ``` v++ -t hw \ - --platform xilinx_vck190_base_202510_1 \ + --platform xilinx_vck190_base_202520_1 \ --package.defer_aie_run \ - -p ../Module_04_xclbin/build/build_dir.hw.xilinx_vck190_base_202510_1/hpc.xclbin \ + -p ../Module_04_xclbin/build/build_dir.hw.xilinx_vck190_base_202520_1/hpc.xclbin \ ../Module_02_aie/build/libadf.a \ --package.out_dir ./build \ --package.rootfs $(COMMON_IMAGE_VERSAL)/rootfs.ext4 \ diff --git a/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/Module_07_results/README.md b/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/Module_07_results/README.md index 2a85668c2e..5a5d0c3915 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/Module_07_results/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/Module_07_results/README.md @@ -39,8 +39,8 @@ Following is a table comparing the executions times to simulate 12,800 particles |Name|Hardware|Algorithm|Average Execution Time for 1 Timestep (seconds)| |---|---|--|---| |Python NBody Simulator|x86 Linux Machine|O(N)|14.96| -|C++ NBody Simulator|A72 Embedded Arm Processor|O(N2)|120.552| -|AI Engine NBody Simulator|Versal AI Engine IP|O(N)|0.00809135| +|C++ NBody Simulator|A72 Embedded Arm Processor|O(N2)|121.295| +|AI Engine NBody Simulator|Versal AI Engine IP|O(N)|0.00888979| As you can see, the N-Body Simulator implemented on the AI Engine offers a x2,800 improvement over the Python O(N) implementation and a x24,800 improvement over the C++ O(N2) implementation. A vectorized C++ NBody Simulator O(N) implementation can be created with pthreads, but is left as an exercise for the user. diff --git a/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/README.md b/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/README.md index 192d477fca..b0718ce9fd 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/README.md @@ -15,7 +15,7 @@ # N-Body Simulator -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction @@ -47,7 +47,7 @@ This tutorial can be run on the [VCK190 Board](https://www.xilinx.com/products/b 2. Obtain licenses for AI Engine tools. 3. Follow the instructions for the [Vitis Software Platform Installation](https://docs.amd.com/r/en-US/ug1701-vitis-accelerated-embedded/Installing-the-Vitis-Software-Platform) and ensure you have the following tools: - * [Vitis™ Unified Software Development Platform 2025.1](https://docs.amd.com/v/u/en-US/ug1416-vitis-documentation) + * [Vitis™ Unified Software Development Platform 2025.2](https://docs.amd.com/v/u/en-US/ug1416-vitis-documentation) * [Embedded Platform VCK190 Base or VCK190 Base](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html) ### *Environment*: Setting Up Your Shell Environment @@ -67,6 +67,7 @@ source $(XILINX_VITIS)/settings64.sh source $(COMMON_IMAGE_VERSAL)/environment-setup-cortexa72-cortexa53-amd-linux ``` + 2. Source the environment script: ```bash @@ -75,7 +76,7 @@ source sample_env_setup.sh ### *Validation*: Confirming Tool Installation -Ensure you are using the 2025.1 version of the AMD tools. +Ensure you are using the 2025.2 version of the AMD tools. ```bash which vitis @@ -83,6 +84,7 @@ which aiecompiler ``` ## Goals of this Tutorial + ### HPC Applications The goal of this tutorial is to create a general-purpose floating point accelerator for HPC applications. This tutorial demonstrates a x24,800 performance improvement using the AI Engine accelerator over the naive C++ implementation on the A72 embedded Arm® processor. @@ -90,13 +92,15 @@ The goal of this tutorial is to create a general-purpose floating point accelera |Name|Hardware|Algorithm Complexity|Average Execution Time to Simulate 12,800 Particles for 1 Timestep (seconds)| |---|---|--|---| |Python N-Body Simulator|x86 Linux Machine|O(N)|14.96| -|C++ N-Body Simulator|A72 Embedded Arm Processor|O(N2)|120.552| -|AI Engine N-Body SImulator|Versal AI Engine IP|O(N)|0.00809135| +|C++ N-Body Simulator|A72 Embedded Arm Processor|O(N2)|121.295| +|AI Engine N-Body SImulator|Versal AI Engine IP|O(N)|0.00888979| ### PL Data-Mover Kernels + Another goal of this tutorial is to showcase how to generate PL Data-Mover kernels These kernels moves any amount of data from DDR buffers to AXI-Streams. ## The N-Body Problem + The N-Body problem is the problem of predicting the motions of a group of N objects which each have a gravitational force on each other. For any particle `i` in the system, the summation of the gravitational forces from all the other particles results in the acceleration of particle `i`. From this acceleration, we can calculate a particle's velocity and position (`x y z vx vy vz`) will be in the next timestep. Newtonian physics describes the behavior of very large bodies/particles within our universe. With certain assumptions, the laws can be applied to bodies/particles ranging from astronomical size to a golf ball (and even smaller). #### 12,800 Particles simulated on a 400 tile AI Engine accelerator for 300 timesteps @@ -128,6 +132,7 @@ If given an initial velocity (vt) and position (xt), we ca * Velocity Equation: vt+1=vt+a\*ts ### Gravity Equations - N Bodies + Our NBody simulator will extends the above gravity equation to calcuate positions, accelerations, and velocities in the x, y, and z directions of N bodies in a system. For the sake of simplicity in implementation, the following assumptions were made: @@ -172,13 +177,14 @@ The N-Body Simulator is implemented on an `XCVC1902 AMD Versal Adaptive SoC` dev *Note:* The entire design is a compute-bound problem, meaning we are limited to how fast the AI Engine tiles compute the floating-point gravity equations. This is not a memory-bound design. -## Where We're Headed ... +## Where We're Headed ... + Complete modules 01-07 in the following order: ### Module 01 - Python Simulations on x86 The module shows a python implementation of the N-Body Simulator and execution times to run the N-Body Simulator on an x86 machine. -[Read more ...](Module_01_python_sims) +[Read more ...](Module_01_python_sims/README.md) ### Module 02 - AI Engine Design This module presents the final 400 tile AI Engine design: @@ -188,20 +194,20 @@ This module presents the final 400 tile AI Engine design: * An N-Body System with 100 `nbody_subsystem` graphs (i.e., 400 `nbody()` kernels) which use all 400 AI Engine tile resources * Invoke the AI Engine compiler -[Read more...](Module_02_aie) - +[Read more...](Module_02_aie/README.md) + ### Module 03 - PL Kernels This modules presents the PL HLS kernels: * Create datamover PL HLS kernels from AMD Vitis Utility Library * Create and simulate packet switching PL HLS kernels -[Read more...](Module_03_pl_kernels) +[Read more...](Module_03_pl_kernels/README.md) ### Module 04 - Full System Design This module shows how to link the AI Engine design and PL kernels together into a single XCLBIN and view the actual hardware implementation Vivado™ solution. -[Read more...](Module_04_xclbin) +[Read more...](Module_04_xclbin/README.md) ### Module 05 - Host Software This module presents the host software that enables the entire design: @@ -209,7 +215,7 @@ This module presents the host software that enables the entire design: * Create a C++ N-Body Simulator to profile and compare performance between the A72 processor and AI Engine * Create a host application that runs the system design for multiple timesteps and create animation data for post-processing -[Read more...](Module_05_host_sw) +[Read more...](Module_05_host_sw/README.md) ### Module 06 - SD Card and Hardware Run This module conducts the hardware run: @@ -217,7 +223,7 @@ This module conducts the hardware run: * Execute the host applications and runs the system design on hardware * Save animation data from hardware run -[Read more...](Module_06_sd_card_and_hw_run) +[Read more...](Module_06_sd_card_and_hw_run/README.md) ### Module 07 - Results This module review the results of the hardware run: @@ -226,7 +232,7 @@ This module review the results of the hardware run: * Estimate the number of GFLOPS of the design * Explore ways to increase design bandwidth -[Read more...](Module_07_results) +[Read more...](Module_07_results/README.md) ### (Optional) x1_design and x10_design This tutorial contains 3 AI Engine designs: diff --git a/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/description.json b/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/description.json index c767451c92..a03484231f 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/description.json +++ b/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/description.json @@ -13,8 +13,7 @@ "pre_exec": "./env_setup_versal.sh" }, "board": { - "pre_exec": "./env_setup_versal.sh", - "post_exec": "./addon/copy_perf_files.sh" + "pre_exec": "./env_setup_versal.sh" } }, "user": { @@ -33,7 +32,7 @@ "vitis_aie_x86sim": 50, "vitis_hw_build": 470, "vitis_hw_emu": 470, - "vitis_hw_run": 60 + "vitis_hw_run": 600 } } ], @@ -43,10 +42,11 @@ "vitis_hw_run" ], "category": "canary", - "custom_build_target": - { - "all": "build", - "hw" : "run" - } + "custom_board_target": "run_test", + "custom_build_target": + { + "all": "build", + "hw" : "run" + } } } diff --git a/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/sample_env_setup.sh b/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/sample_env_setup.sh index 3f3566035c..787d6e92c1 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/sample_env_setup.sh +++ b/AI_Engine_Development/AIE/Design_Tutorials/08-n-body-simulator/sample_env_setup.sh @@ -6,9 +6,9 @@ # ======================================================= # Set Platform ,Vitis and Versal Image repo # ======================================================= -export PLATFORM_REPO_PATHS= -export XILINX_VITIS = /2025.1 -export COMMON_IMAGE_VERSAL= +export PLATFORM_REPO_PATHS= +export XILINX_VITIS = /2025.2 +export COMMON_IMAGE_VERSAL= # ==================================================== # Source Versal Image ,Vitis and Aietools @@ -25,7 +25,7 @@ export DSPLIB_VITIS= # ========================================================= # Platform Selection... # ========================================================= -tgt_plat=xilinx_vck190_base_202510_1 +tgt_plat=xilinx_vck190_base_202520_1 export PLATFORM=$PLATFORM_REPO_PATHS/$tgt_plat/$tgt_plat\.xpfm # ========================================================== diff --git a/AI_Engine_Development/AIE/Design_Tutorials/09-ddc_chain/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/09-ddc_chain/Makefile index 831f71a6a1..ae0f8e9d44 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/09-ddc_chain/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/09-ddc_chain/Makefile @@ -7,7 +7,7 @@ # Set COMMSLIB_ROOT to the absolute path to commslib # ######################################################################### -VERSAL_VITIS_PLATFORM = xilinx_vck190_base_202510_1 +VERSAL_VITIS_PLATFORM = xilinx_vck190_base_202520_1 VITIS_PLATFORM_DIR = ${PLATFORM_REPO_PATHS}/${VERSAL_VITIS_PLATFORM} export PLATFORM = ${VITIS_PLATFORM_DIR}/${VERSAL_VITIS_PLATFORM}.xpfm diff --git a/AI_Engine_Development/AIE/Design_Tutorials/09-ddc_chain/README.md b/AI_Engine_Development/AIE/Design_Tutorials/09-ddc_chain/README.md index ffcabdc830..fa604e1816 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/09-ddc_chain/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/09-ddc_chain/README.md @@ -15,7 +15,7 @@ # Digital Down-conversion Chain: Converting from Intrinsics to API -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents @@ -143,7 +143,7 @@ The 32-branch digital down-conversion design can be built using the command line ### Setup and Initialization -IMPORTANT: Before beginning the tutorial ensure you have installed Vitis™ 2025.1 software. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). +IMPORTANT: Before beginning the tutorial ensure you have installed Vitis™ 2025.2 software. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). Set the environment variable ```COMMON_IMAGE_VERSAL``` to the full path where you have downloaded the Common Images. Then set the environment variable ```PLATFORM_REPO_PATHS``` to the value ```$XILINX_VITIS/base_platforms```. The remaining environment variables are configured in the top level Makefile. diff --git a/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/AIE/README.md b/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/AIE/README.md index 8b755cd736..2ad979f34c 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/AIE/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/AIE/README.md @@ -1383,12 +1383,12 @@ A summary of resource utilization and power for all variations is given in the f | GeMM Configuration | Number of Compute Cores | Vector Load | Number of Active Memory Banks | Mem R/W Rate | Active AI Engine Tiles | Interconnect Load | FF (Regs) | CLB LUTS | Dynamic Power
(in mW) | |:------------------:|:-----------------------:|:-----------:|:-----------------------------:|:------------:|:----------------------:|:-----------------:|:---------:|:---------:|:-------------------------:| -| 32x32x32 | 24 | 14.54% | 231 | 3.575% | 44 | 12.87% | 13559 | 2851 | 2741 | -| 64x64x64 | 24 | 33.74% | 252 | 6.110% | 43 | 13.10% | 13563 | 2854 | 3355 | -| 128x128x128 | 24 | 36.58% | 231 | 8.905% | 43 | 13.10% | 13524 | 2842 | 3562 | -| 256x256x256 | 24 | 61.63% | 231 | 14.700% | 43 | 13.10% | 13542 | 2595 | 4426 | -| 512x512x512 | 24 | 71.40% | 252 | 12.125% | 43 | 13.41% | 13537 | 2833 | 4516 | -| 1024x1024x1024 | 24 | 82.98% | 252 | 13.960% | 43 | 12.57% | 13540 | 2834 | 4872 | +| 32x32x32 | 24 | 14.54% | 231 | 3.575% | 44 | 12.87% | 13633 | 2934 | 2741 | +| 64x64x64 | 24 | 35.53% | 252 | 6.345% | 43 | 13.10% | 13579 | 2881 | 3401 | +| 128x128x128 | 24 | 36.62% | 231 | 8.910% | 43 | 13.10% | 13507 | 3006 | 3563 | +| 256x256x256 | 24 | 61.82% | 231 | 14.725% | 43 | 13.10% | 13576 | 2880 | 4432 | +| 512x512x512 | 24 | 71.42% | 252 | 12.125% | 43 | 13.41% | 13507 | 3006 | 4524 | +| 1024x1024x1024 | 24 | 82.96% | 252 | 13.980% | 43 | 12.57% | 13540 | 2834 | 4876 | @@ -1465,8 +1465,8 @@ A summary of throughput and latency for all variations is shown in the following | GeMM Configuration | Data Transfer Size | Latency
(in μs) | Throughput
(in MSPS) | TOPs | Matrices/s
(in 10^6/s)| |:------------------:|:------------------:|:-------------------:|:-------------------------:|:------:|:-------------------------:| -| 32x32x32 | 1024 | 0.304 | 4073.595 | 0.260 | 3.9781 | -| 64x64x64 | 4096 | 0.633 | 5682.969 | 0.727 | 1.3874 | +| 32x32x32 | 1024 | 0.304 | 4076.636 | 0.260 | 3.9781 | +| 64x64x64 | 4096 | 0.633 | 5680.999 | 0.727 | 1.3874 | | 128x128x128 | 16384 | 2.371 | 2920.499 | 0.747 | 0.1782 | | 256x256x256 | 65536 | 3.180 | 2290.347 | 1.172 | 0.0349 | | 512x512x512 | 262144 | 1.782 | 1298.522 | 1.369 | 0.0049 | @@ -1510,12 +1510,12 @@ A consolidated summary of observations for all the point sizes and all the corre | GeMM Configuration | Perf
(in MSPS) | Latency
(in μs) | TOPs | No. of Compute Cores | Vector Load | No. of Active Mem Banks | Mem R/W Rate | Active AIE Tiles | Dynamic Power
(in mW) | TOPs per Watt | |:------------------:|:------------------:|:-------------------:|:-----:|:--------------------:|:-----------:|:-----------------------:|:------------:|:----------------:|:-------------------------:|:-------------:| -| 32x32x32 | 4459.930 | 0.303 | 0.260 | 24 | 14.54% | 231 | 3.575% | 44 | 2741 | 0.1022 | -| 64x64x64 | 5701.559 | 0.633 | 0.727 | 24 | 33.74% | 252 | 6.110% | 46 | 3355 | 0.2229 | -| 128x128x128 | 2920.603 | 2.3712 | 0.747 | 24 | 36.58% | 231 | 8.905% | 46 | 3562 | 0.2139 | -| 256x256x256 | 2290.395 | 3.1808 | 1.172 | 24 | 61.63% | 231 | 14.700% | 46 | 4426 | 0.2692 | -| 512x512x512 | 1337.707 | 1.782 | 1.369 | 24 | 71.40% | 252 | 12.125% | 46 | 4516 | 0.3034 | -| 1024x1024x1024 | 769.376 | 3.3312 | 1.551 | 24 | 82.98% | 252 | 13.960% | 46 | 4872 | 0.3208 | +| 32x32x32 | 4076.636 | 0.303 | 0.260 | 24 | 14.54% | 231 | 3.575% | 44 | 2741 | 0.1022 | +| 64x64x64 | 5608.999 | 0.633 | 0.727 | 24 | 35.53% | 252 | 6.345% | 46 | 3401 | 0.2229 | +| 128x128x128 | 2920.499 | 2.3712 | 0.747 | 24 | 36.62% | 231 | 8.910% | 46 | 3563 | 0.2139 | +| 256x256x256 | 2290.347 | 3.1808 | 1.172 | 24 | 61.82% | 231 | 14.725% | 46 | 4432 | 0.2692 | +| 512x512x512 | 1337.522 | 1.782 | 1.369 | 24 | 71.42% | 252 | 12.125% | 46 | 4524 | 0.3034 | +| 1024x1024x1024 | 769.482 | 3.3312 | 1.551 | 24 | 82.96% | 252 | 13.980% | 46 | 4876 | 0.3208 | User may find an a much tighter placement solution which may reduce the power consumption further and lead to a more favourable performance, as indicated by the low Vector Load. diff --git a/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/AIE/description.json b/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/AIE/description.json index e92647eb9e..3d4b699d5f 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/AIE/description.json +++ b/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/AIE/description.json @@ -13,8 +13,7 @@ "pre_exec": "./env_setup_versal.sh" }, "board": { - "pre_exec": "./env_setup_versal.sh", - "post_exec": "./addon/copy_perf_files.sh" + "pre_exec": "./env_setup_versal.sh" } }, "user": { @@ -50,7 +49,6 @@ "all": "run", "hw": "sd_card" }, - "custom_board_target": "run_test", - "customized_params": "multi_params.json" + "custom_board_target": "run_test" } } diff --git a/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/AIE/sample_env_setup.sh b/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/AIE/sample_env_setup.sh index 8f3b32faab..aa5edd154d 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/AIE/sample_env_setup.sh +++ b/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/AIE/sample_env_setup.sh @@ -6,9 +6,9 @@ # ======================================================= # Set Platform ,Vitis and Versal Image repo # ======================================================= -export PLATFORM_REPO_PATHS= -export XILINX_VITIS = /2025.1 -export COMMON_IMAGE_VERSAL= +export PLATFORM_REPO_PATHS= +export XILINX_VITIS = /2025.2 +export COMMON_IMAGE_VERSAL= # ==================================================== # Source Versal Image ,Vitis and Aietools # ==================================================== @@ -22,7 +22,7 @@ export DSPLIB_VITIS= # ========================================================= # Platform Selection... # ========================================================= -tgt_plat=xilinx_vck190_base_202510_1 +tgt_plat=xilinx_vck190_base_202520_1 export PLATFORM=$PLATFORM_REPO_PATHS/$tgt_plat/$tgt_plat\.xpfm # ========================================================== # Validating Tool Installation diff --git a/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/DSP/README.md b/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/DSP/README.md index 80675b0d28..114b16870e 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/DSP/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/DSP/README.md @@ -187,7 +187,7 @@ The expanded command is as follows: ``` cd $(BUILD_TARGET_DIR); \ -v++ -l --platform xilinx_vck190_base_202510_1 --save-temps --temp_dir $(BUILD_TARGET_DIR)/_x \ +v++ -l --platform xilinx_vck190_base_202520_1 --save-temps --temp_dir $(BUILD_TARGET_DIR)/_x \ --verbose -g --clock.freqHz 500000000:gemm_large_ocm_0 --clock.defaultTolerance 0.001 \ --config $(SYSTEM_CONFIGS_REPO)/gemm.cfg --vivado.prop fileset.sim_1.xsim.simulate.log_all_signals=true \ --vivado.prop run.synth_1.{STEPS.SYNTH_DESIGN.ARGS.CONTROL_SET_OPT_THRESHOLD}={16} \ @@ -341,7 +341,7 @@ or cp $(PROJECT_REPO)/run_script.sh $(BUILD_TARGET_DIR)/ cd $(BUILD_TARGET_DIR); \ -v++ -p -t hw --save-temps --temp_dir $(BUILD_TARGET_DIR)/_x -f xilinx_vck190_base_202510_1 \ +v++ -p -t hw --save-temps --temp_dir $(BUILD_TARGET_DIR)/_x -f xilinx_vck190_base_202520_1 \ --package.rootfs $(XLNX_VERSAL)/rootfs.ext4 --package.kernel_image $(XLNX_VERSAL)/Image --package.boot_mode=sd \ --package.out_dir $(BUILD_TARGET_DIR)/package --package.image_format=ext4 --package.sd_file $(BUILD_TARGET_DIR)/gemm_dsp_xrt.elf \ $(BUILD_TARGET_DIR)/gemm.hw.xclbin @@ -407,7 +407,7 @@ and do: When hardware emulation is launched, you see the QEMU simulator load. Wait for the autoboot countdown to go to zero. After a few minutes, the root Linux prompt comes up: ```bash -root@versal-rootfs-common-2025.1:~# +root@versal-rootfs-common-2025.2:~# ``` After the root prompt comes up, run the following commands to run the design: @@ -483,7 +483,7 @@ Transmit delay: 0 msec/char 0 msec/line **Step 7.** Power on the board. -**Step 8.** Wait until you see the `root@versal-rootfs-common-2025_1` Linux command prompt. Press enter a few times to get past any `xinit` errors. +**Step 8.** Wait until you see the `root@versal-rootfs-common-2025_2` Linux command prompt. Press enter a few times to get past any `xinit` errors. **Step 9.** Run the following commands in the TeraTerm terminal: @@ -846,7 +846,7 @@ For all applications, designers must work to predefined specifications and build ### Resource Utilization -Resource utilization and power are measured using Vivado, vcdanalyze, and Power Design Manager (PDM) for Versal (2025.1 version) tools. +Resource utilization and power are measured using Vivado, vcdanalyze, and Power Design Manager (PDM) for Versal (2025.2 version) tools. The registers, CLB LUT, BRAM, URAM and DSP Engine utilization information can be found in the Vivado project if you perform the following steps: @@ -865,9 +865,9 @@ Resource Utilization for 32x32x32 matrix is as follows - +----------------------------+-------+-------+------------+-----------+-------+ | Site Type | Used | Fixed | Prohibited | Available | Util% | +----------------------------+-------+-------+------------+-----------+-------+ -| Registers | 48108 | 4 | 0 | 1799680 | 2.88 | -| CLB LUTs | 9202 | 0 | 0 | 899840 | 1.41 | -| LOOKAHEAD8 | 139 | 0 | 0 | 112480 | 0.12 | +| Registers | 58442 | 4 | 0 | 1799680 | 2.88 | +| CLB LUTs | 14594| 0 | 0 | 899840 | 1.41 | +| LOOKAHEAD8 | 380 | 0 | 0 | 112480 | 0.12 | | RAMB36E5 | 0 | 0 | 0 | 967 | 0.00 | | URAM | 192 | 0 | 0 | 463 | 41.47 | | DSP58 | 1024 | 1024 | 0 | 1968 | 52.03 | @@ -880,8 +880,8 @@ Resource Utilization for 64x64x64 matrix is as follows - +----------------------------+-------+-------+------------+-----------+-------+ | Site Type | Used | Fixed | Prohibited | Available | Util% | +----------------------------+-------+-------+------------+-----------+-------+ -| Registers | 70862 | 9 | 0 | 1799680 | 4.15 | -| CLB LUTs | 17264 | 0 | 0 | 899840 | 2.31 | +| Registers | 71160 | 9 | 0 | 1799680 | 4.15 | +| CLB LUTs | 17283 | 0 | 0 | 899840 | 2.31 | | LOOKAHEAD8 | 651 | 0 | 0 | 112480 | 0.58 | | RAMB36E5 | 64 | 0 | 0 | 967 | 6.62 | | URAM | 192 | 0 | 0 | 463 | 41.47 | @@ -895,8 +895,8 @@ Resource Utilization for 128x128x128 matrix is as follows - +----------------------------+-------+-------+------------+-----------+-------+ | Site Type | Used | Fixed | Prohibited | Available | Util% | +----------------------------+-------+-------+------------+-----------+-------+ -| Registers | 70998 | 12 | 0 | 1799680 | 4.14 | -| CLB LUTs | 17357 | 0 | 0 | 899840 | 2.29 | +| Registers | 71022 | 12 | 0 | 1799680 | 4.14 | +| CLB LUTs | 17474 | 0 | 0 | 899840 | 2.29 | | LOOKAHEAD8 | 651 | 0 | 0 | 112480 | 0.58 | | RAMB36E5 | 64 | 0 | 0 | 967 | 6.62 | | URAM | 192 | 0 | 0 | 463 | 41.47 | @@ -910,8 +910,8 @@ Resource Utilization for 256x256x256 matrix is as follows - +----------------------------+-------+-------+------------+-----------+-------+ | Site Type | Used | Fixed | Prohibited | Available | Util% | +----------------------------+-------+-------+------------+-----------+-------+ -| Registers | 70859 | 7 | 0 | 1799680 | 4.14 | -| CLB LUTs | 17345 | 0 | 0 | 899840 | 2.31 | +| Registers | 71117 | 7 | 0 | 1799680 | 4.14 | +| CLB LUTs | 17491 | 0 | 0 | 899840 | 2.31 | | LOOKAHEAD8 | 652 | 0 | 0 | 112480 | 0.58 | | RAMB36E5 | 64 | 0 | 0 | 967 | 6.62 | | URAM | 192 | 0 | 0 | 463 | 41.47 | @@ -925,8 +925,8 @@ Resource Utilization for 512x512x512 matrix is as follows - +----------------------------+-------+-------+------------+-----------+-------+ | Site Type | Used | Fixed | Prohibited | Available | Util% | +----------------------------+-------+-------+------------+-----------+-------+ -| Registers | 67769 | 11 | 0 | 1799680 | 3.97 | -| CLB LUTs | 16285 | 0 | 0 | 899840 | 2.18 | +| Registers | 67839 | 11 | 0 | 1799680 | 3.97 | +| CLB LUTs | 16264 | 0 | 0 | 899840 | 2.18 | | LOOKAHEAD8 | 652 | 0 | 0 | 112480 | 0.58 | | RAMB36E5 | 64 | 0 | 0 | 967 | 6.62 | | URAM | 144 | 0 | 0 | 463 | 31.10 | @@ -968,12 +968,12 @@ A summary of power utilization is given in the following table +--------------------+-------------------+ | GeMM Configuration | Dynamic Power (W) | +--------------------+-------------------+ -| 32x32x32 | 8.017 | -| 64x64x64 | 8.575 | -| 128x128x128 | 8.778 | -| 256x256x256 | 8.693 | -| 512x512x512 | 8.659 | -| 1024x1024x1024 | 8.758 | +| 32x32x32 | 7.469 | +| 64x64x64 | 8.659 | +| 128x128x128 | 8.665 | +| 256x256x256 | 8.682 | +| 512x512x512 | 8.538 | +| 1024x1024x1024 | 8.682 | +--------------------+-------------------+ ``` @@ -1036,12 +1036,12 @@ TOPS and power utilization for DSP based martix multiplication is more or less i +--------------------+---------------+ | GeMM Configuration | TOPs/W | +--------------------+---------------+ -| 32x32x32 | 0.168301 | -| 64x64x64 | 0.164612 | -| 128x128x128 | 0.162999 | -| 256x256x256 | 0.164874 | -| 512x512x512 | 0.165557 | -| 1024x1024x1024 | 0.163690 | +| 32x32x32 | 0.180649 | +| 64x64x64 | 0.163015 | +| 128x128x128 | 0.165125 | +| 256x256x256 | 0.165083 | +| 512x512x512 | 0.167903 | +| 1024x1024x1024 | 0.165123 | +--------------------+---------------+ ``` @@ -1059,12 +1059,12 @@ A summary of throughput and latency for all variations is shown in the following +--------------------+-------------------+------------------+---------------+-----------+--------------------+-------------+-------------------------+--------------+------------------+--------------------+----------------+ | GeMM Configuration | perf (in MSPS) | Latency(us) | Matrices/s | TOPs | No.of Active Cores | Vector Load | No. of Active mem Banks | Mem R/W Rate | Active AIE Tiles | Dynamic Power (mW) | TOPs per Watt | +--------------------+-------------------+------------------+---------------+-----------+--------------------+-------------+-------------------------+--------------+------------------+--------------------+----------------+ -| 32x32x32 | 10541.176 | 0.097 | 10.29 x 10^6 | 1.34927 | NA | NA | NA | NA | NA | 8017 | 0.168301 | -| 64x64x64 | 11027.692 | 0.371 | 2.69 x 10^6 | 1.41154 | NA | NA | NA | NA | NA | 8575 | 0.164612 | -| 128x128x128 | 5589.083 | 2.931 | 3.41 x 10^5 | 1.43081 | NA | NA | NA | NA | NA | 8778 | 0.162999 | -| 256x256x256 | 2799.316 | 23.411 | 4.27 x 10^4 | 1.43325 | NA | NA | NA | NA | NA | 8693 | 0.164874 | -| 512x512x512 | 1399.957 | 187.25 | 5.34 x 10^3 | 1.43356 | NA | NA | NA | NA | NA | 8659 | 0.165557 | -| 1024x1024x1024 | 699.997 | 1497.9 | 6.67 x 10^2 | 1.43359 | NA | NA | NA | NA | NA | 8758 | 0.163690 | +| 32x32x32 | 10541.176 | 0.097 | 10.29 x 10^6 | 1.34927 | NA | NA | NA | NA | NA | 7469 | 0.180649 | +| 64x64x64 | 11027.692 | 0.371 | 2.69 x 10^6 | 1.41154 | NA | NA | NA | NA | NA | 8659 | 0.163015 | +| 128x128x128 | 5589.083 | 2.931 | 3.41 x 10^5 | 1.43081 | NA | NA | NA | NA | NA | 8665 | 0.165125 | +| 256x256x256 | 2799.316 | 23.411 | 4.27 x 10^4 | 1.43325 | NA | NA | NA | NA | NA | 8682 | 0.165083 | +| 512x512x512 | 1399.957 | 187.25 | 5.34 x 10^3 | 1.43356 | NA | NA | NA | NA | NA | 8538 | 0.167903 | +| 1024x1024x1024 | 699.997 | 1497.9 | 6.67 x 10^2 | 1.43359 | NA | NA | NA | NA | NA | 8682 | 0.165123 | +--------------------+-------------------+------------------+---------------+-----------+--------------------+-------------+-------------------------+--------------+------------------+--------------------+----------------+ ``` diff --git a/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/DSP/sample_env_setup.sh b/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/DSP/sample_env_setup.sh index b539a6d35a..aed873bbcb 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/DSP/sample_env_setup.sh +++ b/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/DSP/sample_env_setup.sh @@ -6,9 +6,9 @@ # ======================================================= # Set Platform ,Vitis and Versal Image repo # ======================================================= -export PLATFORM_REPO_PATHS= -export XILINX_VITIS = /2025.1 -export COMMON_IMAGE_VERSAL= +export PLATFORM_REPO_PATHS= +export XILINX_VITIS = /2025.2 +export COMMON_IMAGE_VERSAL= # ==================================================== # Source Versal Image ,Vitis and Aietools # ==================================================== @@ -19,7 +19,7 @@ source $XILINX_VITIS/settings64.sh # ========================================================= # Platform Selection... # ========================================================= -tgt_plat=xilinx_vck190_base_202510_1 +tgt_plat=xilinx_vck190_base_202520_1 export PLATFORM=$PLATFORM_REPO_PATHS/$tgt_plat/$tgt_plat\.xpfm # ========================================================== # Validating Tool Installation diff --git a/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/README.md b/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/README.md index 16e2b6fbff..39d8941bd2 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/10-GeMM_AIEvsDSP/README.md @@ -15,7 +15,7 @@ # Versal GeMM Implementation Using Vitis Acceleration Library and DSP58 Tutorial -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents @@ -67,6 +67,7 @@ After completing the tutorial, you should be able to: ### Design Overview #### AIE + In this design, the multiplication of 2 square matrices (MatA and MatB) is done using a 24-AIE core overlay. MatA is divided into 3 x 8 blocks and MatB into 8 x 3 blocks. MatA input is provided 1x8 block at a time, using 8 input streams, and MatB is provided using 24 input streams for each 8x3 blocks. Output Matrix MatC is divided into 3x3 blocks and is given out @@ -74,6 +75,7 @@ as 1x3block at a time using 3 output streams. 24 core overlay is chosen to keep Dimensions, 32x32x32-64x64x64 onwards to 1024x1024x1024 and keep the performance high. #### DSP + In this design, Matrix multiplication is implemented using Systolic array of 1024 DSP58 Engines. There are 32 DSP58 cascade chains, each chain has 32 DSP58s. Matrix-Matrix multiplication is decomposed into Matrix-Vector multiplication. One Matrix B column vector is multiplied by each row of Matrix A. This is achieved by broadcasting Matrix B column vector to DSPs at the same position in each cascade chain, while all 1K elements of Matrix A are read and each element drives one Port A of DSP58. One cascade chain implements @@ -135,7 +137,7 @@ GeMM_AIEvsDSP * [AM009 AI Engine Architecture Manual](https://docs.amd.com/r/en-US/am009-versal-ai-engine/Revision-History) -* [Versal ACAP AI Engines for Dummies](https://forums.xilinx.com/t5/Design-and-Debug-Techniques-Blog/Versal-ACAP-AI-Engines-for-Dummies/ba-p/1132493) +* [Versal adaptive SoC AI Engines for Dummies](https://forums.xilinx.com/t5/Design-and-Debug-Techniques-Blog/Versal-ACAP-AI-Engines-for-Dummies/ba-p/1132493) @@ -188,8 +190,8 @@ The script sets up the environment variables and sources scripts explained below 1. The `PLATFORM_REPO_PATHS` environment variable is based on where you downloaded the platform. 2. The `XILINX_TOOLS_LOCATION` path to the AMD tools is used to source the `settings64.sh` script. -3. The `XLNX_VERSAL` path to the `xilinx-versal-common-v2025.1` directory is used in the step below. -4. The platform is set up by running the `xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux` script as provided in the platform download This script sets up the `SDKTARGETSYSROOT` and `CXX` variables. If the script is not present, you _must_ run the `xilinx-versal-common-v2025.1/sdk.sh` script. +3. The `XLNX_VERSAL` path to the `xilinx-versal-common-v2025.2` directory is used in the step below. +4. The platform is set up by running the `xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux` script as provided in the platform download This script sets up the `SDKTARGETSYSROOT` and `CXX` variables. If the script is not present, you _must_ run the `xilinx-versal-common-v2025.2/sdk.sh` script. 5. `DSPLIB_VITIS` is the path to the downloaded Vitis Libraries. This is only required for the AI Engine implementation. 6. In the script, you can optionally set up an `XRT_ROOT` environment variable, pointing to XRT - RPMs, which can be packaged in the Vitis compiler packaging step. If it is not set up, this environment variable is automatically excluded from packaging. 7. The script also sets up the `PLATFORM` variable pointing to the required `.xpfm` file of the target platform set by the variable `tgt_plat`. @@ -217,7 +219,7 @@ platforminfo --list | grep -m 1 -A 9 vck190 The output of the above command should be as follows: ```bash - "baseName": "xilinx_vck190_base_202510_1", + "baseName": "xilinx_vck190_base_202520_1", "version": "1.0", "type": "sdsoc", "dataCenter": "false", @@ -234,8 +236,8 @@ The output of the above command should be as follows: The Makefile and source files for the AI Engine and HLS implementations are in the `AIE` and `DSP` directories respectively. For the documentation of the flow to build the design and details of the hardware and software design, follow each of the links below: -* [AI Engine design implementation](AIE) -* [DSP design implementation with DSP Engines](DSP) +* [AI Engine design implementation](AIE/README.md) +* [DSP design implementation with DSP Engines](DSP/README.md) ## AI Engine and DSP Implementation Comparison @@ -243,8 +245,8 @@ The following table shows a comparison between a 1024 x 1024 x1024 GeMM design i | Design Target | TOPS
| Average Latency (in μs) | AIE Vector Cores | AIE Vector Load | Active Mem Banks /
Mem R/W Rate | Active AIE Tiles | FF (Regs) /
CLB LUTs | BRAMs | DSPs | Dynamic Power
(in mW) | TOPS per Watt
(in TOPS/Watt) | |:-------------:|:----------------------------------:|:-----------------------:|:----------------:|:---------------:|:------------------------------------:|:----------------:|:-------------------------:|:-----:|:----:|:-------------------------:|:---------------------------------------:| -| AIE | 1.551 | 3.331 | 24 | 842.98% | 252 /
14.245% | 43 | 26478 /
13548 |66 | 0 | 4911 | 0.320 | -| DSP | 1.433 | 1497.971 | NA | NA | NA | NA | 70986 /
17340 | 64 | 1024 | 8758 | 0.163 | +| AIE | 1.551 | 3.331 | 24 | 82.96% | 252 /
13.980% | 46 | 26471 /
13546 |66 | 0 | 4876 | 0.320 | +| DSP | 1.433 | 1497.971 | NA | NA | NA | NA | 71086 /
17324 | 64 | 1024 | 8682 | 0.165 | It is important to understand that those 46 AI Engines tiles are not all required for the GeMM compute: 24 AI Engines/vector cores are required for computation, and 22 AI Engines are required for the memory to store the Matrices and also to enable connectivity around the array. The average load on these additional 22 AI Engine tiles is 84.63%. @@ -278,10 +280,10 @@ Below are links to the XRT information used by this tutorial: * [XRT AIE API](https://github.com/Xilinx/XRT/blob/master/src/runtime_src/core/include/experimental/xrt_aie.h): Documents the AI Engine XRT API calls -* [XRT Release Notes](https://www.xilinx.com/support/documentation/sw_manuals/xilinx2025_1/ug1451-xrt-release-notes.pdf) +* [XRT Release Notes](https://www.xilinx.com/support/documentation/sw_manuals/xilinx2025_2/ug1451-xrt-release-notes.pdf) -#### [Vitis Unified Software Development Platform 2025.1 Documentation](https://docs.amd.com/v/u/en-US/ug1416-vitis-documentation) +#### [Vitis Unified Software Development Platform 2025.2 Documentation](https://docs.amd.com/v/u/en-US/ug1416-vitis-documentation) Below are links to Vitis related information referenced in this tutorial: diff --git a/AI_Engine_Development/AIE/Design_Tutorials/11-Bilinear_Interpolation/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/11-Bilinear_Interpolation/Makefile index b0d3183d8f..50f4816ff5 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/11-Bilinear_Interpolation/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/11-Bilinear_Interpolation/Makefile @@ -8,9 +8,9 @@ ECHO = @echo export TARGET = hw_emu -RELEASE=2025.1 +RELEASE=2025.2 BOARD=vck190 -BASE_NUM=202510_1 +BASE_NUM=202520_1 # Platform Selection... VERSAL_VITIS_PLATFORM = xilinx_${BOARD}\_base_${BASE_NUM} diff --git a/AI_Engine_Development/AIE/Design_Tutorials/11-Bilinear_Interpolation/README.md b/AI_Engine_Development/AIE/Design_Tutorials/11-Bilinear_Interpolation/README.md index c5dfbab95f..96b0912ac2 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/11-Bilinear_Interpolation/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/11-Bilinear_Interpolation/README.md @@ -15,7 +15,7 @@ # Bilinear Interpolation -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents diff --git a/AI_Engine_Development/AIE/Design_Tutorials/11-Bilinear_Interpolation/aie/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/11-Bilinear_Interpolation/aie/Makefile index 457b18ea5d..6cfd7aa879 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/11-Bilinear_Interpolation/aie/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/11-Bilinear_Interpolation/aie/Makefile @@ -7,7 +7,7 @@ SRC_DIR := ./src MY_SOURCES := $(shell find $(SRC_DIR) -name *.cpp) $(shell find $(SRC_DIR) -name *.h) -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm COMPILE_OPTS := --aie.pl-freq=625 --aie.adf-api-log-level=2 --aie.kernel-linting \ diff --git a/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/Makefile index 4f7f4a08d8..ffebe94987 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/Makefile @@ -5,12 +5,12 @@ # Author: Mark Rollins ECHO = @echo -export TARGET ?= hw_emu +export TARGET ?= hw -RELEASE=2025.1 +RELEASE=2025.2 TOP_DIR ?= $(shell readlink -f .) -PLATFORM_NAME = xilinx_vck190_base_202510_1 +PLATFORM_NAME = xilinx_vck190_base_202520_1 PLATFORM_PATH = ${PLATFORM_REPO_PATHS} export PLATFORM = ${PLATFORM_PATH}/${PLATFORM_NAME}/${PLATFORM_NAME}.xpfm diff --git a/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/README.md b/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/README.md index 4b85eabd08..8b090905b7 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/README.md @@ -15,7 +15,7 @@ # 64K-Pt IFFT @ 2 Gsps Using a 2D Architecture -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents @@ -39,8 +39,9 @@ A 1D FFT may be implemented on the AI Engine array using a 2D FFT algorithm with The 2D architecture is not new to AI Engine. [XAPP1356](https://docs.amd.com/r/en-US/xapp1356-fft-ai-engine) first explored its use several years ago to achieve 3.7 Gsps with 10 AI Engine tiles. In this tutorial, we explore using the 2D architecture to implement large point transforms in the SSR > 1 regime: specifically a 64K-pt IFFT @ 2 Gsps. In this scenario, the design requires both AI Engine tile resources for compute and programmable logic (PL) resources for sample reordering as shown in detail below. -## Matlab Model -A Matlab model of the 64K-pt IFFT implemented as a $256 \times 256$ 2D architecture is shown below. The model & algorithm consist of the following steps: +## MATLAB Model + +A MATLAB® model of the 64K-pt IFFT implemented as a $256 \times 256$ 2D architecture is shown below. The model & algorithm consist of the following steps: 1. Load the input data in column-major order into a $256 \times 256$ matrix. 1. Take 256-pt transforms along each row 1. Perform a point-wise multiplication of the data matrix with a "twiddle matrix" (see code below for its detailed definition) @@ -137,17 +138,17 @@ The figure below summarizes the AI Engine and PL resources required to implement ### Setup & Initialization -IMPORTANT: Before beginning the tutorial ensure you have installed Vitis™ 2025.1 software. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). +IMPORTANT: Before beginning the tutorial ensure you have installed Vitis™ 2025.2 software. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). Set the environment variable ```COMMON_IMAGE_VERSAL``` to the full path where you have downloaded the Common Images. Then set the environment variable ```PLATFORM_REPO_PATHS``` to the value ```$XILINX_VITIS/base_platforms```. Additional information on this process may be found [here](../../../AIE#environment-settings). The remaining environment variables are configured in the top level Makefile ```/12-IFFT64K-2D/Makefile``` file. ``` -RELEASE=2025.1 +RELEASE=2025.2 TOP_DIR ?= $(shell readlink -f .) -PLATFORM_NAME = xilinx_vck190_base_202510_1 +PLATFORM_NAME = xilinx_vck190_base_202520_1 PLATFORM_PATH = ${PLATFORM_REPO_PATHS} export PLATFORM = ${PLATFORM_PATH}/${PLATFORM_NAME}/${PLATFORM_NAME}.xpfm diff --git a/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/aie/ifft256p4/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/aie/ifft256p4/Makefile index b765eb4d48..90a9ec5812 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/aie/ifft256p4/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/aie/ifft256p4/Makefile @@ -9,8 +9,7 @@ SIM_FIFO := false MY_APP := ifft256p4_app MY_SOURCES := ${MY_APP}.cpp ifft256p4_graph.h ifft256p4.h ifft256p4.cpp -PLATFORM_USE := xilinx_vck190_base_202510_1 -PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcvc1902-vsva2197-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing @@ -20,7 +19,7 @@ DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ AIE_OUTPUT := libadf.a -AIE_FLAGS := ${DSPLIB_OPTS} --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} +AIE_FLAGS := ${DSPLIB_OPTS} --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} @@ -74,7 +73,7 @@ trace: aiesimulator --online -wdb -ctf 2>&1| tee -a log throughput: - @../../scripts/throughput.py aiesimulator_output/data/sig_o_0.txt --iscomplex + @../../scripts/check_throughput.py PLIO_i_0 4935.93 5.0 regression: matlab -batch regression @@ -85,7 +84,7 @@ analyze: clean: rm -rf .Xil Work libadf.a rm -rf aiesimulator_output* aiesimulator*.log - rm -rf x86simulator_output* + rm -rf x86simulator_output* function_wdb_dir rm -rf log log* rm -rf *.xpe *.elf *.db *.soln Map_* xnw* *.lp *.log .xil .Xil *.lp *.db *.log *.exe *.vcd *.json rm -rf vitis_analyzer* pl_sample_counts* pl_sample_count_* diff --git a/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/aie/ifft256p4_rot/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/aie/ifft256p4_rot/Makefile index 8fa43d43df..9551d60c70 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/aie/ifft256p4_rot/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/aie/ifft256p4_rot/Makefile @@ -9,8 +9,7 @@ SIM_FIFO := false MY_APP := ifft256p4_rot_app MY_SOURCES := ${MY_APP}.cpp ifft256p4_rot_graph.h ifft256p4_rot.h ifft256p4_rot.cpp -PLATFORM_USE := xilinx_vck190_base_202510_1 -PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcvc1902-vsva2197-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing @@ -20,7 +19,7 @@ DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ AIE_OUTPUT := libadf.a -AIE_FLAGS := ${DSPLIB_OPTS} --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} +AIE_FLAGS := ${DSPLIB_OPTS} --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} @@ -74,7 +73,7 @@ trace: aiesimulator --online -wdb -ctf 2>&1| tee -a log throughput: - @../../scripts/throughput.py aiesimulator_output/data/sig_o_0.txt --iscomplex + @../../scripts/check_throughput.py PLIO_i_0 3984.98 5.0 regression: matlab -batch regression @@ -85,7 +84,7 @@ analyze: clean: rm -rf .Xil Work libadf.a rm -rf aiesimulator_output* aiesimulator*.log - rm -rf x86simulator_output* + rm -rf x86simulator_output* function_wdb_dir rm -rf log log* rm -rf *.xpe *.elf *.db *.soln Map_* xnw* *.lp *.log .xil .Xil *.lp *.db *.log *.exe *.vcd *.json rm -rf vitis_analyzer* pl_sample_counts* pl_sample_count_* diff --git a/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/aie/ifft64k/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/aie/ifft64k/Makefile index e645bc45c6..ef6d6ba7ce 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/aie/ifft64k/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/aie/ifft64k/Makefile @@ -4,13 +4,13 @@ # # Author: Mark Rollins -AIE_SIM_ONLY := false - SIM_FIFO := false MY_APP := ifft64k_app MY_SOURCES := ${MY_APP}.cpp ifft64k_graph.h ../ifft256p4_rot/ifft256p4_rot_graph.h ../ifft256p4/ifft256p4_graph.h +PART_USE := xcvc1902-vsva2197-2MP-e-S + CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ @@ -21,15 +21,11 @@ DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ AIE_OUTPUT := libadf.a -AIE_FLAGS := ${DSPLIB_OPTS} --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} +AIE_FLAGS := ${DSPLIB_OPTS} --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} endif -ifeq (${AIE_SIM_ONLY},true) - AIE_FLAGS := ${AIE_FLAGS} --aie.Xpreproc="-DAIE_SIM_ONLY" -endif - .PHONY: help clean x86com x86sim sim profile throughput @@ -53,7 +49,7 @@ help:: @echo " make clean" @echo " Command to remove all the generated files." -all: ${AIE_OUTPUT} +all: ${AIE_OUTPUT} sim throughput_ok x86all: clean x86com x86sim @@ -78,17 +74,17 @@ profile: trace: aiesimulator --online -wdb -ctf 2>&1| tee -a log -throughput: - @../../scripts/throughput.py aiesimulator_output/data/front_o_0.txt --iscomplex - @../../scripts/throughput.py aiesimulator_output/data/front_o_1.txt --iscomplex - @../../scripts/throughput.py aiesimulator_output/data/front_o_2.txt --iscomplex - @../../scripts/throughput.py aiesimulator_output/data/front_o_3.txt --iscomplex - @../../scripts/throughput.py aiesimulator_output/data/front_o_4.txt --iscomplex - @../../scripts/throughput.py aiesimulator_output/data/back_o_0.txt --iscomplex - @../../scripts/throughput.py aiesimulator_output/data/back_o_1.txt --iscomplex - @../../scripts/throughput.py aiesimulator_output/data/back_o_2.txt --iscomplex - @../../scripts/throughput.py aiesimulator_output/data/back_o_3.txt --iscomplex - @../../scripts/throughput.py aiesimulator_output/data/back_o_4.txt --iscomplex +throughput_ok: + @../../scripts/check_throughput.py PLIO_front_o_0 3987.50 5.0 + @../../scripts/check_throughput.py PLIO_front_o_1 3987.50 5.0 + @../../scripts/check_throughput.py PLIO_front_o_2 3987.50 5.0 + @../../scripts/check_throughput.py PLIO_front_o_3 3987.50 5.0 + @../../scripts/check_throughput.py PLIO_front_o_4 3987.50 5.0 + @../../scripts/check_throughput.py PLIO_back_o_0 4926.04 5.0 + @../../scripts/check_throughput.py PLIO_back_o_1 4926.04 5.0 + @../../scripts/check_throughput.py PLIO_back_o_2 4926.04 5.0 + @../../scripts/check_throughput.py PLIO_back_o_3 4926.04 5.0 + @../../scripts/check_throughput.py PLIO_back_o_4 4926.04 5.0 regression: matlab -batch regression diff --git a/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/aie/ifft64k/ifft64k_app.cpp b/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/aie/ifft64k/ifft64k_app.cpp index 4ce7088998..25cf023680 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/aie/ifft64k/ifft64k_app.cpp +++ b/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/aie/ifft64k/ifft64k_app.cpp @@ -26,13 +26,8 @@ class my_graph : public graph { std::string fname_o = "data/front_o_" + std::to_string(ff) + ".txt"; std::string pname_i = "PLIO_front_i_" + std::to_string(ff); std::string pname_o = "PLIO_front_o_" + std::to_string(ff); -#ifdef AIE_SIM_ONLY front_i[ff] = input_plio::create(pname_i,plio_64_bits,fname_i); front_o[ff] = output_plio::create(pname_o,plio_64_bits,fname_o); -#else - front_i[ff] = input_plio::create(pname_i,plio_64_bits); - front_o[ff] = output_plio::create(pname_o,plio_64_bits); -#endif connect( front_i[ff].out[0], dut.front_i[ff] ); connect( dut.front_o[ff], front_o[ff].in[0] ); } @@ -41,13 +36,8 @@ class my_graph : public graph { std::string fname_o = "data/back_o_" + std::to_string(bb) + ".txt"; std::string pname_i = "PLIO_back_i_" + std::to_string(bb); std::string pname_o = "PLIO_back_o_" + std::to_string(bb); -#ifdef AIE_SIM_ONLY back_i[bb] = input_plio::create(pname_i,plio_64_bits,fname_i); back_o[bb] = output_plio::create(pname_o,plio_64_bits,fname_o); -#else - back_i[bb] = input_plio::create(pname_i,plio_64_bits); - back_o[bb] = output_plio::create(pname_o,plio_64_bits); -#endif connect( back_i[bb].out[0], dut.back_i[bb] ); connect( dut.back_o[bb], back_o[bb].in[0] ); } diff --git a/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/aie/sincos_test/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/aie/sincos_test/Makefile index be3efa4887..b87092a367 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/aie/sincos_test/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/aie/sincos_test/Makefile @@ -9,8 +9,7 @@ SIM_FIFO := false MY_APP := sincos_test_app MY_SOURCES := ${MY_APP}.cpp sincos_test_graph.h sincos_test.h sincos_test.cpp -PLATFORM_USE := xilinx_vck190_base_202510_1 -PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcvc1902-vsva2197-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing @@ -20,7 +19,7 @@ DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ AIE_OUTPUT := libadf.a -AIE_FLAGS := ${DSPLIB_OPTS} --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} +AIE_FLAGS := ${DSPLIB_OPTS} --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} diff --git a/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/ps_apps/host.cpp b/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/ps_apps/host.cpp index 5f084707a8..fcf5ae6563 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/ps_apps/host.cpp +++ b/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/ps_apps/host.cpp @@ -4,11 +4,6 @@ // // Author: Mark Rollins -#include "ifft64k_graph.h" - -// Instantiate AIE graph: -ifft64k_graph aie_dut; - #include #include #include @@ -50,8 +45,6 @@ static constexpr unsigned NUM_SAMPLES_O = 2*DDR_WORD_DEPTH_O; // 2 x 32-bit ( static constexpr unsigned DDR_BUFFSIZE_I_BYTES = NUM_SAMPLES_I * 4; // Each real/imag sample is 4 bytes static constexpr unsigned DDR_BUFFSIZE_O_BYTES = NUM_SAMPLES_O * 4; // Each real/imag sample is 4 bytes -static constexpr unsigned TOTAL_O_BYTES = LOOP_CNT_O*260*52*8; // Includes overhead on a single PLIO - // ------------------------------------------------------------ // Main // ------------------------------------------------------------ @@ -165,10 +158,6 @@ int main(int argc, char* argv[]) dma_snk_run.set_arg( 2, LOOP_CNT_O ); std::cout << STR_PASSED << "dma_snk_run.set_arg( 2, LOOP_CNT_O=" << LOOP_CNT_O << " )" << std::endl; - // Start profiling: - hdl_prof.start(xrt::aie::profiling::profiling_option::io_stream_start_to_bytes_transferred_cycles, - "aie_dut.back_o[0]","",TOTAL_O_BYTES); - dma_src_run.start(); std::cout << STR_PASSED << "dma_src_run.start()" << std::endl; @@ -181,26 +170,6 @@ int main(int argc, char* argv[]) dma_snk_run.wait(); std::cout << STR_PASSED << "dma_snk_run.wait()" << std::endl; - // Stop profiling: - uint64_t cycle_count = hdl_prof.read(); - hdl_prof.stop(); - - // ------------------------------------------------------------ - // Check Throughput - // ------------------------------------------------------------ - - float total_time = float(cycle_count) * (0.8e-9); - float rate_gsps = (5.0/8.0)*(1e-9)*float(TOTAL_O_BYTES)/total_time; // 5 PLIOs and 8B/sample - float target_gsps = 2.4; // Based on HW_EMU - float target_err = 5.0; - float rate_err = 100.0*fabs(target_gsps-rate_gsps)/target_gsps; - bool rate_flag = ( rate_err > target_err ); - std::cout << STR_INFO << "cycle_count: " << cycle_count << " (cycles)" << std::endl; - std::cout << STR_INFO << "total_time: " << total_time << " (sec)" << std::endl; - std::cout << STR_INFO << "throughput: " << rate_gsps << " (Gsps)" << std::endl; - std::cout << STR_INFO << "target: " << target_gsps << " (Gsps)" << std::endl; - std::cout << STR_INFO << "rate_err: " << rate_err << "%" << std::endl; - // ------------------------------------------------------------ // Retrieve Results // ------------------------------------------------------------ @@ -251,13 +220,9 @@ int main(int argc, char* argv[]) ss_a.close(); // Done: - if ( flag == 0 && rate_flag == 0) + if ( flag == 0 ) std::cout << STR_INFO << "--- PASSED ---" << std::endl; - else if ( flag == 0 && rate_flag == 1 ) - std::cout << STR_INFO << "*** FAILED THROUGHPUT ***" << std::endl; - else if ( flag == 1 && rate_flag == 0 ) - std::cout << STR_INFO << "*** FAILED FUNCTIONAL ***" << std::endl; else - std::cout << STR_INFO << "*** FAILED FUNCTIONAL & THROUGHPUT ***" << std::endl; - return(flag | rate_flag); + std::cout << STR_INFO << "*** FAILED ***" << std::endl; + return(flag); } diff --git a/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/scripts/check_throughput.py b/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/scripts/check_throughput.py new file mode 100755 index 0000000000..859cfa9a0c --- /dev/null +++ b/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/scripts/check_throughput.py @@ -0,0 +1,50 @@ +#!/usr/bin/python3 +# +# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Mark Rollins + +import argparse +import sys +import os +import re + +# ------------------------------------------------------------ +# Find Throughput from AIE Simulation +# ------------------------------------------------------------ + +def check_throughput(args): + error = 0 + plio = args.plio[0] + target = float(args.target[0]) + accuracy = float(args.accuracy[0]) + with open("AIESimulator.log") as file: + for line in file: + regexp = plio + " .* ([\\d.]+)" + match = re.search(regexp,line) + if match: + actual = float(match.group(1)) + diff = abs(100*(target-actual)/target) + if (actual < target and diff > accuracy): + error = 1 + print("*** ERROR ***") + print(" Target: " + str(target) + " Actual: " + str(actual) + " % Diff: " + str(diff)) + else: + error = 0 + return(error) + +# ------------------------------------------------------------ +# Entry Point +# ------------------------------------------------------------ + +if __name__ == "__main__": + parser = argparse.ArgumentParser(prog=sys.argv[0],description='Check throughput against expected') + parser.add_argument('plio',nargs='+') + parser.add_argument('target',nargs='+') + parser.add_argument('accuracy',nargs='+') + Args = sys.argv + Args.pop(0) + args = parser.parse_args(Args) + error = check_throughput(args) + sys.exit(error) diff --git a/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/scripts/throughput.py b/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/scripts/throughput.py deleted file mode 100755 index ed2a8dd96c..0000000000 --- a/AI_Engine_Development/AIE/Design_Tutorials/12-IFFT64K-2D/scripts/throughput.py +++ /dev/null @@ -1,110 +0,0 @@ -# -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -# -# Author: Mark Rollins -# -#!/tools/gensys/anaconda3/bin/python3 -import numpy as np -from math import * -import sys -import argparse - -def GetTime_ns(Stamp): - Time_ns = float(Stamp[1]) - if(Stamp[2] == 'ps'): - Time_ns = Time_ns/1000.0 - elif(Stamp[2] == 'us'): - Time_ns = Time_ns*1000.0 - elif(Stamp[2] == 'ms'): - Time_ns = Time_ns*1000000.0 - elif(Stamp[2] == 's'): - Time_ns = Time_ns*1000000000.0 - return(Time_ns) - -def ReadFile(filename): - # Detect the number of data per PLIO output - fdr = open(filename,'r') - ts = fdr.readline() - d = fdr.readline() - dw = d.split() - fdr.close() - coltime = 0 - coldata = 1 - numdata = len(dw) - coltlast = numdata + 1 - # Initializes the output array - # Format: timestamp (in ns) val1 val2 ... valN TLAST (0 or 1) - a = np.zeros((0,numdata+2)) - fdr = open(filename,'r') - line = ' ' - lnum = 0; - while line !="" : - line = fdr.readline() - if line=='': - continue - res = line.split() - if(res[0] != 'T'): # It should be a timestamp - continue - l = np.zeros((1,numdata+2)) - # Extract the time stamp - l[0][0] = GetTime_ns(res) - line = fdr.readline() - res = line.split() - # extract the TLAST - if(res[0]=='TLAST'): - tlast = 1 - line = fdr.readline() - res = line.split() - else: - tlast = 0 - l[0,coltlast] = tlast - # Extract all values - for i in range(numdata): - l[0,i+1] = float(res[i]) - # Appends to the whole array - a = np.append( a , l,axis=0) - fdr.close() - return(a) - -def Throughput(Filename,IsComplex): - V = ReadFile(Filename) -# print("\n==============================") -# print(Filename) -# print("\n") - NRows = V.shape[0] - NCols = V.shape[1] - NFullFrames = int(np.sum(V[:,NCols-1])) -# print("Number of Full Frames: " + str(NFullFrames)) - # Basic Throughput computation - if IsComplex: - Ratio = 0.5 - else: - Ratio = 1 - RawThroughputMsps = float(NRows*(NCols-2))/(V[NRows-1,0]-V[0,0])*Ratio*1000.0 - print(" Raw Throughput: %.2f (Msps)" % RawThroughputMsps) - # If the output is frame based, compute a more precise throughput - tlast = np.where(V[:,NCols-1] == 1.0) - if(len(tlast[0])<=1): - TotalThroughput = RawThroughputMsps - else: - tlast = tlast[0] - EndRow = tlast[len(tlast)-2]+1 - # EndRow is the number of Rows I take into account for the number of datasource - # The timestamp I am interested in is the timestamp of the next transaction - TotalThroughputMsps = float(EndRow*(NCols-2))/(V[EndRow,0]-V[0,0])*Ratio*1000.0 - print(" Throughput: %.2f" % TotalThroughputMsps) -# print("\n") - -# Entry point of this file -if __name__ == "__main__": - parser = argparse.ArgumentParser(prog=sys.argv[0], description='Compute the throughput corresponding to some output of AIE Simulations') - parser.add_argument('--iscomplex', action='store_true', help='Indicates Complex data in the file') - parser.add_argument('filename',nargs='+') - Args = sys.argv - Args.pop(0) - args = parser.parse_args(Args) - -for f in args.filename: - Throughput(f,args.iscomplex) - diff --git a/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/Makefile index f97384e9f0..0e4edb8545 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/Makefile @@ -6,26 +6,6 @@ ECHO = @echo -export TARGET := hw - -RELEASE=2025.1 -BOARD=vck190 -BASE_NUM=202510_1 - -# Platform Selection... -VERSAL_VITIS_PLATFORM = xilinx_${BOARD}\_base_${BASE_NUM} -VITIS_PLATFORM_DIR = ${PLATFORM_REPO_PATHS}/${VERSAL_VITIS_PLATFORM} -export VITIS_PLATFORM_XPFM = ${VITIS_PLATFORM_DIR}/${VERSAL_VITIS_PLATFORM}.xpfm - -# Set SysRoot, RootFS and Image -export VITIS_SYSROOTS = ${COMMON_IMAGE_VERSAL}/sysroots/cortexa72-cortexa53-amd-linux -export SDKTARGETSYSROOT = ${VITIS_SYSROOTS} -export KERNEL_IMAGE = ${COMMON_IMAGE_VERSAL}/Image -export ROOTFS = ${COMMON_IMAGE_VERSAL}/rootfs.ext4 -export XLNX_VERSAL = ${COMMON_IMAGE_VERSAL} -export PLATFORM = ${VITIS_PLATFORM_XPFM} -export SYSROOT = ${SDKTARGETSYSROOT} - ############## # Build Flow # ############## diff --git a/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/README.md b/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/README.md index 7323ff2254..eadfae2cbf 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/README.md @@ -15,7 +15,7 @@ # Implementing FFT and DFT Designs on AI Engines -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Abstract diff --git a/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/dft16/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/dft16/Makefile index cb513531b4..1b2c0471f2 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/dft16/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/dft16/Makefile @@ -11,14 +11,13 @@ MY_APP := dft16_app MY_SOURCES := ${MY_APP}.cpp dft16_graph.h dft_1xN_widget_graph.h dft_1xN_widget.h dft_1xN_widget.cpp \ twiddle_dft16.h -PLATFORM_USE := xilinx_vck190_base_202510_1 -PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcvc1902-vsva2197-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing AIE_OUTPUT := libadf.a -AIE_FLAGS := --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} +AIE_FLAGS := --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} @@ -48,14 +47,14 @@ profile: aiesimulator --online -wdb -text --profile --profile 2>&1| tee -a log throughput_ok: - @../python/check_throughput.py PLIO_dft_o_0 4309.0 5.0 - @../python/check_throughput.py PLIO_dft_o_1 4309.0 5.0 - @../python/check_throughput.py PLIO_dft_o_2 4309.0 5.0 - @../python/check_throughput.py PLIO_dft_o_3 4309.0 5.0 - @../python/check_throughput.py PLIO_dft_o_4 4309.0 5.0 - @../python/check_throughput.py PLIO_dft_o_5 4309.0 5.0 - @../python/check_throughput.py PLIO_dft_o_6 4309.0 5.0 - @../python/check_throughput.py PLIO_dft_o_7 4309.0 5.0 + @../python/check_throughput.py PLIO_dft_o_0 4309.31 5.0 + @../python/check_throughput.py PLIO_dft_o_1 4309.31 5.0 + @../python/check_throughput.py PLIO_dft_o_2 4309.31 5.0 + @../python/check_throughput.py PLIO_dft_o_3 4309.31 5.0 + @../python/check_throughput.py PLIO_dft_o_4 4309.31 5.0 + @../python/check_throughput.py PLIO_dft_o_5 4309.31 5.0 + @../python/check_throughput.py PLIO_dft_o_6 4309.31 5.0 + @../python/check_throughput.py PLIO_dft_o_7 4309.31 5.0 clean: rm -rf Work Work* ${WORK_DIR} diff --git a/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/fft32_dsplib/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/fft32_dsplib/Makefile index cff2820789..da70ed34ab 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/fft32_dsplib/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/fft32_dsplib/Makefile @@ -10,8 +10,7 @@ SIM_FIFO := false MY_APP := fft32_dsplib_app MY_SOURCES := ${MY_APP}.cpp fft32_dsplib_graph.h -PLATFORM_USE := xilinx_vck190_base_202510_1 -PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcvc1902-vsva2197-2MP-e-S CHECK_FIFO := --evaluate-fifo-depth -Xrouter=disablePathBalancing @@ -21,7 +20,7 @@ DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ --include=${DSPLIB_ROOT}/L1/include/aie \ --include=${DSPLIB_ROOT}/L1/src/aie -AIE_FLAGS := --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ${DSPLIB_OPTS} +AIE_FLAGS := --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ${DSPLIB_OPTS} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} @@ -54,7 +53,7 @@ vcd: aiesimulator --dump-vcd=hough_tile 2>&1| tee -a log throughput_ok: - @../python/check_throughput.py PLIO_o_0 1715.602094 5.0 + @../python/check_throughput.py PLIO_o_0 1716.03 5.0 loopII: @../python/get_loop_II.py Work/aie diff --git a/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/fft32_dsplib_split/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/fft32_dsplib_split/Makefile index 63d22dd6c4..a65d991e9a 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/fft32_dsplib_split/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/fft32_dsplib_split/Makefile @@ -10,8 +10,7 @@ SIM_FIFO := false MY_APP := fft32_dsplib_app MY_SOURCES := ${MY_APP}.cpp fft32_dsplib_graph.h -PLATFORM_USE := xilinx_vck190_base_202510_1 -PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcvc1902-vsva2197-2MP-e-S CHECK_FIFO := --evaluate-fifo-depth -Xrouter=disablePathBalancing @@ -21,7 +20,7 @@ DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ --include=${DSPLIB_ROOT}/L1/include/aie \ --include=${DSPLIB_ROOT}/L1/src/aie -AIE_FLAGS := --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ${DSPLIB_OPTS} +AIE_FLAGS := --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ${DSPLIB_OPTS} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} @@ -54,7 +53,7 @@ vcd: aiesimulator --dump-vcd=hough_tile 2>&1| tee -a log throughput_ok: - @../python/check_throughput.py PLIO_o_0 1483.574197 5.0 + @../python/check_throughput.py PLIO_o_0 1483.57 5.0 loopII: @../python/get_loop_II.py Work/aie diff --git a/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/fft32_dsplib_ssr/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/fft32_dsplib_ssr/Makefile index 85afd82a3a..acd1b2d21b 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/fft32_dsplib_ssr/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/fft32_dsplib_ssr/Makefile @@ -10,8 +10,7 @@ SIM_FIFO := false MY_APP := fft32_dsplib_app MY_SOURCES := ${MY_APP}.cpp fft32_dsplib_graph.h -PLATFORM_USE := xilinx_vck190_base_202510_1 -PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcvc1902-vsva2197-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing @@ -21,7 +20,7 @@ DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ --include=${DSPLIB_ROOT}/L1/include/aie \ --include=${DSPLIB_ROOT}/L1/src/aie -AIE_FLAGS := ${MY_APP}.cpp --platform=${PLATFORM} --aie.output-archive=${AIE_OUTPUT} ${DSPLIB_OPTS} +AIE_FLAGS := ${MY_APP}.cpp --part=${PART_USE} --aie.output-archive=${AIE_OUTPUT} ${DSPLIB_OPTS} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} @@ -52,10 +51,10 @@ profile: aiesimulator --online -wdb -text --profile 2>&1| tee -a log throughput_ok: - @../python/check_throughput.py PLIO_o_0 683.509662 5.0 - @../python/check_throughput.py PLIO_o_1 683.509662 5.0 - @../python/check_throughput.py PLIO_o_2 683.509662 5.0 - @../python/check_throughput.py PLIO_o_3 683.509662 5.0 + @../python/check_throughput.py PLIO_o_0 683.99 5.0 + @../python/check_throughput.py PLIO_o_1 683.99 5.0 + @../python/check_throughput.py PLIO_o_2 683.99 5.0 + @../python/check_throughput.py PLIO_o_3 683.99 5.0 loopII: @../python/get_loop_II.py Work/aie diff --git a/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/fft32_r2/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/fft32_r2/Makefile index ca90e9220d..e5ab21569d 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/fft32_r2/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/13-FFT-DFT-on-AIE/fft32_r2/Makefile @@ -10,14 +10,13 @@ SIM_FIFO := false MY_APP := fft32_r2_app MY_SOURCES := {$MY_APP}.cpp fft32_r2_graph.h fft32_r2_kernel.h fft32_r2_kernel.cpp fft32_r2_twiddle.h -PLATFORM_USE := xilinx_vck190_base_202510_1 -PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcvc1902-vsva2197-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing AIE_OUTPUT := libadf.a -AIE_FLAGS := ${MY_APP}.cpp --platform=${PLATFORM} --aie.output-archive=${AIE_OUTPUT} +AIE_FLAGS := ${MY_APP}.cpp --part=${PART_USE} --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} @@ -47,7 +46,7 @@ profile: aiesimulator --online -wdb -text --profile 2>&1| tee -a log throughput_ok: - @../python/check_throughput.py PLIO_o_0 1519.316011 5.0 + @../python/check_throughput.py PLIO_o_0 1477.42 5.0 loopII: @../python/get_loop_II.py Work/aie diff --git a/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/Makefile index 2dfbad06cc..47c4a8b817 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/Makefile @@ -6,26 +6,6 @@ ECHO = @echo -export TARGET := hw - -RELEASE=2025.1 -BOARD=vck190 -BASE_NUM=202510_1 - -# Platform Selection... -VERSAL_VITIS_PLATFORM = xilinx_${BOARD}\_base_${BASE_NUM} -VITIS_PLATFORM_DIR = ${PLATFORM_REPO_PATHS}/${VERSAL_VITIS_PLATFORM} -export VITIS_PLATFORM_XPFM = ${VITIS_PLATFORM_DIR}/${VERSAL_VITIS_PLATFORM}.xpfm - -# Set SysRoot, RootFS and Image -export VITIS_SYSROOTS = ${COMMON_IMAGE_VERSAL}/sysroots/cortexa72-cortexa53-amd-linux -export SDKTARGETSYSROOT = ${VITIS_SYSROOTS} -export KERNEL_IMAGE = ${COMMON_IMAGE_VERSAL}/Image -export ROOTFS = ${COMMON_IMAGE_VERSAL}/rootfs.ext4 -export XLNX_VERSAL = ${COMMON_IMAGE_VERSAL} -export PLATFORM = ${VITIS_PLATFORM_XPFM} -export SYSROOT = ${SDKTARGETSYSROOT} - ############## # Build Flow # ############## diff --git a/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/README.md b/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/README.md index d45ce2f3bf..c5bb22c12b 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/README.md @@ -15,7 +15,7 @@ # Bitonic SIMD Sorting on AI Engine for `float` Datatypes -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents diff --git a/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/bitonic_fp1024/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/bitonic_fp1024/Makefile index 55ce98b241..6c3d9a1de9 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/bitonic_fp1024/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/bitonic_fp1024/Makefile @@ -11,14 +11,13 @@ SIM_FIFO := false MY_APP := bitonic_fp1024_app MY_SOURCES := ${MY_APP}.cpp bitonic_fp1024.h bitonic_fp1024.cpp bitonic_fp1024_graph.h -PLATFORM_USE := xilinx_vck190_base_202510_1 -PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcvc1902-vsva2197-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing AIE_OUTPUT := libadf.a -AIE_FLAGS := --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} +AIE_FLAGS := --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} @@ -73,7 +72,7 @@ trace: aiesimulator --online -wdb -text 2>&1| tee -a log throughput_ok: - @../scripts/check_throughput.py PLIO_o 127.647374 5.0 + @../scripts/check_throughput.py PLIO_o 122.51 5.0 analyze: vitis_analyzer aiesimulator_output/default.aierun_summary diff --git a/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/bitonic_fp16/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/bitonic_fp16/Makefile index e728419452..e7af063e9f 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/bitonic_fp16/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/bitonic_fp16/Makefile @@ -11,14 +11,13 @@ SIM_FIFO := false MY_APP := bitonic_fp16_app MY_SOURCES := ${MY_APP}.cpp bitonic_fp16.h bitonic_fp16.cpp bitonic_fp16_graph.h -PLATFORM_USE := xilinx_vck190_base_202510_1 -PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcvc1902-vsva2197-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing AIE_OUTPUT := libadf.a -AIE_FLAGS := --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} +AIE_FLAGS := --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} @@ -73,7 +72,7 @@ trace: aiesimulator --online -wdb -text 2>&1| tee -a log throughput_ok: - @../scripts/check_throughput.py PLIO_o 462.205104 5.0 + @../scripts/check_throughput.py PLIO_o 459.66 5.0 analyze: vitis_analyzer aiesimulator_output/default.aierun_summary diff --git a/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/sortcpp_fp1024/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/sortcpp_fp1024/Makefile index 35b9396ce3..dcb2647309 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/sortcpp_fp1024/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/sortcpp_fp1024/Makefile @@ -11,14 +11,13 @@ SIM_FIFO := false MY_APP := sortcpp_fp1024_app MY_SOURCES := ${MY_APP}.cpp sortcpp_fp1024.h sortcpp_fp1024.cpp sortcpp_fp1024_graph.h -PLATFORM_USE := xilinx_vck190_base_202510_1 -PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcvc1902-vsva2197-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing AIE_OUTPUT := libadf.a -AIE_FLAGS := --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} +AIE_FLAGS := --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} @@ -73,7 +72,7 @@ trace: aiesimulator --online -wdb -text 2>&1| tee -a log throughput_ok: - @../scripts/check_throughput.py PLIO_o 8.828252 5.0 + @../scripts/check_throughput.py PLIO_o 8.95 5.0 analyze: vitis_analyzer aiesimulator_output/default.aierun_summary diff --git a/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/sortcpp_fp16/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/sortcpp_fp16/Makefile index 6f0f84099a..35ead5f17b 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/sortcpp_fp16/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/14-Bitonic-Sorting/sortcpp_fp16/Makefile @@ -11,14 +11,13 @@ SIM_FIFO := false MY_APP := sortcpp_fp16_app MY_SOURCES := ${MY_APP}.cpp sortcpp_fp16.h sortcpp_fp16.cpp sortcpp_fp16_graph.h -PLATFORM_USE := xilinx_vck190_base_202510_1 -PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcvc1902-vsva2197-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing AIE_OUTPUT := libadf.a -AIE_FLAGS := --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} +AIE_FLAGS := --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} @@ -73,7 +72,7 @@ trace: aiesimulator --online -wdb -text 2>&1| tee -a log throughput_ok: - @../scripts/check_throughput.py PLIO_o 16.858076 5.0 + @../scripts/check_throughput.py PLIO_o 17.28 5.0 analyze: vitis_analyzer aiesimulator_output/default.aierun_summary diff --git a/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/Makefile index dea1c8f058..5e4e1fda1a 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/Makefile @@ -9,7 +9,7 @@ export TARGET ?= hw_emu export AIE_SIM_ONLY := false -VERSAL_VITIS_PLATFORM = xilinx_vck190_base_202510_1 +VERSAL_VITIS_PLATFORM = xilinx_vck190_base_202520_1 VITIS_PLATFORM_DIR = ${PLATFORM_REPO_PATHS}/${VERSAL_VITIS_PLATFORM} export VITIS_PLATFORM_XPFM = ${VITIS_PLATFORM_DIR}/${VERSAL_VITIS_PLATFORM}.xpfm diff --git a/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/README.md b/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/README.md index abb70abb0f..18b216f26c 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/README.md @@ -15,7 +15,7 @@ # Fractional Delay Farrow Filter -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents @@ -291,13 +291,13 @@ Launch vitis_analyzer `vitis_analyzer aiesimulator_output/default.aierun_summary *Figure 13 - Farrow Filter Final Implementation Trace View* -Steady state throughput is 1024/913.6e-6 = 1121 Msps. +Steady state throughput is 1024/913e-6 = 1122 Msps. ## Build and Run Design ### Setup and Initialization -IMPORTANT: Before beginning the tutorial ensure you have installed Vitis™ 2025.1 software. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). +IMPORTANT: Before beginning the tutorial ensure you have installed Vitis™ 2025.2 software. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). Set the environment variable ```COMMON_IMAGE_VERSAL``` to the full path where you have downloaded the Common Images. Then set the environment variable ```PLATFORM_REPO_PATHS``` to the value ```$XILINX_VITIS/base_platforms```. The remaining environment variables are configured in the top level Makefile. diff --git a/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/images/farrow_final_array_view.png b/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/images/farrow_final_array_view.png index e5425f15f7..719aedccf6 100755 Binary files a/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/images/farrow_final_array_view.png and b/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/images/farrow_final_array_view.png differ diff --git a/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/images/farrow_final_trace_view.png b/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/images/farrow_final_trace_view.png index b732990225..ec2c7ccb0e 100755 Binary files a/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/images/farrow_final_trace_view.png and b/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/images/farrow_final_trace_view.png differ diff --git a/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/images/farrow_hw_terminal.png b/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/images/farrow_hw_terminal.png index 9367e3171f..178c566769 100755 Binary files a/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/images/farrow_hw_terminal.png and b/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/images/farrow_hw_terminal.png differ diff --git a/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/ps_apps/host.cpp b/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/ps_apps/host.cpp index 52a38c424b..640455bdbb 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/ps_apps/host.cpp +++ b/AI_Engine_Development/AIE/Design_Tutorials/15-farrow_filter/ps_apps/host.cpp @@ -44,7 +44,7 @@ static constexpr unsigned NUM_SAMPLES_O = DDR_WORD_DEPTH_O * 4; // 32-bit (ci static constexpr unsigned DDR_BUFFSIZE_I_BYTES = NUM_SAMPLES_I * 4; // Each sample is 4 bytes (32-bits) static constexpr unsigned DDR_BUFFSIZE_O_BYTES = NUM_SAMPLES_O * 4; // Each sample is 4 bytes (32-bits) static constexpr unsigned TOTAL_O_BYTES = DDR_BUFFSIZE_O_BYTES * LOOP_CNT_O; -static constexpr double TARGET_THROUGHPUT = 1135; // Measured in hw_emu 2025.1 +static constexpr double TARGET_THROUGHPUT = 1135; // Measured in hw_emu 2025.2 // ------------------------------------------------------------ diff --git a/AI_Engine_Development/AIE/Design_Tutorials/16-1M-Point-FFT-32Gsps/README.md b/AI_Engine_Development/AIE/Design_Tutorials/16-1M-Point-FFT-32Gsps/README.md index 43ec383cb1..9478b487b3 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/16-1M-Point-FFT-32Gsps/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/16-1M-Point-FFT-32Gsps/README.md @@ -15,7 +15,7 @@ # 1 Million Point `float` FFT @ 32 Gsps on AI Engine -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents @@ -37,23 +37,27 @@ A 1D FFT may be implemented on the AI Engine array using a 2D FFT algorithm with This approach is used in this tutorial to design a 1M-pt FFT for `float` data types that achieves an impressive throughput rate exceeding 32 Gsps. The design partitions all compute to the AI Engine array and uses URAM resources in programmable logic to implement the sample reordering needed for the "matrix transpose" operation outlined in detail below. -## Matlab Models +## MATLAB Models + +A MATLAB® model `matlab/aie_model_fft_fp_1mpt.m` provides a simple algorithmic model of the 1M-pt transform, implementing it using a $1024\times 1024$ 2D architecture. The algorithm performs conceptually the following steps: -A Matlab model `matlab/aie_model_fft_fp_1mpt.m` provides a simple algorithmic model of the 1M-pt transform, implementing it using a $1024\times 1024$ 2D architecture. The algorithm performs conceptually the following steps: * Write the 1M incoming samples into a $1024\times 1024$ matrix in column major order * Perform 1K-pt transforms along the matrix rows * Multiply the 2D matrix pointwise with another 2D matrix of equal size filled with "twiddle factors". * Perform 1K-pt transforms along the matrix columns * Extract the 1M outgoing samples in row-major order -The Matlab models are used to validate the AI Engine design. The I/O testvectors may be generated into the folder `/aie_src/data` using the following approach below. Note these I/O testvectors are not required to run the design on the VCK190 evaluation board. They are required only for the purpose of simulating the AI Engine portion of the design in isolation using either `x86simulator` or `aiesimulator`. +The MATLAB models are used to validate the AI Engine design. The I/O testvectors may be generated into the folder `/aie_src/data` using the following approach below. Note these I/O testvectors are not required to run the design on the VCK190 evaluation board. They are required only for the purpose of simulating the AI Engine portion of the design in isolation using either `x86simulator` or `aiesimulator`. + ``` [shell]% cd /aie_src [shell]% make testvectors ``` + ## Design Overview The figure below shows block diagram of the 1M-pt transform. It may be described as follows: + * The "front-end" compute consists of 32 identical instances of a FFT-1024 kernel followed by a twiddle rotation kernel. The FFT-1024 kernels use 5 AI Engine tiles, one for each radix-4 stage, given $1024=4\times 4\times 4\times 4\times 4$. Each tile employs two 64-bit PLIO streams @ 520 MHz. Given these streams carry `cfloat` data types requiring 64-bits per sample, it follows each PLIO stream may transfer 520 Msps; overall this provides a throughput of $32\times 2\times 520=33.28$ Gsps. * The "transpose" block in the PL provides sample reordering that effects the "row-wise" vs "column-wise" processing outlined above -- in effect performing a matrix transpose operation using URAM resources in the PL. Note a very large multi-ported memory resource is required with 64 I/O streams. * The "back-end" compute consists of 32 identical instances of an FFT-1024 kernel. Once again, these kernels use 5 AI Engine tiles each with two 64-bit PLIO streams @ 520 MHz. @@ -62,22 +66,27 @@ The figure below shows block diagram of the 1M-pt transform. It may be described ![figure](images/block-diagram.png) ### AI Engine Graph View + The diagram below shows the graph view of the AI Engine array for this design. As noted above, the design contains 32 instances of 1024-pt "row" FFTs in the front-end and 32 instances of 1024-pt "column" FFTs in the back-end. Each 1024-pt transform is implemented using 5 tiles in each case. An extra tile implements "twiddle rotation" for each FFT instance in the front-end. Consequently, we can see in the diagram below there are 32 instances of a "6-tile subgraph" that implement the front-end transforms and twiddle rotations, along with 32 instances of a "5-tile subgraph" for the back-end compute processing. ![figure](images/aie-graph-view.png) ### AI Engine Array View + The diagram below shows the floor plan view of the AI Engine array. The design requires resources from a $44\times 8$ rectangular region of the array. The three leftmost and rightmost array columns are left unused in this case. ![figure](images/aie-array-view.png) ### VC1902 Floorplan View + The diagram below shows the floorplan view of the VC1902 device, where all the PL resources for the design are highlighted showing the utilization. Since the AI Engine array makes use of PLIO resources distributed across the full width of the die, the PL circuitry exhibits the same characteristic. ![figure](images/design-floorplan.png) ### AI Engine Design Validation + The AI Engine design may be validated in functional simulation using either the X86 or AIE simulators. To use the X86 simulator to compile, simulate, then validate the outputs of the simulation, use the following approach: + ``` [shell]% cd /aie_src [shell]% make x86_compile @@ -86,6 +95,7 @@ The AI Engine design may be validated in functional simulation using either the ``` To use the AIE simulator to do the same things plus validate the design I/O throughput as measured from simulated PLIO timestamps, use the following approach: + ``` [shell]% cd /aie_src [shell]% make aie_compile @@ -95,6 +105,7 @@ To use the AIE simulator to do the same things plus validate the design I/O thro ``` ### VC1902 Timing Closure + The diagram below shows the timing summary report for the overall design. Timing closure is achieved on all end-points. ![figure](images/timing-summary.png) @@ -116,7 +127,9 @@ The diagram below summarizes the PL resources used by the design. BRAM and URAM This design runs on the VCK190 evaluation board using a custom platform and bare metal OS. Consequently, no environment setup is needed to point to base platforms or Linux filesystems. The bitstream may be built directly from the top level Makefile. ### Hardware + To build the design for hardware, please execute the following steps: + ``` [shell]% cd [shell]% make all diff --git a/AI_Engine_Development/AIE/Design_Tutorials/16-1M-Point-FFT-32Gsps/aie_src/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/16-1M-Point-FFT-32Gsps/aie_src/Makefile index 512d0709ac..ada87f0974 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/16-1M-Point-FFT-32Gsps/aie_src/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/16-1M-Point-FFT-32Gsps/aie_src/Makefile @@ -9,7 +9,13 @@ PLATFORMNAME ?= $(PLATFORMDIR)/$(PF_STDNAME)/export/$(PF_STDNAME)/$(PF_STDNAME). INCLUDES = --include=./ --include=./inc --include=./kernels TEST_BENCH = ./test_ssrfft_1m.cpp -OTHER_OPTS = --aie.constraints=./shim_loc.json --aie.xlopt=1 + +# The Xchess option disables "automatic chess_separator insertion" which compromises +# throughput by introducing artifical scheduling boundaries for blocks exceeding the +# default threshold (default can be changed with the "+Olbb" option). +OTHER_OPTS = --aie.constraints=./shim_loc.json --aie.xlopt=1 \ + --aie.Xchess=main:backend.mist2.xargs="+Olbb=0" + ROUTER_OPTS = --aie.Xmapper=disableFloorplanning --aie.Xrouter=disablepathbalancing \ --aie.Xrouter=disableSSFifoSharing --aie.disable-multirate NUM_ITERATION = 4 diff --git a/AI_Engine_Development/AIE/Design_Tutorials/16-1M-Point-FFT-32Gsps/description.json b/AI_Engine_Development/AIE/Design_Tutorials/16-1M-Point-FFT-32Gsps/description.json index 8975ededf5..426e25e5cf 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/16-1M-Point-FFT-32Gsps/description.json +++ b/AI_Engine_Development/AIE/Design_Tutorials/16-1M-Point-FFT-32Gsps/description.json @@ -23,8 +23,7 @@ } ], "targets": [ - "vitis_hw_build", - "vitis_hw_run" + "vitis_hw_build" ], "category": "canary", "make_options": [ @@ -33,11 +32,7 @@ "custom_build_target": { "all": "all" }, - "custom_board_target": "run_test", "tasks": { - "board" : { - "pre_exec" : ["./env_setup_versal.sh"] - }, "build": { "pre_exec": ["./env_setup_versal.sh"] } diff --git a/AI_Engine_Development/AIE/Design_Tutorials/17-Hough-Transform/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/17-Hough-Transform/Makefile index b8fbe409da..591ed4be76 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/17-Hough-Transform/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/17-Hough-Transform/Makefile @@ -6,26 +6,6 @@ ECHO = @echo -export TARGET := hw - -RELEASE=2025.1 -BOARD=vck190 -BASE_NUM=202510_1 - -# Platform Selection... -VERSAL_VITIS_PLATFORM = xilinx_${BOARD}\_base_${BASE_NUM} -VITIS_PLATFORM_DIR = ${PLATFORM_REPO_PATHS}/${VERSAL_VITIS_PLATFORM} -export VITIS_PLATFORM_XPFM = ${VITIS_PLATFORM_DIR}/${VERSAL_VITIS_PLATFORM}.xpfm - -# Set SysRoot, RootFS and Image -export VITIS_SYSROOTS = ${COMMON_IMAGE_VERSAL}/sysroots/cortexa72-cortexa53-amd-linux -export SDKTARGETSYSROOT = ${VITIS_SYSROOTS} -export KERNEL_IMAGE = ${COMMON_IMAGE_VERSAL}/Image -export ROOTFS = ${COMMON_IMAGE_VERSAL}/rootfs.ext4 -export XLNX_VERSAL = ${COMMON_IMAGE_VERSAL} -export PLATFORM = ${VITIS_PLATFORM_XPFM} -export SYSROOT = ${SDKTARGETSYSROOT} - ############## # Build Flow # ############## diff --git a/AI_Engine_Development/AIE/Design_Tutorials/17-Hough-Transform/README.md b/AI_Engine_Development/AIE/Design_Tutorials/17-Hough-Transform/README.md index 774b88c13e..9e3fe32df8 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/17-Hough-Transform/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/17-Hough-Transform/README.md @@ -15,7 +15,7 @@ # System Partitioning of a Hough Transform on AI Engine -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents @@ -59,9 +59,9 @@ Some aspects of each phase is outlined in the following diagram. ![figure](images/system-partitioning-methodology.png) -### Hough Transform Matlab Model +### Hough Transform MATLAB Model -A proper algorithm model is required for system partitioning. It is started with the Matlab model shown below. A detailed study of this model identifies key aspects of the system design that impact its solution. For example: +A proper algorithm model is required for system partitioning. It is started with the MATLAB® model shown below. A detailed study of this model identifies key aspects of the system design that impact its solution. For example: * The overall compute load complexity is driven by the image size through $R$ and $C$ dimensions. * The resolution adopted for $\theta$ through the `theta_res` parameter drives complexity, bandwidth, and histogram storage. @@ -103,7 +103,7 @@ function [H,theta,rho,rho_calc] = hough_model( BW, theta_res ) end ``` -The Matlab model is run and its performance compared to the built-in Matlab function `hough` is found in the Image Processing Toolbox. Here, it is run with a $216\times 240$ image of the AMD Instinct and show "heat maps" of the 2D Hough Transform output histograms for both the Matlab function and the AMD 16-bit Matlab model. +The MATLAB model is run and its performance compared to the built-in MATLAB function `hough` is found in the Image Processing Toolbox. Here, it is run with a $216\times 240$ image of the AMD Instinct and show "heat maps" of the 2D Hough Transform output histograms for both the MATLAB function and the AMD 16-bit MATLAB model. ![figure](images/hough_model.png) @@ -113,7 +113,7 @@ This section illustrates the details of system partitioning for the Hough Transf ### Goals -This tutorial aims at identifying the "best we can do" using only AI Engine resources to implement the Hough Transform. To this end, a target throughput requirement of 220 Mpixel/sec (or Mpps) is set and the question is posed, "How many AI Engine tiles are required?" As understood from the Matlab model above, the image size and $\theta$ resolution are key parameters driving compute, bandwidth, and storage. With this in mind, brainstorm solutions for how you can parallelize the Hough Transform algorithm across multiple AI Engine tiles. +This tutorial aims at identifying the "best we can do" using only AI Engine resources to implement the Hough Transform. To this end, a target throughput requirement of 220 Mpixel/sec (or Mpps) is set and the question is posed, "How many AI Engine tiles are required?" As understood from the MATLAB model above, the image size and $\theta$ resolution are key parameters driving compute, bandwidth, and storage. With this in mind, brainstorm solutions for how you can parallelize the Hough Transform algorithm across multiple AI Engine tiles. ### Parallelizing Over "Image Tiles" @@ -135,7 +135,7 @@ Having identified some possible parallelization schemes, dive into the Requireme ### Analyzing Compute Requirements -Next, use a spreadsheet analysis to assess compute requirements. Load the system input parameters on the left side of the spreadsheet shown below and analyze compute parameters on the right side. It is useful to tabulate the numbers of processor cycles required by each loop body in the original Matlab model of the Hough Transform. Based on the AI Engine compute capacity of 32 MACs/cycle for `int16` data types, you can process two MACs/pixel per $\theta$ value in real time. Based on these vector estimates, the spreadsheet indicates to process 5.7 cycles per pixel to meet the 220 Mpps throughput objective. This is equivalent to 45 cycles for the vector processor with its eight lanes SIMD execution. The compute bound for the vector processor is high at 5000 Mpps. However, assuming an 8-cycle "read-modify-write" instruction to update the histogram tables in the third compute workload, the throughput is limited by the scalar processor to 39 Mpps if using 32 tiles. When projected to more tiles, reaching the 220 Mpps target with even 128 tiles is not possible. +Next, use a spreadsheet analysis to assess compute requirements. Load the system input parameters on the left side of the spreadsheet shown below and analyze compute parameters on the right side. It is useful to tabulate the numbers of processor cycles required by each loop body in the original MATLAB model of the Hough Transform. Based on the AI Engine compute capacity of 32 MACs/cycle for `int16` data types, you can process two MACs/pixel per $\theta$ value in real time. Based on these vector estimates, the spreadsheet indicates to process 5.7 cycles per pixel to meet the 220 Mpps throughput objective. This is equivalent to 45 cycles for the vector processor with its eight lanes SIMD execution. The compute bound for the vector processor is high at 5000 Mpps. However, assuming an 8-cycle "read-modify-write" instruction to update the histogram tables in the third compute workload, the throughput is limited by the scalar processor to 39 Mpps if using 32 tiles. When projected to more tiles, reaching the 220 Mpps target with even 128 tiles is not possible. ![figure](images/analyzing-compute.png) diff --git a/AI_Engine_Development/AIE/Design_Tutorials/17-Hough-Transform/aie/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/17-Hough-Transform/aie/Makefile index 5b3ccf512f..47158bb60c 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/17-Hough-Transform/aie/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/17-Hough-Transform/aie/Makefile @@ -9,14 +9,13 @@ SIM_FIFO := false MY_APP := hough_tile_app MY_SOURCES := ${MY_APP}.cpp hough_tile.h hough_tile.cpp hough_tile_shared.h hough_tile_graph.h -PLATFORM_USE := xilinx_vck190_base_202510_1 -PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcvc1902-vsva2197-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing AIE_OUTPUT := libadf.a -AIE_FLAGS := --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} +AIE_FLAGS := --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} @@ -65,7 +64,7 @@ profile: throughput_ok: @for ii in {0..31}; do \ - ../scripts/check_throughput.py PLIO_o_$$ii 5007.633588 5.0; \ + ../scripts/check_throughput.py PLIO_o_$$ii 5007.63 5.0; \ done loop_II: diff --git a/AI_Engine_Development/AIE/Design_Tutorials/17-Hough-Transform/scripts/check_throughput.py b/AI_Engine_Development/AIE/Design_Tutorials/17-Hough-Transform/scripts/check_throughput.py index 44a5b1e35e..bd41dd532d 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/17-Hough-Transform/scripts/check_throughput.py +++ b/AI_Engine_Development/AIE/Design_Tutorials/17-Hough-Transform/scripts/check_throughput.py @@ -21,7 +21,7 @@ def check_throughput(args): accuracy = float(args.accuracy[0]) with open("AIESimulator.log") as file: for line in file: - regexp = plio + " .* ([\d.]+)" + regexp = plio + " .* ([\\d.]+)" match = re.search(regexp,line) if match: actual = float(match.group(1)) diff --git a/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/Makefile index dc60f3954f..423a95b426 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/Makefile @@ -7,9 +7,9 @@ ECHO = @echo export TARGET ?= hw -RELEASE=2025.1 +RELEASE=2025.2 -PLATFORM_NAME = xilinx_vck190_base_202510_1 +PLATFORM_NAME = xilinx_vck190_base_202520_1 PLATFORM_PATH = ${PLATFORM_REPO_PATHS} export PLATFORM = ${PLATFORM_PATH}/${PLATFORM_NAME}/${PLATFORM_NAME}.xpfm diff --git a/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/README.md b/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/README.md index 5853087c42..6fefe0e6e5 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/README.md @@ -15,7 +15,7 @@ # MUltiple SIgnal Classification (MUSIC) Algorithm on AI Engine -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents @@ -41,7 +41,7 @@ This tutorial implements the Multiple Signal Classification (MUSIC) Algorithm [1] on the AI Engine. MUSIC is a popular algorithm for Direction of Arrival (DOA) estimation in antenna array systems. This tutorial assumes a system model with an 8-element uniform linear array (ULA). The algorithm chosen for AI Engine implementation operates directly on 128 x 8 data snapshots using a QR-Factorization followed by a Singular Value Decomposition (SVD) to obtain the basis vectors of the noise subspace. The QRD algorithm uses the well known modified Gram-Schmidt approach. The SVD algorithm adopts a one-sided Jacobi rotation approach with a fixed set of four iterations. -This tutorial implements the MUSIC algorithm fully in the AI Engine and validates its performance in real time hardware running on the VC1902 device (-2M speed grade) on the VCK190 evaluation board. A Hardware-in-the-Loop (HIL) demonstrator connects a host computer running MATLAB over TCP/IP to the VCK190 board that delivers buffered array snapshots to the board and receives DOA estimates back in real time to demonstrate a best effort DOA estimation throughput rate of 1 MHz. The following table summarizes the system parameters for this tutorial. +This tutorial implements the MUSIC algorithm fully in the AI Engine and validates its performance in real time hardware running on the VC1902 device (-2M speed grade) on the VCK190 evaluation board. A Hardware-in-the-Loop (HIL) demonstrator connects a host computer running MATLAB® over TCP/IP to the VCK190 board that delivers buffered array snapshots to the board and receives DOA estimates back in real time to demonstrate a best effort DOA estimation throughput rate of 1 MHz. The following table summarizes the system parameters for this tutorial. This MUSIC tutorial was co-developed by AMD and our third party partner, [Fidus Systems](https://fidus.com). @@ -291,16 +291,16 @@ Timing closure of the top-level device is achieved automatically with the standa ### Setup and Initialization -IMPORTANT: Before beginning the tutorial ensure you have installed Vitis™ 2025.1 software. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). +IMPORTANT: Before beginning the tutorial ensure you have installed Vitis™ 2025.2 software. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). Set the environment variable ```COMMON_IMAGE_VERSAL``` to the full path where you have downloaded the Common Images. Then set the environment variable ```PLATFORM_REPO_PATHS``` to the value ```$XILINX_VITIS/base_platforms```. Additional information on this process may be found [here](../../../AIE#environment-settings). The remaining environment variables are configured in the top level Makefile ```/18-MUSIC-Algorithm/Makefile``` file. ``` -RELEASE=2025.1 +RELEASE=2025.2 -PLATFORM_NAME = xilinx_vck190_base_202510_1 +PLATFORM_NAME = xilinx_vck190_base_202520_1 PLATFORM_PATH = ${PLATFORM_REPO_PATHS} export PLATFORM = ${PLATFORM_PATH}/${PLATFORM_NAME}/${PLATFORM_NAME}.xpfm @@ -464,7 +464,7 @@ Step #6: The client instance plots the received responses. ## Conclusions -This tutorial has presented a high-performance AI Engine implementation of the popular MUSIC algorithm for estimating DOA using an antenna array. The MUSIC algorithm employed here adopts a QRD/SVD approach for subspace estimation that is well matched to the AI Engine compute capacity. Software pipelining techniques are employed to create a massively parallel data flow graph across $157$ AI Engine compute tiles to implement a high-performance implementation capable of processing $128\times 8$ data snaphots at a sustained throughput rate of 1 $\mu s$ per snapshot. The full MUSIC algorithm including noise subspace basis identification, MUSIC spectrum evaluation, and null detection is implemented fully in the AI Engine array with no supporting logic from PL required. A comprehensive Hardware-in-the-Loop demonstrator system is built using an external host running Matlab to communicate to the VCK190 evaluation board over Ethernet. +This tutorial has presented a high-performance AI Engine implementation of the popular MUSIC algorithm for estimating DOA using an antenna array. The MUSIC algorithm employed here adopts a QRD/SVD approach for subspace estimation that is well matched to the AI Engine compute capacity. Software pipelining techniques are employed to create a massively parallel data flow graph across $157$ AI Engine compute tiles to implement a high-performance implementation capable of processing $128\times 8$ data snaphots at a sustained throughput rate of 1 $\mu s$ per snapshot. The full MUSIC algorithm including noise subspace basis identification, MUSIC spectrum evaluation, and null detection is implemented fully in the AI Engine array with no supporting logic from PL required. A comprehensive Hardware-in-the-Loop demonstrator system is built using an external host running MATLAB to communicate to the VCK190 evaluation board over Ethernet. ## References diff --git a/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/Makefile index b65d34b193..8168f4b4c8 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/Makefile @@ -18,7 +18,7 @@ MY_SOURCES := ${MY_APP}.cpp doa/doa.cpp doa/doa.h \ scanner/scanner_graph.h scanner/scanner.cpp scanner/scanner.h \ svd/svd_graph.h svd/svd.cpp svd/svd.h -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/doa/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/doa/Makefile index 4129047755..a8ae13efad 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/doa/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/doa/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := doa_app MY_SOURCES := ${MY_APP}.cpp doa.h doa.cpp doa_graph.h -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/finder/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/finder/Makefile index 633a3e7c29..f3b7b7866a 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/finder/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/finder/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := finder_app MY_SOURCES := ${MY_APP}.cpp finder.h finder.cpp finder_graph.h -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/io_adapter/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/io_adapter/Makefile index 9ba47bd579..0f5a2885fd 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/io_adapter/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/io_adapter/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := io_adapter_app MY_SOURCES := ${MY_APP}.cpp io_adapter_graph.h io_adapter.cpp io_adapter.h -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/qrd/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/qrd/Makefile index fa024d5ae4..930e369bb2 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/qrd/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/qrd/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := qrd_app MY_SOURCES := ${MY_APP}.cpp qrd_norm.h qrd_norm.cpp qrd_qr.cpp qrd_qr.h qrd_graph.h -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/scanner/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/scanner/Makefile index 6c95bc41ca..3a9c7053aa 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/scanner/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/scanner/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := scanner_app MY_SOURCES := ${MY_APP}.cpp scanner.h scanner.cpp scanner_graph.h -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/svd/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/svd/Makefile index 86095fbdba..0b2d580ecb 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/svd/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/aie/svd/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := svd_app MY_SOURCES := ${MY_APP}.cpp svd.h svd.cpp svd_graph.h -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/description.json b/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/description.json index a04573f033..d46297e2d0 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/description.json +++ b/AI_Engine_Development/AIE/Design_Tutorials/18-MUSIC-Algorithm/description.json @@ -23,8 +23,7 @@ } ], "targets": [ - "vitis_hw_build", - "vitis_hw_run" + "vitis_hw_build" ], "category": "canary", "make_options": [ @@ -33,11 +32,7 @@ "custom_build_target": { "all": "all" }, - "custom_board_target": "run_test", "tasks": { - "board" : { - "pre_exec" : ["./env_setup_versal.sh"] - }, "build": { "pre_exec": ["./env_setup_versal.sh"] } diff --git a/AI_Engine_Development/AIE/Design_Tutorials/19-Softmax-Function/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/19-Softmax-Function/Makefile index e1c2f96fb6..fabe897c7d 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/19-Softmax-Function/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/19-Softmax-Function/Makefile @@ -8,9 +8,9 @@ ECHO = @echo export TARGET = hw_emu -RELEASE=2025.1 +RELEASE=2025.2 BOARD=vck190 -BASE_NUM=202510_1 +BASE_NUM=202520_1 # Platform Selection... VERSAL_VITIS_PLATFORM = xilinx_${BOARD}\_base_${BASE_NUM} diff --git a/AI_Engine_Development/AIE/Design_Tutorials/19-Softmax-Function/README.md b/AI_Engine_Development/AIE/Design_Tutorials/19-Softmax-Function/README.md index c4c807d0f7..f6f5ef6442 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/19-Softmax-Function/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/19-Softmax-Function/README.md @@ -15,7 +15,7 @@ # Softmax Function -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents diff --git a/AI_Engine_Development/AIE/Design_Tutorials/19-Softmax-Function/aie/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/19-Softmax-Function/aie/Makefile index 1126416c4d..3a6ab5de5b 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/19-Softmax-Function/aie/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/19-Softmax-Function/aie/Makefile @@ -7,7 +7,7 @@ SRC_DIR := ./src MY_SOURCES := $(shell find $(SRC_DIR) -name *.cpp) $(shell find $(SRC_DIR) -name *.h) -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm diff --git a/AI_Engine_Development/AIE/Design_Tutorials/20-TDM-Mixer/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/20-TDM-Mixer/Makefile index 1fd6679a5f..f99213f6bf 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/20-TDM-Mixer/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/20-TDM-Mixer/Makefile @@ -4,11 +4,6 @@ # # Author: Mark Rollins -RELEASE=2025.1 - -PLATFORM_NAME = xilinx_vck190_base_202510_1 -PLATFORM_PATH = ${PLATFORM_REPO_PATHS} - ############## # Build Flow # ############## diff --git a/AI_Engine_Development/AIE/Design_Tutorials/20-TDM-Mixer/README.md b/AI_Engine_Development/AIE/Design_Tutorials/20-TDM-Mixer/README.md index ea6616e312..048c0bd58b 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/20-TDM-Mixer/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/20-TDM-Mixer/README.md @@ -15,7 +15,7 @@ # Time-Division Multiplexed Mixer Example -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents @@ -36,7 +36,7 @@ This tutorial targets three goals using the context of the TDM Mixer: * Show how the non-linear `sincos()` generator in each AI Engine tile can be used to vectorize workloads involving phase or frequency generation without the use of lookup tables. * Provide another example of how AI Engine code can be optimized for improved software pipelining to achieve higher throughputs through simple code refactoring. -Finally, the tutorial also uses the new Vitis Functional Simulation to run functional simulations of AI Engine designs in the Matlab context. This new flow allows the designer to feed I/O's from Matlab directly to and from the AI Engine for x86 functional simulation without the use of I/O files. This direct connection of the x86simulator to your system model context in Matlab facilitates the verification of your algorithm vectorization as you migrate your algorithms to AI Engine. +Finally, the tutorial also uses the new Vitis Functional Simulation to run functional simulations of AI Engine designs in the MATLAB® context. This new flow allows the designer to feed I/O's from MATLAB directly to and from the AI Engine for x86 functional simulation without the use of I/O files. This direct connection of the x86simulator to your system model context in MATLAB facilitates the verification of your algorithm vectorization as you migrate your algorithms to AI Engine. ## Corner-Turning using Tile DMA @@ -119,9 +119,9 @@ Note the computation in Line 61-62 involves two 8-lane vector multiplications. T ## Vitis Functional Simulation -This tutorial uses a new tool feature called Vitis Functional Simulation (VFS) to validate the TDM Mixer implementation in AI Engine against its MATLAB behavioral models. The VFS feature automatically creates "shared objects" of your AI Engine and PL HLS-based kernels in your Versal design, allowing it to be brought into familiar system-level simulation frameworks, namely MATLAB and Python. This allows functional verification of your Versal AI Engine and PL designs without leaving your preferred simulation framework and without creating I/O files for this purpose. VFS is a production tool feature in 2025.1. +This tutorial uses a new tool feature called Vitis Functional Simulation (VFS) to validate the TDM Mixer implementation in AI Engine against its MATLAB behavioral models. The VFS feature automatically creates "shared objects" of your AI Engine and PL HLS-based kernels in your Versal design, allowing it to be brought into familiar system-level simulation frameworks, namely MATLAB and Python. This allows functional verification of your Versal AI Engine and PL designs without leaving your preferred simulation framework and without creating I/O files for this purpose. -The Matlab version of VFS is used to validate the TDM Mixer functional performance. The diagram below shows the MATLAB m-code required to use VFS: +The MATLAB version of VFS is used to validate the TDM Mixer functional performance. The diagram below shows the MATLAB m-code required to use VFS: * Make sure you source `${XILINX_VITIS}/settings64.sh` before starting your MATLAB session. * Create an instance of your AI Engine graph using `vfs.aieGraph` in Line 59. diff --git a/AI_Engine_Development/AIE/Design_Tutorials/20-TDM-Mixer/aie/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/20-TDM-Mixer/aie/Makefile index d8de739968..784190a330 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/20-TDM-Mixer/aie/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/20-TDM-Mixer/aie/Makefile @@ -11,8 +11,7 @@ SIM_FIFO := false MY_APP := tdm_mixer_app MY_SOURCES := ${MY_APP}.cpp tdm_mixer_graph.h tdm_mixer.h tdm_mixer.cpp -PLATFORM_USE := xilinx_vck190_base_202510_1 -PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm +PART_USE := xcvc1902-vsva2197-2MP-e-S CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing @@ -22,7 +21,7 @@ DSPLIB_OPTS := --include=${DSPLIB_ROOT}/L2/include/aie \ AIE_OUTPUT := libadf.a -AIE_FLAGS := ${DSPLIB_OPTS} --platform=${PLATFORM} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} +AIE_FLAGS := ${DSPLIB_OPTS} --part=${PART_USE} ${MY_APP}.cpp --aie.output-archive=${AIE_OUTPUT} ifeq (${SIM_FIFO}, true) AIE_FLAGS := ${AIE_FLAGS} ${CHECK_FIFO} @@ -80,7 +79,7 @@ analyze: vitis_analyzer aiesimulator_output/default.aierun_summary throughput_ok: - @../python/check_throughput.py PLIO_o 4629.82 5.0 + @../python/check_throughput.py PLIO_o 4664.62 5.0 clean: rm -rf .Xil Work libadf.a diff --git a/AI_Engine_Development/AIE/Design_Tutorials/20-TDM-Mixer/python/check_throughput.py b/AI_Engine_Development/AIE/Design_Tutorials/20-TDM-Mixer/python/check_throughput.py index e6d387e6c8..859cfa9a0c 100755 --- a/AI_Engine_Development/AIE/Design_Tutorials/20-TDM-Mixer/python/check_throughput.py +++ b/AI_Engine_Development/AIE/Design_Tutorials/20-TDM-Mixer/python/check_throughput.py @@ -21,7 +21,7 @@ def check_throughput(args): accuracy = float(args.accuracy[0]) with open("AIESimulator.log") as file: for line in file: - regexp = plio + " .* ([\d.]+)" + regexp = plio + " .* ([\\d.]+)" match = re.search(regexp,line) if match: actual = float(match.group(1)) diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/Makefile index 443eed3d0b..e52f73027a 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/Makefile @@ -6,7 +6,7 @@ export TARGET ?= hw -PLATFORM_NAME = xilinx_vck190_base_202510_1 +PLATFORM_NAME = xilinx_vck190_base_202520_1 PLATFORM_PATH = ${PLATFORM_REPO_PATHS} export PLATFORM = ${PLATFORM_PATH}/${PLATFORM_NAME}/${PLATFORM_NAME}.xpfm diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/README.md b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/README.md index fca5a01fe9..049a5d96f0 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/README.md @@ -15,7 +15,7 @@ # Back-Projection for Synthetic Aperture Radar on AI Engines -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Abstract diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/bp_update/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/bp_update/Makefile index a4e0c7da6c..c257759ceb 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/bp_update/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/bp_update/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := bp_update_app MY_SOURCES := ${MY_APP}.cpp bp_update_graph.h bp_update.h bp_update.cpp input_combine.h input_combine.cpp -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/cos_lib/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/cos_lib/Makefile index 111545fe17..4f24d62d8c 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/cos_lib/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/cos_lib/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := cos_lib_app MY_SOURCES := ${MY_APP}.cpp cos_lib_graph.h cos_lib_lut_init.h -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/dR_comp/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/dR_comp/Makefile index 58102bfe0a..a29a9566e8 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/dR_comp/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/dR_comp/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := dR_comp_app MY_SOURCES := ${MY_APP}.cpp dR_comp_graph.h dR_comp.h dR_comp.cpp -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/diff3dsq/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/diff3dsq/Makefile index 65044bb5da..b64a29c792 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/diff3dsq/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/diff3dsq/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := diff3dsq_app MY_SOURCES := ${MY_APP}.cpp diff3dsq_graph.h diff3dsq.h diff3dsq.cpp -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/expjx/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/expjx/Makefile index 978e683564..4558c4aafe 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/expjx/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/expjx/Makefile @@ -13,7 +13,7 @@ MY_SOURCES := ${MY_APP}.cpp expjx_graph.h expjx.h expjx.cpp \ ../cos_lib/cos_lib_graph.h ../cos_lib/cos_lib_lut_init.h \ ../sin_lib/sin_lib_graph.h ../sin_lib/sin_lib_lut_init.h -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/fmod_floor/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/fmod_floor/Makefile index df2c4f7af2..aacbd0cc4e 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/fmod_floor/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/fmod_floor/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := fmod_floor_app MY_SOURCES := ${MY_APP}.cpp fmod_floor_graph.h fmod_floor.h fmod_floor.cpp -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/ifft2k_async/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/ifft2k_async/Makefile index f854be5a47..9d49017ab7 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/ifft2k_async/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/ifft2k_async/Makefile @@ -13,7 +13,7 @@ MY_SOURCES := ${MY_APP}.cpp ifft2k_async_graph.h ifft2k_async.h ifft2k_as ifft2k_async_twiddles_internal.h ifft2k_async_twiddles_external.h \ slope_offset.h slope_offset.cpp dummy_async.h dummy_async.cpp -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/interp1/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/interp1/Makefile index f2ee459e5b..8a4ada2f7c 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/interp1/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/interp1/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := interp1_app MY_SOURCES := ${MY_APP}.cpp interp1_graph.h interp1.h interp1.cpp dummy_async.h dummy_async.cpp -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/range_gen/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/range_gen/Makefile index b4cd27cbad..b27c8f1ba1 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/range_gen/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/range_gen/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := range_gen_app MY_SOURCES := ${MY_APP}.cpp range_gen_graph.h range_gen.h range_gen.cpp -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/sar_engine/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/sar_engine/Makefile index f74e933065..568467d11f 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/sar_engine/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/sar_engine/Makefile @@ -20,7 +20,7 @@ MY_SOURCES := ${MY_APP}.cpp sar_engine_graph.h \ ../bp_update/bp_update_graph.h ../bp_update/bp_update.h ../bp_update/bp_update.cpp \ ../interp1/interp1_graph.h ../interp1/interp1.h ../interp1/interp1.cpp -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/sar_top_1engine/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/sar_top_1engine/Makefile index 407923fff1..7385bee1a5 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/sar_top_1engine/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/sar_top_1engine/Makefile @@ -31,7 +31,7 @@ MY_SOURCES := ${MY_APP}.cpp ${MY_APP}_aie_routed.aiecst ${MY_APP}.aiecst ../interp1/interp1_graph.h ../interp1/interp1.h ../interp1/interp1.cpp -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/sar_top_8engine/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/sar_top_8engine/Makefile index e3b6dc40f8..327e26fb96 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/sar_top_8engine/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/sar_top_8engine/Makefile @@ -31,7 +31,7 @@ MY_SOURCES := ${MY_APP}.cpp ${MY_APP}.aiecst ${MY_APP}_aie_routed.aiecst ../interp1/interp1_graph.h ../interp1/interp1.h ../interp1/interp1.cpp -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/sin_lib/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/sin_lib/Makefile index 045c01c6ed..2fa44c4d0f 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/sin_lib/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/sin_lib/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := sin_lib_app MY_SOURCES := ${MY_APP}.cpp sin_lib_graph.h sin_lib_lut_init.h -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/sqrt_lib/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/sqrt_lib/Makefile index 3c1774c58f..2f88e377db 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/sqrt_lib/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/aie/sqrt_lib/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := sqrt_lib_app MY_SOURCES := ${MY_APP}.cpp sqrt_lib_graph.h -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/device1/host.cpp b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/device1/host.cpp index 6b134bd75a..c64509e39c 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/device1/host.cpp +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/device1/host.cpp @@ -202,9 +202,10 @@ int main(int argc, char* argv[]) std::cout << STR_PASSED << "image_bo.sync(XCL_BO_SYNC_BO_FROM_DEVICE);" << std::endl; std::cout << STR_INFO << "Done Frame " << ff << std::endl; } // ff - // If I uncomment out these lines I get a bus-error -- why??? - // my_graph0.wait(); - // std::cout << STR_PASSED << "my_graph0.wait();" << std::endl; + + my_graph0.wait(); + std::cout << STR_PASSED << "my_graph0.wait();" << std::endl; + uint64_t toc = my_graph0.get_timestamp(); my_graph0.end(); std::cout << STR_PASSED << "my_graph0.end();" << std::endl; diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/images/bp-engine-graph-view.png b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/images/bp-engine-graph-view.png index 98b94e8ca0..62fdea5306 100755 Binary files a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/images/bp-engine-graph-view.png and b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/images/bp-engine-graph-view.png differ diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/md/backproject-engine.md b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/md/backproject-engine.md index ffefc3ee45..b7f4e31c7d 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/md/backproject-engine.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/md/backproject-engine.md @@ -65,7 +65,7 @@ The floorplan view of the SAR BP engine design is shown in the following figure. ### Resource Utilization -The AI Engine resources for the SAR BP engine are shown below. The design uses 14 tiles for compute and 26 tiles overall for compute and buffering. Recall the earlier system partitioning analysis estimated a total of 31 tiles, indicating this initial provisioning was not overly aggressive. The engine requires a total of four GMIO interface ports. The memory footprint of the design is quite large but the mapper/router is able to automatically find a contention-free solution with a simple area group constraint. +The AI Engine resources for the SAR BP engine are shown below. The design uses 14 tiles for compute and 26 tiles overall for compute and buffering. Recall the earlier system partitioning analysis estimated a total of 31 tiles, indicating this initial provisioning was not overly aggressive. The engine requires a total of one GMIO and two PLIO interface ports. The memory footprint of the design is quite large but the mapper/router is able to automatically find a contention-free solution with a simple area group constraint. ![figure](../images/bp-engine-aie-resources.png) @@ -92,7 +92,7 @@ The latency of the design can be considered as the time required for processing #### Hardware -The single engine version of the design may also be run in hardware on the VCK190 evaluation board. In this case, `NPULSE_USE=586` and `NFRAME=16` to run a full 16 frames with the full compliment of radar pulses for each. Throughput is measured using the `xrt::graph::get_timestamp()` function that returns a time stamp from the AIE array. The difference between two such timestamps provides the number of AI Engine clock cycles between the them. Specifically, two time stamps are taken in [Line 178](../device1/host.cpp#L178) and [Line 208](../device1/host.cpp#L208) of `device1/host.cpp`. A screenshot of this run captured from the VCK190 board is shown below. +The single engine version of the design may also be run in hardware on the VCK190 evaluation board. In this case, `NPULSE_USE=586` and `NFRAME=16` to run a full 16 frames with the full compliment of radar pulses for each. Throughput is measured using the `xrt::graph::get_timestamp()` function that returns a time stamp from the AIE array. The difference between two such timestamps provides the number of AI Engine clock cycles between them. Specifically, two time stamps are taken in [Line 178](../device1/host.cpp#L178) and [Line 208](../device1/host.cpp#L208) of `device1/host.cpp`. A screenshot of this run captured from the VCK190 board is shown below. * Note the final throughput computed using `xrt::graph::get_timestamp()` is 2.6 frames per second. This matches well to the estimate computed from the 2-pulse simulation performed via hardware emulation. diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/md/design-builds.md b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/md/design-builds.md index 53f350506b..720959a0a8 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/md/design-builds.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/md/design-builds.md @@ -19,17 +19,17 @@ ### Setup and Initialization -IMPORTANT: Before beginning the tutorial ensure you have installed Vitis™ 2025.1 software. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). +IMPORTANT: Before beginning the tutorial ensure you have installed Vitis™ 2025.2 software. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). Set the environment variable ```COMMON_IMAGE_VERSAL``` to the full path where you have downloaded the Common Images. Then set the environment variable ```PLATFORM_REPO_PATHS``` to the value ```$XILINX_VITIS/base_platforms```. Additional information on this process may be found [here](../../../AIE#environment-settings). The remaining environment variables are configured in the top level Makefile ```/21-Back-Projection-SAR/Makefile``` file. ``` -RELEASE=2025.1 +RELEASE=2025.2 TOP_DIR ?= $(shell readlink -f .) -PLATFORM_NAME = xilinx_vck190_base_202510_1 +PLATFORM_NAME = xilinx_vck190_base_202520_1 PLATFORM_PATH = ${PLATFORM_REPO_PATHS} export PLATFORM = ${PLATFORM_PATH}/${PLATFORM_NAME}/${PLATFORM_NAME}.xpfm diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/md/multiple-engines.md b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/md/multiple-engines.md index 3616f94944..6f318f581b 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/md/multiple-engines.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/md/multiple-engines.md @@ -53,7 +53,7 @@ This section shows the device-level details of the 8-engine design. These are su ### Hardware Throughput -The 8-engine design was also run in hardware on Vthe CK190 evaluation board. Once again, `NPULSE_USE=586` and `NFRAME=16` was used to run a full 16 frames with the full compliment of radar pulses for each. The throughput was measured using the `xrt::graph::get_timestamp()` function as before. A screenshot captured from the VCK190 board run is shown below. +The 8-engine design was also run in hardware on the VCK190 evaluation board. Once again, `NPULSE_USE=586` and `NFRAME=16` was used to run a full 16 frames with the full compliment of radar pulses for each. The throughput was measured using the `xrt::graph::get_timestamp()` function as before. A screenshot captured from the VCK190 board run is shown below. * The final throughput using `xrt::graph::get_timestamp()` is 18.9 frames per second. This is only slighty lower than 8X times the frame rate achieved with the single engine, indicating the data flow remains very efficient even with eight separate engines. diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/bp_update/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/bp_update/Makefile index 6117e88b26..5123578b07 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/bp_update/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/bp_update/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := bp_update_app MY_SOURCES := ${MY_APP}.cpp bp_update_graph.h bp_update.h bp_update.cpp -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/cos_lib/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/cos_lib/Makefile index 441df87999..286c062c3f 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/cos_lib/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/cos_lib/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := cos_lib_app MY_SOURCES := ${MY_APP}.cpp cos_lib_graph.h cos_lib_lut_init.h -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/diff3dsq/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/diff3dsq/Makefile index 054306fea9..406e8e1fa3 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/diff3dsq/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/diff3dsq/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := diff3dsq_app MY_SOURCES := ${MY_APP}.cpp diff3dsq_graph.h diff3dsq.h diff3dsq.cpp -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/fmod_floor/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/fmod_floor/Makefile index fecc3b6ce0..824bb96525 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/fmod_floor/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/fmod_floor/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := fmod_floor_app MY_SOURCES := ${MY_APP}.cpp fmod_floor_graph.h fmod_floor.h fmod_floor.cpp -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/ifft4096/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/ifft4096/Makefile index 3f40f081d2..eabeebeca5 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/ifft4096/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/ifft4096/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := ifft4096_app MY_SOURCES := ${MY_APP}.cpp ifft4096_graph.h -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/sin_lib/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/sin_lib/Makefile index 3c578f14cb..10da815f61 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/sin_lib/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/sin_lib/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := sin_lib_app MY_SOURCES := ${MY_APP}.cpp sin_lib_graph.h sin_lib_lut_init.h -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/sqrt_lib/Makefile b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/sqrt_lib/Makefile index 3f88c5ccc4..a31906f1a4 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/sqrt_lib/Makefile +++ b/AI_Engine_Development/AIE/Design_Tutorials/21-Back-Projection-SAR/proto/sqrt_lib/Makefile @@ -11,7 +11,7 @@ SIM_FIFO := false MY_APP := sqrt_lib_app MY_SOURCES := ${MY_APP}.cpp sqrt_lib_graph.h -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM ?= ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm CHECK_FIFO := --aie.evaluate-fifo-depth --aie.Xrouter=disablePathBalancing diff --git a/AI_Engine_Development/AIE/Design_Tutorials/Design_Tutorials.rst b/AI_Engine_Development/AIE/Design_Tutorials/Design_Tutorials.rst index fe62ea9a24..01ea8b9ef9 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/Design_Tutorials.rst +++ b/AI_Engine_Development/AIE/Design_Tutorials/Design_Tutorials.rst @@ -60,7 +60,7 @@ The :doc:`landing page <../AIE>` of AI Engine Development contains important inf - This tutorial uses the LeNet algorithm to implement a system-level design to perform image classification using the AI Engine and PL logic, including block RAM (BRAM). The design demonstrates functional partitioning between the AI Engine and PL. It also highlights memory partitioning and hierarchy among DDR memory, PL (BRAM) and AI Engine memory. * - :doc:`Super Sampling Rate FIR Filters <./02-super_sampling_rate_fir/README>` - - The purpose of this tutorial is to provide a methodology to enable you to make appropriate choices depending on the filter characteristics, and to provide examples on how to implement Super Sampling Rate (SSR) FIR Filters on a Versal® ACAP AI Engine processor array. + - The purpose of this tutorial is to provide a methodology to enable you to make appropriate choices depending on the filter characteristics, and to provide examples on how to implement Super Sampling Rate (SSR) FIR Filters on a Versal™ Adaptive SoC AI Engine processor array. * - :doc:`Beamforming Design <./03-beamforming/README>` - This tutorial demonstrates the creation of a beamforming system running on the AI Engine, PL, and PS, and the validation of the design running on this heterogeneous domain. @@ -96,7 +96,7 @@ The :doc:`landing page <../AIE>` of AI Engine Development contains important inf - This tutorial demonstrates the steps to upgrade a 32-branch digital down-conversion chain so that it is compliant with the latest tools and coding practice. * - :doc:`Versal GeMM Implementation <./10-GeMM_AIEvsDSP/README>` - - This tutorial performs two implementations of a system-level design: one with AI Engine, and the other with RTL using the DSP Engines. In each implementation, the tutorial takes you through the hardware emulation and hardware flow in the context of a complete Versal ACAP system design. + - This tutorial performs two implementations of a system-level design: one with AI Engine, and the other with RTL using the DSP Engines. In each implementation, the tutorial takes you through the hardware emulation and hardware flow in the context of a complete Versal adaptive SoC system design. * - :doc:`Bilinear Interpolation <./11-Bilinear_Interpolation/README>` - This tutorial demonstrates how the bilinear interpolation algorithm may be efficiently implemented using AI Engines. It also provides guidance for customizing the design to function with varying image resolutions, and to take advantage of multicore processing on the AI Engine array to achieve desired throughput. diff --git a/AI_Engine_Development/AIE/Design_Tutorials/README.md b/AI_Engine_Development/AIE/Design_Tutorials/README.md index 1964401e5d..b6cdbb53f7 100644 --- a/AI_Engine_Development/AIE/Design_Tutorials/README.md +++ b/AI_Engine_Development/AIE/Design_Tutorials/README.md @@ -34,16 +34,17 @@ The **[README](../README.md)** of AI Engine Development contains important infor Super Sampling Rate FIR Filters - The purpose of this tutorial is to provide a methodology to enable you to make appropriate choices depending on the filter characteristics, and to provide examples on how to implement Super Sampling Rate (SSR) FIR Filters on a Versal® ACAP AI Engine processor array. + The purpose of this tutorial is to provide a methodology to enable you to make appropriate choices depending on the filter characteristics, and to provide examples on how to implement Super Sampling Rate (SSR) FIR Filters on a Versal™ adaptive SoC AI Engine processor array. Beamforming Design This tutorial demonstrates the creation of a beamforming system running on the AI Engine, PL, and PS, and the validation of the design running on this heterogeneous domain. + Polyphase Channelizer This tutorial demonstrates an implementation of a system-level design (such as Polyphase Channelizer) using a combination of AI Engine and PL/HLS kernels. - - + + Prime Factor FFT-1008 This Versal system example implements a 1008-pt FFT using the Prime Factor Algorithm. The design uses both AI Engine and PL kernels working cooperatively. AI Engine elements are hand-coded using AIE API. PL elements are implemented using Vitis HLS. System integration in Vitis is managed using the new v++ Unified Command Line flow. @@ -75,7 +76,7 @@ The **[README](../README.md)** of AI Engine Development contains important infor Versal GeMM Implementation - This tutorial performs two implementations of a system-level design: one with AI Engine, and the other with RTL using the DSP Engines. In each implementation, the tutorial takes you through the hardware emulation and hardware flow in the context of a complete Versal ACAP system design. + This tutorial performs two implementations of a system-level design: one with AI Engine, and the other with RTL using the DSP Engines. In each implementation, the tutorial takes you through the hardware emulation and hardware flow in the context of a complete Versal adaptive SoC system design. Bilinear Interpolation diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/01-aie_a_to_z-sourcelink.rst b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/01-aie_a_to_z-sourcelink.rst index 333e560348..34b35a6e54 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/01-aie_a_to_z-sourcelink.rst +++ b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/01-aie_a_to_z-sourcelink.rst @@ -1,5 +1,5 @@ ####################################################### -Version: Vitis 2025.1 +Version: Vitis 2025.2 ####################################################### -To view the source files for this tutorial, click `here `_. \ No newline at end of file +To view the source files for this tutorial, click `here `_. diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/03-pl_application_creation.md b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/03-pl_application_creation.md index 74544d49bd..10d836b5fd 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/03-pl_application_creation.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/03-pl_application_creation.md @@ -64,9 +64,9 @@ In this example, HLS kernels are used which bridge between memory and the AXI4-S Click ***Next*** -7. In the **Edit Settings** page select ***Vitis Kernel Flow Target*** under **flow_target** and ***Generate a Vitis XO*** under **package.output_format** and click ***Next*** +7. In the **Edit Settings** page select ***vitis*** under **flow_target** and ***xo*** under **package.output_format** and click ***Next*** - ![missing image](images/232_mm2s_comp4.jpg) + ![missing image](images/251_mm2s_comp4.jpg) 8. Click ***Finish*** diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/04-ps_application_creation_run_all.md b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/04-ps_application_creation_run_all.md index f511c2e2e1..e0b3989ffa 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/04-ps_application_creation_run_all.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/04-ps_application_creation_run_all.md @@ -31,7 +31,10 @@ In this section of the tutorial, you will learn how to build a PS bare-metal app ![missing image](images/252_ps_os.jpg) -5. Build the platform. +5. Open the platform configuration file **vitis-comp.json** and go to the Boad Support Package section for the standalone_psv_coterxa72_0 domain. Enable the **aiebaremetal** library + ![missing image](images/252_bsp.jpg) + +6. Build the platform. ## Step 2. Build the Baremetal AI Engine Control Application @@ -45,47 +48,26 @@ In this section of the tutorial, you will learn how to build a PS bare-metal app 5. Right-click the `src` folder under the **A-to-Z_app** project, and click ***Import → Files***. -6. Import the `aie_control.cpp` file from the AI Engine application project (`simple_application/build/hw/Work/ps/c_rts/aie_control.cpp`). +6. Import the `baremetal_metadata_compile.cpp` file from the AI Engine application project (`simple_application/build/hw/Work/baremetal_metadata_compile.cpp`). 7. Import `main.cpp` from the `src` folder from the git repository. - Go through the `main.cpp` file. You can see that the code is initializing the input data and the memory space for the output data. One thing to note is the use of the `.init()` and `.run()` APIs to control the AI Engine. + Go through the `main.cpp` file. You can see that the code is initializing the input data and the memory space for the output data. One thing to note is the use of the `.run()` and `.end()` APIs to control the AI Engine. ``` - printf("Starting AIE Graph\n"); - printf("Graph Initialization\n"); - mygraph.init(); - printf("Done \n"); - printf("- \n"); - printf("Running Graph for 4 iterations\n"); - mygraph.run(4); + gr.run(4); ``` There are two options to enable an AI Engine graph from a system: * Enable the graph in the PDI. This means that the graph will be started during BOOT and will run forever. - * Enable the AI Engine graph from the PS program using the `.init()` and `.run()` APIs. This is what you are using in this case. - -8. Under the **A-to-Z_app component** open **UserConfig.cmake** under **Settings**. In the **Directories** section add the following directories under **Include Paths (-I)**. - * `/simple_aie_application/src` - * `../../../workspace/simple_aie_application/build/hw/Work/ps/c_rts/` - * `$ENV{XILINX_VITIS}/aietools/include` - - ![missing image](images/232_ps_app_cfg1.jpg) - -9. Still in the **UserConfig.cmake** file, in the **Libraries** section add - - * `adf_api` under **Libraries (-l)** - * `$ENV{XILINX_VITIS}/aietools/lib/aarchnone64.o` under **Library search path (-L)** - - ![missing image](images/232_ps_app_cfg2.jpg) - + * Enable the AI Engine graph from the PS program using `.run()` APIs. This is what you are using in this case. -10. in the **Symbols** section add `__PS_BARE_METAL__` +8. Under the **A-to-Z_app component** open **UserConfig.cmake** under **Settings**. In the **Symbols** section add `__PS_BARE_METAL__` ![missing image](images/251_ps_app_cfg3.jpg) -11. Modify the Linker Script to increase the heap size for AIE library. +9. Modify the Linker Script to increase the heap size for AIE library. * In the Project Explorer, expand the A-to-z_app component. @@ -95,7 +77,7 @@ In this section of the tutorial, you will learn how to build a PS bare-metal app ![missing image](images/232_heapsize.jpg) -12. Build the A72 PS component (`A-to-Z_app`). +10. Build the A72 PS component (`A-to-Z_app`). > Note: The creation of the Vitis fixed platform and the ps application can be automated running "make ps_app" @@ -117,7 +99,7 @@ In this section of the tutorial, you will learn how to build a PS bare-metal app >**NOTE:** The option will add the line --package.defer_aie_run in the package configuration file. This is required when running the AI Engine graph from th - e PS (see the [Versal ACAP AI Engine Programming Environment User Guide (UG1076)](https://docs.amd.com/r/en-US/ug1076-ai-engine-environment/Integrating-the-Application-Using-the-Vitis-Tools-Flow)). + e PS (see the [Versal adaptive SoC AI Engine Programming Environment User Guide (UG1076)](https://docs.amd.com/r/en-US/ug1076-ai-engine-environment/Integrating-the-Application-Using-the-Vitis-Tools-Flow)). If the user is looking for a free running graph, this option should be disabled 4. In the **AI Engine section** deselect the option **Enable debug** diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/Makefile index 41fea91139..9470b52420 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/Makefile @@ -6,7 +6,7 @@ ################################################################################ # Variables needed for AMD tools version checking, PLEASE DO NOT MODIFY # ################################################################################ -REQUIRED_VERSION = 2025.1 +REQUIRED_VERSION = 2025.2 VIVADO_VERSION := $(shell vivado -version 2>/dev/null | grep "vivado ") VITIS_VERSION := $(shell vitis -version 2>/dev/null | grep "Vitis " | sed 's/\*//g') diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/README.md index 7ae11aa3c2..fdbbdbd67d 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/README.md @@ -15,9 +15,9 @@ # A to Z Bare-metal Flow -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** -This tutorial introduces a complete end-to-end flow for a bare-metal host application using AI Engines and PL kernels. The tutorial is based on the 2025.1 Vitis unified software platform. +This tutorial introduces a complete end-to-end flow for a bare-metal host application using AI Engines and PL kernels. The tutorial is based on the 2025.2 Vitis unified software platform. >**NOTE**: This tutorial has been written for multiple versions of the tools. Each version available can be found in the specific Github branch. The recommendation is to use the latest version available. diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/description.json b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/description.json index 380a7f3a0d..668a25577f 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/description.json +++ b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/description.json @@ -26,21 +26,13 @@ } ], "targets": [ - "vitis_hw_emu" + "vitis_hw_build" ], "category": "canary", "custom_build_target": { - "all": "run" - }, - "custom_board_target": "run_test", - "tasks": { - "board": { - "pre_exec": "./env_setup_versal.sh" - }, - "build": { - "pre_exec": "./env_setup_versal.sh" - } + "all": "all", + "hw":"all" } } } diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/images/232_ps_app_cfg1.jpg b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/images/232_ps_app_cfg1.jpg deleted file mode 100755 index c4dbf8ace3..0000000000 Binary files a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/images/232_ps_app_cfg1.jpg and /dev/null differ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/images/232_ps_app_cfg2.jpg b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/images/232_ps_app_cfg2.jpg deleted file mode 100755 index ce09bd6a39..0000000000 Binary files a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/images/232_ps_app_cfg2.jpg and /dev/null differ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/images/251_mm2s_comp4.jpg b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/images/251_mm2s_comp4.jpg new file mode 100755 index 0000000000..7dfd229c3c Binary files /dev/null and b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/images/251_mm2s_comp4.jpg differ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/images/252_bsp.jpg b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/images/252_bsp.jpg new file mode 100755 index 0000000000..121719bbe8 Binary files /dev/null and b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/images/252_bsp.jpg differ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/src/main.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/src/main.cpp index 1a55414fb7..2a11ec5828 100755 --- a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/src/main.cpp +++ b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/src/main.cpp @@ -41,12 +41,10 @@ #include "xil_printf.h" #include "xil_cache.h" #include "xil_io.h" -#include "sleep.h" #include "xparameters.h" - -#include "project.cpp" - +#include "xaiengine.h" +#include "aeg_baremetal_api.h" #define MM2S_BASE XPAR_XMM2S_0_BASEADDR #define S2MM_BASE XPAR_XS2MM_0_BASEADDR @@ -58,6 +56,8 @@ #define INPUT_SIZE 128 #define OUTPUT_SIZE 128 +BaremetalGraph gr("mygraph"); + int InitInputData(int32_t** in, int size) { int i; @@ -156,14 +156,8 @@ int main() printf("Done \n"); printf("- \n"); - printf("Starting AIE Graph\n"); - printf("Graph Initialization\n"); - mygraph.init(); - printf("Done \n"); - printf("- \n"); - printf("Running Graph for 4 iterations\n"); - mygraph.run(4); + gr.run(4); int checks = 1; @@ -179,6 +173,8 @@ int main() printf("Done \n"); printf("- \n"); + gr.end(); + printf("Checking Output Data: \n"); int err = 0; int32_t golden, dataIn, realTemp, imTemp; diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/vitis/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/vitis/Makefile index 3f4bb16edf..5dafdc751c 100755 --- a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/vitis/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/vitis/Makefile @@ -23,7 +23,6 @@ help:: $(ECHO) " Command to remove all the generated files." pfm:../vivado/build/xsa_platform/${XSA} - mkdir workspace vitis -s vitis_pfm.py ${VITIS_PLATFORM} ${XSA} pl_app: hls_comp vpp_link @@ -55,6 +54,8 @@ build_ps: package: vitis -s package.py ${TARGET} +all: vitis + vitis: pfm aie_app hls_comp vpp_link ps_app package run_hw_emu: ${WORKSPACE}/${HW_EMU_PKG}/launch_hw_emu.sh diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/vitis/ps_app.py b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/vitis/ps_app.py index 49ce4da567..fa2bc04a43 100755 --- a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/vitis/ps_app.py +++ b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/vitis/ps_app.py @@ -9,6 +9,8 @@ app_path= os.getcwd() +Vitis_dir = os.environ.get('XILINX_VITIS') + client = vitis.create_client() client.update_workspace(path="./workspace") @@ -18,18 +20,16 @@ if (not os.path.isdir("./workspace/"+platform_name)): platform = client.create_platform_component(name = platform_name,hw_design = "./workspace/simple_aie_application_system_project/build/hw/hw_link/binary_container_1.xsa",os = "standalone",cpu = "psv_cortexa72_0",domain_name = "standalone_psv_cortexa72_0") platform = client.get_component(name=platform_name) + domain = platform.get_domain(name="standalone_psv_cortexa72_0") + status = domain.set_lib(lib_name="aiebaremetal", path=Vitis_dir+"/data/embeddedsw/XilinxProcessorIPLib/drivers/aiebaremetal_v1_0") status = platform.build() if (not os.path.isdir("./workspace/A-to-Z_app")): comp = client.create_app_component(name="A-to-Z_app",platform = platform_path ,domain = "standalone_psv_cortexa72_0") comp = client.get_component(name="A-to-Z_app") status = comp.import_files(from_loc="../src", files=["main.cpp"], dest_dir_in_cmp = "src") - status = comp.import_files(from_loc="./workspace/simple_aie_application/build/hw/Work/ps/c_rts", files=["aie_control.cpp"], dest_dir_in_cmp = "src") - + status = comp.import_files(from_loc="./workspace/simple_aie_application/build/hw/Work", files=["baremetal_metadata_compile.cpp"], dest_dir_in_cmp = "src") comp.set_app_config(key = 'USER_COMPILE_DEFINITIONS', values = "__PS_BARE_METAL__") - comp.set_app_config(key = 'USER_INCLUDE_DIRECTORIES', values = ['../../../workspace/simple_aie_application/src','../../../workspace/simple_aie_application/build/hw/Work/ps/c_rts/','$ENV{XILINX_VITIS}/aietools/include']) - comp.set_app_config(key = 'USER_LINK_LIBRARIES', values = 'adf_api') - comp.set_app_config(key = 'USER_LINK_DIRECTORIES', values = '$ENV{XILINX_VITIS}/aietools/lib/aarchnone64.o') vitis.dispose() diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/vitis/vpp_link.py b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/vitis/vpp_link.py index a0b067ff5e..82eb7813c3 100755 --- a/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/vitis/vpp_link.py +++ b/AI_Engine_Development/AIE/Feature_Tutorials/01-aie_a_to_z/vitis/vpp_link.py @@ -12,7 +12,6 @@ args=str(sys.argv) client = vitis.create_client() -#client.set_workspace(path="./workspace") client.update_workspace(path="./workspace") if cmd_args == 1: diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/README.md index e8be691a2a..28c3995e5c 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/README.md @@ -15,24 +15,24 @@ # GMIO Tutorial -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction A GMIO port attribute is used to make external memory-mapped connections to or from the global memory. These connections are made between AI Engine kernels or programmable logic kernels and the logical global memory ports of a hardware platform design. This tutorial is designed to demonstrate how to work with the GMIO interface in AI Engine simulator and hardware flows. ->**IMPORTANT**: Before beginning the tutorial make sure you have installed the AMD Vitis™ 2025.1 software. The Vitis release includes all the embedded base platforms including the VCK190 base platform that is used in this tutorial. In addition, ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). +>**IMPORTANT**: Before beginning the tutorial make sure you have installed the AMD Vitis™ 2025.2 software. The Vitis release includes all the embedded base platforms including the VCK190 base platform that is used in this tutorial. In addition, ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). The ‘common image’ package contains a prebuilt Linux kernel and root file system that can be used with the AMD Versal™ board for embedded design development using the Vitis software platform. Before starting this tutorial, run the following steps: 1. Go to the directory where you have unzipped the Versal Common Image package. -2. In a Bash shell, run the ``/Common Images Dir/xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux`` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ``/Common Images Dir/xilinx-versal-common-v2025.1/sdk.sh``. -3. Set up your ROOTFS and IMAGE to point to the ``rootfs.ext4`` and Image files located in the ``/Common Images Dir/xilinx-versal-common-v2025.1`` directory. +2. In a Bash shell, run the ``/Common Images Dir/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux`` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ``/Common Images Dir/xilinx-versal-common-v2025.2/sdk.sh``. +3. Set up your ROOTFS and IMAGE to point to the ``rootfs.ext4`` and Image files located in the ``/Common Images Dir/xilinx-versal-common-v2025.2`` directory. 4. Set up your PLATFORM_REPO_PATHS environment variable to ``$XILINX_VITIS/base_platforms``. -This tutorial targets VCK190 production board for 2025.1 version. +This tutorial targets VCK190 production board for 2025.2 version. ## Objectives diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/perf_profile_aie_gmio/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/perf_profile_aie_gmio/Makefile index 2c06ea4b19..34ea8f4e2b 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/perf_profile_aie_gmio/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/perf_profile_aie_gmio/Makefile @@ -7,9 +7,9 @@ MODE = linux ARCH = aie ifeq ($(ARCH), aie) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm else ifeq ($(ARCH), aie-ml) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm else $(error ARCH is not supported) endif @@ -47,19 +47,19 @@ __check_defined = \ $(error Undefined $1$(if $2, ($2)))) guard-PLATFORM_REPO_PATHS: - $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202510_1) + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202520_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) ### diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/perf_profile_aie_gmio/sw/host.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/perf_profile_aie_gmio/sw/host.cpp index 41fedd5820..6da7bcfc3c 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/perf_profile_aie_gmio/sw/host.cpp +++ b/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/perf_profile_aie_gmio/sw/host.cpp @@ -8,6 +8,7 @@ SPDX-License-Identifier: MIT #include "xrt/xrt_aie.h" #include #include +#include class Timer { std::chrono::high_resolution_clock::time_point mTimeStart; public: diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/single_aie_gmio.md b/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/single_aie_gmio.md index 6dcff83212..7df6e8d816 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/single_aie_gmio.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/single_aie_gmio.md @@ -15,7 +15,7 @@ # AI Engine GMIO Programming Model -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** This example introduces the AI Engine GMIO programming model. It includes three steps: diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/single_aie_gmio/step1/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/single_aie_gmio/step1/Makefile index 53d485a957..b7ba9fbe92 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/single_aie_gmio/step1/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/single_aie_gmio/step1/Makefile @@ -6,9 +6,9 @@ TARGET = hw ARCH = aie ifeq ($(ARCH), aie) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm else ifeq ($(ARCH), aie-ml) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm else $(error ARCH is not supported) endif @@ -40,19 +40,19 @@ __check_defined = \ $(error Undefined $1$(if $2, ($2)))) guard-PLATFORM_REPO_PATHS: - $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202510_1) + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202520_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) ### diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/single_aie_gmio/step2/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/single_aie_gmio/step2/Makefile index 53d485a957..b7ba9fbe92 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/single_aie_gmio/step2/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/single_aie_gmio/step2/Makefile @@ -6,9 +6,9 @@ TARGET = hw ARCH = aie ifeq ($(ARCH), aie) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm else ifeq ($(ARCH), aie-ml) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm else $(error ARCH is not supported) endif @@ -40,19 +40,19 @@ __check_defined = \ $(error Undefined $1$(if $2, ($2)))) guard-PLATFORM_REPO_PATHS: - $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202510_1) + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202520_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) ### diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/single_aie_gmio/step3/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/single_aie_gmio/step3/Makefile index 22600abe09..feebb459a0 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/single_aie_gmio/step3/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/02-using-gmio/single_aie_gmio/step3/Makefile @@ -6,9 +6,9 @@ TARGET = hw_emu ARCH = aie ifeq ($(ARCH), aie) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm else ifeq ($(ARCH), aie-ml) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm else $(error ARCH is not supported) endif @@ -47,19 +47,19 @@ __check_defined = \ $(error Undefined $1$(if $2, ($2)))) guard-PLATFORM_REPO_PATHS: - $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202510_1) + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202520_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) ### diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/03-rtp-reconfiguration/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/03-rtp-reconfiguration/README.md index 0b43227250..08f604c754 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/03-rtp-reconfiguration/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/03-rtp-reconfiguration/README.md @@ -15,24 +15,24 @@ # Runtime Parameter Reconfiguration -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction This tutorial is designed to demonstrate how the runtime parameters (RTP) can be used during AIE execution to modify the parameters of AI Engine kernels. Both scalar and array parameters are supported. ->**IMPORTANT**: Before beginning the tutorial make sure you have installed the AMD Vitis™ 2025.1 software. The Vitis release includes all the embedded base platforms including the VCK190 base platform that is used in this tutorial. In addition, ensure that you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). +>**IMPORTANT**: Before beginning the tutorial make sure you have installed the AMD Vitis™ 2025.2 software. The Vitis release includes all the embedded base platforms including the VCK190 base platform that is used in this tutorial. In addition, ensure that you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). The ‘common image’ package contains a prebuilt Linux kernel and root file system that can be used with the AMD Versal™ board for embedded design development using Vitis tools. Before starting this tutorial, run the following steps: 1. Go to the directory where you have unzipped the Versal Common Image package. -2. In a Bash shell, run the ``/Common Images Dir/xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux`` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ``/Common Images Dir/xilinx-versal-common-v2025.1/sdk.sh``. -3. Set up your ROOTFS and IMAGE to point to the `rootfs.ext4` and Image files located in the ``/Common Images Dir/xilinx-versal-common-v2025.1`` directory. +2. In a Bash shell, run the ``/Common Images Dir/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux`` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ``/Common Images Dir/xilinx-versal-common-v2025.2/sdk.sh``. +3. Set up your ROOTFS and IMAGE to point to the `rootfs.ext4` and Image files located in the ``/Common Images Dir/xilinx-versal-common-v2025.2`` directory. 4. Set up your PLATFORM_REPO_PATHS environment variable to ``$XILINX_VITIS/base_platforms``. -This tutorial targets the VCK190 production board for the 2025.1 version. +This tutorial targets the VCK190 production board for the 2025.2 version. ## Overview diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/03-rtp-reconfiguration/async_array_rtp/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/03-rtp-reconfiguration/async_array_rtp/Makefile index aef803b769..8745d35f5f 100755 --- a/AI_Engine_Development/AIE/Feature_Tutorials/03-rtp-reconfiguration/async_array_rtp/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/03-rtp-reconfiguration/async_array_rtp/Makefile @@ -6,9 +6,9 @@ TARGET = hw_emu ARCH = aie ifeq ($(ARCH), aie) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm else ifeq ($(ARCH), aie-ml) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm else $(error ARCH is not supported) endif @@ -47,19 +47,19 @@ __check_defined = \ $(error Undefined $1$(if $2, ($2)))) guard-PLATFORM_REPO_PATHS: - $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202510_1) + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202520_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) ### diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/03-rtp-reconfiguration/async_array_rtp_read/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/03-rtp-reconfiguration/async_array_rtp_read/Makefile index aef803b769..8745d35f5f 100755 --- a/AI_Engine_Development/AIE/Feature_Tutorials/03-rtp-reconfiguration/async_array_rtp_read/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/03-rtp-reconfiguration/async_array_rtp_read/Makefile @@ -6,9 +6,9 @@ TARGET = hw_emu ARCH = aie ifeq ($(ARCH), aie) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm else ifeq ($(ARCH), aie-ml) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm else $(error ARCH is not supported) endif @@ -47,19 +47,19 @@ __check_defined = \ $(error Undefined $1$(if $2, ($2)))) guard-PLATFORM_REPO_PATHS: - $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202510_1) + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202520_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) ### diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/03-rtp-reconfiguration/async_rtp/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/03-rtp-reconfiguration/async_rtp/Makefile index aef803b769..8745d35f5f 100755 --- a/AI_Engine_Development/AIE/Feature_Tutorials/03-rtp-reconfiguration/async_rtp/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/03-rtp-reconfiguration/async_rtp/Makefile @@ -6,9 +6,9 @@ TARGET = hw_emu ARCH = aie ifeq ($(ARCH), aie) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm else ifeq ($(ARCH), aie-ml) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm else $(error ARCH is not supported) endif @@ -47,19 +47,19 @@ __check_defined = \ $(error Undefined $1$(if $2, ($2)))) guard-PLATFORM_REPO_PATHS: - $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202510_1) + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202520_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) ### diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/03-rtp-reconfiguration/sync_rtp/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/03-rtp-reconfiguration/sync_rtp/Makefile index aef803b769..8745d35f5f 100755 --- a/AI_Engine_Development/AIE/Feature_Tutorials/03-rtp-reconfiguration/sync_rtp/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/03-rtp-reconfiguration/sync_rtp/Makefile @@ -6,9 +6,9 @@ TARGET = hw_emu ARCH = aie ifeq ($(ARCH), aie) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm else ifeq ($(ARCH), aie-ml) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm else $(error ARCH is not supported) endif @@ -47,19 +47,19 @@ __check_defined = \ $(error Undefined $1$(if $2, ($2)))) guard-PLATFORM_REPO_PATHS: - $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202510_1) + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202520_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) ### diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/04-packet-switching/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/04-packet-switching/README.md index eecf47f0cc..0dc43a0f99 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/04-packet-switching/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/04-packet-switching/README.md @@ -15,7 +15,7 @@ # Packet Switching Tutorial -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** AI Engine kernels can share a single processor and execute in an interleaved manner. In addition, they can also share multiple stream connections on a single physical channel. The explicit packet switching feature allows fine-grain control over how packets are generated, distributed, and consumed in a graph computation. Explicit packet switching is typically recommended in cases where many low bandwidth streams from a common programmable logic (PL) source can be distributed to different AI Engine destinations. Similarly many low bandwidth streams from different AI Engine sources to a common PL destination can also take advantage of this feature. Because a single physical channel is shared between multiple streams, you minimize the number of AI Engine - PL interface streams used. @@ -23,18 +23,18 @@ This tutorial walks you through the steps to create buffer interface AI Engine k There is a limitation in the current version of the AI Engine tools that only integer format values are supported in data files for the AI Engine simulator. Details on the data format and how to convert data from other types to integer format are covered in steps 1 and 2. ->**IMPORTANT**: Before beginning the tutorial make sure you have installed the AMD Vitis™ software platform 2025.1. The Vitis release includes all the embedded base platforms including the VCK190 base platform that is used in this tutorial. In addition, ensure that you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). +>**IMPORTANT**: Before beginning the tutorial make sure you have installed the AMD Vitis™ software platform 2025.2. The Vitis release includes all the embedded base platforms including the VCK190 base platform that is used in this tutorial. In addition, ensure that you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). The ‘common image’ package contains a prebuilt Linux kernel and root file system that can be used with the AMD Versal™ board for embedded design development using the Vitis tools. Before starting this tutorial, run the following steps: 1. Go to the directory where you have unzipped the Versal Common Image package. -2. In a Bash shell, run the ``/**Common Images Dir**/xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux`` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ``/**Common Images Dir**/xilinx-versal-common-v2025.1/sdk.sh``. -3. Set up your ROOTFS and IMAGE to point to the `rootfs.ext4` and Image files located in the ``/**Common Images Dir**/xilinx-versal-common-v2025.1`` directory. +2. In a Bash shell, run the ``/**Common Images Dir**/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux`` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ``/**Common Images Dir**/xilinx-versal-common-v2025.2/sdk.sh``. +3. Set up your ROOTFS and IMAGE to point to the `rootfs.ext4` and Image files located in the ``/**Common Images Dir**/xilinx-versal-common-v2025.2`` directory. 4. Set up your PLATFORM_REPO_PATHS environment variable to ``$XILINX_VITIS/base_platforms``. -This tutorial targets VCK190 production board for 2025.1 version. +This tutorial targets VCK190 production board for 2025.2 version. ## Objectives diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/04-packet-switching/buffer_aie/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/04-packet-switching/buffer_aie/Makefile index c9b61598b1..9f10268914 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/04-packet-switching/buffer_aie/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/04-packet-switching/buffer_aie/Makefile @@ -6,9 +6,9 @@ TARGET = hw_emu ARCH = aie ifeq ($(ARCH), aie) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm else ifeq ($(ARCH), aie-ml) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm else $(error ARCH is not supported) endif @@ -47,19 +47,19 @@ __check_defined = \ $(error Undefined $1$(if $2, ($2)))) guard-PLATFORM_REPO_PATHS: - $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202510_1) + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202520_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) ### diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/04-packet-switching/buffer_aie_mix_int32_float_cint16/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/04-packet-switching/buffer_aie_mix_int32_float_cint16/Makefile index 5a3f101a13..970eb1b98b 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/04-packet-switching/buffer_aie_mix_int32_float_cint16/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/04-packet-switching/buffer_aie_mix_int32_float_cint16/Makefile @@ -6,9 +6,9 @@ TARGET = hw_emu ARCH = aie ifeq ($(ARCH), aie) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm else ifeq ($(ARCH), aie-ml) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm else $(error ARCH is not supported) endif @@ -47,19 +47,19 @@ __check_defined = \ $(error Undefined $1$(if $2, ($2)))) guard-PLATFORM_REPO_PATHS: - $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202510_1) + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202520_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) ### diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/04-packet-switching/pktstream_aie/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/04-packet-switching/pktstream_aie/Makefile index 47e0f3ea50..2a7b26d590 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/04-packet-switching/pktstream_aie/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/04-packet-switching/pktstream_aie/Makefile @@ -6,9 +6,9 @@ TARGET = hw_emu ARCH = aie ifeq ($(ARCH), aie) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm else ifeq ($(ARCH), aie-ml) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm else $(error ARCH is not supported) endif @@ -47,19 +47,19 @@ __check_defined = \ $(error Undefined $1$(if $2, ($2)))) guard-PLATFORM_REPO_PATHS: - $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202510_1) + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202520_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) ### all: ${XSA} ${HOST_EXE} package diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/LICENSE.txt b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/LICENSE.txt index 9f81dade70..d071efe45b 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/LICENSE.txt +++ b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/LICENSE.txt @@ -1,4 +1,4 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/Makefile index c9521ea1a2..b6c05b713c 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/Makefile @@ -1,12 +1,12 @@ # /* -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +# Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. # SPDX-License-Identifier: X11 # */ F_PROJ_ROOT ?= $(shell bash -c 'export MK_PATH=$(MK_PATH); echo $${MK_PATH%/AI_Engine_Development/*}') -ROOTFS ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/rootfs.ext4 -IMAGE ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/Image +ROOTFS ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/rootfs.ext4 +IMAGE ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/Image SDKTARGETSYSROOT ?= ${SYSROOT} # Makefile input options @@ -34,7 +34,7 @@ else endif PACKAGE_OUT = ./package.$(TARGET) -BASE_PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm +BASE_PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm # Command-line options VPP := v++ @@ -99,19 +99,19 @@ __check_defined = \ $(error Undefined $1$(if $2, ($2)))) guard-PLATFORM_REPO_PATHS: - $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202510_1) + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202520_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-aarch64-xilinx-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-aarch64-xilinx-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-aarch64-xilinx-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-aarch64-xilinx-linux) ### diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/README.md index 26625c35e1..bb8552edc1 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/README.md @@ -15,7 +15,7 @@ # AI Engine Versal Integration -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction @@ -25,19 +25,19 @@ This tutorial demonstrates creating a system design running on the AI Engine, PS This tutorial steps through software emulation, hardware emulation, and hardware flow in the context of a complete Versal adaptive SoC system integration. By default, the Makefile is set for `hw_emu`. If you need to build for `hw`, use the corresponding TARGET option as described in corresponding sections. -**IMPORTANT**: Before beginning the tutorial ensure you have installed Vitis™ 2025.1 software. The software includes all the embedded base platforms including the VCK190 base platform that is used in this tutorial. In addition, ensure you have downloaded the Common Images for Embedded Vitis Platforms from this link. +**IMPORTANT**: Before beginning the tutorial ensure you have installed Vitis™ 2025.2 software. The software includes all the embedded base platforms including the VCK190 base platform that is used in this tutorial. In addition, ensure you have downloaded the Common Images for Embedded Vitis Platforms from this link. -https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms/2025.1.html +https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms/2025.2.html The 'common image' package contains a prebuilt Linux kernel and root file system that can be used with the Versal board for embedded design development using Vitis. Before starting this tutorial run the following steps: 1. Navigate to the directory where you have unzipped the Versal Common Image package. -2. In a Bash shell, run the ```/Common Images Dir/xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux``` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ```/Common Images Dir/xilinx-versal-common-v2025.1/sdk.sh```. -3. Set up your ROOTFS, and IMAGE to point to the ```rootfs.ext4``` and Image files located in the ```/Common Images Dir/xilinx-versal-common-v2025.1``` directory. -4. Set up your PLATFORM_REPO_PATHS environment variable to ```$XILINX_VITIS/base_platforms/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm```. +2. In a Bash shell, run the ```/Common Images Dir/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux``` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ```/Common Images Dir/xilinx-versal-common-v2025.2/sdk.sh```. +3. Set up your ROOTFS, and IMAGE to point to the ```rootfs.ext4``` and Image files located in the ```/Common Images Dir/xilinx-versal-common-v2025.2``` directory. +4. Set up your PLATFORM_REPO_PATHS environment variable to ```$XILINX_VITIS/base_platforms/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm```. -This tutorial targets VCK190 production board for 2025.1 version. +This tutorial targets VCK190 production board for 2025.2 version. ## Objectives @@ -50,7 +50,7 @@ After completing this tutorial, you should be able to: * Package the design to run on software emulation, hardware emulation, and an easy-to-boot SD card image to run on hardware. * Become familiar with the new Vitis unified IDE -This tutorial contains two flows that you can work through: the Vitis classic command line flow incorporating the aiecompiler, aiesimulator, and v++ command, and the new Vitis unified IDE flow which demonstrates the use of the new tool available in the 2025.1 release as described in the *Vitis Unified IDE and Common Command-Line Reference Guide* ([UG1393](https://docs.amd.com/r/en-US/ug1393-vitis-application-acceleration/Using-the-Vitis-Unified-IDE)). The classic command-line flow is documented in the following text. The new Vitis unified IDE flow can be found [here](./unified-ide.md). +This tutorial contains two flows that you can work through: the Vitis classic command line flow incorporating the aiecompiler, aiesimulator, and v++ command, and the new Vitis unified IDE flow which demonstrates the use of the new tool available in the 2025.2 release as described in the *Vitis Unified IDE and Common Command-Line Reference Guide* ([UG1702](https://docs.amd.com/r/en-US/ug1702-vitis-accelerated-reference)). The classic command-line flow is documented in the following text. The new Vitis unified IDE flow can be found [here](./unified-ide.md). ## Tutorial Overview @@ -95,7 +95,7 @@ make aie TARGET=hw Or ```bash -v++ -c --mode aie --target hw --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm --include "$XILINX_VITIS/aietools/include" --include "./aie" --include "./data" --include "./aie/kernels" --include "./" --aie.xlopt=0 --work_dir=./Work aie/graph.cpp +v++ -c --mode aie --target hw --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm --include "$XILINX_VITIS/aietools/include" --include "./aie" --include "./data" --include "./aie/kernels" --include "./" --aie.xlopt=0 --work_dir=./Work aie/graph.cpp ``` The generated output from `aiecompiler` is the `Work` directory, and the `libadf.a` file. This file contains the compiled AI Engine configuration, graph, and Kernel `.elf` files. @@ -266,8 +266,8 @@ make kernels TARGET=hw_emu or ```bash -v++ -c --mode hls --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm --config pl_kernels/s2mm.cfg -v++ -c --mode hls --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm --config pl_kernels/mm2s.cfg +v++ -c --mode hls --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm --config pl_kernels/s2mm.cfg +v++ -c --mode hls --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm --config pl_kernels/mm2s.cfg ``` ### 2. Use V++ to Link AI Engine, HLS Kernels with the Platform @@ -293,7 +293,7 @@ make xsa TARGET=hw_emu or ```bash -v++ -l --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm s2mm.xo mm2s.xo libadf.a -t hw_emu --save-temps -g --config system.cfg -o tutorial.xsa +v++ -l --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm s2mm.xo mm2s.xo libadf.a -t hw_emu --save-temps -g --config system.cfg -o tutorial.xsa ``` Now you have a generated `.xsa` that will be used to execute your design on the platform. @@ -332,11 +332,11 @@ Or ```bash cd ./sw v++ --package -t hw_emu \ - -f $PLATFORM_REPO_PATHS/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm \ - --package.rootfs=$PLATFORM_REPO_PATHS/sw/versal/xilinx-versal-common-v2025.1/rootfs.ext4 \ + -f $PLATFORM_REPO_PATHS/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm \ + --package.rootfs=$PLATFORM_REPO_PATHS/sw/versal/xilinx-versal-common-v2025.2/rootfs.ext4 \ --package.image_format=ext4 \ --package.boot_mode=sd \ - --package.kernel_image=$PLATFORM_REPO_PATHS/sw/versal/xilinx-versal-common-v2025.1/Image \ + --package.kernel_image=$PLATFORM_REPO_PATHS/sw/versal/xilinx-versal-common-v2025.2/Image \ --package.defer_aie_run \ --package.sd_file host.exe ../tutorial.xsa ../libadf.a cd .. @@ -431,7 +431,7 @@ Since Profiling is deprecated in Hardware Emulation Flow, comment the line 'AIE_ or ```bash - v++ -l --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm s2mm.xo mm2s.xo libadf.a -t hw --save-temps -g --config system.cfg -o tutorial.xsa + v++ -l --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm s2mm.xo mm2s.xo libadf.a -t hw --save-temps -g --config system.cfg -o tutorial.xsa ``` 2. Then re-run the packaging step with: @@ -445,11 +445,11 @@ Since Profiling is deprecated in Hardware Emulation Flow, comment the line 'AIE_ ```bash cd ./sw v++ --package -t hw \ - -f $PLATFORM_REPO_PATHS/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm \ - --package.rootfs=$PLATFORM_REPO_PATHS/sw/versal/xilinx-versal-common-v2025.1/rootfs.ext4 \ + -f $PLATFORM_REPO_PATHS/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm \ + --package.rootfs=$PLATFORM_REPO_PATHS/sw/versal/xilinx-versal-common-v2025.2/rootfs.ext4 \ --package.image_format=ext4 \ --package.boot_mode=sd \ - --package.kernel_image=$PLATFORM_REPO_PATHS/sw/versal/xilinx-versal-common-v2025.1/Image \ + --package.kernel_image=$PLATFORM_REPO_PATHS/sw/versal/xilinx-versal-common-v2025.2/Image \ --package.defer_aie_run \ --package.sd_file host.exe ../tutorial.xsa ../libadf.a cd .. @@ -477,7 +477,7 @@ You should see **TEST PASSED**. You have successfully run your design on hardwar In this tutorial you learned the following: * How to compile PLIO and PL Kernels using `v++ -c`. -* How to link the `libadf.a`, PLIO, and PL kernels to the `xilinx_vck190_base_202510_1` platform. +* How to link the `libadf.a`, PLIO, and PL kernels to the `xilinx_vck190_base_202520_1` platform. * How to use Vitis Analyzer to explore the various reports generated from compilation and emulation/simulation. * How to package your host code, and the generated `xclbin` and `libadf.a` into an SD card directory. * How to execute the design for hardware emulation. diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/graph.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/graph.cpp index 555e2d6417..11dcf5031e 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/graph.cpp +++ b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/graph.cpp @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/graph.h b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/graph.h index e16f212b58..ff454bc3d4 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/graph.h +++ b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/graph.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/include.h b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/include.h index fd61914a84..d4aeb10ed2 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/include.h +++ b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/include.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels.h b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels.h index 28e8e3d526..c24676bc3b 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels.h +++ b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/classifiers/classify.cc b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/classifiers/classify.cc index 95167702bd..bc91de62a9 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/classifiers/classify.cc +++ b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/classifiers/classify.cc @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/decimators/hb27.cc b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/decimators/hb27.cc index edc84d5f23..5d80423535 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/decimators/hb27.cc +++ b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/decimators/hb27.cc @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/interpolators/hb27_2i.cc b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/interpolators/hb27_2i.cc index ceb94e6561..0f6c6aed10 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/interpolators/hb27_2i.cc +++ b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/interpolators/hb27_2i.cc @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/interpolators/hb27_2i_API.cc b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/interpolators/hb27_2i_API.cc index c29d17209a..8edcbc5a02 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/interpolators/hb27_2i_API.cc +++ b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/interpolators/hb27_2i_API.cc @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/polar_clip.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/polar_clip.cpp index a6e21c3387..162379febf 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/polar_clip.cpp +++ b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/aie/kernels/polar_clip.cpp @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/pl_kernels/mm2s.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/pl_kernels/mm2s.cpp index 34388760b1..3e85a90269 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/pl_kernels/mm2s.cpp +++ b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/pl_kernels/mm2s.cpp @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/pl_kernels/s2mm.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/pl_kernels/s2mm.cpp index db02f5abfd..16c7a3b8c8 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/pl_kernels/s2mm.cpp +++ b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/pl_kernels/s2mm.cpp @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/sw/data.h b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/sw/data.h index b84c8cba1c..2e05870ca6 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/sw/data.h +++ b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/sw/data.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/sw/host.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/sw/host.cpp index a59721886e..e62c5d43af 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/sw/host.cpp +++ b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/sw/host.cpp @@ -1,9 +1,10 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ #include +#include #include #include "experimental/xrt_kernel.h" diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/sw/host.h b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/sw/host.h index 593b8f30a2..0f26b5a81b 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/sw/host.h +++ b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/sw/host.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/system.cfg b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/system.cfg index db1b577ebf..f996b6a683 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/system.cfg +++ b/AI_Engine_Development/AIE/Feature_Tutorials/05-AI-engine-versal-integration/system.cfg @@ -1,5 +1,5 @@ ## -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +# Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. # SPDX-License-Identifier: X11 ## diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/06-versal-system-design-clocking-tutorial/06-versal-system-design-clocking-tutorial-sourcelink.rst b/AI_Engine_Development/AIE/Feature_Tutorials/06-versal-system-design-clocking-tutorial/06-versal-system-design-clocking-tutorial-sourcelink.rst deleted file mode 100644 index 7c927d6549..0000000000 --- a/AI_Engine_Development/AIE/Feature_Tutorials/06-versal-system-design-clocking-tutorial/06-versal-system-design-clocking-tutorial-sourcelink.rst +++ /dev/null @@ -1,6 +0,0 @@ - -####################################################### -Version: Vitis 2022.2 -####################################################### - -To view the source files for this tutorial, click `here `_. \ No newline at end of file diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/06-versal-system-design-clocking-tutorial/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/06-versal-system-design-clocking-tutorial/Makefile index 4cd1a57844..6d04924911 100755 --- a/AI_Engine_Development/AIE/Feature_Tutorials/06-versal-system-design-clocking-tutorial/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/06-versal-system-design-clocking-tutorial/Makefile @@ -21,9 +21,9 @@ KERNEL_XO := pl_kernels/s2mm.xo pl_kernels/mm2s.xo pl_kernels/polar_clip.xo CONFIG_FILE := system.cfg SDKTARGETSYSROOT ?= $(SYSROOT) -PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm -ROOTFS ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/rootfs.ext4 -IMAGE ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/Image +PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm +ROOTFS ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/rootfs.ext4 +IMAGE ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/Image # Command-line options VPP := v++ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/06-versal-system-design-clocking-tutorial/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/06-versal-system-design-clocking-tutorial/README.md index 8aa6969f3c..b8e3792185 100755 --- a/AI_Engine_Development/AIE/Feature_Tutorials/06-versal-system-design-clocking-tutorial/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/06-versal-system-design-clocking-tutorial/README.md @@ -15,7 +15,7 @@ # Versal System Design Clocking -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction @@ -37,16 +37,16 @@ In the design, the following clocking steps are used: | `mm2s` & `s2mm` | 150 MHz and 100 MHz (`v++ -c` & `v++ -l`) | For detailed information, see the Clocking the PL Kernels section [here](https://docs.amd.com/r/en-US/ug1076-ai-engine-environment/Clocking-the-PL-Kernels). -**IMPORTANT**: Before beginning the tutorial, make sure you have installed the Vitis 2025.1 software. The Vitis release includes all the embedded base platforms including the VCK190 base platform that is used in this tutorial. In addition, ensure you have downloaded the Common Images for Embedded Vitis Platforms from this link: The common image package contains a prebuilt Linux kernel and root file system that can be used with the AMD Versal™ board for embedded design development using Vitis. +**IMPORTANT**: Before beginning the tutorial, make sure you have installed the Vitis 2025.2 software. The Vitis release includes all the embedded base platforms including the VCK190 base platform that is used in this tutorial. In addition, ensure you have downloaded the Common Images for Embedded Vitis Platforms from this link: The common image package contains a prebuilt Linux kernel and root file system that can be used with the AMD Versal™ board for embedded design development using Vitis. Before starting this tutorial, run the following steps: 1. Go to the directory where you have unzipped the Versal Common Image package. -2. In a Bash shell, run the `/Common Images Dir/xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux` script. This script sets up the `SDKTARGETSYSROOT` and `CXX` variables. If the script is not present, you must run the `/Common Images Dir/xilinx-versal-common-v2025.1/sdk.sh`. -3. Set up your `ROOTFS` and `IMAGE` to point to the `rootfs.ext4`, and `Image` files located in the `/Common Images Dir/xilinx-versal-common-v2025.1` directory. +2. In a Bash shell, run the `/Common Images Dir/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux` script. This script sets up the `SDKTARGETSYSROOT` and `CXX` variables. If the script is not present, you must run the `/Common Images Dir/xilinx-versal-common-v2025.2/sdk.sh`. +3. Set up your `ROOTFS` and `IMAGE` to point to the `rootfs.ext4`, and `Image` files located in the `/Common Images Dir/xilinx-versal-common-v2025.2` directory. 4. Set up your `PLATFORM_REPO_PATHS` environment variable to `$XILINX_VITIS/base_platforms/`. -This tutorial targets VCK190 production board for 2025.1 version. +This tutorial targets VCK190 production board for 2025.2 version. ## Objectives @@ -78,27 +78,27 @@ In this design, you will use three kernels called: **MM2S**, **S2MM**, and **Pol Run the following commands. ```bash - v++ -c --mode hls --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202420_1 /xilinx_vck190_base_202420_1 .xpfm + v++ -c --mode hls --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202520_1 /xilinx_vck190_base_202520_1 .xpfm --freqhz=150000000 --config pl_kernels/mm2s.cfg \ - v++ -c --mode hls --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202420_1 /xilinx_vck190_base_202420_1 .xpfm + v++ -c --mode hls --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202520_1 /xilinx_vck190_base_202520_1 .xpfm --freqhz=150000000 --config pl_kernels/s2mm.cfg \ - v++ -c --mode hls --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202420_1 /xilinx_vck190_base_202420_1 .xpfm + v++ -c --mode hls --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202520_1 /xilinx_vck190_base_202520_1 .xpfm --freqhz=200000000 --config ./pl_kernels/polar_clip.cfg \ ``` OR use MHz, for example: ```bash - v++ -c --mode hls --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202420_1 /xilinx_vck190_base_202420_1 .xpfm + v++ -c --mode hls --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202520_1 /xilinx_vck190_base_202520_1 .xpfm --freqhz=150MHz --config pl_kernels/mm2s.cfg \ ``` OR prepare a config file and pass it during v++ compile, for example: ```bash - v++ -c --mode hls --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202420_1/xilinx_vck190_base_202420_1.xpfm + v++ -c --mode hls --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm --config ./pl_kernels/polar_clip.cfg \ In polar_clip.cfg: @@ -125,7 +125,7 @@ A brief explanation of the `v++` options: | `--freqhz` | Tells the Vitis compiler to use a specific clock defined by a nine digit number. Specifying this will help with the compiler make optimizations based on kernel timing.| | `--config` | to specify the kernel config file that contains settings for synthesis like top function, kernel name etc.| -For additional information, see [Vitis Compiler Command](https://docs.amd.com/r/en-US/ug1393-vitis-application-acceleration/v-Command). +For additional information, see [Vitis Compiler Command](https://docs.amd.com/r/en-US/ug1702-vitis-accelerated-reference/v-Command). After completion, you will have the `mm2s.xo`, `s2mm.xo`, and `polar_clip.xo` files ready to be used by `v++`. The host application will communicate with these kernels to read/write data into memory. @@ -160,7 +160,7 @@ Here you might notice some connectivity and clocking options. With the changes made, you can now run the following command. In v++ link command, we have three ways to direct clocking in linker stage: ```--clock-id=``` , ```--freqhz``` and ```–clock.freqHz``` ```bash - v++ --link --target hw --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202420_1/xilinx_vck190_base_202420_1.xpfm + v++ --link --target hw --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm pl_kernels/s2mm.xo pl_kernels/mm2s.xo pl_kernels/polar_clip.xo ./aie/libadf.a --freqhz=200000000:mm2s.ap_clk --freqhz=200000000:s2mm.ap_clk --config system.cfg --save-temps -o tutorial1.xsa ``` @@ -204,7 +204,7 @@ Once the linking is done, you can view clock report generated by v++ --link afte * To compile, PL kernel frequency for Polar_clip = 200 MHz (same as given in command in step 2.3) -To check the platform frequency, give command at terminal: platforminfo $PLATFORM_REPO_PATHS/xilinx_vck190_base_202420_1/xilinx_vck190_base_202420_1.xpfm +To check the platform frequency, give command at terminal: platforminfo $PLATFORM_REPO_PATHS/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm Clock frequency used by Vitis for linking are derived in following way: @@ -244,7 +244,7 @@ When the `v++` linker is complete, you can compile the host code that will run o 1. Open `./sw/host.cpp`, and familiarize yourself with the contents. Pay close attention to API calls and the comments provided. - Do take note that Xilinx Runtime [(XRT)](https://xilinx.github.io/XRT/2022.2/html/index.html) is used in the host application. This API layer is used to communicate with the PL, specifically the PLIO kernels for reading and writing data. To understand how to use this API in an AI Engine application, see [Programming the PS Host Application](https://docs.amd.com/r/en-US/ug1076-ai-engine-environment/Programming-the-PS-Host-Application). + Do take note that Xilinx Runtime [(XRT)](https://xilinx.github.io/XRT) is used in the host application. This API layer is used to communicate with the PL, specifically the PLIO kernels for reading and writing data. To understand how to use this API in an AI Engine application, see [Programming the PS Host Application](https://docs.amd.com/r/en-US/ug1076-ai-engine-environment/Programming-the-PS-Host-Application). The output size of the kernel run is half of what was allocated earlier. This is something to keep in mind. By changing the `s2mm` kernel from a 32-bit input/output to a 64-bit input/output, the kernel call will be adjusted. If this is not changed, it will hang because XRT is waiting for the full length to be processed when in reality half the count was done (even though all the data will be present). In the `host.cpp`, look at line 117 and 118 and comment them out. You should have uncommented the following line: @@ -267,7 +267,7 @@ To run the design on hardware using an SD card, you need to package all the file 2. In an easier to read command-line view, here is the command: ```bash - v++ --package --target hw --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202420_1 /xilinx_vck190_base_202420_1.xpfm \ + v++ --package --target hw --platform $PLATFORM_REPO_PATHS/xilinx_vck190_base_202520_1 /xilinx_vck190_base_202520_1.xpfm \ --package.rootfs ${ROOTFS} \ --package.kernel_image ${IMAGE} \ --package.boot_mode=sd \ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/07-AI-Engine-Floating-Point/FIRFilter/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/07-AI-Engine-Floating-Point/FIRFilter/Makefile index 86c972da93..7ec45d47ae 100755 --- a/AI_Engine_Development/AIE/Feature_Tutorials/07-AI-Engine-Floating-Point/FIRFilter/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/07-AI-Engine-Floating-Point/FIRFilter/Makefile @@ -7,7 +7,7 @@ TARGET = hw_emu HOST_EXE = host.exe -PFM_NAME := xilinx_vck190_base_202510_1 +PFM_NAME := xilinx_vck190_base_202520_1 PFM_NAME := $(strip $(PFM_NAME)) PLATFORM := ${PLATFORM_REPO_PATHS}/${PFM_NAME}/${PFM_NAME}.xpfm diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/07-AI-Engine-Floating-Point/MatMult/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/07-AI-Engine-Floating-Point/MatMult/Makefile index 1c63698eb1..d376425c6c 100755 --- a/AI_Engine_Development/AIE/Feature_Tutorials/07-AI-Engine-Floating-Point/MatMult/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/07-AI-Engine-Floating-Point/MatMult/Makefile @@ -7,7 +7,7 @@ TARGET = hw_emu HOST_EXE = host.exe -PFM_NAME := xilinx_vck190_base_202510_1 +PFM_NAME := xilinx_vck190_base_202520_1 PFM_NAME := $(strip $(PFM_NAME)) PLATFORM := ${PLATFORM_REPO_PATHS}/${PFM_NAME}/${PFM_NAME}.xpfm diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/07-AI-Engine-Floating-Point/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/07-AI-Engine-Floating-Point/README.md index 48307ac41c..a7e72efcb9 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/07-AI-Engine-Floating-Point/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/07-AI-Engine-Floating-Point/README.md @@ -15,7 +15,7 @@ # Using Floating-Point in the AI Engine -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction @@ -26,10 +26,10 @@ The ‘common image’ package contains a prebuilt Linux kernel and root file sy Before starting this tutorial, run the following steps: 1. Go to the directory where you have unzipped the Versal Common Image package. -2. In a Bash shell, run the `/Common Images Dir/xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux` script. This script sets up the `SDKTARGETSYSROOT` and `CXX` variables. If the script is not present, run the `/Common Images Dir/xilinx-versal-common-v2025.1/sdk.sh`. -3. Set up your `ROOTFS`, and `IMAGE` to point to the `rootfs.ext4` and `Image` files located in the `/Common Images Dir/xilinx-versal-common-v2025.1` directory. +2. In a Bash shell, run the `/Common Images Dir/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux` script. This script sets up the `SDKTARGETSYSROOT` and `CXX` variables. If the script is not present, run the `/Common Images Dir/xilinx-versal-common-v2025.2/sdk.sh`. +3. Set up your `ROOTFS`, and `IMAGE` to point to the `rootfs.ext4` and `Image` files located in the `/Common Images Dir/xilinx-versal-common-v2025.2` directory. 4. Set up your `PLATFORM_REPO_PATHS` environment variable to `$XILINX_VITIS/base_platforms/`. -This tutorial targets the VCK190 production board for 2025.1 version. +This tutorial targets the VCK190 production board for 2025.2 version. @@ -134,16 +134,16 @@ for (i = 0 ; i < 8 ; i++) All values in hexadecimal: -| ret
Index
(Lane) | | xbuf
Start | xbuf
Offset | Final
xbuf
Index | | zbuf
Start | zbuf
Offset | Final
zbuf
Index | -| :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | -| 0 | | 2 | B | D | | 7 | 0 | 7 | -| 1 | | 2 | C | E | | 7 | 1 | 8 | -| 2 | | 2 | D | F | | 7 | 2 | 9 | -| 3 | | 2 | E | 10 | | 7 | 3 | A | -| 4 | | 2 | F | 11 | | 7 | 4 | B | -| 5 | | 2 | 0 | 2 | | 7 | 5 | C | -| 6 | | 2 | 1 | 3 | | 7 | 6 | D | -| 7 | | 2 | 2 | 4 | | 7 | 7 | E | +| ret
Index
(Lane) | xbuf
Start | xbuf
Offset | Final
xbuf
Index | zbuf
Start | zbuf
Offset | Final
zbuf
Index | +| :---: | :---: | :---: | :---: | :---: | :---: | :---: | +| 0 | 2 | B | D | 7 | 0 | 7 | +| 1 | 2 | C | E | 7 | 1 | 8 | +| 2 | 2 | D | F | 7 | 2 | 9 | +| 3 | 2 | E | 10 | 7 | 3 | A | +| 4 | 2 | F | 11 | 7 | 4 | B | +| 5 | 2 | 0 | 2 | 7 | 5 | C | +| 6 | 2 | 1 | 3 | 7 | 6 | D | +| 7 | 2 | 2 | 4 | 7 | 7 | E | #### fpneg, fpabs, fpadd, fpsub diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/README.md index 8f77e759a3..ebc01e415c 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/README.md @@ -15,7 +15,7 @@ # DSP Library Tutorial -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction @@ -23,13 +23,13 @@ Versal™ adaptive SoCs combine programmable logic (PL), processing system (PS), This tutorial demonstrates how to use kernels provided by the DSP Library for a filtering application, how to analyze the design results, and how to use filter parameters to optimize the design's performance using simulation. It does not take the design to a hardware implementation, however. -**IMPORTANT**: Before beginning the tutorial, make sure that you have read and followed the *Vitis Software Platform Release Notes* (v2025.1) for setting up the software and installing the VCK190 base platform. +**IMPORTANT**: Before beginning the tutorial, make sure that you have read and followed the *Vitis Software Platform Release Notes* (v2025.2) for setting up the software and installing the VCK190 base platform. Before starting this tutorial, run the following steps. -1. Set up your platform by running the `xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux` script as provided in the platform download. This script sets up the `SYSROOT` and `CXX` variables. If the script is not present, you _must_ run `xilinx-versal-common-v2025.1/sdk.sh`. -2. Set up your ROOTFS to point to the `xilinx-versal-common-v2025.1/rootfs.ext4`. -3. Set up your IMAGE to point to `xilinx-versal-common-v2025.1/Image`. +1. Set up your platform by running the `xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux` script as provided in the platform download. This script sets up the `SYSROOT` and `CXX` variables. If the script is not present, you _must_ run `xilinx-versal-common-v2025.2/sdk.sh`. +2. Set up your ROOTFS to point to the `xilinx-versal-common-v2025.2/rootfs.ext4`. +3. Set up your IMAGE to point to `xilinx-versal-common-v2025.2/Image`. 4. Set up your `PLATFORM_REPO_PATHS` environment variable based upon where you downloaded the platform. 5. Download the Vitis Libraries from https://github.com/Xilinx/Vitis_Libraries For example: `git clone https://github.com/Xilinx/Vitis_Libraries.git` into your desired directory. @@ -345,7 +345,7 @@ Selecting the **Array** option on the navigation bar shows the physical implemen ![Vitis Analyzer Array](images/DSPLib_tutorial_part_3_Vitis_Analyzer_Array.png) -Selecting the **Trace** option on the navigation bar now shows the channel filter tiles ((18,0) through (22,0)) almost fully occupied with processing the data; the computational load between the channel filter's constituent engines now matching that of the halfband filter (23,0). The design now completes in 8 iterations in ~20 microseconds, compared to ~43. +Selecting the **Trace** option on the navigation bar now shows the channel filter tiles ((18,0) through (22,0)) almost fully occupied with processing the data; the computational load between the channel filter's constituent engines now matching that of the halfband filter (23,0). The design now completes in 8 iterations in ~20 microseconds, compared to ~44. Note: Please ensure that when using trace view, you examine the waveform within the 0 to 25 us range. diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/images/DSPLib_tutorial_part_2_Vitis_Analyzer_Trace.png b/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/images/DSPLib_tutorial_part_2_Vitis_Analyzer_Trace.png index f2baeefb42..de2fecb6af 100644 Binary files a/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/images/DSPLib_tutorial_part_2_Vitis_Analyzer_Trace.png and b/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/images/DSPLib_tutorial_part_2_Vitis_Analyzer_Trace.png differ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/images/DSPLib_tutorial_part_3_Vitis_Analyzer_Array.png b/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/images/DSPLib_tutorial_part_3_Vitis_Analyzer_Array.png index 0ef5505e76..09a33f3ae3 100644 Binary files a/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/images/DSPLib_tutorial_part_3_Vitis_Analyzer_Array.png and b/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/images/DSPLib_tutorial_part_3_Vitis_Analyzer_Array.png differ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/images/DSPLib_tutorial_part_3_Vitis_Analyzer_Trace.png b/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/images/DSPLib_tutorial_part_3_Vitis_Analyzer_Trace.png index d22f7777c7..cf66d81471 100644 Binary files a/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/images/DSPLib_tutorial_part_3_Vitis_Analyzer_Trace.png and b/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/images/DSPLib_tutorial_part_3_Vitis_Analyzer_Trace.png differ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/part_1/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/part_1/Makefile index d5301c37a1..5bfeb71996 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/part_1/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/part_1/Makefile @@ -12,7 +12,7 @@ AIE_DATA_DIR := $(PWD)/data AIE_GRAPH_FILES := $(AIE_SRC_DIR)/test.cpp -PFM_NAME := xilinx_vck190_base_202510_1 +PFM_NAME := xilinx_vck190_base_202520_1 PLATFORM := $(PLATFORM_REPO_PATHS)/$(PFM_NAME)/$(PFM_NAME).xpfm diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/part_2/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/part_2/Makefile index 5654cc7678..fc81931ee9 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/part_2/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/part_2/Makefile @@ -11,7 +11,7 @@ AIE_DATA_DIR := $(PWD)/data AIE_GRAPH_FILES := $(AIE_SRC_DIR)/test.cpp -PFM_NAME := xilinx_vck190_base_202510_1 +PFM_NAME := xilinx_vck190_base_202520_1 PLATFORM := $(PLATFORM_REPO_PATHS)/$(PFM_NAME)/$(PFM_NAME).xpfm diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/part_3/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/part_3/Makefile index 33b6804925..ff8392745f 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/part_3/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/08-dsp-library/part_3/Makefile @@ -11,7 +11,7 @@ AIE_DATA_DIR := $(PWD)/data AIE_GRAPH_FILES := $(AIE_SRC_DIR)/test.cpp -PFM_NAME := xilinx_vck190_base_202510_1 +PFM_NAME := xilinx_vck190_base_202520_1 PLATFORM := $(PLATFORM_REPO_PATHS)/$(PFM_NAME)/$(PFM_NAME).xpfm diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/09-debug-walkthrough/Hardware/Makefile.host_profile b/AI_Engine_Development/AIE/Feature_Tutorials/09-debug-walkthrough/Hardware/Makefile.host_profile index 8377fca6e0..ff3ccda103 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/09-debug-walkthrough/Hardware/Makefile.host_profile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/09-debug-walkthrough/Hardware/Makefile.host_profile @@ -5,8 +5,8 @@ F_PROJ_ROOT ?= $(shell bash -c 'export MK_PATH=$(MK_PATH); echo $${MK_PATH%/AI_Engine_Development/*}') -ROOTFS ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/rootfs.ext4 -IMAGE ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/Image +ROOTFS ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/rootfs.ext4 +IMAGE ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/Image SDKTARGETSYSROOT ?= ${SYSROOT} # Makefile input options @@ -75,16 +75,16 @@ guard-PLATFORM_REPO_PATHS: $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202420_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-aarch64-xilinx-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-aarch64-xilinx-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-aarch64-xilinx-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-aarch64-xilinx-linux) ### diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/09-debug-walkthrough/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/09-debug-walkthrough/README.md index a149218590..3341f78b4c 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/09-debug-walkthrough/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/09-debug-walkthrough/README.md @@ -15,7 +15,7 @@ # AI Engine Debug Walkthrough Tutorial - From Simulation to Hardware -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction @@ -34,16 +34,16 @@ Techniques to uncover both functional and performance level bugs are described i Source level debug includes visibility into the register contents view, variable values view, breakpoints view, and hence, necessitates a GUI. The Vitis integrated design environment (IDE) is the tool that supports these debug requirements. This tutorial demonstrates how to use the Vitis IDE to manage these challenges and additional tools and methodologies to assist with your design debug. ->**IMPORTANT**: Before beginning the tutorial, make sure you have installed the Vitis 2025.1 software. The Vitis release includes all the embedded base platforms including the VCK190 base platform that is used in this tutorial. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from this link: . +>**IMPORTANT**: Before beginning the tutorial, make sure you have installed the Vitis 2025.2 software. The Vitis release includes all the embedded base platforms including the VCK190 base platform that is used in this tutorial. Ensure you have downloaded the Common Images for Embedded Vitis Platforms from this link: . The `common image` package contains a prebuilt Linux kernel and root file system that can be used with a Versal adaptive SoC board for embedded design development using Vitis. Before starting this tutorial, run the following steps: 1. Go to the directory where you have unzipped the Versal Common Image package. -2. In a Bash shell, run `/Common Images Dir/xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux script`. This script sets up the `SDKTARGETSYSROOT` and `CXX` variables. If the script is not present, you must run `/Common Images Dir/xilinx-versal-common-v2025.1/sdk.sh`. -3. Set up your `ROOTFS` and `IMAGE` to point to the `rootfs.ext4` and `Image` files located in the `/Common Images Dir/xilinx-versal-common-v2025.1` directory. +2. In a Bash shell, run `/Common Images Dir/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux script`. This script sets up the `SDKTARGETSYSROOT` and `CXX` variables. If the script is not present, you must run `/Common Images Dir/xilinx-versal-common-v2025.2/sdk.sh`. +3. Set up your `ROOTFS` and `IMAGE` to point to the `rootfs.ext4` and `Image` files located in the `/Common Images Dir/xilinx-versal-common-v2025.2` directory. 4. Set up your PLATFORM_REPO_PATHS environment variable to `$XILINX_VITIS/base_platforms`. -This tutorial targets a 2025.1 VCK190 production board. +This tutorial targets a 2025.2 VCK190 production board. ## Example Design: Peak Detector diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/09-debug-walkthrough/cmd_src/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/09-debug-walkthrough/cmd_src/Makefile index 8f84fb31f4..2d9ade0347 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/09-debug-walkthrough/cmd_src/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/09-debug-walkthrough/cmd_src/Makefile @@ -5,8 +5,8 @@ F_PROJ_ROOT ?= $(shell bash -c 'export MK_PATH=$(MK_PATH); echo $${MK_PATH%/AI_Engine_Development/*}') -ROOTFS ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/rootfs.ext4 -IMAGE ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/Image +ROOTFS ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/rootfs.ext4 +IMAGE ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/Image SDKTARGETSYSROOT ?= ${SYSROOT} # Makefile input options @@ -27,7 +27,7 @@ EXECUTABLE = host.exe PACKAGE_OUT = ./package.$(TARGET) -BASE_PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm +BASE_PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm # Command-line options VPP := v++ @@ -73,19 +73,19 @@ __check_defined = \ $(error Undefined $1$(if $2, ($2)))) guard-PLATFORM_REPO_PATHS: - $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202510_1) + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202520_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-aarch64-xilinx-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-aarch64-xilinx-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-aarch64-xilinx-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-aarch64-xilinx-linux) ### diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/README.md index a0b2b70686..ee7792b46c 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/README.md @@ -15,7 +15,7 @@ # Designing with the AI Engine DSPLib and Vitis Model Composer -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction @@ -26,11 +26,11 @@ The purpose of this tutorial is to provide hands-on experience for designing AI Install the tools: * Get and install [MATLAB and Simulink](https://www.mathworks.com/products/get-matlab.html?s_tid=gn_getml). - * The following MATLAB releases are supported: R2024a, R2024b, R2025a. + * The following MATLAB releases are supported: R2024a, R2024b, R2025a, R2025b. * Do not forget to also install the DSP System Toolbox (necessary for this tutorial). -* Get and install [AMD Vitis 2025.1](https://www.xilinx.com/support/download.html). +* Get and install [AMD Vitis 2025.2](https://www.xilinx.com/support/download.html). ->**IMPORTANT**: Before beginning the tutorial, make sure you have read and followed the *Vitis Software Platform Release Notes* (v2025.1) for setting up software and installing the VCK190 base platform. +>**IMPORTANT**: Before beginning the tutorial, make sure you have read and followed the *Vitis Software Platform Release Notes* (v2025.2) for setting up software and installing the VCK190 base platform. ## Overview @@ -198,18 +198,20 @@ These are there to help you if you cannot complete any of the four stages. Notice that before implementing the Decimation Filter the vector length was ``2048``, but after implementation this is reduced to ``1024``. 16. Update the design with the other three filters using the following parameters: + + +| **Parameter** | **HB1** | **HB2** | **HB3** | **Channel Filter** | +|-----------------------------------|----------------------------|----------------------------|----------------------------|----------------------------| +| Filter Block | FIR Halfband Decimator | FIR Halfband Decimator | FIR Halfband Decimator | FIR Asymmetric Filter | +| Input/Output Data Type | `cint16` | `cint16` | `cint16` | `cint16` | +| Filter Coefficients Data Type | `int16` | `int16` | `int16` | `int16` | +| Filter Coefficients | `hb1_aie` | `hb2_aie` | `hb3_aie` | `cfi` | +| Filter Length | N/A | N/A | N/A | `length(cfi)` | +| Input Window Size (samples) | 2048 | 1024 | 512 | 256 | +| Scale Output Down by 2^ | `Shift1` | `Shift2` | `Shift3` | `ShiftCF` | +| Rounding Mode | `floor` | `floor` | `floor` | `floor` | +| Saturation Mode | `0-None` | `0-None` | `0-None` | `0-None` | - | Parameter |HB1 | HB2 | HB3 | Channel Filter | - | :--- | :--- | :--- | :--- | :--- | - | Filter Block | FIR Halfband Decimator | FIR Halfband Decimator | FIR Halfband Decimator | FIR Asymmetric Filter | - | Input Output data type | cint16 | cint16 | cint16 | cint16 | - | Filter Coefficients Data Type | int16 | int16 | int16 | int16 | - | Filter Coefficients | hb1_aie | hb2_aie | hb3_aie | cfi | - | Filter Length | N/A | N/A | N/A | length(cfi) | - | Input window size (Number of samples) | 2048 | 1024 | 512 | 256 | - | Scale output down by 2^ | Shift1 | Shift2 | Shift3 | ShiftCF | - | Rounding mode | floor | floor | floor | floor | - | Saturation mode | 0-None | 0-None | 0-None | 0-None | 17. Update the **Output Size** parameter of the **To Fixed Size** block to ``256``. The design should display like as follows: @@ -276,7 +278,7 @@ In this stage, you will generate the graph code of this design and perform bit-t 2. Double-click the block **Model Composer Hub** and click on the **Code Generation** tab. 3. Select the **FIRchain** subsystem, and set the following parameters on the **Analyze** tab: * Check **Collect profiling statistics and enable 'printf' for debugging**. - * Check **Collect trace data for Vitis Analyzer and viewing internal signals**. + * Check **Collect trace data for Vitis Analyzer, view internal signals, and latency**. 4. Click **Analyze**. The Simulink design is run to generate the testbench, then the graph code is generated and compiled. The source code can be viewed in ``./code/ip/FIRchain/src/FIRchain.h``: @@ -286,18 +288,18 @@ The Simulink design is run to generate the testbench, then the graph code is gen #define __XMC_FIRCHAIN_H__ #include -#include "./FIR_Halfband_Decimator_7c26216f/FIR_Halfband_Decimator_7c26216f.h" -#include "./FIR_Halfband_Decimator_c4185433/FIR_Halfband_Decimator_c4185433.h" -#include "./FIR_Halfband_Decimator_69968948/FIR_Halfband_Decimator_69968948.h" -#include "./FIR_Asymmetric_4303455c/FIR_Asymmetric_4303455c.h" +#include "./FIR_Halfband_Decimator_e52f70d5/FIR_Halfband_Decimator_e52f70d5.h" +#include "./FIR_Halfband_Decimator_5d110589/FIR_Halfband_Decimator_5d110589.h" +#include "./FIR_Halfband_Decimator_f09fd8f2/FIR_Halfband_Decimator_f09fd8f2.h" +#include "./FIR_Asymmetric_da0a14e6/FIR_Asymmetric_da0a14e6.h" #include "aiecode_src/FreqShift.h" class FIRchain_base : public adf::graph { public: - FIR_Halfband_Decimator_7c26216f FIR_Halfband_Decimator; - FIR_Halfband_Decimator_c4185433 FIR_Halfband_Decimator1; - FIR_Halfband_Decimator_69968948 FIR_Halfband_Decimator2; - FIR_Asymmetric_4303455c FIR_Asymmetric; + FIR_Halfband_Decimator_e52f70d5 FIR_Halfband_Decimator; + FIR_Halfband_Decimator_5d110589 FIR_Halfband_Decimator1; + FIR_Halfband_Decimator_f09fd8f2 FIR_Halfband_Decimator2; + FIR_Asymmetric_da0a14e6 FIR_Asymmetric; adf::kernel FreqShift_0; public: @@ -317,8 +319,10 @@ public: adf::connect net1 (FIR_Halfband_Decimator.out[0], FIR_Halfband_Decimator1.in[0]); adf::connect net2 (FIR_Halfband_Decimator1.out[0], FIR_Halfband_Decimator2.in[0]); adf::connect net3 (FIR_Halfband_Decimator2.out[0], FIR_Asymmetric.in[0]); - adf::connect< adf::window<1024> > net4 (FIR_Asymmetric.out[0], FreqShift_0.in[0]); - adf::connect< adf::window<1024> > net5 (FreqShift_0.out[0], Out1); + adf::connect net4 (FIR_Asymmetric.out[0], FreqShift_0.in[0]); + adf::dimensions(FreqShift_0.in[0]) = {256}; + adf::connect net5 (FreqShift_0.out[0], Out1); + adf::dimensions(FreqShift_0.out[0]) = {256}; } }; diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/VMC_DSPLib_Solution_Stage2.slx b/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/VMC_DSPLib_Solution_Stage2.slx index 8934fa3460..c8c7c8df5e 100644 Binary files a/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/VMC_DSPLib_Solution_Stage2.slx and b/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/VMC_DSPLib_Solution_Stage2.slx differ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/VMC_DSPLib_Solution_Stage3.slx b/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/VMC_DSPLib_Solution_Stage3.slx index fdbf7e687e..0ae0d531b5 100644 Binary files a/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/VMC_DSPLib_Solution_Stage3.slx and b/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/VMC_DSPLib_Solution_Stage3.slx differ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/VMC_DSPLib_Solution_Stage4.slx b/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/VMC_DSPLib_Solution_Stage4.slx index 7a6739772e..c2c398be0e 100644 Binary files a/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/VMC_DSPLib_Solution_Stage4.slx and b/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/VMC_DSPLib_Solution_Stage4.slx differ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/aiecode_src/FreqShift.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/aiecode_src/FreqShift.cpp index bedc16b776..8e714b1611 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/aiecode_src/FreqShift.cpp +++ b/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/aiecode_src/FreqShift.cpp @@ -8,7 +8,9 @@ SPDX-License-Identifier: X11 * */ -#include +#include +#include +#include // Definition of the 2 constants 1 and 1/sqrt(2) #define One 16384 @@ -22,20 +24,87 @@ alignas (32) int16_t cos_sin[16] = // FRAME_LENGTH should be a power of 2 greater than or equal to 32 template -void FreqShift(input_window_cint16 * __restrict in, output_window_cint16 * __restrict out) +void FreqShift(adf::input_buffer& __restrict in, + adf::output_buffer& __restrict out) { - v8cint16 coeffs = *(v8cint16*) cos_sin; - - v8cint16 data = undef_v8cint16(); - v8cacc48 acc; + // Load sine-cosine values to this kernel + aie::vector coeffs = aie::load_v<8>((cint16*)cos_sin); + + // Placeholder vectors for incoming data and multiplication product + aie::vector data; + aie::accum acc; + + // Pointers to 8-element vectors from input and output + auto pi1 = aie::begin_vector_circular<8>(in); + auto po1 = aie::begin_vector_circular<8>(out); + + // Loop over the input frame in 8 element chunks + for(unsigned i = 0; i < FRAME_LENGTH/8; i++) + chess_prepare_for_pipelining + chess_loop_range(4,) + { + // Get 8 samples from input + data = *pi1++; + + // Frequency shift: Element-wise multiplication with sine-cosine + acc = aie::mul(data,coeffs); + + // Send 8 samples to output with bit shift + *po1++ = srs(acc,ACC_SHIFT); + } +} +// SSR=8 implementation: we need to interleave the input streams +template +void FreqShift8(adf::input_buffer& __restrict in1, + adf::input_buffer& __restrict in2, + adf::input_buffer& __restrict in3, + adf::input_buffer& __restrict in4, + adf::input_buffer& __restrict in5, + adf::input_buffer& __restrict in6, + adf::input_buffer& __restrict in7, + adf::input_buffer& __restrict in8, + adf::output_buffer& __restrict out) +{ + // Load sine-cosine values to this kernel + aie::vector coeffs = aie::load_v<8>((cint16*)cos_sin); + + // Placeholder vectors for incoming data and multiplication product + aie::vector data; + aie::accum acc; + + // Pointers to single element from each input + cint16 * __restrict pi1 = in1.data(); + cint16 * __restrict pi2 = in2.data(); + cint16 * __restrict pi3 = in3.data(); + cint16 * __restrict pi4 = in4.data(); + cint16 * __restrict pi5 = in5.data(); + cint16 * __restrict pi6 = in6.data(); + cint16 * __restrict pi7 = in7.data(); + cint16 * __restrict pi8 = in8.data(); + + // Pointer to 8-element vector from output + auto po1 = aie::begin_vector<8>(out); + + // Loop over the input frame in 8 element chunks for(unsigned i=0; i(ACC_SHIFT); } - -} +} \ No newline at end of file diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/aiecode_src/FreqShift.h b/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/aiecode_src/FreqShift.h index a86e92e2ae..908b0fb540 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/aiecode_src/FreqShift.h +++ b/AI_Engine_Development/AIE/Feature_Tutorials/10-aie-dsp-lib-model-composer/aiecode_src/FreqShift.h @@ -6,4 +6,16 @@ SPDX-License-Identifier: X11 #include template -void FreqShift(input_window_cint16 * __restrict in, output_window_cint16 * __restrict out); +void FreqShift(adf::input_buffer& __restrict in, + adf::output_buffer& __restrict out); + +template +void FreqShift8(adf::input_buffer& __restrict in1, + adf::input_buffer& __restrict in2, + adf::input_buffer& __restrict in3, + adf::input_buffer& __restrict in4, + adf::input_buffer& __restrict in5, + adf::input_buffer& __restrict in6, + adf::input_buffer& __restrict in7, + adf::input_buffer& __restrict in8, + adf::output_buffer& __restrict out); \ No newline at end of file diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/11-ai-engine-emulation-waveform-analysis/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/11-ai-engine-emulation-waveform-analysis/Makefile index 323fd205d8..5862d6fa92 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/11-ai-engine-emulation-waveform-analysis/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/11-ai-engine-emulation-waveform-analysis/Makefile @@ -5,10 +5,10 @@ XF_PROJ_ROOT ?= $(shell bash -c 'export MK_PATH=$(MK_PATH); echo $${MK_PATH%/AI_Engine_Development/*}') -ROOTFS = ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/rootfs.ext4 -IMAGE = ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/Image +ROOTFS = ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/rootfs.ext4 +IMAGE = ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/Image SDKTARGETSYSROOT ?= ${SYSROOT} -BASE_PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm +BASE_PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm # Makefile input options @@ -65,16 +65,16 @@ guard-PLATFORM_REPO_PATHS: $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_es1_base_202120_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-aarch64-xilinx-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-aarch64-xilinx-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-aarch64-xilinx-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-aarch64-xilinx-linux) ### diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/11-ai-engine-emulation-waveform-analysis/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/11-ai-engine-emulation-waveform-analysis/README.md index 67b15135d4..e42eaae031 100755 --- a/AI_Engine_Development/AIE/Feature_Tutorials/11-ai-engine-emulation-waveform-analysis/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/11-ai-engine-emulation-waveform-analysis/README.md @@ -15,7 +15,7 @@ # Versal Emulation Waveform Analysis -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction @@ -25,16 +25,16 @@ This tutorial demonstrates how you can use the AMD Vivado™ Design Suite logic It is strongly recommended to go through the **Versal Integration tutorial** and the **Versal System Design Clocking tutorial** before running this tutorial. -**IMPORTANT**: Before beginning the tutorial, make sure you have installed the Vitis 2025.1 software. The Vitis release includes all the embedded base platforms including the VCK190 base platform that is used in this tutorial. In addition, ensure you have downloaded the Common Images for Embedded Vitis Platforms from this link: The common image package contains a prebuilt Linux kernel and root file system that can be used with the Versal board for embedded design development using Vitis. +**IMPORTANT**: Before beginning the tutorial, make sure you have installed the Vitis 2025.2 software. The Vitis release includes all the embedded base platforms including the VCK190 base platform that is used in this tutorial. In addition, ensure you have downloaded the Common Images for Embedded Vitis Platforms from this link: The common image package contains a prebuilt Linux kernel and root file system that can be used with the Versal board for embedded design development using Vitis. Before starting this tutorial run the following steps: 1. Go to the directory where you have unzipped the Versal Common Image package. -2. In a Bash shell run the `/Common Images Dir/xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux` script. This script sets up the `SDKTARGETSYSROOT` and `CXX` variables. If the script is not present, you must run the `/Common Images Dir/xilinx-versal-common-v2025.1/sdk.sh`. -3. Set up your `ROOTFS` and `IMAGE` to point to the `rootfs.ext4` and `Image` files located in the `/Common Images Dir/xilinx-versal-common-v2025.1` directory. +2. In a Bash shell run the `/Common Images Dir/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux` script. This script sets up the `SDKTARGETSYSROOT` and `CXX` variables. If the script is not present, you must run the `/Common Images Dir/xilinx-versal-common-v2025.2/sdk.sh`. +3. Set up your `ROOTFS` and `IMAGE` to point to the `rootfs.ext4` and `Image` files located in the `/Common Images Dir/xilinx-versal-common-v2025.2` directory. 4. Set up your `PLATFORM_REPO_PATHS` environment variable to `$XILINX_VITIS/base_platforms/`. -This tutorial targets VCK190 production board for 2025.1 version. +This tutorial targets VCK190 production board for 2025.2 version. ## Objectives diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/README.md index 98f10cb7dd..94e3af9291 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/README.md @@ -15,7 +15,7 @@ # AI Engine Performance and Deadlock Analysis Tutorial -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction @@ -23,18 +23,18 @@ This tutorial introduces you to performance analysis and optimization methods, a ## Before You Begin -**IMPORTANT**: Before beginning the tutorial, make sure that you have installed the AMD Vitis™ 2025.1 software. The Vitis release includes all the embedded base platforms, including the VCK190 base platform that is used in this tutorial. In addition, ensure that you have downloaded the Common Images for Embedded Vitis Platforms from this link https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html +**IMPORTANT**: Before beginning the tutorial, make sure that you have installed the AMD Vitis™ 2025.2 software. The Vitis release includes all the embedded base platforms, including the VCK190 base platform that is used in this tutorial. In addition, ensure that you have downloaded the Common Images for Embedded Vitis Platforms from this link https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html The ‘common image’ package contains a prebuilt Linux kernel and root file system that can be used with the AMD Versal™ board for embedded design development using Vitis. Before starting this tutorial, run the following steps: 1. Go to the directory where you have unzipped the Versal Common Image package. -2. In a Bash shell, run the /**Common Images Dir**/xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you **must** run the /**Common Images Dir**/xilinx-versal-common-v2025.1/sdk.sh. -3. Set up your ROOTFS, and IMAGE to point to the rootfs.ext4 and Image files located in the /**Common Images Dir**/xilinx-versal-common-v2025.1 directory. +2. In a Bash shell, run the /**Common Images Dir**/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you **must** run the /**Common Images Dir**/xilinx-versal-common-v2025.2/sdk.sh. +3. Set up your ROOTFS, and IMAGE to point to the rootfs.ext4 and Image files located in the /**Common Images Dir**/xilinx-versal-common-v2025.2 directory. 4. Set up your PLATFORM_REPO_PATHS environment variable to $XILINX_VITIS/base_platforms. -This tutorial targets VCK190 production board for 2025.1 version. +This tutorial targets VCK190 production board for 2025.2 version. ### Objectives diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/aie_execution_measurement.md b/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/aie_execution_measurement.md index 98a72d98b8..7a64fc9b6e 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/aie_execution_measurement.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/aie_execution_measurement.md @@ -15,7 +15,7 @@ # AI Engine Graph Execution and Measurement -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** AI Engine graph execution uses locks for memory synchronization. The stream interfaces have inherent data synchronization through backward or forward pressure. diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/aie_hang_analysis.md b/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/aie_hang_analysis.md index a55085aa70..4e9e2db0e9 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/aie_hang_analysis.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/aie_hang_analysis.md @@ -15,7 +15,7 @@ # AI Engine Deadlock Analysis -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** This tutorial introduces you to some common deadlock scenarios and shows you how to detect deadlocks (design hangs) in different tool flows. The methods introduced to detect and analyze deadlock issues include: @@ -97,7 +97,7 @@ If you are using Vitis Analyzer to do stall analysis, run the AI Engine simulato aiesimulator --pkg-dir=./Work --online -wdb -ctf -**Note:** For more information about AI Engine stall analysis using Vitis Analyzer in the hardware emulation flow, refer to the _Versal ACAP AI Engine Programming Environment User Guide_ ([UG1076](https://docs.amd.com/r/en-US/ug1076-ai-engine-environment)). +**Note:** For more information about AI Engine stall analysis using Vitis Analyzer in the hardware emulation flow, refer to the _Versal adaptive SoC AI Engine Programming Environment User Guide_ ([UG1076](https://docs.amd.com/r/en-US/ug1076-ai-engine-environment)). In Vitis Analyzer, the Performance Metrics view gives an overview of the stalls in the design: @@ -121,7 +121,7 @@ Select the stall in **Lock Stalls** in Trace view, and switch to Graph view. The From the above analysis, the cause of the hang is given. The direct resolution, without modifying kernel code, is to increase the FIFO size between the two kernels. -For more information about AI Engine stall analysis feature, refer to the _Versal ACAP AI Engine Programming Environment User Guide_ ([UG1076](https://docs.amd.com/r/en-US/ug1076-ai-engine-environment)). +For more information about AI Engine stall analysis feature, refer to the _Versal adaptive SoC AI Engine Programming Environment User Guide_ ([UG1076](https://docs.amd.com/r/en-US/ug1076-ai-engine-environment)). ## AI Engine Deadlock Detection in the Hardware Emulation Flow @@ -359,7 +359,7 @@ This section provides details of other methods of detecting and analyzing AI Eng **Tip:** Cross-probe between **Graph** and **Array** view in Vitis Analyzer to understand kernels, buffers, and the locations of ports. ` -- **Using `devmem` to probe AI Engine registers to see AI Engine status:** By using the `devmem` command, you can read AI Engine registers to see the AI Engine internal status. The register reference can be found in the _Versal ACAP AI Engine Register Reference_ ([AM015](https://www.xilinx.com/html_docs/registers/am015/am015-versal-aie-register-reference.html)). +- **Using `devmem` to probe AI Engine registers to see AI Engine status:** By using the `devmem` command, you can read AI Engine registers to see the AI Engine internal status. The register reference can be found in the _Versal adaptive SoC AI Engine Register Reference_ ([AM015](https://www.xilinx.com/html_docs/registers/am015/am015-versal-aie-register-reference.html)). For example, the core status registers can be found here: diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/aie_status_analysis.md b/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/aie_status_analysis.md index 4328163841..2a5d3d9ee3 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/aie_status_analysis.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/aie_status_analysis.md @@ -15,7 +15,7 @@ # AI Engine Status Analysis -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** This tutorial shows you how to output a summary of the AI Engine status for further analysis in an AMD Vitis™ Analyzer. The main methods to output AI Engine status are as follows: diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_dmafifo_opt/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_dmafifo_opt/Makefile index 95efe2876d..c85823db37 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_dmafifo_opt/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_dmafifo_opt/Makefile @@ -3,7 +3,7 @@ #SPDX-License-Identifier: MIT TARGET = hw_emu -PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm +PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm XSA = vck190_aie_base_graph_${TARGET}.xsa HOST_EXE = host.exe @@ -37,19 +37,19 @@ __check_defined = \ $(error Undefined $1$(if $2, ($2)))) guard-PLATFORM_REPO_PATHS: - $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202510_1) + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202520_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) ### diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_dmafifo_opt/pl_kernels/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_dmafifo_opt/pl_kernels/Makefile index bc7306a6e6..dd38ae5f25 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_dmafifo_opt/pl_kernels/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_dmafifo_opt/pl_kernels/Makefile @@ -2,7 +2,7 @@ #Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT -PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm +PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm .PHONY: clean diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_nofifo_hang/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_nofifo_hang/Makefile index 8045c2f4c6..860ff9ea81 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_nofifo_hang/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_nofifo_hang/Makefile @@ -3,7 +3,7 @@ #SPDX-License-Identifier: MIT TARGET = hw_emu -PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm +PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm XSA = vck190_aie_base_graph_${TARGET}.xsa HOST_EXE = host.exe @@ -40,19 +40,19 @@ __check_defined = \ $(error Undefined $1$(if $2, ($2)))) guard-PLATFORM_REPO_PATHS: - $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202510_1) + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202520_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) ### diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_nofifo_hang/pl_kernels/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_nofifo_hang/pl_kernels/Makefile index bc7306a6e6..dd38ae5f25 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_nofifo_hang/pl_kernels/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_nofifo_hang/pl_kernels/Makefile @@ -2,7 +2,7 @@ #Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT -PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm +PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm .PHONY: clean diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_ssfifo/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_ssfifo/Makefile index 46e0fee8e6..322d81133a 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_ssfifo/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_ssfifo/Makefile @@ -3,7 +3,7 @@ #SPDX-License-Identifier: MIT TARGET = hw_emu -PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm +PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm XSA = vck190_aie_base_graph_${TARGET}.xsa HOST_EXE = host.exe @@ -38,19 +38,19 @@ __check_defined = \ $(error Undefined $1$(if $2, ($2)))) guard-PLATFORM_REPO_PATHS: - $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202510_1) + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202520_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) ### diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_ssfifo/pl_kernels/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_ssfifo/pl_kernels/Makefile index bc7306a6e6..dd38ae5f25 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_ssfifo/pl_kernels/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/13-aie-performance-analysis/testcase_ssfifo/pl_kernels/Makefile @@ -2,7 +2,7 @@ #Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT -PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm +PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm .PHONY: clean diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part1a/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part1a/Makefile index 197eb4c352..b8423fee07 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part1a/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part1a/Makefile @@ -16,7 +16,7 @@ AIE_DATA_DIR = ./data RM = rm -f RMDIR = rm -rf -PLATFORM_VERSION = 202510_1 +PLATFORM_VERSION = 202520_1 PLATFORM ?= $(PLATFORM_REPO_PATHS)/xilinx_vck190_base_$(PLATFORM_VERSION)/xilinx_vck190_base_$(PLATFORM_VERSION).xpfm # AIE compiler settings diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part1a/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part1a/README.md index ee2f27288b..b6999f5801 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part1a/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part1a/README.md @@ -14,7 +14,7 @@ # Implementing an IIR Filter on the AI Engine - Part 1a -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Preliminaries diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part1b/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part1b/Makefile index 197eb4c352..b8423fee07 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part1b/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part1b/Makefile @@ -16,7 +16,7 @@ AIE_DATA_DIR = ./data RM = rm -f RMDIR = rm -rf -PLATFORM_VERSION = 202510_1 +PLATFORM_VERSION = 202520_1 PLATFORM ?= $(PLATFORM_REPO_PATHS)/xilinx_vck190_base_$(PLATFORM_VERSION)/xilinx_vck190_base_$(PLATFORM_VERSION).xpfm # AIE compiler settings diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part1b/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part1b/README.md index 1596c32eb6..07b5ffb747 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part1b/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part1b/README.md @@ -15,7 +15,7 @@ # Implementing an IIR Filter on the AI Engine - Part 1b -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Recap diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2a/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2a/Makefile index b0fa8fada7..b919570c0b 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2a/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2a/Makefile @@ -9,7 +9,7 @@ AIE_OUT_DIR = ./Work AIE_GRAPH_FILES = ../src/tb.cpp RMDIR = rm -rf -PLATFORM_VERSION = 202510_1 +PLATFORM_VERSION = 202520_1 PLATFORM ?= $(PLATFORM_REPO_PATHS)/xilinx_vck190_base_$(PLATFORM_VERSION)/xilinx_vck190_base_$(PLATFORM_VERSION).xpfm # AIE compiler settings @@ -28,7 +28,7 @@ aiesim: ./src/kernel.cpp ./src/kernel.hpp ./src/tb.cpp ./src/graph.hpp ./src/C1. echo && \ echo "Running..." && \ echo && \ - aiesimulator --pkg-dir=./Work --i=.. --profile | tee aiesim.log + aiesimulator --pkg-dir=./Work --input-dir=.. --profile | tee aiesim.log @echo @echo "Checking if Julia is available..." diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2a/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2a/README.md index 74daae3432..026fcc2936 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2a/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2a/README.md @@ -15,7 +15,7 @@ # Implementing an IIR Filter on the AI Engine - Part 2a -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Preliminaries diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2a/check.jl b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2a/check.jl index de24e68c40..54685e99cf 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2a/check.jl +++ b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2a/check.jl @@ -36,13 +36,13 @@ ref_file = ws_dir * "data/impresponse.dat"; # impulse response from Julia if (mode == "aie") - cp_cmd = `cp build/hw/aiesimulator_output/output.dat build/hw/aiesimulator_output/output.dat.mod`; - sed_cmd = `sed -i '/T/d' build/hw/aiesimulator_output/output.dat.mod`; # remove lines which begin with "T" + cp_cmd = `cp Emulation-AIE/aiesimulator_output/output.dat Emulation-AIE/aiesimulator_output/output.dat.mod`; + sed_cmd = `sed -i '/T/d' Emulation-AIE/aiesimulator_output/output.dat.mod`; # remove lines which begin with "T" run(cp_cmd); run(sed_cmd); - dut_file = ws_dir * "build/hw/aiesimulator_output/output.dat.mod"; # impulse response from AI engine simulation + dut_file = ws_dir * "Emulation-AIE/aiesimulator_output/output.dat.mod"; # impulse response from AI engine simulation else diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2b/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2b/Makefile index 2f2bc1dde6..ee6fea244d 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2b/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2b/Makefile @@ -9,7 +9,7 @@ AIE_GRAPH_FILES = ../src/tb.cpp AIE_OUT_DIR = ./Work RMDIR = rm -rf -PLATFORM_VERSION = 202510_1 +PLATFORM_VERSION = 202520_1 PLATFORM ?= $(PLATFORM_REPO_PATHS)/xilinx_vck190_base_$(PLATFORM_VERSION)/xilinx_vck190_base_$(PLATFORM_VERSION).xpfm # AIE compiler settings @@ -28,7 +28,7 @@ aiesim: ./src/kernel.cpp ./src/kernel.hpp ./src/tb.cpp ./src/graph.hpp ./src/C1_ echo && \ echo "Running..." && \ echo && \ - aiesimulator --pkg-dir=./Work --i=.. --profile | tee aiesim.log + aiesimulator --pkg-dir=./Work --input-dir=.. --profile | tee aiesim.log @echo @echo "Checking if Julia is available..." diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2b/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2b/README.md index ecd975ac1d..e31bd4f5ae 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2b/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2b/README.md @@ -15,7 +15,7 @@ # Implementing an IIR Filter on the AI Engine - Part 2b -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Preliminaries diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2b/check.jl b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2b/check.jl index 0ce3a55c3e..99814c7b97 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2b/check.jl +++ b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/Part2b/check.jl @@ -36,13 +36,13 @@ ref_file = ws_dir * "data/impresponse.dat"; # impulse response from Julia if (mode == "aie") - cp_cmd = `cp build/hw/aiesimulator_output/output.dat Emulation-AIE/aiesimulator_output/output.dat.mod`; - sed_cmd = `sed -i '/T/d' build/hw/aiesimulator_output/output.dat.mod`; # remove lines which begin with "T" + cp_cmd = `cp Emulation-AIE/aiesimulator_output/output.dat Emulation-AIE/aiesimulator_output/output.dat.mod`; + sed_cmd = `sed -i '/T/d' Emulation-AIE/aiesimulator_output/output.dat.mod`; # remove lines which begin with "T" run(cp_cmd); run(sed_cmd); - dut_file = ws_dir * "build/hw/aiesimulator_output/output.dat.mod"; # impulse response from AI engine simulation + dut_file = ws_dir * "Emulation-AIE/aiesimulator_output/output.dat.mod"; # impulse response from AI engine simulation else diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/README.md index 8657635e93..7931069563 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/14-implementing-iir-filter/README.md @@ -15,7 +15,7 @@ # Implementing an IIR Filter on the AI Engine -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** This is a multi-part tutorial on implementing an [infinite impulse response (IIR) filter](https://en.wikipedia.org/wiki/Infinite_impulse_response) on the AI Engine. diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/15-post-link-recompile/Files/PS/src/host.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/15-post-link-recompile/Files/PS/src/host.cpp index 56de6ba6fe..515e4d75f4 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/15-post-link-recompile/Files/PS/src/host.cpp +++ b/AI_Engine_Development/AIE/Feature_Tutorials/15-post-link-recompile/Files/PS/src/host.cpp @@ -3,6 +3,7 @@ Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: MIT */ +#include #include #include diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/15-post-link-recompile/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/15-post-link-recompile/README.md index c2df327cef..7b9579a434 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/15-post-link-recompile/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/15-post-link-recompile/README.md @@ -15,7 +15,7 @@ # Post-Link Recompile of an AI Engine Application -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction @@ -36,16 +36,16 @@ In the second case, you use the `.xsa` file generated during the link stage as t This tutorial details all the steps to perform hardware emulation (`hw_emu`), but it also supports the hardware implementation flow by changing the compilation target. -**IMPORTANT**: Before beginning the tutorial, make sure that you have installed the Vitis 2025.1 software. The AMD Vitis™ release includes all the embedded base platforms including the VCK190 base platform that is used in this tutorial. In addition, ensure that you have downloaded the Common Images for Embedded Vitis Platforms from this link [https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms/2025.1.html](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms/2025.1.html). +**IMPORTANT**: Before beginning the tutorial, make sure that you have installed the Vitis 2025.2 software. The AMD Vitis™ release includes all the embedded base platforms including the VCK190 base platform that is used in this tutorial. In addition, ensure that you have downloaded the Common Images for Embedded Vitis Platforms from this link [https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms/2025.2.html](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms/2025.2.html). The ‘common image’ package contains a prebuilt Linux kernel and root file system that can be used with the Versal board for embedded design development using Vitis. Before starting this tutorial, run the following steps: 1. Go to the directory where you have unzipped the Versal Common Image package. -2. In a Bash shell, run the `/Common Images Dir/xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux` script. This script sets up the `SDKTARGETSYSROOT` and `CXX` variables. If the script is not present, run the `/Common Images Dir/xilinx-versal-common-v2025.1/sdk.sh`. -3. Set up your `ROOTFS`, and `IMAGE` to point to the `rootfs.ext4` and `Image` files located in the `/Common Images Dir/xilinx-versal-common-v2025.1` directory. +2. In a Bash shell, run the `/Common Images Dir/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux` script. This script sets up the `SDKTARGETSYSROOT` and `CXX` variables. If the script is not present, run the `/Common Images Dir/xilinx-versal-common-v2025.2/sdk.sh`. +3. Set up your `ROOTFS`, and `IMAGE` to point to the `rootfs.ext4` and `Image` files located in the `/Common Images Dir/xilinx-versal-common-v2025.2` directory. 4. Set up your `PLATFORM_REPO_PATHS` environment variable to `$XILINX_VITIS/base_platforms/`. -This tutorial targets the VCK190 production board for 2025.1 version. +This tutorial targets the VCK190 production board for 2025.2 version. The sub-directory `Files` contains all the source files necessary for this tutorial. diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/15-post-link-recompile/WithIntermediatePlatform/Phase1/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/15-post-link-recompile/WithIntermediatePlatform/Phase1/Makefile index 83b01f65a7..d9c022f4d2 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/15-post-link-recompile/WithIntermediatePlatform/Phase1/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/15-post-link-recompile/WithIntermediatePlatform/Phase1/Makefile @@ -8,7 +8,7 @@ # Makefile input options TARGET ?= hw_emu -PFM_NAME ?= xilinx_vck190_base_202510_1 +PFM_NAME ?= xilinx_vck190_base_202520_1 #Directories FILES_DIR ?= ../../Files @@ -64,19 +64,19 @@ __check_defined = \ $(error Undefined $1$(if $2, ($2)))) guard-PLATFORM_REPO_PATHS: - $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202510_1) + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202520_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-aarch64-xilinx-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-aarch64-xilinx-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-aarch64-xilinx-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-aarch64-xilinx-linux) ######################################################## @@ -138,4 +138,4 @@ clean: rm -rf *.bin *.BIN cfg emu_qemu_scripts launch* *.txt *.sh rm -rf sd_card aiesim *.wcfg *.wdb *.bif *.exe *.img sim temp rm -rf aie_primitive.json drivers vpl_gen_fixed_presynth.pdi - rm -rf .crashReporter extracted plkernels vpl_gen_fixed.isd + rm -rf .crashReporter extracted plkernels vpl_gen_fixed.isd analyzer_input diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/15-post-link-recompile/WithIntermediatePlatform/Phase2/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/15-post-link-recompile/WithIntermediatePlatform/Phase2/Makefile index a046bb9b54..cafe9760e1 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/15-post-link-recompile/WithIntermediatePlatform/Phase2/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/15-post-link-recompile/WithIntermediatePlatform/Phase2/Makefile @@ -5,13 +5,13 @@ -# ROOTFS ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/rootfs.ext4 -# IMAGE ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/Image +# ROOTFS ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/rootfs.ext4 +# IMAGE ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/Image # SDKTARGETSYSROOT ?= ${SYSROOT} # # Makefile input options TARGET ?= hw_emu -PFM_NAME ?= xilinx_vck190_base_202510_1 +PFM_NAME ?= xilinx_vck190_base_202520_1 #Directories FILES_DIR ?= ../../Files @@ -68,10 +68,10 @@ __check_defined = \ $(error Undefined $1$(if $2, ($2)))) guard-PLATFORM_REPO_PATHS: - $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202510_1) + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202520_1) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-aarch64-xilinx-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-aarch64-xilinx-linux) ######################################################## @@ -176,4 +176,4 @@ clean: rm -rf aiesimulator_output pl_sample* rm -rf *.bin *.BIN cfg emu_qemu_scripts launch* *.txt *.sh rm -rf sd_card aiesim *.wcfg *.wdb *.bif *.exe *.img sim temp - rm -rf .crashReporter + rm -rf .crashReporter baremetal_metadata_package.cpp diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/15-post-link-recompile/WithoutIntermediatePlatform/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/15-post-link-recompile/WithoutIntermediatePlatform/Makefile index 0d3d210d0a..c271912747 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/15-post-link-recompile/WithoutIntermediatePlatform/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/15-post-link-recompile/WithoutIntermediatePlatform/Makefile @@ -8,7 +8,7 @@ # Makefile input options TARGET ?= hw_emu -PFM_NAME ?= xilinx_vck190_base_202510_1 +PFM_NAME ?= xilinx_vck190_base_202520_1 #Directories FILES_DIR ?= $(PWD)/../Files @@ -75,19 +75,19 @@ __check_defined = \ $(error Undefined $1$(if $2, ($2)))) guard-PLATFORM_REPO_PATHS: - $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202510_1) + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202520_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-aarch64-xilinx-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-aarch64-xilinx-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-aarch64-xilinx-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-aarch64-xilinx-linux) ######################################################## @@ -224,4 +224,4 @@ clean: rm -rf *.bin *.BIN cfg emu_qemu_scripts launch* *.txt *.sh rm -rf sd_card aiesim *.wcfg *.wdb *.bif *.exe *.img sim temp rm -rf *.json *.pdi drivers extracted .crashReporter - rm -rf ./plkernels vpl_gen_fixed.isd + rm -rf ./plkernels vpl_gen_fixed.isd analyzer_input baremetal_metadata_package.cpp diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/Makefile index 914cd6e3a2..064fe6d47c 100755 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/Makefile @@ -1,5 +1,4 @@ - -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +#Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: X11 @@ -19,16 +18,16 @@ KERNEL_XO := s2mm.xo mm2s.xo polar_clip.xo CONFIG_FILE := system.cfg SDKTARGETSYSROOT ?= $(SYSROOT) -PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm -ROOTFS ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/rootfs.ext4 -IMAGE ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/Image +PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm +ROOTFS ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/rootfs.ext4 +IMAGE ?= ${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/Image # Command-line options VPP := v++ AIECC := v++ --mode aie -c AIE_INCLUDE_FLAGS := --include="$(XILINX_VITIS_AIETOOLS)/include" --include="./aie" --include="./data" --include="./aie/kernels" --include="./" -AIE_FLAGS := --target=hw $(AIE_INCLUDE_FLAGS) --aie.workdir=./Work --platform=${XILINX_VITIS}/base_platforms/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm +AIE_FLAGS := --target=hw $(AIE_INCLUDE_FLAGS) --aie.workdir=./Work --platform=${XILINX_VITIS}/base_platforms/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm VPP_XO_FLAGS := --mode hls -c --platform $(PLATFORM) VPP_LINK_FLAGS := -l --platform $(PLATFORM) ip_repo/polar_clip.xo pl_kernels/s2mm.xo pl_kernels/mm2s.xo $(GRAPH_O) -t $(TARGET) --save-temps -g --config $(CONFIG_FILE) -o $(PFM).xsa @@ -61,9 +60,11 @@ sd_card: kernels aie xclbin host package # The graph is generated by having the -target=hw-link kernels: $(KERNEL_XO) -%.xo: pl_kernels/%.cpp - $(VPP) $(VPP_XO_FLAGS) --config pl_kernels/s2mm.cfg - $(VPP) $(VPP_XO_FLAGS) --config pl_kernels/mm2s.cfg +s2mm.xo: pl_kernels/s2mm.cpp + $(VPP) $(VPP_XO_FLAGS) --config pl_kernels/s2mm.cfg + +mm2s.xo: pl_kernels/mm2s.cpp + $(VPP) $(VPP_XO_FLAGS) --config pl_kernels/mm2s.cfg polar_clip.xo: vivado -mode batch -source polar_clip_rtl_kernel.tcl @@ -123,4 +124,5 @@ endif clean: rm -rf _x v++* $(KERNEL_XO) $(GRAPH_O) *.o *.compile_summary* *.xpe xnwOut *.xclbin* *.log *.xsa Work *.db *.csv *$(PFM)* *.jou .Xil rm -rf sw/*.o sw/*.elf sw/*.xpe sw/xnwOut sw/Work sw/*.csv sw/*.db sw/*.bin sw/*.BIN sw/*.bif sw/launch_hw_emulator.sh sw/*.txt sw/emulation sw/.Xil - + rm -rf s2mm/reports/.db mm2s/reports/.db s2mm/logs mm2s/logs analyzer_input + rm -rf ip_repo polar_clip project_polar_clip s2mm mm2s diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/README.md index c81b817644..d0d7ff6186 100755 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/README.md @@ -15,28 +15,28 @@ # Using RTL IP with AI Engines -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction This tutorial demonstrates the following two features of the Vitis™ unified software platform flow: -1. Ability to reuse any AXI-based IP you have created as an RTL IP. -2. The ability to control your platform, and convert your RTL IP to an RTL kernel allows for a more streamlined process for creating the design you need. +1. Reusing an AXI-based IP initially created as an RTL IP. +2. Controlling the platform, and converting an RTL IP to a kernel to allow for a more streamlined process for creating the design you need. -**IMPORTANT**: Before beginning the tutorial make sure you have installed the Vitis 2025.1 software. The Vitis release includes all the embedded base platforms including the VCK190 base platform that is used in this tutorial. In addition, do ensure you have downloaded the Common Images for Embedded Vitis Platforms from this link +**IMPORTANT**: Before beginning the tutorial make sure you have installed the Vitis 2025.2 software. The Vitis release includes all the embedded base platforms including the VCK190 base platform that is used in this tutorial. In addition, do ensure you have downloaded the Common Images for Embedded Vitis Platforms from this link -https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms/2025.1.html +https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms/2025.2.html The 'common image' package contains a prebuilt Linux kernel and root file system that can be used with the Versal™ board for embedded design development using Vitis. Before starting this tutorial run the following steps: 1. Goto the directory where you have unzipped the Versal Common Image package -2. In a Bash shell run the /Common Images Dir/xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the /Common Images Dir/xilinx-versal-common-v2025.1/sdk.sh. -3. Set up your ROOTFS, and IMAGE to point to the rootfs.ext4 and Image files located in the /Common Images Dir/xilinx-versal-common-v2025.1 directory. -4. Set up your PLATFORM_REPO_PATHS environment variable to $XILINX_VITIS/base_platforms/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm +2. In a Bash shell run the /Common Images Dir/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the /Common Images Dir/xilinx-versal-common-v2025.2/sdk.sh. +3. Set up your ROOTFS, and IMAGE to point to the rootfs.ext4 and Image files located in the /Common Images Dir/xilinx-versal-common-v2025.2 directory. +4. Set up your PLATFORM_REPO_PATHS environment variable to $XILINX_VITIS/base_platforms/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm -This tutorial targets VCK190 production board for 2025.1 version. +This tutorial targets VCK190 production board for 2025.2 version. ## Objectives @@ -84,20 +84,20 @@ Package your RTL code as a Vivado IP and generate a Vitis RTL kernel. Note the following points: * The script creates a Vivado Design Suite project; this is required to create any IP because all source and constraint files need to be local to the IP. - * Lines 40 and 41 are used to associate the correct clock pins to the interfaces. This is required for the Vitis compiler which links those interfaces to the platform clocking. + * Lines 34 and 35 are used to associate the correct clock pins to the interfaces. This is required for the Vitis compiler which links those interfaces to the platform clocking. ```tcl ipx::associate_bus_interfaces -busif in_sample -clock ap_clk [ipx::current_core] ipx::associate_bus_interfaces -busif out_sample -clock ap_clk [ipx::current_core] ``` - * On lines 44 and 45 the `FREQ_HZ` bus parameter is removed. This parameter is used in IP integrator, and is to make sure the associated clock of the interface is used correctly. However, the Vitis compiler sets this during the compilation process, and having it set in the IP will cause the compiler to incorrectly link the clocks. + * On lines 38 and 39 the `FREQ_HZ` bus parameter is removed. This parameter is used in Vivado IP integrator to ensure corrent association of the clock interface. The Vitis compiler sets this during the compilation process, and having it set in the IP may cause the compiler to incorrectly link the clocks. ```tcl ipx::remove_bus_parameter FREQ_HZ [ipx::get_bus_interfaces in_sample -of_objects [ipx::current_core]] ipx::remove_bus_parameter FREQ_HZ [ipx::get_bus_interfaces out_sample -of_objects [ipx::current_core]] ``` - * At the end of the script there is the `package_xo` command. This command analyzes the IP that was created to make sure proper AXI interfaces are used and other rule checks are followed. It then creates the XO file in the same location as the IP repository. A key function used in this command is the `-output_kernel_xml`. The `kernel.xml` file is key to the RTL kernel as it describes to the Vitis tool how the kernel should be controlled. You can find more information on [RTL kernels and their requirements](https://docs.amd.com/r/en-US/ug1393-vitis-application-acceleration/Packaging-RTL-Kernels). + * At the end of the script notice the `package_xo` command. This command analyzes the newly created IP to make sure it contains the proper AXI interfaces. It then creates the XO file in the same location as the IP repository. A key function used in this command is the `-output_kernel_xml`. The `kernel.xml` file is key to the RTL kernel as it describes to the Vitis tool how the kernel should be controlled. You can find more information on [RTL kernels and their requirements](https://docs.amd.com/r/en-US/ug1393-vitis-application-acceleration/Packaging-RTL-Kernels). ```tcl package_xo -kernel_name $kernelName \ @@ -120,13 +120,13 @@ Package your RTL code as a Vivado IP and generate a Vitis RTL kernel. ``` ## Step 2 - Creating HLS kernels with Vitis compiler -The `mm2s` and `s2mm` kernels are HLS-based and use the Vitis compiler to compile them into XO files. +The `mm2s` and `s2mm` are HLS-based kernels that the Vitis compiler packages into XO files. To build these kernels run the following commands: ```bash -v++ -c --platform -g --save-temps -k mm2s pl_kernels/mm2s.cpp -o mm2s.xo -v++ -c --platform -g --save-temps -k mm2s pl_kernels/s2mm.cpp -o s2mm.xo +v++ -c --platform -k mm2s pl_kernels/mm2s.cpp -o mm2s.xo +v++ -c --platform -k s2mm pl_kernels/s2mm.cpp -o s2mm.xo ``` or @@ -136,7 +136,7 @@ make kernels ``` ## Step 3 - Interfacing ADF graph to Programmable Logic -To set up the ADF graph to interface with the `polar_clip` RTL kernel and the `mm2s` and `s2mm` HLS kernels, you must add connections to PLIOs that represent the respective PL kernels. +To interface the ADF graph to the `polar_clip` RTL kernel and the `mm2s` and `s2mm` HLS kernels, you must add connections between PLIOs and the corresponding PL kernels IOs. 1. The following `graph.h` shows how to connect to the RTL kernel. @@ -160,15 +160,15 @@ To set up the ADF graph to interface with the `polar_clip` RTL kernel and the `m ``` 2. Note the following: - * Two additional `PLIO` objects `clip_in` and `clip_out` are added. These are to hook up to the `polar_clip` RTL kernel. + * Two additional `PLIO` objects `clip_in` and `clip_out` are added. These hook up to the `polar_clip` RTL kernel. * There are additional net objects to hook up the RTL kernel to the rest of the platform object. -For more information on RTL kernels in the AI Engine see: [Design Flow Using RTL Programmable Logic](https://docs.amd.com/r/en-US/ug1393-vitis-application-acceleration/Vitis-Development-Flow-for-RTL-Designers). +For more information on RTL kernels in the AI Engine see: [Integrating AIE and PL Components](https://docs.amd.com/r/en-US/ug1701-vitis-accelerated-embedded/Integrating-AIE-and-PL-Components). 3. Compile the graph using the following command: ```bash - v++ --mode aie -c --target=hw --include="/include" --include="./aie" --include="./data" --include="./aie/kernels" --include="./" --aie.workdir=./Work --platform=${XILINX_VITIS}/base_platforms/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm aie/graph.cpp + v++ --mode aie -c --target=hw --include="/include" --include="./aie" --include="./data" --include="./aie/kernels" --include="./" --aie.workdir=./Work --platform=${XILINX_VITIS}/base_platforms/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm aie/graph.cpp ``` or @@ -193,7 +193,7 @@ Because there is no HLS kernel in the ADF graph, the `system.cfg` file, which is 3. Build the emulation design using the following command: ```bash - v++ -l --platform ${XILINX_VITIS}/base_platforms/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm s2mm.xo mm2s.xo polar_clip.xo libadf.a -t hw_emu --save-temps -g --config system.cfg -o tutorial.xsa + v++ -l --platform ${XILINX_VITIS}/base_platforms/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm s2mm.xo mm2s.xo polar_clip.xo libadf.a -t hw_emu --save-temps -g --config system.cfg -o tutorial.xsa ``` or @@ -232,11 +232,11 @@ To package the design run: ```bash cd ./sw v++ -p -t hw_emu \ - -f ${XILINX_VITIS}/base_platforms/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm \ - --package.rootfs=${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/rootfs.ext4 \ + -f ${XILINX_VITIS}/base_platforms/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm \ + --package.rootfs=${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/rootfs.ext4 \ --package.image_format=ext4 \ --package.boot_mode=sd \ - --package.kernel_image=${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.1/Image \ + --package.kernel_image=${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v2025.2/Image \ --package.defer_aie_run \ --package.sd_file host.exe ../tutorial.xsa ../libadf.a cd .. diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/aie/graph.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/aie/graph.cpp index 29490ed7bc..4d7810cf7f 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/aie/graph.cpp +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/aie/graph.cpp @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/aie/graph.h b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/aie/graph.h index aef434aa4a..718e6008b9 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/aie/graph.h +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/aie/graph.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/aie/include.h b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/aie/include.h index a265976f53..3808fbd013 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/aie/include.h +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/aie/include.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ #ifndef __INCLUDE_H__ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/aie/kernels.h b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/aie/kernels.h index eda8696a6c..abd84370a2 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/aie/kernels.h +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/aie/kernels.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ #ifndef __KERNELS_H__ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip.v b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip.v index 0036f61302..9a06f7124e 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip.v +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip.v @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ // ============================================================== diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_mac_muladd_16s_16s_32s_32_4_1.v b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_mac_muladd_16s_16s_32s_32_4_1.v index 46a83f77ea..e0b1690bd6 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_mac_muladd_16s_16s_32s_32_4_1.v +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_mac_muladd_16s_16s_32s_32_4_1.v @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ // ============================================================== diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_mul_mul_16s_16s_16_4_1.v b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_mul_mul_16s_16s_16_4_1.v index 485b347f5b..5827bcc8b8 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_mul_mul_16s_16s_16_4_1.v +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_mul_mul_16s_16s_16_4_1.v @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_mul_mul_16s_16s_32_4_1.v b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_mul_mul_16s_16s_32_4_1.v index 734af398e5..fd65b5b0c7 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_mul_mul_16s_16s_32_4_1.v +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_mul_mul_16s_16s_32_4_1.v @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ `timescale 1 ns / 1 ps diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_mul_mul_25s_10ns_25_4_1.v b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_mul_mul_25s_10ns_25_4_1.v index 10b8ed5a65..8d00053800 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_mul_mul_25s_10ns_25_4_1.v +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_mul_mul_25s_10ns_25_4_1.v @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ `timescale 1 ns / 1 ps diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_regslice_core.v b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_regslice_core.v index 9e5c227590..24ff3e6835 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_regslice_core.v +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_regslice_core.v @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ // ============================================================== diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_rotation_cos_lut.v b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_rotation_cos_lut.v index b41dd7bb12..fac6fcde3d 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_rotation_cos_lut.v +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_rotation_cos_lut.v @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ // ============================================================== diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_rotation_sin_lut.v b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_rotation_sin_lut.v index 659db8eaba..a65e072a3c 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_rotation_sin_lut.v +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/verilog/polar_clip_rotation_sin_lut.v @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip.vhd b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip.vhd index 7773a79411..9662a5d810 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip.vhd +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip.vhd @@ -1,5 +1,5 @@ ---Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +--Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. --SPDX-License-Identifier: X11 -- ============================================================== diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_mac_muladd_16s_16s_32s_32_4_1.vhd b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_mac_muladd_16s_16s_32s_32_4_1.vhd index c3e5fda13f..8126048094 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_mac_muladd_16s_16s_32s_32_4_1.vhd +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_mac_muladd_16s_16s_32s_32_4_1.vhd @@ -1,5 +1,5 @@ ---Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +--Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. --SPDX-License-Identifier: X11 -- ============================================================== diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_mul_mul_16s_16s_16_4_1.vhd b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_mul_mul_16s_16s_16_4_1.vhd index d4f7ce0cc9..eff179db5f 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_mul_mul_16s_16s_16_4_1.vhd +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_mul_mul_16s_16s_16_4_1.vhd @@ -1,5 +1,5 @@ ---Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +--Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. --SPDX-License-Identifier: X11 library IEEE; diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_mul_mul_16s_16s_32_4_1.vhd b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_mul_mul_16s_16s_32_4_1.vhd index 29519bbd18..c0461b8cdd 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_mul_mul_16s_16s_32_4_1.vhd +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_mul_mul_16s_16s_32_4_1.vhd @@ -1,5 +1,5 @@ ---Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +--Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. --SPDX-License-Identifier: X11 diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_mul_mul_25s_10ns_25_4_1.vhd b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_mul_mul_25s_10ns_25_4_1.vhd index 38077aea0c..520772a53d 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_mul_mul_25s_10ns_25_4_1.vhd +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_mul_mul_25s_10ns_25_4_1.vhd @@ -1,5 +1,5 @@ ---Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +--Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. --SPDX-License-Identifier: X11 library IEEE; diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_regslice_both.vhd b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_regslice_both.vhd index b7dac1d472..8a7813fb19 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_regslice_both.vhd +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_regslice_both.vhd @@ -1,5 +1,5 @@ ---Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +--Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. --SPDX-License-Identifier: X11 -- ============================================================== diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_rotation_cos_lut.vhd b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_rotation_cos_lut.vhd index 13832a20ed..ebf7457600 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_rotation_cos_lut.vhd +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_rotation_cos_lut.vhd @@ -1,5 +1,5 @@ ---Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +--Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. --SPDX-License-Identifier: X11 -- ============================================================== diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_rotation_sin_lut.vhd b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_rotation_sin_lut.vhd index 9ee136c68c..7bb2c9a95b 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_rotation_sin_lut.vhd +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/hdl/vhdl/polar_clip_rotation_sin_lut.vhd @@ -1,5 +1,5 @@ ---Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +--Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. --SPDX-License-Identifier: X11 -- ============================================================== diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/mm2s.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/mm2s.cpp index 6b4e9d1003..398f6dce88 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/mm2s.cpp +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/mm2s.cpp @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/s2mm.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/s2mm.cpp index db02f5abfd..16c7a3b8c8 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/s2mm.cpp +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/pl_kernels/s2mm.cpp @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/polar_clip_rtl_kernel.tcl b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/polar_clip_rtl_kernel.tcl index ee23158310..79ebca3b6b 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/polar_clip_rtl_kernel.tcl +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/polar_clip_rtl_kernel.tcl @@ -1,5 +1,5 @@ -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +#Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: X11 set kernelName "polar_clip" diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/sw/data.h b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/sw/data.h index e7aa946f34..fe840303d3 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/sw/data.h +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/sw/data.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ #pragma once diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/sw/host.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/sw/host.cpp index 25383943ec..bb53f820c3 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/sw/host.cpp +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/sw/host.cpp @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ #include diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/sw/host.h b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/sw/host.h index 1c2ad88ed8..14eb22b170 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/sw/host.h +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/sw/host.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: X11 */ #pragma once diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/system.cfg b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/system.cfg index 6914e10534..02ac80b39d 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/system.cfg +++ b/AI_Engine_Development/AIE/Feature_Tutorials/17-RTL-IP-with-AIE-Engines/system.cfg @@ -1,5 +1,5 @@ -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +#Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: X11 [connectivity] diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/18-aie_a_to_z_custom_linux_platform/18-aie_a_to_z_custom_linux_platform-sourcelink.rst b/AI_Engine_Development/AIE/Feature_Tutorials/18-aie_a_to_z_custom_linux_platform/18-aie_a_to_z_custom_linux_platform-sourcelink.rst deleted file mode 100644 index 306c7c9258..0000000000 --- a/AI_Engine_Development/AIE/Feature_Tutorials/18-aie_a_to_z_custom_linux_platform/18-aie_a_to_z_custom_linux_platform-sourcelink.rst +++ /dev/null @@ -1,6 +0,0 @@ - -####################################################### -Version: Vitis 2022.2 -####################################################### - -To view the source files for this tutorial, click `here `_. \ No newline at end of file diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/18-aie_a_to_z_custom_linux_platform/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/18-aie_a_to_z_custom_linux_platform/README.md index 5e22ae9121..2caeb1ac83 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/18-aie_a_to_z_custom_linux_platform/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/18-aie_a_to_z_custom_linux_platform/README.md @@ -17,100 +17,12 @@ ***Version: Vitis 2025.1*** -## Introduction - -The AMD Vitis™ environment comprises tools, libraries, and IP that let you program, run, and debug the different elements of an AMD Versal™ adaptive SoC application, including AI Engine kernels and graphs, programmable logic (PL) functions, and software applications running on the processing system (PS). The Vitis tools use a platform-based approach in which the system is conceptually divided into the following elements, which can be developed and tested in parallel: - -* **Platform** - Platforms provide the foundational hardware IP blocks and software features upon which the adaptable subsystem and software application can be built and integrated. -* **Adaptable subsystem** - Adaptable subsystems perform well-defined functions, leveraging PL blocks and AI Engine graphs. - -This tutorial introduces you to this platform-based approach to develop the elements mentioned above individually and leverage the parallelism to develop and test the application. The adaptable subsystem that contains the PL kernels and AI Engine graph can be developed and tested on the AMD standard base platform, while the custom platform that best suits your application is still under development. This tutorial also demonstrates how you can easily validate the design by means of hardware emulation or hardware using the base platform, and quickly switch to the custom platform with minimal changes. - -### Methodology Overview -The following figure shows a high-level representation of the development methodology based on the Vitis environment design flow. - -![Vitis_Environment_Design_flow](./images/vitis_design_flow.png) - -The Vitis environment development methodology reflects the heterogeneous nature of Versal adaptive SoC systems, which typically consist of PS, PL and AI Engine functionality. Using the Vitis tools, you can develop and verify these components independently and gradually integrate them to form the final system. - -The foundation of the Vitis environment design methodology is an iterative approach and parallel development. As a result, AMD strongly recommends the following best practices: - -* Develop the adaptable subsystem and the custom platform in parallel. -* Debug and verify the AI Engine graph and each of the PL kernels individually before proceeding with integration. -* Use a standard AMD platform (such as the VCK190) to integrate and verify the adaptable subsystem comprised of the AI Engine graph and PL kernels before targeting the custom platform and ensure performance goals are met at each stage of the flow. - * AMD platforms are pre-verified and ready to be deployed on hardware. By using an AMD standard base platform, developers of AI Engine graphs and PL kernels can verify the adaptable subsystem using simulation or hardware boards without the uncertainties and the complexities of the custom platform. -* Develop and verify the custom platform. -* Integrate the subsystem with the custom platform and test the integration. - - -The steps in this tutorial are tightly coupled with the recommended best practices and introduce you to a complete end-to-end flow for a Linux-based host application for AI Engines and PL kernels using a base platform. You can then create a custom platform and re-target the design using the custom platform. - -**IMPORTANT**: Before beginning the tutorial, make sure that you have read and followed the *Vitis Software Platform Release Notes* (v2025.1) for setting up software and installing the VCK190 base platform. - -## Objectives - -After completing this tutorial, you should be able to: - -* Run the system design targeting the base platform. -* Create a custom platform. -* Re-target the design that was using the VCK190 base platform to now use the custom platform. - The steps include: - * Re-compiling ADF graphs targeting the custom platform - * Re-compiling Programmable Logic (PL) kernels targeting the custom platform. - * Exploring Vitis Analyzer for viewing the compilation and simulation summary reports. - * Re-linking and re-packaging the design to run hardware emulation and hardware. - -## Tutorial -Run these three steps to complete this tutorial. -* Step 1: Run system design targeting the base platform -* Step 2: Create a custom platform -* Step 3: Run the system design targeting the custom platform - -**Note**: Step 1 and Step 2 can be performed in any order. - -## Step 1: Run system design targeting the base platform - -This step walks you through the complete flow of creating a system design running on the AI Engine, PS, and PL targeting the base platform. The base platforms are pre-verified, which provides a stable foundation to built upon, allowing you to focus on AI Engine graph and PL kernels. AMD highly recommends that you debug and address all performance issues, such as deadlocks, stalls, or bubbles, using a base platform before integrating the subsystem with the custom platform. - -You will validate the design running on these heterogeneous domains by software emulation, hardware emulation, and then running on actual hardware. - -1. Click the link below, and follow the step-by-step procedure to run the design targeting the base platform. - - **Note: The link redirects you to a different tutorial location.** - - [Running system design on AI Engine, PS, and PL using base platform](../05-AI-engine-versal-integration/README.md) - -2. When you have completed the step-by-step procedure at the link above, return to this page and proceed to Step 2. - - -## Step 2: Create a custom platform - -In this step, you will create a custom platform based on the VCK190 Evaluation board. - -1. Click the link below, and follow the step-by-step procedure to complete this step. - - **Note: The link below redirects you to the different tutorial location.** - - [Creating Custom Platfom based on VCK190 Evaluation board](../../../../Getting_Started/Vitis_Platform/README.md) - - **Note**: You can either create custom embedded acceleration platforms by building from scratch, or modifing AMD embedded platforms. This module focuses on quickly creating a platform using a Versal adaptive SoC extensible embedded platform example. -2. When you have completed the step-by-step procedure at the link above, return to this page and proceed to Step 3. - -## Step 3: Run the system design targeting the custom platform - -Next, re-target the design from Step 1 on the custom platform created in Step 2. - -1. Click the link below, and follow the step-by-step procedure to complete this step. - - [AI Engine Graph Integration and Validation using a Custom Linux Platform](steps_to_run_design_on_cust_plfm.md). - -To read more about the AI Engine flow, see the *Versal ACAP AI Engine Programming Environment User Guide* ([UG1076](https://docs.amd.com/r/en-US/ug1076-ai-engine-environment)). - - -### Support - -GitHub issues will be used for tracking requests and bugs. For questions go to [support.xilinx.com](https://support.xilinx.com/). +> **Note:** +> This tutorial is no longer maintained and is replaced with examples in the [Vitis System Design tutorials](../../../../Vitis_System_Design/Design_Tutorials/README.md). +> Previous versions are available in earlier branches. +> To access them, switch to an older branch (e.g., `2025.1`). +

Copyright © 2020–2025 Advanced Micro Devices, Inc.

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- - - AMD logo - -

AMD Vitis™ AI Engine Tutorials

- See Vitis™ Development Environment on amd.com -
- See Vitis™ AI Development Environment on amd.com -
- -# AI Engine Graph Integration and Validation using a Custom Linux Platform - -***Version: Vitis 2024.2*** - -In this tutorial, you will use the design sources that are used to run the system design on base platform in [Running system design on AI Engine, PS, and PL using base platform](../05-AI-engine-versal-integration/README.md). You will re-target the design to use the custom platform created in [Creating Custom Platfom based on VCK190 Evaluation board](../../../../Getting_Started/Vitis_Platform/README.md). - -To read more about the AI Engine flow, see the *Versal ACAP AI Engine Programming Environment User Guide* ([UG1076](https://docs.amd.com/r/en-US/ug1076-ai-engine-environment)). - -## Prerequisites - -As described in [AI Engine A-to-Z Flow for Linux](README.md), two steps (tutorials) must be run before running this tutorial. - -* **Run system design targeting the base platform**. Follow the step-by-step procedure in [Running system design on AI Engine, PS, and PL using base platform](../05-AI-engine-versal-integration/README.md) to complete this step. - -* **Create a custom platform**. Follow the step-by-step procedure in [Creating Custom Platfom based on VCK190 Evaluation board](../../../../Getting_Started/Vitis_Platform/README.md) to complete this step. - -After you complete these prerequisite tutorials, you are ready to run AI Engine graph integration and validation using a custom Linux platform. - -**IMPORTANT**: Before beginning the tutorial, make sure that you have read and followed the *Vitis Software Platform Release Notes* for setting up software and installing the VCK190 base platform. - - -## Setting up the environment - -First, set up the environment for integrating the subsystem with the custom platform and validating the design using the hardware emulation and hardware as follows: - -1. Set up your `PLATFORM_REPO_PATHS` environment variable based upon where you created the custom platform during Step 2. - For example, if the custom platform is created in the path `/export/vck190_custom/`, the `PLATFORM_REPO_PATHS `should be set accordingly. -2. Change the `BASE_PLATFORM` in the [Makefile](../05-AI-engine-versal-integration/Makefile) to point to the custom `.xpfm` file created in the `/export/vck190_custom/` directory. - - For example: `BASE_PLATFORM = ${PLATFORM_REPO_PATHS}/vck190_custom.xpfm` - -3. Make sure your `ROOTFS` and `IMAGE` are still pointing to the `xilinx-versal-common-v2024.2` directory. - - **Note** : The `$PLATFORM_REPO_PATHS` now points to the custom platform and it does not contain the `rootfs.ext4` and `Image` files as pointed in the Makefile. - - Note that all other commands in the Makefile remain the same. Only the platform needs to be changed for re-targeting the design using custom platform. - - ## Re-compiling ADF graph - -After making the necessary environment changes, re-compile the ADF graph targeting the custom platform using the command below: - - ```bash - make aie TARGET=hw - ``` - -or - -```bash -v++ -c --mode aie --target hw --platform $PLATFORM_REPO_PATHS/vck190_custom.xpfm --include "$XILINX_VITIS/aietools/include" --include "./aie" --include "./data" --include "./aie/kernels" --include "./" -work_dir=./Work aie/graph.cpp` -``` - -## Re-compiling Programmable Logic (PL) kernels targeting the custom platform -Re-compile the PL kernets targeting the custom platform using the command below: - - ```bash - make kernels TARGET=hw - ``` - -or - -```bash -v++ -c --mode hls --platform $PLATFORM_REPO_PATHS/vck190_custom.xpfm --config pl_kernels/s2mm.cfg -v++ -c --mode hls --platform $PLATFORM_REPO_PATHS/vck190_custom.xpfm --config pl_kernels/mm2s.cfg -``` - -## Hardware Emulation - -Next, run the Hardware Emulation targeting the custom platform as follows: - -1. Link AI Engine & PL kernels with platform. - - ```bash - make xsa TARGET=hw_emu - ``` - - or - - ```bash - v++ -l --platform $PLATFORM_REPO_PATHS/vck190_custom.xpfm s2mm.xo mm2s.xo libadf.a -t hw_emu --save-temps -g --config system.cfg -o tutorial.xsad - ``` - -2. Compile the A72 Host Application. - - ```bash - make host - ``` - - or - - ```bash - cd ./sw - - aarch64-xilinx-linux-g++ -Wall -c -std=c++14 -Wno-int-to-pointer-cast --sysroot=$SDKTARGETSYSROOT -I$SDKTARGETSYSROOT/usr/include/xrt -I$SDKTARGETSYSROOT/usr/include -I./ -I../aie -I$XILINX_VITIS/aietools/include -I$XILINX_VITIS/include -o main.o .cpp - - aarch64-xilinx-linux-g++ main.o -lxrt_coreutil -L$SDKTARGETSYSROOT/usr/lib --sysroot=$SDKTARGETSYSROOT -L$XILINX_VITIS/aietools/lib/aarch64.o -o host.exe - cd .. - ``` - -3. Package the Design. - - ```bash - make package TARGET=hw_emu - ``` - - or - - ```bash - cd ./sw - v++ --package -t hw_emu \ - -f $PLATFORM_REPO_PATHS/vck190_custom.xpfm \ - --package.rootfs=$ROOTFS \ - --package.image_format=ext4 \ - --package.boot_mode=sd \ - --package.kernel_image=$IMAGE \ - --package.defer_aie_run \ - --package.sd_file host.exe ../tutorial.xsa ../libadf.a - cd .. - ``` - -4. Run Hardware Emulation. - - ```bash - make run_emu TARGET=hw_emu - ``` - - or - - ```bash - cd ./sw - ./launch_hw_emu.sh -aie-sim-options ../aiesimulator_output/aiesim_options.txt -add-env AIE_COMPILER_WORKDIR=../Work - ``` - -5. Execute the following command when the emulated Linux prompt finally appears. - - ```bash - cd /run/media/*1 - export XILINX_XRT=/usr - dmesg -n 4 && echo "Hide DRM messages..." - ``` - -6. Run the design using the following command. - - ```bash - ./host.exe a.xclbin - ``` - -7. You should see an output displaying TEST PASSED. When this is shown, run the keyboard command: `Ctrl+A x` to end the QEMU instance. - -8. You can view the profiling and trace results of hardware emulation in an AMD Vitis™ Analyzer by running the following command: - -```bash -vitis_analyzer --classic sw/sim/behav_waveform/default.aierun_summary -``` - -9. You can easily compare the results of the custom platform with the one generated using base platform. Comparison of the trace is supported through classic Vitis™ Analyzer only. For example: - -* Select **File > Open Summary** to open the summary file generated for the base platform target. -* Once the summary file opens, click **Trace** to open the VCD data which gives information about kernels, tiles and nets within the AI Engine. -* Click the **Compare** option and from the drop-down select the trace output of other summary file as shown in the following figure. - -![hw_emu_trace_compare](./images/hw_emu_trace_comp1.PNG) - -* Observe the trace information of two summary files in single view as highlighted below. - -![hw_emu_trace_compare2](./images/hw_emu_trace_comp2.PNG) - -## Targeting Hardware - -You can easily build for hardware by following the steps below. - -**Note**: Because you already compiled the AI Engine graph and PL kernels for hardware emulation in the previous step, you do not need to re-compile them again for targeting the hardware. However, re-link and re-package for hardware run. - -1. Link AI Engine and PL kernels with the platform: - - ```bash - make xsa TARGET=hw - ``` - - or - - ```bash - v++ -l --platform $PLATFORM_REPO_PATHS/vck190_custom.xpfm s2mm.xo mm2s.xo libadf.a -t hw --save-temps -g --config system.cfg -o tutorial.xsa - ``` - -2. Re-run the packaging step with: - - ```bash - make package TARGET=hw - ``` - - or - - ```bash - cd ./sw - v++ --package -t hw \ - -f $PLATFORM_REPO_PATHS/vck190_custom.xpfm \ - --package.rootfs=$ROOTFS \ - --package.image_format=ext4 \ - --package.boot_mode=sd \ - --package.kernel_image=$IMAGE \ - --package.defer_aie_run \ - --package.sd_file host.exe ../tutorial.xsa ../libadf.a - cd .. - ``` - - When you run on hardware, ensure that you have a supported SD card. Format the SD card with the `sw/sd_card.img` file. Then plug the SD card into the board and power it up. - -3. When a Linux prompt appears, run the following commands: - - ```bash - dmesg -n 4 && echo "Hide DRM messages..." - cd /run/media/*1 - export XILINX_XRT=/usr - ./host.exe a.xclbin - ``` - - You should see TEST PASSED. You have successfully run your design on hardware. - -To read more about the AI Engine flow, see the *Versal ACAP AI Engine Programming Environment User Guide* ([UG1076](https://docs.amd.com/r/en-US/ug1076-ai-engine-environment)). - -### Support - -GitHub issues will be used for tracking requests and bugs. For questions go to [support.xilinx.com](https://support.xilinx.com/). - - -

Copyright © 2020–2025 Advanced Micro Devices, Inc.

- -

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diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/20-aiecompiler-features/ConditionalObjects/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/20-aiecompiler-features/ConditionalObjects/Makefile index 61328e49e5..4b51b00c28 100755 --- a/AI_Engine_Development/AIE/Feature_Tutorials/20-aiecompiler-features/ConditionalObjects/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/20-aiecompiler-features/ConditionalObjects/Makefile @@ -5,10 +5,10 @@ CASE ?= 1 ARCH ?= aie ifeq ($(ARCH), aie) -PFM_NAME := xilinx_vck190_base_202510_1 +PFM_NAME := xilinx_vck190_base_202520_1 $(info "ARCH set for AI Engine Architecture (ARCH = $(ARCH))") else ifeq ($(ARCH), aie-ml) -PFM_NAME := xilinx_vek280_base_202510_1 +PFM_NAME := xilinx_vek280_base_202520_1 $(info "ARCH set for AI Engine ML Architecture (ARCH = $(ARCH))") else $(error "ARCH should be either aie for AI Engine or aie-ml for AI Engine ML (ARCH = $(ARCH))") diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/20-aiecompiler-features/Multicast/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/20-aiecompiler-features/Multicast/Makefile index 9c99639a1a..529bfd2279 100755 --- a/AI_Engine_Development/AIE/Feature_Tutorials/20-aiecompiler-features/Multicast/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/20-aiecompiler-features/Multicast/Makefile @@ -5,10 +5,10 @@ CASE ?= 1 ARCH ?= aie ifeq ($(ARCH), aie) -PFM_NAME := xilinx_vck190_base_202510_1 +PFM_NAME := xilinx_vck190_base_202520_1 $(info "ARCH set for AI Engine Architecture (ARCH = $(ARCH))") else ifeq ($(ARCH), aie-ml) -PFM_NAME := xilinx_vek280_base_202510_1 +PFM_NAME := xilinx_vek280_base_202520_1 $(info "ARCH set for AI Engine ML Architecture (ARCH = $(ARCH))") else $(error "ARCH should be either aie for AI Engine or aie-ml for AI Engine ML (ARCH = $(ARCH))") diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/20-aiecompiler-features/Multirate/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/20-aiecompiler-features/Multirate/Makefile index bec1c3d58c..6a31f81570 100755 --- a/AI_Engine_Development/AIE/Feature_Tutorials/20-aiecompiler-features/Multirate/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/20-aiecompiler-features/Multirate/Makefile @@ -6,10 +6,10 @@ VERSION ?= 1 ARCH ?= aie ifeq ($(ARCH), aie) -PFM_NAME := xilinx_vck190_base_202510_1 +PFM_NAME := xilinx_vck190_base_202520_1 $(info "ARCH set for AI Engine Architecture (ARCH = $(ARCH))") else ifeq ($(ARCH), aie-ml) -PFM_NAME := xilinx_vek280_base_202510_1 +PFM_NAME := xilinx_vek280_base_202520_1 $(info "ARCH set for AI Engine ML Architecture (ARCH = $(ARCH))") else $(error "ARCH should be either aie for AI Engine or aie-ml for AI Engine ML (ARCH = $(ARCH))") diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/20-aiecompiler-features/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/20-aiecompiler-features/README.md index a234661c36..0d3d99a919 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/20-aiecompiler-features/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/20-aiecompiler-features/README.md @@ -15,14 +15,14 @@ # AI Engine Compiler Features -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction The `aiecompiler` is evolving and therefore it may be difficult for you to keep up with new features. This tutorial shares a variety of features that are useful for AI Engine / AI Engine-ML (AIE-ML) programming to create more visible and efficient code compared to early versions of the compiler. ->**IMPORTANT**: Before beginning the tutorial, make sure that you have installed the AMD Vitis™ Unified Software Platform 2025.1. +>**IMPORTANT**: Before beginning the tutorial, make sure that you have installed the AMD Vitis™ Unified Software Platform 2025.2. Data generation for this tutorial requires [Python 3](https://www.python.org/downloads/). The following packages are required: diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/21-two_tone_filter/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/21-two_tone_filter/README.md index ad18b4c79b..fce123023e 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/21-two_tone_filter/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/21-two_tone_filter/README.md @@ -15,7 +15,7 @@ # Signal Processing on AI Engine Using Vitis DSP Libraries and Vitis Model Composer -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction @@ -25,10 +25,10 @@ This tutorial guides you to design an FIR filter with an FFT using the DSP libra Install the tools: -- Get and install **[MathWorks MATLAB® and Simulink® (R2024 or R2024b or R2025a)](https://www.mathworks.com/products/get-matlab.html?s_tid=gn_getml)** -- Get and install **[AMD Vitis 2025.1](https://www.xilinx.com/support/download.html)** +- Get and install **[MathWorks MATLAB® and Simulink® (R2025a or R2024b or R2024a)](https://www.mathworks.com/products/get-matlab.html?s_tid=gn_getml)** +- Get and install **[AMD Vitis 2025.2](https://www.xilinx.com/support/download.html)** -> IMPORTANT: Before beginning the tutorial, make sure you have read and followed the Vitis Software Platform Release Notes (v2025.1) for setting up software and installing the VCK190 base platform. +> IMPORTANT: Before beginning the tutorial, make sure you have read and followed the Vitis Software Platform Release Notes (v2025.2) for setting up software and installing the VCK190 base platform. ## Overview @@ -135,7 +135,7 @@ Make sure to set the PLATFORM_REPO_PATHS environment variable. Enter the following command to source the Vitis tool: ``` -source //Vitis/2025.1/settings.sh +source //Vitis/2025.2/settings.sh ``` #### Set the DSP Library Path @@ -262,7 +262,8 @@ Next step is to verify the performance of the design. In the Graph View, select the *I/O* tab and observe the **Throughput** column for each ports. -The output PLIO port (PLIO_fft_o) throughput shows the value 2307.80 MBYTES PER SEC (MBPS). To get the throughput in Sample per second, this throughput needs to be divided by four because the data type used is cint16, which is four bytes in size. This gives a throughput value of 576.95 MSPS. +The output PLIO port (PLIO_fft_o) throughput shows the value 2307.08 MBYTES PER SEC (MBPS). To get the throughput in Sample per second, this throughput needs to be divided by four because the data type used is cint16, which is four bytes in size. This gives a throughput value of 576.77 MSPS. +Close the Vitis Analyzer. Optional: By running the make throughput command, it lists the throughput for the FIR and FFT output. This uses the custom python script which reads the time stamp from the output file and displays the value. @@ -376,7 +377,6 @@ make analyze ``` Select the Graph view and verify the number of FIR kernels. Similarly, verify the number of FFTs implemented. -![Graph View - Design 2](./images/Graph_view_ssr_gt1.png) Review reports such as Array and Trace. @@ -386,7 +386,7 @@ Next step is to verify the performance of the design. In the Graph View, select the *I/O* tab and observe the **Throughput** column for each ports. -The output of four PLIO ports (PLIO_fft_o_0, PLIO_fft_o_1, PLIO_fft_o_2, PLIO_fft_o_3) throughput shows the values 2853.16, 2853.16, 2853.16, 2853.16 MBYTES PER SEC (MBPS) repectively for each ports. To get the throughput in Sample per second, this throughput needs to be divided by four because the data type used is cint16, which is four bytes in size. This gives a throughput value of for each ports ~713.29 MSPS. There are four outputs and combined throughput of all output is ~2853 Msps. +The output of four PLIO ports (PLIO_fft_o_0, PLIO_fft_o_1, PLIO_fft_o_2, PLIO_fft_o_3) throughput shows the values 2853.55, 2851.97, 2852.36, 2852.76 MBYTES PER SEC (MBPS) repectively for each ports. To get the throughput in Sample per second, this throughput needs to be divided by four because the data type used is cint16, which is four bytes in size. This gives a throughput value of for each ports ~713 MSPS. There are four outputs and combined throughput of all output is ~2853 Msps. [Optional]: By running the make throughput command, it lists the throughput for the FIR and FFT output. This uses the custom python script which reads the time stamp from the output file and displays the value. @@ -443,7 +443,7 @@ Click **Next**. #### Select the Platform -Select the platform as *xilinx_vck190_base_202510_1*. +Select the platform as *xilinx_vck190_base_202520_1*. Click **Next** and review the Summary and then select **Finish**. diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/21-two_tone_filter/images/Graph_view_ssr_lt1.png b/AI_Engine_Development/AIE/Feature_Tutorials/21-two_tone_filter/images/Graph_view_ssr_lt1.png index 0b485d97ef..0629b9d4cf 100755 Binary files a/AI_Engine_Development/AIE/Feature_Tutorials/21-two_tone_filter/images/Graph_view_ssr_lt1.png and b/AI_Engine_Development/AIE/Feature_Tutorials/21-two_tone_filter/images/Graph_view_ssr_lt1.png differ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/21-two_tone_filter/images/Vitis_analyzer_reports.png b/AI_Engine_Development/AIE/Feature_Tutorials/21-two_tone_filter/images/Vitis_analyzer_reports.png index 8c361f8854..d7aaec4851 100755 Binary files a/AI_Engine_Development/AIE/Feature_Tutorials/21-two_tone_filter/images/Vitis_analyzer_reports.png and b/AI_Engine_Development/AIE/Feature_Tutorials/21-two_tone_filter/images/Vitis_analyzer_reports.png differ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/21-two_tone_filter/ssr_gt1/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/21-two_tone_filter/ssr_gt1/Makefile index 41bfff6e97..ad0f67245b 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/21-two_tone_filter/ssr_gt1/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/21-two_tone_filter/ssr_gt1/Makefile @@ -3,7 +3,7 @@ # SPDX-License-Identifier: X11 # */ -PLATFORM_VER := xilinx_vck190_base_202510_1 +PLATFORM_VER := xilinx_vck190_base_202520_1 PLATFORM := platform=${PLATFORM_REPO_PATHS}/${PLATFORM_VER}/${PLATFORM_VER}.xpfm PROJECT_PATH := $(shell pwd) SIM_OUTPUT := aiesimulator_output diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/21-two_tone_filter/ssr_lt1/makefile_flow/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/21-two_tone_filter/ssr_lt1/makefile_flow/Makefile index 729f1909cc..527acf50f1 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/21-two_tone_filter/ssr_lt1/makefile_flow/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/21-two_tone_filter/ssr_lt1/makefile_flow/Makefile @@ -3,7 +3,7 @@ # SPDX-License-Identifier: X11 # */ -PLATFORM_VER := xilinx_vck190_base_202510_1 +PLATFORM_VER := xilinx_vck190_base_202520_1 PLATFORM := platform=${PLATFORM_REPO_PATHS}/${PLATFORM_VER}/${PLATFORM_VER}.xpfm PROJECT_PATH := $(shell pwd) SIM_OUTPUT := aiesimulator_output diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/AIE_reload_whole_array/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/AIE_reload_whole_array/Makefile index 22950903b1..92d1479c72 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/AIE_reload_whole_array/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/AIE_reload_whole_array/Makefile @@ -6,9 +6,9 @@ TARGET = hw ARCH = aie ifeq ($(ARCH), aie) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm else ifeq ($(ARCH), aie-ml) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm else $(error ARCH is not supported) endif diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/README.md index ec624d5974..1c50dc6284 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/README.md @@ -14,7 +14,7 @@ # Compiling AI Engine Graphs for Independent Partitions & Partition Reloading -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction @@ -22,7 +22,7 @@ This tutorial demonstrates the workflow for compiling AI Engine graphs within AI The AI Engine graphs, which are distributed across different partitions, are independently verified using the AI Engine simulator and later integrated onto the device using the V++ linker and packager. This workflow is particularly well-suited for collaborative development, where multiple teams work concurrently on different parts of a system project, or when integrating user-developed designs with vendor-provided IPs (e.g., from AMD). ->**IMPORTANT**: Before beginning the tutorial, make sure you have installed AMD Vitis™ 2025.1 software. +>**IMPORTANT**: Before beginning the tutorial, make sure you have installed AMD Vitis™ 2025.2 software. The Vitis release includes all the embedded base platforms, including the VCK190 base platform that is used in this tutorial. In addition, ensure that you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). @@ -31,11 +31,11 @@ The 'common image' package contains a pre-built Linux kernel and root file syste Before starting this tutorial, run the following steps: 1. Open the directory where the Versal Common Image package is unzipped. -2. In a bash shell, run the ``/Common Images Dir/xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux`` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ``/Common Images Dir/xilinx-versal-common-v2025.1/sdk.sh`` file. -3. Set up your ROOTFS and IMAGE to point to the `rootfs.ext4` and image files located in the ``/Common Images Dir/xilinx-versal-common-v2025.1`` directory. +2. In a bash shell, run the ``/Common Images Dir/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux`` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ``/Common Images Dir/xilinx-versal-common-v2025.2/sdk.sh`` file. +3. Set up your ROOTFS and IMAGE to point to the `rootfs.ext4` and image files located in the ``/Common Images Dir/xilinx-versal-common-v2025.2`` directory. 4. Set up your PLATFORM_REPO_PATHS environment variable to ``$XILINX_VITIS/base_platforms``. -This tutorial targets the VCK190 production board for the 2025.1 version. +This tutorial targets the VCK190 production board for the 2025.2 version. ## Overview @@ -82,4 +82,3 @@ GitHub issues will be used for tracking requests and bugs. For questions go to [

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- diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/Makefile index a58d0140ca..421fd594ec 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/Makefile @@ -6,9 +6,9 @@ TARGET = hw ARCH = aie ifeq ($(ARCH), aie) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm else ifeq ($(ARCH), aie-ml) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm else $(error ARCH is not supported) endif @@ -50,19 +50,19 @@ __check_defined = \ $(error Undefined $1$(if $2, ($2)))) guard-PLATFORM_REPO_PATHS: - $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202510_1) + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded xilinx_vck190_base_202520_1) guard-ROOTFS: - $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.1/rootfs.ext4) + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v2025.2/rootfs.ext4) guard-IMAGE: - $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.1/Image) + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v2025.2/Image) guard-CXX: - $(call check_defined, CXX, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, CXX, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) guard-SDKTARGETSYSROOT: - $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux) + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux) ### diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/pr0_gmio/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/pr0_gmio/Makefile index 88c5d25bb3..25fdd4ecc3 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/pr0_gmio/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/pr0_gmio/Makefile @@ -6,9 +6,9 @@ TARGET = hw ARCH = aie ifeq ($(ARCH), aie) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm else ifeq ($(ARCH), aie-ml) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm else $(error ARCH is not supported) endif diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/pr0_gmio/sw/host.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/pr0_gmio/sw/host.cpp index 3b9a9c3375..315fd6277e 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/pr0_gmio/sw/host.cpp +++ b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/pr0_gmio/sw/host.cpp @@ -8,7 +8,7 @@ SPDX-License-Identifier: MIT #include "xrt/xrt_kernel.h" #include "xrt/xrt_graph.h" #include "xrt/xrt_aie.h" - +#include using namespace adf; void ref_func(int32* din,int32 c[8],int32* dout,int size){ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/pr1_rtp/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/pr1_rtp/Makefile index 662031c33d..6024ad773f 100755 --- a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/pr1_rtp/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/pr1_rtp/Makefile @@ -6,9 +6,9 @@ TARGET = hw ARCH = aie ifeq ($(ARCH), aie) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm else ifeq ($(ARCH), aie-ml) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm else $(error ARCH is not supported) endif diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/pr1_rtp/sw/host.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/pr1_rtp/sw/host.cpp index e31451d275..640e4c03bf 100755 --- a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/pr1_rtp/sw/host.cpp +++ b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/pr1_rtp/sw/host.cpp @@ -9,7 +9,6 @@ SPDX-License-Identifier: MIT #include #include "xrt/xrt_kernel.h" #include "xrt/xrt_graph.h" - const int ITERATION=4; const int ELEM_per_iter=256; int run(int argc, char* argv[]){ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/pr2_perf/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/pr2_perf/Makefile index 662031c33d..6024ad773f 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/pr2_perf/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/independent_graphs/pr2_perf/Makefile @@ -6,9 +6,9 @@ TARGET = hw ARCH = aie ifeq ($(ARCH), aie) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm else ifeq ($(ARCH), aie-ml) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm else $(error ARCH is not supported) endif diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/partition_reload.md b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/partition_reload.md index c120534837..d62d9deea6 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/partition_reload.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/partition_reload.md @@ -121,6 +121,22 @@ Following is an example code for controlling graph and associated GMIO data tran delete ghdl; delete hwctx_1; + + +**NOTE** + +In Vitis 2025.2, host applications that use xrt::aie::buffer and async calls ( i.e; bufIn->async() ) may encounter runtime failure because AIE resources remains allocated after the deleting the buffer/graph/hw_context objects, preventing subsequent xclbin loads. Symptoms include errors such as: + +[drm:zocl_create_aie [zocl]] *ERROR* Request AIE partition 262, -22 +[drm:zocl_aie_request_part_fd [zocl]] *ERROR* AIE partition 262 does not exist. + +As a workaround in 25.2, applications should explicitly call wait() on each xrt::aie::buffer that was launched via async() before deleting the hw context or ending of the applicaiton as shown below + + bufIn->wait(); + bufIn2->wait(); + +**Reloading partition** + To reload the same partition multiple times, there can be multiple approaches: 1. Exit and restart the application. When the hardware context is created again in host code, the corresponding AI Engine PDI is reloaded into the partition. diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/partition_reload_diff_graph/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/partition_reload_diff_graph/Makefile index fa7a59bed5..e78115ad9e 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/partition_reload_diff_graph/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/partition_reload_diff_graph/Makefile @@ -6,9 +6,9 @@ TARGET = hw ARCH = aie ifeq ($(ARCH), aie) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm else ifeq ($(ARCH), aie-ml) - PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202510_1/xilinx_vek280_base_202510_1.xpfm + PLATFORM ?= ${PLATFORM_REPO_PATHS}/xilinx_vek280_base_202520_1/xilinx_vek280_base_202520_1.xpfm else $(error ARCH is not supported) endif diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/partition_reload_diff_graph/pr0_gmio/sw/host.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/partition_reload_diff_graph/pr0_gmio/sw/host.cpp index 1f76c5f20b..63ecaad8a2 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/partition_reload_diff_graph/pr0_gmio/sw/host.cpp +++ b/AI_Engine_Development/AIE/Feature_Tutorials/23-AIE_independent_graphs/partition_reload_diff_graph/pr0_gmio/sw/host.cpp @@ -7,7 +7,7 @@ SPDX-License-Identifier: MIT #include "xrt/xrt_kernel.h" #include "xrt/xrt_graph.h" #include "xrt/xrt_aie.h" - +#include void ref_func(int* din,int c[8],int* dout,int size){ static int d[8]={0,0,0,0,0,0,0,0}; for(int i=0;iwait(); - + bufIn->wait(); ref_func(dinArray,coeff,doutRef,ITERATION*1024/4); for(int i=0;iwait(); - + bufIn2->wait(); for(int i=0;i void ref_func(int* din,int c[8],int* dout,int size){ static int d[8]={0,0,0,0,0,0,0,0}; for(int i=0;iwait(); - + bufIn->wait(); ref_func(dinArray,coeff,doutRef,ITERATION*1024/4); for(int i=0;iwait(); - + bufIn2->wait(); for(int i=0;i void ref_func(int* din,int c[8],int* dout,int size){ static int d[8]={0,0,0,0,0,0,0,0}; for(int i=0;i/dev/null | grep "vivado ") VITIS_VERSION := $(shell vitis -version 2>/dev/null | grep "Vitis " | sed 's/\*//g') diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/README.md index be671a4bed..3f231a51ea 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/README.md @@ -15,10 +15,11 @@ # RTL / AI Engine interfacing Examples -***Version: Vivado / Vitis 2025.1*** +***Version: Vivado / Vitis 2025.2*** ## Introduction -The AI Engine can be connected to the Programmable Logic (PL) using AXI compliant AXI4-Stream interfaces. In most availabe examples, the connectivity between the PL and the AI Engine is shown using HLS kernels connected to the DDR as the default VCK190 base platform does not include any other blocks than the infrastructure blocks. To accelerate part of an application, connecting the AI Engine to a user's existing RTL requires knowledge of the AXI-Stream protocol and how it can be used to connect with the AI Engines using the AMD Vitis™ Acceleration flow. It might require some modification or bridging from the existing RTL. For example, to communicate with the AI Engine, the RTL needs to have a compliant AXI4-Stream interace (for example, it needs to be able to handle back pressure when tready is low). + +The AMD Versal AI Engine can be connected to the Programmable Logic (PL) using AXI compliant AXI4-Stream interfaces. In most availabe examples, the connectivity between the PL and the AI Engine is shown using HLS kernels connected to the DDR as the default VCK190 base platform does not include any other blocks than the infrastructure blocks. To accelerate part of an application, connecting the AI Engine to a user's existing RTL requires knowledge of the AXI-Stream protocol and how it can be used to connect with the AI Engines using the AMD Vitis™ Acceleration flow. It might require some modification or bridging from the existing RTL. For example, to communicate with the AI Engine, the RTL needs to have a compliant AXI4-Stream interace (for example, it needs to be able to handle back pressure when tready is low). This tutorial shows multiple examples on how to connect RTL blocks with AXI4-Stream present in a custom platform to the AI Engine using the Vitis Acceleration flow. --- @@ -111,12 +112,10 @@ vitis -w Vitis/workspace_1/ ![Waveforms](./images/hw_emu.jpg) -5. After ~10us of simulation time, you see transactions on the AXI4-Stream interfaces from and to the AI Engine demonstrating the good behaviour of the design. +5. After ~15us of simulation time, you see transactions on the AXI4-Stream interfaces from and to the AI Engine demonstrating the good behaviour of the design. ![Waveforms](./images/251_hw_emu_1.jpg) -> ***Note***: In the Vitis workspace, you can see an application called `dummy_ps_app`. This application is just a simple hello_world application, which is running on the A72 processors. Running this application runs the PMC, which is loading the AI Engine. The application is added to the packaged file using the option ps_elf in `package.cfg`. - > ***Note***: The option `enable_aie_debug` is set to *false* in the `package.cfg`. With this option set to true, the AI Engine waits for the Vitis IDE to connect to the emulation and start the AI Engine. In this case, there is no need to debug inside the AI Engine, thus this option is set to *false*. --- @@ -127,10 +126,6 @@ As the V++ linker is only able to work inside a BD, add an IP block inside it to ### Hardware Platform In this example, the Vivado design consists of a top-level RTL file, which instantiates the AXI4S_Counter and the dummy Sink IPs used in the previous part as well as a BD. The BD was generated from the CED and contains all the required elements for the Vitis acceleration flow. - - In the BD, two instances of the AXI4-Stream Register slice IP are added. They are configured in such way that they only act as a pass-through thus can be considered as wires. But they are required to have AXI4-Stream interfaces to which the V++ linker can connect the AI Engine. One side of these IP instances (M00_AXIS for one and S00_AXIS for the other) is connected to the external ports of the BD (which are then connected to the AXI4S_Counter and the dummy Sink IPs inside the top level). The other interfaces are left uncorrected and added to the plaform, similar to what was done in **Part 1**. ``` @@ -184,7 +179,7 @@ vitis -w Vitis/workspace_2/ ## Part 3 - Connecting Monitored RTL Interfaces to AI Engine ### Creating the design -In some cases, it can be useful to add debug capabilities to the interfaces to monitor the data that is going in and out of the array. When using RTL interfaces (this type of design is called flat design), ILAs cannot be added directly by v++ link. One way of adding the debug capabilities is to add the ILAs directly into the Vivado design. This is what is done in the design from **Part 1**: +In some cases, it can be useful to add debug capabilities to the interfaces to monitor the data that is going in and out of the array. One way of adding the debug capabilities is to add the ILAs directly into the Vivado design. This is what is done in this part using the design from **Part 1**: ![Custom IPs with ILAs](./images/custom_IPs_ILAs.jpg) @@ -218,7 +213,46 @@ To run the design and observe the traces from the ILAs, open Vivado. ![ILA Output](./images/ILA_output.jpg) --- -## Part 4 - Broadcasting Data to the AI Engine and the Programmable +## Part 4 - Monitoring the AI Engine interfaces using V++ Link + +### Creating the design +Another way to add ILA to monitor the activity to/from the AI Engine is to add ILA from V++ link. In this part, we will use the same vivado design from **Part 1** and only add debug options to v++ to add the ILAs to the AI Engine interfaces. + +To build the full project, including the Vivado HW design and the Vitis project, run the following command: +``` +make all ILA_VPP=1 +``` + +The only difference with the project from **Part 1** are the following line to the config file for the v++ link stage +``` +[debug] +aie.chipscope=PLIO_i_0 +aie.chipscope=PLIO_o_0 +``` +![CFG file](./images/252_cfg_vpp_ila.jpg) + +If we open the Vivado design generated from v++ (Vitis/workspace_4/system_project/build/hw/hw_link/binary_container_1/binary_container_1/vivado/vpl/prj/prj.xpr) we can see one ILA added in the Vitis region monitoring the input and output PLIOs of the AI Engine: + +![CFG file](./images/252_design_vpp_ila.jpg) + +### Running the Design in Hardware + +To run the design and observe the traces from the ILAs, open Vivado. + +1. Prepare the VCK190 by connecting the UART/JTAG USB cable to your compute and set the boot mode to JTAG. + +2. Power on the VCK190. + +3. Open Vivado and open the Vivado HW manager. + +4. Connect to the target and program the device using the generated `BOOT.BIN` (`Vitis/workspace_4/system_project/build/hw/package/package/BOOT.BIN`) and use the `.ltx` file from the V++ linker generated Vivado project (`Vitis/workspace_3/system_project/build/hw/hw_link/binary_container_1/binary_container_1/vivado/vpl/prj/prj.runs/impl_1/debug_nets.ltx`). + +5. Open the ILA view and run auto trigger. You should see activity going in and out of the AI Engine + +![ILA configuration](./images/251_vpp_ila_hw.jpg) + +--- +## Part 5 - Broadcasting Data to the AI Engine and the Programmable In some cases, the same data might need to be processed by both the AI Engine and the PL so you might need a way to broadcast the data to both the domains. On important thing to keep in mind with working with compliant AXI4-Stream interfaces (as the AI Engine expects an AXI4-Stream compliant interface) is that the master and slave interfaces need to handle the handshaking protocol (with tvalid and tready). Thus, when connecting multiple slaves to a single master is not as simple as connecting the two slaves to the same master interface (as there would be two tready signals). The master would need to handle the logic between the two tready from the slaves. Another option is to use an IP that would handle this for you. In the Vivado catalog, the AXI4-Stream Broadcaster IP is intended for this type of use case. @@ -245,9 +279,9 @@ make all AXI4S_BROADCAST=1 You can verify the good behaviour of the design running through Hardware emulation and looking at the waveforms, using the same steps as in **Part 1**. To run the Hardware Emulation and visualize the waveforms of the AXI4-Stream interfaces, go through the following steps: -1. Open the workspace_4 in Vitis IDE. +1. Open the workspace_5 in Vitis IDE. ``` -vitis -w Vitis/workspace_4/ +vitis -w Vitis/workspace_5/ ``` 2. In the flow navigator, make sure the component system project is selected and click on **Start Emulator** under **Hardware Emulation**. @@ -256,7 +290,7 @@ vitis -w Vitis/workspace_4/ 4. Add the AXIS interface signals (tready, tvalid, tdata) from the AXI4S_Counter_0 IP and the S00_AXIS from the dummy_sink_0 IP to the waveform window and run the simulation for 30us. -5. After ~10us of simulation time, you see transactions on the AXI4-Stream interfaces from the AXI4-Stream broadcaster to the AI Engine, the AXI4-Stream broadcaster to the PL and from the AI Engine to the PL demonstrating the good behaviour of the design. +5. After ~15us of simulation time, you see transactions on the AXI4-Stream interfaces from the AXI4-Stream broadcaster to the AI Engine, the AXI4-Stream broadcaster to the PL and from the AI Engine to the PL demonstrating the good behaviour of the design. ![HW emulation waveforms](./images/hw_emu_AXIS_broadcast.jpg) diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/Vitis/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/Vitis/Makefile index 663b75a697..2e4be96d60 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/Vitis/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/Vitis/Makefile @@ -24,15 +24,22 @@ ifeq ($(INCLUDE_ILAS), 0) TARGET := hw_emu else ifeq ($(AXI4S_BROADCAST), 1) - DESIGN_PART := 4 + DESIGN_PART := 5 XSA := custom_pfm_strmIn_strmOut_AXIS_Broadcast.xsa VITIS_PLATFORM := custom_pfm_strmIn_strmOut_AXIS_Broadcast_0_1 TARGET := hw_emu else - XSA := custom_pfm_strmIn_strmOut.xsa - VITIS_PLATFORM := custom_pfm_strmIn_strmOut_0_1 - DESIGN_PART := 1 - TARGET := hw_emu + ifeq ($(ILA_VPP), 1) + XSA := custom_pfm_strmIn_strmOut.xsa + VITIS_PLATFORM := custom_pfm_strmIn_strmOut_0_1 + DESIGN_PART := 4 + TARGET := hw + else + XSA := custom_pfm_strmIn_strmOut.xsa + VITIS_PLATFORM := custom_pfm_strmIn_strmOut_0_1 + DESIGN_PART := 1 + TARGET := hw_emu + endif endif endif diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/Vitis/vitis_pfm.py b/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/Vitis/vitis_pfm.py index db9ec68467..05cd4bf131 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/Vitis/vitis_pfm.py +++ b/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/Vitis/vitis_pfm.py @@ -26,3 +26,5 @@ platform = client.get_component(name=component_name) status = platform.build() + +vitis.dispose() \ No newline at end of file diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/Vitis/vpp_link.py b/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/Vitis/vpp_link.py index 155cb8f822..38b284d2a4 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/Vitis/vpp_link.py +++ b/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/Vitis/vpp_link.py @@ -19,21 +19,6 @@ platform_path=app_path+"/workspace_"+design_part+"/"+platform_name+"/export/"+platform_name+"/"+platform_name+".xpfm" -# -# Create Embedded Platform for dummy PS app -# -platform = client.create_platform_component(name = "vck190_hw",hw_design = "vck190",os = "standalone",cpu = "psv_cortexa72_0",domain_name = "standalone_psv_cortexa72_0") -platform = client.get_component(name="vck190_hw") -status = platform.build() - -# -# Create dummy PS app -# -comp = client.create_app_component(name="dummy_ps_app",platform = app_path+"/workspace_"+design_part+"/vck190_hw/export/vck190_hw/vck190_hw.xpfm",domain = "standalone_psv_cortexa72_0") -comp = client.get_component(name="dummy_ps_app") -status = comp.import_files(from_loc="./src/ps_app", files=["dummy_ps_app.c", "platform.c", "platform.h"], dest_dir_in_cmp = "src") -comp.build() - # # Create System Project # @@ -49,12 +34,14 @@ cfg.add_values(section='connectivity', key='sc', values=['master_axi_1:ai_engine_0.PLIO_i_0']) cfg.add_values(section='connectivity', key='sc', values=['ai_engine_0.PLIO_o_0:slave_axi_1']) +if (design_part=="4"): + cfg.add_values(section='debug', key='aie.chipscope', values=['PLIO_i_0']) + cfg.add_values(section='debug', key='aie.chipscope', values=['PLIO_o_0']) # # Edit Packager configuration # cfg = client.get_config_file(proj.project_location+'/package/package.cfg') cfg.set_value(section='package', key='enable_aie_debug', value='false') -cfg.add_values(section='package', key='ps_elf', values=[app_path+"/workspace_"+design_part+"/dummy_ps_app/build/dummy_ps_app.elf,a72-0"]) proj.build(target = target_sys) diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/images/252_cfg_vpp_ila.jpg b/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/images/252_cfg_vpp_ila.jpg new file mode 100755 index 0000000000..b9d62b4bc7 Binary files /dev/null and b/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/images/252_cfg_vpp_ila.jpg differ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/images/252_design_vpp_ila.jpg b/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/images/252_design_vpp_ila.jpg new file mode 100755 index 0000000000..59bbd0230a Binary files /dev/null and b/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/images/252_design_vpp_ila.jpg differ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/images/252_vpp_ila_hw.jpg b/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/images/252_vpp_ila_hw.jpg new file mode 100755 index 0000000000..1ca23003ee Binary files /dev/null and b/AI_Engine_Development/AIE/Feature_Tutorials/24-aie_pl_interface/images/252_vpp_ila_hw.jpg differ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/25-AIE-kernel-optimization/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/25-AIE-kernel-optimization/Makefile index 8d8d60438e..c61a5955b8 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/25-AIE-kernel-optimization/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/25-AIE-kernel-optimization/Makefile @@ -8,9 +8,9 @@ ECHO = @echo export TARGET = hw_emu -RELEASE=2025.1 +RELEASE=2025.2 BOARD=vck190 -BASE_NUM=202510_1 +BASE_NUM=202520_1 # Platform Selection... VERSAL_VITIS_PLATFORM = xilinx_${BOARD}\_base_${BASE_NUM} diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/25-AIE-kernel-optimization/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/25-AIE-kernel-optimization/README.md index 1c3a16b64f..d30059b24a 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/25-AIE-kernel-optimization/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/25-AIE-kernel-optimization/README.md @@ -15,7 +15,7 @@ # AI Engine Algorithm Performance Optimization -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Table of Contents @@ -514,7 +514,7 @@ As you gain experience working with AI Engine architecture and applying these pr [[1]]: Versal Adaptive SoC AI Engine Architecture Manual ([AM009](https://docs.amd.com/r/en-US/am009-versal-ai-engine)). -[[2]]: Vitis Accelerated Flow Reference Guide ([UG1702](https://docs.amd.com/r/en-US/ug1702-vitis-accelerated-reference)). +[[2]]: Vitis Reference Guide ([UG1702](https://docs.amd.com/r/en-US/ug1702-vitis-accelerated-reference)). [[3]]: Bilinear interpolation. 16 Dec 2024, 22:13 UTC. In Wikipedia: The Free Encyclopedia. Wikimedia Foundation Inc. Encyclopedia on-line. Available from [wikipedia.org/wiki/Bilinear_interpolation](https://en.wikipedia.org/wiki/Bilinear_interpolation). Internet. 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a/AI_Engine_Development/AIE/Feature_Tutorials/25-AIE-kernel-optimization/labA/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/25-AIE-kernel-optimization/labA/Makefile @@ -7,7 +7,7 @@ SRC_DIR := ./src MY_SOURCES := $(shell find $(SRC_DIR) -name *.cpp) $(shell find $(SRC_DIR) -name *.h) -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm COMPILE_OPTS := --aie.pl-freq=625 --aie.adf-api-log-level=2 --aie.kernel-linting \ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/25-AIE-kernel-optimization/labB/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/25-AIE-kernel-optimization/labB/Makefile index 5d0e4bcffa..5cbba30931 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/25-AIE-kernel-optimization/labB/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/25-AIE-kernel-optimization/labB/Makefile @@ -7,7 +7,7 @@ SRC_DIR := ./src MY_SOURCES := $(shell find $(SRC_DIR) -name *.cpp) $(shell find $(SRC_DIR) -name *.h) -PLATFORM_USE := xilinx_vck190_base_202510_1 +PLATFORM_USE := xilinx_vck190_base_202520_1 PLATFORM := ${PLATFORM_REPO_PATHS}/${PLATFORM_USE}/${PLATFORM_USE}.xpfm COMPILE_OPTS := --aie.pl-freq=625 --aie.adf-api-log-level=2 --aie.kernel-linting \ diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/README.md index 6efdb3042c..6e0b913fae 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/README.md @@ -15,7 +15,7 @@ # A "Gentle" Introduction to AI Engine Kernel Programming -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Overview diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/avx_aie/aie/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/avx_aie/aie/Makefile index cbdf08c349..d15c2ea299 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/avx_aie/aie/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/avx_aie/aie/Makefile @@ -3,7 +3,7 @@ # SPDX-License-Identifier: MIT ##################################################################### -PLATFORM_REPO_PATHS = $(XILINX_VITIS)/base_platforms +#PLATFORM_REPO_PATHS = $(XILINX_VITIS)/base_platforms CURRENT_DIR = $(shell pwd) WKSPC_DIR = $(abspath $(dir $(lastword $(MAKEFILE_LIST)))/..) @@ -17,7 +17,7 @@ AIE_DATA_DIR = ./data RM = rm -f RMDIR = rm -rf -PLATFORM_VERSION = 202420_1 +PLATFORM_VERSION = 202520_1 PLATFORM ?= $(PLATFORM_REPO_PATHS)/xilinx_vck190_base_$(PLATFORM_VERSION)/xilinx_vck190_base_$(PLATFORM_VERSION).xpfm # AIE compiler settings @@ -40,4 +40,4 @@ clean: rm -rf Emulation-SW .PHONY: incremental clean -incremental: clean all \ No newline at end of file +incremental: clean all diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/contrived/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/contrived/Makefile index fe9ead0457..148b91f8e7 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/contrived/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/contrived/Makefile @@ -12,8 +12,8 @@ AIE_CC = aiecompiler AIE_TOP_FILE = ../src/tb.cpp AIE_OUT_DIR = ./Work -PLATFORM_REPO_PATHS = $(XILINX_VITIS)/base_platforms -PLATFORM_VERSION = 202420_1 +#PLATFORM_REPO_PATHS = $(XILINX_VITIS)/base_platforms +PLATFORM_VERSION = 202520_1 PLATFORM ?= $(PLATFORM_REPO_PATHS)/xilinx_vck190_base_$(PLATFORM_VERSION)/xilinx_vck190_base_$(PLATFORM_VERSION).xpfm # Compiler settings diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/unit_tests/matmul/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/unit_tests/matmul/Makefile index 24b433f780..5dd7646d53 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/unit_tests/matmul/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/unit_tests/matmul/Makefile @@ -12,8 +12,8 @@ AIE_CC = aiecompiler AIE_TOP_FILE = ../src/tb.cpp AIE_OUT_DIR = ./Work -PLATFORM_REPO_PATHS = $(XILINX_VITIS)/base_platforms -PLATFORM_VERSION = 202420_1 +#PLATFORM_REPO_PATHS = $(XILINX_VITIS)/base_platforms +PLATFORM_VERSION = 202520_1 PLATFORM ?= $(PLATFORM_REPO_PATHS)/xilinx_vck190_base_$(PLATFORM_VERSION)/xilinx_vck190_base_$(PLATFORM_VERSION).xpfm # Compiler settings diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/unit_tests/mtxvec/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/unit_tests/mtxvec/Makefile index 4c4d4935f6..e8596f7884 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/unit_tests/mtxvec/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/unit_tests/mtxvec/Makefile @@ -12,8 +12,8 @@ AIE_CC = aiecompiler AIE_TOP_FILE = ../src/tb.cpp AIE_OUT_DIR = ./Work -PLATFORM_REPO_PATHS = $(XILINX_VITIS)/base_platforms -PLATFORM_VERSION = 202420_1 +#PLATFORM_REPO_PATHS = $(XILINX_VITIS)/base_platforms +PLATFORM_VERSION = 202520_1 PLATFORM ?= $(PLATFORM_REPO_PATHS)/xilinx_vck190_base_$(PLATFORM_VERSION)/xilinx_vck190_base_$(PLATFORM_VERSION).xpfm # Compiler settings diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/unit_tests/sqmag/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/unit_tests/sqmag/Makefile index 62dc225bc2..013783f78b 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/unit_tests/sqmag/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/unit_tests/sqmag/Makefile @@ -12,8 +12,8 @@ AIE_CC = aiecompiler AIE_TOP_FILE = ../src/tb.cpp AIE_OUT_DIR = ./Work -PLATFORM_REPO_PATHS = $(XILINX_VITIS)/base_platforms -PLATFORM_VERSION = 202420_1 +#PLATFORM_REPO_PATHS = $(XILINX_VITIS)/base_platforms +PLATFORM_VERSION = 202520_1 PLATFORM ?= $(PLATFORM_REPO_PATHS)/xilinx_vck190_base_$(PLATFORM_VERSION)/xilinx_vck190_base_$(PLATFORM_VERSION).xpfm # Compiler settings diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/unit_tests/sumdiff/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/unit_tests/sumdiff/Makefile index 2748e54820..02ebf82dfb 100644 --- a/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/unit_tests/sumdiff/Makefile +++ b/AI_Engine_Development/AIE/Feature_Tutorials/26-gentle_intro_to_aie_kernel_programming/unit_tests/sumdiff/Makefile @@ -12,8 +12,8 @@ AIE_CC = aiecompiler AIE_TOP_FILE = ../src/tb.cpp AIE_OUT_DIR = ./Work -PLATFORM_REPO_PATHS = $(XILINX_VITIS)/base_platforms -PLATFORM_VERSION = 202420_1 +#PLATFORM_REPO_PATHS = $(XILINX_VITIS)/base_platforms +PLATFORM_VERSION = 202520_1 PLATFORM ?= $(PLATFORM_REPO_PATHS)/xilinx_vck190_base_$(PLATFORM_VERSION)/xilinx_vck190_base_$(PLATFORM_VERSION).xpfm # Compiler settings @@ -64,4 +64,4 @@ clean: rm -rf .logger .PHONY: incremental clean -incremental: clean all \ No newline at end of file +incremental: clean all diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/Makefile new file mode 100755 index 0000000000..e1d9ae17a2 --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/Makefile @@ -0,0 +1,187 @@ +# +#Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +#SPDX-License-Identifier: MIT +# + +include ./common.mk +include ./verif_path.mk + + +######################################### +# +# SYSTEM FILENAMES +# +######################################## +XSA := ${PNAME}.xsa +HOST_EXE := host.exe +HOST_API_EXE := host_api.exe +LIBADF := $(AIE_DIR)/libadf.a + + +########################################################################################################################################################## +### DO NOT MODIFY BELOW THIS LINE UNLESS NECESSARY +################################################################################################################################################ + +KERNEL_CPP := $(KERNELS_DIR)/gen2s_$(DATAW)_$(PLIOW).cpp \ + $(KERNELS_DIR)/s2mm_$(DATAW)_$(PLIOW).cpp +XO_FILES := $(subst .cpp,.xo,$(KERNEL_CPP)) + +XOS = $(XO_FILES) +VCC = v++ +VPP_SPEC = $(ADDON_DIR)/system_$(strip $(NAntenna)).cfg +VPP_FLAGS =--save-temps --verbose --config ${VPP_SPEC} + +ifeq ($(strip $(ENABLE_TRACE)),true) + VPP_FLAGS += --profile.data all:all:all +endif + +.PHONY: clean run_hw_emu data + +disp: + echo $(KERNELS_DIR) + echo $(XOS) + + + +### +.PHONY: all_hw all_hw_emu run upd_host_hw aie postaie data aiesim aieviz aiesim-fifo compareaie x86 x86sim comparex86 + + +###################################################################### +# +# Full chains +# +###################################################################### + +build_hw: + make TARGET=hw clean data aie kernels xclbin host package + +build_hw_emu: + make TARGET=hw_emu clean data aie kernels xclbin host package + +launch_hw_emu: + ./launch_hw_emu.sh -add-env AIE_COMPILER_WORKDIR=$(AIE_DIR)/Work -aie-sim-options $(ADDON_DIR)/aiesim_options.txt -run-app embedded_exec.sh + +run_hw_emu: + make build_hw_emu launch_hw_emu + +upd_host_hw: + make TARGET=hw host package + +###################################################################### +# +# AIE Compilation/Simulation +# +###################################################################### +aie: + make -C $(AIE_DIR) aie + +postaie: + make -C $(AIE_DIR) aie XSA=../${PNAME}.xsa + +data: + make -C $(AIE_DIR) data + +aiesim: + make -C $(AIE_DIR) aiesim + +aieviz: + make -C $(AIE_DIR) aieviz + +simviz: + make -C $(AIE_DIR) simviz + +x86: + make -C $(AIE_DIR) x86 + +x86sim: + make -C $(AIE_DIR) x86sim + +###################################################################### +# +# PL Kernels compilation +# +###################################################################### + +kernels: guard-PLATFORM_REPO_PATHS ${XOS} +${XOS}: + make -C pl_kernels/ PLATFORM=${PLATFORM} all + + +###################################################################### +# +# System Link +# +###################################################################### + +xclbin: guard-PLATFORM_REPO_PATHS ${XSA} +${XSA}: ${LIBADF} ${VPP_SPEC} ${XOS} + ${VCC} -g -l --platform ${PLATFORM} ${XOS} ${LIBADF} -t ${TARGET} ${VPP_FLAGS} -o $@ + +$(VPP_SPEC): + make -C $(ADDON_DIR) all + +###################################################################### +# +# PS host code compilation +# +###################################################################### + +host: guard-CXX guard-SDKTARGETSYSROOT ${HOST_EXE} +${HOST_EXE}: $(HOST_DIR)/*.cpp + make -C $(HOST_DIR) AIE_DIR=$(AIE_DIR) all + + +###################################################################### +# +# Packaging --> SD Card Image +# and creates directory to Store Profile Data +# +###################################################################### + +package: guard-ROOTFS guard-IMAGE guard-PLATFORM_REPO_PATHS package_${TARGET} +package_${TARGET}: ${LIBADF} ${XSA} ${HOST_EXE} + ${VCC} -p -t ${TARGET} -f ${PLATFORM} \ + --package.rootfs ${ROOTFS} \ + --package.kernel_image ${IMAGE} \ + --package.boot_mode=sd \ + --package.image_format=ext4 \ + --package.defer_aie_run \ + --package.sd_dir $(AIE_DIR)/data \ + --package.sd_file $(ADDON_DIR)/embedded_exec.sh \ + --package.sd_file $(ADDON_DIR)/xrt.ini \ + --package.sd_file $(ADDON_DIR)/newdir \ + --package.sd_file $(ADDON_DIR)/newdir_api \ + --package.sd_file ${HOST_EXE} ${XSA} ${LIBADF} \ + --package.sd_file ${HOST_API_EXE} + zip sd_card_$(shell date +%y%m%d_%H%M)_SysLevelTrace.zip sd_card.img + mkdir -p ProfileData + +###################################################################### +# +# Clean functions +# +###################################################################### + +clean: + rm -rf _x v++_* ${XOS} ${OS} ${LIBADF} *.o.* *.o *.xpe *.xo.* \ + vek280*.xclbin* vck190*.xclbin* *.xsa *.log *.jou xnwOut Work Map_Report.csv \ + ilpProblem* sol.db drivers .Xil *bin *BIN *.bif launch_hw_emu.sh cfg emu_qemu_scripts \ + [!d]*.json *.txt *.wdb *.wcfg *.pdi v++.package_summary sim qemu_dts_files sd_card sd_card.img \ + dtb_creation.sh .ipcache *summary *.sh .AIE_SIM_CMD_LINE_OPTIONS .crashReporter logs .wsdata sd_card_*_SysLevelTrace.zip _ide \ + analyzer_input baremetal_metadata_package.cpp + make -C ${AIE_DIR} clean + make -C ${KERNELS_DIR} clean + make -C ${HOST_DIR} clean + +clean-all: clean + make clean + make -C ${AIE_DIR} clean-all + +soft-clean: + make -C ${AIE_DIR} soft-clean + +clean-git: clean-all + rm -rf ProfileData + rm -rf images/Thumbs.db + diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/README.md new file mode 100755 index 0000000000..91b46a8237 --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/README.md @@ -0,0 +1,265 @@ + + + + + +

AI Engine Development

+ See Vitis™ Development Environment on xilinx.com
 + See Vitis™ AI Development Environment on xilinx.com +
+ + + +# System Timeline Tutorial + +***Version: Vitis 2025.2*** + +This small tutorial is based on a basic design to test Vitis System Timeline feature. + +## Introduction + +In Vitis 2025.2 AMD introduced a new (early access) feature called **System Timeline**. This allows the user to trace all subsystems of the device (PL, PS and EI Engine array) and display them in Vitis Analyzer on the same graph with sychronized timeline. The goal is to have a deeper understanding of the way the various elements of the system work together and track system controller bugs: missing kernel start, wrong number of iterations... + + +>**IMPORTANT**: Before beginning the tutorial make sure you have installed the AMD Vitis™ 2025.2 software. The Vitis release includes all the embedded base platforms including the VCK190 base platform that is used in this tutorial. In addition, ensure you have downloaded the Common Images for Embedded Vitis Platforms from [this link](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html). + +The ‘common image’ package contains a prebuilt Linux kernel and root file system that can be used with the AMD Versal™ board for embedded design development using the Vitis software platform. + +Before starting this tutorial, run the following steps: + +1. Go to the directory where you have unzipped the Versal Common Image package. +2. In a Bash shell, run the ``/Common Images Dir/xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux`` script. This script sets up the SDKTARGETSYSROOT and CXX variables. If the script is not present, you must run the ``/Common Images Dir/xilinx-versal-common-v2025.2/sdk.sh``. +3. Set up your ROOTFS and IMAGE to point to the ``rootfs.ext4`` and Image files located in the ``/Common Images Dir/xilinx-versal-common-v2025.2`` directory. +4. Set up your PLATFORM_REPO_PATHS environment variable to ``$XILINX_VITIS/base_platforms``. + +This tutorial targets VCK190 production board for 2025.2 version. + +Data generation for this tutorial requires [Python 3](https://www.python.org/downloads/). The following packages are required: + +- os +- sys +- numpy + +>**Note**: This tutorial assumes that you have a basic understanding of the Adaptive Data Flow (ADF) API and Xilinx® Runtime (XRT) API usage. For more information about ADF API and XRT usage, refer to AI Engine Runtime Parameter Reconfiguration Tutorial and the Versal Adaptive SoC AI Engine Programming Environment User Guide ([UG1076](https://docs.amd.com/access/sources/dita/map?isLatest=true&ft:locale=en-US&url=ug1076-ai-engine-environment)). + +## Objectives + +After completing this tutorial, you will be able to: + +- Follow the complete flow to enable System Timeline for Hw debug. + + +## System Timeline complete flow + +This tutorial is decomposed in 6 stages: + +- AI Engine design and compilation +- PL kernels compilation +- Link stage to create the xsa with the AI Engine interface and the PL Kernels +- Host code compilation +- Packaging and create SD card image +- Run the design on the board and capture the trace +- Analyze the trace + +The Makefile is built so that you can address each step alone or concatenate all steps in a single command: + +```Makefile +build_hw: + make TARGET=hw clean data aie kernels xclbin host package +``` + + +### AI Engine design and compilation + +The design is based on the replication of the same processing chain: + +1. Passthrough. +2. Filtering. +3. Gain. +4. Passthrough. + +The filter and the gain kernels receive asynchronous RTP to set the coefficients and the gain value. + +By default 4 of these chains are implemented in the design. It can be changed using the Makefile parameter `NAntenna`. + +In `graph.cpp` the graph is instanciated as follows: `MyGraph G("");`. The value `40` means that a utilization ratio of 40% is specified for the filter and the gain leading to a co-location for these 2 kernels. If you want them in different tiles, just replace by a value above 50. + +Here is the subgraph of the 4th antenna: + +![No graph image](images/AIEgraph.png) + +What is important is that during the compilation, the user should declare that trace events should be extracted during runtime. Some specific flags have to be set depending on the way to extract these events: through GMIO or PLIO: + +**GMIO based event extraction** + +*aiecompiler_trace_gmio_options.cfg* + +```shell +[aie] +event-trace=runtime +broadcast-enable-core=true +event-trace-port=gmio +xlopt=0 +``` + +**PLIO based event extraction** + +*aiecompiler_trace_plio_options.cfg* + +```shell +[aie] +event-trace=runtime +broadcast-enable-core=true +num-trace-streams=16 +event-trace-port=plio +trace-plio-width=128 +xlopt=0 +``` + +Here are some options definitions: +- `event-trace=runtime`: trace events will be specified at runtime. This is actually the only possible option for hardware tracing. +- `broadcast-enable-core=true`: ensures that the enable core signals are broadcasted so that all kernels start within a few clock cycles of each other. +- `event-trace-port=gmio/plio`: selects the port type used for event tracing. GMIO is generally used for designs with limited PL resources, while PLIO is preferred for designs with sufficient PL resources. +- `num-trace-streams=16`: sets the number of trace streams within the AI Engine array to be used for event tracing. The default is 4 streams, the maximum is 16. Increasing the number of streams can help reduce contention within the trace data path, especially in designs with a large number of active kernels. The drawback is that it would use more resource making it more difficult for the router to route the AI Engine design by itself. +- `trace-plio-width=128`: specifies the width of the PLIO trace interface. +- `xlopt=0`: disables extra optimizations that could interfere with event tracing. Typically the compiler will avoid inlining the kernels within the main function, allowing the user to see each kernel as a separate entity in the trace and have a clear view of all iterations. + +### Link stage + +PL Trace is enabled during system link stage. This is done adding the `--profile.data` flag to the `v++` command line. + +```shell +v++ -g -l --platform ${PLATFORM} ${XOS} ${LIBADF} -t hw --save-temps --verbose --config ${VPP_SPEC} --profile.data all:all:all -o XCLBIN_File +``` + +The --profile option can be used to profile many different activities. For more information, see [--profile Options in UG1702](https://docs.amd.com/r/en-US/ug1702-vitis-accelerated-reference/profile-Options). + +. +`--profile.data all:all:all` will monitor data on all kernels and compute units. + + +### Run on hardware + +The packaging step is creating a zip version of the sd card image that can be used in any usual SD Card flash software like Balena Etcher. + +When the application is run on hardware, using XRT on Linux, the trace is captured using the following `xrt.ini` file specification: + +```shell +# Debug group for the aie, ps and pl +[Debug] +aie_profile = false +aie_trace = true +device_trace=fine +continuous_trace = true +host_trace=true + +# PL Trace buffer +trace_buffer_size = 32M +trace_buffer_offload_interval_ms = 5 + +# Subsection for AIE profile settings only if aie_profile is set to true +[AIE_profile_settings] +# Interval in between reading counters (in us) +interval_us = 1000 + +tile_based_aie_metrics = all:heat_map +tile_based_aie_memory_metrics = all:conflicts +tile_based_interface_tile_metrics = all:output_throughputs + + +# Subsection for AIE Trace only if aie_trace is set to true +[AIE_trace_settings] +# PLIO +reuse_buffer = true +periodic_offload = true +buffer_offload_interval_us = 50 +buffer_size = 100M + +tile_based_aie_tile_metrics = all:functions +enable_system_timeline = true + +[Runtime] +verbosity = 10 +``` + +The option `enable-system-timeline`is true by default. More information can be found at [*xrt.ini* file in UG1702](https://docs.amd.com/r/en-US/ug1702-vitis-accelerated-reference/xrt.ini-File). + +Plug the sd card in your board, connect the right COM port and boot the board. + +Login with username `petalinux` and set the password to whatever you want, let say `p`. + +For the next steps you should be the superuser: `sudo su` and enter yout password. +Change `root` password: `passwd root`, let's use `r` as the password. + +As you will have to copy back the trace files you must allow connection with `root` through ethernet: `vi /etc/ssh/sshd_config`. Change the option of `PermitRootLogin` into `yes`. + +Now, go to the application directory: `cd /run/media/mmcblk0p1`. + +In order to allow multiple runs with different options you can use the script `newdir` which will copy the necessary files into directory `ptest1`, `ptest2`, and so on. + +in ptest1, check the content of `xrt.ini` and `embedded_exec.sh`. + +Run the application: `./embedded_exec.sh` + +All trace files should be generated in 2s. If you want to perform another test with other parameters, you can run `./newdir` from `/run/media/mmcblk0p1` and change the parameters as you wish in `ptest2/xrt.ini`. Type `reboot` to restart the board and re-run the application. + +Once you have run the application with multiple sets of parameters, you can copy the various `ptest` directories back to your development machine using `scp` (use `ifconfig` to get the board inet address). + +You can copy the whole `ptest*`directories to `ProfileData` on your development machine. The minimum set of files that you have to copy is: `*.csv, *.txt, *.bin, *summary` + +![MissingImage](images/TraceFiles.png) + +Now you can run `vitis_analyzer`on your development machine with the summary file: `vitis_analyzer xrt.run_summary`. to view the System Timeline you have to allow it on the tool: In the top bar menu click on *Vitis -> New Feature Preview*, and check *System Timeline*. + +Click on the analysis tab on the left of Vitis Analyzer, and click on *Timeline Trace*. + +The overall view covers the complete simulation time: + +![Missing image](images/OverallTrace.png) + +At the begining we can see when the processing system is opening the device and starts the PL kernels: + +![Missing images](images/StartPLKernels.png) + +Zooming in where the AI Engine graph starts, we can see the PL Kernels **gen2s** generating the data and the AI Engine kernels consuming these data. These trace are not perfectly aligned but still enough to understand the overall behaviour of the system. + +![Missing image](images/StartGraph.png) + +The polling interval is crucial in event alignment. Reducing the polling interval can help to better align events in the timeline at the expense of some timestamp file size increase. In order to show the effect of different polling intervals, you can modify the `buffer_offload_interval_us` parameter in `xrt.ini` file. The default value is 50µs, In the following example I increased it to 100µs: + +![Missing image](images/StartGraphV2.png) + +As you can see , the PL kernels are out of sync with the AI Engine array iterations. + +### Other tests + +You can play with all parameters: + +- trace_buffer_offload_interval_ms +- tile_based_aie_tile_metrics +- Change or remove AI Engine Profiling metrics +- Change number of iterations in embedded_exec.sh + +## Conclusion + +In this tutorial, we explored how to set up and analyze system-level traces for AI Engine applications using system timeline feature. We covered the necessary configuration changes, the process of running the application on the target hardware, and the steps to collect and analyze the generated trace files. By leveraging the Vitis Analyzer tool, we can gain valuable insights into the performance and behavior of our AI Engine applications, enabling us to optimize and improve their efficiency. + + +## License + +___ + + The MIT License (MIT) + + Copyright (c) 2025 Advanced Micro Devices, Inc. All rights reserved. + SPDX-License-Identifier: MIT + +## Support + +GitHub issues will be used for tracking requests and bugs. For questions, go to [support.xilinx.com](https://support.xilinx.com/). + +
+ +

Copyright © 2021–2025 Advanced Micro Devices, Inc.

+ +

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diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/Utils/CreateData.py b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/Utils/CreateData.py new file mode 100755 index 0000000000..3d13216acd --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/Utils/CreateData.py @@ -0,0 +1,67 @@ +#!/usr/bin/env python3 +# +#Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +#SPDX-License-Identifier: MIT +# + +import os +import sys +import numpy as np + +OK = 1 + +if (len(sys.argv) < 5): + OK = 0 + print("P1", file = sys.stderr) +elif (len(sys.argv) != int(sys.argv[3])+4): + OK = 0 + print("P2", file = sys.stderr) + +if (OK == 0): + print ("Usage: CreateData NbDataPerLine Base Dimensions LengthDim1 [LengthDim2 ...]", file = sys.stderr) + exit(1) + +NDataPerLine = int(sys.argv[1]) +Base = int(sys.argv[2]) +NDims = int(sys.argv[3]) +DimL = np.zeros([NDims],dtype = int) +CumL = np.zeros([NDims],dtype = int) + +print("Numerical Base: ", int(Base), file = sys.stderr) +print("Number of Dimensions: ",int(NDims), file = sys.stderr) +for i in range(int(sys.argv[3])): + DimL[i] = int(sys.argv[i+4]) + print("Length Dimension ", str(i), ": ",str(DimL[i]), file = sys.stderr) + +L = 1; +for i in range(NDims): + CumL[i] = L + L = L*DimL[i] + +print("\nTotal Length: ", str(L), file = sys.stderr) +Data = np.zeros([L], dtype=int) +Mod = np.zeros([NDims],dtype = int) + + +for i in range(L): + x = i + for j in range(NDims-1,-1,-1): + Mod[j] = x/CumL[j] + x = x - CumL[j]*Mod[j] + + + x = 0 + b = 1 + for j in range(NDims): + x = x + b*Mod[j] + b = b*Base + Data[i] = x + + +for i in range(L): + if(i%NDataPerLine != NDataPerLine-1): + print(str(Data[i]),end = "\t") + else: + print(str(Data[i])) + +print("") diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/Utils/CreateLinearData.py b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/Utils/CreateLinearData.py new file mode 100755 index 0000000000..d9a93fbd24 --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/Utils/CreateLinearData.py @@ -0,0 +1,73 @@ +#!/usr/bin/env python3 +# +#Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +#SPDX-License-Identifier: MIT +# + +import os +import sys +import numpy as np + +OK = 1 + +if (len(sys.argv) != 4): + OK = 0 + +if (OK == 0): + print ("Usage: CreateLinearData DataType PLIO_Width Length", file = sys.stderr) + exit(1) + +DataType = sys.argv[1]; +PLIO_Width = int(sys.argv[2]) +Length = int(sys.argv[3]) + +Vmin = 0 +Vmax = 0 +Nbits = 0 + +if ( DataType == 'uint8'): + Vmax = 255 + Nbits = 8 +elif(DataType == 'int8'): + Vmin = -128 + Vmax = 127 + Nbits=8 +elif(DataType == 'uint16'): + Vmax = 65535 + Nbits=16 +elif(DataType == 'int16'): + Vmin = -32768 + Vmax = 32767 + Nbits = 16 +elif(DataType == 'uint32'): + Vmax = 4294967295 + Nbits=32 +elif(DataType == 'int32'): + Vmin = -2147483648 + Vmax = 2147483647 + Nbits = 32 + +print("Data Type: ",DataType, file = sys.stderr) +print(" Min: ",int(Vmin), file = sys.stderr) +print(" Max: ",int(Vmax), file = sys.stderr) +print(" Nbits: ",int(Nbits), file = sys.stderr) + +NDataPerLine = int(PLIO_Width)/int(Nbits) + +print("\nTotal Length: ", str(Length), file = sys.stderr) +print("\nN Data Per Line: ", str(NDataPerLine), file = sys.stderr) + + +V = 0 + +for i in range(Length): + if(i%NDataPerLine != NDataPerLine-1): + print(str(V),end = "\t") + else: + print(str(V)) + + V = V+1 + if(V>Vmax): + V = Vmin + +print("") diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/Utils/DisplayPlot.py b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/Utils/DisplayPlot.py new file mode 100755 index 0000000000..25f4ec771d --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/Utils/DisplayPlot.py @@ -0,0 +1,60 @@ +#!/usr/bin/env python3 +# +#Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +#SPDX-License-Identifier: MIT +# + +import os +import sys +import numpy as np +import csv + + +OK = 1 + + +NArgs = len(sys.argv) + +if (NArgs < 2): + print ("Usage: DisplayPlot.py Filename(s)", file = sys.stderr) + exit(1) + +#loop on the files +for i in range(1, NArgs): + Filename = sys.argv[i] + + if (not os.path.isfile(Filename)): + print("File ", Filename, " does not exist", file = sys.stderr) + OK = 0 + continue + + print("File ", Filename, " exists", file = sys.stderr) + + with open(Filename, 'r') as csvfile: + # creating a csv reader object + csvreader = csv.reader(csvfile) + + # extracting field names through first row + fields = next(csvreader) + + # extracting each data row one by one + rows = [] + for row in csvreader: + rows.append(row) + + # get total number of rows + print("Total no. of rows: %d" % (csvreader.line_num)) + + # printing the field names + print('Field names are:' + ', '.join(field for field in fields)) + + # printing first 5 rows + print('\nFirst 5 rows are:\n') + for row in rows[:5]: + # parsing each column of a row + for col in row: + print("%10s" % col, end=" "), + print('\n') + + print(rows) + diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/BaseSystemCFG.cfg b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/BaseSystemCFG.cfg new file mode 100755 index 0000000000..48b4e7beb7 --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/BaseSystemCFG.cfg @@ -0,0 +1,28 @@ +# +#Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +#SPDX-License-Identifier: MIT +# + + +[connectivity] +# # All inputs are on 8 bits +# nk=mm2s_8_128:4 + +# # 1 output is in 16 bits, the other one in 32 bits +# nk=s2mm_32_128:1 +# nk=s2mm_16_128:1 + +# stream_connect=mm2s_8_128_1.s:ai_engine_0.inputA1 +# stream_connect=mm2s_8_128_2.s:ai_engine_0.inputB1 +# stream_connect=ai_engine_0.outputC1:s2mm_32_128_1.s + +# stream_connect=mm2s_8_128_3.s:ai_engine_0.inputA2 +# stream_connect=mm2s_8_128_4.s:ai_engine_0.inputB2 +# stream_connect=ai_engine_0.outputC2:s2mm_16_128_1.s + + +[advanced] +param=hw_emu.enableProfiling=true +param=compiler.addOutputTypes=hw_export +[clock] +defaultFreqHz=325000000 diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/Makefile new file mode 100755 index 0000000000..587f532604 --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/Makefile @@ -0,0 +1,40 @@ +# +#Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +#SPDX-License-Identifier: MIT +# + +include ../common.mk + +.PHONY: clean + +ConfigName := system_$(NAntenna).cfg + +$(info "-------------------------------------------------------------------------") +$(info "Hw Configuration File Build: $(ConfigName)") +$(info "-------------------------------------------------------------------------") +$(info "Number of Antenna : $(NAntenna)") +$(info "Width of PLIO I/F : $(PLIOW)") +$(info "Data Width (Nb Bits): $(DATAW)") +$(info "-------------------------------------------------------------------------") + + + + +all: SystemFileCreation + + +SystemFileCreation: + head --lines=7 BaseSystemCFG.cfg > $(ConfigName) + echo "nk=gen2s_$(DATAW)_$(PLIOW):$(NAntenna)" >> $(ConfigName) + echo "nk=s2mm_$(DATAW)_$(PLIOW):$(NAntenna)" >> $(ConfigName) + number=1 ; id0=0 ; while [[ $$number -le $(NAntenna) ]] ; do \ + echo "stream_connect=gen2s_$(DATAW)_$(PLIOW)_$$number.s:ai_engine_0.Input_$$id0" >> $(ConfigName) ; \ + echo "stream_connect=ai_engine_0.Output_$$id0:s2mm_$(DATAW)_$(PLIOW)_$$number.s" >> $(ConfigName) ; \ + echo " " >> $(ConfigName) ; \ + ((number = number + 1)) ; \ + ((id0 = id0 + 1)) ; \ + done + tail --line=6 BaseSystemCFG.cfg >> $(ConfigName) + +clean: + rm -rf system*.cfg diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/aiesim_options.txt b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/aiesim_options.txt new file mode 100755 index 0000000000..60c944e739 --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/aiesim_options.txt @@ -0,0 +1,8 @@ +# +#Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +#SPDX-License-Identifier: MIT +# + + +AIE_PKG_DIR=/home/oliviert/xirguup/NewVersions/SourceCode/AIEML/SparseMatrixMultiply/aie/Work +AIE_DUMP_VCD=foo diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/embedded_exec.sh b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/embedded_exec.sh new file mode 100755 index 0000000000..baa9943af7 --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/embedded_exec.sh @@ -0,0 +1,12 @@ +#!/bin/bash +# +#Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +#SPDX-License-Identifier: MIT +# + + +export XILINX_XRT=/usr + +./host.exe a.xclbin 100 &> out.txt + + diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/newdir b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/newdir new file mode 100755 index 0000000000..c1bdf59a34 --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/newdir @@ -0,0 +1,20 @@ +#!/bin/bash +# +# Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# + +num=1 +while [ -d ptest$num ]; do +num=$(($num+1)) +done + +echo "Creating ptest$num..." +mkdir ptest$num + +cd ptest$num +cp -r ../data . +cp ../a.xclbin . +cp ../host.exe . +cp ../xrt.ini . +cp ../embedded_exec.sh . diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/newdir_api b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/newdir_api new file mode 100755 index 0000000000..340e927dda --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/newdir_api @@ -0,0 +1,16 @@ +#!/bin/bash +# +# Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# + + + +echo "Creating ptest_api..." +mkdir ptest_api + +cd ptest_api +cp -r ../data . +cp ../a.xclbin . +cp ../host_api.exe host.exe +cp ../embedded_exec.sh . diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/system_4.cfg b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/system_4.cfg new file mode 100755 index 0000000000..c88025fb41 --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/system_4.cfg @@ -0,0 +1,27 @@ +# +#Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +#SPDX-License-Identifier: MIT +# + + +[connectivity] +nk=gen2s_16_128:4 +nk=s2mm_16_128:4 +stream_connect=gen2s_16_128_1.s:ai_engine_0.Input_0 +stream_connect=ai_engine_0.Output_0:s2mm_16_128_1.s + +stream_connect=gen2s_16_128_2.s:ai_engine_0.Input_1 +stream_connect=ai_engine_0.Output_1:s2mm_16_128_2.s + +stream_connect=gen2s_16_128_3.s:ai_engine_0.Input_2 +stream_connect=ai_engine_0.Output_2:s2mm_16_128_3.s + +stream_connect=gen2s_16_128_4.s:ai_engine_0.Input_3 +stream_connect=ai_engine_0.Output_3:s2mm_16_128_4.s + + +[advanced] +param=hw_emu.enableProfiling=true +param=compiler.addOutputTypes=hw_export +[clock] +defaultFreqHz=325000000 diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/xrt.ini b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/xrt.ini new file mode 100755 index 0000000000..606f800b24 --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/addon_files/xrt.ini @@ -0,0 +1,41 @@ +# +# Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# UG1393 for details + +# Debug group for the aie +[Debug] +aie_profile = true +aie_trace = true +device_trace=fine +continuous_trace = true +host_trace=true + +trace_buffer_size = 32M +trace_buffer_offload_interval_ms = 5 + +# Subsection for AIE profile settings only if aie_profile is set to true +[AIE_profile_settings] +# Interval in between reading counters (in us) +interval_us = 1000 + +tile_based_aie_metrics = all:heat_map +tile_based_aie_memory_metrics = all:conflicts +tile_based_interface_tile_metrics = all:output_throughputs + + +# Subsection for AIE Trace only if aie_trace is set to true +[AIE_trace_settings] +# PLIO +reuse_buffer = true +periodic_offload = true +buffer_offload_interval_us = 50 +buffer_size = 100M + +tile_based_aie_tile_metrics = all:functions +enable_system_timeline = true + +[Runtime] +verbosity = 10 + diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/Makefile new file mode 100755 index 0000000000..de27301842 --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/Makefile @@ -0,0 +1,124 @@ +# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT + + +include ../common.mk + +$(info "-------------------------------------------------------------------------") +$(info "AI Engine Build") +$(info "-------------------------------------------------------------------------") +$(info "Number of Antenna : $(NAntenna)") +$(info "Multirate Enabled : $(MULTIRATE)") +$(info "Number of Iterations : $(NIterations)") +$(info "Width of PLIO I/F : $(PLIOW)") +$(info "Data Width (Nb Bits) : $(DATAW)") +$(info "Data Frame Length : $(FRAME_LENGTH)") +$(info "Filter Margin Length : $(MARGIN_LENGTH)") +$(info "PL Kernel Frequency : $(FREQ_HZ)") +$(info "Ready for Hw/Sw Tracing: $(ENABLE_TRACE)") +$(info "Ready for Sim Profiling: $(ENABLE_PROFILE)") +$(info "-------------------------------------------------------------------------") + +# Event trace: Simulation and Hardware +ifeq ($(strip $(ARCH)),aie) + ARCH_AIECMP := 10 +else ifeq ($(strip $(ARCH)),aie-ml) + ARCH_AIECMP := 20 +else + $(error "ARCH should be either aie for AI Engine or aie-ml for AI Engine ML (ARCH = $(ARCH))") +endif + + + +SYSTEM_VAR := NAntenna=$(NAntenna) MULTIRATE=$(MULTIRATE) NIterations=$(NIterations) PLIOW=$(PLIOW) DATAW=$(DATAW) FREQ_HZ=$(FREQ_HZ) FRAME_LENGTH=$(FRAME_LENGTH) MARGIN_LENGTH=$(MARGIN_LENGTH) + +SYSTEM_VAR_D := -DNAntenna=$(NAntenna) -DMULTIRATE=$(MULTIRATE) -DNIterations=$(NIterations) -DPLIOW=$(PLIOW) -DFREQ_HZ=$(FREQ_HZ) -DFRAME_LENGTH=$(FRAME_LENGTH) -DMARGIN_LENGTH=$(MARGIN_LENGTH) -DARCH_AIECMP=$(ARCH_AIECMP) + +ifeq ($(TOOLV),2024.2) + PreProc := --aie.Xpreproc "\"$(SYSTEM_VAR_D)\"" +else + PreProc := --aie.Xpreproc "$(SYSTEM_VAR_D)" +endif + +GRAPH = src/graph.cpp +LIBADF = libadf.a +AIE_CMPL_CMD := v++ --compile --mode aie --include "./src" --include "./src/kernels" --aie.workdir ./Work ${GRAPH} --platform $(PLATFORM) +AIE_FLAGS := --aie.log-level 5 +AIE_FLAGS += $(PreProc) +AIE_FLAGS += --aie.output-archive $(LIBADF) +# AIE_FLAGS += --aie.Xchess=main:darts.xargs=-nb + +AIE_SIM_CMD := aiesimulator --pkg-dir=./Work + +# Event trace: Simulation and Hardware +ifeq ($(strip $(ENABLE_TRACE)),true) + AIE_FLAGS += --config aiecompiler_trace_$(TRACE_CHANNEL)_options.cfg + AIE_SIM_CMD += --dump-vcd foo + AIE_SIM_CMD += --options-file=aiesim-options.txt +endif + +# Profiling +ifeq ($(strip $(ENABLE_PROFILE)),true) + AIE_SIM_CMD += --profile --display-gmio-throughput +endif + + +all: clean data aie aiesim simviz + +run: clean data aie aiesim + + +.PHONY: data help _help + +NSamples := $(shell echo " 2 * 256 * $(NIterations)" | bc) +disp: + @echo $(NSamples) + +data: + mkdir -p data + echo $(PWD) + echo $(ROOTDIR) + $(UTILS_DIR)/CreateLinearData.py int16 $(PLIOW) $(NSamples) > data/input.txt + cp -rf data $(ROOTDIR) + +aie: ${LIBADF} +${LIBADF}: src/* + $(AIE_CMPL_CMD) $(AIE_FLAGS) + +aiesim: ${LIBADF} + ${AIE_SIM_CMD} + +events: + vcdanalyze -v --pkg-dir ./Work --vcd foo.vcd + +extract: + grep Events < trdata.aiesim/events.txt + + +aieviz: $(LIBADF) + vitis_analyzer ./Work/graph.aiecompile_summary + +simviz: $(LIBADF) + vitis_analyzer aiesimulator_output/default.aierun_summary + +help: + make -s _help + +_help: + echo -e "\n\n===========================================\n" + echo "Targeted Architectures (Can be modified in common.mk):" + echo "ARCH=aie: AI Engine (default)" + echo "ARCH=aie-ml: AI Engine ML" + echo " " + echo -e "\n===========================================\n" + + +clean: + rm -rf _x libadf.a Work .Xil vitis_analyzer* foo.vcd *.log pl_sample* aiesimulator_output + rm -rf .AIE_SIM_CMD_LINE_OPTIONS *.csv *.db temp + rm -rf logs trdata.aiesim ISS_RPC_SERVER_PORT .wsdata plio_throughput_info.json + rm -rf + +clean-all: + make clean + rm -rf data diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/aiecompiler_trace_gmio_options.cfg b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/aiecompiler_trace_gmio_options.cfg new file mode 100755 index 0000000000..43b99fbf82 --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/aiecompiler_trace_gmio_options.cfg @@ -0,0 +1,12 @@ +# +#Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +#SPDX-License-Identifier: MIT +# + +[aie] +event-trace=runtime +broadcast-enable-core=true + +event-trace-port=gmio + +xlopt=0 diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/aiecompiler_trace_plio_options.cfg b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/aiecompiler_trace_plio_options.cfg new file mode 100755 index 0000000000..edf4f5e85f --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/aiecompiler_trace_plio_options.cfg @@ -0,0 +1,14 @@ +# +#Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +#SPDX-License-Identifier: MIT +# + +[aie] +event-trace=runtime +broadcast-enable-core=true + +num-trace-streams=16 +event-trace-port=plio +trace-plio-width=128 + +xlopt=0 diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/aiesim-options.txt b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/aiesim-options.txt new file mode 100755 index 0000000000..0faad12155 --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/aiesim-options.txt @@ -0,0 +1,19 @@ +# +#Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +#SPDX-License-Identifier: MIT +# + +AIE_DUMP_VCD_IO=true +AIE_DUMP_VCD_CORE=true +AIE_DUMP_VCD_SHIM=true +AIE_DUMP_VCD_MEM=true +AIE_DUMP_VCD_STREAM_SWITCH=true +AIE_DUMP_VCD_CLK=true + + +#AIE_DUMP_VCD_IO=true +#AIE_DUMP_VCD_CORE=false +#AIE_DUMP_VCD_SHIM=true +#AIE_DUMP_VCD_MEM=false +#AIE_DUMP_VCD_STREAM_SWITCH=false +#AIE_DUMP_VCD_CLK=false diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/src/graph.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/src/graph.cpp new file mode 100755 index 0000000000..fedd900fae --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/src/graph.cpp @@ -0,0 +1,92 @@ +// Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT + +#include + +#include "graph.h" + +#if MULTIRATE == false +MyGraph G(""); +#else +MyGraphUp G(""); +#endif + +#if defined(__AIESIM__) || defined(__X86SIM__) + +template +void UpdateParam(MyGraph &G, cint16 Gain, int32 FilterSel) +{ + for(int i=0;i +void UpdateParam(MyGraphUp &G, cint16 Gain, int32 FilterSel) +{ + for(int i=0;i +class GraphWithRTP : public graph { + +public: + kernel ptin,filt,gaink,ptout; + + port in; + port out; + port Gval,Fsel; + + GraphWithRTP() { + ptin = kernel::create(passthrough_strbuf); + source(ptin) = "kernels/Passthrough.cpp"; + runtime(ptin) = (double)RATIO_PT/100.0; + + filt = kernel::create(filter_buf); + source(filt) = "kernels/Filter.cpp"; + runtime(filt) = (double)RATIO/100.0; + + gaink = kernel::create(gain); + source(gaink) = "kernels/Gain.cpp"; + runtime(gaink) = (double)RATIO/100.0; + + ptout = kernel::create(passthrough_bufstr); + source(ptout) = "kernels/Passthrough.cpp"; + runtime(ptout) = (double)RATIO_PT/100.0; + + connect(in, ptin.in[0]); + connect(ptin.out[0],filt.in[0]); + connect(filt.out[0],gaink.in[0]); + connect(gaink.out[0],ptout.in[0]); + connect(ptout.out[0],out); + + connect(Gval,async(gaink.in[1])); + connect(Fsel,async(filt.in[1])); + }; +}; + +template +class GraphUpsampleWithRTP : public graph { + +public: + kernel ptin,filt,gaink,ptout; + + port in; + port out; + port Gval,Fsel; + + GraphUpsampleWithRTP() { + ptin = kernel::create(passthrough_strbuf); + source(ptin) = "kernels/Passthrough.cpp"; + runtime(ptin) = (double)RATIO_PT/100.0; + + filt = kernel::create(filter_buf); + source(filt) = "kernels/Filter.cpp"; + runtime(filt) = (double)RATIO/100.0; + + gaink = kernel::create(gain); + source(gaink) = "kernels/Gain.cpp"; + runtime(gaink) = (double)RATIO/100.0; + + ptout = kernel::create(upsample_buffer); + source(ptout) = "kernels/Upsample.cpp"; + runtime(ptout) = (double)RATIO_PT/100.0; + + connect(in, ptin.in[0]); + connect(ptin.out[0],filt.in[0]); + connect(filt.out[0],gaink.in[0]); + connect(gaink.out[0],ptout.in[0]); + connect(ptout.out[0],out); + + connect(Gval,async(gaink.in[1])); + connect(Fsel,async(filt.in[1])); + }; +}; + + +template +class AllGraphs : public graph { +public: + GraphWithRTP<80,RATIO_FILTER_GAIN> G; + AllGraphs RG; + + port in[N]; + port out[N]; + port gin[N],fin[N]; + + + AllGraphs() + { + connect<> (in[N-1],G.in); + connect<> (G.out,out[N-1]); + connect<> (gin[N-1],G.Gval); + connect<> (fin[N-1],G.Fsel); + + for(int i=0;i (in[i],RG.in[i]); + connect<> (RG.out[i],out[i]); + connect<> (gin[i],RG.gin[i]); + connect<> (fin[i],RG.fin[i]); + } + + }; +}; + +template +class AllGraphs<1,RATIO_FILTER_GAIN> : public graph +{ +public: + GraphWithRTP<80, RATIO_FILTER_GAIN> G; + + port in[1]; + port out[1]; + port gin[1],fin[1]; + + + AllGraphs() + { + connect<> (in[0],G.in); + connect<> (G.out,out[0]); + connect<> (gin[0],G.Gval); + connect<> (fin[0],G.Fsel); + }; +}; + +template +class AllGraphsUp : public graph { +public: + GraphUpsampleWithRTP<80,RATIO_FILTER_GAIN,UPRATIO> G; + AllGraphsUp RG; + + port in[N]; + port out[N]; + port gin[N],fin[N]; + + + AllGraphsUp() + { + connect<> (in[N-1],G.in); + connect<> (G.out,out[N-1]); + connect<> (gin[N-1],G.Gval); + connect<> (fin[N-1],G.Fsel); + + for(int i=0;i (in[i],RG.in[i]); + connect<> (RG.out[i],out[i]); + connect<> (gin[i],RG.gin[i]); + connect<> (fin[i],RG.fin[i]); + } + + }; +}; + +template +class AllGraphsUp<1,RATIO_FILTER_GAIN,UPRATIO> : public graph +{ +public: + GraphUpsampleWithRTP<80, RATIO_FILTER_GAIN,UPRATIO> G; + + port in[1]; + port out[1]; + port gin[1],fin[1]; + + + AllGraphsUp() + { + connect<> (in[0],G.in); + connect<> (G.out,out[0]); + connect<> (gin[0],G.Gval); + connect<> (fin[0],G.Fsel); + }; +}; + +template +class MyGraph : public graph +{ +public: + AllGraphs G; + input_plio in[N]; + output_plio out[N]; + input_port gin[N],fin[N]; + + MyGraph(std::string Prefix) + { +#if PLIOW == 32 +#define PLIO_IF plio_32_bits +#elif PLIOW == 64 +#define PLIO_IF plio_64_bits +#elif PLIOW == 128 +#define PLIO_IF plio_128_bits +#endif + +#define FREQ_MHZ ((double)FREQ_HZ/1000000.0) + + for(int idx=0;idx (in[idx].out[0],G.in[idx]); + connect<> (G.out[idx],out[idx].in[0]); + connect<> (gin[idx],G.gin[idx]); + connect<> (fin[idx],G.fin[idx]); + } +#undef PLIO_IF + }; +}; + + +template +class MyGraphUp : public graph +{ +public: + AllGraphsUp G; + input_plio in[N]; + output_plio out[N]; + input_port gin[N],fin[N]; + + MyGraphUp(std::string Prefix) + { +#if PLIOW == 32 +#define PLIO_IF plio_32_bits +#elif PLIOW == 64 +#define PLIO_IF plio_64_bits +#elif PLIOW == 128 +#define PLIO_IF plio_128_bits +#endif + +#define FREQ_MHZ ((double)FREQ_HZ/1000000.0) + + for(int idx=0;idx (in[idx].out[0],G.in[idx]); + connect<> (G.out[idx],out[idx].in[0]); + connect<> (gin[idx],G.gin[idx]); + connect<> (fin[idx],G.fin[idx]); + } +#undef PLIO_IF + }; +}; diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/src/kernels.h b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/src/kernels.h new file mode 100755 index 0000000000..1cd753f2a8 --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/src/kernels.h @@ -0,0 +1,32 @@ +// Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT + +#pragma once + +#include +#include + +#include "system_settings.h" + +void gain(adf::input_buffer> &__restrict in, + adf::output_buffer> &__restrict out,cint16 Gain); + +void passthrough_buffer(adf::input_buffer> &__restrict in, + adf::output_buffer> &__restrict out); + + +void passthrough_stream(input_stream *__restrict in, output_stream *__restrict out); + +void passthrough_bufstr(adf::input_buffer> &__restrict in, + output_stream *__restrict out); + +void passthrough_strbuf(input_stream *__restrict in, + adf::output_buffer> &__restrict out); + +void filter_str(input_stream *__restrict in, output_stream *__restrict out,int32 FiltSel); + +void filter_buf(adf::input_buffer,adf::margin> &__restrict in, + adf::output_buffer> &__restrict out,int32 FiltSel); + +template +void upsample_buffer(adf::input_buffer> &__restrict in, adf::output_buffer> &__restrict out); diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/src/kernels/Filter.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/src/kernels/Filter.cpp new file mode 100755 index 0000000000..cd534433fc --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/src/kernels/Filter.cpp @@ -0,0 +1,196 @@ +// Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT + +#include "kernels.h" + + +alignas(32) int16_t weights[2][16] = + {{ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16}, + { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1}}; +const int ShiftVal[2] = {7,4}; + + +#if ARCH_AIECMP == 10 +void filter_buf(adf::input_buffer, adf::margin> &__restrict in, + adf::output_buffer> &__restrict out, + int32 FiltSel) +{ + aie::vector data; // 1024 bits + aie::accum acc; // 384 bits; + auto pi1 = aie::begin_vector<8>(in); + auto po1 = aie::begin_vector<4>(out); + + // Load the coeffs vector with weights + aie::vector coeffs = aie::load_v<16>(weights[FiltSel]); + const int SHIFT_VAL = ShiftVal[FiltSel]; + + // Define the operator + constexpr unsigned Lanes = 4, Points = 16, CoeffStep = 1, DataStepX = 1, DataStepY = 1; + + using mul_ops = aie::sliding_mul_ops; + + // Reading 256 bits - 0 + data.insert(0, *pi1++); + // Reading 256 bits - 1 + data.insert(1, *pi1++); + + for (unsigned i = 0; i < BUFFER_SIZE / 32; i++) + chess_prepare_for_pipelining + chess_loop_range(4, 32) + { + // Reading 256 bits - 2 --> 8 samples + data.insert(2, *pi1++); + + // mul performs multiplication accumulations with no initial value for the accumulator + acc = mul_ops::mul(coeffs, 0, data, 1); + *po1++ = acc.to_vector(SHIFT_VAL); + + acc = mul_ops::mul(coeffs, 0, data, 5); + *po1++ = acc.to_vector(SHIFT_VAL); + + // Reading 256 bits - 3 --> 8 samples + data.insert(3, *pi1++); + + // mul performs multiplication accumulations with no initial value for the accumulator + acc = mul_ops::mul(coeffs, 0, data, 9); + *po1++ = acc.to_vector(SHIFT_VAL); + + acc = mul_ops::mul(coeffs, 0, data, 13); + *po1++ = acc.to_vector(SHIFT_VAL); + + // Reading 256 bits - 0 --> 8 samples + data.insert(0, *pi1++); + + // mul performs multiplication accumulations with no initial value for the accumulator + acc = mul_ops::mul(coeffs, 0, data, 17); + *po1++ = acc.to_vector(SHIFT_VAL); + + acc = mul_ops::mul(coeffs, 0, data, 21); + *po1++ = acc.to_vector(SHIFT_VAL); + + // Reading 256 bits - 1 --> 8 samples + data.insert(1, *pi1++); + + // mul performs multiplication accumulations with no initial value for the accumulator + acc = mul_ops::mul(coeffs, 0, data, 25); + *po1++ = acc.to_vector(SHIFT_VAL); + + acc = mul_ops::mul(coeffs, 0, data, 29); + *po1++ = acc.to_vector(SHIFT_VAL); + } +} + +void filter_str(input_stream *__restrict in, output_stream *__restrict out, + int32 FiltSel) + +{ + static cint16 Memory[32]; + + aie::accum acc; // 384 bits; + + // Load the coeffs vector with weights + aie::vector coeffs = aie::load_v<16>(weights[FiltSel]); + const int SHIFT_VAL = ShiftVal[FiltSel]; + + // Load the data vector with memory + aie::vector data = aie::load_v<32>(Memory); + + // Define the operator + constexpr unsigned Lanes=4, Points=16, CoeffStep=1, DataStepX=1, DataStepY=1; + + using mul_ops = aie::sliding_mul_ops; + + for(unsigned i=0; i(in)); + acc = mul_ops::mul(coeffs, 0, data, 1); + writeincr(out,acc.to_vector(SHIFT_VAL)); + + data.insert(5, readincr_v<4>(in)); + acc = mul_ops::mul(coeffs, 0, data, 5); + writeincr(out,acc.to_vector(SHIFT_VAL)); + + + // mul performs multiplication accumulations with no initial value for the accumulator + data.insert(6, readincr_v<4>(in)); + acc = mul_ops::mul(coeffs, 0, data, 9); + writeincr(out,acc.to_vector(SHIFT_VAL)); + + data.insert(7, readincr_v<4>(in)); + acc = mul_ops::mul(coeffs, 0, data, 13); + writeincr(out,acc.to_vector(SHIFT_VAL)); + + + // mul performs multiplication accumulations with no initial value for the accumulator + data.insert(0, readincr_v<4>(in)); + acc = mul_ops::mul(coeffs, 0, data, 17); + writeincr(out,acc.to_vector(SHIFT_VAL)); + + data.insert(1, readincr_v<4>(in)); + acc = mul_ops::mul(coeffs, 0, data, 21); + writeincr(out,acc.to_vector(SHIFT_VAL)); + + + // mul performs multiplication accumulations with no initial value for the accumulator + data.insert(2, readincr_v<4>(in)); + acc = mul_ops::mul(coeffs, 0, data, 25); + writeincr(out,acc.to_vector(SHIFT_VAL)); + + data.insert(3, readincr_v<4>(in)); + acc = mul_ops::mul(coeffs, 0, data, 29); + writeincr(out,acc.to_vector(SHIFT_VAL)); + } + + // Save filter memory + data.store(Memory); + +} +#elif ARCH_AIECMP == 20 +void filter_buf(adf::input_buffer, adf::margin> &__restrict in, + adf::output_buffer> &__restrict out, + int32 FiltSel) +{ + aie::vector data; // 1024 bits + aie::accum acc; // 512 bits; + auto pi1 = aie::begin_vector<16>(in); + auto po1 = aie::begin_vector<16>(out); + + // Load the coeffs vector with weights + aie::vector coeffs = aie::load_v<16>(weights[FiltSel]); + const int SHIFT_VAL = ShiftVal[FiltSel]; + + // Define the operator + constexpr unsigned Lanes = 16, Points = 16, CoeffStep = 1, DataStepX = 1, DataStepY = 1; + + using mul_ops = aie::sliding_mul_ops; + + // Reading 512 bits - 16 samples + data.insert(0, *pi1++); + + for (unsigned i = 0; i < BUFFER_SIZE / 32; i++) + chess_prepare_for_pipelining + chess_loop_range(4, 32) + { + // Reading 512 bits - 1 --> 16 samples + data.insert(1, *pi1++); + + // mul performs multiplication accumulations with no initial value for the accumulator + acc = mul_ops::mul(coeffs, 0, data, 1); + *po1++ = acc.to_vector(SHIFT_VAL); + + // Reading 256 bits - 0 --> 16 samples + data.insert(0, *pi1++); + + // mul performs multiplication accumulations with no initial value for the accumulator + acc = mul_ops::mul(coeffs, 0, data, 17); + *po1++ = acc.to_vector(SHIFT_VAL); + } +} +#endif + + + diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/src/kernels/Gain.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/src/kernels/Gain.cpp new file mode 100755 index 0000000000..a767a2eca7 --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/src/kernels/Gain.cpp @@ -0,0 +1,17 @@ +// Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT +#include "../kernels.h" + +void gain(adf::input_buffer> & in, +adf::output_buffer> & out, +cint16 Gain) +{ + auto pin = aie::begin_vector<8>(in); + auto pout = aie::begin_vector<8>(out); + + for(int i=0;i(0); + } +} \ No newline at end of file diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/src/kernels/Passthrough.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/src/kernels/Passthrough.cpp new file mode 100755 index 0000000000..dd3aa6c9e7 --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/src/kernels/Passthrough.cpp @@ -0,0 +1,98 @@ +// Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT + +#include "kernels.h" + + +void passthrough_buffer(adf::input_buffer> &__restrict in, adf::output_buffer> &__restrict out) +{ + auto pi1 = aie::begin_vector<8>(in); + auto po1 = aie::begin_vector<8>(out); + + // Copy input to output + for (int i = 0; i < BUFFER_SIZE/8 ; i++) + chess_prepare_for_pipelining + { + *po1++ = *pi1++; + } + +} + +#if ARCH_AIECMP == 10 + +void passthrough_stream(input_stream *__restrict in, output_stream *__restrict out) +{ + for (int i = 0; i < BUFFER_SIZE/4 ; i++) + chess_prepare_for_pipelining + { + writeincr(out,readincr_v<4>(in)); + } +} + +void passthrough_bufstr(adf::input_buffer> &__restrict in, output_stream *__restrict out) +{ + auto pi1 = aie::begin_vector<4>(in); + + // Copy input to output + for (int i = 0; i < BUFFER_SIZE/4 ; i++) + chess_prepare_for_pipelining + { + auto inval = *pi1++; + writeincr(out,inval); + } + +} + +void passthrough_strbuf(input_stream *__restrict in, adf::output_buffer> &__restrict out) +{ + auto po1 = aie::begin_vector<4>(out); + + // Copy input to output + for (int i = 0; i < BUFFER_SIZE/4 ; i++) + chess_prepare_for_pipelining + { + auto inval = readincr_v<4>(in); + *po1++ = inval; + } + +} + +#elif ARCH_AIECMP == 20 + +void passthrough_stream(input_stream *__restrict in, output_stream *__restrict out) +{ + for (int i = 0; i < BUFFER_SIZE ; i++) + chess_prepare_for_pipelining + { + writeincr(out,readincr(in)); + } +} + +void passthrough_bufstr(adf::input_buffer> &__restrict in, output_stream *__restrict out) +{ + auto pi1 = aie::begin(in); + + // Copy input to output + for (int i = 0; i < BUFFER_SIZE ; i++) + chess_prepare_for_pipelining + { + auto inval = *pi1++; + writeincr(out,inval); + } + +} + +void passthrough_strbuf(input_stream *__restrict in, adf::output_buffer> &__restrict out) +{ + auto po1 = aie::begin(out); + + // Copy input to output + for (int i = 0; i < BUFFER_SIZE ; i++) + chess_prepare_for_pipelining + { + auto inval = readincr(in); + *po1++ = inval; + } + +} +#endif diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/src/kernels/Upsample.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/src/kernels/Upsample.cpp new file mode 100755 index 0000000000..73a0e20252 --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/aie/src/kernels/Upsample.cpp @@ -0,0 +1,25 @@ +// Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: MIT + +#include "kernels.h" + + +template +void upsample_buffer(adf::input_buffer> &__restrict in, adf::output_buffer> &__restrict out) +{ + auto pi1 = aie::begin_vector<8>(in); + auto po1 = aie::begin_vector<8>(out); + + // Copy input to output + for (int i = 0; i < BUFFER_SIZE/8 ; i++) + chess_prepare_for_pipelining + { + auto reg = *pi1++; + for(int j=0;j plkernels/HLSConfig_$(basename $@).cfg + sed -i "s/syn.file=/syn.file=..\/$(basename $@).cpp/g" plkernels/HLSConfig_$(basename $@).cfg + v++ --compile --mode hls --platform $(PLATFORM) --config plkernels/HLSConfig_$(basename $@).cfg --work_dir plkernels/$(basename $@) + cp plkernels/$(basename $@)/$(basename $@).xo . + +clean: + rm -rf _x *.xo* *.log .Xil .crashReporter plkernels gen2s_* s2mm_* mm2s_* diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/pl_kernels/gen2sCPP.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/pl_kernels/gen2sCPP.cpp new file mode 100755 index 0000000000..2a3f703de3 --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/pl_kernels/gen2sCPP.cpp @@ -0,0 +1,60 @@ +/* +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +SPDX-License-Identifier: MIT +*/ + + + +#include +#include +#include + + +extern "C" { + #define BUS_SIZE + #define DATA_SIZE + #define ARRAY_SIZE + + #define RATIO (BUS_SIZE/DATA_SIZE) + + +void FUNCTION_NAME (hls::stream >& s, int size) { + + #pragma HLS interface axis port=s + + #pragma HLS INTERFACE s_axilite port=size bundle=control + #pragma HLS interface s_axilite port=return bundle=control + ap_int d[RATIO]; + #pragma HLS ARRAY_RESHAPE variable=d type=complete dim=1 + ap_int v[ARRAY_SIZE]; + + // Generator Table initialization + INIT_D:for(int i=0; i D + if constexpr (RATIO==1) + v[i] = d[0]; + else if constexpr (RATIO==2) + v[i] = (d[0],d[1]); + else if constexpr (RATIO==4) + v[i] = (d[0],d[1],d[2],d[3]); + else if constexpr (RATIO==8) + v[i] = (d[0],d[1],d[2],d[3],d[4],d[5],d[6],d[7]); + + for(int j=0;j x; + x.data = v[i%ARRAY_SIZE]; + s.write(x); + } + } +} diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/pl_kernels/mm2sCPP.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/pl_kernels/mm2sCPP.cpp new file mode 100755 index 0000000000..f241a949e9 --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/pl_kernels/mm2sCPP.cpp @@ -0,0 +1,44 @@ +/* +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +SPDX-License-Identifier: MIT +*/ +#include +#include +#include + + +extern "C" { + + #define BUS_SIZE + #define DATA_SIZE + #define ARRAY_SIZE + #define FRAME_SIZE + + void FUNCTION_NAME (ap_int* mem, hls::stream >& s, int size) { + #pragma HLS INTERFACE m_axi port=mem offset=slave bundle=gmem + + #pragma HLS interface axis port=s + + #pragma HLS INTERFACE s_axilite port=mem bundle=control + #pragma HLS INTERFACE s_axilite port=size bundle=control + #pragma HLS interface s_axilite port=return bundle=control + ap_int v[ARRAY_SIZE]; + + for(int i=0;i x; + x.data = v[i%ARRAY_SIZE]; + x.last = ((i%FRAME_SIZE)==127); + x.keep_all(); + s.write(x); + } + + } + +} diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/pl_kernels/s2mmCPP.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/pl_kernels/s2mmCPP.cpp new file mode 100755 index 0000000000..e74b8b476d --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/pl_kernels/s2mmCPP.cpp @@ -0,0 +1,39 @@ +/* +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +SPDX-License-Identifier: MIT +*/ +#include +#include +#include + +extern "C" { + + #define BUS_SIZE + #define DATA_SIZE + #define ARRAY_SIZE + + void FUNCTION_NAME (ap_int* mem, hls::stream >& s, int size) + { + + static ap_int v[ARRAY_SIZE]; + + #pragma HLS INTERFACE m_axi port=mem offset=slave bundle=gmem + + #pragma HLS interface axis port=s + + #pragma HLS INTERFACE s_axilite port=mem bundle=control + #pragma HLS INTERFACE s_axilite port=size bundle=control + #pragma HLS interface s_axilite port=return bundle=control + + for(int i = 0; i < size; i++) { + #pragma HLS PIPELINE II=1 + ap_axis x = s.read(); + v[i%ARRAY_SIZE]=x.data; + } + + for(int i = 0; i < ARRAY_SIZE; i++) { + #pragma HLS PIPELINE II=1 + mem[i] = v[i]; + } + } +} diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/sw/Makefile b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/sw/Makefile new file mode 100755 index 0000000000..e862935c6f --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/sw/Makefile @@ -0,0 +1,49 @@ +# +# Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# + +include ../common.mk + +$(info "-------------------------------------------------------------------------") +$(info "Host Software Build") +$(info "-------------------------------------------------------------------------") +$(info "Number of Antenna : $(NAntenna)") +$(info "-------------------------------------------------------------------------") + + +HOST_EXE = ../host.exe +HOST_API_EXE = ../host_api.exe +HOST_INC = -I../ -I$(AIE_DIR)/src +HOST_OBJ = host.o +HOST_API_OBJ = host_api.o +HOST_SRC = host.cpp +# HOST_OPT := -print-search-dirs + + +CXXFLAGS += -std=c++17 -pipe -g -feliminate-unused-debug-types $(HOST_OPT) -I$(XILINX_HLS)/include/ -I${SDKTARGETSYSROOT}/usr/include/xrt/ -I${SDKTARGETSYSROOT}/usr/include -g -Wall -c -fmessage-length=0 --sysroot=${SDKTARGETSYSROOT} ${HOST_INC} -I${AIE_DIR} -DFRAME_SIZE=$(FRAME_SIZE) + +LDFLAGS += -lgcc -lc -lxilinxopencl -lxrt_coreutil -lpthread -lrt -ldl -lcrypt -lstdc++ +LDFLAGS += -L${SDKTARGETSYSROOT}/usr/lib/ --sysroot=${SDKTARGETSYSROOT} -L$(XILINX_VITIS)/aietools/lib/aarch64.o + + +SYSTEM_DEF := -DNAntenna=$(NAntenna) -DPLIOW=$(PLIOW) -DDATAW=$(DATAW) -DFRAME_LENGTH=$(FRAME_LENGTH) + +.PHONY: clean all + +all: $(HOST_EXE) $(HOST_API_EXE) + +${HOST_EXE}: ${HOST_OBJ} + ${CXX} -o $@ $^ ${LDFLAGS} + +${HOST_API_EXE}: ${HOST_API_OBJ} + ${CXX} -o $@ $^ ${LDFLAGS} + +${HOST_OBJ}: ${HOST_SRC} + ${CXX} ${CXXFLAGS} $(SYSTEM_DEF) -DUSE_XRT_EVENT_API=false -o $@ $< + +${HOST_API_OBJ}: ${HOST_SRC} + ${CXX} ${CXXFLAGS} $(SYSTEM_DEF) -DUSE_XRT_EVENT_API=true -o $@ $< + +clean: + rm -rf ${HOST_OBJ} ${HOST_API_OBJ} .Xil ${HOST_EXE} ${HOST_API_EXE} diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/sw/host.cpp b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/sw/host.cpp new file mode 100755 index 0000000000..4a95dcd971 --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/sw/host.cpp @@ -0,0 +1,231 @@ +/* +Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +SPDX-License-Identifier: MIT +*/ +#include +#include +#include +#include +#include +#include +#include + +#include "experimental/xrt_kernel.h" +#include "experimental/xrt_graph.h" +#include "xrt/xrt_aie.h" +#include "host.h" + +// const int Niter = 999; +const int PROFILE_WINDOW_SIZE_in_bytes = 1024; + +template +int load_data_file(std::string fname,T * data,int L) +{ + T d; + int l=0; + + std::ifstream fin(fname); + if(!fin) return(-1); + + while(fin>>d) + { + data[l++] = d; + if(l==L) break; + } + fin.close(); + return(l); +} + +// union { +// struct { short re,im;} cpx; +// int val; +// } cvt; + + +// Simulation + +#define MEM_SIZE(NITER) ((NITER) * FRAME_LENGTH / PLIO_NDATA ) + +int run(int argc, char* argv[]){ + + int pl_bram_size_in_bytes = PL_MEMORY_SIZE*PLIO_NBYTES; + + //TARGET_DEVICE macro needs to be passed from gcc command line + if(argc != 2 && argc != 3) { + std::cout << "Usage: " << argv[0] <<" [Niterations (default 1000)]" << std::endl; + return EXIT_FAILURE; + } + + std::string niter("1000"); + if(argc==3) + niter = std::string(argv[2]); + + int Niter = std::stoi(niter); + int profile_output_size_in_bytes = PROFILE_WINDOW_SIZE_in_bytes * Niter; + + char* xclbinFilename = argv[1]; + + + std::cout << "The simulation will run " << Niter << " Iterations" << std::endl << std::endl; + + // Open xclbin + xrt::device device = xrt::device(0); //device index=0 + if(device == nullptr) + throw std::runtime_error("No valid device handle found. Make sure using right xclOpen index."); + xrt::uuid uuid = device.load_xclbin(xclbinFilename); + + // s2mm & mm2s kernel handle + const int NioStreams = NAntenna; + const int NplKernels = NioStreams; + xrt::kernel * s2mm[NplKernels]; + xrt::kernel * gen2s[NplKernels]; + + for(int i=0;igroup_id(0)); + host_out[i] = out_bo[i]->map(); + } + + //kernel run + xrt::run s2mm_run[NplKernels]; + xrt::run gen2s_run[NplKernels]; + + // graph run + auto cghdl = xrt::graph(device,uuid,"G"); + cghdl.reset(); + std::cout << "graph Reset" << std::endl; + + // Update RTPs Before Run + int16_t coef1[] = {1,0}; + // int16_t coef2[] = {2,0}; + // int16_t coef3[] = {4,0}; + + std::string AntName[NAntenna]; + for(int i=0;isync(XCL_BO_SYNC_BO_FROM_DEVICE); + + int match = 0; + + // std::ofstream out("out.txt",std::ofstream::out); + // for (int i = 0; i < OUTPUT_SIZE; i++) { + // if(host_out1[i]!=0 || host_out2[i]!=0){ + // std::cout<<"ERROR: i="< it contains 4 samples --> 16 bytes +#define PLIO_NBYTES (PLIOW/8) +#define PLIO_NDATA (PLIO_NBYTES/DATA_NBYTES) + +// Array size defined in mm2s and s2mm +#define PL_MEMORY_SIZE 512 diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/verif_path.mk b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/verif_path.mk new file mode 100755 index 0000000000..e2a48148ec --- /dev/null +++ b/AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/verif_path.mk @@ -0,0 +1,33 @@ +# +#Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +#SPDX-License-Identifier: MIT +# + +# Version Number TOOLV must be defined (common.mk should be called before) + + +### +# Guarding Checks. Do not modify. +### +check_defined = \ + $(strip $(foreach 1,$1, \ + $(call __check_defined,$1,$(strip $(value 2))))) + +__check_defined = \ + $(if $(value $1),, \ + $(error Undefined $1$(if $2, ($2)))) + +guard-PLATFORM_REPO_PATHS: + $(call check_defined, PLATFORM_REPO_PATHS, Set your where you downloaded your platform) + +guard-ROOTFS: + $(call check_defined, ROOTFS, Set to: xilinx-versal-common-v$(TOOLV)/rootfs.ext4) + +guard-IMAGE: + $(call check_defined, IMAGE, Set to: xilinx-versal-common-v(TOOLV)/Image) + +guard-CXX: + $(call check_defined, CXX, Run: xilinx-versal-common-v(TOOLV)/environment-setup-cortexa72-cortexa53-xilinx-linux) + +guard-SDKTARGETSYSROOT: + $(call check_defined, SDKTARGETSYSROOT, Run: xilinx-versal-common-v(TOOLV)/environment-setup-cortexa72-cortexa53-xilinx-linux) \ No newline at end of file diff --git a/AI_Engine_Development/AIE/Feature_Tutorials/README.md b/AI_Engine_Development/AIE/Feature_Tutorials/README.md index df50847bef..9c397cc3e8 100755 --- a/AI_Engine_Development/AIE/Feature_Tutorials/README.md +++ b/AI_Engine_Development/AIE/Feature_Tutorials/README.md @@ -63,7 +63,7 @@ The [**README**](../README.md) of AI Engine Development contains important infor Debug Walkthrough Tutorial -This tutorial demonstrates how to debug a multi-processor application using the Versal ACAP AI Engines, using a beamformer example design. The tutorial illustrates functional debug and performance level debug techniques. +This tutorial demonstrates how to debug a multi-processor application using the Versal adaptive SoC AI Engines, using a beamformer example design. The tutorial illustrates functional debug and performance level debug techniques. AI Engine DSP Library and Model Composer Tutorial @@ -73,7 +73,7 @@ This tutorial shows how to design AI Engine applications using Model Composer. T Versal Emulation Waveform Analysis -This tutorial demonstrates how you can use the Vivado logic simulator (XSIM) waveform GUI, and the Vitis analyzer to debug and analyze your design for a Versal ACAP. +This tutorial demonstrates how you can use the Vivado logic simulator (XSIM) waveform GUI, and the Vitis analyzer to debug and analyze your design for a Versal adaptive SoC. AI Engine Performance and Deadlock Analysis Tutorial @@ -120,7 +120,11 @@ This multi-part tutorial describes how to implement an [infinite impulse respons A Gentle Introduction to AI Engine Kernel Programming In this tutorial, we will guide you on how to get data into and out of a kernel using a simple contrived example. - + + + System Timeline Tutorial + This tutorial demostrates how to use System Timeline, a new feature allows the user to trace all subsystems of the device (PL, PS and EI Engine array) and display them in Vitis Analyzer on the same graph with sychronized timeline. + diff --git a/AI_Engine_Development/AIE/README.md b/AI_Engine_Development/AIE/README.md index f1b01eced6..dbcfdd01d5 100644 --- a/AI_Engine_Development/AIE/README.md +++ b/AI_Engine_Development/AIE/README.md @@ -31,7 +31,7 @@ To easily find the right documentation corresponding to the development stage yo The major documentation for AI Engine includes: -- *Versal ACAP AI Engine Architecture Manual* [AM009](https://docs.amd.com/r/en-US/am009-versal-ai-engine) +- *Versal adaptive SoC AI Engine Architecture Manual* [AM009](https://docs.amd.com/r/en-US/am009-versal-ai-engine) - *AI Engine Tools and Flows* [UG1076](https://docs.amd.com/r/en-US/ug1076-ai-engine-environment) - *AI Engine Kernel and Graph Programming Guide* [UG1079](https://docs.amd.com/r/en-US/ug1079-ai-engine-kernel-coding) @@ -45,16 +45,16 @@ If you are new with AI Engine, the following training courses can help you under ### Environment Settings -**IMPORTANT**: Before beginning the tutorial make sure you have read and followed the *Vitis Release Notes And Installation Guide* ([UG1742](https://docs.amd.com/access/sources/dita/map?Doc_Version=2025.1%20English&url=ug1742-vitis-release-notes)) (v2025.1) for setting up software and installing the VCK190 base platform. +**IMPORTANT**: Before beginning the tutorial make sure you have read and followed the *Vitis Release Notes And Installation Guide* ([UG1742](https://docs.amd.com/r/en-US/ug1742-vitis-release-notes)) (v2025.2) for setting up software and installing the VCK190 base platform. Run the following steps to setup environment (do **NOT** apply to tutorials that do not use the VCK190 base platform): -1. Set up your platform by running the `xilinx-versal-common-v2025.1/environment-setup-cortexa72-cortexa53-amd-linux` script as provided in the platform download. This script sets up the `SYSROOT` and `CXX` variables. If the script is not present, you **must** run the `xilinx-versal-common-v2025.1/sdk.sh` command. -2. Set up your `ROOTFS` to point to the `xilinx-versal-common-v2025.1/rootfs.ext4`. -3. Set up your `IMAGE` to point to `xilinx-versal-common-v2025.1/Image`. +1. Set up your platform by running the `xilinx-versal-common-v2025.2/environment-setup-cortexa72-cortexa53-amd-linux` script as provided in the platform download. This script sets up the `SYSROOT` and `CXX` variables. If the script is not present, you **must** run the `xilinx-versal-common-v2025.2/sdk.sh` command. +2. Set up your `ROOTFS` to point to the `xilinx-versal-common-v2025.2/rootfs.ext4`. +3. Set up your `IMAGE` to point to `xilinx-versal-common-v2025.2/Image`. 4. Set up your `PLATFORM_REPO_PATHS` environment variable based upon where you downloaded the platform. ### Getting Started with AI Engine Development Using the AI Engine Tutorials @@ -437,6 +437,20 @@ These tutorials target the **VCK190** board. The table below lists the tutorials + + System Timeline Tutorial + Base + Linux + Yes + + MM2S / S2MM + Yes + Yes + Yes + Yes + Yes + Yes + ### Design Tutorials diff --git a/CHANGELOG.md b/CHANGELOG.md index 5009440b07..295b333c85 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,28 @@ # Vitis-Tutorials ChangeLog +## 2025.2 (Dec. 4, 2025) + +### New Tutorials + +- AI_Engine_Development/AIE-MLv2/Feature_Tutorials/01-aie-mlv2_a_to_z/ +- AI_Engine_Development/AIE-MLv2/Design_Tutorials/01-Radio-ML/ +- AI_Engine_Development/AIE/Feature_Tutorials/27-system-timeline/ + +### Tutorial Updates + +- Removed a few tutorials due to discontinued feature support or replacement by consolidated and updated content. + - Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/ + - Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/ + - Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ + - AI_Engine_Development/AIE/Feature_Tutorials/18-aie_a_to_z_custom_linux_platform/ + +### EoU Improvements + +- Introduce a new sub-category `AIE-MLv2` under `AI_Engine_Development` to host new tutorials focused on Versal Gen2 devices with AI Engine ML v2 architecture. + +
+ 2025.1 Release + ## 2025.1_update (Sep. 10, 2025) ### New Tutorials @@ -50,9 +73,9 @@ - Introduce a new category `Vitis_System_Design` to host new tutorials focused on system design flows. - Remove tutorials from the `Hardware_Acceleration` category in this branch. These tutorials are still available in previous branches. +
- -
+
2024.2 Release ## 2024.2_update (Feb. 25, 2025) diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/LICENSE b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/LICENSE deleted file mode 100644 index f7ac91ea81..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/LICENSE +++ /dev/null @@ -1,21 +0,0 @@ -The MIT License (MIT) - -Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. - -Permission is hereby granted, free of charge, to any person obtaining a copy -of this software and associated documentation files (the "Software"), to deal -in the Software without restriction, including without limitation the rights -to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -copies of the Software, and to permit persons to whom the Software is -furnished to do so, subject to the following conditions: - -The above copyright notice and this permission notice shall be included in all -copies or substantial portions of the Software. - -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/README.md b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/README.md index 35dc2a07fb..2e80ef13cf 100644 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/README.md +++ b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/README.md @@ -18,709 +18,10 @@ - Target board: VCK190 - Last update: 06 Sep. 2024 - -## Table of Contents - -[1.0 Introduction](#1-introduction) - -[2.0 Project Setup](#2-project-setup) - -[3.0 Decimation FIR Filter DSP Design](#3-decimation-fir-filter-dsp-design) - -[4.0 Using the Thin Platform](#4-using-the-thin-platform) - -[References](#references) - -[Support](#support) - -[License](#license) - -## 1 Introduction - -Developing a DSP algorithm with the AI Engine technology is only one part of the design flow and not necessarily the most complicated one. At the end of the day, the DSP kernels implemented into the AI Engine array have to be connected with the Programmable Logic (PL) datamover kernels and with the ARM A72 CPU host Programmable Subsystem (PS): the PL kernels require AMD Vitis™ HLS as design flow, the PS application requires C/C++ programming with either XRT or OpenCL APIs to manage the kernels at runtime execution on the target board within the PetaLinux OS. - -Building a system from scratch like this is not trivial and it is better to have a good starting point that could be adapted with few changes, a sort of "system design template" or "toolbox" to use some improper terminology. - -This tutorial explains how to design a DSP algorithm and implement it into the AI Engine domain of the AMD Versal™ device, using the production [VCK190](https://www.xilinx.com/products/boards-and-kits/vck190.html) target board and the AMD Vitis 2024.1 [Unified software platform](https://www.xilinx.com/products/design-tools/vitis/vitis-platform.html) design tools. - -The DSP algorithm is a decimation FIR filter taken from the Vitis 2024.1 [DSP Libraries (for AI Engine)](https://github.com/Xilinx/Vitis_Libraries/tree/2024.1/dsp). - -You will build a system running on the VCK190 board having: - -- A DSP kernel implemented on AI Engine domain (the decimation FIR filter) -- Two PL datamover kernels, designed with [HLS](https://docs.amd.com/v/u/en-US/dh0090-vitis-hls-hub) -- Software application for the ARM host processor using the [XRT](https://www.xilinx.com/products/design-tools/vitis/xrt.html) APIs -- An SD card with PetaLinux OS for booting - -As you use this document, it is assumed that you have named this tutorial repository ``02-AIE_DSP_with_Makefile_and_GUI`` and placed it in a certain working directory ``${WRK_DIR}``. For example, in this case: -``export WRK_DIR=/media/danieleb/DATA/2024.1/Vitis-Tutorials/Developer_Contributed``. - -The organization of the folders tree of this tutorial is illustrated here (with emphasis on the folder related to AI Engine; otherwise, the tree would explode): - -``` -/media/danieleb/DATA/2024.1 - | - ├── Vitis_Libraries - │   ├── dsp - │   │   ├── docs - │   │   ├── ext - │   │   ├── L1 - │   │   └── L2 - │   │   ├── benchmarks - │   │   ├── examples - │   │   ├── include - │   │   ├── meta - │   │   └── tests/aie - │   │ - ├── Vitis-Tutorials - │   ├── AI_Engine_Development - │   │   ├── Design_Tutorials - │   │   ├── Feature_Tutorials - │ │ └── Introduction - │ ├── Developer_Contributed # the ${WRK_DIR} - │ │ └── 01-Versal_Custom_Thin_Platform_Extensible_System - │ │ └── 03-HLS_Code_Optimization - │ │ └── 02-AIE_DSP_with_Makefile_and_GUI # this tutorial - │ │ | └── files # current directory - -``` - - -## 2 Project Setup - -### 2.1 Warnings - -1. Everything shown in this project used an Ubuntu 22.04 Desktop with related Vitis 2024.1 release. - -2. It is recommended to write the SD card that boots the VCK190 board with the Windows OS utility called [Win32 Disk Imager 1.0](https://sourceforge.net/projects/win32diskimager/). - -3. Some figures are screenshots related to the earlier release of Vitis and there might be a few differences, although minimal, with the current one. - -4. It is recommended that you set correctly the environment before running any script, as described in details in the next subsection 2.3.6. The ``*_sample_env_setup.sh`` [scripts](files/scripts) contain a template to be customized for your needs. - -5. The [run_all.sh](files/run_all.sh) must always be launched **only after** all the variables of previous script have been set at least once, and **only from** the [files](files) folder, which has to be your current directory. - -6. Read the entire README.md document carefully before launching any script or Makefile. - -### 2.2 Dos-to-Unix Conversion - -In case you get some unexpected errors during the execution of the scripts, once pre-process all the``*.sh``, ``*.cpp``, ``*.h`` files with the [dos2unix](http://archive.ubuntu.com/ubuntu/pool/universe/d/dos2unix/dos2unix_6.0.4.orig.tar.gz) utility. -In that case, run the following commands from your Ubuntu host PC: - -```bash -#sudo apt-get install dos2unix -cd #your working directory -cd 02-AIE_DSP_with_Makefile_and_GUI/files -source scripts/dos2unix_all.sh -``` - -### 2.3 Environment Setup - -#### 2.3.1 Archives Download - -You need the following archives from either AMD/Xilinx Download or GitHub websites, in particular: - -- From [Vitis (SW Developer) Downloads](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/vitis.html) area, take the **2024.1 Vitis Installer** (it makes the Vitis install process easy) and the **2024.1 Vitis Update** (if any). - -- From [Vitis Embedded Platforms](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html) area, take the **Common Images for Embedded Vitis Platforms 2024.1**. - -- From [PetaLinux](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-design-tools.html) area, take the **2024.1 PetaLinux Tools Installer**. - -- Go to the bottom of [PetaLinux 2024.1 - Product Update Release Notes and Known Issues](https://support.xilinx.com/s/article/000034483?language=en_US) and take **2024.1_PetaLinux_Package_List.xlsx** file, which contains all the packages needed by PetaLinux into your Ubuntu OS computer (install all of them before installing PetaLinux). - -- Go to the [Xilinx GitHub page](www.github,com/Xilinx) and zip both the [Vitis Libraries](https://github.com/Xilinx/Vitis_Libraries) and [Vitis Tutorials](https://github.com/Xilinx/Vitis-Tutorials) with branch related to this 2024.1 release. - -- Go to the [AMD Alveo™ Packages](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/alveo.html) area, select release 2024.1 and Ubuntu 22.04 OS, and then take the **Xilinx Runtime (XRT)** archive. - -At the end, you should have the following files: - -```text -Xilinx_Unified_2024.1_*_Lin64.bin -Xilinx_Vivado_Vitis_Update_2024.1_*.tar.gz -xilinx-versal-common-v2024.1_*.tar.gz -Vitis_Libraries-main.zip -Vitis-Tutorials-2024.1.zip -xrt_202410.*-amd64-xrt.deb -``` - -First, install the basic version of Vitis 2024.1 via the installer ``Xilinx_Unified_2024.1_*_Lin64.bin``. Then add the update ``Xilinx_Vivado_Vitis_Update_2024.1*.tar.gz``. Everything is placed in the folder ``/tools/Xilinx/``. - -#### 2.3.2 Sudo or not Sudo? - -You **might** need ``sudo`` privilege to install tools on these folders, primarily ``/tools`` and ``/opt``, unless you change the ownership and group of folders accordingly. - -If you created the ``/tools`` directory as a super-user (or ``root``, or with ``sudo``), whatever you want to write or install there can only be done by the ``root`` super-user. -This is a basic Linux OS behavior. However, you can change the group and owner so that you can do what you like as a normal user, the way you do it in your ``$HOME`` directory. - -So, if you run the following commands (and you need ``sudo``): - -```shell -sudo su -mkdir /tools -mkdir /opt -# -R stays for recursively on each subfolder -chown -R you_user_name /tools -chgrp -R you_user_name /tools -chown -R you_user_name /opt -chgrp -R you_user_name /opt -exit -``` - -Then you can install the above tools and archives without ``sudo`` privilege, just as a normal user. - -As a last cross-check, if you installed the tools as a normal user, you should see the hidden folder ``.Xilinx`` inside your ``$HOME`` directory. If you installed them as a super-user, you should see -the hidden folder ``.Xilinx`` inside your ``/root`` directory. - -In case of installation done with the ``sudo`` privilege, there seems to be only a small issue with one line in the script ``installLibs.sh``: - -```shell -su - $user -c "touch $logFile; chmod 777 $logFile" -``` - -The ``touch`` and ``chmod`` commands can not be executed because the logfile is located below the ``/root`` directory and the shell was switched to a normal user without root privileges. -This means that the script assumes that the installation was done without root privileges. That line in the script could be replaced by the following commands: - -```shell -sudo touch $logFile -sudo chmod 777 $logFile -``` - -In conclusion, either the installation had root privileges (``sudo``) and the ``installLibs.sh`` needs to be changed, or the installation was done as a normal user. - -#### 2.3.3 Install Versal Common - -You have to install this archive ``xilinx-versal-common-v2024.1_*.tar.gz`` in the folder ``/opt/xilinx/common/`` folder (which has to be into an ``ext4`` file system, not on an ``NTFS`` one). - -Then, you have to execute the following commands as a normal user, according to what is discussed in the previous subsection: - -```shell -cd /opt/xilinx/common/xilinx-versal-common-v2024.1/ -chmod 777 ./sdk.sh # if needed -./sdk.sh -p -y -d . -``` - -Check if you need to decompress the file ``rootfs.ext4.gz`` directly. -You can then remove the ``sdk.sh`` file to save storage space. - -#### 2.3.4 Install XRT - -The easiest way to download XRT was from the [ALVEO](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/alveo.html) site. -Select the ALVEO U200 card and then the Ubuntu 22.04 OS to arrive at this [link](https://www.xilinx.com/bin/public/openDownload?filename=xrt_202410.2.17.319_22.04-amd64-xrt.deb). - -Then install the archive via the following command: - -```shell -sudo apt install --reinstall ./xrt_.deb -``` - -To set ``xrt`` into your terminal, you need the following command: - -```shell -source /opt/xilinx/xrt/settings.sh -``` - -which is also in the ``*_sample_env_setup.sh`` scripts. - -#### 2.3.5 Install Petalinux - -**WARNING: You cannot install PetaLinux into an NFS driver; otherwise, the install process ends with a non-predictable error message**. - -Before installing ``petalinux``, check in the Excel foil ``2024.1_PetaLinux_Package_List.xlsx`` what all packages ``petalinux`` requires. Once done, install the missing ones. - -``` -#create the destination folder -sudo mkdir /petalinux_2024.1 -#change permissions -$ chmod 777 ~/Downloads/petalinux-v2024.1-*-installer.run -$ ~/Downloads/petalinux-v2024.1-*-installer.run -d /petalinux_2024.1 - -. . . - -INFO: Installing PetaLinux... -INFO: Checking PetaLinux installer integrity... -INFO: Installing PetaLinux to "/petalinux_2024.1/." -INFO: Installing buildtools in /petalinux_2024.1/./components/yocto/buildtools -INFO: Installing buildtools-extended in /petalinux_2024.1/./components/yocto/buildtools_extended -INFO: PetaLinux has been installed to /petalinux_2024.1/. -``` - -To set ``petalinux`` into your terminal, you need the following command: - -```shell -source /petalinux_2024.1/settings.sh -``` - -which was also placed in the script ``*_sample_env_setup.sh``. - -#### 2.3.6 Set Environmental Variables - -The ``*_sample_env_setup.sh`` [scripts](files/scripts) contain a template to be adapted by the user to set the tools environment for designing an embedded system on the VCK190 target board. - -Once done, call the script with the following command: - -```shell -cd #your working directory -cd 02-AIE_DSP_with_Makefile_and_GUI/files -# set your environment -source files/scripts/_sample_env_setup.sh -``` - -## 3 Decimation FIR Filter DSP Design - -In this section, you will build the decimation FIR filter DSP system using the Vitis GUI. The PS application will apply XRT APIs. The OS is PetaLinux. - - -### 3.1 GUI-based Flow - -Note that the **classic Vitis IDE (Eclipse-based)** has been deprecated and will be removed in a future release, being it replaced by the **new Vitis Unified IDE**. If you want to use the classic IDE you have to call it with ``vitis --classic`` command as in the following: - -```shell -cd #your working directory -cd 02-AIE_DSP_with_Makefile_and_GUI/files -# set your environment -#source files/scripts/_sample_env_setup.sh -# call the Vitis GUI -cd gui-flow/fir-dsplib_prj -vitis --classic --workspace ./classic_xrt_wrk -``` - -Follow the following steps: - -1. Select ``File -> Application Project -> Next`` from the GUI and then select the ``xilinx_vck190_base_202410_1`` platform for your project. - -2. Click Next and give a name to your application project and your system project. For example, ``dsplib_fir_AIE`` and ``dsplib_fir_system``, respectively. - -3. Select ``aie_engine`` as the target processor and click ``Next`` twice. - -4. Select an ``Empty application`` template and click ``Finish``. Following the above steps, you have created the folder for the AI Engine subsystem. - -5. Select ``File -> New -> HW Kernel Project -> Next`` from the GUI and then select the ``xilinx_vck190_base_202310_1`` platform again for your project. Click ``Next``. - -6. Give a name to your PL HW kernel project, for example ``dsplib_fir_PL``. Ensure that you are still using the ``dsplib_fir_system``. Click ``Finish``. With these steps 5 and 6, you have created the folder for the PL subsystem. - -7. Select ``File -> New -> Application Project -> Next`` from the GUI and then select the ``xilinx_vck190_base_202310_1`` platform for your project. - -8. Click ``Next`` and give ``dsplib_fir_PS`` as name to your application project and ensure that you are still using the ``dsplib_fir_system``. - -9. Select ``cortexA72`` as the target processor and click ``Next``. Then select the ``xrt domain``. - -10. Set the path names for the ``Sysroot, Root FS, Kernel Image`` of the embedded OS. Then click ``Next``. Here are the environment settings for your reference: - - ```text - - /opt/xilinx/common/xilinx-versal-common-v2023.2/sysroots/cortexa72-cortexa53-amd-linux #Sysroot path - - /opt/xilinx/common/xilinx-versal-common-v2023.2/rootfs.ext4 #Root FS - - /opt/xilinx/common/xilinx-versal-common-v2023.2/Image #Kernel Image - ``` - -11. Select an ``Empty application`` template and click ``Finish``. With steps 7 to 11, you have created the folder for the PS subsystem. Now it is time to import all the source files into the Vitis project (still empty at the moment). - -12. From Vitis GUI, right-click on the ``dsplib_fir_AIE [aiengine]`` folder, select ``Import Sources`` and take all the source files from ``files/src/ip/aie/src`` and put them into ``dsplib_fir_AIE/src``. Copy the entire subfolder ``files/src/ip/aie/src/graphs`` into ``dsplib_fir_AIE/src/``. Repeat the step for all the data files from ``files/src/ip/aie/data`` to ``dsplib_fir_AIE/data``. - -13. From Vitis GUI, right-click on the ``dsplib_fir_PL`` folder, select ``Import Sources`` and take all the source files from the two folders ``files/src/ip/mm2s_aie/src`` and ``files/src/ip/s2mm_aie/src`` and put them into ``dsplib_fir_PL/src``. - -14. From Vitis GUI, right-click on the ``dsplib_fir_PS [xrt]`` folder, select ``Import Sources`` and take all the source files from ``files/src/ps_apps/aie_test/src`` and put them into ``dsplib_fir_PS/src``. - -15. From Vitis GUI, right-click on the ``dsplib_fir_system_hw_link [pl]``, select ``Import Sources`` and take the ``files/src/vitis/src/system.cfg`` file and put it into ``dsplib_fir_system_hw_link [pl]`` itself. Now that all the source files have been imported, you should see something like in Figure 3.1-1. Now set up all the settings to finally build the entire project. - -16. Select the ``dsplib_fir_AIE.prj`` file and select the ``Top-Level File`` file named ``fir_graph.cpp``. - -17. From Vitis GUI, right-click on the ``dsplib_fir_AIE [aiengine]`` domain and select ``C/C++ Build Settings``. Make sure to select ``Configuration [All Configurations]``. Add the following directories to the default ones in ``Input Spec``, then click ``Apply and Close``. You should see something like in Figure 3.2-2. - - ```text - ${env_var:XILINX_VITIS}/aietools/include - ${env_var:DSPLIB_ROOT}/L1/src/aie - ${env_var:DSPLIB_ROOT}/L1/include/aie - ${env_var:DSPLIB_ROOT}/L2/include/aie - ${env_var:XILINX_HLS}/include - ${workspace_loc:/${ProjName}/src} - ${workspace_loc:/${ProjName}/src/graphs} - ${workspace_loc:/${ProjName}/data} - ``` - -18. Click on ``dsplib_fir_system_hw_link.prj`` file, right-click on ``binary_container_1``, select ``Edit V++ Options settings``, and add ``--config=../system.cfg`` as illustrated in Figure 3.2-3. - -19. The ``system.cfg`` file for ``aie_L2dsplib_system_hw_link [pl]`` domain is set as in the following (see Figure 3.2-4): - - ``` - [connectivity] - stream_connect=mm2s_1.s:ai_engine_0.DataIn1 - stream_connect=ai_engine_0.DataOut1:s2mm_1.s - ``` - -20. Click on the ``dsplib_fir_PL.prj`` file. Push the ``Add the HW functions`` button and select the ``mm2s`` and ``s2mm`` functions, as illustrated in Figure 3.2.5. - -21. From Vitis GUI, right-click on the ``dsplib_fir_PS [xrt]`` domain and select ``C/C++ Build Settings``. Make sure to select ``Configuration [All Configurations]``. - - - As illustrated in Figure 3.2-6, for the GCC host compiler, the other dialect flag has to be set to - - ``` - -std=c++17 - ``` - - Then click ``Apply and Close``. - - - As illustrated in Figure 3.2-7, add the following library search paths (``-L`` flag): - - ```text - ${env_var:XILINX_VITIS)/aietools/lib/aarch64.o - ${SYSROOT}/usr/lib - ``` - - - and libraries (``-l`` flag): - - ```text - xilinxopencl - xaiengine - adf_api_xrt - xrt_core - xrt_coreutil - ``` - - - As illustrated in Figure 3.2.8, add the following directories to the default ones in ``Include``, then click ``Apply and Close``. - - ```text - ${env_var:XILINX_VITIS}/aietools/include - ${env_var:XILINX_VITIS}/include - ${env_var:XILINX_HLS}/include - ${env_var:DSPLIB_ROOT}/L1/src/aie - ${env_var:DSPLIB_ROOT}/L1/include/aie - ${env_var:DSPLIB_ROOT}/L2/include/aie - ${workspace_loc:/dsplib_fir_AIE/src} - ${workspace_loc:/dsplib_fir_AIE/src/graphs} - ${SYSROOT}/usr/include/xrt - ``` - - -![figure1B](files/images/fir_sys.png) - -*(Figure 3.2-1) Setting OS paths to compile the host software subsystem.* - -![figure2B](files/images/fir_aie.png) - -*(Figure 3.2-2) Vitis GUI-based flow: C/C++ Build Settings for the AIE subsystem.* - -![figure3B](files/images/fir_sys_pl.png) - -*(Figure 3.2-3) Vitis GUI-based flow: assigning the system.cfg file to the binary container.* - -![figure4B](files/images/fir_connect.png) - -*(Figure 3.2-4) Vitis GUI-based flow: system.cfg configuration file in details.* - -![figure5B](files/images/fir_hls.png) - -*(Figure 3.2-5) Vitis GUI-based flow: project settings for the kernels of PL subsystem.* - -![figure6B](files/images/fir_dialect.png) - -*(Figure 3.2-6) Vitis GUI-based flow: settings the C++ dialect to compile the host software subsystem.* - -![figure7B](files/images/fir_PS_libs.png) - -*(Figure 3.2-7) Setting the libraries and related paths to compile the host software subsystem.* - -![figure8B](files/images/fir_ps_inc.png) - -*(Figure 3.2-8) Setting the include paths to compile the host software subsystem.* - -### 3.2 Makefile-based Flow - -Alternatively, to the GUI-based flow, use Vitis from command line with the proper makefile by typing the following: - -```shell -cd #your working directory -cd 02-AIE_DSP_with_Makefile_and_GUI/files -# set your environment -#source files/scripts/_sample_env_setup.sh -# launch makefile-based flow -#source ./run_all.sh -cd make-flow -make all -``` - -### 3.3 Test on VCK190 Target Board - -Whatever flow you have selected based on either GUI or Makefile, once you have written the generated SD card, you can boot the VCK190 board. - -At the prompt on UART terminal digit, insert the ``petalinux`` username and choose a password to login, for example, ``root``. -You should see the following: - -```text -versal-rootfs-common-20231 login: petalinux -Password: -versal-rootfs-common-20231:~$ sudo su -Password: -versal-rootfs-common-20231:/home/petalinux# mount /dev/mmcblk0p1 /mnt -versal-rootfs-common-20231:/home/petalinux# cd /mnt - -versal-rootfs-common-20231:/mnt# ls -l -total 33549 --rwxrwx--- 1 root disk 4002464 Jan 1 2015 BOOT.BIN --rwxrwx--- 1 root disk 22268416 Jan 1 2015 Image -drwxrwx--- 2 root disk 512 Apr 14 2023 System Volume Information --rwxrwx--- 1 root disk 6840118 Jan 1 2015 binary_container_1.xclbin --rwxrwx--- 1 root disk 3015 Jan 1 2015 boot.scr --rwxrwx--- 1 root disk 1238840 Jan 1 2015 dsp_fir.exe -versal-rootfs-common-20231:/mnt# -versal-rootfs-common-20231:/mnt# -``` - -You can now launch the following commands: - -```shell -sudo su -mount /dev/mmcblk0p1 /mnt -cd /mnt -./dsplib_fir_PS binary_container_1.xclbin -``` - -You should see the following: - -``` -versal-rootfs-common-20231:/mnt# ./dsp_fir.exe ./binary_container_1.xclbin -. . . -INFO: iterations = 0 -INFO: words SizeIn = 8192 -INFO: words SizeOut = 4096 -INFO: bytes SizeIn = 32768 -INFO: bytes SizeOut = 16384 -. . . -PASSED: my_graph.reset() -PASSED: my_graph.run(0) -INFO: Waiting for kernels to end... -PASSED: in_0_run.wait() -PASSED: out_0_run.wait() -PASSED: out_0_bo.sync(XCL_BO_SYNC_BO_FROM_DEVICE) -INFO: Veryfing output data vs. golden ones - -PASSED: ./dsp_fir.exe - -versal-rootfs-common-20231:/mnt# -``` - -## 4 Using the Thin Platform - -### 4.1 Get the Thin Platform - -The [Versal Custom Thin Platform Extensible System](https://github.com/Xilinx/Vitis-Tutorials/tree/2022.1/Developer_Contributed/01-Versal_Custom_Thin_Platform_Extensible_System) tutorial has the following aspects to be considered: - -- It is always well-maintained and promptly updated along the various Vitis releases. -- By default, it generates a ``sd_card.img`` file with ``petalinux`` file system on it and the SD card has only one partition (FAT32). -- It applies a hierarchy of ``Makefiles`` that should enable an "easier" customization of the system to be designed, without touching or modifying the directories structure and the Makefile themselves too. - -Few notes to be mentioned besides what is already reported in its related [README.md](https://github.com/Xilinx/Vitis-Tutorials/blob/2022.1/Developer_Contributed/01-Versal_Custom_Thin_Platform_Extensible_System/README.md) file: - -1. Do not use the ``sd_card.img`` file generated in the ``package_output_hw``. On the contrary, format the SD card with a Windows OS utility like [SD Card Formatter (5.0.2 developed by Tuxera Inc)](https://www.sdcard.org/cms/wp-content/uploads/2020/11/SD_Card-Formatter_Press_Release.pdf) in FAT32 format to a size of more than 2GB (at least). Then you can directly copy the files from the ``package_output_hw/sd_card`` folder. The reason is that with the ``sd_card.img`` file, the VCK190 sometimes does not boot for this particular design. - -2. At the prompt on UART terminal digit, insert the ``petalinux`` username and choose a password (for example, ``root``). - - -### 4.2 Integrate the FIR Filter in the Thin Platform - -As already stated in the previous subsection, the Thin Platform has several advantages, being based on makefile flow, including ease of use, and fast compilation time. In this separate section, you will design the same project of section [3 Decimation FIR Filter DSP Design](#31-decimation-fir-filter-dsp-design), -that is, a decimation-by-2 FIR filter taken from the Vitis DSP Library for AI Engine. -This time, you will implement such a design into the Thin Platform makefile based template as an alternative to using the two flows described in subsection 3.1 (GUI-based flow) and 3.2 (Makefile-based flow). - -The [prepare_thin-plat_files.sh](files/scripts/prepare_thin-plat_files.sh) script called from within [run_all.sh](files/run_all.sh) script copies the Thin Platform folder and renames it into ``thin-plat``. It then removes folders (``ip/counter``, ``ip/mm2s_vadd_s``, ``ip/s2mm_vadd_s``, ``ip/subtractor``) that are not required for this FIR filter design. It then changes other files, as explained in the next section. - -```shell -cd #your working directory -cd 02-AIE_DSP_with_Makefile_and_GUI/files #current dir -# set your environment -#source files/scripts/_sample_env_setup.sh -# source run_all.# -source ./scripts/prepare_thin-plat-files.sh -``` - -#### 4.2.1 What To Change in the Thin Platform - -The original Thin Platform has the following subfolders: - -``` -01-Versal_Custom_Thin_Platform_Extensible_System/ -├── documentation -├── linux -├── ps_apps -│   └── linux -│   ├── aie_dly_test -│   ├── vadd_mm_cpp -│   ├── vadd_mm_ocl -│   └── vadd_s -├── vitis -│   ├── ip -│   │   ├── aie -│   │   ├── counter -│   │   ├── mm2s_vadd_s -│   │   ├── s2mm_vadd_s -│   │   ├── subtractor -│   │   ├── vadd_mm -│   │   ├── vadd_s -│   ├── src -│   └── xpfm_export -└── vivado -``` - -while this project requires the following folders: - -``` -thin-plat/ -├── linux -├── ps_apps -│   └── linux -│   └── aie_test -├── vitis -│   ├── ip -│   │   ├── aie -│   │   ├── mm2s_aie -│   │   ├── s2mm_aie -│   ├── src -│   └── xpfm_export -└── vivado -``` - -therefore you should have to do manually the following changes: - -1. Add your AI Engine graph and kernels code into the ``vitis/ip/aie`` folder and adapt the related ``vitis/ip/aie/Makefile`` to your case. -1. Add your HLS kernels code into the ``vitis/ip`` folder, one HLS kernel in each subfolder, for example, ``vitis/ip/mm2s_aie`` and ``vitis/ip/s2mm_aie``. Then check or adapt the related ``vitis/ip/mm2s_aie/Makefile`` and ``vitis/ip/s2mm_aie/Makefile``. -1. Add your PS code into the ``ps_apps/linux`` folder. For example, ``ps_apps/linux/aie_test``. Then check or adapt the related ``ps_apps/linux/aie_test/Makefile``. -1. Adapt the ``vitis/src/system.cfg`` configuration file for the Vitis Linker according to your connectivity (in this specific case, it is the same as the original Thin Platform repository, so no changes at all). -1. Do not modify the ``vitis/ip/Makefiles`` because it orchestrates all the Makefiles of the various subfolders. The remaining ones are managed "automatically" by the other Makefiles of the Thin Platform project. - -To provide ease, all above steps are already done by the script [prepare_thin-plat_files.sh](files/scripts/prepare_thin-plat_files.sh) and the Makefiles are already changed and available in this repository. - -Run the following commands: - -```shell -cd #your working directory -cd 02-AIE_DSP_with_Makefile_and_GUI/files #cur dir -# set your environment -#source files/scripts/_sample_env_setup.sh -#prepare the Thin Platform folder -source ./scripts/prepare_thin-plat_files.sh -``` - -Now you can build the SD card with the following commands: - -```shell -cd #your working directory -cd 02-AIE_DSP_with_Makefile_and_GUI/files -# set your environment -#source files/scripts/_sample_env_setup.sh -cd thin-plat -make all TARGET=hw -``` - -As already mentioned in the previous subsection, do not use the ``sd_card.img`` file generated in the ``package_output_hw`` directly. On the contrary, just format the SD card with a Windows OS utility like [SD Card Formatter (5.0.2 developed by Tuxera Inc)](https://www.sdcard.org/cms/wp-content/uploads/2020/11/SD_Card-Formatter_Press_Release.pdf) in FAT32 to a size of more than 2GB (at least) as illustrated in Figure 4.2.1-1. Then you can directly copy the files from the ``package_output_hw/sd_card`` folder, as illustrated in Figure 4.2.1-2. - -![figure1C](files/images/fat32_format_sdcard.png) - -*(Figure 4.2.1-1) FAT32 formatting to prepare the sd card for VCK190.* - -![figure2C](files/images/copy_files_sdcard.png) - -*(Figure 4.2.1-2) Copy the files on sd card to boot the VCK190.* - -### 4.3 Run on VCK190 Target Board - -At the prompt on UART terminal digit, insert the ``petalinux`` username and choose a password to login. For example, ``root``. You should see the following: - -```text -versal-rootfs-common-20231 login: petalinux -You are required to change your password immediately (administrator enforced). -New password: -Retype new password: - -versal-rootfs-common-20231:~$ sudo su - -We trust you have received the usual lecture from the local System -Administrator. It usually boils down to these three things: - #1) Respect the privacy of others. - #2) Think before you type. - #3) With great power comes great responsibility. -Password: -``` - -You can now launch the following commands: - -```shell -sudo su -mount /dev/mmcblk0p1 /mnt -cd /mnt -./xrt_host.exe ./*.xclbin -``` - -You should see something similar to this: - -```text -versal-rootfs-common-20231:/mnt# ./xrt_host.exe ./a.xclbin - -INFO: iterations = 0 -INFO: words SizeIn = 8192 -INFO: words SizeOut = 4096 -INFO: bytes SizeIn = 32768 -INFO: bytes SizeOut = 16384 -PASSED: auto my_device = xrt::device(0) -PASSED: auto xclbin_uuid = my_device.load_xclbin(./a.xclbin) -PASSED: auto in_0 = xrt::kernel(my_device, xclbin_uuid, "mm2s:{mm2s_1}") -. . . - -PASSED: my_graph.reset() -PASSED: my_graph.run(0) -INFO: Waiting for kernels to end... -PASSED: in_0_run.wait() -PASSED: out_0_run.wait() -PASSED: out_0_bo.sync(XCL_BO_SYNC_BO_FROM_DEVICE) -INFO: Veryfing output data vs. golden ones - -PASSED: ./xrt_host.exe - -versal-rootfs-common-20231:/mnt# -``` - - - -## References - -### [AI Engine Documentation](https://docs.amd.com/search/all?filters=Document_ID~%2522UG1076%2522_%2522UG1079%2522&content-lang=en-US) - -Contains sections on how to develop AI Engine graphs, how to use the AI Engine compiler and AI Engine simulation, and performance analysis. - -### Vitis DSP Libraries - -* [Vitis DSP Libraries Comprehensive Documentation](https://xilinx.github.io/Vitis_Libraries/dsp/2022.1/) - -### Xilinx Runtime (XRT) Architecture - -Below are the links to the XRT information used by this tutorial: - -* [XRT Documentation](https://xilinx.github.io/XRT/master/html/index.html): Explains general XRT API calls used in the PS Host Application. - -* [XRT Github Repo](https://github.com/Xilinx/XRT): Contains the XRT source code. - -* [XRT AI Engine API](https://github.com/Xilinx/XRT/blob/master/src/runtime_src/core/include/experimental/xrt_aie.h): Documents the AI Engine XRT API calls. - -* [XRT Release Notes](https://docs.amd.com/r/en-US/ug1451-xrt-release-notes) - -### Vitis Unified Software Development Platform 2022.1 Documentation - -Below are links to Vitis related information referenced in this tutorial: - -* [Vitis Application Acceleration Development Flow Documentation](https://docs.amd.com/r/en-US/ug1393-vitis-application-acceleration) - -* [Vitis Application Acceleration Development Flow Tutorials](https://github.com/Xilinx/Vitis-Tutorials) - -* [Vitis HLS](https://docs.amd.com/r/en-US/ug1399-vitis-hls) - -### Vitis Model Composer - -* [Vitis Model Composer examples](https://github.com/Xilinx/Vitis_Model_Composer) - -* [Vitis Model Composer Tutorial](https://docs.amd.com/r/en-US/ug1498-model-composer-sys-gen-tutorial/Locating-the-Tutorial-Design-Files) - -#### Support - -GitHub issues will be used for tracking requests and bugs. For questions, go to [support.xilinx.com](https://support.xilinx.com/). - +> **Note:** +> This tutorial has not been validated with the latest Vitis release. +> Previous versions are available in earlier branches. +> To access them, switch to an older branch (e.g., `2024.1`).
diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/Makefile b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/Makefile deleted file mode 100644 index 840a846f3d..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/Makefile +++ /dev/null @@ -1,134 +0,0 @@ -# -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -# -# Author: Daniele Bagni -# Date: 10 Sep 2024 - -SHELL := /bin/bash - -PHONY = help all clean -PHONY += kernels hw_link system host aie -PHONY += prepare_files build -.PHONY: $(PHONY) - - -# ========================================================= -# Source directories -# ========================================================= -RELATIVE_PROJECT_DIR := ./ -PROJECT_DIR := $(shell readlink -f $(RELATIVE_PROJECT_DIR)) - -#PROJECT_AIE_DIR := $(PROJECT_DIR)/make-flow/dsp_AIE -#PROJECT_PL_DIR := $(PROJECT_DIR)/make-flow/dsp_PL -#PROJECT_PS_DIR := $(PROJECT_DIR)/make-flow/dsp_PS -#PROJECT_HWLINK_DIR := $(PROJECT_DIR)/make-flow/dsp_system_hw_link -#PROJECT_SYSTEM_DIR := $(PROJECT_DIR)/make-flow/dsp_system - -EMBEDDED_PACKAGE_OUT = $(PROJECT_DIR)/make-flow/dsp_system/Hardware/package -EMBEDDED_EXEC_SCRIPT = $(PROJECT_DIR)/make-flow/dsp_system/Hardware/embedded_exec.sh -PACKAGE_FILES += $(EMBEDDED_EXEC_SCRIPT) -SD_FILES_WITH_PREFIX = $(foreach sd_file,$(PACKAGE_FILES),--package.sd_file $(sd_file)) - - -# ======================================================= -# global variables for this tutorial -# ======================================================= - -#BOARD=${XLNX_BOARD} -BOARD=vck190 - -#RELEASE=${XLNX_RELEASE} -RELEASE=2025.1 -#RELEASE=2023.2 - -#BASE_NUM=${XLNX_BASE_NUM} -BASE_NUM=202510_1 -#BASE_NUM=202320_1 - - -# Platform Selection... -VERSAL_VITIS_PLATFORM = xilinx_${BOARD}\_base_${BASE_NUM} -VITIS_PLATFORM_DIR = ${PLATFORM_REPO_PATHS}/${VERSAL_VITIS_PLATFORM} -export VITIS_PLATFORM_XPFM = ${VITIS_PLATFORM_DIR}/${VERSAL_VITIS_PLATFORM}.xpfm -# Set SysRoot, RootFS and Image -export VITIS_SYSROOTS = ${COMMON_IMAGE_VERSAL}/sysroots/cortexa72-cortexa53-amd-linux -export SDKTARGETSYSROOT = ${VITIS_SYSROOTS} -export KERNEL_IMAGE = ${COMMON_IMAGE_VERSAL}/Image -export ROOTFS = ${COMMON_IMAGE_VERSAL}/rootfs.ext4 -export XLNX_VERSAL = ${COMMON_IMAGE_VERSAL} -export PLATFORM = ${VITIS_PLATFORM_XPFM} - -# ========================================================= -# commands directories -# ========================================================= - -show_dir: - -@echo " " - -@echo starting folder PROJECT_DIR is: ${PROJECT_DIR} - -@echo " " - $(MAKE) -C $(PROJECT_DIR)/make-flow/dsp_AIE/Hardware show_dir - -@echo " " - $(MAKE) -C $(PROJECT_DIR)/make-flow/dsp_PL/Hardware show_dir - -@echo " " - $(MAKE) -C $(PROJECT_DIR)/make-flow/dsp_PS/Hardware show_dir - -@echo " " - $(MAKE) -C $(PROJECT_DIR)/make-flow/dsp_system_hw_link/Hardware show_dir - -@echo " " - $(MAKE) -C $(PROJECT_DIR)/make-flow/dsp_system/Hardware show_dir - -@echo " " - - - -run: all -sd_card: all - -all: - $(MAKE) prepare_files - $(MAKE) build - - -prepare_files: -# source $(PROJECT_DIR)/make-flow/local_var_setup.sh - cp -fr $(PROJECT_DIR)/src/ip/aie/data $(PROJECT_DIR)/make-flow/dsp_AIE/ - cp -fr $(PROJECT_DIR)/src/ip/aie/src $(PROJECT_DIR)/make-flow/dsp_AIE/ - cp -fr $(PROJECT_DIR)/src/ip/mm2s_aie/src $(PROJECT_DIR)/make-flow/dsp_PL/ - cp -f $(PROJECT_DIR)/src/ip/s2mm_aie/src/s2mm.cpp $(PROJECT_DIR)/make-flow/dsp_PL/src/ - cp -fr $(PROJECT_DIR)/src/ps_apps/aie_test/src $(PROJECT_DIR)/make-flow/dsp_PS/ - cp -f $(PROJECT_DIR)/src/vitis/src/system.cfg $(PROJECT_DIR)/make-flow/dsp_system_hw_link/ - - -build: - $(MAKE) kernels - $(MAKE) aie - $(MAKE) host - $(MAKE) hw_link - $(MAKE) system - -clean: - $(MAKE) -C $(PROJECT_DIR)/make-flow/dsp_system_hw_link/Hardware clean - $(MAKE) -C $(PROJECT_DIR)/make-flow/dsp_system/Hardware clean - $(MAKE) -C $(PROJECT_DIR)/make-flow/dsp_PS/Hardware clean - $(MAKE) -C $(PROJECT_DIR)/make-flow/dsp_PL/Hardware clean - $(MAKE) -C $(PROJECT_DIR)/make-flow/dsp_AIE/Hardware clean - rm -rf $(PROJECT_DIR)/make-flow/dsp_AIE/src - rm -rf $(PROJECT_DIR)/make-flow/dsp_AIE/data - rm -rf $(PROJECT_DIR)/make-flow/dsp_PL/src - rm -rf $(PROJECT_DIR)/make-flow/dsp_PS/src - - -aie: - $(MAKE) show_dir - $(MAKE) -C $(PROJECT_DIR)/make-flow/dsp_AIE/Hardware all - -kernels: - $(MAKE) -C $(PROJECT_DIR)/make-flow/dsp_PL/Hardware all - -hw_link: - $(MAKE) -C $(PROJECT_DIR)/make-flow/dsp_system_hw_link/Hardware all - -system: - $(MAKE) -C $(PROJECT_DIR)/make-flow/dsp_system/Hardware all - -host: - $(MAKE) -C $(PROJECT_DIR)/make-flow/dsp_PS/Hardware all diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/description.json b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/description.json deleted file mode 100644 index 4891f0704d..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/description.json +++ /dev/null @@ -1,37 +0,0 @@ -{ - "name": "Developer_Contributed-02-AIE_DSP_with_Makefile_and_GUI--make-flow", - "description": "02-AIE_DSP_with_Makefile_and_GUI--make-flow", - "gui": "false", - "flow": "versal", - - "platform_allowlist": [ "vck190"], - "platform_blocklist": [], - - "testinfo": { - "test_name": "CTB_02-AIE_DSP", - "jobs": [ - { - "max_memory_MB": 65536 - } - ], - "targets": [ - "vitis_hw_build", - "vitis_hw_run" - ], - "make_options": [ - "EMBEDDED_PACKAGE_OUT=./make-flow/dsp_system/Hardware/package", - "EMBEDDED_EXEC_SCRIPT=./embedded_exec.sh" - ], - "custom_build_target": { - "all": "all", - "hw": "sd_card" - }, - "custom_board_target": "run_test", - "tasks": { - "build": { - "pre_exec": ["./env_setup_versal.sh"] - } - } - - } -} diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/copy_files_sdcard.png b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/copy_files_sdcard.png deleted file mode 100644 index 3798691956..0000000000 Binary files a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/copy_files_sdcard.png and /dev/null differ diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fat32_format_sdcard.png b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fat32_format_sdcard.png deleted file mode 100644 index 213dd0b587..0000000000 Binary files a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fat32_format_sdcard.png and /dev/null differ diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_PS_libs.png b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_PS_libs.png deleted file mode 100644 index 1d59d2245b..0000000000 Binary files a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_PS_libs.png and /dev/null differ diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_aie.png b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_aie.png deleted file mode 100644 index 7bbf171167..0000000000 Binary files a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_aie.png and /dev/null differ diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_connect.png b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_connect.png deleted file mode 100644 index 95e8807bd8..0000000000 Binary files a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_connect.png and /dev/null differ diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_dialect.png b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_dialect.png deleted file mode 100644 index add14958c1..0000000000 Binary files a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_dialect.png and /dev/null differ diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_hls.png b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_hls.png deleted file mode 100644 index 3de148a483..0000000000 Binary files a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_hls.png and /dev/null differ diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_ps_inc.png b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_ps_inc.png deleted file mode 100644 index f4b82ea716..0000000000 Binary files a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_ps_inc.png and /dev/null differ diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_sys.png b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_sys.png deleted file mode 100644 index 12fd2fa81a..0000000000 Binary files a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_sys.png and /dev/null differ diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_sys_pl.png b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_sys_pl.png deleted file mode 100644 index 1ff6eb4e19..0000000000 Binary files a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/fir_sys_pl.png and /dev/null differ diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/thinplatf_prompt.png b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/thinplatf_prompt.png deleted file mode 100644 index e260c371ba..0000000000 Binary files a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/thinplatf_prompt.png and /dev/null differ diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/thinplatf_runtime.png b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/thinplatf_runtime.png deleted file mode 100644 index ba903aaff7..0000000000 Binary files a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/images/thinplatf_runtime.png and /dev/null differ diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/make-flow/dsp_AIE/Hardware/makefile b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/make-flow/dsp_AIE/Hardware/makefile deleted file mode 100644 index 4160938bcb..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/make-flow/dsp_AIE/Hardware/makefile +++ /dev/null @@ -1,57 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -# ========================================================= -# PROJECT and MODULE REPOS -# ========================================================= -#relative directory -RELATIVE_PROJECT_DIR := ../ - -#absolute directory -PROJECT_AIE_DIR := $(shell readlink -f $(RELATIVE_PROJECT_DIR)) - -show_dir: - -@echo from dsp_AIE, RELATIVE PROJECT DIR is: $(RELATIVE_PROJECT_DIR) - -@echo from dsp_AIE, CURRENT PROJECT DIR is: $(PROJECT_AIE_DIR) - - -# AIE compiler tools -#AIE_SRC_DIR = .. #DB: old -AIE_SRC_DIR = $(PROJECT_AIE_DIR) -AIE_CC = aiecompiler -#AIE_GRAPH_FILES = ../src/fir_graph.cpp #DB: old -AIE_GRAPH_FILES = $(PROJECT_AIE_DIR)/src/fir_graph.cpp -#AIE_OUT_DIR = ./Work #DB: old -AIE_OUT_DIR = $(PROJECT_AIE_DIR)/Hardware/Work -#AIE_DATA_DIR = ./data #DB: old -AIE_DATA_DIR = $(PROJECT_AIE_DIR)/data -#AIE_HW_DIR = ./hw #DB: never used? -#AIE_TRACE_DIR = ./Trace #DB: never used? -RM = rm -f -RMDIR = rm -rf - -# AIE compiler settings -AIE_FLAGS = -v -Xchess=main:darts.xargs=-nb \ - -include="$(XILINX_VITIS)/aietools/include" -include="$(XILINX_HLS)/include" \ - -include="$(DSPLIB_ROOT)/L1/src/aie" -include="$(DSPLIB_ROOT)/L1/include/aie" -include="$(DSPLIB_ROOT)/L2/include/aie" \ - -include="$(PROJECT_AIE_DIR)/data" -include="$(PROJECT_AIE_DIR)/src/graphs" -include="$(PROJECT_AIE_DIR)/src/" \ - -target=hw -platform=$(VITIS_PLATFORM_XPFM) -workdir=$(AIE_OUT_DIR) -# -# primary build targets -# - - -all: show_dir ./libadf.a - -./libadf.a: $(PROJECT_AIE_DIR)/src/fir_graph.cpp $(PROJECT_AIE_DIR)/src/graphs/fir_graph.h - -$(AIE_CC) $(AIE_FLAGS) $(AIE_GRAPH_FILES) - -clean: - $(RMDIR) $(AIE_OUT_DIR) $(AIE_DATA_DIR) .Xil ./aiesim* ./ess* ./profile* ../data/out* - find ./ -type f | grep -v makefile | xargs rm -Rf - -.PHONY: all clean - - -.PHONY: incremental -incremental: all diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/make-flow/dsp_PL/Hardware/makefile b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/make-flow/dsp_PL/Hardware/makefile deleted file mode 100644 index 198b0b2a0b..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/make-flow/dsp_PL/Hardware/makefile +++ /dev/null @@ -1,67 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -#relative directory -RELATIVE_PROJECT_DIR := ../ - -#absolute directory -PROJECT_PL_DIR := $(shell readlink -f $(RELATIVE_PROJECT_DIR)) - -show_dir: - -@echo from dsp_PL, RELATIVE PROJECT DIR is: $(RELATIVE_PROJECT_DIR) - -@echo from dsp_PL, CURRENT PROJECT DIR is: $(PROJECT_PL_DIR) - - -# compiler tools -VPP ?= ${XILINX_VITIS}/bin/v++ -RM = rm -f -RMDIR = rm -rf - -TARGET = hw -VPP_OPTS = --target $(TARGET) - -# -# Hw kernel files -# - -BUILD_SUBDIRS = $(PROJECT_PL_DIR)/Hardware/build -HW_KERNEL_OBJS += $(PROJECT_PL_DIR)/Hardware/build/mm2s.xo -SRC_KERNEL_OBJS += $(PROJECT_PL_DIR)/Hardware/build/mm2s.xo -HW_KERNEL_OBJS += $(PROJECT_PL_DIR)/Hardware/build/s2mm.xo -SRC_KERNEL_OBJS += $(PROJECT_PL_DIR)/Hardware/build/s2mm.xo - -ALL_MESSAGE_FILES = $(subst .xo,.o,.mdb,$(SRC_KERNEL_OBJS)) - -# -# primary build targets -# - -.PHONY: all clean show_dir - -all: show_dir $(HW_KERNEL_OBJS) - - -clean: - -$(RM) $(SRC_KERNEL_OBJS) $(ALL_MESSAGE_FILES) - -$(RMDIR) $(BUILD_SUBDIRS) - -$(RMDIR) .Xil *.log .crash* - -.PHONY: incremental -incremental: all - - -nothing: - -# -# Hw Kernels compile; -# - -$(PROJECT_PL_DIR)/Hardware/build/mm2s.xo: $(PROJECT_PL_DIR)/src/mm2s.cpp $(PROJECT_PL_DIR)/Hardware/mm2s-compile.cfg - -@mkdir -p $(@D) - -@$(RM) $@ - $(VPP) $(VPP_OPTS) --compile -I"$( binary_container_1.xsa.sh - $(VPP_LINKER) $(VPP_OPTS) --link --config $(PROJECT_HWLINK_DIR)/system.cfg --platform $(VITIS_PLATFORM_XPFM) --config $(PROJECT_HWLINK_DIR)/Hardware/binary_container_1-link.cfg -o"$@" $(BINARY_CONTAINER_1_OBJS) diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/make-flow/dsp_system_hw_link/system.cfg b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/make-flow/dsp_system_hw_link/system.cfg deleted file mode 100644 index 92b9c9e9bc..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/make-flow/dsp_system_hw_link/system.cfg +++ /dev/null @@ -1,7 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -[connectivity] -stream_connect=mm2s_1.s:ai_engine_0.DataIn1 -stream_connect=ai_engine_0.DataOut1:s2mm_1.s diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/run_all.sh b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/run_all.sh deleted file mode 100644 index 83d075e650..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/run_all.sh +++ /dev/null @@ -1,62 +0,0 @@ -#!/bin/bash - -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -# DO NOT CHANGE THE ORDER OF THE FOLLOWING COMMANDS! - -# global variable - -# where you are -#echo " " -#echo "STARTING DIR IS: " $PWD -#echo " " -arg=$PWD - -# https://stackoverflow.com/questions/25416991/bash-script-to-check-file-name-begins-with-expected-string -#grab last 5 characters of the variable with -last5=${arg:${#arg}-5} -echo $last5 -if [[ "${last5}" == "files" ]]; -then - - echo "you started from the right folder" $arg - - # clean everything - make clean - # clean file text formats - source ./scripts/dos2unix_all.sh - - # set the environment - #source ./scripts/desktop_sample_env_setup.sh - source ./scripts/guupServer_sample_env_setup.sh - - ############################################################################## - # prepare folders for the GUI-based flow - rm -rf gui-flow # remove previous content - mkdir ./gui-flow # make a new dir - mkdir ./gui-flow/fir-dsplib_prj # make another subdir - - ############################################################################## - # design with Makefile flow - # build everything - # make all - - ############################################################################## - # design with the THIN PLATFORM - - #prepare the files for makefile flow - source ./scripts/prepare_thin-plat_files.sh - - # build all by using prebuilt petalinux and xpfm - cd thin-plat - make all TARGET=hw - # return to <*/files> folder - cd .. - - -else - echo ${arg} - echo "IS A WRONG DIRECTORY: <*/files> must be the last folder from where to start!" - echo "EXITING" -fi diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/desktop_sample_env_setup.sh b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/desktop_sample_env_setup.sh deleted file mode 100644 index 7a495d93e2..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/desktop_sample_env_setup.sh +++ /dev/null @@ -1,142 +0,0 @@ -#!/bin/bash - -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -# Author: Daniele Bagni -# Date: 27 Feb 20223 - -###################################################################################### -# WARNING: THIS SCRIPT IS AN EXAMPLE FOR VERSAL ENV SETUP on A LINUX DESKTOP -###################################################################################### - - -# ======================================================= -# global variables for this tutorial -# ======================================================= -RELEASE=2025.1 -BOARD=vck190 -#BASE_NUM=202510_1 -BASE_NUM=202510_1 - -#TUTORIAL=AIE_DSP_with_Makefile_and_GUI_2023 -export TUTORIAL=02-AIE_DSP_with_Makefile_and_GUI - -#export WRK_DIR=/media/danieleb/DATA/${RELEASE}/Vitis-Tutorials-${RELEASE}/Developer_Contributed -export WRK_DIR=/media/danieleb/DATA/2025.1/Vitis-Tutorials_2025.1/Developer_Contributed - - -# ======================================================= -# Set Platform, Vitis and Petalinux repo -# ======================================================= -#export PLATFORM_REPO_PATHS = -export PLATFORM_REPO_PATHS=/media/danieleb/DATA/${RELEASE}/tools/Xilinx/Vitis/${RELEASE}/base_platforms - -#export XILINX_VITIS = -export XILINX_VITIS=/media/danieleb/DATA/${RELEASE}/tools/Xilinx/Vitis/${RELEASE} - -#export PETALINUX = -export PETALINUX=/tools/Xilinx/PetaLinux/${RELEASE} - -# ================================================================================== -# Set Versal Common Image repo (OR eventually install it into /tmp) -# This local foldr must not be a "NFS" hard disk drive, only "ext4" is supported -# ================================================================================== - -# export TMP DIRECTORY= -mkdir -p /tmp/danieleb -export TMPDIR=/tmp/danieleb - -# PETALINUX and VERSAL COMMON IMAGE -##export COMMON_IMAGE_VERSAL= -export COMMON_IMAGE_VERSAL=${HOME}/common/xilinx-versal-common-v${RELEASE} - -: ' # do it only once -## clean versal common image local folder content -rm -rf ${COMMON_IMAGE_VERSAL} -mkdir -p ${COMMON_IMAGE_VERSAL} - -## set the folder of Versal Common Image source files -#export VERSAL_COMMON_2023v1=${PETALINUX}/../../bsp/internal/xilinx-versal-common-v${RELEASE}/ #only for GUUP -export VERSAL_COMMON_2023v1=/opt/xilinx/common/xilinx-versal-common-v${RELEASE} -cd ${VERSAL_COMMON_2023v1} -## install Versal SDK on $HOME/common -./sdk.sh -y -p -d ${COMMON_IMAGE_VERSAL} -#copy the other files -cp bl31.elf boot.scr Image README.txt rootfs.ext4 rootfs.manifest u-boot.elf ${COMMON_IMAGE_VERSAL} - -##back to the wrk dir -cd ${WRK_DIR}/${TUTORIAL}/files/ -' - -# ==================================================== -# Source Versal Image, Vitis and Aietools -# ==================================================== -unset LD_LIBRARY_PATH -source ${COMMON_IMAGE_VERSAL}/environment-setup-cortexa72-cortexa53-amd-linux -# Run the below command to setup environment and CXX -source ${XILINX_VITIS}/settings64.sh - -# ======================================================== -# Set DSP Library for Vitis -# ======================================================== -#export DSPLIB_ROOT= -export DSPLIB_VITIS=/media/danieleb/DATA/${RELEASE}/Vitis_Libraries-main -export DSPLIB_ROOT=${DSPLIB_VITIS}/dsp - - -# ========================================================= -# Platform Selection... -# ========================================================= -#tgt_plat=xilinx_vck190_base_202220_1 -#export PLATFORM=$PLATFORM_REPO_PATHS/$tgt_plat/$tgt_plat\.xpfm - -export VERSAL_VITIS_PLATFORM=xilinx_${BOARD}\_base_${BASE_NUM} -export VITIS_PLATFORM_DIR=${PLATFORM_REPO_PATHS}/${VERSAL_VITIS_PLATFORM} -export VITIS_PLATFORM_XPFM=${VITIS_PLATFORM_DIR}/${VERSAL_VITIS_PLATFORM}.xpfm - -# ======================================================== -# Set SysRoot, RootFS and Image -# ======================================================== -export VITIS_SYSROOTS=${COMMON_IMAGE_VERSAL}/sysroots/cortexa72-cortexa53-amd-linux -export SDKTARGETSYSROOT=${VITIS_SYSROOTS} -export KERNEL_IMAGE=${COMMON_IMAGE_VERSAL}/Image -export ROOTFS=${COMMON_IMAGE_VERSAL}/rootfs.ext4 - -# ======================================================== -# for compatibility with official Vitis Tutorials -# ======================================================== -export XLNX_VERSAL=${COMMON_IMAGE_VERSAL} -export PLATFORM=${VITIS_PLATFORM_XPFM} - - -# ======================================================== -# check env variables -# ======================================================== -echo " " -echo "Vitis/Petalinux GUUP Environmental variables" -echo " " -echo "LD_LIBRARY_PATH " $LD_LIBRARY_PATH -echo "XILINX_VITIS " $XILINX_VITIS -echo "BSP_DIR " $BSP_DIR -#echo "PETALINUX_VER " $PETALINUX_VER -echo "PLATFORM_REPO_PATHS " $PLATFORM_REPO_PATHS -echo "XILINX_XRT " $XILINX_XRT -echo "XILINX_VIVADO " $XILINX_VIVADO -#echo "XILINXD_LICENSE_FILE " $XILINXD_LICENSE_FILE -echo "XILINX_HLS " $XILINX_HLS -#echo "XSCT_TOOLCHAIN" $XSCT_TOOLCHAIN -#echo "XDG_DATA_DIRS " $XDG_DATA_DIRS -#echo "GUUP_ROOT " $GUUP_ROOT -echo "SHELL " $SHELL -#echo "LM_LICENSE_FILE " $LM_LICENSE_FILE -#echo "PYTHONPATH " $PYTHONPATH -#echo "PETALINUX_MAJOR_VER " $PETALINUX_MAJOR_VER -echo "PETALINUX " $PETALINUX -echo "SDKTARGETSYSROOT " ${VITIS_SYSROOTS} -echo "VERSAL_COMMON_2023v1 " ${VERSAL_COMMOM_2023v1} -echo "COMMON_IMAGE_VERSAL " ${COMMON_IMAGE_VERSAL} -echo "KERNEL_IMAGE " ${KERNEL_IMAGE} -echo "ROOTFS " ${ROOTFS} -echo "VITIS_PLATFORM_XPFM " ${VITIS_PLATFORM_XPFM} -#echo "PATH " ${PATH} diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/dos2unix_all.sh b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/dos2unix_all.sh deleted file mode 100644 index 5c22105c41..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/dos2unix_all.sh +++ /dev/null @@ -1,16 +0,0 @@ -#!/bin/bash - -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -# Dos2Unix conversion just to avoid any trouble with file formats -for file in $(find . -name "*.sh" ); do dos2unix ${file}; done -for file in $(find . -name "*.tcl"); do dos2unix ${file}; done -for file in $(find . -name "*.h" ); do dos2unix ${file}; done -for file in $(find . -name "config" ); do dos2unix ${file}; done -for file in $(find . -name "*.c*" ); do dos2unix ${file}; done -for file in $(find . -name "*.m" ); do dos2unix ${file}; done -for file in $(find . -name "*.dat" ); do dos2unix ${file}; done -for file in $(find . -name "*.txt" ); do dos2unix ${file}; done -for file in $(find . -name "?ake*" ); do dos2unix ${file}; done diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/env_setup.sh b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/env_setup.sh deleted file mode 100644 index 0ca865fba2..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/env_setup.sh +++ /dev/null @@ -1,34 +0,0 @@ -#!/bin/bash - -# Report current shell -current_shell=$(echo $0) -echo "[env_setup.sh] Current shell: $current_shell" -if [ "$current_shell" = "-bash" ]; then - # Print Bash version - echo "[env_setup.sh] Bash version: $BASH_VERSION" -fi - -# Vitis Libraries -#export DSPLIB_VITIS=/proj/xtools/xilinx_central_repo/Vitis_Libraries -# Point to the Vitis Libraries HEAD -# DB: commented by me -#export DSPLIB_VITIS=/proj/xtools/xilinx_central_repo/FaaSApps_next -#export DSPLIB_ROOT=${DSPLIB_VITIS}/dsp - -# GHE Repo URL for CI -export DEVICE_TREE_REPO=https://gitenterprise.xilinx.com/Linux/device-tree-xlnx.git -export ATF_REPO=https://gitenterprise.xilinx.com/Linux/arm-trusted-firmware.git -export UBOOT_REPO=https://github.com/Xilinx/u-boot-xlnx -#REPO for Embd_Sw/F/01 -export ATF_CHECKOUT=master -export UBOOT_CHECKOUT=master - -# Add CMake to PATH -export PATH=${XILINX_VITIS}/tps/lnx64/cmake-3.3.2/bin:$PATH - -# Add git to PATH -export PATH=${XILINX_VITIS}/tps/lnx64/git-2.41.0/bin:$PATH - -# Update Perl Version -source perl.sh - diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/env_setup_petalinux.sh b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/env_setup_petalinux.sh deleted file mode 100644 index aabd065d84..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/env_setup_petalinux.sh +++ /dev/null @@ -1,29 +0,0 @@ -#!/bin/bash -# ------------------------- -# Setup common environments -# - Vitis Library Path -# ------------------------- -#source env_setup.sh - - - -# ------------------------------- -# Environment Setup for PetaLinux -# ------------------------------- - -# A tutorial either uses the pre-built SDK toolchain or the PetaLinux to build things from scratch. - -export BSP_DIR=/proj/petalinux/${XLNX_RELEASE}/petalinux-v${XLNX_RELEASE}_daily_latest/bsp/release -export PETALINUX=/proj/petalinux/${XLNX_RELEASE}/petalinux-v${XLNX_RELEASE}_daily_latest/tool/petalinux-v${XLNX_RELEASE}-final - - -source $PETALINUX/settings.sh - - -# ------------------------- -# The following Env Var are provided by Regression Framework. No need to setup manually -# - XILINX_VITIS -# - XILINX_VIVADO -# - XILINX_HLS -# - PLATFORM_REPO_PATHS -# ------------------------- diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/env_setup_petalinux_versal.sh b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/env_setup_petalinux_versal.sh deleted file mode 100644 index a36fc82486..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/env_setup_petalinux_versal.sh +++ /dev/null @@ -1,42 +0,0 @@ -#!/bin/bash -#!/bin/bash -# ------------------------- -# Use PetaLinux toolset -# Setup common image path COMMON_IMAGE_VERSAL -# ------------------------- - - - - - -# ------------------------- -# Setup common environments -# - Vitis Library Path -# ------------------------- -source env_setup.sh - - - -# ------------------------------- -# Environment Setup for PetaLinux -# ------------------------------- - -# A tutorial either uses the pre-built SDK toolchain or the PetaLinux to build things from scratch. - -source env_setup_petalinux.sh - -# ------------------------------- -# Versal Common Image Path -# ------------------------------- - -export COMMON_IMAGE_VERSAL=/proj/xbb/xrt-embedded/${XLNX_RELEASE}/sw/latest/sysroot/versal/xilinx-versal-common-v${XLNX_RELEASE} -echo Setting Up COMMON_IMAGE_VERSAL=$COMMON_IMAGE_VERSAL - - -# ------------------------- -# The following Env Var are provided by Regression Framework. No need to setup manually -# - XILINX_VITIS -# - XILINX_VIVADO -# - XILINX_HLS -# - PLATFORM_REPO_PATHS -# ------------------------- diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/env_setup_versal.sh b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/env_setup_versal.sh deleted file mode 100644 index c2010ad911..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/env_setup_versal.sh +++ /dev/null @@ -1,24 +0,0 @@ -#!/bin/bash -# ------------------------- -# Setup common environments -# - Vitis Library Path -# ------------------------- -source env_setup.sh - - -#export COMMON_IMAGE_VERSAL=/proj/xbb/xrt-embedded/2023.1/sw/latest/sysroot/versal/xilinx-versal-common-v2023.1 #DB: this works only on USA servers -export COMMON_IMAGE_VERSAL=/home/danieleb/common/xilinx-versal-common-v${XLNX_RELEASE} -echo Setting Up COMMON_IMAGE_VERSAL=$COMMON_IMAGE_VERSAL #DB: this works also for EMEA servers - -# Run Environment setup to get SDKTARGETSYSROOT and CXX -unset LD_LIBRARY_PATH -source ${COMMON_IMAGE_VERSAL}/environment-setup-cortexa72-cortexa53-amd-linux - - -# ------------------------- -# The following Env Var are provided by Regression Framework. No need to setup manually -# - XILINX_VITIS -# - XILINX_VIVADO -# - XILINX_HLS -# - PLATFORM_REPO_PATHS -# ------------------------- diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/guupServer_sample_env_setup.sh b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/guupServer_sample_env_setup.sh deleted file mode 100644 index 3b70b00ea2..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/guupServer_sample_env_setup.sh +++ /dev/null @@ -1,138 +0,0 @@ -#!/bin/bash - -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -# Author: Daniele Bagni -# Date: 05 Sep 2024 - -###################################################################################### -# WARNING: THIS SCRIPT IS VALID ONLY FOR VCK190 on AMD/XILINX GUUP (LINUX) SERVERS -###################################################################################### - -# ======================================================= -# GUUP Environment Setup: -# set Platform, Vitis and Petalinux repo -# ======================================================= -#ts 2023.1_released -petalinux petalinux-v2023.1_daily_latest -#ts 2023.2_released -petalinux petalinux-v2023.2_daily_latest -#ts 2025.1_released -petalinux petalinux-v2025.1_daily_latest - -# ======================================================= -# global variables for this tutorial -# ======================================================= -export XLNX_BOARD=vck190 - -#export XLNX_RELEASE=2023.2 -#export XLNX_BASE_NUM=202320_1 -export XLNX_RELEASE=2025.1 -export XLNX_BASE_NUM=202510_1 - -export TUTORIAL=02-AIE_DSP_with_Makefile_and_GUI -export GUUP_DIR=/group/xirguup -#export WRK_DIR=${GUUP_DIR}/danieleb/ide${XLNX_RELEASE}/Developer_Contributed -export WRK_DIR=${GUUP_DIR}/danieleb/ide2025.1/Vitis-Tutorials/Developer_Contributed - -# ======================================================= -# to emulate SPRITE regression env in GUUP Servers -# ======================================================= -cd ${WRK_DIR}/${TUTORIAL}/files/scripts -echo " " -echo ${PWD} -echo " " -source ./env_setup_versal.sh -#back to the wrk dir -cd ${WRK_DIR}/${TUTORIAL}/files -echo " " -echo ${PWD} -echo " " - -#================================================================================== -# Set Versal Common Image repo (OR eventually install it into /tmp) -# This local foldr must not be a "NFS" hard disk drive, only "ext4" is supported -# ================================================================================== - -# export TMP DIRECTORY= -mkdir -p /tmp/danieleb -export TMPDIR=/tmp/danieleb - -# PETALINUX and VERSAL COMMON IMAGE -export COMMON_IMAGE_VERSAL=${HOME}/common/xilinx-versal-common-v${XLNX_RELEASE} - -: ' -# do it only once -# clean versal folder content -rm -rf ${COMMON_IMAGE_VERSAL} -# install SDK -export VERSAL_COMMON_2023v1=$PETALINUX/../../bsp/internal/xilinx-versal-common-v${XLNX_RELEASE}/ -cd ${VERSAL_COMMON_2023v1} -bash ./sdk.sh -y -p -d ${COMMON_IMAGE_VERSAL} -cp bl31.elf boot.scr Image README.txt rootfs.ext4 rootfs.manifest u-boot.elf ${COMMON_IMAGE_VERSAL}/ -' - -# ======================================================== -# Set DSP Library for Vitis -# ======================================================== -## already set in "env_setup.sh" but not yet available in EMEA servers -#export DSPLIB_ROOT= - -export DSPLIB_VITIS=/group/xirguup/danieleb/ide${XLNX_RELEASE}/Vitis_Libraries -export DSPLIB_ROOT=${DSPLIB_VITIS}/dsp -#export DSPLIB_VITIS=/group/xirguup/danieleb/ide2023.2/Vitis_Libraries -#export DSPLIB_ROOT=${DSPLIB_VITIS}/xf_dsp-next - - - -# ========================================================= -# Platform Selection... -# ========================================================= -export VERSAL_VITIS_PLATFORM=xilinx_${XLNX_BOARD}\_base_${XLNX_BASE_NUM} -export VITIS_PLATFORM_DIR=${PLATFORM_REPO_PATHS}/${VERSAL_VITIS_PLATFORM} -export VITIS_PLATFORM_XPFM=${VITIS_PLATFORM_DIR}/${VERSAL_VITIS_PLATFORM}.xpfm - -# ======================================================== -# Set SysRoot, RootFS and Image -# ======================================================== -export VITIS_SYSROOTS=${COMMON_IMAGE_VERSAL}/sysroots/cortexa72-cortexa53-amd-linux -export SDKTARGETSYSROOT=${VITIS_SYSROOTS} -export KERNEL_IMAGE=${COMMON_IMAGE_VERSAL}/Image -export ROOTFS=${COMMON_IMAGE_VERSAL}/rootfs.ext4 - -# ======================================================== -# for compatibility with official Vitis Tutorials -# ======================================================== -export XLNX_VERSAL=${COMMON_IMAGE_VERSAL} -export PLATFORM=${VITIS_PLATFORM_XPFM} - -# ======================================================== -# check env variables -# ======================================================== -echo " " -echo "Vitis/Petalinux GUUP Environmental variables" -echo " " -echo "LD_LIBRARY_PATH " $LD_LIBRARY_PATH -echo "XILINX_VITIS " $XILINX_VITIS -echo "BSP_DIR " $BSP_DIR -#echo "PETALINUX_VER " $PETALINUX_VER -echo "PLATFORM_REPO_PATHS " $PLATFORM_REPO_PATHS -echo "XILINX_XRT " $XILINX_XRT -echo "XILINX_VIVADO " $XILINX_VIVADO -#echo "XILINXD_LICENSE_FILE " $XILINXD_LICENSE_FILE -echo "XILINX_HLS " $XILINX_HLS -#echo "XSCT_TOOLCHAIN" $XSCT_TOOLCHAIN -#echo "XDG_DATA_DIRS " $XDG_DATA_DIRS -#echo "GUUP_ROOT " $GUUP_ROOT -echo "SHELL " $SHELL -#echo "LM_LICENSE_FILE " $LM_LICENSE_FILE -#echo "PYTHONPATH " $PYTHONPATH -#echo "PETALINUX_MAJOR_VER " $PETALINUX_MAJOR_VER -echo "PETALINUX " $PETALINUX -echo "SDKTARGETSYSROOT " ${VITIS_SYSROOTS} -echo "VERSAL_COMMON_2023v1 " ${VERSAL_COMMOM_2023v1} -echo "COMMON_IMAGE_VERSAL " ${COMMON_IMAGE_VERSAL} -echo "VITIS_PLATFORM_XPFM " ${VITIS_PLATFORM_XPFM} -echo "KERNEL_IMAGE " ${KERNEL_IMAGE} -echo "ROOTFS " ${ROOTFS} -echo "PLATFORM_REPO_PATHS " ${PLATFORM_REPO_PATHS} -#echo "PATH " ${PATH} -echo "DSPLIB_ROOT " ${DSPLIB_ROOT} diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/perl.sh b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/perl.sh deleted file mode 100644 index c3d929f5bb..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/perl.sh +++ /dev/null @@ -1,10 +0,0 @@ -#!/bin/bash - -################################################################## -echo "Override perl related env variables" -PERL_5_24_1=/tools/batonroot/rodin/devkits/lnx64/perl-5.24.1 -export PERL_HOME=${PERL_5_24_1} -export PATH=${PERL_5_24_1}/bin:${PATH} - -echo "Updated PERL_HOME: ${PERL_HOME}" -echo "Updated PATH: ${PATH}" diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/prepare_thin-plat_files.sh b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/prepare_thin-plat_files.sh deleted file mode 100644 index 1d16b65dac..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/scripts/prepare_thin-plat_files.sh +++ /dev/null @@ -1,49 +0,0 @@ -#!/bin/bash - -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -# remove previous folder without deleting it -mv ${WRK_DIR}/${TUTORIAL}/files/thin-plat ${WRK_DIR}/${TUTORIAL}/files/tmp -# copy original Thin Platform repo and rename it -cp -r ${WRK_DIR}/01-Versal_Custom_Thin_Platform_Extensible_System ${WRK_DIR}/${TUTORIAL}/files/ -mv ${WRK_DIR}/${TUTORIAL}/files/01-Versal_Custom_Thin_Platform_Extensible_System ${WRK_DIR}/${TUTORIAL}/files/thin-plat -# clean just to be shure -make clean -C ${WRK_DIR}/${TUTORIAL}/files/thin-plat - -# remove folders that are not needed -cd ${WRK_DIR}/${TUTORIAL}/files/thin-plat -rm -rf vitis/ip/vadd* vitis/ip/counter vitis/ip/subtractor -rm -rf ps_apps/linux/vadd* -rm -rf documentation -# rename folders -mv ps_apps/linux/aie_dly_test ps_apps/linux/aie_test -mv vitis/ip/mm2s_vadd_s vitis/ip/mm2s_aie -mv vitis/ip/s2mm_vadd_s vitis/ip/s2mm_aie - -# remove files that are not needed -cd ${WRK_DIR}/${TUTORIAL}/files/ -rm -f ./thin-plat/README* -rm -f ./thin-plat/*.json -rm -f ./thin-plat/vitis/ip/aie/data/* -rm -f ./thin-plat/vitis/ip/aie/src/* -rm -rf ./thin-plat/vitis/ip/aie/vitis*wrapper* -rm -rf ./thin-plat/vitis/ip/aie/vck190*wrapper* -rm -rf ./thin-plat/vitis/ip/aie/src/graphs/* -rm -rf ./thin-plat/vitis/ip/aie/src/kernels/* -rm -f ./thin-plat/vitis/ip/mm2s_aie/src/* -rm -f ./thin-plat/vitis/ip/s2mm_aie/src/* -rm -f ./thin-plat/ps_apps/linux/aie_test/src/* -rm -f ./thin-plat/vitis/src/system.cfg - -# copy the source code files -cp ./src/ip/aie/data/* ./thin-plat/vitis/ip/aie/data/ -cp ./src/ip/aie/src/* ./thin-plat/vitis/ip/aie/src/ -cp ./src/ip/aie/src/graphs/* ./thin-plat/vitis/ip/aie/src/graphs/ -cp ./src/ip/mm2s_aie/src/* ./thin-plat/vitis/ip/mm2s_aie/src/ -cp ./src/ip/s2mm_aie/src/* ./thin-plat/vitis/ip/s2mm_aie/src/ -cp ./src/ps_apps/aie_test/src/* ./thin-plat/ps_apps/linux/aie_test/src/ -cp ./src/vitis/src/system.cfg ./thin-plat/vitis/src/system.cfg - -# copy the modified makefiles -cp -rf ./src/thin-plat/* ./thin-plat/ diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ip/aie/data/golden_2col.txt b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ip/aie/data/golden_2col.txt deleted file mode 100644 index 293506368b..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ip/aie/data/golden_2col.txt +++ /dev/null @@ -1,4096 +0,0 @@ -126 450 --1613 -975 -4149 -9673 -8363 -8704 --8622 -6170 --13008 5317 --1192 -10116 --582 -12624 -916 -1407 -5510 13283 --8939 -8363 -1015 -8789 -3450 6493 -7153 196 -8806 5149 -7940 2513 -5513 -4188 -10820 2461 -4557 4302 --8028 297 -5947 3053 -10012 3034 -609 5584 --10914 -5842 --4279 -3815 -2474 -2697 -1122 -5173 -4727 -3252 -3391 7058 --2163 7085 --8312 3453 --602 5024 -2662 6059 --8539 -1687 -1188 -1216 -2487 -2432 --4051 1696 -9195 2308 -4180 -370 -4421 -4835 --5591 7636 --9464 6325 --8368 -3950 -6787 1464 --4675 6689 --1248 1126 --13143 -1630 --9840 13569 -7260 4052 -10688 1259 -14676 -3329 --2758 -10182 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@@ -% Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -% SPDX-License-Identifier: MIT - -%% -I4c = load("input_128b.txt") -I2c = zeros(2048*4, 2); -%% -I2c(1:4:end, 1) = I4c(:, 1); -I2c(1:4:end, 2) = I4c(:, 2); -I2c(2:4:end, 1) = I4c(:, 3); -I2c(2:4:end, 2) = I4c(:, 4); -I2c(3:4:end, 1) = I4c(:, 5); -I2c(3:4:end, 2) = I4c(:, 6); -I2c(4:4:end, 1) = I4c(:, 7); -I2c(4:4:end, 2) = I4c(:, 8); -%% -fid = fopen("input_2col.txt", "w"); -for i= 1 : 8192 - fprintf(fid, "%7d %7d\n", I2c(i, 1), I2c(i, 2)); -end -fclose(fid) -%% diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ip/aie/src/fir_graph.cpp b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ip/aie/src/fir_graph.cpp deleted file mode 100644 index 587bf3c83b..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ip/aie/src/fir_graph.cpp +++ /dev/null @@ -1,27 +0,0 @@ -// Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -// SPDX-License-Identifier: MIT - - -#include "fir_graph.h" - -/* -adf::PLIO *pl128_in = new adf::PLIO("DataIn1", adf::plio_128_bits,"data/input_128b.txt", 250); -adf::PLIO *pl128_out = new adf::PLIO("DataOut1", adf::plio_128_bits,"data/output_128b.txt", 250); -simulation::platform<1,1> platform(pl128_in, pl128_out); -*/ - -TopGraph filter ; - -/* -connect<> net0(platform.src[0], filter.in); -connect<> net1(filter.out, platform.sink[0]); -*/ - -#if defined(__AIESIM__) // || defined(__NEW_X86Sim__) -int main(void) { - filter.init() ; - filter.run(ITER_CNT); //N_ITERATIONS); - filter.end() ; - return 0 ; -} -#endif diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ip/aie/src/graphs/fir_graph.h b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ip/aie/src/graphs/fir_graph.h deleted file mode 100644 index c6d116c870..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ip/aie/src/graphs/fir_graph.h +++ /dev/null @@ -1,65 +0,0 @@ -// Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -// SPDX-License-Identifier: MIT - -#ifndef __GRAPH_H__ -#define __GRAPH_H__ - -#include //DB - -//#pragma once - -//#include "fir_aie_defines.h" -#include "system_settings.h" //DB: this was commented in the Makefile flow -//#include "system_settings_comm.h" - -using namespace adf; -namespace dsplib = xf::dsp::aie; - -class FirGraph: public graph -{ -private: - // Channel Filter coefficients - std::vector FIR_TAP_COEFS = std::vector{-1124, -2408, 4655, 14455, 14455, 4655, -2408, -1124}; - //std::vector FIR_TAP_COEFS = std::vector{1, 0, 0, 0, 0, 0, 0, 0}; - - //FIR Graph class - //dsplib::fir::sr_sym::fir_sr_sym_graph chan_FIR; - dsplib::fir::decimate_asym::fir_decimate_asym_graph chan_FIR; - -public: - port in; - port out; - - // Constructor - with FIR graph class initialization - FirGraph():chan_FIR(FIR_TAP_COEFS) { - - // Margin gets automatically added within the FIR graph class. - // Margin equals to FIR length rounded up to nearest multiple of 32 Bytes. - connect<>(in, chan_FIR.in[0]); - connect<>(chan_FIR.out[0], out); - - //location(chan_FIR.m_firKernels[0]) = tile(18,0); - - }; -}; - - -class TopGraph : public graph { - - public: - adf::input_plio in; - adf::output_plio out; - - FirGraph F; - - TopGraph() - { - in = adf::input_plio::create( "DataIn1", adf::plio_128_bits,"data/input_128b.txt", 250); - out = adf::output_plio::create("DataOut1", adf::plio_128_bits,"data/output_128b.txt", 250); - connect<> (in.out[0],F.in); - connect<> (F.out, out.in[0]); - }; -}; - - -#endif diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ip/aie/src/graphs/system_settings.h b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ip/aie/src/graphs/system_settings.h deleted file mode 100644 index 624c620713..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ip/aie/src/graphs/system_settings.h +++ /dev/null @@ -1,35 +0,0 @@ -// Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -// SPDX-License-Identifier: MIT - -//DB: daniele.bagni@amd.com -//DB: 3 August 2022 - -#pragma once - -#include -//#include "fir_sr_sym_graph.hpp" -#include "fir_decimate_asym_graph.hpp" - -// Filter parameters -#define DATA_TYPE cint16 -#define COEFF_TYPE int16 - -#define FIR_LEN_CHAN 8 -#define DECIMATE_FACTOR 2 -#define SHIFT_CHAN 15//0 for ramp -#define ROUND_MODE_CHAN 0 -#define AIES_CHAN 1 - -#define WINDOW_SIZE 1024 - -// Simulation parameters -#define NUM_ITER 8 -//DB: a bit redundant but just in case to be sure -#define ITER_CNT (NUM_ITER) -#define N_ITERATIONS (NUM_ITER) - -#define TP_CASC_LEN 1 -#define TP_USE_COEFF_RELOAD 0 -#define TP_NUM_OUTPUTS 1 -#define TP_DUAL_IP 0 -#define TP_API 0 diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ps_apps/aie_test/src/golden.h b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ps_apps/aie_test/src/golden.h deleted file mode 100644 index af2488f55a..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ps_apps/aie_test/src/golden.h +++ /dev/null @@ -1,9226 +0,0 @@ -// Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -// SPDX-License-Identifier: MIT - -#pragma once - -short int golden[] = { - 126 , - 450 , - -1613 , - -975 , - 4149 , - -9673 , - 8363 , - -8704 , - -8622 , - -6170 , - -13008 , - 5317 , - -1192 , - -10116 , - -582 , - -12624 , - 916 , - -1407 , - 5510 , - 13283 , - -8939 , - -8363 , - 1015 , - -8789 , - 3450 , - 6493 , - 7153 , - 196 , - 8806 , - 5149 , - 7940 , - 2513 , - 5513 , - -4188 , - 10820 , - 2461 , - 4557 , - 4302 , - -8028 , - 297 , - 5947 , - 3053 , - 10012 , - 3034 , - 609 , - 5584 , - -10914 , - -5842 , - -4279 , - -3815 , - 2474 , - -2697 , - 1122 , - -5173 , - 4727 , - -3252 , - 3391 , - 7058 , - -2163 , - 7085 , - -8312 , - 3453 , - -602 , - 5024 , - 2662 , - 6059 , - -8539 , - -1687 , - 1188 , - -1216 , - 2487 , - -2432 , - -4051 , - 1696 , - 9195 , - 2308 , - 4180 , - -370 , - 4421 , - -4835 , - -5591 , - 7636 , - -9464 , - 6325 , - -8368 , - -3950 , - 6787 , - 1464 , - -4675 , - 6689 , - -1248 , - 1126 , - -13143 , - -1630 , - -9840 , - 13569 , - 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-7944 , - -10796 , - 5678 , - 4525 , - 8808 , - 11238 , - -7793 , - 1187 , - 12121 , - -177 , - -2805 , - -14950 , - -5277 , - -532 , - -8628 , - 1911 , - 7285 , - 2042 , - 9487 , - -4489 , - -7891 , - 4398 , - 5018 , - 6658 , - -5924 , - -102 , - 7100 , - -1930 , - 12897 , - -7969 , - 4819 , - 2355 , - 2234 , - -6502 , - 571 , - -4274 , - -9374 , - 9198 , - -750 , - 8950 , - 2379 , - 4621 , - 12036 , - 6782 , - -3453 , - -11546 , - 1947 , - -3118 , - 309 , - 138 , - -11376 , - 5540 , - -6507 , - 1276 , - 8697 , - -2148 , - 5163 , - 3733 , - -11562 , - -4079 , - 5039 , - 2416 , - 8072 , - 5173 , - 11859 , - 1364 , - 2513 , - -3586 , - -3007 , - -2680 , - 3844 , - -4731 , - 402 , - -7854 , - -4679 , - 4179 , - 10422 , - 3355 , - 11194 , - 3949 , - 9904 , - 8022 , - -9066 , - 11504 , - 3462 , - 1065 , - -7418 , - 1434 , - 3218 , - -3290 , - -5797 , - 3970 , - 3985 , - -4131 , - -8018 , - -14081 , - 5467 , - -3654 , - -3690 , - 14119 , - -3376 , - -2442 , - 8884 , - 1009 , - 2823 , - -4468 , - -6357 , - -3643 , - -4723 , - -3576 , - -1656 , - -13955 , - -2092 , - -9594 , - -5834 , - -1218 , - 3901 , - -5389 , - -8796 , - 10431 , - -1487 , - -2166 , - 12115 , - -13766 , - 2423 , - 3255 , - 8986 , - -3248 , - 5717 , - 2647 , - -5705 , - -165 , - -2055 , - 16471 , - -4868 , - 11998 , - 2807 , - -5449 , - 8214 , - -3777 , - 9914 , - 6811 , - -5873 , - -1143 , - -344 , - -3554 , - -2257 , - -2444 , - -3553 , - -473 , - 5821 , - 8478 , - -5746 , - 8351 , - -292 , - -2256 , - -9762 , - 7264 , - -4005 , - 10218 , - 485 , - -1191 , - -5534 , - -4206 , - -6288 , - -13180 , - -2576 , - 6390 , - -4104 , - -2783 , - -1570 , - -14138 , - 1288 , - 2682 , - 1762 , - -1467 , - -8163 , - -11447 , - -576 , - 4148 , - -9900 , - 4122 , - 201 , - -2154 , - -14418 , - -3794 , - 8346 , - 4252 , - 855 , - -2629 , - -12444 , - -7572 , - -9508 , - 4554 , - -5309 , - 8913 , - 2530 , - -1162 , - 11602 , - -9049 , - -3317 , - -11556 , - -10226 , - 4201 , - 4222 , - -5070 , - 10970 , - 49 , - -8610 , - 1733 , - -4437 , - 9108 , - 1072 , - -1623 , - 3546 , - -5303 , - -4423 , - -5879 , - -3487 , - 1062 , - -2756 , - -7522 , - -7069 , - -406 , - 3909 , - 6997 , - 12887 , - 7435 , - 1973 , - -9276 , - -2969 , - 5237 , - 5358 , - 15214 , - 8673 , - -1251 , - -8126 , - 4072 , - 5443 , - 2919 , - -2133 , - 9719 , - -5520 , - -1336 , - -3304 , - -2343 , - 4500 , - 5992 , - 4078 , - 6636 , - 10315 , - -7053 , - -5183 , - -3019 , - 1649 , - 1601 , - 16888 , - 3030 , - 1983 , - 9964 , - -10807 , - 2000 , - -2806 , - -1988 , - -3122 , - 12539 , - 3457 , - 9542 , - 13624 , - -3004 , - 2399 , - 988 , - -4596 , - 151 , - 7401 , - 8640 , - -2869 , - 7832 , - 1906 , - -7478 , - 12669 , - -398 , - 175 , - 6586 , - -152 , - -6670 , - 3066 , - -7181 , - -8650 , - -9653 , - 705 , - -1428 , - -3189 , - 6120 , - 1614 , - 4765 , - 13946 , - -4742 , - 2730 , - 8902 , - 4329 , - 6696 , - 1416 , - -10954 , - 666 , - -630 , - 64 , - 4043 , - -909 , - -5357 , - 6493 , - -2710 , - -400 , - 7531 , - -120 , - 3924 , - -3362 , - 11473 , - -4936 , - -3102 , - 4168 , - -5174 , - -462 , - 10342 , - 2870 , - 3659 , - -12879 , - 4094 , - -6221 , - -2549 , - 4888 , - 5370 , - 1954 , - 4618 , - -1009 , - 2607 , - 1709 , - -2087 , - 4621 , - -2267 , - 3350 , - -3817 , - -9633 , - -6846 , - -948 , - 7974 , - 6290 , - 1890 , - 2617 , - 7138 , - 748 , - 10110 , - 219 , - -10819 , - 4411 , - -1735 , - -308 , - -2190 , - -4883 , - -7555 , - -5791 , - -2846 -}; -/* Ramp golden -short int golden[] = { - 0, 0, 2, 2, 4, 4, 6, 6, - 8, 8, 10, 10, 12, 12, 14, 14, - 16, 16, 18, 18, 20, 20, 22, 22, - 24, 24, 26, 26, 28, 28, 30, 30, - 32, 32, 34, 34, 36, 36, 38, 38, - 40, 40, 42, 42, 44, 44, 46, 46, - 48, 48, 50, 50, 52, 52, 54, 54, - 56, 56, 58, 58, 60, 60, 62, 62, - 64, 64, 66, 66, 68, 68, 70, 70, - 72, 72, 74, 74, 76, 76, 78, 78, - 80, 80, 82, 82, 84, 84, 86, 86, - 88, 88, 90, 90, 92, 92, 94, 94, - 96, 96, 98, 98, 100, 100, 102, 102, - 104, 104, 106, 106, 108, 108, 110, 110, - 112, 112, 114, 114, 116, 116, 118, 118, - 120, 120, 122, 122, 124, 124, 126, 126, - 128, 128, 130, 130, 132, 132, 134, 134, - 136, 136, 138, 138, 140, 140, 142, 142, - 144, 144, 146, 146, 148, 148, 150, 150, - 152, 152, 154, 154, 156, 156, 158, 158, - 160, 160, 162, 162, 164, 164, 166, 166, - 168, 168, 170, 170, 172, 172, 174, 174, - 176, 176, 178, 178, 180, 180, 182, 182, - 184, 184, 186, 186, 188, 188, 190, 190, - 192, 192, 194, 194, 196, 196, 198, 198, - 200, 200, 202, 202, 204, 204, 206, 206, - 208, 208, 210, 210, 212, 212, 214, 214, - 216, 216, 218, 218, 220, 220, 222, 222, - 224, 224, 226, 226, 228, 228, 230, 230, - 232, 232, 234, 234, 236, 236, 238, 238, - 240, 240, 242, 242, 244, 244, 246, 246, - 248, 248, 250, 250, 252, 252, 254, 254, - 256, 256, 258, 258, 260, 260, 262, 262, - 264, 264, 266, 266, 268, 268, 270, 270, - 272, 272, 274, 274, 276, 276, 278, 278, - 280, 280, 282, 282, 284, 284, 286, 286, - 288, 288, 290, 290, 292, 292, 294, 294, - 296, 296, 298, 298, 300, 300, 302, 302, - 304, 304, 306, 306, 308, 308, 310, 310, - 312, 312, 314, 314, 316, 316, 318, 318, - 320, 320, 322, 322, 324, 324, 326, 326, - 328, 328, 330, 330, 332, 332, 334, 334, - 336, 336, 338, 338, 340, 340, 342, 342, - 344, 344, 346, 346, 348, 348, 350, 350, - 352, 352, 354, 354, 356, 356, 358, 358, - 360, 360, 362, 362, 364, 364, 366, 366, - 368, 368, 370, 370, 372, 372, 374, 374, - 376, 376, 378, 378, 380, 380, 382, 382, - 384, 384, 386, 386, 388, 388, 390, 390, - 392, 392, 394, 394, 396, 396, 398, 398, - 400, 400, 402, 402, 404, 404, 406, 406, - 408, 408, 410, 410, 412, 412, 414, 414, - 416, 416, 418, 418, 420, 420, 422, 422, - 424, 424, 426, 426, 428, 428, 430, 430, - 432, 432, 434, 434, 436, 436, 438, 438, - 440, 440, 442, 442, 444, 444, 446, 446, - 448, 448, 450, 450, 452, 452, 454, 454, - 456, 456, 458, 458, 460, 460, 462, 462, - 464, 464, 466, 466, 468, 468, 470, 470, - 472, 472, 474, 474, 476, 476, 478, 478, - 480, 480, 482, 482, 484, 484, 486, 486, - 488, 488, 490, 490, 492, 492, 494, 494, - 496, 496, 498, 498, 500, 500, 502, 502, - 504, 504, 506, 506, 508, 508, 510, 510, - 512, 512, 514, 514, 516, 516, 518, 518, - 520, 520, 522, 522, 524, 524, 526, 526, - 528, 528, 530, 530, 532, 532, 534, 534, - 536, 536, 538, 538, 540, 540, 542, 542, - 544, 544, 546, 546, 548, 548, 550, 550, - 552, 552, 554, 554, 556, 556, 558, 558, - 560, 560, 562, 562, 564, 564, 566, 566, - 568, 568, 570, 570, 572, 572, 574, 574, - 576, 576, 578, 578, 580, 580, 582, 582, - 584, 584, 586, 586, 588, 588, 590, 590, - 592, 592, 594, 594, 596, 596, 598, 598, - 600, 600, 602, 602, 604, 604, 606, 606, - 608, 608, 610, 610, 612, 612, 614, 614, - 616, 616, 618, 618, 620, 620, 622, 622, - 624, 624, 626, 626, 628, 628, 630, 630, - 632, 632, 634, 634, 636, 636, 638, 638, - 640, 640, 642, 642, 644, 644, 646, 646, - 648, 648, 650, 650, 652, 652, 654, 654, - 656, 656, 658, 658, 660, 660, 662, 662, - 664, 664, 666, 666, 668, 668, 670, 670, - 672, 672, 674, 674, 676, 676, 678, 678, - 680, 680, 682, 682, 684, 684, 686, 686, - 688, 688, 690, 690, 692, 692, 694, 694, - 696, 696, 698, 698, 700, 700, 702, 702, - 704, 704, 706, 706, 708, 708, 710, 710, - 712, 712, 714, 714, 716, 716, 718, 718, - 720, 720, 722, 722, 724, 724, 726, 726, - 728, 728, 730, 730, 732, 732, 734, 734, - 736, 736, 738, 738, 740, 740, 742, 742, - 744, 744, 746, 746, 748, 748, 750, 750, - 752, 752, 754, 754, 756, 756, 758, 758, - 760, 760, 762, 762, 764, 764, 766, 766, - 768, 768, 770, 770, 772, 772, 774, 774, - 776, 776, 778, 778, 780, 780, 782, 782, - 784, 784, 786, 786, 788, 788, 790, 790, - 792, 792, 794, 794, 796, 796, 798, 798, - 800, 800, 802, 802, 804, 804, 806, 806, - 808, 808, 810, 810, 812, 812, 814, 814, - 816, 816, 818, 818, 820, 820, 822, 822, - 824, 824, 826, 826, 828, 828, 830, 830, - 832, 832, 834, 834, 836, 836, 838, 838, - 840, 840, 842, 842, 844, 844, 846, 846, - 848, 848, 850, 850, 852, 852, 854, 854, - 856, 856, 858, 858, 860, 860, 862, 862, - 864, 864, 866, 866, 868, 868, 870, 870, - 872, 872, 874, 874, 876, 876, 878, 878, - 880, 880, 882, 882, 884, 884, 886, 886, - 888, 888, 890, 890, 892, 892, 894, 894, - 896, 896, 898, 898, 900, 900, 902, 902, - 904, 904, 906, 906, 908, 908, 910, 910, - 912, 912, 914, 914, 916, 916, 918, 918, - 920, 920, 922, 922, 924, 924, 926, 926, - 928, 928, 930, 930, 932, 932, 934, 934, - 936, 936, 938, 938, 940, 940, 942, 942, - 944, 944, 946, 946, 948, 948, 950, 950, - 952, 952, 954, 954, 956, 956, 958, 958, - 960, 960, 962, 962, 964, 964, 966, 966, - 968, 968, 970, 970, 972, 972, 974, 974, - 976, 976, 978, 978, 980, 980, 982, 982, - 984, 984, 986, 986, 988, 988, 990, 990, - 992, 992, 994, 994, 996, 996, 998, 998, - 1000, 1000, 1002, 1002, 1004, 1004, 1006, 1006, - 1008, 1008, 1010, 1010, 1012, 1012, 1014, 1014, - 1016, 1016, 1018, 1018, 1020, 1020, 1022, 1022, - 1024, 1024, 1026, 1026, 1028, 1028, 1030, 1030, - 1032, 1032, 1034, 1034, 1036, 1036, 1038, 1038, - 1040, 1040, 1042, 1042, 1044, 1044, 1046, 1046, - 1048, 1048, 1050, 1050, 1052, 1052, 1054, 1054, - 1056, 1056, 1058, 1058, 1060, 1060, 1062, 1062, - 1064, 1064, 1066, 1066, 1068, 1068, 1070, 1070, - 1072, 1072, 1074, 1074, 1076, 1076, 1078, 1078, - 1080, 1080, 1082, 1082, 1084, 1084, 1086, 1086, - 1088, 1088, 1090, 1090, 1092, 1092, 1094, 1094, - 1096, 1096, 1098, 1098, 1100, 1100, 1102, 1102, - 1104, 1104, 1106, 1106, 1108, 1108, 1110, 1110, - 1112, 1112, 1114, 1114, 1116, 1116, 1118, 1118, - 1120, 1120, 1122, 1122, 1124, 1124, 1126, 1126, - 1128, 1128, 1130, 1130, 1132, 1132, 1134, 1134, - 1136, 1136, 1138, 1138, 1140, 1140, 1142, 1142, - 1144, 1144, 1146, 1146, 1148, 1148, 1150, 1150, - 1152, 1152, 1154, 1154, 1156, 1156, 1158, 1158, - 1160, 1160, 1162, 1162, 1164, 1164, 1166, 1166, - 1168, 1168, 1170, 1170, 1172, 1172, 1174, 1174, - 1176, 1176, 1178, 1178, 1180, 1180, 1182, 1182, - 1184, 1184, 1186, 1186, 1188, 1188, 1190, 1190, - 1192, 1192, 1194, 1194, 1196, 1196, 1198, 1198, - 1200, 1200, 1202, 1202, 1204, 1204, 1206, 1206, - 1208, 1208, 1210, 1210, 1212, 1212, 1214, 1214, - 1216, 1216, 1218, 1218, 1220, 1220, 1222, 1222, - 1224, 1224, 1226, 1226, 1228, 1228, 1230, 1230, - 1232, 1232, 1234, 1234, 1236, 1236, 1238, 1238, - 1240, 1240, 1242, 1242, 1244, 1244, 1246, 1246, - 1248, 1248, 1250, 1250, 1252, 1252, 1254, 1254, - 1256, 1256, 1258, 1258, 1260, 1260, 1262, 1262, - 1264, 1264, 1266, 1266, 1268, 1268, 1270, 1270, - 1272, 1272, 1274, 1274, 1276, 1276, 1278, 1278, - 1280, 1280, 1282, 1282, 1284, 1284, 1286, 1286, - 1288, 1288, 1290, 1290, 1292, 1292, 1294, 1294, - 1296, 1296, 1298, 1298, 1300, 1300, 1302, 1302, - 1304, 1304, 1306, 1306, 1308, 1308, 1310, 1310, - 1312, 1312, 1314, 1314, 1316, 1316, 1318, 1318, - 1320, 1320, 1322, 1322, 1324, 1324, 1326, 1326, - 1328, 1328, 1330, 1330, 1332, 1332, 1334, 1334, - 1336, 1336, 1338, 1338, 1340, 1340, 1342, 1342, - 1344, 1344, 1346, 1346, 1348, 1348, 1350, 1350, - 1352, 1352, 1354, 1354, 1356, 1356, 1358, 1358, - 1360, 1360, 1362, 1362, 1364, 1364, 1366, 1366, - 1368, 1368, 1370, 1370, 1372, 1372, 1374, 1374, - 1376, 1376, 1378, 1378, 1380, 1380, 1382, 1382, - 1384, 1384, 1386, 1386, 1388, 1388, 1390, 1390, - 1392, 1392, 1394, 1394, 1396, 1396, 1398, 1398, - 1400, 1400, 1402, 1402, 1404, 1404, 1406, 1406, - 1408, 1408, 1410, 1410, 1412, 1412, 1414, 1414, - 1416, 1416, 1418, 1418, 1420, 1420, 1422, 1422, - 1424, 1424, 1426, 1426, 1428, 1428, 1430, 1430, - 1432, 1432, 1434, 1434, 1436, 1436, 1438, 1438, - 1440, 1440, 1442, 1442, 1444, 1444, 1446, 1446, - 1448, 1448, 1450, 1450, 1452, 1452, 1454, 1454, - 1456, 1456, 1458, 1458, 1460, 1460, 1462, 1462, - 1464, 1464, 1466, 1466, 1468, 1468, 1470, 1470, - 1472, 1472, 1474, 1474, 1476, 1476, 1478, 1478, - 1480, 1480, 1482, 1482, 1484, 1484, 1486, 1486, - 1488, 1488, 1490, 1490, 1492, 1492, 1494, 1494, - 1496, 1496, 1498, 1498, 1500, 1500, 1502, 1502, - 1504, 1504, 1506, 1506, 1508, 1508, 1510, 1510, - 1512, 1512, 1514, 1514, 1516, 1516, 1518, 1518, - 1520, 1520, 1522, 1522, 1524, 1524, 1526, 1526, - 1528, 1528, 1530, 1530, 1532, 1532, 1534, 1534, - 1536, 1536, 1538, 1538, 1540, 1540, 1542, 1542, - 1544, 1544, 1546, 1546, 1548, 1548, 1550, 1550, - 1552, 1552, 1554, 1554, 1556, 1556, 1558, 1558, - 1560, 1560, 1562, 1562, 1564, 1564, 1566, 1566, - 1568, 1568, 1570, 1570, 1572, 1572, 1574, 1574, - 1576, 1576, 1578, 1578, 1580, 1580, 1582, 1582, - 1584, 1584, 1586, 1586, 1588, 1588, 1590, 1590, - 1592, 1592, 1594, 1594, 1596, 1596, 1598, 1598, - 1600, 1600, 1602, 1602, 1604, 1604, 1606, 1606, - 1608, 1608, 1610, 1610, 1612, 1612, 1614, 1614, - 1616, 1616, 1618, 1618, 1620, 1620, 1622, 1622, - 1624, 1624, 1626, 1626, 1628, 1628, 1630, 1630, - 1632, 1632, 1634, 1634, 1636, 1636, 1638, 1638, - 1640, 1640, 1642, 1642, 1644, 1644, 1646, 1646, - 1648, 1648, 1650, 1650, 1652, 1652, 1654, 1654, - 1656, 1656, 1658, 1658, 1660, 1660, 1662, 1662, - 1664, 1664, 1666, 1666, 1668, 1668, 1670, 1670, - 1672, 1672, 1674, 1674, 1676, 1676, 1678, 1678, - 1680, 1680, 1682, 1682, 1684, 1684, 1686, 1686, - 1688, 1688, 1690, 1690, 1692, 1692, 1694, 1694, - 1696, 1696, 1698, 1698, 1700, 1700, 1702, 1702, - 1704, 1704, 1706, 1706, 1708, 1708, 1710, 1710, - 1712, 1712, 1714, 1714, 1716, 1716, 1718, 1718, - 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1880, 1880, 1882, 1882, 1884, 1884, 1886, 1886, - 1888, 1888, 1890, 1890, 1892, 1892, 1894, 1894, - 1896, 1896, 1898, 1898, 1900, 1900, 1902, 1902, - 1904, 1904, 1906, 1906, 1908, 1908, 1910, 1910, - 1912, 1912, 1914, 1914, 1916, 1916, 1918, 1918, - 1920, 1920, 1922, 1922, 1924, 1924, 1926, 1926, - 1928, 1928, 1930, 1930, 1932, 1932, 1934, 1934, - 1936, 1936, 1938, 1938, 1940, 1940, 1942, 1942, - 1944, 1944, 1946, 1946, 1948, 1948, 1950, 1950, - 1952, 1952, 1954, 1954, 1956, 1956, 1958, 1958, - 1960, 1960, 1962, 1962, 1964, 1964, 1966, 1966, - 1968, 1968, 1970, 1970, 1972, 1972, 1974, 1974, - 1976, 1976, 1978, 1978, 1980, 1980, 1982, 1982, - 1984, 1984, 1986, 1986, 1988, 1988, 1990, 1990, - 1992, 1992, 1994, 1994, 1996, 1996, 1998, 1998, - 2000, 2000, 2002, 2002, 2004, 2004, 2006, 2006, - 2008, 2008, 2010, 2010, 2012, 2012, 2014, 2014, - 2016, 2016, 2018, 2018, 2020, 2020, 2022, 2022, - 2024, 2024, 2026, 2026, 2028, 2028, 2030, 2030, - 2032, 2032, 2034, 2034, 2036, 2036, 2038, 2038, - 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6520, 6520, 6522, 6522, 6524, 6524, 6526, 6526, - 6528, 6528, 6530, 6530, 6532, 6532, 6534, 6534, - 6536, 6536, 6538, 6538, 6540, 6540, 6542, 6542, - 6544, 6544, 6546, 6546, 6548, 6548, 6550, 6550, - 6552, 6552, 6554, 6554, 6556, 6556, 6558, 6558, - 6560, 6560, 6562, 6562, 6564, 6564, 6566, 6566, - 6568, 6568, 6570, 6570, 6572, 6572, 6574, 6574, - 6576, 6576, 6578, 6578, 6580, 6580, 6582, 6582, - 6584, 6584, 6586, 6586, 6588, 6588, 6590, 6590, - 6592, 6592, 6594, 6594, 6596, 6596, 6598, 6598, - 6600, 6600, 6602, 6602, 6604, 6604, 6606, 6606, - 6608, 6608, 6610, 6610, 6612, 6612, 6614, 6614, - 6616, 6616, 6618, 6618, 6620, 6620, 6622, 6622, - 6624, 6624, 6626, 6626, 6628, 6628, 6630, 6630, - 6632, 6632, 6634, 6634, 6636, 6636, 6638, 6638, - 6640, 6640, 6642, 6642, 6644, 6644, 6646, 6646, - 6648, 6648, 6650, 6650, 6652, 6652, 6654, 6654, - 6656, 6656, 6658, 6658, 6660, 6660, 6662, 6662, - 6664, 6664, 6666, 6666, 6668, 6668, 6670, 6670, - 6672, 6672, 6674, 6674, 6676, 6676, 6678, 6678, - 6680, 6680, 6682, 6682, 6684, 6684, 6686, 6686, - 6688, 6688, 6690, 6690, 6692, 6692, 6694, 6694, - 6696, 6696, 6698, 6698, 6700, 6700, 6702, 6702, - 6704, 6704, 6706, 6706, 6708, 6708, 6710, 6710, - 6712, 6712, 6714, 6714, 6716, 6716, 6718, 6718, - 6720, 6720, 6722, 6722, 6724, 6724, 6726, 6726, - 6728, 6728, 6730, 6730, 6732, 6732, 6734, 6734, - 6736, 6736, 6738, 6738, 6740, 6740, 6742, 6742, - 6744, 6744, 6746, 6746, 6748, 6748, 6750, 6750, - 6752, 6752, 6754, 6754, 6756, 6756, 6758, 6758, - 6760, 6760, 6762, 6762, 6764, 6764, 6766, 6766, - 6768, 6768, 6770, 6770, 6772, 6772, 6774, 6774, - 6776, 6776, 6778, 6778, 6780, 6780, 6782, 6782, - 6784, 6784, 6786, 6786, 6788, 6788, 6790, 6790, - 6792, 6792, 6794, 6794, 6796, 6796, 6798, 6798, - 6800, 6800, 6802, 6802, 6804, 6804, 6806, 6806, - 6808, 6808, 6810, 6810, 6812, 6812, 6814, 6814, - 6816, 6816, 6818, 6818, 6820, 6820, 6822, 6822, - 6824, 6824, 6826, 6826, 6828, 6828, 6830, 6830, - 6832, 6832, 6834, 6834, 6836, 6836, 6838, 6838, - 6840, 6840, 6842, 6842, 6844, 6844, 6846, 6846, - 6848, 6848, 6850, 6850, 6852, 6852, 6854, 6854, - 6856, 6856, 6858, 6858, 6860, 6860, 6862, 6862, - 6864, 6864, 6866, 6866, 6868, 6868, 6870, 6870, - 6872, 6872, 6874, 6874, 6876, 6876, 6878, 6878, - 6880, 6880, 6882, 6882, 6884, 6884, 6886, 6886, - 6888, 6888, 6890, 6890, 6892, 6892, 6894, 6894, - 6896, 6896, 6898, 6898, 6900, 6900, 6902, 6902, - 6904, 6904, 6906, 6906, 6908, 6908, 6910, 6910, - 6912, 6912, 6914, 6914, 6916, 6916, 6918, 6918, - 6920, 6920, 6922, 6922, 6924, 6924, 6926, 6926, - 6928, 6928, 6930, 6930, 6932, 6932, 6934, 6934, - 6936, 6936, 6938, 6938, 6940, 6940, 6942, 6942, - 6944, 6944, 6946, 6946, 6948, 6948, 6950, 6950, - 6952, 6952, 6954, 6954, 6956, 6956, 6958, 6958, - 6960, 6960, 6962, 6962, 6964, 6964, 6966, 6966, - 6968, 6968, 6970, 6970, 6972, 6972, 6974, 6974, - 6976, 6976, 6978, 6978, 6980, 6980, 6982, 6982, - 6984, 6984, 6986, 6986, 6988, 6988, 6990, 6990, - 6992, 6992, 6994, 6994, 6996, 6996, 6998, 6998, - 7000, 7000, 7002, 7002, 7004, 7004, 7006, 7006, - 7008, 7008, 7010, 7010, 7012, 7012, 7014, 7014, - 7016, 7016, 7018, 7018, 7020, 7020, 7022, 7022, - 7024, 7024, 7026, 7026, 7028, 7028, 7030, 7030, - 7032, 7032, 7034, 7034, 7036, 7036, 7038, 7038, - 7040, 7040, 7042, 7042, 7044, 7044, 7046, 7046, - 7048, 7048, 7050, 7050, 7052, 7052, 7054, 7054, - 7056, 7056, 7058, 7058, 7060, 7060, 7062, 7062, - 7064, 7064, 7066, 7066, 7068, 7068, 7070, 7070, - 7072, 7072, 7074, 7074, 7076, 7076, 7078, 7078, - 7080, 7080, 7082, 7082, 7084, 7084, 7086, 7086, - 7088, 7088, 7090, 7090, 7092, 7092, 7094, 7094, - 7096, 7096, 7098, 7098, 7100, 7100, 7102, 7102, - 7104, 7104, 7106, 7106, 7108, 7108, 7110, 7110, - 7112, 7112, 7114, 7114, 7116, 7116, 7118, 7118, - 7120, 7120, 7122, 7122, 7124, 7124, 7126, 7126, - 7128, 7128, 7130, 7130, 7132, 7132, 7134, 7134, - 7136, 7136, 7138, 7138, 7140, 7140, 7142, 7142, - 7144, 7144, 7146, 7146, 7148, 7148, 7150, 7150, - 7152, 7152, 7154, 7154, 7156, 7156, 7158, 7158, - 7160, 7160, 7162, 7162, 7164, 7164, 7166, 7166, - 7168, 7168, 7170, 7170, 7172, 7172, 7174, 7174, - 7176, 7176, 7178, 7178, 7180, 7180, 7182, 7182, - 7184, 7184, 7186, 7186, 7188, 7188, 7190, 7190, - 7192, 7192, 7194, 7194, 7196, 7196, 7198, 7198, - 7200, 7200, 7202, 7202, 7204, 7204, 7206, 7206, - 7208, 7208, 7210, 7210, 7212, 7212, 7214, 7214, - 7216, 7216, 7218, 7218, 7220, 7220, 7222, 7222, - 7224, 7224, 7226, 7226, 7228, 7228, 7230, 7230, - 7232, 7232, 7234, 7234, 7236, 7236, 7238, 7238, - 7240, 7240, 7242, 7242, 7244, 7244, 7246, 7246, - 7248, 7248, 7250, 7250, 7252, 7252, 7254, 7254, - 7256, 7256, 7258, 7258, 7260, 7260, 7262, 7262, - 7264, 7264, 7266, 7266, 7268, 7268, 7270, 7270, - 7272, 7272, 7274, 7274, 7276, 7276, 7278, 7278, - 7280, 7280, 7282, 7282, 7284, 7284, 7286, 7286, - 7288, 7288, 7290, 7290, 7292, 7292, 7294, 7294, - 7296, 7296, 7298, 7298, 7300, 7300, 7302, 7302, - 7304, 7304, 7306, 7306, 7308, 7308, 7310, 7310, - 7312, 7312, 7314, 7314, 7316, 7316, 7318, 7318, - 7320, 7320, 7322, 7322, 7324, 7324, 7326, 7326, - 7328, 7328, 7330, 7330, 7332, 7332, 7334, 7334, - 7336, 7336, 7338, 7338, 7340, 7340, 7342, 7342, - 7344, 7344, 7346, 7346, 7348, 7348, 7350, 7350, - 7352, 7352, 7354, 7354, 7356, 7356, 7358, 7358, - 7360, 7360, 7362, 7362, 7364, 7364, 7366, 7366, - 7368, 7368, 7370, 7370, 7372, 7372, 7374, 7374, - 7376, 7376, 7378, 7378, 7380, 7380, 7382, 7382, - 7384, 7384, 7386, 7386, 7388, 7388, 7390, 7390, - 7392, 7392, 7394, 7394, 7396, 7396, 7398, 7398, - 7400, 7400, 7402, 7402, 7404, 7404, 7406, 7406, - 7408, 7408, 7410, 7410, 7412, 7412, 7414, 7414, - 7416, 7416, 7418, 7418, 7420, 7420, 7422, 7422, - 7424, 7424, 7426, 7426, 7428, 7428, 7430, 7430, - 7432, 7432, 7434, 7434, 7436, 7436, 7438, 7438, - 7440, 7440, 7442, 7442, 7444, 7444, 7446, 7446, - 7448, 7448, 7450, 7450, 7452, 7452, 7454, 7454, - 7456, 7456, 7458, 7458, 7460, 7460, 7462, 7462, - 7464, 7464, 7466, 7466, 7468, 7468, 7470, 7470, - 7472, 7472, 7474, 7474, 7476, 7476, 7478, 7478, - 7480, 7480, 7482, 7482, 7484, 7484, 7486, 7486, - 7488, 7488, 7490, 7490, 7492, 7492, 7494, 7494, - 7496, 7496, 7498, 7498, 7500, 7500, 7502, 7502, - 7504, 7504, 7506, 7506, 7508, 7508, 7510, 7510, - 7512, 7512, 7514, 7514, 7516, 7516, 7518, 7518, - 7520, 7520, 7522, 7522, 7524, 7524, 7526, 7526, - 7528, 7528, 7530, 7530, 7532, 7532, 7534, 7534, - 7536, 7536, 7538, 7538, 7540, 7540, 7542, 7542, - 7544, 7544, 7546, 7546, 7548, 7548, 7550, 7550, - 7552, 7552, 7554, 7554, 7556, 7556, 7558, 7558, - 7560, 7560, 7562, 7562, 7564, 7564, 7566, 7566, - 7568, 7568, 7570, 7570, 7572, 7572, 7574, 7574, - 7576, 7576, 7578, 7578, 7580, 7580, 7582, 7582, - 7584, 7584, 7586, 7586, 7588, 7588, 7590, 7590, - 7592, 7592, 7594, 7594, 7596, 7596, 7598, 7598, - 7600, 7600, 7602, 7602, 7604, 7604, 7606, 7606, - 7608, 7608, 7610, 7610, 7612, 7612, 7614, 7614, - 7616, 7616, 7618, 7618, 7620, 7620, 7622, 7622, - 7624, 7624, 7626, 7626, 7628, 7628, 7630, 7630, - 7632, 7632, 7634, 7634, 7636, 7636, 7638, 7638, - 7640, 7640, 7642, 7642, 7644, 7644, 7646, 7646, - 7648, 7648, 7650, 7650, 7652, 7652, 7654, 7654, - 7656, 7656, 7658, 7658, 7660, 7660, 7662, 7662, - 7664, 7664, 7666, 7666, 7668, 7668, 7670, 7670, - 7672, 7672, 7674, 7674, 7676, 7676, 7678, 7678, - 7680, 7680, 7682, 7682, 7684, 7684, 7686, 7686, - 7688, 7688, 7690, 7690, 7692, 7692, 7694, 7694, - 7696, 7696, 7698, 7698, 7700, 7700, 7702, 7702, - 7704, 7704, 7706, 7706, 7708, 7708, 7710, 7710, - 7712, 7712, 7714, 7714, 7716, 7716, 7718, 7718, - 7720, 7720, 7722, 7722, 7724, 7724, 7726, 7726, - 7728, 7728, 7730, 7730, 7732, 7732, 7734, 7734, - 7736, 7736, 7738, 7738, 7740, 7740, 7742, 7742, - 7744, 7744, 7746, 7746, 7748, 7748, 7750, 7750, - 7752, 7752, 7754, 7754, 7756, 7756, 7758, 7758, - 7760, 7760, 7762, 7762, 7764, 7764, 7766, 7766, - 7768, 7768, 7770, 7770, 7772, 7772, 7774, 7774, - 7776, 7776, 7778, 7778, 7780, 7780, 7782, 7782, - 7784, 7784, 7786, 7786, 7788, 7788, 7790, 7790, - 7792, 7792, 7794, 7794, 7796, 7796, 7798, 7798, - 7800, 7800, 7802, 7802, 7804, 7804, 7806, 7806, - 7808, 7808, 7810, 7810, 7812, 7812, 7814, 7814, - 7816, 7816, 7818, 7818, 7820, 7820, 7822, 7822, - 7824, 7824, 7826, 7826, 7828, 7828, 7830, 7830, - 7832, 7832, 7834, 7834, 7836, 7836, 7838, 7838, - 7840, 7840, 7842, 7842, 7844, 7844, 7846, 7846, - 7848, 7848, 7850, 7850, 7852, 7852, 7854, 7854, - 7856, 7856, 7858, 7858, 7860, 7860, 7862, 7862, - 7864, 7864, 7866, 7866, 7868, 7868, 7870, 7870, - 7872, 7872, 7874, 7874, 7876, 7876, 7878, 7878, - 7880, 7880, 7882, 7882, 7884, 7884, 7886, 7886, - 7888, 7888, 7890, 7890, 7892, 7892, 7894, 7894, - 7896, 7896, 7898, 7898, 7900, 7900, 7902, 7902, - 7904, 7904, 7906, 7906, 7908, 7908, 7910, 7910, - 7912, 7912, 7914, 7914, 7916, 7916, 7918, 7918, - 7920, 7920, 7922, 7922, 7924, 7924, 7926, 7926, - 7928, 7928, 7930, 7930, 7932, 7932, 7934, 7934, - 7936, 7936, 7938, 7938, 7940, 7940, 7942, 7942, - 7944, 7944, 7946, 7946, 7948, 7948, 7950, 7950, - 7952, 7952, 7954, 7954, 7956, 7956, 7958, 7958, - 7960, 7960, 7962, 7962, 7964, 7964, 7966, 7966, - 7968, 7968, 7970, 7970, 7972, 7972, 7974, 7974, - 7976, 7976, 7978, 7978, 7980, 7980, 7982, 7982, - 7984, 7984, 7986, 7986, 7988, 7988, 7990, 7990, - 7992, 7992, 7994, 7994, 7996, 7996, 7998, 7998, - 8000, 8000, 8002, 8002, 8004, 8004, 8006, 8006, - 8008, 8008, 8010, 8010, 8012, 8012, 8014, 8014, - 8016, 8016, 8018, 8018, 8020, 8020, 8022, 8022, - 8024, 8024, 8026, 8026, 8028, 8028, 8030, 8030, - 8032, 8032, 8034, 8034, 8036, 8036, 8038, 8038, - 8040, 8040, 8042, 8042, 8044, 8044, 8046, 8046, - 8048, 8048, 8050, 8050, 8052, 8052, 8054, 8054, - 8056, 8056, 8058, 8058, 8060, 8060, 8062, 8062, - 8064, 8064, 8066, 8066, 8068, 8068, 8070, 8070, - 8072, 8072, 8074, 8074, 8076, 8076, 8078, 8078, - 8080, 8080, 8082, 8082, 8084, 8084, 8086, 8086, - 8088, 8088, 8090, 8090, 8092, 8092, 8094, 8094, - 8096, 8096, 8098, 8098, 8100, 8100, 8102, 8102, - 8104, 8104, 8106, 8106, 8108, 8108, 8110, 8110, - 8112, 8112, 8114, 8114, 8116, 8116, 8118, 8118, - 8120, 8120, 8122, 8122, 8124, 8124, 8126, 8126, - 8128, 8128, 8130, 8130, 8132, 8132, 8134, 8134, - 8136, 8136, 8138, 8138, 8140, 8140, 8142, 8142, - 8144, 8144, 8146, 8146, 8148, 8148, 8150, 8150, - 8152, 8152, 8154, 8154, 8156, 8156, 8158, 8158, - 8160, 8160, 8162, 8162, 8164, 8164, 8166, 8166, - 8168, 8168, 8170, 8170, 8172, 8172, 8174, 8174, - 8176, 8176, 8178, 8178, 8180, 8180, 8182, 8182, - 8184, 8184, 8186, 8186, 8188, 8188, 8190, 8190 -};*/ diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ps_apps/aie_test/src/input.h b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ps_apps/aie_test/src/input.h deleted file mode 100644 index da18927562..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ps_apps/aie_test/src/input.h +++ /dev/null @@ -1,4114 +0,0 @@ -// Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -// SPDX-License-Identifier: MIT - -#pragma once - -short int cint16input[] = { -//DB adding two input lines of zeros to reset the internal filter states - 0, 0, 0, 0, 0, 0, 0, 0, - 0, 0, 0, 0, 0, 0, 0, 0, - -3701, -13136, 10775, -8233, 8594, -8350, 3010, -7129, - -854, -12141, -15933, -1952, -11431, 2610, -5876, 9654, - -16005, -14649, 13079, -7961, -4823, -15861, 641, -6558, - -8150, -11182, 7075, 4045, 8589, 13495, -3035, 13763, - 1428, -9596, -11807, -6798, -11890, -14610, 11915, -3099, - 14286, 3140, -14877, 15923, 12823, -13993, 12008, 12167, - 5817, -2895, 6899, 8567, 15968, 2761, 2883, 4074, - 3885, -10030, 9490, 1086, 10804, 271, 13538, 6518, - -2149, -3409, 11240, 13794, -7287, -6218, -13038, 2024, - 5234, 3350, 14199, 2449, 1509, 3941, 15163, -1075, - 669, 12097, -2389, 83, -8974, -745, -9400, -16295, - -11550, 10304, 5500, -16040, -4240, 3699, 13132, 1389, - -16090, -16186, 9173, -44, 12843, 4894, -9669, -12721, - 10186, 3450, 7251, 14585, -11038, 10288, 4856, 969, - 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-3729, 7273, -6197, 15557, -1346, 3833, -2549, -8896, - 10756, 9875, 2650, -4481, 664, -12551, -15191, -2294, - 5380, 11769, -11887, -151, -12577, 9622, 1764, -3987, - -7446, 7841, -14268, 15398, -5985, 1373, 12930, -12079, - -1968, 14021, -14516, -10892, -11084, -12205, 15276, -5287, - 5772, 2443, 3695, -5975, -4613, 9885, 457, 7074, - 3176, 10150, 6563, -12260, -1494, -12338, 15404, 8188, - 6265, -10541, 183, 499, -7051, 10627, -12972, 6930, - -4205, -5812, 13691, -4969, 1247, 1682, 13090, -7742, - -12539, -13789, -4296, -10184, 11374, -11196, 13108, 13505, - 10489, 6504, 2518, -13253, 15570, 1850, 6734, -7279, - -11982, 13889, -2605, 7878, -10961, -1986, -4896, 9423, - 14298, -879, -9204, -3290, -7581, -7935, -15047, -13931, - 13233, 4251, -8034, 15202, -2590, 13834, -2823, -2341, - 14402, 5115, 5814, -11822, 6920, -12381, -6985, -14702, - -4714, 7503, 7549, 6031, 12205, -8684, 7059, 5333, - -14574, -1359, -3826, -2145, 6316, 10512, -7399, 4640, - -4882, -5085, -4617, -8015, -10052, 10224, -2158, 9743, - 12389, -5167, 13391, -11971, 6796, 2212, 15464, -15428, - 4059, -2319, -1092, -2144, -2437, -2054, 3395, -7887, - -5778, -15586, 9116, -5249, 6395, -15793, 12152, 10425, - 5675, -10681, 11479, 13002, 10688, 6301, 4982, -7681, - -11079, -13015, 1944, -7774, 2990, -3177, 10308, 2646, - 15095, -15103, -434, -4516, 3203, -12853, -15254, -854, - 9399, -14575, -13816, -13615, -3675, 68, -6900, -10525, - -8412, -41, 15193, -1703, 8125, -2784, -5299, 12509, - 15060, -11096, 10843, 2976, 11803, -15783, 2617, 3802, - -3561, 2855, 4533, -11727, -9343, 11187, 12968, -1433, - -14956, 4824, 11478, 15061, 2435, -8970, 7914, -9184, - 2043, 1412, 6738, 4873, -2800, -16100, 7069, 6348, - 14413, 4812, -14782, -8664, 2425, -4615, -8564, -9040, - 640, -7688, 13450, 5053, -11104, 10957, -6055, -5615, - 11989, 2761, -8009, -3505, -15595, -10663, 8411, -11140, - -10747, 2112, 12449, 6906, 15210, 13478, 4876, 15033, - -14853, -12128, -172, 8223, 6550, 6398, 13769, -7911, - 6727, -14921, -11917, -14954, -12450, 931, 10323, -6319, - -15485, 14334, -11741, -9886, 9974, 4696, 6617, 1430, - 9860, 4638, 14743, -11673, -15565, -1865, -10800, 12126, - 16252, 12413, -3785, -307, -291, -3909, -13677, 5753, - 15993, -1053, 1816, -6409, 15693, -3954, 9255, -10044, - 14971, -2072, -439, 10993, -5298, -9879, 6670, -9649, - 13045, -900, -12427, -6041, -9989, 7617, 1405, 9713, - -13669, 16264, 16123, 2400, -14348, 3493, 10767, 11686, - 10564, -1532, 14533, 13040, -8162, -8429, 4086, -15064, - -11487, -13870, 14449, 11285, -3503, -1546, -171, -5648, - -12940, 5971, -11402, 2482, -5059, 14384, -12005, -5894, - 15691, -11969, 3109, 4676, 9238, 15532, 4606, -5524, - -10867, -12732, -14062, 14533, 3893, -13105, 16120, 8366, - -5767, 9051, 15651, -1186, 13478, 1621, 14623, 426, - -11249, 4321, 13543, -6064, 1106, -15235, -13937, 15803, - 6700, -15363, 4880, -795, 5485, -11303, -4998, -5517, - -3375, -724, -6058, 9980, 13337, 2079, 13775, 5150, - 3486, -3072, 14212, 13100, 15955, 2754, 6092, 8054, - -11204, 14871, -10086, 12578, 7617, -4568, 6535, 7183, - -15115, -2341, -7604, 3656, 10889, -2792, -3316, -4108, - -2913, -719, -11299, 10049, 10046, -4380, 6261, -7134, - -15041, -13300, -2209, -10556, -1276, -12858, 8193, 1969, - 4764, 16015, -16120, 7377, 649, 8910, -971, -15967, - 5154, 6576, 13255, 2227, 2051, -2846, -2517, -2300, - 2324, -15676, -8255, 11699, -16165, -14831, 12203, 1610, - -12127, -15488, -2527, -14989, 5269, -13481, -8017, -11433, - -7779, 10273, -1387, -11836, -310, -3313, 8993, -3890, - -10322, 6521, -10539, 10129, -3292, 10158, 4161, -15871, - 4895, -11083, 14308, -14274, 13619, 6201, -13541, 5579, - 14004, -8671, 10240, -6707, 11026, 15542, 3381, -2352, - -11334, -9606, -5340, 11161, 9037, 13965, -13718, 14096, - -1166, 16114, 935, 11144, -8348, -7312, 16321, -1148, - -1444, -9781, 9890, -1563, 13622, 10416, 6242, 1768, - -3262, 3312, -4180, -6583, -10398, 1574, 15144, -6282, - -13232, -2208, 7071, -7414, -15473, 13649, 3, -15463, - 11624, 14346, -2736, 12382, 1097, 3637, -8285, 6609, - -7026, 11586, 11971, -16208, -15914, 7006, -13590, 13986, - 1366, 12558, -12967, 6412, 11488, -2112, -7732, 414, - -2481, -4455, -5289, -3334, -7847, -12784, -5072, -16200, - -3896, 4019, -1027, 7594, -5632, 7167, -859, -12948, - -8616, -15914, -499, -15190, 10693, 12447, -10526, -906, - 4906, -10929, 4850, 10825, -8247, -14099, -13115, -14786, - 2024, -535, 3259, 15316, -15264, -3649, -16045, 6176, - 14378, -1056, -7591, -9405, -15952, 7452, -13500, -15031, - 7251, 9400, 5775, -2226, 13024, 13948, -10271, -15242, - -14004, -10096, -9082, -5193, -6185, 14986, -14120, -9623, - -5714, 16008, 3083, 4579, -11562, 8048, 10702, -10186, - 13976, -6710, 5333, -5306, 767, -15774, -8263, -11592, - -3029, 4765, -12715, 7690, -3589, -9221, 13711, -11294, - 10209, 14799, 11833, -12317, -13914, 4875, -14237, 4235, - 13711, 6882, -13687, 9764, -11503, 2769, 16158, -13279, - 6410, 7869, -2997, -11510, -10259, -9164, 5919, -6930, - -9415, 13960, 1246, -9387, -10860, -8916, 3581, -6222, - -6566, 6678, -8705, -8603, -2397, 8820, 12763, 7566, - 9269, 10111, 15654, 8885, -1393, -14155, 4150, -5412, - -3161, 1544, -5720, 9057, 9288, 13318, 2239, 12730, - 10525, 10546, 9149, -12294, -5042, 1071, -15268, 12946, - 7090, 5823, 10082, -4934, -3458, 9978, -5870, 14222, - -1194, 776, -7748, -11383, -4296, 9607, -5867, -5440, - 13712, -3563, 81, 13053, -1427, 16125, 8186, -908, - 15376, -15665, -1391, 5884, 11506, -8138, -14356, -1754, - -5598, -1488, 14527, 765, 13234, 11814, 13237, -7332, - 10487, 12949, -3513, 7575, -14444, 14797, -2636, -6098, - -10363, -8647, 392, 8573, 1365, 10336, -6157, 8986, - -4059, 16018, 12361, 6148, 12548, -3785, 15621, -3555, - -4334, 5318, 13541, -4019, -15851, 5961, -2729, -72, - 14093, -37, 618, 15437, 1822, 13624, -5789, 4254, - 2485, -15601, 1050, 1845, 15746, -2895, 16167, -1247, - -8040, 4756, -1363, 12881, 15504, -12768, -13102, -5558, - -1595, -6974, 15195, -5116, -8433, -14752, -12575, -5537, - -8602, -3913, 14651, 7340, -5577, -12147, -4506, 16266, - -5417, 14334, 9128, -14278, 12979, 8803, 14746, -8958, - 1451, 3495, 1494, 14088, 6694, 14428, -1715, -106, - 13793, -15119, -7643, -1057, -368, -11565, 2618, 7779, - 7730, 1302, -8903, -1278, 1119, 5900, 4042, -14560, - -1723, -3905, 11508, 1295, 5019, 9971, -11285, 2261, - 4740, 10224, -5745, -2810, 10306, 14384, -15412, 15910, - -2739, -6880, -7009, 3231, 13341, -16102, -3621, -266, - 1379, 15258, -1810, 10865, 5324, -7552, 329, 10110, - -7312, 11668, -15946, -575, -13939, -11666, 4431, 4867, - 884, 11749, 6825, -1158, -2603, 508, 12291, 12805, - -16320, 47, 10821, 1874, -1219, -2098, 5630, -1993, - -8760, -2640, 13401, -3727, 9396, 121, -4616, -7342, - -11144, -5202, -12023, -5801, 12027, 1492, -14653, 13560, - 11438, 8250, 8317, -6244, 2092, 3104, 3373, 12404, - -2316, 15718, -934, 3977, 10977, -9198, -14075, -14760, - 13164, 3019, -921, -4129, 7957, -973, -3780, -1688, -//DB: remove the last 2 lines of data to compensate for the 2 first lines of zeros -// -10971, -9525, 1922, -1967, -4812, -14443, -15426, 1282, -// 7301, 9117, -4762, -14116, -15768, -4345, -15216, -12374, -// 0, 0, 0, 0, 0, 0, 0, 0, -// 0, 0, 0, 0, 0, 0, 0, 0 -}; - -/*Ramp input -short int cint16input[] = { - - 0, 0, 1, 1, 2, 2, 3, 3, - 4, 4, 5, 5, 6, 6, 7, 7, - 8, 8, 9, 9, 10, 10, 11, 11, - 12, 12, 13, 13, 14, 14, 15, 15, - 16, 16, 17, 17, 18, 18, 19, 19, - 20, 20, 21, 21, 22, 22, 23, 23, - 24, 24, 25, 25, 26, 26, 27, 27, - 28, 28, 29, 29, 30, 30, 31, 31, - 32, 32, 33, 33, 34, 34, 35, 35, - 36, 36, 37, 37, 38, 38, 39, 39, - 40, 40, 41, 41, 42, 42, 43, 43, - 44, 44, 45, 45, 46, 46, 47, 47, - 48, 48, 49, 49, 50, 50, 51, 51, - 52, 52, 53, 53, 54, 54, 55, 55, - 56, 56, 57, 57, 58, 58, 59, 59, - 60, 60, 61, 61, 62, 62, 63, 63, - 64, 64, 65, 65, 66, 66, 67, 67, - 68, 68, 69, 69, 70, 70, 71, 71, - 72, 72, 73, 73, 74, 74, 75, 75, - 76, 76, 77, 77, 78, 78, 79, 79, - 80, 80, 81, 81, 82, 82, 83, 83, - 84, 84, 85, 85, 86, 86, 87, 87, - 88, 88, 89, 89, 90, 90, 91, 91, - 92, 92, 93, 93, 94, 94, 95, 95, - 96, 96, 97, 97, 98, 98, 99, 99, - 100, 100, 101, 101, 102, 102, 103, 103, - 104, 104, 105, 105, 106, 106, 107, 107, - 108, 108, 109, 109, 110, 110, 111, 111, - 112, 112, 113, 113, 114, 114, 115, 115, - 116, 116, 117, 117, 118, 118, 119, 119, - 120, 120, 121, 121, 122, 122, 123, 123, - 124, 124, 125, 125, 126, 126, 127, 127, - 128, 128, 129, 129, 130, 130, 131, 131, - 132, 132, 133, 133, 134, 134, 135, 135, - 136, 136, 137, 137, 138, 138, 139, 139, - 140, 140, 141, 141, 142, 142, 143, 143, - 144, 144, 145, 145, 146, 146, 147, 147, - 148, 148, 149, 149, 150, 150, 151, 151, - 152, 152, 153, 153, 154, 154, 155, 155, - 156, 156, 157, 157, 158, 158, 159, 159, - 160, 160, 161, 161, 162, 162, 163, 163, - 164, 164, 165, 165, 166, 166, 167, 167, - 168, 168, 169, 169, 170, 170, 171, 171, - 172, 172, 173, 173, 174, 174, 175, 175, - 176, 176, 177, 177, 178, 178, 179, 179, - 180, 180, 181, 181, 182, 182, 183, 183, - 184, 184, 185, 185, 186, 186, 187, 187, - 188, 188, 189, 189, 190, 190, 191, 191, - 192, 192, 193, 193, 194, 194, 195, 195, - 196, 196, 197, 197, 198, 198, 199, 199, - 200, 200, 201, 201, 202, 202, 203, 203, - 204, 204, 205, 205, 206, 206, 207, 207, - 208, 208, 209, 209, 210, 210, 211, 211, - 212, 212, 213, 213, 214, 214, 215, 215, - 216, 216, 217, 217, 218, 218, 219, 219, - 220, 220, 221, 221, 222, 222, 223, 223, - 224, 224, 225, 225, 226, 226, 227, 227, - 228, 228, 229, 229, 230, 230, 231, 231, - 232, 232, 233, 233, 234, 234, 235, 235, - 236, 236, 237, 237, 238, 238, 239, 239, - 240, 240, 241, 241, 242, 242, 243, 243, - 244, 244, 245, 245, 246, 246, 247, 247, - 248, 248, 249, 249, 250, 250, 251, 251, - 252, 252, 253, 253, 254, 254, 255, 255, - 256, 256, 257, 257, 258, 258, 259, 259, - 260, 260, 261, 261, 262, 262, 263, 263, - 264, 264, 265, 265, 266, 266, 267, 267, - 268, 268, 269, 269, 270, 270, 271, 271, - 272, 272, 273, 273, 274, 274, 275, 275, - 276, 276, 277, 277, 278, 278, 279, 279, - 280, 280, 281, 281, 282, 282, 283, 283, - 284, 284, 285, 285, 286, 286, 287, 287, - 288, 288, 289, 289, 290, 290, 291, 291, - 292, 292, 293, 293, 294, 294, 295, 295, - 296, 296, 297, 297, 298, 298, 299, 299, - 300, 300, 301, 301, 302, 302, 303, 303, - 304, 304, 305, 305, 306, 306, 307, 307, - 308, 308, 309, 309, 310, 310, 311, 311, - 312, 312, 313, 313, 314, 314, 315, 315, - 316, 316, 317, 317, 318, 318, 319, 319, - 320, 320, 321, 321, 322, 322, 323, 323, - 324, 324, 325, 325, 326, 326, 327, 327, - 328, 328, 329, 329, 330, 330, 331, 331, - 332, 332, 333, 333, 334, 334, 335, 335, - 336, 336, 337, 337, 338, 338, 339, 339, - 340, 340, 341, 341, 342, 342, 343, 343, - 344, 344, 345, 345, 346, 346, 347, 347, - 348, 348, 349, 349, 350, 350, 351, 351, - 352, 352, 353, 353, 354, 354, 355, 355, - 356, 356, 357, 357, 358, 358, 359, 359, - 360, 360, 361, 361, 362, 362, 363, 363, - 364, 364, 365, 365, 366, 366, 367, 367, - 368, 368, 369, 369, 370, 370, 371, 371, - 372, 372, 373, 373, 374, 374, 375, 375, - 376, 376, 377, 377, 378, 378, 379, 379, - 380, 380, 381, 381, 382, 382, 383, 383, - 384, 384, 385, 385, 386, 386, 387, 387, - 388, 388, 389, 389, 390, 390, 391, 391, - 392, 392, 393, 393, 394, 394, 395, 395, - 396, 396, 397, 397, 398, 398, 399, 399, - 400, 400, 401, 401, 402, 402, 403, 403, - 404, 404, 405, 405, 406, 406, 407, 407, - 408, 408, 409, 409, 410, 410, 411, 411, - 412, 412, 413, 413, 414, 414, 415, 415, - 416, 416, 417, 417, 418, 418, 419, 419, - 420, 420, 421, 421, 422, 422, 423, 423, - 424, 424, 425, 425, 426, 426, 427, 427, - 428, 428, 429, 429, 430, 430, 431, 431, - 432, 432, 433, 433, 434, 434, 435, 435, - 436, 436, 437, 437, 438, 438, 439, 439, - 440, 440, 441, 441, 442, 442, 443, 443, - 444, 444, 445, 445, 446, 446, 447, 447, - 448, 448, 449, 449, 450, 450, 451, 451, - 452, 452, 453, 453, 454, 454, 455, 455, - 456, 456, 457, 457, 458, 458, 459, 459, - 460, 460, 461, 461, 462, 462, 463, 463, - 464, 464, 465, 465, 466, 466, 467, 467, - 468, 468, 469, 469, 470, 470, 471, 471, - 472, 472, 473, 473, 474, 474, 475, 475, - 476, 476, 477, 477, 478, 478, 479, 479, - 480, 480, 481, 481, 482, 482, 483, 483, - 484, 484, 485, 485, 486, 486, 487, 487, - 488, 488, 489, 489, 490, 490, 491, 491, - 492, 492, 493, 493, 494, 494, 495, 495, - 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8180, 8180, 8181, 8181, 8182, 8182, 8183, 8183, - 8184, 8184, 8185, 8185, 8186, 8186, 8187, 8187, - 8188, 8188, 8189, 8189, 8190, 8190, 8191, 8191 -};*/ diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ps_apps/aie_test/src/xrt_host.cpp b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ps_apps/aie_test/src/xrt_host.cpp deleted file mode 100644 index 60183a65ba..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/ps_apps/aie_test/src/xrt_host.cpp +++ /dev/null @@ -1,143 +0,0 @@ -// Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -// SPDX-License-Identifier: MIT - - -#include -#include -#include -#include -#include -#include -#include -#include - -#include "input.h" -#include "golden.h" - -#include "fir_graph.cpp" - -#define TYPE_DATA int16_t - -static const uint32_t ITERATIONS = 0; - -static const char* STR_ERROR = "ERROR: "; -static const char* STR_FAILED = "FAILED: "; -static const char* STR_PASSED = "PASSED: "; -static const char* STR_INFO = "INFO: "; -static const char* STR_USAGE = "USAGE: "; - -int main(int argc, char* argv[]) { - - // Check command line - if(argc < 2) { - std::cout << STR_USAGE << argv[0] <<" " << std::endl; - return EXIT_FAILURE; - } - - // Calculating samples / bsize - uint32_t iterations = ITERATIONS; - - if(argc >= 3) { - iterations = atoi(argv[2]); - } - - /* - //for AIE project here are the settings in words size - #define INPUT_SIZE (8192 ) //rows of complex data: Re + jIm - #define OUTPUT_SIZE (8192/2) //rows of complex data: Re + jIm - */ - int wSizeIn = 8192; - int bSizeIn = wSizeIn * sizeof(TYPE_DATA) * 2; - int wSizeOut = wSizeIn / 2; - int bSizeOut = wSizeOut * sizeof(TYPE_DATA) * 2; - - std::cout << STR_INFO << "iterations = " << iterations << std::endl; - std::cout << STR_INFO << "words SizeIn = " << wSizeIn << std::endl; - std::cout << STR_INFO << "words SizeOut = " << wSizeOut << std::endl; - std::cout << STR_INFO << "bytes SizeIn = " << bSizeIn << std::endl; - std::cout << STR_INFO << "bytes SizeOut = " << bSizeOut << std::endl; - - // Loading the xclbin - char* xclbinFilename = argv[1]; - - unsigned int dev_index = 0; - auto my_device = xrt::device(dev_index); - std::cout << STR_PASSED << "auto my_device = xrt::device(" << dev_index << ")" << std::endl; - - auto xclbin_uuid = my_device.load_xclbin(xclbinFilename); - std::cout << STR_PASSED << "auto xclbin_uuid = my_device.load_xclbin(" << xclbinFilename << ")" << std::endl; - - // Starting the input mm2s kernels - auto in_0 = xrt::kernel(my_device, xclbin_uuid, "mm2s:{mm2s_1}"); - std::cout << STR_PASSED << "auto in_0 = xrt::kernel(my_device, xclbin_uuid, \"mm2s:{mm2s_1}\")" << std::endl; - - auto in_0_bo = xrt::bo(my_device, bSizeIn, XCL_BO_FLAGS_NONE, in_0.group_id(0)); - std::cout << STR_PASSED << "auto in_0_bo = xrt::bo(my_device, bSizeIn, XCL_BO_FLAGS_NONE, in_0.group_id(0) (=" << in_0.group_id(0) << "))" << std::endl; - - auto in_0_bo_mapped = in_0_bo.map(); - std::cout << STR_PASSED << "auto in_0_bo_mapped = = in_0_bo.map()" << std::endl; - - //setting input data - memcpy(in_0_bo_mapped, cint16input, bSizeIn); - std::cout << STR_PASSED << "memcpy(in_0_bo_mapped, cint16input, bSizeIn)" << std::endl; - - in_0_bo.sync(XCL_BO_SYNC_BO_TO_DEVICE); - std::cout << STR_PASSED << "in_0_bo.sync(XCL_BO_SYNC_BO_TO_DEVICE)" << std::endl; - - auto in_0_run = in_0(in_0_bo, nullptr, bSizeIn); - std::cout << STR_PASSED << "auto in_0_run = in_0(in_0_bo, nullptr, " << bSizeIn << ")" << std::endl; - - // Starting the output s2mm kernels - auto out_0 = xrt::kernel(my_device, xclbin_uuid, "s2mm:{s2mm_1}"); - std::cout << STR_PASSED << "auto out_0 = xrt::kernel(my_device, xclbin_uuid, \"s2mm:{s2mm_1}\")" << std::endl; - - auto out_0_bo = xrt::bo(my_device, bSizeOut, XCL_BO_FLAGS_NONE, out_0.group_id(0)); - std::cout << STR_PASSED << "auto out_0_bo = xrt::bo(my_device, bSizeOut, XCL_BO_FLAGS_NONE, out.group_id(0) (=" << out_0.group_id(0) << "))" << std::endl; - - auto out_0_bo_mapped = out_0_bo.map(); - std::cout << STR_PASSED << "auto out_0_bo_mapped = out_0_bo.map()" << std::endl; - memset(out_0_bo_mapped, 0x0, bSizeOut); - - auto out_0_run = out_0(out_0_bo, nullptr, bSizeOut); - std::cout << STR_PASSED << "auto out_0_run = out(out_0_bo, nullptr, " << bSizeOut << ")" << std::endl; - - // Starting the AIE kernel - auto my_graph = xrt::graph(my_device, xclbin_uuid, "filter"); - std::cout << STR_PASSED << "auto my_graph = xrt::graph(my_device, xclbin_uuid, \"filter\")" << std::endl; - - my_graph.reset(); - std::cout << STR_PASSED << "my_graph.reset()" << std::endl; - - my_graph.run(iterations); - std::cout << STR_PASSED << "my_graph.run(" << iterations << ")" << std::endl; - - // Waiting for all kernels to end - std::cout << std::endl << STR_INFO << "Waiting for kernels to end..." << std::endl << std::endl; - - in_0_run.wait(); - std::cout << STR_PASSED << "in_0_run.wait()" << std::endl; - -// my_graph.end(); -// std::cout << STR_PASSED << "my_graph.end()" << std::endl; - - out_0_run.wait(); - std::cout << STR_PASSED << "out_0_run.wait()" << std::endl; - - // Retrieving the results - out_0_bo.sync(XCL_BO_SYNC_BO_FROM_DEVICE); - std::cout << STR_PASSED << "out_0_bo.sync(XCL_BO_SYNC_BO_FROM_DEVICE)" << std::endl; - - // Verifying the results - int error_cnt = 0; - std::cout << std::endl << STR_INFO << "Veryfing output data vs. golden ones " << std::endl << std::endl; - for(int i = 0; i < (wSizeOut * 2) - 8; i++) { - if(out_0_bo_mapped[8+i] != golden[i]) { - printf("Error found @ %d, %d != %d\n", i, out_0_bo_mapped[i], golden[i]); - error_cnt++; - } - } - - std::cout << std::endl << ((error_cnt>0) ? STR_FAILED : STR_PASSED) << argv[0] << std::endl << std::endl; - - return ((error_cnt>0) ? EXIT_FAILURE : EXIT_SUCCESS ); -} diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/thin-plat/ps_apps/linux/Makefile b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/thin-plat/ps_apps/linux/Makefile deleted file mode 100644 index 5c7494e194..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/thin-plat/ps_apps/linux/Makefile +++ /dev/null @@ -1,34 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -ECHO := @echo - -APP_DIR := exe -APP_DIRS_EXCLUDE := $(patsubst %/,%,$(dir $(wildcard exe*/))) -APP_DIRS := $(patsubst %/,%,$(dir $(wildcard */))) -APP_NAME := $(filter-out ${APP_DIRS_EXCLUDE},$(APP_DIRS)) -APP_NAME_CLEAN := $(addsuffix .clean,$(APP_NAME)) - -.PHONY: clean help all $(APP_NAME) $(APP_NAME_CLEAN) - -help:: - $(ECHO) "Makefile Usage:" - $(ECHO) " make all" - $(ECHO) " Command to generate the ps_apps used in this design" - $(ECHO) "" - $(ECHO) " make clean" - $(ECHO) " Command to remove all the generated files." - -all: ${APP_DIR} $(APP_NAME) - -$(APP_DIR): - mkdir ${APP_DIR} - -$(APP_NAME): - make all -C $@ - -clean: $(APP_NAME_CLEAN) - rm -rf $(APP_DIR) - -$(APP_NAME_CLEAN): - make clean -C $(basename $@) diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/thin-plat/vitis/ip/Makefile b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/thin-plat/vitis/ip/Makefile deleted file mode 100644 index 368787ac9b..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/thin-plat/vitis/ip/Makefile +++ /dev/null @@ -1,35 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -ECHO := @echo - -XO_DIR := xo_hw -XO_DIRS_EXCLUDE := $(patsubst %/,%,$(dir $(wildcard ${XO_DIR}*/))) -KERNEL_DIRS := $(patsubst %/,%,$(dir $(wildcard */))) -KERNEL_NAME := $(filter-out ${XO_DIRS_EXCLUDE},$(KERNEL_DIRS)) -KERNEL_NAME_CLEAN := $(addsuffix .clean,$(KERNEL_NAME)) - -.PHONY: help clean all $(KERNEL_NAME) - -help:: - $(ECHO) "Makefile Usage:" - $(ECHO) " make all" - $(ECHO) " Command to generate the All IPs used in this design" - $(ECHO) "" - $(ECHO) " make clean" - $(ECHO) " Command to remove all the generated files." - -all: ${XO_DIR} $(KERNEL_NAME) - -$(XO_DIR): - mkdir ${XO_DIR} - -$(KERNEL_NAME): - make all -C $@ - -clean: $(KERNEL_NAME_CLEAN) - rm -rf $(XO_DIR) - -$(KERNEL_NAME_CLEAN): - make clean -C $(basename $@) diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/thin-plat/vitis/ip/aie/Makefile b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/thin-plat/vitis/ip/aie/Makefile deleted file mode 100644 index 987d630f4b..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/thin-plat/vitis/ip/aie/Makefile +++ /dev/null @@ -1,92 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -ECHO := @echo - -PLATFORM_CUSTOM := vck190_thin - -XPFM := ../../xpfm_export/build/platform/${PLATFORM_CUSTOM}/export/${PLATFORM_CUSTOM}/${PLATFORM_CUSTOM}.xpfm - -AIE_WS := . -AIE_SRC := ${AIE_WS}/src -AIE_GRAPHS := ${AIE_SRC}/graphs -AIE_KERNELS := ${AIE_SRC}/kernels -MAP_OPT := BufferOptLevel7 -MAX_CYCLES := 10000 -FLAG = true -MY_APP := fir_graph -TEST_BENCH = ${AIE_SRC}/${MY_APP}.cpp -SIM_OUTPUT = ${AIE_WS}/aiesimulator_output -WORK_DIR = ${AIE_WS}/Work -LOG_FILE = ${AIE_WS}/log -OTHER_OPTS = --kernel-linting -Xchess="-std=c++17" -xlopt=2 --genArchive --pl-register-threshold=125 --log-level=5 --test-iterations=-1 --pl-axi-lite=false -#PL_FREQ = --pl-freq=lte_0:153.6 --pl-freq=lte_1:153.6 --pl-freq=tx_chain0.pccfr_pl:307.2 --pl-freq=tx_chain0.wcfr_pl:307.2 --pl-freq=tx_chain0.dpd_out0:500.0 -PL_FREQ = --pl-freq=500.0 - -TIME_LOG = ${AIE_WS}/timelog -CONSTRAINT_FILE = ${AIE_SRC}/${MY_APP}.aiecst - -AIE_OUTPUT := libadf.a - -#DB -DSPLIB_INCLUDES = -include="$(DSPLIB_ROOT)/L1/include/aie" \ - -include="$(DSPLIB_ROOT)/L1/src/aie" \ - -include="$(DSPLIB_ROOT)/L1/tests/aie/inc" \ - -include="$(DSPLIB_ROOT)/L1/tests/aie/src" \ - -include="$(DSPLIB_ROOT)/L2/include/aie" \ - -include="$(DSPLIB_ROOT)/L2/tests/aie/common/inc" - -.PHONY: help clean all - -help:: - $(ECHO) "Makefile Usage:" - $(ECHO) " make all" - $(ECHO) " Command to generate everything for this design" - $(ECHO) "" - $(ECHO) " make sim_analyzer" - $(ECHO) " Run AIE simulator and generate outputs suitable for Vitis Analyzer" - $(ECHO) "" - $(ECHO) " make get_op" - $(ECHO) " Strip simulator output data from timestamps and copy to new file" - $(ECHO) "" - $(ECHO) " make clean" - $(ECHO) " Command to remove all the generated files." - -all : ${AIE_OUTPUT} -allx86 : clean x86compile x86sim - -#${AIE_OUTPUT}: ${AIE_SRC}/* ${AIE_GRAPHS}/* ${AIE_KERNELS}/* -${AIE_OUTPUT}: ${AIE_SRC}/* ${AIE_GRAPHS}/* - $(MAKE) clean - aiecompiler -target=hw -v --use-phy-shim=${FLAG} ${DSPLIB_INCLUDES} -include=${AIE_SRC} -include=${AIE_GRAPHS} ${TEST_BENCH} ${OTHER_OPTS} -Xmapper=${MAP_OPT} --platform=${XPFM} -workdir=${WORK_DIR} ${PL_FREQ} |& tee ${LOG_FILE} - #aiecompiler -target=hw --dataflow -v --use-phy-shim=${FLAG} --constraints=${CONSTRAINT_FILE} ${DSPLIB_INCLUDES} -include=${AIE_KERNELS} -include=${AIE_SRC} -include=${AIE_GRAPHS} ${TEST_BENCH} ${OTHER_OPTS} -Xmapper=${MAP_OPT} --platform=${XPFM} -workdir=${WORK_DIR} ${PL_FREQ} |& tee ${LOG_FILE} - -sim: - aiesimulator --pkg-dir=$(WORK_DIR) -o $(SIM_OUTPUT) --simulation-cycle-timeout $(MAX_CYCLES) |& tee -a $(LOG_FILE) - -sim_analyzer: - aiesimulator --pkg-dir=$(WORK_DIR) --profile --online -wdb -ctf -o $(SIM_OUTPUT) --simulation-cycle-timeout $(MAX_CYCLES) |& tee -a $(LOG_FILE) - -analyze: - vitis_analyzer -report system.wdb - -get_op: - grep -v T ${SIM_OUTPUT}/data/output0.txt > ${SIM_OUTPUT}/data/output0_raw.txt - grep -v T ${SIM_OUTPUT}/data/output1.txt > ${SIM_OUTPUT}/data/output1_raw.txt - grep -v T ${SIM_OUTPUT}/data/output2.txt > ${SIM_OUTPUT}/data/output2_raw.txt - grep -v T ${SIM_OUTPUT}/data/output3.txt > ${SIM_OUTPUT}/data/output3_raw.txt - -x86sim: - x86simulator --pkg-dir=$(WORK_DIR) |& tee -a $(LOG_FILE) - -clean: - rm -rf Work Work* $(WORK_DIR) - rm -rf .Xil - rm -rf aiesimulator_output aiesimulator.log - rm -rf aiesimulator_output - rm -rf log log* $(LOG_FILE) - rm -rf libadf.a *.xpe *.elf *.db *.soln Map_* xnw* *.lp *.log .xil .Xil *.lp *.db *.log *.exe - -timestamp: - @echo TIME: >> $(TIME_LOG);\ - date +%s >> $(TIME_LOG) diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/thin-plat/vitis/ip/mm2s_aie/Makefile b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/thin-plat/vitis/ip/mm2s_aie/Makefile deleted file mode 100644 index 5f72acdd48..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/thin-plat/vitis/ip/mm2s_aie/Makefile +++ /dev/null @@ -1,35 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -ECHO := @echo - -PLATFORM_CUSTOM ?= vck190_thin - -XPFM := ../../xpfm_export/build/platform/${PLATFORM_CUSTOM}/export/${PLATFORM_CUSTOM}/${PLATFORM_CUSTOM}.xpfm - -KERNEL := mm2s -KERNEL_SRC := ./src/${KERNEL}.cpp -XO := ../xo_hw/${KERNEL}.xo - -.PHONY: clean all help - -help:: - $(ECHO) "Makefile Usage:" - $(ECHO) " make all" - $(ECHO) " Command to generate the hls-mm2s-kernel used in this design" - $(ECHO) "" - $(ECHO) " make clean" - $(ECHO) " Command to remove all the generated files." - -all: ${XO} - -${XO}: ${KERNEL_SRC} ${XPFM} - v++ --compile --debug --save-temps \ - --platform ${XPFM} \ - --kernel ${KERNEL} \ - --output ${XO} \ - ${KERNEL_SRC} - -clean: - rm -f $(XO)* *.log - rm -rf .Xil _x/ diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/thin-plat/vitis/ip/s2mm_aie/Makefile b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/thin-plat/vitis/ip/s2mm_aie/Makefile deleted file mode 100644 index e0880c70ef..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/thin-plat/vitis/ip/s2mm_aie/Makefile +++ /dev/null @@ -1,35 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -ECHO := @echo - -PLATFORM_CUSTOM ?= vck190_thin - -XPFM := ../../xpfm_export/build/platform/${PLATFORM_CUSTOM}/export/${PLATFORM_CUSTOM}/${PLATFORM_CUSTOM}.xpfm - -KERNEL := s2mm -KERNEL_SRC := ./src/${KERNEL}.cpp -XO := ../xo_hw/${KERNEL}.xo - -.PHONY: clean all help - -help:: - $(ECHO) "Makefile Usage:" - $(ECHO) " make all" - $(ECHO) " Command to generate the hls-s2mm-kernel used in this design" - $(ECHO) "" - $(ECHO) " make clean" - $(ECHO) " Command to remove all the generated files." - -all: ${XO} - -${XO}: ${KERNEL_SRC} ${XPFM} - v++ --compile --debug --save-temps \ - --platform ${XPFM} \ - --kernel ${KERNEL} \ - --output ${XO} \ - ${KERNEL_SRC} - -clean: - rm -f $(XO)* *.log - rm -rf .Xil _x/ diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/vitis/src/system.cfg b/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/vitis/src/system.cfg deleted file mode 100644 index 92b9c9e9bc..0000000000 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/vitis/src/system.cfg +++ /dev/null @@ -1,7 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -[connectivity] -stream_connect=mm2s_1.s:ai_engine_0.DataIn1 -stream_connect=ai_engine_0.DataOut1:s2mm_1.s diff --git a/Developer_Contributed/03-HLS_Code_Optimization/LICENSE b/Developer_Contributed/03-HLS_Code_Optimization/LICENSE deleted file mode 100644 index 6ce74ef144..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/LICENSE +++ /dev/null @@ -1,21 +0,0 @@ -The MIT License (MIT) - -Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. - -Permission is hereby granted, free of charge, to any person obtaining a copy -of this software and associated documentation files (the "Software"), to deal -in the Software without restriction, including without limitation the rights -to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -copies of the Software, and to permit persons to whom the Software is -furnished to do so, subject to the following conditions: - -The above copyright notice and this permission notice shall be included in all -copies or substantial portions of the Software. - -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. diff --git a/Developer_Contributed/03-HLS_Code_Optimization/README.md b/Developer_Contributed/03-HLS_Code_Optimization/README.md index a85303c04f..aff65a28f4 100644 --- a/Developer_Contributed/03-HLS_Code_Optimization/README.md +++ b/Developer_Contributed/03-HLS_Code_Optimization/README.md @@ -19,1483 +19,10 @@ - Last update: 06 Sep 2024 - -## Table of Contents - -[Introduction](#introduction) - -[0 Project Setup](#project-setup) - -[1 Fixed Point FIR Filter](#1-fixed-point-fir-filter) - -[2 Floating Point FIR Filter](#2-floating-point-fir-filter) - -[3 Median Filter for Image Processing](#3-median-filter-for-image-processing) - -[4 Compute the Histogram of an Image](#4-compute-the-histogram-of-an-image) - -[5 Image Histogram Equalization](#5-image-histogram-equalization) - -[6 Square Root](#6-square-root) - -[7 Atan2](#7-atan2) - -[8 Vector Addition](#8-vector-addition) - -[9 Floating Point Matrix Multiplication](#9-floating-point-matrix-multiplication) - -[10 Two Examples with Vitis Acceleration Flow Running on HW](#10-two-examples-with-vitis-acceleration-flow-running-on-hw) - -[Appendix](#appendix) - -[References](#references) - -[Support](#support) - -[License](#license) - -## Introduction - -This tutorial explains how to properly optimize C/C++ code suitable for DSP designs and algorithms to get the maximum performance in terms of **lowest latency with maximum throughput** with the AMD Vitis™ HLS design flow. - -You will also see how to create an embedded system running on either [ZCU102](https://www.xilinx.com/products/boards-and-kits/ek-u1-zcu102-g.html) or [VCK190](https://www.xilinx.com/products/boards-and-kits/vck190.html) embedded board, which includes one of the IP cores (acknowledged as "kernel") designed with Vitis HLS, with either makefile- or GUI-based flow. - -Within a "simplified" HLS terminology: - -- **Latency** is the amount of clock cycles estimated by the Vitis HLS scheduler among the first input and the last output of a certain function. -- **Initialization_Interval** (shortly **II**) is the amount of clock cycles between two events (either two subsequent calls to the same function or two following iterations in the same loop) and it is intimately related to the **throughput**, which is given by **Estimated_Clock_Frequency/Initialization_Interval**. - -In some cases, the maximum performance can be obtained just with Vitis HLS compiler directives without touching the code. In other cases, this might also require some code change to "help" the compiler do a better job. There is not a single solution that fits for all possible applications as each application is a world in itself. But the examples illustrated here cover a large variety of cases seen in recent years across the globe, as the most representative to illustrate "good" coding style for HLS. - -In the following document, it is assumed you have named this tutorial repository ``03-HLS_Code_Optimization`` and placed it in a certain working directory ``${WRK_DIR}`` (for example, in this case, ``export WRK_DIR=/media/danieleb/DATA/2024.1/Vitis-Tutorials/Developer_Contributed``). - -The organization of the folders tree of this tutorial is illustrated here: - -``` -${WRK_DIR} -| -└── 03-HLS_Code_Optimization - | - ├── README.md - ├── run_all.sh - ├── files - | ├── docs - | ├── examples - | | ├── 1_fix_fir_filter - | | ├── 2_float_fir_filter - | | ├── 3_img_median_filter - | | ├── 4_dependency - | | ├── 5_img_histEq - | | ├── 6_sqrt - | | ├── 7_atan2 - | | ├── 8_vector_add - | | | ├── make-flow (zcu102 only) - | | ├── 9_matrix_mult - | | | ├── make-flow - | | | | ├── zcu102 - | | | | ├── vck190 - | | - | ├── images - | ├── log - | ├── scripts -``` - -The shell script named [run_all.sh](files/run_all.sh) contains the commands to launch the Vitis HLS flow on all the applications placed in the [examples](files/examples) folder. -Once you have setup the environment properly, according to what is described in the next section, you can run the script with the command: - -```shell -cd /${WRK_DIR}/03-HLS_Code_Optimization/files -#source ./scripts/_sample_env_setup.sh -source ./run_all.sh -``` - -Note that the Vitis HLS flow adopted in this tutorial is composed of three major steps: - -- Functional C Simulation (known as **csim** in HLS terminology) -- Synthesis from C/C++ to RTL (known as **syn**) -- Cycle accurate C/RTL Simulation (known as **sim**) - -The fourth step, known as Implementation (known as **imp**), is applied transparently by the Vitis Acceleration flow as described in section [10 Two Examples with Vitis Acceleration Flow Running on HW](#10-two-examples-with-vitis-acceleration-flow-running-on-hw), by applying either makefile-based flow or Vitis GUI-based flow. - -### Warnings - -1. Everything shown in this project used an Ubuntu 22.04 Desktop with related Vitis 2024.1 release. - -2. It is recommended to write the SD card that boots the VCK190 board with the Windows OS utility called [Win32 Disk Imager 1.0](https://sourceforge.net/projects/win32diskimager/). - -3. Some figures are screenshots related to the earlier release of Vitis and there might be a few differences, although minimal, with the current one. - -4. It is recommended that you set up the environment correctly before running any script, as described in details in the next subsection. The ``*_sample_env_seytup.sh`` [scripts](files/scripts) contain a template to be customized for your needs. - -5. The [run_all.sh](files/run_all.sh) must always be launched **only after** all the variables of previous script have been set at least once, and **only from** the [files](files) folder, which has to be your current directory. - -6. Read the entire README.md document carefully before launching any script or Makefile. - -### Vitis HLS Classic IDE - -According to the [000036339 2024.1](https://support.xilinx.com/s/article/000036339?language=en_US) article the Vitis HLS 2024.1 -release adopts a new GUI, therefore the "classic" command: -``` -vitis_hls your_script_file.tcl -``` -is now deprecated and should be replaced by the new command: -``` -vitis-run --mode hls --tcl your_script_file.tcl -``` -To call the old, classic HLS GUI you have to use this new command: -``` -vitis_hls --classic -``` - - -### Dos-to-Unix Conversion - -In case you experience some unexpected errors during the execution of the scripts, once pre-process all the``*.sh``, ``*.cpp``, ``*.h`` files with the [dos2unix](http://archive.ubuntu.com/ubuntu/pool/universe/d/dos2unix/dos2unix_6.0.4.orig.tar.gz) utility. -In that case, run the following commands from your Ubuntu host PC: - -```bash -#sudo apt-get install dos2unix -cd #your working directory -for file in $(find . -name "*.sh" ); do dos2unix ${file}; done -for file in $(find . -name "*.tcl"); do dos2unix ${file}; done -for file in $(find . -name "*.h" ); do dos2unix ${file}; done -for file in $(find . -name "config" ); do dos2unix ${file}; done -for file in $(find . -name "*.c*" ); do dos2unix ${file}; done -for file in $(find . -name "*akefile" ); do dos2unix ${file}; done -``` - -### Cleaning the Project - -To clean the project files launch the following commands: - -``` -cd /${WRK_DIR}/03-HLS_Code_Optimization/files/examples -make clean -make vck190_clean -make zcu102_clean -``` - -## Project Setup - -### 0.1 Archives Download - -You need the following archives, in particular: - -- From [Vitis (SW Developer) Downloads](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/vitis.html) area, take the **2024.1 Vitis Installer** (it makes the Vitis install process easy) and the **2024.1 Vitis Update** (if any). - -- From [Vitis Embedded Platforms](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-platforms.html) area, take the **Common Images for Embedded Vitis Platforms 2024.1**. - -- From [PetaLinux](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-design-tools.html) area, take the **2024.1 PetaLinux Tools Installer**. - -- Go to the bottom of [PetaLinux 2024.1- Product Update Release Notes and Known Issues](https://support.xilinx.com/s/article/000036178?language=en_US) and take **2024.1_PetaLinux_Package_List.xlsx** file, which contains all the packages needed by PetaLinux into your Ubuntu OS computer (install all of them before installing PetaLinux). - -- Go to the [Xilinx GitHub page](www.github,com/Xilinx) and zip both the [Vitis Libraries](https://github.com/Xilinx/Vitis_Libraries) and [Vitis Tutorials](https://github.com/Xilinx/Vitis-Tutorials) with branch related to this 2024.1 release. - -- Go to the [AMD Alveo™ Packages](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/alveo.html) area, select release 2024.1 and Ubuntu 22.04 OS, and then take the **Xilinx Runtime (XRT)** archive. - - -At the end, you should have something like the following files: - -```text -Xilinx_Unified_2024.1_*_Lin64.bin -Xilinx_Vivado_Vitis_Update_2024.1_*.tar.gz -xilinx-versal-common-v2024.1_*.tar.gz -Vitis_Libraries-main.zip -Vitis-Tutorials-2024.1.zip -xrt_202410.*-amd64-xrt.deb -``` - -First, install the basic version of Vitis 2024.1 via its installer ``Xilinx_Unified_2024.1_*_Lin64.bin``, and then its update ``Xilinx_Vivado_Vitis_Update_2024.1_*.tar.gz``. -Everything is placed in the ``/tools/Xilinx/`` folder. - -### 0.2 Sudo or not Sudo? - -You **might** need ``sudo`` privilege to install the tools on these folders, primarily ``/tools`` and ``/opt``, unless you change the ownership and group of those folders accordingly. - -In fact, if you created the ``/tools`` directory as a super-user (or ``root``, or with ``sudo``), whatever you wish to write/install there can only be done by the ``root`` super-user. -This is a basic Linux OS behavior. However, you can change the group and owner so that you can do what you like as a normal user, the way you do it in your ``$HOME`` directory. - -So, if you run the following commands (and you need ``sudo``): - -```shell -sudo su -mkdir /tools -mkdir /opt -# -R stays for recursively on each subfolder -chown -R you_user_name /tools -chgrp -R you_user_name /tools -chown -R you_user_name /opt -chgrp -R you_user_name /opt -exit -``` -you can install the above tools and archives without ``sudo`` privilege, just as a normal user. -This means installation with user rights works as well: some people in some forums mentioned that this is not possible, but perhaps they do not know these Linux OS concepts. - -As a last cross-check, if you installed the tools as a normal user, you should see the hidden folder ``.Xilinx`` inside your ``$HOME`` directory. If you installed them as a super-user, you should see the hidden folder ``.Xilinx`` inside your ``/root`` directory. - -In case of installation done with the ``sudo`` privilege, there seems to be only a small issue with one line in the ``installLibs.sh`` script: - -```shell -su - $user -c "touch $logFile; chmod 777 $logFile" -``` - -The ``touch`` and ``chmod`` commands cannot be executed because the logfile is located below the ``/root`` directory and the shell was switched to a normal user without root privileges. -This means that the script assumes that the installation was done without root privileges. That line in the script could be replaced by following commands: - -```shell -sudo touch $logFile -sudo chmod 777 $logFile -``` - -In conclusion, either the installation is done with root privileges (``sudo``), then the ``installLibs.sh`` needs to be changed or the installation is done as a normal user. - -### 0.3 Installing Common for Target Boards - -Install the two archives ``xilinx-*-common-v2024.1_*.tar.gz`` in the ``/opt/xilinx/common/`` folder (which has to be into an ``ext4`` file system, not on an ``NTFS`` one). - -Then execute the following commands as a normal user, according to what discussed is in the previous sub-section: - -```shell -cd /opt/xilinx/common/xilinx-versal-common-v2024.1/ -chmod 777 sdk.h # only if needed -./sdk.sh -p -y -d . -cd /opt/xilinx/common/xilinx-zynqmp-common-v2024.1/ -chmod 777 sdk.h # only if needed -./sdk.sh -p -y -d . -``` - -Check that ``rootfs.ext4`` is not compressed as ``rootfs.ext4.gz``; otherwise, you have to manually decompress it. -If you want to save storage space, you can remove both ``sdk.sh`` files as they are large. - -### 0.4 Install XRT - -The easiest way to download XRT is from the [ALVEO](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/alveo.html) site. -Select the ALVEO U200 card and then the Ubuntu 22.04 OS to arrive at this [link](https://www.xilinx.com/bin/public/openDownload?filename=xrt_202410.2.17.319_22.04-amd64-xrt.deb). - -Then install the archive via the following command: - -```shell -sudo apt install --reinstall ./xrt_.deb -``` - -To set ``xrt`` into your terminal, you need the following command: - -```shell -source /opt/xilinx/xrt/settings.sh -``` - -which was also put in the scripts ``*_sample_env_setup.sh``. - -### 0.5 Petalinux - -**WARNING: You cannot install PetaLinux into an NFS driver; otherwise, the install process ends with a non-predictable error message**. - -Before installing ``petalinux``, check in the Excel foil ``2024.1_PetaLinux_Package_List.xlsx`` what all packages ``petalinux`` requires. Once done, install the missing ones. - -``` -#create the destination folder -sudo mkdir /petalinux_2024.1 -#change permissions -$ chmod 777 ~/Downloads/petalinux-v2024.1-*-installer.run -$ ~/Downloads/petalinux-v2024.1-*-installer.run -d /petalinux_2024.1 - -. . . - -INFO: Installing PetaLinux... -INFO: Checking PetaLinux installer integrity... -INFO: Installing PetaLinux to "/petalinux_2024.1/." -INFO: Installing buildtools in /petalinux_2024.1/./components/yocto/buildtools -INFO: Installing buildtools-extended in /petalinux_2024.1/./components/yocto/buildtools_extended -INFO: PetaLinux has been installed to /petalinux_2024.1/. -``` - -To set ``petalinux`` into your terminal, you need the following command: - -```shell -source /petalinux_2024.1/settings.sh -``` - -which was also placed in the script ``*_sample_env_setup.sh``. - -### 0.6 Setup the Environment - -The ``*_sample_env_setup.sh`` [scripts](files/scripts) create the proper environmental variables for either the ZCU102 or the VCK190 target boards respectively on the Ubuntu Desktop. Ensure that they are executable by setting their permissions correctly. Note that they are mutually exclusive and must be launched at least once in the shell window you are using, before doing anything else: - -```shell -cd /${WRK_DIR}/03-HLS_Code_Optimization/files -# make both scripts executable -chmod a+x scripts/*_sample_env_setup.sh -# select one of the next two lines -source scripts/*_zcu102_sample_env_setup.sh ## valid for ZCU102 only -source scripts/*_vck190_sample_env_setup.sh ## valid for VCK190 only -# to build all the design examples -#source ./run_all.sh -``` - -### 0.7 Makefiles and TCL scripts - -Each of the nine [examples](files/example) illustrated in this tutorial comes with their own ``*_script.tcl`` and ``Makefile`` and you can use one of them alternatively to run the three HLS design flow steps (cism, syn, sim), with commands like these: -``vitis-run --mode hls --tcl *_script.tcl`` if you want to use the TCL scripts or ``make all`` if you want to apply the related makefiles. -It is recommended that you read the source code of these files carefully to understand their applications. - -Note that running ``make clean`` from the ``files/examples`` folder cleans all the nine HLS designs and the three Vitis embedded designs. - - -## 1 Fixed Point FIR Filter - -In this section, you will analyze a single rate FIR filter design and apply a step-by-step approach through the most important HLS directives to increase the performance - lower latency and higher throughput (happening when **II=1**). The FIR filter has 16 coefficients (or "taps"). - -The code in this subsection applies [fractional arbitrary precision data types](https://docs.amd.com/r/en-US/ug1399-vitis-hls/Using-Arbitrary-Precision-Data-Types) from the ``ap_fixed.h`` library. The Vitis HLS project ``vhls_fix_fir_prj`` has eight solutions to illustrate the different usage of some HLS compiler directives. More information can be found in the related HLS TCL script named ``fix_fir_filter.tcl``. - -Once you have setup the Vitis HLS environment, launch the following shell commands (they are already included in the [run_all.sh](files/run_all.sh) script): - -```bash -cd /${WRK_DIR}/03-HLS_Code_Optimization/files/examples -cd 1_fix_fir_filter -vitis-run --mode hls --tcl fix_fir_script.tcl -``` - -Alternatively, you can execute the following commands: - -```bash -cd /${WRK_DIR}/03-HLS_Code_Optimization/files/examples -make hls_kernels -``` - -Note that ``make hls_kernels`` processes all nine HLS design examples by launching their appropriate TCL scripts. - -Figure 1-1 illustrates the estimated performance of the different solutions in terms of **Latency**, **Initialization_Interval** and FPGA resources (**LUT**, **FF**, **RAM**, **DSP**), in particular: - -- ``sol1_baseline`` shows what you get from HLS compiler without any optimization. Note the ``set_directive_pipeline -off "fir_filter/Shift_Accum_Loop"`` in the file ``directives1.tcl`` to "force" the HLS compiler doing no optimizations. - -- ``sol2_LoopPipeline`` shows what you get by pipelining the internal loop with ``set_directive_pipeline "fir_filter/Shift_Accum_Loop"`` in the file ``directives2.tcl``. As expected, the latency is reduced to a significant level because of this HLS directive. - -- ``sol3_shiftregPartition`` is like the previous solution plus the ``set_directive_array_partition -dim 1 -type complete "fir_filter" shift_reg``, in the file ``directives3.tcl``, to map the array ``shift_reg`` (which models the tapped delay line of the FIR filter) into a set of 16 standalone registers, which help the compiler to schedule better the operations and reduce further latency. - -- ``sol4_loopUnroll`` is like the previous solution plus ``set_directive_unroll -factor 16 "fir_filter/Shift_Accum_Loop"``, in the file ``directives4.tcl``; now the loop is fully unrolled and you can see that the DSP resources utilized to implement the MAC (multiply-and-accumulate) operation are now 16 instead of 1 of the previous solution. Also, this directive allows for further latency reduction. - -- ``sol5_coeffPartition`` is like the previous solution plus ``set_directive_array_partition -dim 1 -type complete "fir_filter" c``, in the file ``directives5.tcl``. Now, even the input array of coefficients (variable ``c``) is partitioned in a set of registers, and you can see this by looking at the interfaces reported in the file ``fir_filter_csynth.rpt`` changed from: - -``` -+-----------+-----+-----+------------+--------------+--------------+ -| RTL Ports | Dir | Bits| Protocol | Source Object| C Type | -+-----------+-----+-----+------------+--------------+--------------+ -|c_address0 | out| 4| ap_memory| c| array| -|c_ce0 | out| 1| ap_memory| c| array| -|c_q0 | in| 18| ap_memory| c| array| -|c_address1 | out| 4| ap_memory| c| array| -|c_ce1 | out| 1| ap_memory| c| array| -|c_q1 | in| 18| ap_memory| c| array| -``` - -in solution 4 to - -``` -+-----------+-----+-----+------------+--------------+--------------+ -| RTL Ports | Dir | Bits| Protocol | Source Object| C Type | -+-----------+-----+-----+------------+--------------+--------------+ -|c_0 | in| 18| ap_none| c_0| pointer| -. . . -|c_15 | in| 18| ap_none| c_15| pointer| -+-----------+-----+-----+------------+--------------+--------------+ -``` - -in solution 5; - -- ``sol6_II1_top`` is like the previous solution plus ``set_directive_pipeline -II 1 "fir_filter"``, in the file ``directives6.tcl``. Now you have achieved II=1 for the top function. Note that the effective data rate is now equal to the estimated clock frequency because of II=1. Note that this solution has the lowest latency among the previous ones. - -- ``sol6b_II1_top`` generates the same performance of ``sol6_II1_top`` with only three directives in the file ``directives6b.tcl``. This was done to illustrate that pipelining a function at the top level (``set_directive_pipeline -II 1 "fir_filter"``) is quite aggressive but it could also be risky as it forces **unrolling of all internal loops**, which could make the resources utilization to grow too much. Note that you need the ``set_directive_array_partition -dim 1 -type complete "fir_filter" c`` to partition the input array of coefficients, as this array is an I/O parameter ("out of the top function", using an improper terminology). So, I strongly recommend to apply one directive at a time, as done from solution 1 to 6, instead of starting to pipeline the function at top level; - -- In ``sol7_II2_8DSP``, ``sol7_II4_4DSP`` and ``sol7_II8_2DSP`` you can see how using jointly ``set_directive_pipeline -II X "fir_filter"`` and ``set_directive_allocation -limit Y -type operation "fir_filter" mul`` -to use the DSP slices (for the MAC operations) in Time-Division-Multiplexing. -Note that ``X`` and ``Y`` stay in the equation ``Y = 16 / X``. In fact if you have 16 taps, you need 16 MAC operations. If you limit them to be only ``Y=8`` - to make an example, the ``II`` becomes ``16/Y`` and the data rate changes accordingly. Note that this behavior is the effect of the two directives applied together. - -- ``sol8_integers`` applies the same directives of ``sol6_II1_top`` and it was compiled with ``-DHLS_FIXED_POINT`` to replace the ``signed int`` ANSI-C data types with ``ap_fixed<18,2>`` HLS proprietary fixed point data. Now the latency is only 1 clock cycle. - -![figure1-1](files/images/fix_fir1_comparison.png) - -*[Figure 1-1] Fixed-Point FIR Filter designed with Vitis HLS: estimated performance of the various solutions from 1 to 8.* - -## 2 Floating Point FIR Filter - -The Vitis HLS project ``vhls_float_fir_prj`` applies the same code of previous section with the same directives, but with 32-bit floating point data types. - -Once you have setup the Vitis HLS environment, launch the following shell commands (they are already included in the [run_all.sh](files/run_all.sh) script): - -```bash -cd /${WRK_DIR}/03-HLS_Code_Optimization/files -#source ./run_all.sh -cd examples/2_float_fir_filter -vitis-run --mode hls --tcl float_fir_script.tcl -``` - -Alternatively, you can execute the following commands: - -```bash -cd /${WRK_DIR}/03-HLS_Code_Optimization/files/examples -make hls_kernels -``` - -Note that ``make hls_kernels`` processes all nine HLS design examples by launching their appropriate TCL scripts. - -This section shows how the directive ``set_directive_bind_op`` can force the adoption of a certain AMD Vivado™ floating point IP core (illustrated in Figure 2-1), which influences the estimated performance in terms of Latency, Initialization_Interval, and FPGA resources. - -Figure 2-2 shows how trading ``LUT`` vs. ``DSP`` FPGA resources with the ``BIND_OP`` directive with floating point operators and the related variables. - -Note that there are four possible cores to implement a 32-bit floating point multiplication, ``fabric`` (using no DSP slices), ``meddsp`` (using 1 DSP slice), ``fulldsp`` (using 2 DSP slices), and ``maxdsp`` (using 3 DSP slices). -There are two possible cores to implement a 32-bit floating point addition, ``fabric`` (using no DSP slices) and ``fulldsp`` (using 2 DSP slices). - -More information can be found in the HLS TCL script named ``float_fir_filter.tcl``. - -From ``sol0`` to ``sol3``, the floating point operation is progressively bound to more and more DSP slices. Note that ``sol4`` is there only to illustrate how to get a II=1 from a floating point design like this (based on ``sol3``). You get 80 DSP slices because the loop is fully unrolled and there are 16 MAC operations, each using 5 DSP slices. - -![figure2-1](files/images/float_fir_directives.png) - -*[Figure 2-1] Vitis HLS BIND_OP directive to bind a C/C++ variable (i.e., "mult") to an FPGA operator (i.e., "fmul_maxdsp").* - -![figure2-2](files/images/float_fir_comparison.png) - -*[Figure 2-2] Floating-Point FIR Filter designed with Vitis HLS: estimated performance of the various solutions from 0 to 3 (sol4 is like sol3 but with II=1).* - -## 3 Median Filter for Image Processing - -[This article](https://issuu.com/xcelljournal/docs/xcell_journal_issue_86/20) describes a 2D median filter for image processing based on a sorting network, it was public in year 2014 but it is still a good example of how to improve the performance of a naively-written code (in this case a median filter) by changing the code to directly model local memory as if it was in a real hardware implementation. This code change dramatically helps the HLS compiler achieve better performance, in terms of both higher throughput and shorter latency. - -Note that when you achieve **II=1** in the innermost loop, your design is effectively working at pixel rate. So the entire latency to process the whole image is basically slightly larger than the image size (in estimated clock cycles). This happens because the IP core you create works on the entire image. - -Once you have setup the Vitis HLS environment, launch the following shell commands (they are already included in the [run_all.sh](files/run_all.sh) script): - -```bash -cd /${WRK_DIR}/03-HLS_Code_Optimization/files -#source ./run_all.sh -cd examples/3_img_median_filter -vitis-run --mode hls --tcl run_median_script.tcl -``` - -Alternatively, you can execute the following commands: - -```bash -cd /${WRK_DIR}/03-HLS_Code_Optimization/files/examples -make hls_kernels -``` - -Note that ``make hls_kernels`` processes all nine HLS design examples, by launching their appropriate TCL scripts. - -### 3.1 Naive Implementation - -This code is named "naive" as it assumes that all the pixels of the image (with size 1920x1080) are accessed from an external memory independently on each other, which is impossible because in reality, all the pixels flow in a stream from top-left corner to bottom-right corner of the 2D array composing the image (the so called "raster-scan" order). Due to this, the HLS compiler achieves only an **II=5** in the inner loop, thus generating a huge latency for filtering the entire image. Figure 3-1 reports the II=5 in red color from the ``hls_naive_median3x3_prj`` Vitis HLS project. - -![figure3-1](files/images/fig3-1.png) - -*[Figure 3-1] Vitis HLS Synthesis Estimation of a 2D naive median filter code. Note that II=5 (in red color).* - -### 3.2 Implementation with Local Memory - -Respect to the naive case, this code is much more optimized as it contains N local memories called **Line Buffers**, which are more typical of hardware designs than of software designs. Each Line-Buffer stores an entire horizontal line of the 2D image. If the filter kernel size is NxN, you need N Line Buffers. In this design case, N can assume the values of either 3 or 5 or 7. -Furthermore, the NxN **sliding window** is also modeled in the code, thus shifting from left to right for an efficient implementation of the 2D filter behavior. - -Sorting the data to generate the median value is applied via a **sorting network** algorithm, which allows for better performance by exploiting the inner parallel resources in the FPGA when N is not a large number (the sorting network resources increase linearly with N). - -Note that the HLS compiler uses only N-1 ``BRAM_18K`` (memory resources) instead of N (with N=3,5,7) because it considers that the current incoming line does not need to be stored locally. The larger the N, the larger the amount of FF and LUT to implement the sliding window and sorting network (both have an NxN size). - -Figure 3-2 illustrates the HLS Synthesis Estimation of a median filter with three examples of 2D window size (from the ``hls_median_prj`` project), 3x3, 5x5 and 7x7. They all work at a pixel rate. The following figure indicates the easiness of the architectural exploration job with a tool like HLS. - -![figure3-2](files/images/fig3-2.png) - -*[Figure 3-2] Vitis HLS Synthesis Estimation of a 2D optimized median filter based on Line-Buffers directly coded with sliding window sizes of 3x3 (left) 5x5 (central) and 7x7.* - -## 4 Compute the Histogram of an Image - -In this section, you compute the histogram of an image. -This HLS example applies the ``set_directive_dependence`` directive on an array mapped to a **True Dual Port RAM** by the ``#pragma HLS BIND_STORAGE variable=hist type=ram_t2p impl=bram``. - -Once you have setup the Vitis HLS environment, launch the following shell commands (they are already included in the [run_all.sh](files/run_all.sh) script): - -```bash -cd /${WRK_DIR}/03-HLS_Code_Optimization/files -#source ./run_all.sh -cd examples/4_dependency -vitis-run --mode hls --tcl run_dependence_script.tcl -``` - -Alternatively, you can execute the following commands: - -```bash -cd /${WRK_DIR}/03-HLS_Code_Optimization/files/examples -make hls_kernels -``` - -Note that ``make hls_kernels`` processes all nine HLS design examples by launching their appropriate TCL scripts. - -The ``dependence directive`` is an advanced HLS concept. Therefore, it is suggested to read [Managing-Pipeline-Dependencies](https://docs.amd.com/r/en-US/ug1399-vitis-hls/Managing-Pipeline-Dependencies) from UG 1399 carefully to understand the argument better. - -The code to illustrate how to use this directive is just one statement as ``hist[val] = hist[val]+1``. It is normally applied when computing the histogram of an image. - -The Vitis HLS compiler maps the ``hist[]`` array into a Dual Port Block RAM of the FPGA with the ``#pragma HLS BIND_STORAGE variable=hist type=ram_t2p impl=bram`` directive. - -At runtime execution, it might happen that while storing the n-th sample at address ``val``, the n+1 sample is read again at address ``val``. This behavior is managed by assuming a **Read After Write** policy (shortly RAW) between the two ports of the same BRAM in the hardware world. -To avoid possible issues, the HLS compiler in most cases schedules the code in a way to get II=2. In fact, in a perfectly pipelined design with II=1, if for any reason the HLS compiler has scheduled two writes at the same address, then at runtime execution, there will be a collision. Also, the RAW policy generates a not-valid output, which is captured **ONLY** by the cycles accurate simulation **sim**, whereas the simple functional C simulation **csim** generates no errors. - -This scenario happens in ``sol1_orig_depINTER_RAW`` solution of the ``hls_dep_prj`` project if you use the -``set_directive_dependence -dependent false -direction RAW -type inter -variable hist "top_histogram"`` -and here is what you see in the cycle accurate simulation: - -```text -$finish called at time : 21942500 ps : File "/media/danieleb/DATA/2023.2/Vitis-Tutorials-2023.2/Developer_contributed/03-HLS_Code_Optimization/files/examples/4_dependency/hls_dep_prj/sol1_orig_depINTER_RAW/sim/verilog/top_histogram.autotb.v" Line 389 -## quit -INFO: [Common 17-206] Exiting xsim at Mon Sep 26 17:28:01 2022... -got 23 expected 24 -got 22 expected 23 -got 21 expected 22 -got 17 expected 18 -got 18 expected 19 -got 15 expected 16 -got 19 expected 20 -got 18 expected 19 -got 17 expected 18 -got 11 expected 12 - -TEST FAILED: 10 wrong values -INFO: [COSIM-1000] *** C/RTL co-simulation finished: FAIL *** -``` - -In all other situations, you have a perfect match between functional and cycle accurate simulations. It is summarized in the following table: - - -| solution | II | latency | Cycle Accurate Sim | -| :--- | :----: | ---: | :--- | -| sol0: default | 1 | 4362 | PASS | -| sol1: inter WAR | 1 | 4362 | PASS | -| sol1: inter RAW | 1 | 4362 | FAIL | -| sol1: intra RAW | 2 | 8457 | PASS | -| sol2: default | 2 | 8458 | PASS | -| sol3: inter RAW | 2 | 8458 | PASS | -| sol3: inter WAR | 2 | 8458 | PASS | -| sol3: intra RAW | 1 | 4362 | PASS | - - -Figure 4-1 illustrates the various solutions of ``hls_dep_prj`` project. - -In ``sol0_orig_default``, the compiler works without any directive from the user and achieves II=1 and a maximum latency of 4362 cycles. This is the same result that can be achieved by the user in ``sol1_orig_depINTER_WAR`` with -``set_directive_dependence -dependent false -direction WAR -type inter -variable hist "top_histogram"``, which explains what the HLS compiler made by default. - -If you try to use the ``set_directive_dependence -dependent false -direction RAW -type inter -variable hist "top_histogram"`` as in ``sol1_orig_depINTER_RAW``, you get the same maximum latency and II, but the cycle accurate simulation now fails. - -On the other hand, if you try to adopt the -``set_directive_dependence -dependent false -direction RAW -type intra -variable hist "top_histogram"`` as in the ``sol1_orig_depINTRA``, the HLS compiler schedules code with II=2 and so you get twice the latency of previous cases. - -The simple code - -``` -L1:for (int i=0; i`` using a cordic implementation of atan2(). See file ``cordic_atan2.cpp``. - -- ``solution1_cordic_bitaccurate`` is like the previous solution. It is just more optimized for less resources occupation. - -It is evident that the latency, as well as the resources occupation, reduces by lowering the width in bits of the data. - -![figure7-1](files/images/atan2.png) - -*[Figure 7-1] Vitis HLS Synthesis Estimation solution for atan2() case study.* - -## 8 Vector Addition - -This example applies the **load/compute/store coding style**, which is generally the most efficient for implementing kernels when using HLS: - -1. The load and store functions are responsible for moving data in and out of the kernel as efficiently as possible. - -2. The core functionality is decomposed across one or more compute functions. - -3. Whenever possible, the compute function should pass data through **HLS stream objects** and should contain a single set of nested loops. - -4. HLS stream objects are used to pass data between producer and consumer functions. Stream read and write operations have a blocking behavior, which allows consumers and producers to synchronize with each other automatically. - -5. The **dataflow pragma** instructs the compiler to enable task-level pipelining so that all subroutines run in parallel (as a concurrent process in VHDL). - -This is required to load/compute/store functions to execute in a parallel -and pipelined manner. Here the kernel loads, computes, and stores ``size`` integer values per clock cycle and is implemented below (see [hls_krnl_vadd.cpp](files/examples/8_vect_add/src/hls_krnl_vadd.cpp) file): - -```text -/* - Vector Addition Kernel - Arguments: - in1 (input) --> Input vector 1 - in2 (input) --> Input vector 2 - out (output) --> Output vector - size (input) --> Number of elements in vector -*/ - -void krnl_vadd(uint32_t* in1, uint32_t* in2, uint32_t* out, int size) -{ -#pragma HLS INTERFACE m_axi port = in1 bundle = gmem0 -#pragma HLS INTERFACE m_axi port = in2 bundle = gmem1 -#pragma HLS INTERFACE m_axi port = out bundle = gmem0 - - static hls::stream in1_stream("input_stream_1"); - static hls::stream in2_stream("input_stream_2"); - static hls::stream out_stream("output_stream"); - -#pragma HLS dataflow //to run following routines as parallel tasks - load_input(in1, in1_stream, size); - load_input(in2, in2_stream, size); - compute_add(in1_stream, in2_stream, out_stream, size); - store_result(out, out_stream, size); -} -``` - -Once you have setup the Vitis HLS environment, launch the following shell commands (they are already included in the [run_all.sh](files/run_all.sh) script): - -```bash -cd /${WRK_DIR}/03-HLS_Code_Optimization/files -#source ./run_all.sh -cd examples/8_vect_add -vitis-run --mode hls --tcl run_vect_add_script.tcl -``` - -Alternatively, you can execute the following commands: - -```bash -cd /${WRK_DIR}/03-HLS_Code_Optimization/files/examples -make hls_kernels -``` - -Note that ``make hls_kernels`` processes all nine HLS design examples by launching their appropriate TCL scripts. - -Figures 8-1 and 8-2 show the HLS Synthesis Estimation and the Dataflow View respectively related to the ``solution_vitis`` solution targeting the Vitis flow. - -![figure8-1](files/images/vectadd_syn.png) - -*[Figure 8-1] Vitis HLS Synthesis Estimation of Vector Addition case study (Vitis flow solution).* - -![figure8-2](files/images/vectadd_dataflow.png) - -*[Figure 8-2] Dataflow View of Vector Addition case study (Vitis flow solution).* - -## 9 Floating Point Matrix Multiplication - -In this section, you will deal with the matrix multiplier (matrix size 32x32, 32-bit floating point data) described in [XAPP1170: A Zynq Accelerator for Floating Point Matrix Multiplication Designed with Vivado HLS](https://www.xilinx.com/support/documentation/application_notes/xapp1170-zynq-hls.pdf) v2.0 of 21 Jan 2016, which was designed with Vivado 2015.4 System Edition released at that time. - -Similar to what is done in the previous section, this example also applies to the load/compute/store coding style. - -Furthermore, note that this HLS design makes use of **C++ templates** and **unions data types** to model the AXI4-Stream interfaces, as shown in the following code fragment taken from [mmult.h](files/examples/9_matrix_mult_z/src/mmult.h) header file: - -``` -// functions to insert and extract elements from an axi stream -// includes conversion to correct data type -template -T pop_stream(hls::stream< ap_axis> &inp_stream) -{ - ap_axis e; - inp_stream.read(e); - union - { - int ival; - T oval; - } converter; - converter.ival = e.data; - T ret = converter.oval; - - ap_uint strb = e.strb; - ap_uint keep = e.keep; - ap_uint user = e.user; - ap_uint<1> last = e.last; - return ret; -} -``` - -Once you have setup the Vitis HLS environment, launch the following shell commands (they are already included in the [run_all.sh](files/run_all.sh) script): - -```bash -cd /${WRK_DIR}/03-HLS_Code_Optimization/files -#source ./run_all.sh -cd examples/9_matrix_ mult -vitis-run --mode hls --tcl run_matrix_mult_script.tcl -``` - -Alternatively, you can execute the following commands: - -```bash -cd /${WRK_DIR}/03-HLS_Code_Optimization/files/examples -make hls_kernels -``` - -Note that ``make hls_kernels`` processes all nine HLS design examples by launching their appropriate TCL scripts. - -Two HLS projects are then created: - -- ``hls_mmult_prj``, which contains the standalone matrix multiplier core from the baseline ``solution1`` to the most optimized ``solution3``; - -- ``hls_wrapped_mmult_prj``, which contains the previous core of ``solution3`` wrapped with some C++ functions to model the AXI4-Stream interfaces and local memory buffers. This is the real accelerator that becomes part of the embedded system. - -Open these projects with the following commands (they are valid in both Windows and Linus OS): - -``` -cd .. -vitis_hls --classic -p hls_mmult_prj -vitis_hls --classic -p hls_wrapped_mmult_prj -``` - -and use the HLS GUI to visualize the following reports: - -![figure9-1](files/images/hls_mmult_prj.png) - -*[Figure 9-1] Comparison of HLS Synthesis solutions for the ``hls_mmult_prj`` project.* - -![figure9-2](files/images/hls_wrap_mmult_prj.png) - -*[Figure 9-2] HLS Synthesis report for the ``hls_wrapped_mmult_prj`` project.* - -Looking at Figure 9-1, you can note that the calculation of a 32-bit Floating Point real matrix of size 32x32 has a latency of 1354 clock cycles at 300MHz on the ZCU102 target board in the most optimized ``solution3`` of project ``hls_mmult_prj``, whereas it takes about 12 times more clock cycles in the unoptimized baseline ``solution1``. The design does not consume any BRAM_18K, which means that all the 32x32 matrix elements are not stored in the core itself. Finally, the number of DSP slices increases as soon as you optimize the design to decrease its latency from 10 slices in ``solution1`` to 160 slices in ``solution3``. - -In the ``hls_wrapped_mmult_prj`` design, the two input matrices ``A`` and ``B`` and the output matrix ``C`` are stored locally in the core itself (see C++ function ``wrapped_mmult_hw()`` in file [mmult.h](files/examples/9_matrix_mult_z/src/mmult.h)). The data is first read from the external world with 32-bit HLS stream objects (``hls::stream`` and ``axis<32,2,5,6>`` HLS proprietary data types) through the AXI4-Stream interfaces (which takes 2x 1024 clock cycles), then the real matrix multiplication starts (taking about 1354 clock cycles), and finally, the output matrix is written to the external world (in other 1024 clock cycles). The overall core latency is 4443 clock cycles as reported in the HLS synthesis report of Figure 9-2. - -## 10 Two Examples with Vitis Acceleration Flow Running on HW - -So far, you have seen different examples of how to design a high-performance DSP IP core with HLS. Now you will learn to use DSP IP core and run it on the target board in a real embedded system. - -In this section, you will use the [Vitis Acceleration Flow (UG1393)](https://docs.amd.com/r/en-US/ug1393-vitis-application-acceleration/Data-Center-Application-Acceleration-Development-Flow) to build an embedded system that includes: - -- One kernel, designed with HLS, placed in the Programmable Logic (PL). - -- The software application running on the ARM host CPU Programmable System (PS), making use of either OpenCL or [XRT](https://www.xilinx.com/products/design-tools/vitis/xrt.html) host APIs. - -- Either the AMD Zynq™ Ultrascale™ MPSoC [ZCU102](https://www.hackster.io/xilinx/products/zynq-ultrascale-mpsoc-zcu102?ref=project-fa8bc8) or the AMD Versal™ [VCK190](https://www.xilinx.com/products/boards-and-kits/vck190.html) target board. - -- The PetaLinux OS to boot the target board from an SD card. - -Then you will run your example on target board (which is what it is meant for "HW"). - -### 10.1 Build Example 8 for ZCU102 - -Note that the code running on the ARM host CPU of ZCU102 board applies XRT APIs enabled with the ``#define DB_USE_XRT`` from [vadd_include.h](files/examples/8_vect_add/src/vadd_include.h) header file (if you comment that line, OpenCL Host API is used). - -#### 10.1.1 GUI-based Flow - -You can open the Vitis GUI with the commands: - -```bash -cd /${WRK_DIR}/03-HLS_Code_Optimization/files -#source ./run_all.sh -cd examples/8_vect_add -vitis -workspace ./wrk -``` - -Note the following screenshots of Figures 10.1-1, 10.1-2, 10.1-3, 10.1-4, 10.1-5, 10.1-6, and 10.1-7. They highlight the project settings you need to add to the GUI-based environment if you ever developed the project from scratch. - -If you import the zip archive directly in Vitis, all you have to do is **changing these three environmental variables** (``Sysroot path``, ``Root File System``, ``Kernel Image``): - -```text - - /opt/xilinx/common/xilinx-zynqmp-common-v2023.2/sysroots/cortexa72-cortexa53-amd-linux #Sysroot path - - /opt/xilinx/common/xilinx-zynqmp-common-v2023.2/rootfs.ext4 #Root FS - - /opt/xilinx/common/xilinx-zynqmp-common-v2023.2/Image #Kernel Image -``` - -The various detailed project settings are shown here for your reference: - -1. in the ``zcu102_vadd_prj [xrt]`` PS domain - - - note the following lines created by Vitis: - - ```text - -include="${env_var:XILINX_HLS}/include - -include="${workspace_loc:/${ProjName}/src}" - -include=${SYSROOT}/usr/include/xrt/ - ``` - - - and note the following library search paths (``-L`` flag) created by Vitis: - - ```text - -L"${SYSROOT}/usr/lib/" - ``` - - - and libraries (``-l`` flag) added manually by the user: - - ```text - xilinxopencl - xrt_core - xrt_coreutil - ``` - - - for the GCC host compiler the **dialect flag** is set (by default) as: - - ```text - -std=c++11 - ``` - -1. Note that the ``Hardware/binary_container_1-link.cfg`` file (created by Vitis) for ``*_system_hw_link [pl]`` PL domain has the following line: - - ```text - [connectivity] - nk=krnl_vadd:1:krnl_vadd_1 - ``` - -![figure10.1-1](files/images/vadd_prj.png) - -*[Figure 10.1-1] Setting OS paths to compile the host software subsystem.* - -![figure10.1-2](files/images/vadd_dialect.png) - -*[Figure 10.1-2] Setting C++ dialect to compile the host software subsystem.* - -![figure10.1-3](files/images/vadd_libs.png) - -*[Figure 10.1-3] Setting the libraries and related paths to compile the host software subsystem ("-l" and "-L" linker flags).* - -![figure10.1-4](files/images/vadd_include.png) - -*[Figure 10.1-4] Setting the include paths to compile the host software subsystem ("-I" C-preprocessor flag).* - -![figure10.1-5](files/images/vadd_preproc.png) - -*[Figure 10.1-5] Setting C-Preprocessor symbols to compile the host software subsystem ("-D" C-preprocessor flag).* - -![figure10.1-6](files/images/vadd_link.png) - -*[Figure 10.1-6] Vitis Linker Settings.* - -![figure10.1-7](files/images/vadd_pl.png) - -*[Figure 10.1-7] Setting the HLS kernels of PL subsystem.* - -#### 10.1.2 Makefile-based Flow - -Alternatively, to the GUI-based flow, you can use Vitis from command line with the proper makefile by typing the following: - -```bash -cd /${WRK_DIR}/03-HLS_Code_Optimization/files -#source ./run_all.sh -cd examples/8_vect_add -make zcu102_clean zcu102_all -``` - -The makefiles here adopted were automatically generated by Vitis (Eclipse) GUI and then manually modified to use the environmental variables and avoid absolute path names. - -#### 10.1.3 Run the Application on ZCU102 Board - -At the end of the Vitis build process, you will find the ``sd_card.img`` file (~4.2GB size) to boot the ZCU102 board in the folder ``wrk/zcu102_vadd_system/Hardware/package``. - -Once you have booted the ZCU102 board, at the prompt, login with ``petalinux`` username and choose one password (for example ``root``), then launch the following commands: - -``` -sudo su -mount /dev/mmcblk0p1 /mnt -cd /mnt -./zcu102_vadd_prj ./binary_container_1.xclbin -``` - -The runtime execution on ZCU102 works correctly: - -```text -root@zynqmp-common-20221:~# mount /dev/mmcblk0p1 /mnt -root@zynqmp-common-20221:~# cd /mnt -root@zynqmp-common-20221:/mnt# ls -l -total 75655 --rwxrwx--- 1 root disk 28251160 Jan 1 2015 BOOT.BIN --rwxrwx--- 1 root disk 22401536 Jan 1 2015 Image -drwxrwx--- 2 root disk 512 Oct 13 2022 System Volume Information --rwxrwx--- 1 root disk 26543585 Jan 1 2015 binary_container_1.xclbin --rwxrwx--- 1 root disk 2777 Jan 1 2015 boot.scr --rwxrwx--- 1 root disk 269672 Jan 1 2015 zcu102_vadd_prj - -root@zynqmp-common-20221:/mnt# ./zcu102_vadd_prj ./binary_container_1.xclbin -INFO: DATA size in words = 4096 -INFO: DATA size in bytes = 16384 -PASSED: auto my_device = xrt::device(0) -PASSED: auto xclbin_uuid = my_device.load_xclbin(./binary_container_1.xclbin) -PASSED: auto krnl = xrt::kernel(my_device, xclbin_uuid, "krnl_vadd:{krnl_vadd_1}") -INFO: Allocate Buffers in Global Memory -PASSED: auto bo0 = xrt::bo(my_device, size_in_bytes, XCL_BO_FLAGS_NONE, krnl.group_id(0) (=4)) -PASSED: auto bo1 = xrt::bo(my_device, size_in_bytes, XCL_BO_FLAGS_NONE, krnl.group_id(1) (=4)) -PASSED: auto bo2 = xrt::bo(my_device, size_in_bytes, XCL_BO_FLAGS_NONE, krnl.group_id(2) (=4)) -PASSED: auto bo0_map = bo0.map() -PASSED: auto bo1_map = bo1.map() -PASSED: auto bo2_map = bo2_map() -INFO: Creating random input data -INFO: synchronize input buffer data to device global memory -PASSED: bo0.sync(XCL_BO_SYNC_BO_TO_DEVICE) -PASSED: bo1.sync(XCL_BO_SYNC_BO_TO_DEVICE) -INFO: Execution of the kernel -INFO: Waiting for kernels to end... -PASSED: run.wait() -PASSED: bo2.sync(XCL_BO_SYNC_BO_FROM_DEVICE) -INFO: Checking the results -TEST PASSED - -root@zynqmp-common-20221:/mnt# ls -l -total 75832 --rwxrwx--- 1 root disk 28251160 Jan 1 2015 BOOT.BIN --rwxrwx--- 1 root disk 22401536 Jan 1 2015 Image -drwxrwx--- 2 root disk 512 Oct 13 2022 System Volume Information --rwxrwx--- 1 root disk 26543585 Jan 1 2015 binary_container_1.xclbin --rwxrwx--- 1 root disk 2777 Jan 1 2015 boot.scr --rwxrwx--- 1 root disk 1115 Oct 13 08:27 vadd_zcu102_logfile.txt --rwxrwx--- 1 root disk 90112 Oct 13 08:27 vector_inputs.txt --rwxrwx--- 1 root disk 90112 Oct 13 08:27 vector_out.txt --rwxrwx--- 1 root disk 269672 Jan 1 2015 zcu102_vadd_prj -``` - -The files generated during the runtime execution, ``vector_*.txt`` can then be further checked with the Matlab script ``check_res.m``. - -### 10.2 Build Example 9 on Both ZCU102 and VCK190 - -If you want to use the matrix multiplier accelerator (``HLS_accel``) code as it is, add two more kernels in the PL, ``mm2s`` and ``s2mm`` from [mm2s.cpp](files/examples/9_matrix_mult/vitis_src/mm2s.cpp) and [s2mm.cpp](files/examples/9_matrix_mult_z/vitis_src/s2mm.cpp) files respectively, as illustrated in Figure 10.2-1. They implement DMAs to transfer data either from the main memory (for example, the external DDR) with a streaming communication to the matrix multiplier kernel, which is the case of ``mm2s`` kernel, or from the matrix multiplier kernel to the main memory, which is the case of ``s2mm`` kernel. - -Because of these two further kernels, you have to expose their connectivity to the Vitis linker with the file [system.cfg](files/examples/9_matrix_mult_z/vitis_src/system.cfg). It is reported below: - -```text -[connectivity] -sc=mm2s_1.s:HLS_accel_1.INPUT_STREAM -sc=HLS_accel_1.OUTPUT_STREAM:s2mm_1.s -``` - -The ARM host application using XRT APIs is written in the file [xrt_mmult_test.cpp](files/examples/9_matrix_mult_z/vitis_src/xrt_mmult_test.cpp). - -These last four files are placed in the [9_matrix_mult_z/vitis_src](files/examples/9_matrix_mult_z/vitis_src) folder. They are needed to complete the Vitis design, besides the matrix multiplier standalone HLS project, located in [9_matrix_mult_z/src](files/examples/9_matrix_mult-z/src) folder. - -![figure10.2-1](files/images/mm2s-mmult-s2mm.png) - -*[Figure 10.2-1] Matrix multiplier HLS implementation architecture.* - -Note the following screenshots of Figures 10.2-2, 10.2-3, 10.2-4, 10.2-5, 10.2-6, 10.2-7, and 10.2-8. They highlight the ZCU102 target board project settings you need to add to the GUI-based environment if you ever developed the project from scratch. -These settings are the same independently on the target board, that is, they are valid for both ZCU102 and VCK190 targets. - -They are shown below for your reference: - -1. In the application for PS domain (either ``zcu102_mmult_prj [xrt]`` for ZCU102 or ``vck190_mmult_prj [xrt]`` for VCK190) - - - note the following lines created by Vitis: - - ```text - -include="${env_var:XILINX_HLS}/include - -include="${workspace_loc:/${ProjName}/src}" - -include=${SYSROOT}/usr/include/xrt/ - ``` - - - and note the following library search paths (``-L`` flag) created by Vitis: - - ```text - -L"${SYSROOT}/usr/lib/" - ``` - - - and libraries (``-l`` flag) added manually by the user: - - ```text - xilinxopencl - xrt_core - xrt_coreutil - ``` - - - for the GCC host compiler the **dialect flag** is set (by default) as: - - ```text - -std=c++11 - ``` - -2. Note that the ``mmult_system_hw_link/system.cfg`` file (created by the user) for the PL domain has the following lines: - - ```text - [connectivity] - sc=mm2s_1.s:HLS_accel_1.INPUT_STREAM - sc=HLS_accel_1.OUTPUT_STREAM:s2mm_1.s - ``` - -The project settings that are different for each target board are related to ``Sysroot path``, ``Root File System`` and ``Kernel Image`` path names, as shown in the next two subsections. - -![figure10.2-2](files/images/zcu102_mmult_prj.png) - -*[Figure 10.2-2] Matrix Multiplier on ZCU102: Setting OS paths to compile the host software subsystem.* - -![figure10.2-3](files/images/zcu102_mmult_C-dialects.png) - -*[Figure 10.2-3] Matrix Multiplier on ZCU102: Setting C++ dialect to compile the host software subsystem.* - -![figure10.2-4](files/images/zcu102_mmult_libs.png) - -*[Figure 10.2-4] Matrix Multiplier on ZCU102: Setting the libraries and related paths to compile the host software subsystem ("-l" and "-L" linker flags).* - -![figure10.2-5](files/images/zcu102_mmult_inc.png) - -*[Figure 10.2-5] Matrix Multiplier on ZCU102: Setting the include paths to compile the host software subsystem ("-I" C-preprocessor flag).* - -![figure10.2-6](files/images/zcu102_mmult_preproc.png) - -*[Figure 10.2-6] Matrix Multiplier on ZCU102: Setting C-Preprocessor symbols to compile the host software subsystem ("-D" C-preprocessor flag).* - -![figure10.2-7](files/images/zcu102_mmult_hw_link.png) - -*[Figure 10.2-7] Matrix Multiplier on ZCU102: Vitis Linker Settings.* - -![figure10.2-8](files/images/zcu102_mmult_kernels_prj.png) - -*[Figure 10.2-8] Matrix Multiplier on ZCU102: Setting the HLS kernels of PL subsystem.* - -#### 10.2.1 Targeting ZCU102 - -##### 10.2.1.1 GUI-based Flow - -You can open the Vitis GUI with the commands: - -```bash -cd /${WRK_DIR}/03-HLS_Code_Optimization/files -#source ./run_all.sh -cd examples/9_matrix_mult_z -vitis -workspace ./wrk -``` - -Make sure to check these three environmental variables (``Sysroot path``, ``Root File System``, ``Kernel Image``). See the following case: - -```text - - /opt/xilinx/common/xilinx-zynqmp-common-v2023.2/sysroots/cortexa72-cortexa53-amd-linux #Sysroot path - - /opt/xilinx/common/xilinx-zynqmp-common-v2023.2/rootfs.ext4 #Root FS - - /opt/xilinx/common/xilinx-zynqmp-common-v2023.2/Image #Kernel Image -``` - -##### 10.2.1.2 Makefile-based Flow - -Alternatively, to the GUI-based flow, you can use Vitis from command line with the proper makefile by typing the following: - -```bash -cd /${WRK_DIR}/03-HLS_Code_Optimization/files/examples -cd 9_matrix_mult_z -make zcu102_clean zcu102_all -``` - -The makefiles here adopted were automatically generated by Vitis (Eclipse) GUI and then manually modified to use the environmental variables and avoid absolute path names. - -##### 10.2.1.3 Run the Application on ZCU102 Board - -At the end of the Vitis build process, you will find the ``sd_card.img`` file (~4.2GB size) to boot the ZCU102 board in the folder ``wrk/zcu102_mmult_system/Hardware/package``. - -Once you have booted the ZCU102 board, at the prompt, login with ``petalinux`` username and choose one password (for example ``root``), then launch the following commands: - -``` -sudo su -mount /dev/mmcblk0p1 /mnt -cd /mnt -./embedded_exec.sh -``` - -The runtime execution on ZCU102 works correctly: - -```text -INFO: wSizeIn = 2048 -INFO: wSizeOut = 1024 -INFO: bSizeIn = 8192 -INFO: bSizeOut = 4096 -PASSED: auto my_device = xrt::device(0) -PASSED: auto xclbin_uuid = my_device.load_xclbin(binary_container_1.xclbin) -INFO: Opening the Input mm2s Kernel... -PASSED: auto in_0 = xrt::kernel(my_device, xclbin_uuid, "mm2s:{mm2s_1}") -PASSED: auto in_0_bo = xrt::bo(my_device, bSizeIn, XCL_BO_FLAGS_NONE, in_0.group_id(0) (=4)) -PASSED: auto in_0_bo_mapped = in_0_bo.map() -INFO: Setting Input Data -PASSED: in_0_bo_mapped[i] = t -INFO: Compute Golden Result -INFO: Sync Input Buffer... -PASSED: in_0_bo.sync(XCL_BO_SYNC_BO_TO_DEVICE) -INFO: Starting Input mm2s Kernel... -PASSED: auto in_0_run = in_0(in_0_bo, nullptr, 2048) -INFO: Opening Output s2mm Kernel... -PASSED: auto out_0 = xrt::kernel(my_device, xclbin_uuid, "s2mm:{s2mm_1}") -PASSED: auto out_0_bo = xrt::bo(my_device, bsize, XCL_BO_FLAGS_NONE, out.group_id(0) (=4)) -PASSED: auto out_0_bo_mapped = out_0_bo.map() -INFO: Starting Output s2mm Kernel... -PASSED: auto out_0_run = out(out_0_bo, nullptr, 1024) -INFO: Opening and Starting HLS Accel kernel -PASSED: auto my_krnl = xrt::kernel(my_device, xclbin_uuid, "HLS_accel") -PASSED: my_krnl_run -INFO: Waiting for kernels to end... -PASSED: in_0_run.wait() -PASSED: my_krnl_run.wait() -PASSED: out_0_run.wait() -INFO: Sync Output Buffer... -PASSED: out_0_bo.sync(XCL_BO_SYNC_BO_FROM_DEVICE) -INFO: Verifying output data vs. golden ones -PASSED: ./mtrx_mult -``` - -#### 10.2.2 Targeting VCK190 - -##### 10.2.2.1 GUI-based Flow - -You can open the Vitis GUI with the commands: - -```bash -cd /${WRK_DIR}/03-HLS_Code_Optimization/files -#source ./run_all.sh -cd examples/9_matrix_mult_v -vitis -workspace ./vck190_wrk -``` - -Make sure to check these three environmental variables (``Sysroot path``, ``Root File System``, ``Kernel Image``). See the following case: - -```text -- /opt/xilinx/common/xilinx-versal-common-v2023.2/sysroots/cortexa72-cortexa53-amd-linux #Sysroot path -- /opt/xilinx/common/xilinx-versal-common-v2023.2/rootfs.ext4 #Root FS -- /opt/xilinx/common/xilinx-versal-common-v2023.2/Image #Kernel Image -``` - -##### 10.2.2.2 Makefile-based Flow - -Alternatively, to the GUI-based flow, you can use Vitis from command line with the proper makefile by typing the following: - - ```bash - cd /${WRK_DIR}/03-HLS_Code_Optimization/files/examples - cd 9_matrix_mult_v - make vck190_clean vck190_all - ``` - -The makefiles here adopted were automatically generated by Vitis (Eclipse) GUI and then manually modified to use the environmental variables and avoid absolute path names. - -##### 10.2.2.3 Run the Application on VCK190 Board - -At the end of the Vitis build process, you will find the ``sd_card.img`` file (~4.2GB size) to boot the VCK190 board in the folder ``vck190_wrk/vck190_mmult_system/Hardware/package``. - - -At the prompt on UART terminal digit, insert the ``petalinux`` username and the choose a password to login. For example, ``root``. See the following: - -```text -versal-rootfs-common-20231 login: petalinux -You are required to change your password immediately (administrator enforced). -New password: -Retype new password: - -versal-rootfs-common-20231:~$ sudo su - -We trust you have received the usual lecture from the local System -Administrator. It usually boils down to these three things: - #1) Respect the privacy of others. - #2) Think before you type. - #3) With great power comes great responsibility. -Password: -``` - -You can now launch the following commands: - -```shell -sudo su -mount /dev/mmcblk0p1 /mnt -cd /mnt -./xrt_mmult_app ./binary_container_1.xclbin -``` - -The runtime execution on VCK190 works correctly and you should see something like this: - -```text -versal-rootfs-common-20231:/mnt# ./mmult ./binary_container_1.xclbin -INFO: wSizeIn = 2048 -INFO: wSizeOut = 1024 -INFO: bSizeIn = 8192 -INFO: bSizeOut = 4096 -PASSED: auto xclbin_uuid = my_device.load_xclbin(./binary_container_1.xclbin) -INFO: Opening the Input mm2s Kernel... -INFO: Compute Golden Result -. . . -INFO: Sync Input Buffer... -INFO: Opening Output s2mm Kernel... -INFO: Opening HLS Accel kernel -. . . -INFO: Starting Input mm2s Kernel... -INFO: Starting Output s2mm Kernel... -INFO: starting HLS Accel kernel -PASSED: my_krnl_run -INFO: Waiting for kernels to end... -. . . -PASSED: in_0_run.wait() -PASSED: my_krnl_run.wait() -PASSED: out_0_run.wait() -INFO: Sync Output Buffer... -PASSED: out_0_bo.sync(XCL_BO_SYNC_BO_FROM_DEVICE) - -INFO: Verifying output data vs. golden ones - -PASSED: ./mmult - -versal-rootfs-common-20231:/mnt# -``` - -## Appendix - -### A1 ZCU102 Setup - -#### A1.1 SW6 Switch for SD Boot Mode - -From the [ZCU102](https://www.xilinx.com/products/boards-and-kits/ek-u1-zcu102-g.html) web page, read its user guide ([ug1182-zcu102-eval-bd.pdf](https://docs.amd.com/v/u/en-US/ug1182-zcu102-eval-bd)) and make sure that you have followed what is described in **Table 2-4: Switch SW6 Configuration Option Settings** to enable the SD boot mode via the SW6 switch pins (3:0) set as ``1110``, as illustrated in -Figures A1-1 and A1-2. - -![figureA1-1](files/images/zcu102_ug_table.png) - -*[Figure A1-1] ZCU102 SW6 switch setting for SD boot mode (Table 2-4 of UG1182).* - - -![figureA1-2](files/images/zcu102_sw6.jpg) - -*[Figure A1-2] Picture of SW6 switch from my ZCU102 board.* - - - -#### A1.2 TeraTerm UART from Windows10 PC - -If you use a Windows10 PC, install ``TeraTerm VT`` utility (I have ``version 4.106(SVN# 9298)``). - -Then, from the [CP210x USB to UART Bridge VCP Drivers](https://www.silabs.com/developers/usb-to-uart-bridge-vcp-drivers) website, download and install the ``CP210x Universal Windows Driver``. Also, see what is described in this forum [about ZCU102 UART ports](https://support.xilinx.com/s/question/0D52E00006hplYdSAI/zcu102-uart-ports-doesnt-show-up-in-device-manager?language=en_US). - -Now turn on the ZCU102 board with the USB cable connected from J83 micro USB connector to the PC, as illustrated in Figure A1-3. Open ``TeraTerm VT`` and configure the proper COMX port for the Silicon Labs Quad CP2108 USB to UART Bridge (in my case X=7) as illustrated in Figures A1-4. You have to set the following parameters in the GUI, speed 115200, data 8bit, parity none, stop bits 1 bit, and flow control none, as illustrated in figure A1-5 (note that it should be COM7 and not COM3 as wrongly reported in the figure). -If you save it into a ``zcu102_board.ini`` setup file, as illustrated in Figure A1-6, restore the board settings from there. Finally, you can launch your application on the ZCU102, as illustrated in Figure A1-7. - -![figureA1-3](files/images/zcu102_picture.jpg) - -*[Figure A1-3] My ZCU102 board connected to my Windows PC.* - -![figureA1-4](files/images/teraterm_win_setup1.png) - -*[Figure A1-4] Select the proper COM port for the USB to UART Bridge in TeraTerm.* - -![figureA1-5](files/images/teraterm_win_setup2.png) - -*[Figure A1-5] Serial port setup.* - -![figureA1-6](files/images/teraterm_win_setup3.png) - -*[Figure A1-6] Save your ZCU102 configuration for future restore.* - -![figureA1-7](files/images/teraterm_win_setup4.png) - -*[Figure A1-7] Launching the application on ZCU102 from TeraTerm.* - -#### A1.3 Putty UART from Linux PC - -If you use an Ubuntu PC, install ``PuTTY`` utility with the command ``sudo apt install -y putty``. Then you can call it with command line (you have to be ``sudo`` user) ``sudo putty``, as illustrated in Figures A1-8 and A1-9. - -![figureA1-8](files/images/linux_putty_setup1.png) - -*[Figure A1-8] Setting PuTTY utility for the UART communication with ZCU102 from a Linux PC.* - -![figureA1-9](files/images/linux_putty_setup2.png) - -*[Figure A1-9] Launching an application on ZCu102 from PuTTY terminal.* - -## References - -### Vitis DSP Libraries - -- [Vitis DSP Libraries Comprehensive Documentation](https://xilinx.github.io/Vitis_Libraries/dsp/2023.2/) - -### Vitis Unified Software Development Platform 2023.2 Documentation - -Below are links to Vitis related information referenced in this tutorial: - -- [Vitis Application Acceleration Development Flow Documentation](https://docs.amd.com/r/en-US/ug1393-vitis-application-acceleration) - -- [Vitis Application Acceleration Development Flow Tutorials](https://github.com/Xilinx/Vitis-Tutorials) - -- [Vitis Acceleration Flow UG1393](https://docs.amd.com/r/en-US/ug1393-vitis-application-acceleration/Data-Center-Application-Acceleration-Development-Flow) - -- [Vitis HLS](https://docs.amd.com/r/en-US/ug1399-vitis-hls) - -### Support - -GitHub issues will be used for tracking requests and bugs. For questions, go to [forums.xilinx.com](http://forums.xilinx.com/). - - +> **Note:** +> This tutorial has not been validated with the latest Vitis release. +> Previous versions are available in earlier branches. +> To access them, switch to an older branch (e.g., `2024.1`).
diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/Makefile b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/Makefile deleted file mode 100644 index 53db026dd3..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/Makefile +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -.PHONY: help kernels clean all - -clean: - rm -rf *_prj *.log* *~ .Xil .wsdata ./logs - -kernels: - vitis-run --mode hls --tcl ./fix_fir_script.tcl -#vitis_hls ./fix_fir_script.tcl - diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives1.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives1.tcl deleted file mode 100644 index 0e7023260c..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives1.tcl +++ /dev/null @@ -1,5 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -set_directive_top -name fir_filter "fir_filter" -set_directive_pipeline -off "fir_filter/Shift_Accum_Loop" diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives2.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives2.tcl deleted file mode 100644 index a3b0925346..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives2.tcl +++ /dev/null @@ -1,5 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -set_directive_top -name fir_filter "fir_filter" -set_directive_pipeline -II 1 "fir_filter/Shift_Accum_Loop" diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives3.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives3.tcl deleted file mode 100644 index 2eedb740b6..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives3.tcl +++ /dev/null @@ -1,6 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -set_directive_top -name fir_filter "fir_filter" -set_directive_pipeline -II 1 "fir_filter/Shift_Accum_Loop" -set_directive_array_partition -dim 1 -type complete "fir_filter" shift_reg diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives4.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives4.tcl deleted file mode 100644 index 5f800db98f..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives4.tcl +++ /dev/null @@ -1,7 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -set_directive_top -name fir_filter "fir_filter" -set_directive_pipeline -II 1 "fir_filter/Shift_Accum_Loop" -set_directive_array_partition -type complete -dim 1 "fir_filter" shift_reg -set_directive_unroll -factor 16 "fir_filter/Shift_Accum_Loop" diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives5.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives5.tcl deleted file mode 100644 index 4f79880ad3..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives5.tcl +++ /dev/null @@ -1,8 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -set_directive_top -name fir_filter "fir_filter" -set_directive_pipeline -II 1 "fir_filter/Shift_Accum_Loop" -set_directive_array_partition -type complete -dim 1 "fir_filter" shift_reg -set_directive_unroll -factor 16 "fir_filter/Shift_Accum_Loop" -set_directive_array_partition -dim 1 -type complete "fir_filter" c diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives6.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives6.tcl deleted file mode 100644 index 73795cea38..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives6.tcl +++ /dev/null @@ -1,9 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -set_directive_top -name fir_filter "fir_filter" -set_directive_pipeline -II 1 "fir_filter/Shift_Accum_Loop" -set_directive_array_partition -type complete -dim 1 "fir_filter" shift_reg -set_directive_unroll -factor 16 "fir_filter/Shift_Accum_Loop" -set_directive_array_partition -type complete -dim 1 "fir_filter" c -set_directive_pipeline -II 1 "fir_filter" diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives6b.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives6b.tcl deleted file mode 100644 index 3305ef070e..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives6b.tcl +++ /dev/null @@ -1,7 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -set_directive_top -name fir_filter "fir_filter" -set_directive_pipeline -II 1 "fir_filter" -set_directive_array_partition -dim 1 -type complete "fir_filter" c diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives7_2_8.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives7_2_8.tcl deleted file mode 100644 index ea3a3e13bb..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives7_2_8.tcl +++ /dev/null @@ -1,7 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -set_directive_top -name fir_filter "fir_filter" -set_directive_pipeline -II 2 "fir_filter" -set_directive_array_partition -type complete -dim 1 "fir_filter" c -set_directive_allocation -limit 8 -type operation "fir_filter" mul diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives7_4_4.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives7_4_4.tcl deleted file mode 100644 index c91241e56d..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives7_4_4.tcl +++ /dev/null @@ -1,8 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -set_directive_top -name fir_filter "fir_filter" -set_directive_pipeline -II 4 "fir_filter" -set_directive_array_partition -type complete -dim 1 "fir_filter" c -set_directive_allocation -limit 4 -type operation "fir_filter" mul diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives7_8_2.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives7_8_2.tcl deleted file mode 100644 index a54ac5e7d9..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives7_8_2.tcl +++ /dev/null @@ -1,8 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -set_directive_top -name fir_filter "fir_filter" -set_directive_pipeline -II 8 "fir_filter" -set_directive_array_partition -type complete -dim 1 "fir_filter" c -set_directive_allocation -limit 2 -type operation "fir_filter" mul diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives8_integers.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives8_integers.tcl deleted file mode 100644 index f271f97b28..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_directives/directives8_integers.tcl +++ /dev/null @@ -1,10 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -set_directive_top -name fir_filter "fir_filter" -set_directive_pipeline -II 1 "fir_filter/Shift_Accum_Loop" -set_directive_array_partition -type complete -dim 1 "fir_filter" shift_reg -set_directive_unroll -factor 16 "fir_filter/Shift_Accum_Loop" -set_directive_array_partition -type complete -dim 1 "fir_filter" c -set_directive_pipeline -II 1 "fir_filter" diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_script.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_script.tcl deleted file mode 100644 index 534d13a8ba..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/fix_fir_script.tcl +++ /dev/null @@ -1,251 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -# Author: Daniele Bagni, Xilinx Inc - -puts "\n" -puts "************************************************************************" -puts "* EXAMPLE 1) FIXED POINT FIR FILTER DEMO" -puts "************************************************************************" -puts "\n" - -puts " " -puts "Solution8: Using ANSI-C Integers Datatypes instead of HLS Fractional Fixed Point" -puts " " -open_project vhls_fix_fir_prj -set_top fir_filter -add_files src/fir.cpp -add_files -tb src/fir_test.cpp -cflags "-Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -add_files -tb src/data -open_solution "sol8_integers" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -source "./fix_fir_directives/directives8_integers.tcl" -csim_design -clean -csynth_design -#cosim_design -#export_design -format ip_catalog -close_project - - - - - -puts " " -puts "Solution1: Baseline" -puts " " -open_project vhls_fix_fir_prj -set_top fir_filter -add_files src/fir.cpp -cflags "-DHLS_FIXED_POINT" -add_files -tb src/fir_test.cpp -cflags "-Wno-unknown-pragmas -DHLS_FIXED_POINT" -csimflags "-Wno-unknown-pragmas" -add_files -tb src/data -open_solution "sol1_baseline" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -source "./fix_fir_directives/directives1.tcl" -csim_design -clean -csynth_design -#cosim_design -#export_design -rtl vhdl -format ip_catalog -close_project - -if 1 { - -puts " " -puts "Solution2: as 1 + Pipelining the Loop" -puts " " -open_project vhls_fix_fir_prj -set_top fir_filter -add_files src/fir.cpp -cflags "-DHLS_FIXED_POINT" -add_files -tb src/fir_test.cpp -cflags "-Wno-unknown-pragmas -DHLS_FIXED_POINT" -csimflags "-Wno-unknown-pragmas" -add_files -tb src/data -open_solution "sol2_LoopPipeline" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -source "./fix_fir_directives/directives2.tcl" -#csim_design -clean -csynth_design -#cosim_design -#export_design -format ip_catalog -close_project - -puts " " -puts "Solution3: as 2 + Partitioning shift_reg Array" -puts " " -open_project vhls_fix_fir_prj -set_top fir_filter -add_files src/fir.cpp -cflags "-DHLS_FIXED_POINT" -add_files -tb src/fir_test.cpp -cflags "-Wno-unknown-pragmas -DHLS_FIXED_POINT" -csimflags "-Wno-unknown-pragmas" -add_files -tb src/data -open_solution "sol3_shiftregPartition" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -source "./fix_fir_directives/directives3.tcl" -#csim_design -clean -csynth_design -#cosim_design -#export_design -format ip_catalog -close_project - - -puts " " -puts "Solution4: as 3 + Complete Loop Unrolling" -puts " " -open_project vhls_fix_fir_prj -add_files src/fir.cpp -cflags "-DHLS_FIXED_POINT" -add_files -tb src/fir_test.cpp -cflags "-Wno-unknown-pragmas -DHLS_FIXED_POINT" -csimflags "-Wno-unknown-pragmas" -add_files -tb src/data -open_solution "sol4_loopUnroll" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -source "./fix_fir_directives/directives4.tcl" -#csim_design -clean -csynth_design -#cosim_design -#export_design -format ip_catalog -close_project - -puts " " -puts "Solution5: as 4 + Partitioning coeff Array" -puts " " -open_project vhls_fix_fir_prj -set_top fir_filter -add_files src/fir.cpp -cflags "-DHLS_FIXED_POINT" -add_files -tb src/fir_test.cpp -cflags "-Wno-unknown-pragmas -DHLS_FIXED_POINT" -csimflags "-Wno-unknown-pragmas" -add_files -tb src/data -open_solution "sol5_coeffPartition" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -source "./fix_fir_directives/directives5.tcl" -#csim_design -clean -csynth_design -#cosim_design -#export_design -format ip_catalog -close_project - - -puts " " -puts "Solution6: as 5 + Top Level Pipeline" -puts " " -open_project vhls_fix_fir_prj -set_top fir_filter -add_files src/fir.cpp -cflags "-DHLS_FIXED_POINT" -add_files -tb src/fir_test.cpp -cflags "-Wno-unknown-pragmas -DHLS_FIXED_POINT" -csimflags "-Wno-unknown-pragmas" -add_files -tb src/data -open_solution "sol6_II1_top" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -source "./fix_fir_directives/directives6.tcl" -#csim_design -clean -csynth_design -#cosim_design -#export_design -format ip_catalog -close_project - -puts " " -puts "Solution6b: as 1 + Top Level Pipeline and coeff Array Partitioning" -puts " " -open_project vhls_fix_fir_prj -set_top fir_filter -add_files src/fir.cpp -cflags "-DHLS_FIXED_POINT" -add_files -tb src/fir_test.cpp -cflags "-Wno-unknown-pragmas -DHLS_FIXED_POINT" -csimflags "-Wno-unknown-pragmas" -add_files -tb src/data -open_solution "sol6b_II1_top" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -source "./fix_fir_directives/directives6b.tcl" -#csim_design -clean -csynth_design -#cosim_design -#export_design -format ip_catalog -close_project - -puts " " -puts "Solution7_2_8: Partial Unroll by 2 to get 8 DSP48" -puts " " -open_project vhls_fix_fir_prj -set_top fir_filter -add_files src/fir.cpp -cflags "-DHLS_FIXED_POINT" -add_files -tb src/fir_test.cpp -cflags "-Wno-unknown-pragmas -DHLS_FIXED_POINT" -csimflags "-Wno-unknown-pragmas" -add_files -tb src/data -open_solution "sol7_II2_8DSP" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -source "./fix_fir_directives/directives7_2_8.tcl" -#csim_design -clean -csynth_design -#cosim_design -#export_design -format ip_catalog -close_project - -puts " " -puts "Solution7_4_4: Partial Unroll by 4 to get 4 DSP48" -puts " " -open_project vhls_fix_fir_prj -set_top fir_filter -add_files src/fir.cpp -cflags "-DHLS_FIXED_POINT" -add_files -tb src/fir_test.cpp -cflags "-Wno-unknown-pragmas -DHLS_FIXED_POINT" -csimflags "-Wno-unknown-pragmas" -add_files -tb src/data -open_solution "sol7_II4_4DSP" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -source "./fix_fir_directives/directives7_4_4.tcl" -#csim_design -clean -csynth_design -#cosim_design -#export_design -format ip_catalog -close_project - -puts " " -puts "Solution7_8_2: Partial Unroll by 8 to get 2 DSP48" -puts " " -open_project vhls_fix_fir_prj -set_top fir_filter -add_files src/fir.cpp -cflags "-DHLS_FIXED_POINT" -add_files -tb src/fir_test.cpp -cflags "-Wno-unknown-pragmas -DHLS_FIXED_POINT" -csimflags "-Wno-unknown-pragmas" -add_files -tb src/data -open_solution "sol7_II8_2DSP" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -source "./fix_fir_directives/directives7_8_2.tcl" -#csim_design -clean -csynth_design -#cosim_design -#export_design -format ip_catalog -close_project -} - diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/data/fir_coeff.dat b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/data/fir_coeff.dat deleted file mode 100644 index be86eef5ec..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/data/fir_coeff.dat +++ /dev/null @@ -1,18 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -0.180617 -0.045051 -0.723173 -0.347438 -0.660617 -0.383869 -0.627347 -0.021650 -0.910570 -0.800559 -0.745847 -0.813113 -0.383306 -0.617279 -0.575495 -0.530052 diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/data/fir_filter.m b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/data/fir_filter.m deleted file mode 100644 index 1fef0f5b3e..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/data/fir_filter.m +++ /dev/null @@ -1,31 +0,0 @@ -%% -% Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -% SPDX-License-Identifier: MIT% - -% Author: Daniele Bagni, Xilinx Inc - - -function y = fir_filter(x, c) - -global N; - -persistent ref_shift_reg -if isempty(ref_shift_reg) - ref_shift_reg = zeros(1,N); -end -acc = 0; -mult= 0; -y = 0; -for i = N-1 : -1 : 0 - - if (i==0) - ref_shift_reg(0+1)=x; - else - ref_shift_reg(i+1) = ref_shift_reg(i-1+1); - end - mult = ref_shift_reg(i+1)*c(i+1); - acc = acc + mult; -end -y = fix(acc/2^14); - -end diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/data/input.dat b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/data/input.dat deleted file mode 100644 index 3b33d57b4e..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/data/input.dat +++ /dev/null @@ -1,1026 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. 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a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/data/ref_res.dat b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/data/ref_res.dat deleted file mode 100644 index bd1035b1c4..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/data/ref_res.dat +++ /dev/null @@ -1,1026 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. 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-4.777362 -5.047185 -4.553710 -5.196864 -5.168383 -5.223060 -4.986567 -5.217165 -5.240052 -4.902058 -5.634656 -5.170616 -5.098509 -4.880650 -4.825397 -4.041766 -4.570884 -3.998041 -3.558980 -4.250368 -3.922500 -4.349836 -3.596826 -4.122967 -3.128806 -4.258111 -3.460371 -4.130675 -3.810790 -4.468620 diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/data/run_fir_filter.m b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/data/run_fir_filter.m deleted file mode 100644 index 04e9d75bba..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/data/run_fir_filter.m +++ /dev/null @@ -1,37 +0,0 @@ -%% -% Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -% SPDX-License-Identifier: MIT - -%% run fir filter - -close all; -clear all; -clc - -global N; - -N=16; - -%% -coef = load('./data/fir_coeff.dat'); -inp = load('./data/input.dat'); -ref = load('./data/ref_res.dat'); -SAMPLES = numel(ref); - -%% 16_14 bit fixed point -% https://stackoverflow.com/questions/55809019/how-to-convert-float-to-fix16-14 - -i_coef = round(coef* 2^14); -i_inp = round(inp* 2^14); -i_ref = round(ref* 2^14); - -%% compute data -i_res = zeros(SAMPLES, 1); -for i = 1 : SAMPLES - i_res(i) = fir_filter(i_inp(i), i_coef); -end -%% show data -diff = abs(i_res - i_ref); -max_diff = max(diff) - -[int32(i_res(1:32)) int32(i_ref(1:32))] diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/fir.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/fir.cpp deleted file mode 100644 index 8f66c22889..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/fir.cpp +++ /dev/null @@ -1,46 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -Author: Daniele Bagni, Xilinx Inc -*/ - -#include "fir.h" - -out_data_t fir_filter (inp_data_t x, coef_t c[N]) -{ - - static inp_data_t shift_reg[N]; - - acc_t acc = 0; - acc_t mult; - out_data_t y; - - - - Shift_Accum_Loop: for (int i=N-1;i>=0;i--) - { -#pragma HLS LOOP_TRIPCOUNT min=1 max=16 avg=8 - - - if (i==0) - { - //acc+=x*c[0]; - shift_reg[0]=x; - } - else - { - shift_reg[i]=shift_reg[i-1]; - //acc+=shift_reg[i]*c[i]; - } - //acc = acc + shift_reg[i]*c[i]; - mult = shift_reg[i]*c[i]; - acc = acc + mult; - - } - - y = (out_data_t) acc; - - return y; - -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/fir.h b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/fir.h deleted file mode 100644 index 1fa384d414..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/fir.h +++ /dev/null @@ -1,41 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -Author: Daniele Bagni, Xilinx Inc -*/ - -#ifndef _H_FIR_H_ -#define _H_FIR_H_ - -#define N 16 - -#define SAMPLES 1024 - - -//define HLS_FIXED_POINT - - -#ifdef HLS_FIXED_POINT -#include "ap_fixed.h" - -typedef ap_fixed<18,2> coef_t; -typedef ap_fixed<48,12> out_data_t; -typedef ap_fixed<18,2> inp_data_t; -typedef ap_fixed<48,12> acc_t; - -const float THRESHOLD = 1.0; - -#else //FULLY ANSI-C (32-bit) fixed point -typedef signed int coef_t; -typedef signed int out_data_t; -typedef signed int inp_data_t; -typedef signed int acc_t; - -const long long int THRESHOLD = (4*SAMPLES); -#endif - - -out_data_t fir_filter ( inp_data_t x, coef_t c[N] ); - -#endif // _H_FIR_H_ diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/fir_test.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/fir_test.cpp deleted file mode 100644 index 946c0271ed..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/1_fix_fir_filter/src/fir_test.cpp +++ /dev/null @@ -1,165 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -Author: Daniele Bagni, Xilinx Inc -*/ - - -#include -#include -#include - -#include "fir.h" - -#ifndef HLS_FIXED_POINT -const float factor = 16384.0; // 2^14 -const int log2_factor = 14; - -unsigned int ref_fir_filter (signed int x, signed int c[N]) -{ - static signed int ref_shift_reg[N]; - signed long long int acc = 0; - signed int mult; - signed int y; - for (int i=N-1;i>=0;i--) - { - if (i==0) - { - ref_shift_reg[0]=x; - } - else - { - ref_shift_reg[i] = ref_shift_reg[i-1]; - } - mult = ref_shift_reg[i]*c[i]; - acc = acc + ((unsigned long long int) mult); - } - y = acc; - return y; -} -#endif //#ifdef HLS_FIXED_POINT - -int main (void) -{ - - inp_data_t signal[SAMPLES]; - out_data_t output[SAMPLES], golden_ref[SAMPLES]; - coef_t taps[N]; - - FILE *fp1, *fp2, *fp3; - int i, ret_value; - float val1, val2; - int val3; - -#ifndef HLS_FIXED_POINT - float diff, tot_diff, max_diff; - tot_diff = 1e-9f; - max_diff = 1e-9f; -#else - signed long int diff; - signed long long tot_diff=0; - signed long max_diff=0; -#endif - - // LOAD FILTER COEFFICIENTS - fp1=fopen("./data/fir_coeff.dat","r"); - fscanf(fp1, "%*[^\n]\n"); //skip first line - fscanf(fp1, "%*[^\n]\n"); //skip second line - for (i=0;i> log2_factor; - output[i] = tmp; - fprintf(fp1,"%10.5f\n", (float) output[i]); -#endif - } - fclose(fp1); - - // CHECK RESULTS - for (i=0;i max_diff) max_diff=diff; - tot_diff += diff; -#else - diff = output[i] - golden_ref[i]; - if (i<64) fprintf(stdout,"output[%4d]=%10d \t golden_ref[%4d]=%10d\n", i, output[i], i, golden_ref[i] ); - if (diff<0) diff = 0 - diff; - if (diff > max_diff) max_diff=diff; - tot_diff += diff; - //fprintf(stdout,"diff=%10d max_diff=%10d\n", (int) diff, (int) max_diff); -#endif - } - fprintf(stdout, "TOTAL ERROR =%f MAX DIFF=%f\n", (float) tot_diff, (float) max_diff); - - if (tot_diff < THRESHOLD) - { - fprintf(stdout, "\nTEST PASSED!\n"); - ret_value =0; - } - else - { - fprintf(stdout, "\nTEST FAILED!\n"); - ret_value =1; - } - - - return ret_value; - - -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/Makefile b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/Makefile deleted file mode 100644 index 647d992271..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/Makefile +++ /dev/null @@ -1,14 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -.PHONY: help kernels clean all - -clean: - rm -rf *_prj *.log *~ - -kernels: - vitis-run --mode hls --tcl ./float_fir_script.tcl - - -all: kernels diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/float_fir_directives/directives0.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/float_fir_directives/directives0.tcl deleted file mode 100644 index da74336210..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/float_fir_directives/directives0.tcl +++ /dev/null @@ -1,6 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -set_directive_top -name fir_filter "fir_filter" -set_directive_bind_op -op fmul -impl fabric "fir_filter" mult -set_directive_bind_op -op fadd -impl fabric "fir_filter" acc diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/float_fir_directives/directives1.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/float_fir_directives/directives1.tcl deleted file mode 100644 index 90406ec7ba..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/float_fir_directives/directives1.tcl +++ /dev/null @@ -1,6 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -set_directive_top -name fir_filter "fir_filter" -set_directive_bind_op -op fmul -impl meddsp "fir_filter" mult -set_directive_bind_op -op fadd -impl fulldsp "fir_filter" acc diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/float_fir_directives/directives2.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/float_fir_directives/directives2.tcl deleted file mode 100644 index a9f6667a44..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/float_fir_directives/directives2.tcl +++ /dev/null @@ -1,6 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -set_directive_top -name fir_filter "fir_filter" -set_directive_bind_op -op fmul -impl fulldsp "fir_filter" mult -set_directive_bind_op -op fadd -impl fulldsp "fir_filter" acc diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/float_fir_directives/directives3.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/float_fir_directives/directives3.tcl deleted file mode 100644 index b80316faf9..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/float_fir_directives/directives3.tcl +++ /dev/null @@ -1,6 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -set_directive_top -name fir_filter "fir_filter" -set_directive_bind_op -op fmul -impl maxdsp "fir_filter" mult -set_directive_bind_op -op fadd -impl fulldsp "fir_filter" acc diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/float_fir_directives/directives4.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/float_fir_directives/directives4.tcl deleted file mode 100644 index 1b03cc4ca4..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/float_fir_directives/directives4.tcl +++ /dev/null @@ -1,8 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -set_directive_top -name fir_filter "fir_filter" -set_directive_bind_op -op fmul -impl maxdsp "fir_filter" mult -set_directive_bind_op -op fadd -impl fulldsp "fir_filter" acc -set_directive_pipeline "fir_filter" -set_directive_array_partition -dim 1 -type complete "fir_filter" c diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/float_fir_script.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/float_fir_script.tcl deleted file mode 100644 index 9ef16b3cb4..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/float_fir_script.tcl +++ /dev/null @@ -1,123 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -# Author: Daniele Bagni, Xilinx Inc - -puts "\n" -puts "************************************************************************" -puts "* 2) FLOATING POINT FIR FILTER DEMO" -puts "************************************************************************" -puts "\n" - - -puts " " -puts "Solution0: fadd/fmul with FABRIC" -puts " " -open_project vhls_float_fir_prj -set_top fir_filter -add_files src/fir.cpp -add_files -tb src/fir_test.cpp -cflags "-Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -add_files -tb src/data -open_solution "solution0" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -source "./float_fir_directives/directives0.tcl" -csim_design -clean -csynth_design -#cosim_design -#export_design -rtl vhdl -format ip_catalog -close_project - - -puts " " -puts "Solution1: fadd/fmul with DSP (full/med)" -puts " " -open_project vhls_float_fir_prj -set_top fir_filter -add_files src/fir.cpp -add_files -tb src/fir_test.cpp -cflags "-Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -add_files -tb src/data -open_solution "solution1" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -source "./float_fir_directives/directives1.tcl" -#csim_design -clean -csynth_design -#cosim_design -#export_design -rtl vhdl -format ip_catalog -close_project - - - -puts " " -puts "Solution2: fadd/fmul with DSP (full/full)" -puts " " -open_project vhls_float_fir_prj -set_top fir_filter -add_files src/fir.cpp -add_files -tb src/fir_test.cpp -cflags "-Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -add_files -tb src/data -open_solution "solution2" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -source "./float_fir_directives/directives2.tcl" -#csim_design -clean -csynth_design -#cosim_design -#export_design -rtl vhdl -format ip_catalog -close_project - - -puts " " -puts "Solution3: fadd/fmul with DSP (full/max)" -puts " " -open_project vhls_float_fir_prj -set_top fir_filter -add_files src/fir.cpp -add_files -tb src/fir_test.cpp -cflags "-Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -add_files -tb src/data -open_solution "solution3" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -source "./float_fir_directives/directives3.tcl" -#csim_design -clean -csynth_design -#cosim_design -#export_design -rtl vhdl -format ip_catalog -close_project - - - -puts " " -puts "Solution4: as 3 + top II=1 and array c partitioned" -puts " " -open_project vhls_float_fir_prj -set_top fir_filter -add_files src/fir.cpp -add_files -tb src/fir_test.cpp -cflags "-Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -add_files -tb src/data -open_solution "solution4" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -source "./float_fir_directives/directives4.tcl" -#csim_design -clean -csynth_design -#cosim_design -#export_design -rtl vhdl -format ip_catalog -close_project diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/run_float_fir_filter.sh b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/run_float_fir_filter.sh deleted file mode 100644 index b654afaeb1..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/run_float_fir_filter.sh +++ /dev/null @@ -1,5 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -vitis_hls float_fir_script.tcl diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/src/data/fir_coeff.dat b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/src/data/fir_coeff.dat deleted file mode 100644 index be86eef5ec..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/src/data/fir_coeff.dat +++ /dev/null @@ -1,18 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -0.180617 -0.045051 -0.723173 -0.347438 -0.660617 -0.383869 -0.627347 -0.021650 -0.910570 -0.800559 -0.745847 -0.813113 -0.383306 -0.617279 -0.575495 -0.530052 diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/src/data/input.dat b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/src/data/input.dat deleted file mode 100644 index 3b33d57b4e..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/src/data/input.dat +++ /dev/null @@ -1,1026 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. 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a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/src/data/ref_res.dat b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/src/data/ref_res.dat deleted file mode 100644 index bd1035b1c4..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/src/data/ref_res.dat +++ /dev/null @@ -1,1026 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. 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-4.777362 -5.047185 -4.553710 -5.196864 -5.168383 -5.223060 -4.986567 -5.217165 -5.240052 -4.902058 -5.634656 -5.170616 -5.098509 -4.880650 -4.825397 -4.041766 -4.570884 -3.998041 -3.558980 -4.250368 -3.922500 -4.349836 -3.596826 -4.122967 -3.128806 -4.258111 -3.460371 -4.130675 -3.810790 -4.468620 diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/src/fir.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/src/fir.cpp deleted file mode 100644 index 97ded1ec44..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/src/fir.cpp +++ /dev/null @@ -1,50 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -Author: Daniele Bagni, Xilinx Inc -*/ - -#include "fir.h" - -out_data_t fir_filter (inp_data_t x, coef_t c[N]) -{ - - static inp_data_t shift_reg[N]; - - acc_t acc = 0; - acc_t mult; - out_data_t y; - - -// OLD directives: now deprecated -//#pragma HLS RESOURCE variable=mult core=FMul_meddsp -//#pragma HLS RESOURCE variable=acc core=FAddSub_nodsp - - - - Shift_Accum_Loop: for (int i=N-1;i>=0;i--) - { -#pragma HLS LOOP_TRIPCOUNT min=1 max=16 avg=8 - - if (i==0) - { - //acc+=x*c[0]; - shift_reg[0]=x; - } - else - { - shift_reg[i]=shift_reg[i-1]; - //acc+=shift_reg[i]*c[i]; - } - //acc = acc + shift_reg[i]*c[i]; - mult = shift_reg[i]*c[i]; - acc = acc + mult; - - } - - y = (out_data_t) acc; - - return y; - -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/src/fir.h b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/src/fir.h deleted file mode 100644 index 193b2f7f7e..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/src/fir.h +++ /dev/null @@ -1,37 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -Author: Daniele Bagni, Xilinx Inc -*/ - -#ifndef _H_FIR_H_ -#define _H_FIR_H_ - -#define N 16 - -#define SAMPLES 1024 - -const float THRESHOLD = 1.0; - -//#define HLS_FIXED_POINT - -#ifdef HLS_FIXED_POINT -#include "ap_fixed.h" - -typedef ap_fixed<18,2> coef_t; -typedef ap_fixed<48,12> out_data_t; -typedef ap_fixed<18,2> inp_data_t; -typedef ap_fixed<48,12> acc_t; - -#else //FULLY Single-Precision (32-bit) Floating-Point -typedef float coef_t; -typedef float out_data_t; -typedef float inp_data_t; -typedef float acc_t; - -#endif - -out_data_t fir_filter ( inp_data_t x, coef_t c[N] ); - -#endif // _H_FIR_H_ diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/src/fir_test.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/src/fir_test.cpp deleted file mode 100644 index 96ac688ddc..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/2_float_fir_filter/src/fir_test.cpp +++ /dev/null @@ -1,114 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -Author: Daniele Bagni, Xilinx Inc -*/ - -#include -#include -#include - -#include "fir.h" - - -int main (void) -{ - - inp_data_t signal[SAMPLES]; - out_data_t output[SAMPLES], reference[SAMPLES]; - coef_t taps[N]; - - FILE *fp1, *fp2, *fp3; - int i, ret_value; - float val1, val2; - float diff, tot_diff; - int val3; - - tot_diff = 0; - - // LOAD FILTER COEFFICIENTS - fp1=fopen("./data/fir_coeff.dat","r"); - fscanf(fp1, "%*[^\n]\n"); //skip first line - fscanf(fp1, "%*[^\n]\n"); //skip second line - for (i=0;i -#include -#include -#include "ap_bmp.h" - - -//Open the BMP input file -FILE *BMP_InputOpen(char *name) -{ - FILE *bmp_file = fopen(name,"rb"); - if(bmp_file==NULL){ - printf("ERROR: could not open %s for reading\n",name); - } - return bmp_file; -} - -//Open the BMP output file -FILE *BMP_OutputOpen(char *name){ - FILE *bmp_file = fopen(name,"wb"); - if(!bmp_file){ - printf("ERROR: could not open %s for writing\n",name); - } - return bmp_file; -} - -//Close BMP file -int BMP_Close(FILE *bmp_file){ - if(bmp_file){ - fclose(bmp_file); - return 0; - } - else{ - printf("ERROR: could not close the BMP file\n"); - return 1; - } -} - -//Read the BMP file header -int BMP_Read_FileHeader(FILE *bmp_file, BMPHeader *file_header){ - if(!bmp_file){ - printf("ERROR: Can't read the image file\n"); - return 1; - } - - if(!fread(file_header,1,14,bmp_file)){ - printf("ERROR: Failed to read the image file header \n"); - return 1; - } - else - return 0; -} - -//Read the BMP data header -int BMP_Read_ImageHeader(FILE *bmp_file, BMPImageHeader *image_header){ - if(!bmp_file){ - printf("ERROR: Can't read the image file\n"); - return 1; - } - - if(!fread(image_header,1,40,bmp_file)){ - printf("ERROR: Failed to read the image data header \n"); - return 1; - } - else - return 0; -} - -//Read the BMP image data -int BMP_Read_Image(FILE *bmp_file, unsigned char *data, int size){ - if(!bmp_file){ - printf("ERROR: Can't read the image file\n"); - return 1; - } - - if(!fread(data,1,size,bmp_file)){ - printf("ERROR: Can't read the image data\n"); - return 1; - } - else{ - return 0; - } -} - -//Blank BMP Image -BMPImage *BMP_CreateBlank(void){ - BMPImage *bitmap = NULL; - BMPHeader *file_header = NULL; - BMPImageHeader *image_header = NULL; - - unsigned char *data; - - file_header = (BMPHeader *) calloc(sizeof(BMPHeader),1); - if(!file_header){ - printf("ERROR: Can't create file header in blank BMP\n"); - return NULL; - } - - image_header = (BMPImageHeader *) calloc(sizeof(BMPImageHeader),1); - if(!image_header){ - printf("ERROR: Can't create image header in blank BMP\n"); - if(file_header) free(file_header); - return NULL; - } - - bitmap = (BMPImage *) malloc(sizeof(BMPImage)); - if(!bitmap){ - printf("ERROR: Can't create image data in blank BMP\n"); - if(file_header) free(file_header); - if(image_header) free(image_header); - return NULL; - } - - data = (unsigned char *) malloc(MAX_COLS*MAX_ROWS*3); - if(!data){ - printf("ERROR: Allocate image temp space\n"); - if(file_header) free(file_header); - if(image_header) free(image_header); - if(bitmap) free(bitmap); - return NULL; - } - - bitmap->file_header = file_header; - bitmap->image_header = image_header; - bitmap->data = data; - - //Initialize to 0 - int i, j; - for(i = 0; i < MAX_ROWS; i++){ - for(j= 0; j < MAX_COLS; j++){ - bitmap->R[i][j]=0; - bitmap->G[i][j]=0; - bitmap->B[i][j]=0; - bitmap->Y[i][j]=0; - bitmap->U[i][j]=0; - bitmap->V[i][j]=0; - } - } - - return bitmap; -} - -//Delete bitmap from memory -void BMP_Delete(BMPImage *bitmap) -{ - if(bitmap){ - if(bitmap->file_header) free(bitmap->file_header); - if(bitmap->image_header) free(bitmap->image_header); - if(bitmap->data) free(bitmap->data); - free(bitmap); - } -} - - -//Read the image -int BMP_Read(char *file, int row, int col, unsigned char *R, unsigned char *G, unsigned char *B){ - BMPHeader *file_header = NULL; - BMPImageHeader *image_header = NULL; - unsigned char *image_data = NULL; - - FILE *bmp_file = NULL; - - int file_open; - - bmp_file = BMP_InputOpen(file); - - if(!bmp_file){ - printf("ERROR: Can't open file %s\n",file); - return 1; - } - - file_header = (BMPHeader *)malloc(sizeof(BMPHeader)); - if(!file_header){ - printf("ERROR: Can't allocate memory for file header\n"); - return 1; - } - - image_header = (BMPImageHeader *)malloc(sizeof(BMPImageHeader)); - if(!image_header){ - printf("ERROR: Can't allocate memory for image header\n"); - if(file_header) free(file_header); - return 1; - } - - int header_read; - header_read = BMP_Read_FileHeader(bmp_file,file_header); - - if(header_read){ - printf("ERROR: Can't read the image header\n"); - if(file_header) free(file_header); - if(image_header) free(image_header); - return 1; - } - - int img_header_read; - - img_header_read = BMP_Read_ImageHeader(bmp_file,image_header); - if(img_header_read){ - printf("ERROR: Can't read the data header\n"); - if(file_header) free(file_header); - if(image_header) free(image_header); - return 1; - } - - //Allocate memory for the image pixels - image_data = (unsigned char *)malloc(image_header->Height * image_header->Width * 3); - if(!image_data){ - printf("ERROR: Can't allocate memory for the image\n"); - if(file_header) free(file_header); - if(image_header) free(image_header); - return 1; - } - - int img_data_read; - - img_data_read = BMP_Read_Image(bmp_file,image_data,(image_header->Height*image_header->Width*3)); - if(img_data_read){ - printf("ERROR: Can't read the image data\n"); - if(file_header) free(file_header); - if(image_header) free(image_header); - if(image_data) free(image_data); - return 1; - } - - if(row != (int)image_header->Height){ - printf("ERROR: file image height %i different from requested height %i\n",image_header->Height,row); - if(file_header) free(file_header); - if(image_header) free(image_header); - if(image_data) free(image_data); - return 1; - } - - if(col != (int)image_header->Width){ - printf("ERROR: file image height %i different from requested height %i\n",image_header->Width,col); - if(file_header) free(file_header); - if(image_header) free(image_header); - if(image_data) free(image_data); - return 1; - } - - unsigned char *tmp = image_data; - - //Copy the image data into the storage arrays - int i, j; - for(i=0; i < row; i++){ - for(j=0; j < col; j++){ - unsigned char r_temp, b_temp, g_temp; - - b_temp = *tmp++; - g_temp = *tmp++; - r_temp = *tmp++; - - // printf("R %d G %d B %d\n",r_temp,b_temp,g_temp); - - R[(row-1-i)*col+j] = r_temp; - G[(row-1-i)*col+j] = g_temp; - B[(row-1-i)*col+j] = b_temp; - } - } - - BMP_Close(bmp_file); - - if(file_header) free(file_header); - if(image_header) free(image_header); - if(image_data) free(image_data); - - return 0; -} - -//Write the image to a file -int BMP_Write(char *file, int row, int col, unsigned char *R, unsigned char *G, unsigned char *B) -{ - BMPImage *bitmap = NULL; - FILE *output_image; - unsigned char *data; - - bitmap = BMP_CreateBlank(); - if(!bitmap){ - printf("ERROR: Can't create image for output file\n"); - return 1; - } - - bitmap->file_header->FileType = 19778; - bitmap->file_header->FileSize = 0; - bitmap->file_header->Reserved1 = 0; - bitmap->file_header->Reserved2 = 0; - bitmap->file_header->Offset = 54; - - bitmap->image_header->Size = 40; - bitmap->image_header->Width = col; - bitmap->image_header->Height = row; - bitmap->image_header->Planes = 1; - bitmap->image_header->BitsPerPixel = 24; - bitmap->image_header->Compression = 0; - bitmap->image_header->SizeOfBitmap = 3*row*col; - bitmap->image_header->HorzResolution = 2835; - bitmap->image_header->VertResolution = 2835; - bitmap->image_header->ColorsUsed = 0; - bitmap->image_header->ColorsImportant = 0; - - data = bitmap->data; - - //Store the image, bitmaps are stores upside down - int i, j; - for(i = 0; i < row; i++){ - for(j=0; j < col; j++){ - unsigned char r_temp, g_temp, b_temp; - - r_temp = R[(row-1-i)*col+j]; - g_temp = G[(row-1-i)*col+j]; - b_temp = B[(row-1-i)*col+j]; - - // printf("i %d j %d R %d G %d B %d\n",i, j,r_temp,g_temp,b_temp); - - *data++ = b_temp; - *data++ = g_temp; - *data++ = r_temp; - } - } - - output_image = fopen(file,"wb"); - if(!output_image){ - printf("ERROR: Can't open %s for writing\n",file); - BMP_Delete(bitmap); - return 1; - } - - fwrite(&bitmap->file_header->FileType,1,2,output_image); - fwrite(&bitmap->file_header->FileSize,1,4,output_image); - fwrite(&bitmap->file_header->Reserved1,1,2,output_image); - fwrite(&bitmap->file_header->Reserved2,1,2,output_image); - fwrite(&bitmap->file_header->Offset,1,4,output_image); - - fwrite(&bitmap->image_header->Size,1,4,output_image); - fwrite(&bitmap->image_header->Width,1,4,output_image); - fwrite(&bitmap->image_header->Height,1,4,output_image); - fwrite(&bitmap->image_header->Planes,1,2,output_image); - fwrite(&bitmap->image_header->BitsPerPixel,1,2,output_image); - fwrite(&bitmap->image_header->Compression,1,4,output_image); - fwrite(&bitmap->image_header->SizeOfBitmap,1,4,output_image); - fwrite(&bitmap->image_header->HorzResolution,1,4,output_image); - fwrite(&bitmap->image_header->VertResolution,1,4,output_image); - fwrite(&bitmap->image_header->ColorsUsed,1,4,output_image); - fwrite(&bitmap->image_header->ColorsImportant,1,4,output_image); - - fwrite(bitmap->data,1,bitmap->image_header->Height*bitmap->image_header->Width*3,output_image); - - fclose(output_image); - BMP_Delete(bitmap); - - return 0; -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/3_img_median_filter/src/ap_bmp.h b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/3_img_median_filter/src/ap_bmp.h deleted file mode 100644 index 1a9f3ad18c..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/3_img_median_filter/src/ap_bmp.h +++ /dev/null @@ -1,59 +0,0 @@ -/******************************************************************************* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*******************************************************************************/ - -#ifndef __XLNX__BITMAP__ -#define __XLNX__BITMAP__ - -// Basic color definitions -#define BLACK 0 -#define WHITE 255 - -// Maximum image size -#define MAX_ROWS 1080 -#define MAX_COLS 1920 - -//File Information Header -typedef struct{ - unsigned short FileType; - unsigned int FileSize; - unsigned short Reserved1; - unsigned short Reserved2; - unsigned short Offset; -}BMPHeader; - -typedef struct{ - unsigned int Size; - unsigned int Width; - unsigned int Height; - unsigned short Planes; - unsigned short BitsPerPixel; - unsigned int Compression; - unsigned int SizeOfBitmap; - unsigned int HorzResolution; - unsigned int VertResolution; - unsigned int ColorsUsed; - unsigned int ColorsImportant; -}BMPImageHeader; - -typedef struct{ - BMPHeader *file_header; - BMPImageHeader *image_header; - unsigned int *colors; - unsigned char *data; - unsigned char R[MAX_ROWS][MAX_COLS]; - unsigned char G[MAX_ROWS][MAX_COLS]; - unsigned char B[MAX_ROWS][MAX_COLS]; - unsigned char Y[MAX_ROWS][MAX_COLS]; - char U[MAX_ROWS][MAX_COLS]; - char V[MAX_ROWS][MAX_COLS]; -}BMPImage; - -//Read Function -int BMP_Read(char *file, int row, int col, unsigned char *R, unsigned char *G, unsigned char *B); - -//Write Function -int BMP_Write(char *file, int row, int col, unsigned char *R, unsigned char *G, unsigned char *B); - -#endif diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/3_img_median_filter/src/main_test.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/3_img_median_filter/src/main_test.cpp deleted file mode 100644 index 6d6a63ac4e..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/3_img_median_filter/src/main_test.cpp +++ /dev/null @@ -1,154 +0,0 @@ -/******************************************************************************* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*******************************************************************************/ - -#include -#include -#include -#include -#include "median.h" -#include "ap_bmp.h" - - -//pix_t rgb2y(RGB_t pix) -//{ -// pix_t y; -// -// // y = ((66 * pix.R + 129 * pix.G + 25 * pix.B + 128) >> 8) + 16; -// y = ((76 * pix.R + 150 * pix.G + 29 * pix.B + 128) >> 8) ; -// return y; -//} - - - -int main(void) -{ - - int x, y; - int width, height; - char *tempbuf; - char *tempbuf1; - char *tempbuf2; - char *tempbuf3; - char *tempbuf4; - - FILE *fp; - - int check_results = 0; - int diff_R, diff_G, diff_B; - - tempbuf = (char *) malloc(MAX_PATH * sizeof(char)); - tempbuf1 = (char *) malloc(MAX_PATH * sizeof(char)); - - // Arrays to store image data - unsigned char *R, *G, *B; - - //Arrays to send and receive data from the accelerator - pix_t in_pix[MAX_HEIGHT][MAX_WIDTH]; - pix_t out_pix[MAX_HEIGHT][MAX_WIDTH]; - pix_t ref_pix[MAX_HEIGHT][MAX_WIDTH]; - - R = (unsigned char *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(unsigned char)); - G = (unsigned char *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(unsigned char)); - B = (unsigned char *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(unsigned char)); - - //Get image data from disk - sprintf(tempbuf, "%s.bmp", INPUT_IMAGE_BASE); - - // Fill a frame with data - int read_tmp = BMP_Read(tempbuf, MAX_HEIGHT, MAX_WIDTH, R, G, B); - if(read_tmp != 0) { - printf("%s Loading image failed\n", tempbuf); - exit (1); - } - printf("Loaded image file %s of size %4d %4d\n", tempbuf, MAX_HEIGHT, MAX_WIDTH); - - // Copy Input Image to pixel data structure - // Hardware accelerator works on video pixel streams - for(y = 0; y < MAX_HEIGHT; y++){ - for(x = 0; x < MAX_WIDTH; x++){ - RGB_t pixel; - pixel.R = (pix_t) R[y*MAX_WIDTH + x]; - pixel.G = (pix_t) G[y*MAX_WIDTH + x]; - pixel.B = (pix_t) B[y*MAX_WIDTH + x]; - - in_pix[y][x] = pixel.G; //rgb2y(pixel); - } - } - - -#ifdef __SYNTHESIS__ - width = 1920; - height = 1080; -#else - width = 1920; - height = 1080; -#endif - - - - printf("Running the Design Under Test Median[%d][%d] on image size of W=%4d H=%4d\n", KMED, KMED, width, height); - top_median(in_pix, out_pix, height, width); //, fp); - ref_median(in_pix, ref_pix, height, width); //, fp); - - - // Copy Output video pixel stream to Output Image data structure - for(y =0; y < height; y++){ - for(x = 0; x < width; x++){ - pix_t pixel = out_pix[y][x]; - R[y*MAX_WIDTH + x] = (unsigned char) pixel; - G[y*MAX_WIDTH + x] = (unsigned char) pixel; - B[y*MAX_WIDTH + x] = (unsigned char) pixel; - } - } - - //Write the output median image back to disk - sprintf(tempbuf1, "%s.bmp", OUTPUT_IMAGE_BASE); - int write_tmp = BMP_Write(tempbuf1, MAX_HEIGHT, MAX_WIDTH, R, G, B); - if(write_tmp != 0){ - printf("WriteBMP %s failed\n", tempbuf1); - exit(1); - } - - - check_results = 0; - for (y = KMED; y < height-KMED; y++) - { - for (x = KMED; x < width -KMED; x++) - { - diff_R = ref_pix[y][x] - out_pix[y][x]; - diff_R = ABS(diff_R); - int tot_diff = diff_R; - check_results = check_results + diff_R; - //if (tot_diff > 0) - //{ - //printf("x=%3d y=%3d Y=%3d rY=%3d\n", x, y, out_pix[y][x], ref_pix[y][x]); - //printf("diffR=%3d\n", diff_R); - //break; - //} - } - } - printf("median test done\n"); - - - free(R); - free(G); - free(B); - free(tempbuf); - free(tempbuf1); - - if (check_results > 0) - { - printf("TEST FAILED!: error = %d\n", check_results); - check_results = 1; - } - else - { - printf("TEST SUCCESSFUL!\n"); - check_results = 0; - } - - return check_results; - -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/3_img_median_filter/src/median.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/3_img_median_filter/src/median.cpp deleted file mode 100644 index c2a7b9e029..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/3_img_median_filter/src/median.cpp +++ /dev/null @@ -1,208 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#include -#include -#include "median.h" - - - -pix_t sorting_network(pix_t window[KMED*KMED]) -{ -//#pragma HLS PIPELINE II=1 -#pragma HLS INLINE - - int const N=KMED*KMED; - pix_t t[N]; - pix_t z[N]; - - pix_t pixel; - pix_t med_val; - char i, k, stage; - - -for (i=0; i(z); -L2: for (stage = 1; stage <= N; stage++) - { -//#pragma HLS LOOP_TRIPCOUNT min=1 max=9 - - if ((stage%2)==1) - k=0; - if ((stage%2)==0) - k=1; - -L3:for (i = k; i= KKMED) & (col >= KKMED) & (row<(height-KKMED)) & (col<(width-KKMED)) ) - { - med = sorting_network(window); - } - else - { - med = 0; - } - - - //The output image is offset from the input to account for the line buffer - if ((row >= KKMED) & (col >= KKMED) ) - { - pix_t output_pixel; - output_pixel = med; - - out_pix[row-KKMED][col-KKMED] = output_pixel; - } - - - - } - } - - -} - - - - -void ref_median(pix_t in_pix[MAX_HEIGHT][MAX_WIDTH], - pix_t ref_pix[MAX_HEIGHT][MAX_WIDTH], - short height, short width) //, FILE *fp) -{ - short int row; - short int col; - static int cnt=0; - pix_t pix, med; - signed char x,y; - - pix_t window[KMED*KMED]; - - L1: for(row = 0; row < height+KKMED; row++) - { -#pragma HLS LOOP_TRIPCOUNT min=600 max=1080 avg=720 - L2: for(col = 0; col < width+KKMED; col++) - { -#pragma HLS PIPELINE II=1 -#pragma HLS LOOP_TRIPCOUNT min=800 max=1920 avg=1280 - - //This design assumes there are no edges on the boundary of the image - if ( (row >= KMED-1) & (col >= KMED-1) & (row < height) & (col< width) ) - { - L3:for (y=-KMED+1; y<=0; y++) - //L3:for (y=-2; y<=0; y++) - { - - //#pragma HLS LOOP_TRIPCOUNT min=3 max=3 - L4: for (x=-KMED+1; x<=0; x++) - //L4: for (x=-2; x<=0; x++) - { - //#pragma HLS LOOP_TRIPCOUNT min=3 max=3 - - window[(KMED-1+y)*KMED+(KMED-1+x)] = in_pix[row+y][col+x]; - //printf("%3d ", window[(KMED-1+y)*KMED+(KMED-1+x)]); - } - //printf("\n"); - } - pix = sorting_network(window); - ref_pix[row-KKMED][col-KKMED] = pix; - - } - - } // end of L2 - } // end of L1 - - -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/3_img_median_filter/src/median.h b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/3_img_median_filter/src/median.h deleted file mode 100644 index 0ea21fceb3..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/3_img_median_filter/src/median.h +++ /dev/null @@ -1,118 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#ifndef _H_MEDIAN_H_ -#define _H_MEDIAN_H_ - - -//#include "ap_axi_sdata.h" -//#include "ap_interfaces.h" -//#include "ap_bmp.h" - -/* ******************************************************************************* */ -// CONSTANT PARAMETERS - -#define MAX_PATH 1000 - -#define MAX_HEIGHT 1080 -#define MAX_WIDTH 1920 - - //#define KMED3 - -#if defined(KMED3) -#define KMED 3 -#elif defined(KMED5) -#define KMED 5 -#elif defined(KMED7) -#define KMED 7 -#else -#error -#endif - -#define KKMED (KMED/2) -#define BLOCKSIZE KMED - - -/* ******************************************************************************* */ -// I/O Image Settings -#define INPUT_IMAGE_BASE "./test_data/noisy_rgb2y_1080p" - -#if (KMED==7) -//#error < KMED IS 7> -#define OUTPUT_IMAGE_BASE "./test_data/c_out_median7x7_1080p" -#elif (KMED==5) -//#error < KMED IS 5> -#define OUTPUT_IMAGE_BASE "./test_data/c_out_median5x5_1080p" -#elif (KMED==3) -//#error < KMED IS 3> -#define OUTPUT_IMAGE_BASE "./test_data/c_out_median3x3_1080p" -#endif - -//#define REFER_IMAGE_BASE "./test_data/golden_out_median_1080p" -//#define REFER_VAR_BASE "./test_data/golden_out_variance_1080p" -//#define OUTPUT_VAR_BASE "./test_data/c_out_variance_1080p" -//#define C_REFER_IMAGE_BASE "./test_data/c_golden_out_median_1080p" - -/* ******************************************************************************* */ -// SMALL FUNCTIONS IN MACRO -#define ABSDIFF(x,y) ( (x)>(y) ? (x - y) : (y - x) ) -#define ABS(x) ( (x)> 0 ? (x) : -(x) ) -#define MIN(x,y) ( (x)>(y) ? (y) : (x) ) -#define MAX(x,y) ( (x)>(y) ? (x) : (y) ) - - - - -/* ******************************************************************************* */ -// DATA TYPES - -//#define DB_FIXED_POINT - -#ifndef DB_FIXED_POINT -typedef unsigned char pix_t; -#else -#include -typedef ap_uint<11> pix_t; -#endif - -//#define FLOAT_VAR -#ifndef FLOAT_VAR -typedef int var_t; -#else -typedef float var_t; -#endif - -typedef struct ap_rgb{ - unsigned char B; - unsigned char G; - unsigned char R; - } RGB_t; - -typedef signed short int int16_t; -typedef unsigned short int uint16_t; - -//typedef ap_axiu<32,1,1,1> AXI_PIXEL; -//typedef pix_t AXI_PIXEL; - - -/* ******************************************************************************* */ -// FUNCTION PROTOTYPES - -int main_median(void); - -pix_t median(pix_t window[KMED*KMED]); - -void top_median( pix_t in_pix[MAX_HEIGHT][MAX_WIDTH], - pix_t out_pix[MAX_HEIGHT][MAX_WIDTH], - short height, short width); //, FILE *fp); - - -void ref_median(pix_t in_pix[MAX_HEIGHT][MAX_WIDTH], - pix_t ref_pix[MAX_HEIGHT][MAX_WIDTH], - short height, short width); //, FILE *fp); - - - -#endif diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/3_img_median_filter/src/test_data/gray_test.bmp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/3_img_median_filter/src/test_data/gray_test.bmp deleted file mode 100644 index 52440e54ae..0000000000 Binary files a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/3_img_median_filter/src/test_data/gray_test.bmp and /dev/null differ diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/3_img_median_filter/src/test_data/medFilt_test_results.m b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/3_img_median_filter/src/test_data/medFilt_test_results.m deleted file mode 100644 index eed84d2917..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/3_img_median_filter/src/test_data/medFilt_test_results.m +++ /dev/null @@ -1,116 +0,0 @@ -% Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -% SPDX-License-Identifier: MIT - -%% -close all; -clear all; -clc - -%% input test image - -I = imread('../../../5_img_histEq/common/test_data/test_1080p.bmp', 'BMP'); % original RGB image -figure; imshow(I, []); title 'Input RGB Image' -G = rgb2gray(I); % black and white image -figure; imshow(G, []); title 'Input GRAY Image' - -%% add noise - -J = imnoise(G,'salt & pepper',0.08); % add noise -figure; imshow(J, []); title 'Noisy Input Image' - -%% median filter the noisy image - -M3 = medfilt2(J, [3,3]); -M5 = medfilt2(J, [5,5]); -M7 = medfilt2(J, [7,7]); -figure; imshow(M5, []); title 'M5 Filtered Image' -figure; imshow(M3, []); title 'M3 Filtered Image' -figure; imshow(M7, []); title 'M7 Filtered Image' - -%% write images - -imwrite(G, 'gray_test.bmp'); -imwrite(J, 'noisy_rgb2y_1080p.bmp'); -imwrite(M3, 'm_golden_median3x3_1080p.bmp'); -imwrite(M5, 'm_golden_median5x5_1080p.bmp'); -imwrite(M7, 'm_golden_median7x7_1080p.bmp'); - - -% -% %% MEDIAN 3x3 -% II3 = imread('c_out_median3x3_1080p.bmp', 'BMP'); -% dII3 = double(II3); -% -% RR3 = imread('m_golden_median3x3_1080p.bmp', 'BMP'); -% dRR3 = double(RR3); -% -% figure; imshow(II7); title 'C output MEDIAN 3x3' -% figure; imshow(RR7); title 'M GOLDEN output MEDIAN 3x3' -% -% diff_m7 = abs(dRR7 - dII7); -% index_m7 = diff_m7 >0; -% sum(index_m7(:)) -% diff_m7(1:6, :,:) = 0; diff_m7(:, 1:6,:) = 0; diff_m7(end-6:end, :,:) = 0; diff_m7(:, end-6:end, :) = 0; -% index_m7 = diff_m7 >0; -% sum(index_m7(:)) -% figure; imshow(diff_m7,[]); title 'DIFF MEDIAN 7x7 C vs. MATLAB' -% sum_abs_diff_m7 = sum(diff_m7(:)) -% -% -% %% MEDIAN 7x7 -% II7 = imread('c_out_median7x7_1080p.bmp', 'BMP'); -% dII7 = double(II7); -% -% RR7 = imread('m_golden_median7x7_1080p.bmp', 'BMP'); -% dRR7 = double(RR7); -% -% figure; imshow(II7); title 'C output MEDIAN 7x7' -% figure; imshow(RR7); title 'M GOLDEN output MEDIAN 7x7' -% -% diff_m7 = abs(dRR7 - dII7); -% index_m7 = diff_m7 >0; -% sum(index_m7(:)) -% diff_m7(1:6, :,:) = 0; diff_m7(:, 1:6,:) = 0; diff_m7(end-6:end, :,:) = 0; diff_m7(:, end-6:end, :) = 0; -% index_m7 = diff_m7 >0; -% sum(index_m7(:)) -% figure; imshow(diff_m7,[]); title 'DIFF MEDIAN 7x7 C vs. MATLAB' -% sum_abs_diff_m7 = sum(diff_m7(:)) -% -% %% MEDIAN 5x5 -% II5 = imread('c_out_median5x5_1080p.bmp', 'BMP'); -% dII5 = double(II5); -% -% RR5 = imread('m_golden_median5x5_1080p.bmp', 'BMP'); -% dRR5 = double(RR5); -% -% figure; imshow(II5); title 'C output MEDIAN 5x5' -% figure; imshow(RR5); title 'M GOLDEN output MEDIAN 5x5' -% -% diff_m5 = abs(dRR5 - dII5); -% index_m5 = diff_m5 >0; -% sum(index_m5(:)) -% diff_m5(1:4, :,:) = 0; diff_m5(:, 1:4,:) = 0; diff_m5(end-4:end, :,:) = 0; diff_m5(:, end-4:end, :) = 0; -% index_m5 = diff_m5 >0; -% sum(index_m5(:)) -% figure; imshow(diff_m5,[]); title 'DIFF MEDIAN 5x5 C vs. MATLAB' -% sum_abs_diff_m5 = sum(diff_m5(:)) -% -% %% MEDIAN 3x3 -% II3 = imread('c_out_median3x3_1080p.bmp', 'BMP'); -% dII3 = double(II3); -% -% RR3 = imread('m_golden_median3x3_1080p.bmp', 'BMP'); -% dRR3 = double(RR3); -% -% figure; imshow(II3); title 'C output MEDIAN 3x3' -% figure; imshow(RR3); title 'M GOLDEN output MEDIAN 3x3' -% -% diff_m3 = abs(dRR3 - dII3); -% index_m3 = diff_m3 >0; -% sum(index_m3(:)) -% diff_m3(1:2, :,:) = 0; diff_m3(:, 1:2,:) = 0; diff_m3(end-2:end, :,:) = 0; diff_m3(:, end-2:end, :) = 0; -% index_m3 = diff_m3 >0; -% sum(index_m3(:)) -% figure; imshow(diff_m3,[]); title 'DIFF MEDIAN 3x3 C vs. MATLAB' -% sum_abs_diff_m3 = sum(diff_m3(:)) -% %% diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/3_img_median_filter/src/test_data/noisy_rgb2y_1080p.bmp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/3_img_median_filter/src/test_data/noisy_rgb2y_1080p.bmp deleted file mode 100644 index 7966e50a63..0000000000 Binary files a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/3_img_median_filter/src/test_data/noisy_rgb2y_1080p.bmp and /dev/null differ diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/4_dependency/Makefile b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/4_dependency/Makefile deleted file mode 100644 index 1937ff9ed9..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/4_dependency/Makefile +++ /dev/null @@ -1,14 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -.PHONY: help kernels clean all - -clean: - rm -rf *_prj *.log *~ - -kernels: - vitis-run --mode hls --tcl ./run_dependence_script.tcl - - -all: kernels diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/4_dependency/dependency.h b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/4_dependency/dependency.h deleted file mode 100644 index 5bd959776d..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/4_dependency/dependency.h +++ /dev/null @@ -1,16 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#ifndef H_DEPENDENCY_H -#define H_DEPENDENCY_H - -const int nOfSamples = 4*1024; -const int nOfBins = 256; - -void top_histogram(unsigned char din[nOfSamples], unsigned short int dout[nOfBins], const int n_Of_Samples, const int n_Of_Bins); - - - -#endif diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/4_dependency/main_dependency.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/4_dependency/main_dependency.cpp deleted file mode 100644 index 8e7e9d687c..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/4_dependency/main_dependency.cpp +++ /dev/null @@ -1,70 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ -#include -#include - -#include "dependency.h" - -int main(void) -{ - - unsigned char din[nOfSamples]; - unsigned short int dout[nOfBins], ref[nOfBins]; - - int i; - FILE *f = fopen("data.txt", "w"); - if (f==NULL) - fprintf(stderr, "error in opening output data file\n"); - - // clear output arrays - for(i=0; i0) - { - printf("got %5d expected %5d\n", dout[i], ref[i]); - tot_err++; - } - } - - - if (tot_err==0) - printf("\nTEST OK\n"); - else - printf("\nTEST FAILED: %d wrong values\n", tot_err); - - fclose(f); - return 0; //tot_err; - - -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/4_dependency/run_dependence_script.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/4_dependency/run_dependence_script.tcl deleted file mode 100644 index 840cfcf947..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/4_dependency/run_dependence_script.tcl +++ /dev/null @@ -1,154 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -# Author: Daniele Bagni, Xilinx Inc - -puts "\n" -puts "************************************************************************" -puts "* EXAMPLE 4) ABOUT PRAGMA DEPENDENCE on RAW TRUE DUAL PORT BRAMs" -puts "************************************************************************" -puts "\n" - - -############## ORIGINAL C CODE PURELY SEQUENTIAL ##################### - -# solution0: default compiler behavior -open_project hls_dep_prj -set_top top_histogram -add_files top_dependency2.cpp -cflags "-DDB_ORIGINAL" -add_files -tb main_dependency.cpp -cflags "-Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -open_solution "sol0_orig_default" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -set_directive_top -name top_histogram "top_histogram" -csim_design -clean -csynth_design -cosim_design -close_project - -open_project hls_dep_prj -set_top top_histogram -add_files top_dependency2.cpp -cflags "-DDB_ORIGINAL" -add_files -tb main_dependency.cpp -cflags "-Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -# solution1: what if set_directive_dependence -variable hist -type inter WAR -dependent false -open_solution "sol1_orig_depINTER_WAR" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -set_directive_top -name top_histogram "top_histogram" -set_directive_dependence -dependent false -direction WAR -type inter -variable hist "top_histogram" -csynth_design -cosim_design -close_project - -# solution1: what if set_directive_dependence -variable hist -type inter RAW -dependent false -open_project hls_dep_prj -set_top top_histogram -add_files top_dependency2.cpp -cflags "-DDB_ORIGINAL" -add_files -tb main_dependency.cpp -cflags "-Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -open_solution "sol1_orig_depINTER_RAW" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -set_directive_top -name top_histogram "top_histogram" -set_directive_dependence -dependent false -direction RAW -type inter -variable hist "top_histogram" -csynth_design -cosim_design -close_project - -# solution1: set_directive_dependence -variable hist -type intra RAW -dependent false -open_project hls_dep_prj -set_top top_histogram -add_files top_dependency2.cpp -cflags "-DDB_ORIGINAL" -add_files -tb main_dependency.cpp -cflags "-Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -open_solution "sol1_orig_depINTRA" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -set_directive_top -name top_histogram "top_histogram" -set_directive_dependence -dependent false -direction RAW -type intra -variable hist "top_histogram" -csynth_design -cosim_design -close_project - -############## OPTIMIZED C CODE WITH SMALL CACHE ##################### - -# solution2: default compiler behavior -open_project hls_dep_prj -set_top top_histogram -add_files top_dependency2.cpp -add_files -tb main_dependency.cpp -cflags "-Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -open_solution "sol2_cache_default" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -set_directive_top -name top_histogram "top_histogram" -csim_design -clean -csynth_design -cosim_design -close_project - -# solution3: set_directive_dependence -dependent false -direction RAW -type intra -variable hist "top_histogram" -open_project hls_dep_prj -set_top top_histogram -add_files top_dependency2.cpp -add_files -tb main_dependency.cpp -cflags "-Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -open_solution "sol3_cache_depINTRA_RAW" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -set_directive_top -name top_histogram "top_histogram" -set_directive_dependence -dependent false -direction RAW -type intra -variable hist "top_histogram" -csim_design -clean -csynth_design -cosim_design -close_project - -# solution3: set_directive_dependence -dependent false -direction RAW -type inter -variable hist "top_histogram" -open_project hls_dep_prj -set_top top_histogram -add_files top_dependency2.cpp -add_files -tb main_dependency.cpp -cflags "-Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -open_solution "sol3_cache_depINTER_RAW" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -set_directive_top -name top_histogram "top_histogram" -set_directive_dependence -dependent false -direction RAW -type inter -variable hist "top_histogram" -csim_design -clean -csynth_design -cosim_design -close_project - -# solution3: set_directive_dependence -dependent false -direction WAR -type inter -variable hist "top_histogram" -open_project hls_dep_prj -set_top top_histogram -add_files top_dependency2.cpp -add_files -tb main_dependency.cpp -cflags "-Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -open_solution "sol3_cache_depINTER_WAR" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 5 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 1 -set_directive_top -name top_histogram "top_histogram" -set_directive_dependence -dependent false -direction WAR -type inter -variable hist "top_histogram" -csim_design -clean -csynth_design -cosim_design -close_project diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/4_dependency/top_dependency2.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/4_dependency/top_dependency2.cpp deleted file mode 100644 index 01e35ffd57..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/4_dependency/top_dependency2.cpp +++ /dev/null @@ -1,100 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#include "dependency.h" - -#ifdef DB_ORIGINAL // solutions 0 & 1 - -void top_histogram(unsigned char din[nOfSamples], unsigned short int dout[nOfBins], - const int n_Of_Samples, const int n_Of_Bins) -{ - #pragma HLS INTERFACE ap_fifo port=dout - #pragma HLS INTERFACE ap_fifo port=din - - static unsigned short int hist[nOfBins]; - #pragma HLS BIND_STORAGE variable=hist type=ram_t2p impl=bram - //#pragma HLS RESOURCE variable=hist core=RAM_T2P_BRAM // NOW OBSOLETE and replaced by BIND_STORAGE - //#pragma HLS DEPENDENCE variable=hist inter false // this is what Vitis HLS compiler does to get II=1 with this code - - unsigned char val; - - // compute histogram - L1:for (int i=0; i -#include -#include - -#include "ap_bmp.h" - - -//Open the BMP input file -FILE *BMP_InputOpen(char *name) -{ - FILE *bmp_file = fopen(name,"rb"); - if(!bmp_file){ - printf("ERROR: could not open %s for reading\n",name); - } - return bmp_file; -} - -//Open the BMP output file -FILE *BMP_OutputOpen(char *name){ - FILE *bmp_file = fopen(name,"wb"); - if(!bmp_file){ - printf("ERROR: could not open %s for writing\n",name); - } - return bmp_file; -} - -//Close BMP file -int BMP_Close(FILE *bmp_file){ - if(bmp_file){ - fclose(bmp_file); - return 0; - } - else{ - printf("ERROR: could not close %s\n",bmp_file); - return 1; - } -} - -//Read the BMP file header -int BMP_Read_FileHeader(FILE *bmp_file, BMPHeader *file_header){ - if(!bmp_file){ - printf("ERROR: Can't read the image file\n"); - return 1; - } - - if(!fread(file_header,1,14,bmp_file)){ - printf("ERROR: Failed to read the image file header \n"); - return 1; - } - else - return 0; -} - -//Read the BMP data header -int BMP_Read_ImageHeader(FILE *bmp_file, BMPImageHeader *image_header){ - if(!bmp_file){ - printf("ERROR: Can't read the image file\n"); - return 1; - } - - if(!fread(image_header,1,40,bmp_file)){ - printf("ERROR: Failed to read the image data header \n"); - return 1; - } - else - return 0; -} - -//Read the BMP image data -int BMP_Read_Image(FILE *bmp_file, unsigned char *data, int size){ - if(!bmp_file){ - printf("ERROR: Can't read the image file\n"); - return 1; - } - - if(!fread(data,1,size,bmp_file)){ - printf("ERROR: Can't read the image data\n"); - return 1; - } - else{ - return 0; - } -} - -//Blank BMP Image -BMPImage *BMP_CreateBlank(void){ - BMPImage *bitmap = NULL; - BMPHeader *file_header = NULL; - BMPImageHeader *image_header = NULL; - - unsigned char *data; - - file_header = (BMPHeader *) calloc(sizeof(BMPHeader),1); - if(!file_header){ - printf("ERROR: Can't create file header in blank BMP\n"); - return NULL; - } - - image_header = (BMPImageHeader *) calloc(sizeof(BMPImageHeader),1); - if(!image_header){ - printf("ERROR: Can't create image header in blank BMP\n"); - if(file_header) free(file_header); - return NULL; - } - - bitmap = (BMPImage *) malloc(sizeof(BMPImage)); - if(!bitmap){ - printf("ERROR: Can't create image data in blank BMP\n"); - if(file_header) free(file_header); - if(image_header) free(image_header); - return NULL; - } - - data = (unsigned char *) malloc(MAX_COLS*MAX_ROWS*3); - if(!data){ - printf("ERROR: Allocate image temp space\n"); - if(file_header) free(file_header); - if(image_header) free(image_header); - if(bitmap) free(bitmap); - return NULL; - } - - bitmap->file_header = file_header; - bitmap->image_header = image_header; - bitmap->data = data; - - //Initialize to 0 - int i, j; - for(i = 0; i < MAX_ROWS; i++){ - for(j= 0; j < MAX_COLS; j++){ - bitmap->R[i][j]=0; - bitmap->G[i][j]=0; - bitmap->B[i][j]=0; - bitmap->Y[i][j]=0; - bitmap->U[i][j]=0; - bitmap->V[i][j]=0; - } - } - - return bitmap; -} - -//Delete bitmap from memory -void BMP_Delete(BMPImage *bitmap) -{ - if(bitmap){ - if(bitmap->file_header) free(bitmap->file_header); - if(bitmap->image_header) free(bitmap->image_header); - if(bitmap->data) free(bitmap->data); - free(bitmap); - } -} - - -//Read the image -int BMP_Read(char *file, int row, int col, unsigned char *R, unsigned char *G, unsigned char *B){ - BMPHeader *file_header = NULL; - BMPImageHeader *image_header = NULL; - unsigned char *image_data = NULL; - - FILE *bmp_file = NULL; - - int file_open; - - bmp_file = BMP_InputOpen(file); - - if(!bmp_file){ - printf("ERROR: Can't open file %s\n",file); - return 1; - } - - file_header = (BMPHeader *)malloc(sizeof(BMPHeader)); - if(!file_header){ - printf("ERROR: Can't allocate memory for file header\n"); - return 1; - } - - image_header = (BMPImageHeader *)malloc(sizeof(BMPImageHeader)); - if(!image_header){ - printf("ERROR: Can't allocate memory for image header\n"); - if(file_header) free(file_header); - return 1; - } - - int header_read; - header_read = BMP_Read_FileHeader(bmp_file,file_header); - - if(header_read){ - printf("ERROR: Can't read the image header\n"); - if(file_header) free(file_header); - if(image_header) free(image_header); - return 1; - } - - int img_header_read; - - img_header_read = BMP_Read_ImageHeader(bmp_file,image_header); - if(img_header_read){ - printf("ERROR: Can't read the data header\n"); - if(file_header) free(file_header); - if(image_header) free(image_header); - return 1; - } - - //Allocate memory for the image pixels - image_data = (unsigned char *)malloc(image_header->Height * image_header->Width * 3); - if(!image_data){ - printf("ERROR: Can't allocate memory for the image\n"); - if(file_header) free(file_header); - if(image_header) free(image_header); - return 1; - } - - int img_data_read; - - img_data_read = BMP_Read_Image(bmp_file,image_data,(image_header->Height*image_header->Width*3)); - if(img_data_read){ - printf("ERROR: Can't read the image data\n"); - if(file_header) free(file_header); - if(image_header) free(image_header); - if(image_data) free(image_data); - return 1; - } - - if(row != (int)image_header->Height){ - printf("ERROR: file image height %i different from requested height %i\n",image_header->Height,row); - if(file_header) free(file_header); - if(image_header) free(image_header); - if(image_data) free(image_data); - return 1; - } - - if(col != (int)image_header->Width){ - printf("ERROR: file image height %i different from requested height %i\n",image_header->Width,col); - if(file_header) free(file_header); - if(image_header) free(image_header); - if(image_data) free(image_data); - return 1; - } - - unsigned char *tmp = image_data; - - //Copy the image data into the storage arrays - int i, j; - for(i=0; i < row; i++){ - for(j=0; j < col; j++){ - unsigned char r_temp, b_temp, g_temp; - - b_temp = *tmp++; - g_temp = *tmp++; - r_temp = *tmp++; - - // printf("R %d G %d B %d\n",r_temp,b_temp,g_temp); - - R[(row-1-i)*col+j] = r_temp; - G[(row-1-i)*col+j] = g_temp; - B[(row-1-i)*col+j] = b_temp; - } - } - - BMP_Close(bmp_file); - - if(file_header) free(file_header); - if(image_header) free(image_header); - if(image_data) free(image_data); - - return 0; -} - -//Write the image to a file -int BMP_Write(char *file, int row, int col, unsigned char *R, unsigned char *G, unsigned char *B) -{ - BMPImage *bitmap = NULL; - FILE *output_image; - unsigned char *data; - - bitmap = BMP_CreateBlank(); - if(!bitmap){ - printf("ERROR: Can't create image for output file\n"); - return 1; - } - - bitmap->file_header->FileType = 19778; - bitmap->file_header->FileSize = 0; - bitmap->file_header->Reserved1 = 0; - bitmap->file_header->Reserved2 = 0; - bitmap->file_header->Offset = 54; - - bitmap->image_header->Size = 40; - bitmap->image_header->Width = col; - bitmap->image_header->Height = row; - bitmap->image_header->Planes = 1; - bitmap->image_header->BitsPerPixel = 24; - bitmap->image_header->Compression = 0; - bitmap->image_header->SizeOfBitmap = 3*row*col; - bitmap->image_header->HorzResolution = 2835; - bitmap->image_header->VertResolution = 2835; - bitmap->image_header->ColorsUsed = 0; - bitmap->image_header->ColorsImportant = 0; - - data = bitmap->data; - - //Store the image, bitmaps are stores upside down - int i, j; - for(i = 0; i < row; i++){ - for(j=0; j < col; j++){ - unsigned char r_temp, g_temp, b_temp; - - r_temp = R[(row-1-i)*col+j]; - g_temp = G[(row-1-i)*col+j]; - b_temp = B[(row-1-i)*col+j]; - - // printf("i %d j %d R %d G %d B %d\n",i, j,r_temp,g_temp,b_temp); - - *data++ = b_temp; - *data++ = g_temp; - *data++ = r_temp; - } - } - - output_image = fopen(file,"wb"); - if(!output_image){ - printf("ERROR: Can't open %s for writing\n",file); - BMP_Delete(bitmap); - return 1; - } - - fwrite(&bitmap->file_header->FileType,1,2,output_image); - fwrite(&bitmap->file_header->FileSize,1,4,output_image); - fwrite(&bitmap->file_header->Reserved1,1,2,output_image); - fwrite(&bitmap->file_header->Reserved2,1,2,output_image); - fwrite(&bitmap->file_header->Offset,1,4,output_image); - - fwrite(&bitmap->image_header->Size,1,4,output_image); - fwrite(&bitmap->image_header->Width,1,4,output_image); - fwrite(&bitmap->image_header->Height,1,4,output_image); - fwrite(&bitmap->image_header->Planes,1,2,output_image); - fwrite(&bitmap->image_header->BitsPerPixel,1,2,output_image); - fwrite(&bitmap->image_header->Compression,1,4,output_image); - fwrite(&bitmap->image_header->SizeOfBitmap,1,4,output_image); - fwrite(&bitmap->image_header->HorzResolution,1,4,output_image); - fwrite(&bitmap->image_header->VertResolution,1,4,output_image); - fwrite(&bitmap->image_header->ColorsUsed,1,4,output_image); - fwrite(&bitmap->image_header->ColorsImportant,1,4,output_image); - - fwrite(bitmap->data,1,bitmap->image_header->Height*bitmap->image_header->Width*3,output_image); - - fclose(output_image); - BMP_Delete(bitmap); - - return 0; -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/ap_bmp.h b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/ap_bmp.h deleted file mode 100644 index 753d46b5f7..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/ap_bmp.h +++ /dev/null @@ -1,59 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#ifndef __XLNX__BITMAP__ -#define __XLNX__BITMAP__ - -// Basic color definitions -#define BLACK 0 -#define WHITE 255 - -// Maximum image size -#define MAX_ROWS 1080 -#define MAX_COLS 1920 - -//File Information Header -typedef struct{ - unsigned short FileType; - unsigned int FileSize; - unsigned short Reserved1; - unsigned short Reserved2; - unsigned short Offset; -}BMPHeader; - -typedef struct{ - unsigned int Size; - unsigned int Width; - unsigned int Height; - unsigned short Planes; - unsigned short BitsPerPixel; - unsigned int Compression; - unsigned int SizeOfBitmap; - unsigned int HorzResolution; - unsigned int VertResolution; - unsigned int ColorsUsed; - unsigned int ColorsImportant; -}BMPImageHeader; - -typedef struct{ - BMPHeader *file_header; - BMPImageHeader *image_header; - unsigned int *colors; - unsigned char *data; - unsigned char R[MAX_ROWS][MAX_COLS]; - unsigned char G[MAX_ROWS][MAX_COLS]; - unsigned char B[MAX_ROWS][MAX_COLS]; - unsigned char Y[MAX_ROWS][MAX_COLS]; - char U[MAX_ROWS][MAX_COLS]; - char V[MAX_ROWS][MAX_COLS]; -}BMPImage; - -//Read Function -int BMP_Read(char *file, int row, int col, unsigned char *R, unsigned char *G, unsigned char *B); - -//Write Function -int BMP_Write(char *file, int row, int col, unsigned char *R, unsigned char *G, unsigned char *B); - -#endif diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/cdf.h b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/cdf.h deleted file mode 100644 index 17640cd2c5..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/cdf.h +++ /dev/null @@ -1,259 +0,0 @@ -// Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -// SPDX-License-Identifier: MIT - - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 4591, - 26977, - 48282, - 67606, - 80476, - 90016, - 96881, - 102603, - 108967, - 114091, - 119702, - 123732, - 127545, - 131261, - 135052, - 139070, - 142659, - 145785, - 148561, - 151215, - 154031, - 157233, - 160163, - 163166, - 165654, - 168165, - 170948, - 173950, - 177030, - 179982, - 182488, - 185049, - 187904, - 190994, - 194080, - 197090, - 199597, - 201950, - 204584, - 207475, - 210160, - 212784, - 214917, - 216940, - 219062, - 221398, - 223763, - 225935, - 227909, - 229620, - 231614, - 233808, - 236036, - 238211, - 240075, - 241791, - 243423, - 245416, - 247533, - 249554, - 251280, - 252886, - 254521, - 256420, - 258295, - 260155, - 261839, - 263303, - 264666, - 266267, - 267972, - 269498, - 270806, - 271904, - 272997, - 274169, - 275408, - 276611, - 277649, - 278510, - 279383, - 280211, - 281117, - 282046, - 282827, - 283489, - 284078, - 284699, - 285374, - 286031, - 286611, - 287154, - 287612, - 288086, - 288597, - 289132, - 289664, - 290080, - 290462, - 290875, - 291297, - 291701, - 292102, - 292443, - 292711, - 292992, - 293329, - 293652, - 293938, - 294201, - 294432, - 294657, - 294940, - 295234, - 295501, - 295724, - 295921, - 296121, - 296355, - 296566, - 296763, - 296938, - 297122, - 297286, - 297448, - 297630, - 297823, - 297967, - 298107, - 298237, - 298402, - 298564, - 298726, - 298859, - 298982, - 299099, - 299227, - 299354, - 299490, - 299611, - 299720, - 299815, - 299920, - 300034, - 300150, - 300261, - 300343, - 300443, - 300536, - 300631, - 300744, - 300834, - 300927, - 301003, - 301083, - 301175, - 301280, - 301381, - 301471, - 301527, - 301615, - 301711, - 301818, - 301912, - 301996, - 302057, - 302123, - 302192, - 302267, - 302351, - 302424, - 302488, - 302549, - 302625, - 302690, - 302759, - 302813, - 302873, - 302925, - 302980, - 303059, - 303125, - 303210, - 303265, - 303325, - 303397, - 303470, - 303545, - 303599, - 303653, - 303714, - 303770, - 303841, - 303902, - 303968, - 304018, - 304077, - 304131, - 304193, - 304260, - 304324, - 304374, - 304438, - 304511, - 304584, - 304672, - 304741, - 304815, - 304904, - 304989, - 305121, - 305258, - 305429, - 305626, - 305837, - 306126, - 306496, - 306898, - 307153, - 307200, - 307200, - 307200, - 307200, - 307200, - 307200, - 307200, - 307200, - 307200, - 307200, - 307200, - 307200, - 307200, - 307200, - 307200, - 307200, - 307200, - 307200, - 307200, - 307200, - 307200 diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/histogram.h b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/histogram.h deleted file mode 100644 index 9e7c02b0e5..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/histogram.h +++ /dev/null @@ -1,13 +0,0 @@ -// Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -// SPDX-License-Identifier: MIT - -#ifndef _H_HISTOGRAM_H_ -#define _H_HISTOGRAM_H_ - -#include "my_defines.h" - -uint19_t prev_hist[GRAY_LEVELS] = { -#include "./test_data/m_histogram.h" -}; - -#endif diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/main_test.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/main_test.cpp deleted file mode 100644 index 39f2cef3f8..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/main_test.cpp +++ /dev/null @@ -1,163 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#include -#include -#include -#include -#include "my_defines.h" -#include "ap_bmp.h" - - -int main(void) -{ - - int x, y; - int width, height; - char *tempbuf; - char *tempbuf1; - - FILE *fp; - - int check_results = 0; - int diff_R, diff_G, diff_B, tot_err; - int tot_diff_R=0; - int tot_diff_B=0; - int tot_diff_G=0; - int tot_diff_H=0; - int tot_diff_C=0; - - uint25_t cdf[GRAY_LEVELS] = {0}; - uint19_t ref_hist[GRAY_LEVELS] = { 0 }; - uint25_t ref_cdf[GRAY_LEVELS] = { 0 }; - - tempbuf = (char *) malloc(MAX_PATH * sizeof(char)); - tempbuf1 = (char *) malloc(MAX_PATH * sizeof(char)); - - // Arrays to read/write BMP image file - uint8_t *R, *G, *B; - //Arrays to send and receive data from the accelerator - RGB_t *inp_img; - RGB_t *ref_img; - - //memory allocation - R = (uint8_t *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(uint8_t)); - G = (uint8_t *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(uint8_t)); - B = (uint8_t *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(uint8_t)); - inp_img = (RGB_t *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(RGB_t)); - ref_img = (RGB_t *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(RGB_t)); - uint8_t *inp_R = (uint8_t *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(uint8_t)); - uint8_t *inp_G = (uint8_t *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(uint8_t)); - uint8_t *inp_B = (uint8_t *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(uint8_t)); - uint8_t *out_R = (uint8_t *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(uint8_t)); - uint8_t *out_G = (uint8_t *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(uint8_t)); - uint8_t *out_B = (uint8_t *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(uint8_t)); - - //Get image data from file - sprintf(tempbuf, "%s.bmp", INPUT_IMAGE_BASE); - // Fill a frame with data - int read_tmp = BMP_Read(tempbuf, MAX_HEIGHT, MAX_WIDTH, R, G, B); - if(read_tmp != 0) { - printf("%s Loading image failed\n", tempbuf); - exit (1); - } - printf("Loaded image file %s of size %4d %4d\n", tempbuf, MAX_HEIGHT, MAX_WIDTH); - - // Copy Input Image to pixel data structure - // Hardware accelerator works on video pixel streams - for(y = 0; y < MAX_HEIGHT; y++){ - for(x = 0; x < MAX_WIDTH; x++){ - inp_R[y*MAX_WIDTH + x] = R[y*MAX_WIDTH + x]; - inp_G[y*MAX_WIDTH + x] = G[y*MAX_WIDTH + x]; - inp_B[y*MAX_WIDTH + x] = B[y*MAX_WIDTH + x]; - inp_img[y*MAX_WIDTH + x].R = R[y*MAX_WIDTH + x]; - inp_img[y*MAX_WIDTH + x].G = G[y*MAX_WIDTH + x]; - inp_img[y*MAX_WIDTH + x].B = B[y*MAX_WIDTH + x]; - } - } - - // if you want to save simulation time you can decrease both dimensions by 4 - width = MAX_WIDTH; //1920; - height = MAX_HEIGHT; //1080; - - - // compute the histogram and equalize the image to create golden results to check vs. the DUT - ref_img_hist_equaliz( width, height, ref_hist, inp_img, ref_img); - - printf("Running the Design Under Test on image size of W=%4d H=%4d\n", width, height); - wrapper_histogram_equaliz( width, height,ref_hist, inp_R,inp_G,inp_B, out_R,out_G,out_B); - - check_results = 0; - for (y = 0; y < height; y++) - { - for (x = 0; x < width; x++) - { - diff_R = out_R[y*MAX_WIDTH + x] - ref_img[y*MAX_WIDTH + x].R; - diff_R = ABS(diff_R); - tot_diff_R = + diff_R; - diff_G = out_G[y*MAX_WIDTH + x] - ref_img[y*MAX_WIDTH + x].G; - diff_G = ABS(diff_G); - tot_diff_G = + diff_G; - diff_B = out_B[y*MAX_WIDTH + x] - ref_img[y*MAX_WIDTH + x].B; - diff_B = ABS(diff_B); - tot_diff_B = + diff_B; - } - } - tot_err = tot_diff_R + tot_diff_G + tot_diff_B; - printf("\ntotal error in images = %d\n", tot_err); - - - // Copy Output video stream to Image data structure - for(y =0; y < height; y++){ - for(x = 0; x < width; x++){ - R[y*MAX_WIDTH + x] = out_R[y*MAX_WIDTH + x]; - G[y*MAX_WIDTH + x] = out_G[y*MAX_WIDTH + x]; - B[y*MAX_WIDTH + x] = out_B[y*MAX_WIDTH + x]; - } - } - //Write the output image back to disk - sprintf(tempbuf1, "%s.bmp", OUTPUT_IMAGE_BASE); - int write_tmp = BMP_Write(tempbuf1, MAX_HEIGHT, MAX_WIDTH, R, G, B); - if(write_tmp != 0){ - printf("WriteBMP %s failed\n", tempbuf1); - exit(1); - } - // Copy reference video stream to Image data structure - for(y =0; y < height; y++){ - for(x = 0; x < width; x++){ - R[y*MAX_WIDTH + x] = ref_img[y*MAX_WIDTH + x].R; - G[y*MAX_WIDTH + x] = ref_img[y*MAX_WIDTH + x].G; - B[y*MAX_WIDTH + x] = ref_img[y*MAX_WIDTH + x].B; - } - } - //Write the reference image back to disk - sprintf(tempbuf1, "%s.bmp", REFER_IMAGE_BASE); - write_tmp = BMP_Write(tempbuf1, MAX_HEIGHT, MAX_WIDTH, R, G, B); - if(write_tmp != 0){ - printf("WriteBMP %s failed\n", tempbuf1); - exit(1); - } - - //free memory - free(R); free(G); free(B); - free(tempbuf); free(tempbuf1); - free(inp_R); free(inp_G); free(inp_B); - free(out_R); free(out_G); free(out_B); - free(ref_img); free(inp_img); - - if (tot_err > 0) - { - printf("TEST FAILED!: error = %d\n", check_results); - check_results = 1; - } - else - { - printf("TEST SUCCESSFUL!\n"); - check_results = 0; - } - - return check_results; - -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/my_defines.h b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/my_defines.h deleted file mode 100644 index bc6be9b9a2..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/my_defines.h +++ /dev/null @@ -1,87 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - - -#ifndef H_DB_DEFINES_H -#define H_DB_DEFINES_H - - -/* ************************************************************************* */ -/* MAX IMAGE SIZE: */ -/* ************************************************************************* */ - - -#define MAX_WIDTH 1920 -#define MAX_HEIGHT 1080 - -#define MAX_PATH 1000 - -#define GRAY_LEVELS 256 - -#define CLIP(x) (((x)>255) ? 255 : (((x)<0) ? 0 : (x))) -#define ABS(x) ((x) < (-(x)) ? (-(x)) : (x)) - -/* ******************************************************************************* */ -// I/O Image Settings -#define INPUT_IMAGE_BASE "./test_data/test_1080p" -#define OUTPUT_IMAGE_BASE "./test_data/c_out_1080p" -#define REFER_IMAGE_BASE "./test_data/golden_out_1080p" - - -/* ************************************************************************* */ -/* COMPILERS DIRECTIVES */ -/* ************************************************************************* */ - -#ifdef DB_BIT_ACCURATE - -#include "ap_int.h" - -typedef ap_uint<8> uint8_t; -typedef ap_uint<7> uint7_t; -typedef ap_uint<1> uint1_t; -typedef ap_uint<11> uint11_t; -typedef ap_uint<16> uint16_t; -typedef ap_uint<19> uint19_t; -typedef ap_uint<25> uint25_t; -typedef ap_uint<32> uint32_t; -typedef ap_int<11> int11_t; -typedef ap_int<9> int9_t; - -#else - -typedef unsigned char uint8_t; -typedef unsigned char uint7_t; -typedef unsigned char uint1_t; -typedef unsigned short uint11_t; -typedef unsigned short uint16_t; -typedef unsigned long int uint19_t; -typedef unsigned long int uint25_t; -typedef unsigned long int uint32_t; -typedef signed short int11_t; -typedef signed short int9_t; - -#endif - -typedef struct ap_rgb{ - uint8_t R; - uint8_t G; - uint8_t B; - } RGB_t; - - - void ref_img_hist_equaliz( uint11_t width, uint11_t height, uint19_t hist[GRAY_LEVELS], - RGB_t inp_img[MAX_HEIGHT * MAX_WIDTH], RGB_t out_img[MAX_HEIGHT * MAX_WIDTH]); - - void wrapper_histogram_equaliz( uint11_t width, uint11_t height, uint19_t hist[GRAY_LEVELS], - uint8_t inp_R[MAX_WIDTH*MAX_HEIGHT], - uint8_t inp_G[MAX_WIDTH*MAX_HEIGHT], - uint8_t inp_B[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_R[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_G[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_B[MAX_WIDTH*MAX_HEIGHT]); - - - -#endif /* H_DB_DEFINES_H */ diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/ref_histogram.h b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/ref_histogram.h deleted file mode 100644 index b9fdf7da92..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/ref_histogram.h +++ /dev/null @@ -1,15 +0,0 @@ -// Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -// SPDX-License-Identifier: MIT - - -#ifndef _H_REF_HISTOGRAM_H_ -#define _H_REF_HISTOGRAM_H_ - -#include "my_defines.h" - - -uint19_t ref_prev_hist[GRAY_LEVELS] = { -#include "./test_data/m_histogram.h" -}; - -#endif diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/ref_img_hist.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/ref_img_hist.cpp deleted file mode 100644 index 917e1cc6a0..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/ref_img_hist.cpp +++ /dev/null @@ -1,216 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#include -#include -#include -#include - -#include "my_defines.h" -#include "ref_histogram.h" - - -/* ######################################################################### */ - -// computes the Cumulative Density Function cdf[] from the Histrogram hist[] -void ref_compute_cdf(uint19_t hist[GRAY_LEVELS], uint25_t cdf[GRAY_LEVELS]) -{ - uint8_t i, k; - - CDF_L1: for (k = 0; k < GRAY_LEVELS-1; k++) - { - uint25_t tmp_cdf=0; - CDF_L2: for (i = 0; i<=k; i++) - { - tmp_cdf = tmp_cdf + hist[i]; - } - cdf[k] = tmp_cdf; - } - - return; - -} - -/* ######################################################################### */ - -// Computes the histogram of Y plane -void ref_compute_hist( uint11_t width, uint11_t height, uint19_t hist[GRAY_LEVELS], RGB_t inp_img[MAX_WIDTH*MAX_HEIGHT]) -{ - - int i; - uint11_t x, y; - uint8_t Y, U, V; - - - Ly: for (y=0; y> 8; - tmp_G = tmp_G >> 8; - tmp_B = tmp_B >> 8; - R = CLIP( tmp_R); - G = CLIP( tmp_G); - B = CLIP( tmp_B); - out_img[y*MAX_WIDTH +x].R = R; - out_img[y*MAX_WIDTH +x].G = G; - out_img[y*MAX_WIDTH +x].B = B; - - } // end of Lx loop - } // end of Ly loop -} - - -/* ######################################################################### */ - -void ref_rgb2yuv( uint11_t width, uint11_t height, RGB_t inp_img[MAX_WIDTH*MAX_HEIGHT], RGB_t out_img[MAX_WIDTH*MAX_HEIGHT]) -{ - int i; - uint11_t x, y; - int9_t R, G, B, Y, U, V; - - const int9_t Wrgb[3][3] = { - { 66, 129, 25}, - {-38, -74, 112}, - {122, -94, -18}, - }; - - Ly: for (y=0; y> 8) + 16; - tmp_U = ( tmp_U >> 8) + 128; - tmp_V = ( tmp_V >> 8) + 128; - Y = CLIP(tmp_Y); - U = CLIP(tmp_U); - V = CLIP(tmp_V); - out_img[y*MAX_WIDTH +x].R = Y; - out_img[y*MAX_WIDTH +x].G = U; - out_img[y*MAX_WIDTH +x].B = V; - - } // end of Lx loop - } // end of Ly loop - -} - -/* ######################################################################### */ - -void ref_equalization( uint11_t width, uint11_t height, uint25_t cdf[GRAY_LEVELS], - RGB_t inp_img[MAX_WIDTH*MAX_HEIGHT], RGB_t out_img[MAX_WIDTH*MAX_HEIGHT]) -{ - - int i; - uint11_t x, y; - uint8_t Y, U, V; - - Ly: for (y=0; y= (GRAY_LEVELS-1)) - cdf_int = (GRAY_LEVELS-1); - else if (cdf_int <= 0 ) - cdf_int = 0; - Y = (uint8_t) cdf_int; - out_img[y*MAX_WIDTH +x].R = Y; - out_img[y*MAX_WIDTH +x].G = U; - out_img[y*MAX_WIDTH +x].B = V; - - } // end of Lx loop - } // end of Ly loop - -} - - -/* ######################################################################### */ - -void ref_img_hist_equaliz( uint11_t width, uint11_t height, uint19_t hist[GRAY_LEVELS], - RGB_t inp_img[MAX_WIDTH*MAX_HEIGHT], RGB_t out_img[MAX_WIDTH*MAX_HEIGHT]) -{ - uint25_t cdf[GRAY_LEVELS]; - - RGB_t *yuv = (RGB_t *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(RGB_t)); - RGB_t *yeq = (RGB_t *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(RGB_t)); - - // RGB to YUV conversion of current image I(n) - ref_rgb2yuv(width, height, inp_img, yuv); - - // compute histogram of current image I(n) - //// commented to avoid overwriting the reference histogram pre-computed in MATLAB - ////ref_compute_hist(width, height, hist, yuv); - - //compute CDF - ref_compute_cdf(hist, cdf); - - // equalize the current image I(n) - ref_equalization(width, height, cdf, yuv, yeq); - - // YUV to RGB conversion of current image I(n) - ref_yuv2rgb(width, height, yeq, out_img); - - free(yuv); - free(yeq); - -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/test_data/golden_out_1080p.bmp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/test_data/golden_out_1080p.bmp deleted file mode 100644 index e6e9aaa44a..0000000000 Binary files a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/test_data/golden_out_1080p.bmp and /dev/null differ diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/test_data/histEq_test_results.m b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/test_data/histEq_test_results.m deleted file mode 100644 index b78329188a..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/test_data/histEq_test_results.m +++ /dev/null @@ -1,105 +0,0 @@ -% Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -% SPDX-License-Identifier: MIT - -%% -% based on below paper -% https://www.nxp.com/docs/en/application-note/AN4318.pdf - -close all; -clear all; -clc - -%% memory allocation - -images_histogram = zeros(1, 256); -cdf = zeros(1, 256); -h = zeros(1, 256); -my_eq_Y = zeros(1080, 1920); - -if 0 -%% Histogram Equalization with builtin functions - -RGB = imread('test_1080p.bmp', 'BMP'); -f1=figure; imshow(RGB, []); title(f1.CurrentAxes, 'RGB input') -YCBCR = rgb2ycbcr(RGB); -f2=figure; imshow(YCBCR, []); title(f2.CurrentAxes, 'YCBCR input') - -Y = YCBCR(:,:, 1); -f3=figure; imshow(Y, []); title(f3.CurrentAxes, 'input Y ch only') -eq_Y = histeq(Y, 256); -f4=figure; imshow(eq_Y, []); title(f4.CurrentAxes, 'MATLAB equalized Y ch') - -eq_YCBCR = YCBCR; -eq_YCBCR(:,:,1)=eq_Y; -f5=figure; imshow(eq_YCBCR, []); title(f5.CurrentAxes, 'MATLAB equalized YCBCR') - -eq_I = ycbcr2rgb(eq_YCBCR); -f6=figure; imshow(eq_I, []); title(f6.CurrentAxes, 'MATLAB equalized YCBCR2RGB') - -%% Doing things manually - -% Getting histogram -fid = fopen("tmp_histogram.h", "w"); -for grey_level = 0:1:255 - images_histogram(grey_level + 1) = 0; - for i = 1:1:1920 - for j = 1:1:1080 - if Y(j,i) == grey_level - images_histogram(grey_level + 1) = images_histogram(grey_level + 1) + 1; - end - end - end - fprintf(fid, "%d,\n", uint32(images_histogram(grey_level + 1)) ); -end -fclose(fid); - -%Cumulative distribution function (cdf) -for grey_level = 1:1:256 - cdf(grey_level) = 0; - for i = 1:1:grey_level - cdf(grey_level) = cdf(grey_level) + images_histogram(i); - end -end - -gain = 255 /(1920*1080-1) -for i = 1:1:256 - h(i) = (cdf(i)-1) * gain; -end - -% equalization -for i = 1:1:1920 - for j = 1:1:1080 - y = Y(j,i); - my_eq_Y(j,i) = uint8(h(y+1)); - end -end -f7=figure; imshow(my_eq_Y, []); title(f7.CurrentAxes, 'my Equalized Y Image') -eq_YCBCR(:,:,1) = my_eq_Y; -eq_I = ycbcr2rgb(eq_YCBCR); -f8=figure; imshow(eq_I, []); title(f8.CurrentAxes, 'my equalized YUV2RGB') - -save -ascii -double ref_hist.txt images_histogram -save -ascii -double ref_cdf.txt cdf - -diff = abs(double(eq_Y) - my_eq_Y); -f9=figure; imshow(diff, []); title(f9.CurrentAxes, 'DIFF equalized Y') - -max_min = [max(diff(:)) min(diff(:))] - -end % if 0 - -%% testing output from C code - -C = imread('c_out_1080p.bmp', 'BMP'); -figure; imshow(C(:,:, 2), []); title 'HLS output image' -dC = double(C); - -R = imread('golden_out_1080p.bmp', 'BMP'); -dR = double(R); -figure; imshow(R(:,:,2), []); title 'HLS Golden Image' - -diff_y = abs(dR - dC); -diff_y(1:3, :,:) = 0; diff_y(:, 1:3,:) = 0; diff_y(end-3:end, :,:) = 0; diff_y(:, end-3:end, :) = 0; -index_y = diff_y >0; -sum_index_rgb2y_diff = sum(index_y(:)) -figure; imshow(diff_y); title 'DIFF' diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/test_data/m_histogram.h b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/test_data/m_histogram.h deleted file mode 100644 index 171788a5ce..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/test_data/m_histogram.h +++ /dev/null @@ -1,259 +0,0 @@ -// Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -// SPDX-License-Identifier: MIT - -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -39, -183, -1156, -3716, -6081, -5439, -5260, -6643, -9666, -12577, -13835, -15245, -14705, -15018, -19141, -14756, -13188, -12277, -11102, -11869, -15104, -15155, -13826, -13694, -11442, -10933, -11644, -12608, -11092, -10490, -8865, -8389, -9349, -10689, -9648, -9387, -8016, -8335, -9549, -10854, -10693, -10235, -9030, -9174, -10272, -11251, -11299, -10628, -9471, -9436, -10608, -12039, -10968, -10672, -8962, -8616, -9795, -10421, -10749, -9805, -8981, -8401, -9139, -10513, -10937, -9810, -8928, -8332, -9184, -10481, -11338, -10620, -9868, -9076, -10193, -11162, -12377, -11762, -10239, -9130, -9797, -11055, -11187, -10938, -9642, -8842, -9509, -10634, -11051, -11773, -10532, -9634, -10304, -11623, -11978, -12193, -10505, -9277, -9781, -10593, -11444, -12145, -10869, -10147, -11083, -12296, -14697, -14007, -14359, -12862, -13641, -17865, -20369, -20483, -20708, -17980, -17577, -19547, -19432, -18796, -16499, -13481, -12074, -12853, -13698, -15053, -12681, -10746, -9746, -10466, -11127, -11516, -10623, -9073, -8413, -8798, -10016, -10280, -9876, -8742, -7940, -8781, -9611, -10174, -9930, -9063, -8443, -9358, -10773, -10762, -10669, -8728, -8005, -8641, -9524, -9594, -9830, -8188, -7597, -8050, -8917, -8965, -9124, -8093, -7427, -7740, -8682, -9806, -9858, -8133, -6607, -6824, -7375, -7502, -7896, -7182, -6520, -6814, -7310, -7580, -7288, -6380, -6584, -6161, -6612, -8100, -7726, -6668, -5818, -5172, -5110, -5901, -5280, -4889, -4195, -4095, -4500, -4920, -4704, -4481, -3876, -3558, -3745, -3794, -3693, -3188, -2691, -2499, -2414, -2680, -2629, -2576, -2345, -2348, -2465, -2743, -2625, -2204, -1991, -460, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0 diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/test_data/test_1080p.bmp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/test_data/test_1080p.bmp deleted file mode 100644 index 12e2a454fe..0000000000 Binary files a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/test_data/test_1080p.bmp and /dev/null differ diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/test_data/test_results.m b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/test_data/test_results.m deleted file mode 100644 index 7ca6db2a8f..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/common/test_data/test_results.m +++ /dev/null @@ -1,96 +0,0 @@ -% Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -% SPDX-License-Identifier: MIT - -%% -#https://www.nxp.com/docs/en/application-note/AN4318.pdf -close all; -clear all; -clc - -%% -images_histogram = zeros(1, 256); -cdf = zeros(1, 256); -h = zeros(1, 256); -my_eq_Y = zeros(1080, 1920); - -%% -RGB = imread('test_1080p.bmp', 'BMP'); -f1=figure; imshow(RGB, []); title(f1.CurrentAxes, 'RGB input') -YCBCR = rgb2ycbcr(RGB); -%f2=figure; imshow(YCBCR, []); title(f2.CurrentAxes, 'YCBCR input') - -Y = YCBCR(:,:, 1); -f3=figure; imshow(Y, []); title(f3.CurrentAxes, 'input Y ch') -eq_Y = histeq(Y, 256); -f4=figure; imshow(eq_Y, []); title(f4.CurrentAxes, 'MATLAB equalized Y ch') - -eq_YCBCR = YCBCR; -eq_YCBCR(:,:,1)=eq_Y; -%f5=figure; imshow(eq_YCBCR, []); title(f5.CurrentAxes, 'MATLAB equalized YCBCR') - -eq_I = ycbcr2rgb(eq_YCBCR); -f6=figure; imshow(eq_I, []); title(f6.CurrentAxes, 'MATLAB equalized YCBCR2RGB') - - - -%% -% Getting histogram -for grey_level = 0:1:255 - images_histogram(grey_level + 1) = 0; - for i = 1:1:1920 - for j = 1:1:1080 - if Y(j,i) == grey_level - images_histogram(grey_level + 1) = images_histogram(grey_level + 1) + 1; - end - end - end -end - -%Cumulative distribution function (cdf) -for grey_level = 1:1:256 - cdf(grey_level) = 0; - for i = 1:1:grey_level - cdf(grey_level) = cdf(grey_level) + images_histogram(i); - end -end - -gain = 255 /(1920*1080-1) -for i = 1:1:256 - h(i) = (cdf(i)-1) * gain; -end - -for i = 1:1:1920 - for j = 1:1:1080 - y = Y(j,i); - my_eq_Y(j,i) = uint8(h(y+1)); - end -end -f7=figure; imshow(my_eq_Y, []); title(f7.CurrentAxes, 'my Equalized Y Image') -eq_YCBCR(:,:,1) = my_eq_Y; -eq_I = ycbcr2rgb(eq_YCBCR); -f8=figure; imshow(eq_I, []); title(f8.CurrentAxes, 'my equalized YUV2RGB') - -save -ascii -double ref_hist.txt images_histogram -save -ascii -double ref_cdf.txt cdf - -diff = abs(double(eq_Y) - my_eq_Y); -f9=figure; imshow(diff, []); title(f9.CurrentAxes, 'DIFF equalized Y') - -max_min = [max(diff(:)) min(diff(:))] - -%% -if 0 -C = imread('c_out_1080p.bmp', 'BMP'); -figure; imshow(C(:,:, 2), []); title 'HLS output image' -dC = double(C); - -R = imread('golden_out_1080p.bmp', 'BMP'); -dR = double(R); -figure; imshow(R(:,:,2), []); title 'HLS Golden Image' - -diff_y = abs(dR - dC); -diff_y(1:3, :,:) = 0; diff_y(:, 1:3,:) = 0; diff_y(end-3:end, :,:) = 0; diff_y(:, end-3:end, :) = 0; -index_y = diff_y >0; -sum_index_rgb2y_diff = sum(index_y(:)) -figure; imshow(diff_y); title 'DIFF' -end diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/img_hist_v3.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/img_hist_v3.cpp deleted file mode 100644 index 50a125c365..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/img_hist_v3.cpp +++ /dev/null @@ -1,274 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#include -#include -#include - -#include "my_defines.h" -#include "histogram.h" - -const int IMG_DEPTH = MAX_WIDTH*MAX_HEIGHT; -const int CDF_DEPTH = GRAY_LEVELS; - -/* ######################################################################### */ - -// computes the Cumulative Density Function cdf[] from the Histrogram hist[] -void compute_cdf(uint19_t hist[GRAY_LEVELS], uint25_t cdf[GRAY_LEVELS]) -{ - uint8_t i, k; - CDF_L1:for (k = 0; k < GRAY_LEVELS-1; k++) - { - uint25_t tmp_cdf=0; - CDF_L2:for (i = 0; i<=k; i++) - { - #pragma HLS PIPELINE - #pragma HLS LOOP_TRIPCOUNT min=1 max=256 avg=256 - // cdf for current picture from past picture histogram - tmp_cdf = tmp_cdf + hist[i]; - } - cdf[k] = tmp_cdf; - } - - return; - -} - -/* ######################################################################### */ - -void yuv2rgb( uint11_t width, uint11_t height, - //RGB_t inp_img[MAX_HEIGHT * MAX_WIDTH], RGB_t out_img[MAX_HEIGHT * MAX_WIDTH]) - uint8_t inp_Y[MAX_WIDTH*MAX_HEIGHT], - uint8_t inp_U[MAX_WIDTH*MAX_HEIGHT], - uint8_t inp_V[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_R[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_G[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_B[MAX_WIDTH*MAX_HEIGHT]) -{ - - int i; - uint11_t x, y; - int9_t R, G, B, Y, U, V; - int9_t C, D, E; - const int11_t Wyuv[3][3] = { - {298, 0, 409}, - {298, -100, -208}, - {298, 516, 0} - }; - - Ly: for (y=0; y> 8; - tmp_G = tmp_G >> 8; - tmp_R = tmp_R >> 8; - R = CLIP( tmp_R ); - G = CLIP( tmp_G ); - B = CLIP( tmp_B ); - out_R[y*MAX_WIDTH +x] = R; - out_G[y*MAX_WIDTH +x] = G; - out_B[y*MAX_WIDTH +x] = B; - - } // end of Lx loop= - } // end of Ly loop -} - - -/* ######################################################################### */ - -void rgb2yuv( uint11_t width, uint11_t height, - //RGB_t inp_img[MAX_HEIGHT * MAX_WIDTH], RGB_t out_img[MAX_HEIGHT * MAX_WIDTH]) - uint8_t inp_R[MAX_WIDTH*MAX_HEIGHT], - uint8_t inp_G[MAX_WIDTH*MAX_HEIGHT], - uint8_t inp_B[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_Y[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_U[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_V[MAX_WIDTH*MAX_HEIGHT]) -{ - int i; - uint11_t x, y; - int9_t R, G, B, Y, U, V; - const int9_t Wrgb[3][3] = { - { 66, 129, 25}, - {-38, -74, 112}, - {122, -94, -18}, - }; - - Ly: for (y=0; y> 8; - short int tmp_U = ( Wrgb[1][0] * R + Wrgb[1][1] * G + Wrgb[1][2] * B + 128) >> 8; - short int tmp_V = ( Wrgb[2][0] * R + Wrgb[2][1] * G + Wrgb[2][2] * B + 128) >> 8; - tmp_Y = tmp_Y + 16; - tmp_U = tmp_U + 128; - tmp_V = tmp_V + 128; - Y = CLIP(tmp_Y); - U = CLIP(tmp_U); - V = CLIP(tmp_V); - out_Y[y*MAX_WIDTH +x] = Y; - out_U[y*MAX_WIDTH +x] = U; - out_V[y*MAX_WIDTH +x] = V; - } // end of Lx loop - } // end of Ly loop -} - -/* ######################################################################### */ - -void img_hist_equaliz( uint11_t width, uint11_t height, uint25_t cdf[GRAY_LEVELS], - //RGB_t inp_img[MAX_HEIGHT * MAX_WIDTH], RGB_t out_img[MAX_HEIGHT * MAX_WIDTH]) - uint8_t inp_Y[MAX_WIDTH*MAX_HEIGHT], - uint8_t inp_U[MAX_WIDTH*MAX_HEIGHT], - uint8_t inp_V[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_Y[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_U[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_V[MAX_WIDTH*MAX_HEIGHT]) -{ - int i; - uint11_t x, y; - uint8_t Y, U, V; - - uint25_t loc_cdf[GRAY_LEVELS]; - //#pragma HLS BIND_STORAGE variable=loc_hist type=ram_t2p impl=bram - //#pragma HLS DEPENDENCE dependent=false direction=RAW type=intra variable=loc_hist - - L0: for (unsigned char i=0; i<(GRAY_LEVELS-1); i++) - { -#pragma HLS PIPELINE - loc_cdf[i] = cdf[i]; - } - - //float gain = (float) (GRAY_LEVELS-1) / ((float) (height * width -1)); - Ly: for (y=0; y= (GRAY_LEVELS-1)) cdf_int = (GRAY_LEVELS-1); - if (cdf_int <= 0 ) cdf_int = 0; - Y = (uint8_t) cdf_int; - out_Y[y*MAX_WIDTH +x] = Y; - out_U[y*MAX_WIDTH +x] = U; - out_V[y*MAX_WIDTH +x] = V; - - } // end of Lx loop - } // end of Ly loop - -} -/* ######################################################################### */ - -void top_histogram_equaliz( uint11_t width, uint11_t height, - uint25_t cdf[GRAY_LEVELS], -//RGB_t inp_img[MAX_HEIGHT * MAX_WIDTH], RGB_t out_img[MAX_HEIGHT * MAX_WIDTH]) - uint8_t inp_R[MAX_WIDTH*MAX_HEIGHT], - uint8_t inp_G[MAX_WIDTH*MAX_HEIGHT], - uint8_t inp_B[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_R[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_G[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_B[MAX_WIDTH*MAX_HEIGHT]) -{ -#pragma HLS INTERFACE mode=ap_fifo depth=IMG_DEPTH port=inp_G -#pragma HLS INTERFACE mode=ap_fifo depth=IMG_DEPTH port=inp_B -#pragma HLS INTERFACE mode=ap_fifo depth=IMG_DEPTH port=out_R -#pragma HLS INTERFACE mode=ap_fifo depth=IMG_DEPTH port=out_G -#pragma HLS INTERFACE mode=ap_fifo depth=IMG_DEPTH port=out_B -#pragma HLS INTERFACE mode=ap_fifo depth=CDF_DEPTH port=cdf - - -#ifdef __SYNTHESIS__ //HLS CSIM will ignore it! - //NOTE: in HW this is a big chunk of memory - //RGB_t yuv[MAX_WIDTH*MAX_HEIGHT]; - //RGB_t yeq[MAX_WIDTH*MAX_HEIGHT]; - uint8_t yuv_R[MAX_WIDTH*MAX_HEIGHT]; - uint8_t yuv_G[MAX_WIDTH*MAX_HEIGHT]; - uint8_t yuv_B[MAX_WIDTH*MAX_HEIGHT]; - uint8_t yeq_R[MAX_WIDTH*MAX_HEIGHT]; - uint8_t yeq_G[MAX_WIDTH*MAX_HEIGHT]; - uint8_t yeq_B[MAX_WIDTH*MAX_HEIGHT]; -#else - uint8_t *yuv_R = (uint8_t *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(uint8_t)); - uint8_t *yuv_G = (uint8_t *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(uint8_t)); - uint8_t *yuv_B = (uint8_t *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(uint8_t)); - uint8_t *yeq_R = (uint8_t *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(uint8_t)); - uint8_t *yeq_G = (uint8_t *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(uint8_t)); - uint8_t *yeq_B = (uint8_t *) malloc(MAX_HEIGHT * MAX_WIDTH * sizeof(uint8_t)); -#endif - // RGB to YUV conversion of current image I(n) - rgb2yuv(width, height, inp_R,inp_G,inp_B, yuv_R,yuv_G,yuv_B); - - // equalize the current image I(n) and compute its histogram for next image I(n+1) - img_hist_equaliz(width, height, cdf, yuv_R,yuv_G,yuv_B, yeq_R,yeq_G,yeq_B); - - // YUV to RGB conversion of current image I(n) - yuv2rgb(width, height, yeq_R,yeq_G,yeq_B, out_R,out_G,out_B); - -#ifndef __SYNTHESIS__ - free(yuv_R); free(yuv_G);free(yuv_B); - free(yeq_R); free(yeq_G); free(yeq_B); -#endif -} - - -/* ######################################################################### */ -void wrapper_histogram_equaliz( uint11_t width, uint11_t height, uint19_t hist[GRAY_LEVELS], - uint8_t inp_R[MAX_WIDTH*MAX_HEIGHT], - uint8_t inp_G[MAX_WIDTH*MAX_HEIGHT], - uint8_t inp_B[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_R[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_G[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_B[MAX_WIDTH*MAX_HEIGHT]) -// RGB_t inp_img[MAX_HEIGHT * MAX_WIDTH], RGB_t out_img[MAX_HEIGHT * MAX_WIDTH]) -{ - - uint25_t cdf[GRAY_LEVELS]; - - // compute the CDF of current image I(n) from the input histogram - compute_cdf(hist, cdf); - - //Histogram Equalization of current image I(n) - top_histogram_equaliz(width, height, cdf, inp_R,inp_G,inp_B, out_R,out_G,out_B); - - return; - -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/img_hist_v4.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/img_hist_v4.cpp deleted file mode 100644 index 2ae08eb434..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/img_hist_v4.cpp +++ /dev/null @@ -1,164 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#include -#include -#include - -#include "my_defines.h" -#include "histogram.h" - -const int IMG_DEPTH = MAX_WIDTH*MAX_HEIGHT; -const int CDF_DEPTH = GRAY_LEVELS; - -/* ######################################################################### */ - -// computes the Cumulative Density Function cdf[] from the Histrogram hist[] -void compute_cdf(uint19_t hist[GRAY_LEVELS], uint25_t cdf[GRAY_LEVELS]) -{ - uint8_t i, k; - - CDF_L1:for (k = 0; k < GRAY_LEVELS-1; k++) - { - uint25_t tmp_cdf=0; - CDF_L2:for (i = 0; i<=k; i++) - { - #pragma HLS LOOP_TRIPCOUNT min=1 max=256 avg=256 - // cdf for current picture from past picture histogram - tmp_cdf = tmp_cdf + hist[i]; - } - cdf[k] = tmp_cdf; - } - - return; - -} - - - -/* ######################################################################### */ - -void top_histogram_equaliz( uint11_t width, uint11_t height, - uint25_t cdf[GRAY_LEVELS], -//RGB_t inp_img[MAX_WIDTH*MAX_HEIGHT], RGB_t out_img[MAX_WIDTH*MAX_HEIGHT]) - uint8_t inp_R[MAX_WIDTH*MAX_HEIGHT], - uint8_t inp_G[MAX_WIDTH*MAX_HEIGHT], - uint8_t inp_B[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_R[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_G[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_B[MAX_WIDTH*MAX_HEIGHT]) -{ -#pragma HLS INTERFACE mode=ap_fifo depth=IMG_DEPTH port=inp_R -#pragma HLS INTERFACE mode=ap_fifo depth=IMG_DEPTH port=inp_G -#pragma HLS INTERFACE mode=ap_fifo depth=IMG_DEPTH port=inp_B -#pragma HLS INTERFACE mode=ap_fifo depth=IMG_DEPTH port=out_R -#pragma HLS INTERFACE mode=ap_fifo depth=IMG_DEPTH port=out_G -#pragma HLS INTERFACE mode=ap_fifo depth=IMG_DEPTH port=out_B -#pragma HLS INTERFACE mode=ap_fifo depth=CDF_DEPTH port=cdf - - int i; - uint11_t x, y; - uint8_t Y, U, V; - uint8_t cdf_temp; - uint25_t cdf_mult, gain; - uint32_t acc = 0; - uint8_t old, val; - //from rgb2yuv() - uint8_t R, G, B; - const int9_t Wrgb[3][3] = { - { 66, 129, 25}, - {-38, -74, 112}, - {122, -94, -18}, - }; - //from yuv2rgb() - int9_t C, D, E; - const int11_t Wyuv[3][3] = { - {298, 0, 409}, - {298, -100, -208}, - {298, 516, 0} - }; - - Ly:for (y=0; y> 8; - short int tmp_U = ( Wrgb[1][0] * R + Wrgb[1][1] * G + Wrgb[1][2] * B + 128) >> 8; - short int tmp_V = ( Wrgb[2][0] * R + Wrgb[2][1] * G + Wrgb[2][2] * B + 128) >> 8; - tmp_Y = tmp_Y + 16; - tmp_U = tmp_U + 128; - tmp_V = tmp_V + 128; - Y = CLIP(tmp_Y); - U = CLIP(tmp_U); - V = CLIP(tmp_V); - - // histogram equalization - int numer = ( (cdf[Y]-1) *(GRAY_LEVELS-1)); - int denomin = (height * width -1); - cdf_mult = numer / denomin; - // clipping (due to the approssimation done above) - if (cdf_mult >= (GRAY_LEVELS-1)) - cdf_temp = (GRAY_LEVELS-1); - else if (cdf_mult <= 0 ) - cdf_temp = 0; - - cdf_temp = (uint8_t) cdf_mult; - Y = cdf_temp; - - // YUV to RGB conversion of current image I(n) - C = Y - 16; - D = U - 128; - E = V - 128; - short int tmp_R = (Wyuv[0][0] * C + Wyuv[0][2] * E + 128); - short int tmp_G = (Wyuv[1][0] * C + Wyuv[1][1] * D + Wyuv[1][2] * E + 128); - short int tmp_B = (Wyuv[2][0] * C + Wyuv[2][1] * D + 128); - tmp_B = tmp_B >> 8; - tmp_G = tmp_G >> 8; - tmp_R = tmp_R >> 8; - R = CLIP( tmp_R ); - G = CLIP( tmp_G ); - B = CLIP( tmp_B ); - out_R[y*MAX_WIDTH +x] = R; - out_G[y*MAX_WIDTH +x] = G; - out_B[y*MAX_WIDTH +x] = B; - - } // end of Lx loop - } // end of Ly loop - -} - - -/* ######################################################################### */ - -void wrapper_histogram_equaliz( uint11_t width, uint11_t height, - uint19_t hist[GRAY_LEVELS], - uint8_t inp_R[MAX_WIDTH*MAX_HEIGHT], - uint8_t inp_G[MAX_WIDTH*MAX_HEIGHT], - uint8_t inp_B[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_R[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_G[MAX_WIDTH*MAX_HEIGHT], - uint8_t out_B[MAX_WIDTH*MAX_HEIGHT]) -//RGB_t inp_img[MAX_WIDTH*MAX_HEIGHT], RGB_t out_img[MAX_WIDTH*MAX_HEIGHT]) -{ - - uint25_t cdf[GRAY_LEVELS]; - - // compute the CDF of current image I(n) from histogram of previous image I(n-1) - compute_cdf(hist, cdf); - - //Histogram Equalization of current image I(n) - top_histogram_equaliz(width, height, cdf, inp_R,inp_G,inp_B, out_R,out_G,out_B); - - return; - -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/median.h b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/median.h deleted file mode 100644 index 036a7a8f9a..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/median.h +++ /dev/null @@ -1,126 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - - - -#ifndef _H_MEDIAN_H_ -#define _H_MEDIAN_H_ - - -//#include "ap_axi_sdata.h" -//#include "ap_interfaces.h" -//#include "ap_bmp.h" - -/* ******************************************************************************* */ -// CONSTANT PARAMETERS - -#define MAX_PATH 1000 - -#define MAX_HEIGHT 1080 -#define MAX_WIDTH 1920 - -//#define KMED3 - -#if defined(KMED3) -#define KMED 3 -#elif defined(KMED5) -#define KMED 5 -#elif defined(KMED7) -#define KMED 7 -#else -#error -#endif - -#define KKMED (KMED/2) -#define BLOCKSIZE KMED - - -/* ******************************************************************************* */ -// I/O Image Settings -#define INPUT_IMAGE_BASE "./test_data/noisy_rgb2y_1080p" - -#if (KMED==7) -//#error < KMED IS 7> -#define OUTPUT_IMAGE_BASE "./test_data/c_out_median7x7_1080p" -#elif (KMED==5) -//#error < KMED IS 5> -#define OUTPUT_IMAGE_BASE "./test_data/c_out_median5x5_1080p" -#elif (KMED==3) -//#error < KMED IS 3> -#define OUTPUT_IMAGE_BASE "./test_data/c_out_median3x3_1080p" -#endif - -//#define REFER_IMAGE_BASE "./test_data/golden_out_median_1080p" -//#define REFER_VAR_BASE "./test_data/golden_out_variance_1080p" -//#define OUTPUT_VAR_BASE "./test_data/c_out_variance_1080p" -//#define C_REFER_IMAGE_BASE "./test_data/c_golden_out_median_1080p" - -/* ******************************************************************************* */ -// SMALL FUNCTIONS IN MACRO -#define ABSDIFF(x,y) ( (x)>(y) ? (x - y) : (y - x) ) -#define ABS(x) ( (x)> 0 ? (x) : -(x) ) -#define MIN(x,y) ( (x)>(y) ? (y) : (x) ) -#define MAX(x,y) ( (x)>(y) ? (x) : (y) ) - - - - -/* ******************************************************************************* */ -// DATA TYPES - -//#define DB_FIXED_POINT - -#ifndef DB_FIXED_POINT -typedef unsigned char pix_t; -#else -#include -typedef ap_uint<11> pix_t; -#endif - -//#define FLOAT_VAR -#ifndef FLOAT_VAR -typedef int var_t; -#else -typedef float var_t; -#endif - -typedef struct ap_rgb{ - unsigned char B; - unsigned char G; - unsigned char R; - } RGB_t; - -typedef signed short int int16_t; -typedef unsigned short int uint16_t; - -//typedef ap_axiu<32,1,1,1> AXI_PIXEL; -//typedef pix_t AXI_PIXEL; - - -/* ******************************************************************************* */ -// FUNCTION PROTOTYPES - -int main_median(void); - -pix_t median(pix_t window[KMED*KMED]); - -void top_median( pix_t in_pix[MAX_HEIGHT][MAX_WIDTH], - pix_t out_pix[MAX_HEIGHT][MAX_WIDTH], - short height, short width); //, FILE *fp); - - -void ref_median(pix_t in_pix[MAX_HEIGHT][MAX_WIDTH], - pix_t ref_pix[MAX_HEIGHT][MAX_WIDTH], - short height, short width); //, FILE *fp); - -////extern void sw_naive_median( pix_t in_pix[MAX_HEIGHT * MAX_WIDTH], pix_t out_pix[MAX_HEIGHT * MAX_WIDTH], short height, short width); //, FILE *fp); -//extern void hw_naive_median( pix_t in_pix[MAX_HEIGHT * MAX_WIDTH], pix_t out_pix[MAX_HEIGHT * MAX_WIDTH], short int height, short int width); //, FILE *fp); -// -////void sw_linebuf_median(pix_t in_pix[MAX_HEIGHT * MAX_WIDTH], pix_t ref_pix[MAX_HEIGHT * MAX_WIDTH], short height, short width); //, FILE *fp); -//extern void hw_linebuf_median(pix_t in_pix[MAX_HEIGHT * MAX_WIDTH], pix_t ref_pix[MAX_HEIGHT * MAX_WIDTH], short int height, short int width); //, FILE *fp); - - - -#endif diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/run_src3_hls_script.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/run_src3_hls_script.tcl deleted file mode 100644 index d8725d12fe..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/run_src3_hls_script.tcl +++ /dev/null @@ -1,72 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -# Author: Daniele Bagni, Xilinx Inc - -puts "\n" -puts "************************************************************************" -puts "* EXAMPLE 5) IMAGE HISTOGRAM EQUALIZATION DEMO" -puts "************************************************************************" -puts "\n" - -open_project vhls_hist_src3_prj -set_top top_histogram_equaliz -add_files img_hist_v3.cpp -cflags "-I./common" -add_files -tb common/ap_bmp.cpp -cflags "-I./common -Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -add_files -tb common/main_test.cpp -cflags "-I./common -Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -add_files -tb common/ref_img_hist.cpp -cflags "-I./common -Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -add_files -tb common/test_data -cflags "-Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" - - -################## SOLUTION1: Baseline #################### -open_solution "solution1" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 3 -name default -config_export -rtl vhdl -set_clock_uncertainty 0.5 -set_directive_top -name top_histogram_equaliz "top_histogram_equaliz" -csim_design -clean -csynth_design - -################## SOLUTION2: DATAFLOW #################### -open_solution "solution2" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 3 -name default -config_export -rtl vhdl -set_clock_uncertainty 0.5 -set_directive_top -name top_histogram_equaliz "top_histogram_equaliz" -set_directive_dataflow "top_histogram_equaliz" -csynth_design - -################## SOLUTION3: DATAFLOW + CONFIG_DATAFLOW #################### -open_solution "solution3" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 3 -name default -config_export -rtl vhdl -set_clock_uncertainty 0.5 -config_dataflow -default_channel fifo -set_directive_top -name top_histogram_equaliz "top_histogram_equaliz" -set_directive_dataflow "top_histogram_equaliz" -csynth_design - -################## SOLUTION4: as Solution3 + PIPELINE all the innermost loops #################### -open_solution "solution4" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 3 -name default -config_export -rtl vhdl -set_clock_uncertainty 0.5 -config_dataflow -default_channel fifo -set_directive_top -name top_histogram_equaliz "top_histogram_equaliz" -set_directive_dataflow "top_histogram_equaliz" -set_directive_stream -depth 2 -type fifo "top_histogram_equaliz" yuv_R -set_directive_stream -depth 2 -type fifo "top_histogram_equaliz" yuv_G -set_directive_stream -depth 2 -type fifo "top_histogram_equaliz" yuv_B -set_directive_stream -depth 2 -type fifo "top_histogram_equaliz" yeq_R -set_directive_stream -depth 2 -type fifo "top_histogram_equaliz" yeq_G -set_directive_stream -depth 2 -type fifo "top_histogram_equaliz" yeq_B -#set_directive_array_partition -dim 0 -type complete "yuv2rgb" Wyuv -#set_directive_array_partition -dim 0 -type complete "rgb2yuv" Wrgb -csynth_design - -close_project diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/run_src4_hls_script.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/run_src4_hls_script.tcl deleted file mode 100644 index 98a1ccb480..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/5_img_histEq/run_src4_hls_script.tcl +++ /dev/null @@ -1,19 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -open_project vhls_hist_src4_prj -set_top top_histogram_equaliz -add_files img_hist_v4.cpp -cflags "-I./common" -add_files -tb common/ap_bmp.cpp -cflags "-Icommon -Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -add_files -tb common/main_test.cpp -cflags "-Icommon -Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -add_files -tb common/ref_img_hist.cpp -cflags "-Icommon -Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -add_files -tb common/test_data -cflags "-Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -open_solution "solution1" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 3 -name default -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 0.5 -set_directive_top -name top_histogram_equaliz "top_histogram_equaliz" -csim_design -clean -csynth_design diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/Makefile b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/Makefile deleted file mode 100644 index 6b48aa876e..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/Makefile +++ /dev/null @@ -1,14 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -.PHONY: help kernels clean all - -clean: - rm -rf *_prj *.log *~ ./logs - -kernels: - vitis-run --mode hls --tcl ./run_sqrt_script.tcl - - -all: kernels diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/cordic_atan_11bits.h b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/cordic_atan_11bits.h deleted file mode 100644 index e22b6ae5be..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/cordic_atan_11bits.h +++ /dev/null @@ -1,16 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - - 804, - 475, - 251, - 127, - 64, - 32, - 16, - 8, - 4, - 2, - 1, diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/cordic_defines.h b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/cordic_defines.h deleted file mode 100644 index 07ac784205..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/cordic_defines.h +++ /dev/null @@ -1,103 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#ifndef H_CORDIC_DEFINES_H -#define H_CORDIC_DEFINES_H - -/********************************************************************************/ -// COMPILATION FLAGS: you can select only one of them alternatively - -// to enable TOTALLY floating point sqrt reference function for SOLUTION 0 -//#define SQRT_DOUBLE - -// to enable TOTALLY floating point sqrt reference function for SOLUTION 1 -//#define SQRT_REF - -// to enable floating point sqrt function while the rest is integer for SOLUTION 2 -//#define SQRT_FLOAT - -//to enable full version of Cordic sqrt function for SOLUTIONS 3 and 4 -//#define SQRT_CORDIC // ONLY FOR SOLUTION 3 -//#define SQRT_AP_INT // FOR SOLUTION 4 - -/********************************************************************************/ -// CONSTANTS - -#define NC 1024/4 - -#define THRESHOLD 3.0 - - -/********************************************************************************/ -// MACROS -#define ABS(X) ( (X) > 0 ? (X) : -(X) ) - - -/********************************************************************************/ -// DATA TYPES - -#include "ap_int.h" -#include "ap_fixed.h" - -#ifndef SQRT_AP_INT -typedef signed short int teta_t; -typedef signed long int dinp_t; -typedef signed long int dout_t; -#else -typedef ap_int<10> teta_t; -typedef ap_int<18> dinp_t; -typedef ap_int<24> dout_t; -#endif - -/********************************************************************************/ -// EXTERN FUNCTION PROTOTYPES -dout_t process_magnitude_float(dinp_t real_data, dinp_t imag_data); -dout_t process_magnitude_int(dinp_t real_data, dinp_t imag_data); -dout_t process_magnitude_cordic(dinp_t real_data, dinp_t imag_data); -float process_magnitude_ref(float real_data, float imag_data); -double process_magnitude_double(double real_data, double imag_data); - -void top_process_magnitude(dinp_t real_data[NC], dinp_t imag_data[NC], dout_t magn_data[NC]); -unsigned short int cordic_isqrt (unsigned long int x); -signed long int cordic_sqrt(signed long int x0, signed long int y0); - - - - - - -/********************************************************************************/ -//// CHECK COMPILATION PARAMETERS -// -//#if defined(SQRT_DOUBLE) -//#undef SQRT_FLOAT -//#undef SQRT_INT -//#undef SQRT_CORDIC -//#undef SQRT_REF -//#elif defined(SQRT_REF) -//#undef SQRT_FLOAT -//#undef SQRT_INT -//#undef SQRT_CORDIC -//#undef SQRT_DOUBLE -//#elif defined(SQRT_FLOAT) -//#undef SQRT_REF -//#undef SQRT_INT -//#undef SQRT_CORDIC -//#undef SQRT_DOUBLE -//#elif defined(SQRT_INT) -//#undef SQRT_REF -//#undef SQRT_FLOAT -//#undef SQRT_CORDIC -//#undef SQRT_DOUBLE -//#elif defined(SQRT_CORDIC) -//#undef SQRT_REF -//#undef SQRT_FLOAT -//#undef SQRT_INT -//#undef SQRT_DOUBLE -//#else -//#error < NO METHOD SELECTED !> -//#endif - -#endif //H_CORDIC_DEFINES_H diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/cordic_isqrt.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/cordic_isqrt.cpp deleted file mode 100644 index 1a3b52cf66..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/cordic_isqrt.cpp +++ /dev/null @@ -1,59 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#include "cordic_defines.h" - - - -#define ITER 16 - - -#ifdef SQRT_INT - -unsigned short int cordic_isqrt (unsigned long int x) -{ - -#pragma HLS INLINE - unsigned char i; - unsigned short int y; - unsigned long int m; - unsigned short int base = (1<<(ITER-1))&0xFFFF; - - y = 0 ; - L0: for (i = 1; i <= ITER; i++) - { -#pragma HLS PIPELINE - y += base ; - m = (unsigned long int) y * (unsigned long int) y; - if (m > x ) - { - y -= base ; // base should not have been added, so we substract again - } - base = base >> 1 ; // shift 1 digit to the right = divide by 2 - } - return y ; -} - - - -dout_t process_magnitude_int(dinp_t real_data, dinp_t imag_data) -{ -#pragma HLS INLINE OFF - typedef signed long int acc_t; - dinp_t mag_data; - acc_t accu_plus, temp_datar, temp_datai; - - acc_t temp_long; - - temp_datar = (acc_t)real_data*(acc_t)real_data; - temp_datai = (acc_t)imag_data*(acc_t)imag_data; - accu_plus = temp_datar + temp_datai; - - mag_data = cordic_isqrt((unsigned long int) accu_plus); - - return mag_data; -} - -#endif diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/cordic_sqrt.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/cordic_sqrt.cpp deleted file mode 100644 index b9433dd1d8..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/cordic_sqrt.cpp +++ /dev/null @@ -1,105 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#include "cordic_defines.h" -/* - - mode 1: rotation; Rotates (x0,y0) by z0 - (xn,yn)=(cos(z0),sin(z0)) for (x0,y0)=(1,0) - x[i+1] = x[i] - y[i] * d[i] * 2^(-1) - y[i+1] = y[i] + x[i] * d[i] * 2^(-i) - z[i+1] = z[i] - d[i] * atan(2^(-i)) - - d[i] = +1 if y[i]<0 else -1 - - xn = An*sqrt(x[0]^2+y[0]^2) - yn = 0; - zn = z[0] + atan(x[0]/y[0]) - ___ - An = | | sqrt(1+2^(-2*i)) - n - - Gain (An) = 1.64676; n = 10 (0 to 10) - - mode 0: vectoring; Rotates (x0,y0) to X-axis - (xn,zn)=(r,theta) - - -PI/2 original - - EG extended to - 0 to 2PI -*/ - - -#ifdef SQRT_CORDIC -#define ROT 11 - - -template -ap_fixed cordic_sqrt(dinp_t x0, dinp_t y0) -{ - - // atan_lut = round( 2^10 * atan(2.^(-k))) - // with k = 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 - static const signed short int atan_lut[ROT] = { 804, 475, 251, 127, 64, 32, 16, 8, 4, 2, 1 }; - signed short int z, zp; - unsigned char i; - - - ap_fixed x, y, xp, yp, x2; - - // to compensate the cordic gain of G = 1.0/0.6072 - const ap_fixed<16,1, AP_RND_MIN_INF, AP_SAT> inv_G = 0.607253031529134; // that is 0.6072 == 453 / 746; - - - xp=x0; - yp=y0; - zp=0; - -for (i=0;i>i); - y = yp + (xp>>i); - z = zp - atan_lut[i]; - } else { - x = xp + (yp>>i); - y = yp - (xp>>i); - z = zp + atan_lut[i]; - } - xp=x; - yp=y; - zp=z; - } - -// compensating the cordic gain -//#pragma HLS RESOURCE variable=x2 core=MUL6S -#pragma HLS BIND_OP variable=x2 op=mul impl=dsp - - x2 = xp * inv_G; //xn = ((x * 453) / 746) ; - -//x = (xp *311)>>9; // much less accurate - - - return x2; - -} - - -dout_t process_magnitude_cordic(dinp_t real_data, dinp_t imag_data) -{ -#pragma HLS INLINE OFF - -#ifndef SQRT_AP_INT -dout_t mag_data = (dout_t) cordic_sqrt<40,32>( real_data, imag_data ); // for CORDIC SOLUTION 3 WHEN SQRT_AP_INT IS NOT DEFINED -#else -dout_t mag_data = (dout_t) cordic_sqrt<24,18>( real_data, imag_data ); // for CORDIC SOLUTION 4 WHEN SQRT_AP_INT IS DEFINED -#endif - -return mag_data; -} - -#endif //SQRT_CORDIC diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/float_sqrt.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/float_sqrt.cpp deleted file mode 100644 index 2e4c5b140d..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/float_sqrt.cpp +++ /dev/null @@ -1,71 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#include -#include -#include "cordic_defines.h" - - - -#ifdef SQRT_FLOAT - -typedef long long int acc_t; - -dout_t process_magnitude_float(dinp_t real_data, dinp_t imag_data) -{ -#pragma HLS INLINE OFF -#pragma HLS PIPELINE - - dinp_t mag_data; - acc_t accu_plus, temp_datar, temp_datai; - - temp_datar = (acc_t)real_data * (acc_t)real_data; - - - temp_datai = (acc_t)imag_data * (acc_t)imag_data; - - accu_plus = temp_datar + temp_datai; - - mag_data = (dout_t) floor(sqrtf( (float)accu_plus )); - - return mag_data; -} -#endif // SQRT_FLOAT - - -#ifdef SQRT_DOUBLE -double process_magnitude_double(double real_data, double imag_data) -{ -#pragma HLS INLINE OFF -#pragma HLS PIPELINE - - double mag_data, accu_plus, temp_datar, temp_datai; - - temp_datar = real_data * real_data; - temp_datai = imag_data * imag_data; - accu_plus = temp_datar + temp_datai; - - mag_data = sqrt(accu_plus); - - return mag_data; -} -#endif //SQRT_DOUBLE - - -float process_magnitude_ref(float real_data, float imag_data) -{ -#pragma HLS INLINE OFF -#pragma HLS PIPELINE - - float mag_data, accu_plus, temp_datar, temp_datai; - - temp_datar = real_data * real_data; - temp_datai = imag_data * imag_data; - accu_plus = temp_datar + temp_datai; - - mag_data = sqrtf(accu_plus); - - return mag_data; -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/run_sqrt_script.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/run_sqrt_script.tcl deleted file mode 100644 index 6957b01af8..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/run_sqrt_script.tcl +++ /dev/null @@ -1,178 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -# Author: Daniele Bagni, Xilinx Inc - -puts "\n" -puts "************************************************************************" -puts "* EXAMPLE 6) ABOUT Z = SQRT( X^2 + Y^2)" -puts "************************************************************************" -puts "\n" - - -# to enable TOTALLY floating point sqrt reference function for SOLUTION 0 -open_project hls_isqrt_prj -set_top top_process_magnitude -add_files top_magnitude.cpp -cflags "-DSQRT_DOUBLE" -add_files float_sqrt.cpp -cflags "-DSQRT_DOUBLE" -add_files cordic_sqrt.cpp -cflags "-DSQRT_DOUBLE" -add_files cordic_isqrt.cpp -cflags "-DSQRT_DOUBLE" -add_files -tb test_main.cpp -cflags "-DSQRT_DOUBLE" -open_solution "solution0" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 3.0 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 0.5 -set_directive_inline -off "func2_process_magnitude" -set_directive_inline -off "func1_process_magnitude" -set_directive_inline -off "func3_process_magnitude" -set_directive_inline -off "func4_process_magnitude" -set_directive_pipeline "func1_process_magnitude/L1" -set_directive_pipeline "func2_process_magnitude/L2" -set_directive_pipeline "func3_process_magnitude/L3" -set_directive_pipeline "func4_process_magnitude/L4" -#csim_design -ldflags {{-Wl,--stack=268435456}} -clean #ONLY FOR WINDOWS -csim_design -clean -csynth_design -#cosim_design -#cosim_design -ldflags {{-Wl,--stack=268435456}} -rtl systemc #ONLY FOR WINDOWS -close_project - -if 1 { -# to enable TOTALLY floating point sqrt reference function for SOLUTION 1 -open_project hls_isqrt_prj -set_top top_process_magnitude -add_files top_magnitude.cpp -cflags "-DSQRT_REF" -add_files float_sqrt.cpp -cflags "-DSQRT_REF" -add_files cordic_sqrt.cpp -cflags "-DSQRT_REF" -add_files cordic_isqrt.cpp -cflags "-DSQRT_REF" -add_files -tb test_main.cpp -cflags "-DSQRT_REF" -open_solution "solution1" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 3.0 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 0.5 -set_directive_inline -off "func2_process_magnitude" -set_directive_inline -off "func1_process_magnitude" -set_directive_inline -off "func3_process_magnitude" -set_directive_inline -off "func4_process_magnitude" -set_directive_pipeline "func1_process_magnitude/L1" -set_directive_pipeline "func2_process_magnitude/L2" -set_directive_pipeline "func3_process_magnitude/L3" -set_directive_pipeline "func4_process_magnitude/L4" -#csim_design -ldflags {{-Wl,--stack=268435456}} -clean -csim_design -clean -csynth_design -#cosim_design -#cosim_design -ldflags {{-Wl,--stack=268435456}} -rtl systemc -close_project - -# to enable floating point sqrt function while the rest is integer for SOLUTION 2 -open_project hls_isqrt_prj -set_top top_process_magnitude -add_files top_magnitude.cpp -cflags "-DSQRT_FLOAT" -add_files float_sqrt.cpp -cflags "-DSQRT_FLOAT" -add_files cordic_sqrt.cpp -cflags "-DSQRT_FLOAT" -add_files cordic_isqrt.cpp -cflags "-DSQRT_FLOAT" -add_files -tb test_main.cpp -cflags "-DSQRT_FLOAT" -open_solution "solution2" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 3.0 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 0.5 -set_directive_inline -off "func2_process_magnitude" -set_directive_inline -off "func1_process_magnitude" -set_directive_inline -off "func3_process_magnitude" -set_directive_inline -off "func4_process_magnitude" -set_directive_pipeline "func1_process_magnitude/L1" -set_directive_pipeline "func2_process_magnitude/L2" -set_directive_pipeline "func3_process_magnitude/L3" -set_directive_pipeline "func4_process_magnitude/L4" -csim_design -clean -#csim_design -ldflags {{-Wl,--stack=268435456}} -clean -csynth_design -#cosim_design -#cosim_design -ldflags {{-Wl,--stack=268435456}} -rtl systemc -close_project - -# to enable full version of Cordic sqrt function for SOLUTION3 -open_project hls_isqrt_prj -set_top top_process_magnitude -add_files top_magnitude.cpp -cflags "-DSQRT_CORDIC" -add_files float_sqrt.cpp -cflags "-DSQRT_CORDIC" -add_files cordic_sqrt.cpp -cflags "-DSQRT_CORDIC" -add_files cordic_isqrt.cpp -cflags "-DSQRT_CORDIC" -add_files -tb test_main.cpp -cflags "-DSQRT_CORDIC" -open_solution "solution3" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 3.0 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 0.5 -set_directive_inline -off "func2_process_magnitude" -set_directive_inline -off "func1_process_magnitude" -set_directive_inline -off "func3_process_magnitude" -set_directive_inline -off "func4_process_magnitude" -set_directive_pipeline "func1_process_magnitude/L1" -set_directive_pipeline "func2_process_magnitude/L2" -set_directive_pipeline "func3_process_magnitude/L3" -set_directive_pipeline "func4_process_magnitude/L4" -csim_design -clean -#csim_design -ldflags {{-Wl,--stack=268435456}} -clean -csynth_design -#cosim_design -#cosim_design -ldflags {{-Wl,--stack=268435456}} -rtl systemc -close_project - -# to enable arbitrary precision datatypes of Cordic sqrt function for SOLUTION4 -open_project hls_isqrt_prj -set_top top_process_magnitude -add_files top_magnitude.cpp -cflags "-DSQRT_CORDIC -DSQRT_AP_INT" -add_files float_sqrt.cpp -cflags "-DSQRT_CORDIC -DSQRT_AP_INT" -add_files cordic_sqrt.cpp -cflags "-DSQRT_CORDIC -DSQRT_AP_INT" -add_files cordic_isqrt.cpp -cflags "-DSQRT_CORDIC -DSQRT_AP_INT" -add_files -tb test_main.cpp -cflags "-DSQRT_CORDIC -DSQRT_AP_INT" -open_solution "solution4" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 3.0 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 0.5 -set_directive_inline -off "func2_process_magnitude" -set_directive_inline -off "func1_process_magnitude" -set_directive_inline -off "func3_process_magnitude" -set_directive_inline -off "func4_process_magnitude" -set_directive_pipeline "func1_process_magnitude/L1" -set_directive_pipeline "func2_process_magnitude/L2" -set_directive_pipeline "func3_process_magnitude/L3" -set_directive_pipeline "func4_process_magnitude/L4" -csim_design -clean -#csim_design -ldflags {{-Wl,--stack=268435456}} -clean -csynth_design -#cosim_design -#cosim_design -ldflags {{-Wl,--stack=268435456}} -rtl systemc -close_project -} - - - - -# empty solution just to remove CFLAGS from the GUI" -open_project hls_isqrt_prj -set_top top_process_magnitude -add_files top_magnitude.cpp -add_files float_sqrt.cpp -add_files cordic_sqrt.cpp -add_files cordic_isqrt.cpp -add_files -tb test_main.cpp -open_solution "solution_empty" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 3.0 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 0.5 -close_project diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/test_main.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/test_main.cpp deleted file mode 100644 index c470f82a04..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/test_main.cpp +++ /dev/null @@ -1,109 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#include -#include -#include -#include "cordic_defines.h" - -#define AMP 32768 - - -int main(void) -{ - - int ret_val = 0; - float rel_err; - unsigned long int i, j; - int max_err, tot_err; - - dinp_t x, y; - - dinp_t *real, *imag; - dout_t *magn, *ref; - - int d; - - FILE *fil1 = fopen("cordic_isqrt.txt", "wt"); - if(!fil1) - printf("ERROR: could not open output file1\n"); - - // MEMORY ALLOCATION - real = (dinp_t *)malloc(NC * sizeof(dinp_t)); - imag = (dinp_t *)malloc(NC * sizeof(dinp_t)); - magn = (dout_t *)malloc(NC * sizeof(dout_t)); - ref = (dout_t *)malloc(NC * sizeof(dout_t)); - - if (!ref || !magn || !real || !imag) { - if (ref ) free(ref); - if (magn) free(magn); - if (real) free(real); - if (imag) free(imag); - } - // PREPARE INPUT STIMULA - printf("\npreparing input stimula\n"); - - for (i=0; i AMP) x = AMP; // clipping - if (y > AMP) y = AMP; // clipping - real[i] = x; - imag[i] = y; - ref[i] = process_magnitude_ref(real[i],imag[i]); // reference magnitude result - } - - - // CALL DESIGN UNDER TEST - printf("running Design Under Test\n"); - top_process_magnitude(real, imag, magn); - - // CHECK RESULTS - printf("check results\n"); - tot_err = 0; - max_err = 0; - for (j=0; j= max_err) - { - max_err = d; - i = j; // store the address of max error - } - fprintf(fil1, "%10d %10d %10d %10d %10d %10d\n", j, (int) real[j], (int) imag[j], (int) magn[j], (int) ref[j], d); - } - - // SIMULATION RESULT - if (max_err > THRESHOLD) - { - ret_val = 1; - printf("Test failed !\n\n"); - } - else - { - ret_val = 0; - printf("Test successful!\n\n"); - } - - - fclose(fil1); - rel_err = ((float) tot_err)/NC; // relative error - printf("RELATIVE ERROR = %6.4f\n",rel_err); - if (max_err > 0) - printf("MAX ERROR = %d in sqrt(%6d^2 + %6d^2): EXPECTED=%6d, EFFECTIVE=%6d\n", max_err, (int) real[i], (int) imag[i], (int) ref[i], (int) magn[i]); - - free(ref); - free(magn); - free(real); - free(imag); - - - - return ret_val; - -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/top_magnitude.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/top_magnitude.cpp deleted file mode 100644 index 914d1a7be8..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/6_sqrt/top_magnitude.cpp +++ /dev/null @@ -1,132 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#include -#include -#include "cordic_defines.h" - - - -void func1_process_magnitude(dinp_t real_data[NC], dinp_t imag_data[NC], dout_t magn_data[NC]) -{ - - unsigned short int i; - - L1:for (i=0; i -#endif - - func1_process_magnitude( real_data, imag_data, magn_data); - func2_process_magnitude( real_data, imag_data, magn_data); - func3_process_magnitude( real_data, imag_data, magn_data); - func4_process_magnitude( real_data, imag_data, magn_data); - -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/M/cpf_atan2.zip b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/M/cpf_atan2.zip deleted file mode 100644 index 9dd5f2de25..0000000000 Binary files a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/M/cpf_atan2.zip and /dev/null differ diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/M/db_cordic_atan2.m b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/M/db_cordic_atan2.m deleted file mode 100644 index a75507b03e..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/M/db_cordic_atan2.m +++ /dev/null @@ -1,74 +0,0 @@ -% Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -% SPDX-License-Identifier: MIT - -%function [xn, yn, zn] = db_cordic (mode, x0, y0, z0, N) -function [zn] = db_cordic (mode, x0, y0, z0, N) - - %coord_t x, y, xp, yp; - %phase_t z, zp; - %bool xneg, yneg, dneg; - %uint6_t i; - - %static const phase_t atan_2Mi[] = { #include "cordic_atan.h" }; - - I = [0 : N]; - - atan_2Mi = [atan(2.^(-I))]; - - quadrant = 0; - if ((x0>0) & (y0>0)) - quadrant = 1; - elseif ((x0<0) & (y0>0)) - quadrant = 2; - elseif ((x0<0) & (y0<0)) - quadrant = 3; - elseif ((x0>0) & (y0<0)) - quadrant = 4; - end - - x=abs(x0); - y=abs(y0); - z=z0; - - for i=0 : N - - if (mode==1) - dneg = (z<0); - else - dneg = (y>0); - end - - if (dneg) - xp = x + ( y/ 2^i); - yp = y - ( x / 2^i); - zp = z + atan_2Mi(i+1); - else - xp = x - ( y / 2^i); - yp = y + ( x / 2^i); - zp = z - atan_2Mi(i+1); - end - x = xp; - y = yp; - z = zp; - end - - if (quadrant==1) - xn=x; - yn=y; - zn=z; - elseif (quadrant==2) - xn=x; - yn=-y; - zn=pi-z; - elseif (quadrant==3) - xn=-x; - yn=-y; - zn=-(pi-z); - elseif (quadrant==4) - xn=-x; - yn=-y; - zn=-z; - end - - -end diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/M/short_cpf_atan2.m b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/M/short_cpf_atan2.m deleted file mode 100644 index ac8465dbc0..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/M/short_cpf_atan2.m +++ /dev/null @@ -1,53 +0,0 @@ -% Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -% SPDX-License-Identifier: MIT - -clear all -close all -clc -%% -cpf_atan2_res = load('cpf_atan2_data.txt'); -m_atan2 = atan2(cpf_atan2_res(:, 1),cpf_atan2_res(:, 2)); - -%% -diff_atan2 = abs(m_atan2 - cpf_atan2_res(:, 3)); -figure; plot(diff_atan2); -max(diff_atan2) -min(diff_atan2) -sum_abs_diff = sum(diff_atan2) - -% %% write file input_data.h -% N = size(cpf_atan2_res, 1); -% fprintf(fid, 'int input_data[2][%d]={ \n',N); -% for i = 1 : N-1 -% fprintf(fid, '{%10d, %10d},\n', cpf_atan2_res(i, 1), cpf_atan2_res(i,2)); -% end -% fprintf(fid, '{%10d, %10d}\n', cpf_atan2_res(i, 1), cpf_atan2_res(i,2)); -% fprintf(fid, '};\n'); -% fclose(fid); - -%% write file input_data.txt - -N = size(cpf_atan2_res, 1); -fid = fopen('input_data.txt','w'); -for i = 1 : N - fprintf(fid, '%10d %10d\n', cpf_atan2_res(i, 1), cpf_atan2_res(i,2)); -end -fclose(fid); - -% %% write file ref_results.h -% fid2 = fopen('ref_results.h','w'); -% fprintf(fid2, 'float ref_results[%d]={ \n',N); -% for i = 1 : N-1 -% fprintf(fid2, '%20.10f, ', cpf_atan2_res(i,3)); -% end -% fprintf(fid2, '%20.10f', cpf_atan2_res(i,3)); -% fprintf(fid2, ' };\n'); -% fclose(fid2); - -%% write file ref_results.txt -fid2 = fopen('ref_results.txt','w'); -%fprintf(fid2, 'float ref_results[%d]={ \n',N); -for i = 1 : N - fprintf(fid2, '%20.10f\n', cpf_atan2_res(i,3)); -end -fclose(fid2); diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/Makefile b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/Makefile deleted file mode 100644 index 8bd8b6f873..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/Makefile +++ /dev/null @@ -1,14 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -.PHONY: help kernels clean all - -clean: - rm -rf *_prj *.log *~ ./logs - -kernels: - vitis-run --mode hls --tcl ./run_atan2_script.tcl - - -all: kernels diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/cordic.h b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/cordic.h deleted file mode 100644 index 6382357039..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/cordic.h +++ /dev/null @@ -1,62 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - - -#ifndef CORDIC_H_ -#define CORDIC_H_ - -// LEGENDA: 4 possible implementations: -// 1) -// #define DB_DOUBLE_PRECISION //DB: solution1_double -// -// 2) -// #define DB_SINGLE_PRECISION //DB: solution1_float -// -// 3) -// #define DB_CORDIC //DB: solution1_cordic -// -// 4) -// #define DB_CORDIC //DB: solution2_cordic_bitaccurate -// #define BIT_ACCURATE - - - -#if defined(DB_DOUBLE_PRECISION) - -typedef double coord_t; -typedef double phase_t; -typedef unsigned char uint6_t; - -#elif defined(DB_SINGLE_PRECISION) - -typedef float coord_t; -typedef float phase_t; -typedef unsigned char uint6_t; - -#elif defined(DB_CORDIC) - -#include -#include - -typedef ap_fixed<18,9> coord_t; -typedef ap_fixed<16,4> phase_t; -typedef ap_uint<6> uint6_t; - -#else - -#error - -#endif - -#include - - -#define ROT 8 -#define SCALE 10 - - -void top_atan2 (coord_t y0, coord_t x0, phase_t *zn); - -#endif diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/cordic_atan2.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/cordic_atan2.cpp deleted file mode 100644 index df25851ddf..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/cordic_atan2.cpp +++ /dev/null @@ -1,139 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#include "cordic.h" -/* - Gain=1.647; - mode 1: rotation; Rotates (x0,y0) by z0 - (xn,yn)=(cos(z0),sin(z0)) for (x0,y0)=(1,0) - x[i+1] = x[i] - y[i] * d[i] * 2^(-1) - y[i+1] = y[i] + x[i] * d[i] * 2^(-i) - z[i+1] = z[i] - d[i] * atan(2^(-i)) - mode 0: vectoring; Rotates (x0,y0) to X-axis - (xn,zn)=(r,theta) - -PI/2 0) & (y0 > 0)) - quadrant = 1; - else if ((x0 < 0) & (y0 > 0)) - quadrant = 2; - else if ((x0 < 0) & (y0 < 0)) - quadrant = 3; - else if ((x0 > 0) & (y0 < 0)) - quadrant = 4; - - LOOP1: for (i = 0; i <= ROT; i++) - { - - #pragma HLS PIPELINE II=1 - - //dneg= (mode==1) ? (z<0) : (y>0); - dneg = (y > 0); - if (dneg) { -#ifdef BIT_ACCURATE - xp = x + (y >> i); - yp = y - (x >> i); -#else - xp = x + y/lut_pow2[i]; //x+(y>>i); - yp = y - x/lut_pow2[i];//y-(x>>i); -#endif - zp = z + atan_2Mi[i]; - } else { -#ifdef BIT_ACCURATE - xp = x - (y >> i); - yp = y + (x >> i); -#else - xp = x-y/lut_pow2[i]; //x - (y>>i); - yp = y+x/lut_pow2[i];//y + (x>>i); -#endif - zp = z - atan_2Mi[i]; - } - x = xp; - y = yp; - z = zp; - } - - if (quadrant == 1) { - //*xn=x; - //*yn=y; - *zn = z; - } else if (quadrant == 2) { - //*xn=x; - //*yn=-y; - *zn = cord_M_PI - z; - } else if (quadrant == 3) { - //*xn=-x; - //*yn=-y; - *zn = z - cord_M_PI; - } else if (quadrant == 4) { - //*xn=-x; - //*yn=-y; - *zn = -z; - } -} - -void top_atan2(coord_t y0, coord_t x0, phase_t *zn) -{ -#if defined(DB_DOUBLE_PRECISION) - *zn = atan2( (double) y0, (double) x0); -#elif defined(DB_SINGLE_PRECISION) - *zn = atan2f( (float) y0, (float) x0); -#elif defined(DB_CORDIC) - cordic_atan2(y0, x0, zn); -#else -#error -#endif -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/cordic_test.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/cordic_test.cpp deleted file mode 100644 index f6ac7b91ed..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/cordic_test.cpp +++ /dev/null @@ -1,92 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#include -#include -#include "read_file.h" - -#include "cordic.h" - -const int N = 1024*4; //110465; - -coord_t input_data[N][2]; -phase_t ref_results[N][1]; - -int main(void) -{ - coord_t inp_x, inp_y, out_x, out_y; - phase_t inp_rad, out_rad; - float res, ref_res; - - float diff, total_error = 0; - - int i; - FILE *fp, *fm; - - //const float angle = M_PI_2/N; - - fp = fopen("./test_data/vector.dat", "w"); - if (fp == NULL) { - fprintf(stderr, "unable to open output file\n"); - } - fscanf(fp, "%*[^\n]\n"); //skip first line - fscanf(fp, "%*[^\n]\n"); //skip second line - - fm = fopen("./test_data/check_res.m", "w"); - if (fm == NULL) { - fprintf(stderr, "unable to open MATLAB ile\n"); - } - fprintf(fm, "clear all; close all; clc;\n"); - fprintf(fm, "%%%%\n"); - fprintf(fm, "dat = load('vector.dat');\n"); - fprintf(fm, "diff = abs(dat(:,3) - dat(:,4));\n"); - fprintf(fm, "diff2= abs(dat(:,4) - dat(:,5));\n"); - fprintf(fm, "figure; plot(diff); title 'error CORDIC vs. ATAN2'; grid;\n"); - fprintf(fm, "figure; plot(diff2); title 'error2'; grid;\n"); - fprintf(fm, "max_diff = max(diff)\n"); - fprintf(fm, "sum_abs_err = sum(diff)\n"); - fprintf(fm, "max_diff2 = max(diff2)\n"); - fprintf(fm, "sum_abs_err2 = sum(diff2)\n"); - - //read files - read_file("./test_data/input_data.txt", input_data); - read_file("./test_data/ref_results.txt", ref_results); - - // vectoring mode - inp_rad = 0; - for (i = 0; i < N; i++) { - inp_y = (coord_t) input_data[i][0]; - inp_x = (coord_t) input_data[i][1]; - ref_res = (phase_t) ref_results[i][0]; - - //void cordic ( bool mode, coord_t x0, coord_t y0, phase_t z0, coord_t *xn, coord_t *yn, phase_t *zn); - //if ( (inp_y>0) & (inp_x>0) ) - { - // REF DESIGN - float c_atan2 = atan2f((float) inp_y, (float) inp_x); - // DUT - top_atan2(inp_y, inp_x, &out_rad); - - //check results - diff = out_rad - ref_results[i][0]; - if (diff < 0) - diff = 0 - diff; // take absolute value - total_error += diff; - fprintf(fp, "%20.10f %20.10f %20.10f %20.10f %20.10f\n", - (float) inp_y, (float) inp_x, (float) out_rad, - (float) ref_results[i][0], (float) c_atan2); - //fprintf(stderr, "%20.10f %20.10f %20.10f %20.10f\n", (float) inp_y, (float) inp_x, (float) out_rad, (float) ref_results[i][0]); - } - } - - fprintf(stderr, "total error = %f\n", total_error); - fprintf(stderr, "relative error = %f\n", total_error / N); - - fclose(fp); - fclose(fm); - - return 0; - -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/read_file.h b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/read_file.h deleted file mode 100644 index 89aecd5e0b..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/read_file.h +++ /dev/null @@ -1,45 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#ifndef H_READ_FILE_H -#define H_READ_FILE_H - -#include -#include - -template void read_file(char *filename, T outBuf[DIM1][DIM2] ) -{ - int i, j; - - float data; - char str[300]; - - FILE *fid = fopen( filename, "r"); - if (fid==NULL) - fprintf(stderr, "error in opening input file %s\n", filename); - - fscanf(fid, "%*[^\n]\n"); //skip first line - fscanf(fid, "%*[^\n]\n"); //skip second line - for (i = 0; i < DIM1; i++) - { - for (j = 0; j < DIM2; j++) - { - fscanf(fid,"%s", str); - data = atof(str); - outBuf[i][j] = (T) data; - //fprintf(stderr,"%f ", (float) data); - } - fscanf(fid,"\n"); - //fprintf(stderr,"\n"); - } - - fclose(fid); - - return; -} - - - -#endif diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/run_atan2_script.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/run_atan2_script.tcl deleted file mode 100644 index 35b28da087..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/run_atan2_script.tcl +++ /dev/null @@ -1,101 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -# Author: Daniele Bagni, Xilinx Inc - -puts "\n" -puts "************************************************************************" -puts "* EXAMPLE 7) ABOUT ATAN2()" -puts "************************************************************************" -puts "\n" - -################## SOLUTION1_DOUBLE: 64-bit floating point #################### - -open_project hls_atan2_prj -set_top top_atan2 -add_files cordic_atan2.cpp -cflags "-DDB_DOUBLE_PRECISION" -add_files -tb cordic_test.cpp -cflags "-DDB_DOUBLE_PRECISION" -add_files -tb test_data -open_solution "solution1_double" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 3.0 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 0.5 -csim_design -clean -csynth_design -#cosim_design -close_project - -################## SOLUTION1_FLOAT: 32-bit floating point #################### - -open_project hls_atan2_prj -set_top top_atan2 -add_files cordic_atan2.cpp -cflags "-DDB_SINGLE_PRECISION" -add_files -tb cordic_test.cpp -cflags "-DDB_SINGLE_PRECISION" -add_files -tb test_data -open_solution "solution1_single" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 3.0 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 0.5 -csim_design -clean -csynth_design -#cosim_design -close_project - -################## SOLUTION1_CORDIC: cordic algorithm #################### - -open_project hls_atan2_prj -set_top top_atan2 -add_files cordic_atan2.cpp -cflags "-DDB_CORDIC" -add_files -tb cordic_test.cpp -cflags "-DDB_CORDIC" -add_files -tb test_data -open_solution "solution1_cordic" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 3.0 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 0.5 -csim_design -clean -csynth_design -#cosim_design -#export_design -evaluate verilog -format ip_catalog -close_project - - -################## SOLUTION2_CORDIC: simplified cordic algorithm #################### - -open_project hls_atan2_prj -set_top top_atan2 -add_files cordic_atan2.cpp -cflags "-DDB_CORDIC -DBIT_ACCURATE" -add_files -tb cordic_test.cpp -cflags "-DDB_CORDIC -DBIT_ACCURATE" -add_files -tb test_data -open_solution "solution2_cordic_bitaccurate" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 3.0 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 0.5 -csim_design -clean -csynth_design -#cosim_design -#export_design -evaluate verilog -format ip_catalog -close_project - - -################## SOLUTION_EMPTY: to remove CFLAGS from GUI #################### - -open_project hls_atan2_prj -set_top top_atan2 -add_files cordic_atan2.cpp -add_files -tb cordic_test.cpp -add_files -tb test_data -open_solution "solution_empty" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 3.0 -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 0.5 -close_project diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/test_data/atan2_check_res.m b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/test_data/atan2_check_res.m deleted file mode 100644 index db95196a67..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/test_data/atan2_check_res.m +++ /dev/null @@ -1,14 +0,0 @@ -% Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -% SPDX-License-Identifier: MIT - -clear all; close all; clc; -%% -dat = load('vector.dat'); -diff = abs(dat(:,3) - dat(:,4)); -diff2= abs(dat(:,4) - dat(:,5)); -figure; plot(diff); title 'error CORDIC vs. ATAN2'; grid; -figure; plot(diff2); title 'error2'; grid; -max_diff = max(diff) -sum_abs_err = sum(diff) -max_diff2 = max(diff2) -sum_abs_err2 = sum(diff2) diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/test_data/check_res.m b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/test_data/check_res.m deleted file mode 100644 index 3d34dba13c..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/test_data/check_res.m +++ /dev/null @@ -1,11 +0,0 @@ -clear all; close all; clc; -%% -dat = load('vector.dat'); -diff = abs(dat(:,3) - dat(:,4)); -diff2= abs(dat(:,4) - dat(:,5)); -figure; plot(diff); title 'error CORDIC vs. ATAN2'; grid; -figure; plot(diff2); title 'error2'; grid; -max_diff = max(diff) -sum_abs_err = sum(diff) -max_diff2 = max(diff2) -sum_abs_err2 = sum(diff2) diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/test_data/input_data.txt b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/test_data/input_data.txt deleted file mode 100644 index c9c6e3c3f2..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/7_atan2/test_data/input_data.txt +++ /dev/null @@ -1,110467 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. 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All rights reserved. -# SPDX-License-Identifier: MIT - - -.PHONY: help hls_kernels hls_clean zcu102_all zcu102_clean all clean - -hls_clean: - rm -rf *_prj *.log *~ ./logs - -hls_kernels: - vitis-run --mode hls --tcl ./run_vect_add_script.tcl - -zcu102_all: - $(MAKE) -C ./make-flow all - -zcu102_clean: - $(MAKE) -C ./make-flow clean -# mkdir -p ./make-flow/zcu102_vadd/src -# mkdir -p ./make-flow/zcu102_vadd_kernels/src -# mkdir -p ./make-flow/zcu102_vadd_system_hw_link/src - -kernels: hls_kernels -all: zcu102_all hls_kernels -clean: hls_clean zcu102_clean diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/make-flow/Makefile b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/make-flow/Makefile deleted file mode 100644 index 7104e00f5c..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/make-flow/Makefile +++ /dev/null @@ -1,38 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -.PHONY: help all clean zcu102_vadd_clean zcu102_vadd_build zcu102_vadd_prepare - -all: zcu102_vadd_prepare zcu102_vadd_build -clean: zcu102_vadd_clean - - -zcu102_vadd_clean: - $(MAKE) -C ./zcu102_vadd/Hardware clean - $(MAKE) -C ./zcu102_vadd_kernels/Hardware clean - $(MAKE) -C ./zcu102_vadd_system_hw_link/Hardware clean - $(MAKE) -C ./zcu102_vadd_system/Hardware clean - rm -rf ./zcu102_vadd/src - rm -rf ./zcu102_vadd_kernels/src - rm -rf ./zcu102_vadd_system/src - rm -f ./zcu102_vadd_system/Hardware/*.log - rm -f ./zcu102_vadd_system/Hardware/binary* - rm -f ./zcu102_vadd_system/Hardware/*~ - rm -rf ./zcu102_vadd_system/Hardware/.ipcache - rm -rf ./zcu102_vadd_system_hw_link/Hardware/.ipcache/ - rm -rf ./zcu102_vadd_system_hw_link/src - -zcu102_vadd_build: - $(MAKE) -C ./zcu102_vadd/Hardware all - $(MAKE) -C ./zcu102_vadd_kernels/Hardware all - $(MAKE) -C ./zcu102_vadd_system_hw_link/Hardware all - $(MAKE) -C ./zcu102_vadd_system/Hardware all - -zcu102_vadd_prepare: - mkdir -p $(realpath ./zcu102_vadd)/src - mkdir -p $(realpath ./zcu102_vadd_kernels)/src - cp -f $(realpath ../src/host)/* $(realpath ./zcu102_vadd)/src/ - cp -f $(realpath ../src/hls)/vadd_include.h $(realpath ./zcu102_vadd)/src/ - cp -f $(realpath ../src/hls)/hls_krnl* $(realpath ./zcu102_vadd_kernels)/src/ - cp -f $(realpath ../src/hls)/*.h $(realpath ./zcu102_vadd_kernels)/src/ -# mkdir -p $(realpath ./zcu102_vadd_system_hw_link)/src diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/make-flow/zcu102_vadd/Hardware/makefile b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/make-flow/zcu102_vadd/Hardware/makefile deleted file mode 100644 index 193201cf0b..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/make-flow/zcu102_vadd/Hardware/makefile +++ /dev/null @@ -1,62 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -# compiler tools -#XILINX_VITIS ?= /media/danieleb/DATA/2022.2/tools/Xilinx/Vitis/2022.2 - -# compiler tools -HOST_CXX ?= $(XILINX_VITIS)/gnu/aarch64/lin/aarch64-linux/bin/aarch64-linux-gnu-g++ -RM = rm -f -RMDIR = rm -rf - - -#VITIS_PLATFORM = xilinx_zcu102_base_202220_1 -#VITIS_PLATFORM_DIR = $(XILINX_VITIS)/base_platforms/xilinx_zcu102_base_202220_1 -#VITIS_PLATFORM_PATH = $(XILINX_VITIS)/base_platforms/xilinx_zcu102_base_202220_1/xilinx_zcu102_base_202220_1.xpfm - -# host compiler global settings -CXXFLAGS += -std=c++17 -DVITIS_PLATFORM=$(ZYNQMP_VITIS_PLATFORM) -D__USE_XOPEN2K8 -I$(XILINX_HLS)/include/ -I$(COMMON_IMAGE_ZYNQMP)/sysroots/cortexa72-cortexa53-amd-linux/usr/include/xrt/ -O2 -g -Wall -c -fmessage-length=0 --sysroot=$(COMMON_IMAGE_ZYNQMP)/sysroots/cortexa72-cortexa53-amd-linux - -LDFLAGS += -lxilinxopencl -lxrt_core -lxrt_coreutil -lpthread -lrt -ldl -lcrypt -lstdc++ -L$(COMMON_IMAGE_ZYNQMP)/sysroots/cortexa72-cortexa53-amd-linux/usr/lib/ --sysroot=$(COMMON_IMAGE_ZYNQMP)/sysroots/cortexa72-cortexa53-amd-linux - -# -# host files -# - -HOST_OBJECTS += src/cl_host_vadd.o -HOST_OBJECTS += src/xrt_host_vadd.o - -HOST_EXE = zcu102_vadd - -BUILD_SUBDIRS += src/ - -# -# primary build targets -# - -.PHONY: all clean -all: $(HOST_EXE) - -clean: - $(RM) -rf $(HOST_EXE) $(HOST_OBJECTS) ./src *~ - -.PHONY: incremental -incremental: all - - -nothing: - -# -# host rules -# - -src/cl_host_vadd.o: ../src/cl_host_vadd.cpp ../src/cl_vadd.h - -@mkdir -p $(@D) - $(HOST_CXX) $(CXXFLAGS) -o "$@" "$<" - -src/xrt_host_vadd.o: ../src/xrt_host_vadd.cpp ../src/vadd_include.h - -@mkdir -p $(@D) - $(HOST_CXX) $(CXXFLAGS) -o "$@" "$<" - -$(HOST_EXE): $(HOST_OBJECTS) - $(HOST_CXX) -o "$@" $(+) $(LDFLAGS) diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/make-flow/zcu102_vadd_kernels/Hardware/krnl_vadd-compile.cfg b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/make-flow/zcu102_vadd_kernels/Hardware/krnl_vadd-compile.cfg deleted file mode 100644 index b6e63634f3..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/make-flow/zcu102_vadd_kernels/Hardware/krnl_vadd-compile.cfg +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -#platform=/media/danieleb/DATA/2022.2/tools/Xilinx/Vitis/2022.2/base_platforms/xilinx_zcu102_base_202220_1/xilinx_zcu102_base_202220_1.xpfm -save-temps=1 -kernel=krnl_vadd -messageDb=build/krnl_vadd.mdb -temp_dir=build -report_dir=build/reports -log_dir=build/logs - -[advanced] -misc=solution_name=krnl_vadd diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/make-flow/zcu102_vadd_kernels/Hardware/makefile b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/make-flow/zcu102_vadd_kernels/Hardware/makefile deleted file mode 100644 index 46e4aed8e5..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/make-flow/zcu102_vadd_kernels/Hardware/makefile +++ /dev/null @@ -1,58 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -# compiler tools -#XILINX_VITIS ?= /media/danieleb/DATA/2022.2/tools/Xilinx/Vitis/2022.2 -#XILINX_VIVADO ?= /media/danieleb/DATA/2022.2/tools/Xilinx/Vivado/2022.2 -#XILINX_HLS ?= $(XILINX_VITIS)/Vivado_HLS - -VPP ?= ${XILINX_VITIS}/bin/v++ -RM = rm -f -RMDIR = rm -rf - -#VITIS_PLATFORM = xilinx_zcu102_base_202220_1 -#VITIS_PLATFORM_DIR = $(XILINX_VITIS)/base_platforms/xilinx_zcu102_base_202220_1 -#VITIS_PLATFORM_PATH = $(XILINX_VITIS)/base_platforms/xilinx_zcu102_base_202220_1/xilinx_zcu102_base_202220_1.xpfm - -TARGET = hw -VPP_OPTS = --target $(TARGET) - -# -# Hw kernel files -# - - -BUILD_SUBDIRS += build -HW_KERNEL_OBJS += build/krnl_vadd.xo -SRC_KERNEL_OBJS += build/krnl_vadd.xo - -ALL_MESSAGE_FILES = $(subst .xo,.o,.mdb,$(SRC_KERNEL_OBJS)) - -# -# primary build targets -# - -.PHONY: all clean -all: $(HW_KERNEL_OBJS) - - -clean: - -$(RM) $(SRC_KERNEL_OBJS) $(ALL_MESSAGE_FILES) *.log *~ - -$(RMDIR) $(BUILD_SUBDIRS) - -$(RMDIR) .Xil - -.PHONY: incremental -incremental: all - - -nothing: - -# -# Hw Kernels compile; -# - -build/krnl_vadd.xo: ../src/hls_krnl_vadd.cpp ../src/vadd_include.h krnl_vadd-compile.cfg - -@mkdir -p $(@D) - -@$(RM) $@ - $(VPP) $(VPP_OPTS) --compile -I"$( binary_container_1.xclbin.sh - $(VPP_LINKER) $(VPP_OPTS) --link --config binary_container_1-link.cfg --platform $(VITIS_PLATFORM_XPFM) -o"$@" $(BINARY_CONTAINER_1_OBJS) diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/make-flow/zcu102_vadd_system_hw_link/Hardware/xcd.log b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/make-flow/zcu102_vadd_system_hw_link/Hardware/xcd.log deleted file mode 100644 index 5149388f6b..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/make-flow/zcu102_vadd_system_hw_link/Hardware/xcd.log +++ /dev/null @@ -1,142 +0,0 @@ -Mon Feb 27 17:21:03 2023: Running xcd server. This server was built by gradle. -Mon Feb 27 17:21:03 2023: Server was asked to start on port: '46051' -Mon Feb 27 17:21:03 2023: Server is using token UUID: '62d52ddd-c9e6-4551-bb24-8b7cf2d190fa' -Mon Feb 27 17:21:03 2023: SESSION_MGR: creating session with session uuid: '6d04a3e9-ade5-4ab9-8d63-1f78fcd2ec76' and name 'default' -Mon Feb 27 17:21:03 2023: Attempting to start server on port '46051' -Mon Feb 27 17:21:03 2023: XCD main fifo: created main fifo '/tmp/xcdmain62d52ddd-c9e6-4551-bb24-8b7cf2d190fa', fd read = 13 -Mon Feb 27 17:21:03 2023: Running Dispatch Server -Mon Feb 27 17:21:03 2023: Version 2.2.0 -Mon Feb 27 17:21:12 2023: Dispatch Server: Accepted socket connection from client -Mon Feb 27 17:21:12 2023: Starting Socket connection -Mon Feb 27 17:21:12 2023: EXCHANGE_TOKEN received, server token: 62d52ddd-c9e6-4551-bb24-8b7cf2d190fa, passed token: 62d52ddd-c9e6-4551-bb24-8b7cf2d190fa -Mon Feb 27 17:21:12 2023: DISPATCH_HANDLER: Adding handler from function makeHandler in library libxv_system_diagram -Mon Feb 27 17:21:12 2023: SESSION_MGR: creating session with session uuid: 'e942b2dc-14c8-49e2-9af4-da8fea1046af' and name 'link' -Mon Feb 27 17:21:12 2023: KERNEL_SVC: creating session with uuid: 'e942b2dc-14c8-49e2-9af4-da8fea1046af' and name 'link' -Mon Feb 27 17:21:12 2023: GUIDANCE_SMGR: creating guidance session with uuid: 'e942b2dc-14c8-49e2-9af4-da8fea1046af' and name 'link' -Mon Feb 27 17:21:12 2023: SYSTEM_DIAGRAM: creating session with uuid: 'e942b2dc-14c8-49e2-9af4-da8fea1046af' and name 'link' -Mon Feb 27 17:21:14 2023: SESSION_MGR: closing session for UUID 'e942b2dc-14c8-49e2-9af4-da8fea1046af' with name 'link' -Mon Feb 27 17:21:14 2023: KERNEL_SVC: closing session for UUID 'e942b2dc-14c8-49e2-9af4-da8fea1046af' with name 'link' -Mon Feb 27 17:21:14 2023: GUIDANCE_SMGR: closing session for UUID 'e942b2dc-14c8-49e2-9af4-da8fea1046af' with name 'link' -Mon Feb 27 17:21:14 2023: SYSTEM_DIAGRAM: closing session for UUID 'e942b2dc-14c8-49e2-9af4-da8fea1046af' with name 'link' -Mon Feb 27 17:21:14 2023: STOP_SERVER received, server token: 62d52ddd-c9e6-4551-bb24-8b7cf2d190fa, passed token: 62d52ddd-c9e6-4551-bb24-8b7cf2d190fa -Mon Feb 27 17:21:14 2023: Socket received request to stop server. -Mon Feb 27 17:21:14 2023: Dispatch Server: do_await_stop -Mon Feb 27 17:21:14 2023: Dispatch Server: stopping mainFifo_ -Mon Feb 27 17:21:14 2023: XCD main fifo: Stopping -Mon Feb 27 17:21:14 2023: XCD main fifo: do_read error code: Operation canceled -Mon Feb 27 17:21:14 2023: XCD main fifo: bytes_transferred: 0 -Mon Feb 27 17:21:14 2023: SERVER: destructor for server bound to port 46051 -Mon Feb 27 17:21:14 2023: XCD main fifo: Good unlink of /tmp/xcdmain62d52ddd-c9e6-4551-bb24-8b7cf2d190fa -Mon Feb 27 17:21:14 2023: Server exiting with status 0. -Mon Feb 27 17:21:14 2023: Closing log file. -Tue Feb 28 08:01:37 2023: Running xcd server. This server was built by gradle. -Tue Feb 28 08:01:37 2023: Server was asked to start on port: '33495' -Tue Feb 28 08:01:37 2023: Server is using token UUID: '1b050bdd-f25c-4df6-a877-ab207de686ac' -Tue Feb 28 08:01:37 2023: SESSION_MGR: creating session with session uuid: '6d04a3e9-ade5-4ab9-8d63-1f78fcd2ec76' and name 'default' -Tue Feb 28 08:01:37 2023: Attempting to start server on port '33495' -Tue Feb 28 08:01:37 2023: XCD main fifo: created main fifo '/tmp/xcdmain1b050bdd-f25c-4df6-a877-ab207de686ac', fd read = 13 -Tue Feb 28 08:01:37 2023: Running Dispatch Server -Tue Feb 28 08:01:37 2023: Version 2.2.0 -Tue Feb 28 08:01:46 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:01:46 2023: Starting Socket connection -Tue Feb 28 08:01:46 2023: EXCHANGE_TOKEN received, server token: 1b050bdd-f25c-4df6-a877-ab207de686ac, passed token: 1b050bdd-f25c-4df6-a877-ab207de686ac -Tue Feb 28 08:01:46 2023: DISPATCH_HANDLER: Adding handler from function makeHandler in library libxv_system_diagram -Tue Feb 28 08:01:46 2023: SESSION_MGR: creating session with session uuid: 'cf872759-c5bc-422b-85bd-9732ad3ba1ff' and name 'link' -Tue Feb 28 08:01:46 2023: KERNEL_SVC: creating session with uuid: 'cf872759-c5bc-422b-85bd-9732ad3ba1ff' and name 'link' -Tue Feb 28 08:01:46 2023: GUIDANCE_SMGR: creating guidance session with uuid: 'cf872759-c5bc-422b-85bd-9732ad3ba1ff' and name 'link' -Tue Feb 28 08:01:46 2023: SYSTEM_DIAGRAM: creating session with uuid: 'cf872759-c5bc-422b-85bd-9732ad3ba1ff' and name 'link' -Tue Feb 28 08:02:26 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:02:26 2023: Starting Socket connection -Tue Feb 28 08:03:07 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:03:07 2023: Starting Socket connection -Tue Feb 28 08:21:00 2023: Running xcd server. This server was built by gradle. -Tue Feb 28 08:21:00 2023: Server was asked to start on port: '37571' -Tue Feb 28 08:21:00 2023: Server is using token UUID: 'eba00f7e-e8cf-4669-a4e5-9cc798fab2d8' -Tue Feb 28 08:21:00 2023: SESSION_MGR: creating session with session uuid: '6d04a3e9-ade5-4ab9-8d63-1f78fcd2ec76' and name 'default' -Tue Feb 28 08:21:00 2023: Attempting to start server on port '37571' -Tue Feb 28 08:21:00 2023: XCD main fifo: created main fifo '/tmp/xcdmaineba00f7e-e8cf-4669-a4e5-9cc798fab2d8', fd read = 13 -Tue Feb 28 08:21:00 2023: Running Dispatch Server -Tue Feb 28 08:21:00 2023: Version 2.2.0 -Tue Feb 28 08:21:09 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:21:09 2023: Starting Socket connection -Tue Feb 28 08:21:09 2023: EXCHANGE_TOKEN received, server token: eba00f7e-e8cf-4669-a4e5-9cc798fab2d8, passed token: eba00f7e-e8cf-4669-a4e5-9cc798fab2d8 -Tue Feb 28 08:21:09 2023: DISPATCH_HANDLER: Adding handler from function makeHandler in library libxv_system_diagram -Tue Feb 28 08:21:09 2023: SESSION_MGR: creating session with session uuid: '22434663-f463-4ede-84ea-6c07cb4214da' and name 'link' -Tue Feb 28 08:21:09 2023: KERNEL_SVC: creating session with uuid: '22434663-f463-4ede-84ea-6c07cb4214da' and name 'link' -Tue Feb 28 08:21:09 2023: GUIDANCE_SMGR: creating guidance session with uuid: '22434663-f463-4ede-84ea-6c07cb4214da' and name 'link' -Tue Feb 28 08:21:09 2023: SYSTEM_DIAGRAM: creating session with uuid: '22434663-f463-4ede-84ea-6c07cb4214da' and name 'link' -Tue Feb 28 08:21:48 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:21:48 2023: Starting Socket connection -Tue Feb 28 08:22:29 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:22:29 2023: Starting Socket connection -Tue Feb 28 08:26:04 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:26:04 2023: Starting Socket connection -Tue Feb 28 08:26:04 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:26:04 2023: Starting Socket connection -Tue Feb 28 08:26:04 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:26:04 2023: Starting Socket connection -Tue Feb 28 08:26:04 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:26:04 2023: Starting Socket connection -Tue Feb 28 08:26:05 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:26:05 2023: Starting Socket connection -Tue Feb 28 08:26:05 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:26:05 2023: Starting Socket connection -Tue Feb 28 08:26:05 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:26:05 2023: Starting Socket connection -Tue Feb 28 08:26:05 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:26:05 2023: Starting Socket connection -Tue Feb 28 08:29:04 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:29:04 2023: Starting Socket connection -Tue Feb 28 08:29:10 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:29:10 2023: Starting Socket connection -Tue Feb 28 08:29:10 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:29:10 2023: Starting Socket connection -Tue Feb 28 08:29:15 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:29:15 2023: Starting Socket connection -Tue Feb 28 08:29:15 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:29:15 2023: Starting Socket connection -Tue Feb 28 08:29:15 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:29:15 2023: Starting Socket connection -Tue Feb 28 08:29:18 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:29:18 2023: Starting Socket connection -Tue Feb 28 08:29:30 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:29:30 2023: Starting Socket connection -Tue Feb 28 08:32:00 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:32:00 2023: Starting Socket connection -Tue Feb 28 08:32:11 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:32:11 2023: Starting Socket connection -Tue Feb 28 08:32:21 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:32:21 2023: Starting Socket connection -Tue Feb 28 08:32:27 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:32:27 2023: Starting Socket connection -Tue Feb 28 08:32:29 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:32:29 2023: Starting Socket connection -Tue Feb 28 08:32:37 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:32:37 2023: Starting Socket connection -Tue Feb 28 08:32:43 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:32:43 2023: Starting Socket connection -Tue Feb 28 08:33:20 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:33:20 2023: Starting Socket connection -Tue Feb 28 08:34:28 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:34:28 2023: Starting Socket connection -Tue Feb 28 08:36:19 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:36:19 2023: Starting Socket connection -Tue Feb 28 08:38:47 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:38:47 2023: Starting Socket connection -Tue Feb 28 08:41:27 2023: Dispatch Server: Accepted socket connection from client -Tue Feb 28 08:41:27 2023: Starting Socket connection -Tue Feb 28 08:49:19 2023: SESSION_MGR: closing session for UUID '22434663-f463-4ede-84ea-6c07cb4214da' with name 'link' -Tue Feb 28 08:49:19 2023: KERNEL_SVC: closing session for UUID '22434663-f463-4ede-84ea-6c07cb4214da' with name 'link' -Tue Feb 28 08:49:19 2023: GUIDANCE_SMGR: closing session for UUID '22434663-f463-4ede-84ea-6c07cb4214da' with name 'link' -Tue Feb 28 08:49:19 2023: SYSTEM_DIAGRAM: closing session for UUID '22434663-f463-4ede-84ea-6c07cb4214da' with name 'link' -Tue Feb 28 08:49:19 2023: STOP_SERVER received, server token: eba00f7e-e8cf-4669-a4e5-9cc798fab2d8, passed token: eba00f7e-e8cf-4669-a4e5-9cc798fab2d8 -Tue Feb 28 08:49:19 2023: Socket received request to stop server. -Tue Feb 28 08:49:19 2023: Dispatch Server: do_await_stop -Tue Feb 28 08:49:19 2023: Dispatch Server: stopping mainFifo_ -Tue Feb 28 08:49:19 2023: XCD main fifo: Stopping -Tue Feb 28 08:49:19 2023: XCD main fifo: do_read error code: Operation canceled -Tue Feb 28 08:49:19 2023: XCD main fifo: bytes_transferred: 0 -Tue Feb 28 08:49:19 2023: SERVER: destructor for server bound to port 37571 -Tue Feb 28 08:49:19 2023: XCD main fifo: Good unlink of /tmp/xcdmaineba00f7e-e8cf-4669-a4e5-9cc798fab2d8 -Tue Feb 28 08:49:19 2023: Server exiting with status 0. -Tue Feb 28 08:49:19 2023: Closing log file. diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/run_vect_add_script.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/run_vect_add_script.tcl deleted file mode 100644 index 46da05a213..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/run_vect_add_script.tcl +++ /dev/null @@ -1,43 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -puts "\n" -puts "************************************************************************" -puts "* EXAMPLE 8) VECTOR ADDITION DEMO" -puts "************************************************************************" -puts "\n" - -open_project hls_vadd_prj -set_top krnl_vadd -add_files src/hls/hls_krnl_vadd.cpp -add_files -tb src/hls/hls_tb_vadd.cpp -cflags "-Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" -#add_files -tb src/vadd_include.h -cflags "-Wno-unknown-pragmas" -csimflags "-Wno-unknown-pragmas" - -open_solution "solution_vivado" -flow_target vivado -set_part xczu9eg-ffvb1156-2-e -create_clock -period 150.000000MHz -name default -config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 0.5 -#source "./hls_vadd_prj/solution1/directives.tcl" -csim_design -clean -csynth_design -#cosim_design - -open_solution "solution_vitis" -flow_target vitis -set_part xczu9eg-ffvb1156-2-e -create_clock -period 150.000000MHz -name default -# v++ --advanced.param compiler.hlsDataflowStrictMode -config_dataflow -strict_mode warning -# v++ --advanced.param compiler.deadlockDetection -config_export -deadlock_detection sim -# v++ --advanced.param compiler.axiDeadLockFree -config_interface -m_axi_conservative_mode=1 -config_interface -m_axi_addr64 -# v++ --hls.max_memory_ports -config_interface -m_axi_auto_max_ports=0 -config_export -format xo -ipname krnl_vadd -csynth_design -#cosim_design -#export_design -close_project diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/src/hls/hls_krnl_vadd.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/src/hls/hls_krnl_vadd.cpp deleted file mode 100644 index 529d9a9999..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/src/hls/hls_krnl_vadd.cpp +++ /dev/null @@ -1,76 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - - -// Includes -#include -#include -#include "vadd_include.h" - - -// TRIPCOUNT identifier -const int c_size = DATA_SIZE; - -static void load_input(uint32_t* in, hls::stream& inStream, int size) { -mem_rd: - for (int i = 0; i < size; i++) { -#pragma HLS PIPELINE -#pragma HLS LOOP_TRIPCOUNT min = c_size max = c_size - inStream << in[i]; - } -} - -static void compute_add(hls::stream& in1_stream, - hls::stream& in2_stream, - hls::stream& out_stream, - int size) { -// The kernel is operating with vector of NUM_WORDS integers. The + operator performs -// an element-wise add, resulting in NUM_WORDS parallel additions. -execute: - for (int i = 0; i < size; i++) { -#pragma HLS PIPELINE -#pragma HLS LOOP_TRIPCOUNT min = c_size max = c_size - out_stream << (in1_stream.read() + in2_stream.read()); - } -} - -static void store_result(uint32_t* out, hls::stream& out_stream, int size) { -mem_wr: - for (int i = 0; i < size; i++) { -#pragma HLS PIPELINE -#pragma HLS LOOP_TRIPCOUNT min = c_size max = c_size - out[i] = out_stream.read(); - } -} - -//extern "C" { - -/* - Vector Addition Kernel - - Arguments: - in1 (input) --> Input vector 1 - in2 (input) --> Input vector 2 - out (output) --> Output vector - size (input) --> Number of elements in vector -*/ - -void krnl_vadd(uint32_t* in1, uint32_t* in2, uint32_t* out, int size) { -#pragma HLS INTERFACE mode=m_axi bundle=gmem0 depth=c_size port=in1 -#pragma HLS INTERFACE mode=m_axi bundle=gmem1 depth=c_size port=in2 -#pragma HLS INTERFACE mode=m_axi bundle=gmem0 depth=c_size port=out - - static hls::stream in1_stream("input_stream_1"); - static hls::stream in2_stream("input_stream_2"); - static hls::stream out_stream("output_stream"); - -#pragma HLS dataflow - // dataflow pragma instruct compiler to run following three APIs in parallel - load_input(in1, in1_stream, size); - load_input(in2, in2_stream, size); - compute_add(in1_stream, in2_stream, out_stream, size); - store_result(out, out_stream, size); -} -//} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/src/hls/hls_tb_vadd.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/src/hls/hls_tb_vadd.cpp deleted file mode 100644 index eaa4f1ad5a..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/src/hls/hls_tb_vadd.cpp +++ /dev/null @@ -1,61 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#include -#include -#include -#include -#include "vadd_include.h" - - -int main(int argc, char* argv[]) -{ - - uint32_t *ptr_inp_a = (uint32_t *) malloc(DATA_SIZE * sizeof(uint32_t)); - uint32_t *ptr_inp_b = (uint32_t *) malloc(DATA_SIZE * sizeof(uint32_t)); - uint32_t *ptr_res = (uint32_t *) malloc(DATA_SIZE * sizeof(uint32_t)); - - //setting input data - FILE *fin1=fopen("vector_inputs.txt", "w"); - - // Initialization, should only be called once. - //srand(time(NULL)); //this line makes HLS COSIM TO FAIL: cosim is a two steps process, data originated in the second step would be totally different from first step - srand(41); // to fix the problem of fist ;line - for(int i = 0 ; i< DATA_SIZE; i++) - { - // to avoid overflows let us use short ints - unsigned short int r1 = (unsigned short int) rand(); // Returns a pseudo-random integer between 0 and RAND_MAX. - unsigned short int r2 = (unsigned short int) rand(); // Returns a pseudo-random integer between 0 and RAND_MAX. - ptr_inp_a[i] = r1; - ptr_inp_b[i] = r2; - fprintf(fin1, "%10d\t%10d\n", r1, r2); - } - fclose(fin1); - - //call DUT - krnl_vadd(ptr_inp_a, ptr_inp_b, ptr_res, DATA_SIZE); - - // Verify the result - FILE *fin2=fopen("vector_out.txt", "w"); - int match = 0; - for (int i = 0; i < DATA_SIZE; i++) - { - uint32_t host_result = ptr_inp_a[i] + ptr_inp_b[i]; - fprintf(fin2, "%10d\t%10d\n", host_result, ptr_res[i]); - if (ptr_res[i] != host_result) { - printf("MISMATCH ERROR at %d: expected %d got %d\n", i, host_result, ptr_res[i]); - match = 1; - //break; - } - } - fclose(fin2); - free(ptr_inp_a); - free(ptr_inp_b); - free(ptr_res); - - std::cout << "TEST " << (match ? "FAILED" : "PASSED") << std::endl; - return match; - -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/src/hls/vadd_include.h b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/src/hls/vadd_include.h deleted file mode 100644 index 64ff89dcac..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/src/hls/vadd_include.h +++ /dev/null @@ -1,20 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#ifndef _H_VADD_INCLUDE_H_ -#define _H_VADD_INCLUDE_H_ - -#pragma once - -#define DATA_SIZE 4096 - -//to compile host code with XRT APIs instead of OpenCL APIs -#define DB_USE_XRT - -void krnl_vadd(uint32_t* in1, uint32_t* in2, uint32_t* out, int size); - - - -#endif diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/src/host/cl_host_vadd.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/src/host/cl_host_vadd.cpp deleted file mode 100644 index 7d791c436c..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/src/host/cl_host_vadd.cpp +++ /dev/null @@ -1,190 +0,0 @@ -/******************************************************************************* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*******************************************************************************/ - -#include -#include -#include -#include -#include "cl_vadd.h" - - -#define OCL_CHECK(error, call) \ - call; \ - if (error != CL_SUCCESS) { \ - printf("%s:%d Error calling " #call ", error code is: %d\n", __FILE__, __LINE__, error); \ - exit(EXIT_FAILURE); \ - } - -static const std::string error_message = - "Error: Result mismatch:\n" - "i = %d CPU result = %d Device result = %d\n"; - - - -#ifndef DB_USE_XRT - - -int main(int argc, char* argv[]) -{ - // TARGET_DEVICE macro needs to be passed from gcc command line - if (argc != 2) { - std::cout << "Usage: " << argv[0] << " " << std::endl; - return EXIT_FAILURE; - } - - std::string xclbinFilename = argv[1]; - - // Compute the size of array in bytes - size_t size_in_bytes = DATA_SIZE * sizeof(int); - - // Creates a vector of DATA_SIZE elements with an initial value of 10 and 32 - // using customized allocator for getting buffer alignment to 4k boundary - - std::vector devices; - cl_int err; - cl::Context context; - cl::CommandQueue q; - cl::Kernel krnl_vector_add; - cl::Program program; - std::vector platforms; - bool found_device = false; - - // traversing all Platforms To find Xilinx Platform and targeted - // Device in Xilinx Platform - cl::Platform::get(&platforms); - for (size_t i = 0; (i < platforms.size()) & (found_device == false); i++) { - cl::Platform platform = platforms[i]; - std::string platformName = platform.getInfo(); - if (platformName == "Xilinx") { - devices.clear(); - platform.getDevices(CL_DEVICE_TYPE_ACCELERATOR, &devices); - if (devices.size()) { - found_device = true; - break; - } - } - } - if (found_device == false) { - std::cout << "Error: Unable to find Target Device " << std::endl; - return EXIT_FAILURE; - } - - std::cout << "INFO: Reading " << xclbinFilename << std::endl; - FILE* fp; - if ((fp = fopen(xclbinFilename.c_str(), "r")) == nullptr) { - printf("ERROR: %s xclbin not available please build\n", xclbinFilename.c_str()); - exit(EXIT_FAILURE); - } - // Load xclbin - std::cout << "Loading: '" << xclbinFilename << "'\n"; - std::ifstream bin_file(xclbinFilename, std::ifstream::binary); - bin_file.seekg(0, bin_file.end); - unsigned nb = bin_file.tellg(); - bin_file.seekg(0, bin_file.beg); - char* buf = new char[nb]; - bin_file.read(buf, nb); - - // Creating Program from Binary File - cl::Program::Binaries bins; - bins.push_back({buf, nb}); - bool valid_device = false; - for (unsigned int i = 0; i < devices.size(); i++) { - auto device = devices[i]; - // Creating Context and Command Queue for selected Device - OCL_CHECK(err, context = cl::Context(device, nullptr, nullptr, nullptr, &err)); - OCL_CHECK(err, q = cl::CommandQueue(context, device, CL_QUEUE_PROFILING_ENABLE, &err)); - std::cout << "Trying to program device[" << i << "]: " << device.getInfo() << std::endl; - cl::Program program(context, {device}, bins, nullptr, &err); - if (err != CL_SUCCESS) { - std::cout << "Failed to program device[" << i << "] with xclbin file!\n"; - } else { - std::cout << "Device[" << i << "]: program successful!\n"; - OCL_CHECK(err, krnl_vector_add = cl::Kernel(program, "krnl_vadd", &err)); - valid_device = true; - break; // we break because we found a valid device - } - } - if (!valid_device) { - std::cout << "Failed to program any device found, exit!\n"; - exit(EXIT_FAILURE); - } - - // These commands will allocate memory on the Device. The cl::Buffer objects can - // be used to reference the memory locations on the device. - OCL_CHECK(err, cl::Buffer buffer_a(context, CL_MEM_READ_ONLY, size_in_bytes, NULL, &err)); - OCL_CHECK(err, cl::Buffer buffer_b(context, CL_MEM_READ_ONLY, size_in_bytes, NULL, &err)); - OCL_CHECK(err, cl::Buffer buffer_result(context, CL_MEM_WRITE_ONLY, size_in_bytes, NULL, &err)); - - // set the kernel Arguments - int narg = 0; - OCL_CHECK(err, err = krnl_vector_add.setArg(narg++, buffer_a)); - OCL_CHECK(err, err = krnl_vector_add.setArg(narg++, buffer_b)); - OCL_CHECK(err, err = krnl_vector_add.setArg(narg++, buffer_result)); - OCL_CHECK(err, err = krnl_vector_add.setArg(narg++, DATA_SIZE)); - - // We then need to map our OpenCL buffers to get the pointers - int* ptr_a; - int* ptr_b; - int* ptr_result; - OCL_CHECK(err, - ptr_a = (int*)q.enqueueMapBuffer(buffer_a, CL_TRUE, CL_MAP_WRITE, 0, size_in_bytes, NULL, NULL, &err)); - OCL_CHECK(err, - ptr_b = (int*)q.enqueueMapBuffer(buffer_b, CL_TRUE, CL_MAP_WRITE, 0, size_in_bytes, NULL, NULL, &err)); - OCL_CHECK(err, ptr_result = (int*)q.enqueueMapBuffer(buffer_result, CL_TRUE, CL_MAP_READ, 0, size_in_bytes, NULL, - NULL, &err)); - - //setting input data - FILE *fin1=fopen("vector_inputs.txt", "w"); - srand(time(NULL)); // Initialization, should only be called once. - for(int i = 0 ; i< DATA_SIZE; i++) - { - unsigned short int r1 = (unsigned short int) rand(); // Returns a pseudo-random integer between 0 and RAND_MAX. - unsigned short int r2 = (unsigned short int) rand(); // Returns a pseudo-random integer between 0 and RAND_MAX. - ptr_a[i] = r1; - ptr_b[i] = r2; - fprintf(fin1, "%10d\t%10d\n", r1, r2); - } - fclose(fin1); - - - // Data will be migrated to kernel space - OCL_CHECK(err, err = q.enqueueMigrateMemObjects({buffer_a, buffer_b}, 0 /* 0 means from host*/)); - - // Launch the Kernel - OCL_CHECK(err, err = q.enqueueTask(krnl_vector_add)); - - // The result of the previous kernel execution will need to be retrieved in - // order to view the results. This call will transfer the data from FPGA to - // source_results vector - OCL_CHECK(err, q.enqueueMigrateMemObjects({buffer_result}, CL_MIGRATE_MEM_OBJECT_HOST)); - - OCL_CHECK(err, q.finish()); - - // Verify the result - FILE *fin2=fopen("vector_out.txt", "w"); - int match = 0; - for (int i = 0; i < DATA_SIZE; i++) - { - int host_result = ptr_a[i] + ptr_b[i]; - fprintf(fin2, "%10d\t%10d\n", host_result, ptr_result[i]); - if (ptr_result[i] != host_result) - { - printf(error_message.c_str(), i, host_result, ptr_result[i]); - match = 1; - break; - } - } - fclose(fin2); - - OCL_CHECK(err, err = q.enqueueUnmapMemObject(buffer_a, ptr_a)); - OCL_CHECK(err, err = q.enqueueUnmapMemObject(buffer_b, ptr_b)); - OCL_CHECK(err, err = q.enqueueUnmapMemObject(buffer_result, ptr_result)); - OCL_CHECK(err, err = q.finish()); - - std::cout << "TEST " << (match ? "FAILED" : "PASSED") << std::endl; - return (match ? EXIT_FAILURE : EXIT_SUCCESS); -} - -#endif diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/src/host/cl_vadd.h b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/src/host/cl_vadd.h deleted file mode 100644 index 11622e7f27..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/src/host/cl_vadd.h +++ /dev/null @@ -1,39 +0,0 @@ -/******************************************************************************* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*******************************************************************************/ - - -#pragma once - -#include "vadd_include.h" - - -#ifndef DB_USE_XRT - -#define CL_HPP_CL_1_2_DEFAULT_BUILD -#define CL_HPP_TARGET_OPENCL_VERSION 120 -#define CL_HPP_MINIMUM_OPENCL_VERSION 120 -#define CL_HPP_ENABLE_PROGRAM_CONSTRUCTION_FROM_ARRAY_COMPATIBILITY 1 - -#include - -//Customized buffer allocation for 4K boundary alignment -template -struct aligned_allocator -{ - using value_type = T; - T* allocate(std::size_t num) - { - void* ptr = nullptr; - if (posix_memalign(&ptr,4096,num*sizeof(T))) - throw std::bad_alloc(); - return reinterpret_cast(ptr); - } - void deallocate(T* p, std::size_t num) - { - free(p); - } -}; - -#endif diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/src/host/xrt_host_vadd.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/src/host/xrt_host_vadd.cpp deleted file mode 100644 index 52779253bd..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/src/host/xrt_host_vadd.cpp +++ /dev/null @@ -1,134 +0,0 @@ -// Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -// SPDX-License-Identifier: MIT - -#include -#include -#include -#include -#include -#include -//#include -#include - -#include "vadd_include.h" - -#define TYPE_DATA int - -static const std::string error_message = - "Error: Result mismatch:\n" - "i = %d CPU result = %d Device result = %d\n"; - - -//static const char* STR_ERROR = "ERROR: "; -//static const char* STR_FAILED = "FAILED: "; -static const char* STR_PASSED = "PASSED: "; -static const char* STR_INFO = "INFO: "; -static const char* STR_USAGE = "USAGE: "; - - -#ifdef DB_USE_XRT - - -int main(int argc, char* argv[]) { - - // Check command line - if(argc < 2) { - std::cout << STR_USAGE << argv[0] <<" " << std::endl; - return EXIT_FAILURE; - } - - // Compute the size of arrays in bytes - size_t size_in_bytes = DATA_SIZE * sizeof(int); - std::cout << STR_INFO << "DATA size in words = " << DATA_SIZE << std::endl; - std::cout << STR_INFO << "DATA size in bytes = " << size_in_bytes << std::endl; - - // Loading the xclbin - char* xclbinFilename = argv[1]; - - //open the device and return its handle - unsigned int dev_index = 0; - auto my_device = xrt::device(dev_index); - std::cout << STR_PASSED << "auto my_device = xrt::device(" << dev_index << ")" << std::endl; - - //load the xclbin file from disk. This will return the UUID of the xclbin. - auto xclbin_uuid = my_device.load_xclbin(xclbinFilename); - std::cout << STR_PASSED << "auto xclbin_uuid = my_device.load_xclbin(" << xclbinFilename << ")" << std::endl; - - // Starting the (HLS) PL kernel - auto krnl = xrt::kernel(my_device, xclbin_uuid, "krnl_vadd:{krnl_vadd_1}"); - std::cout << STR_PASSED << "auto krnl = xrt::kernel(my_device, xclbin_uuid, \"krnl_vadd:{krnl_vadd_1}\")" << std::endl; - - std::cout << STR_INFO << "Allocate Buffers in Global Memory" << std::endl; - //The buffer type is default buffer object (bo) with host buffer and device buffer. The host buffer is allocated and managed by XRT. - auto bo0 = xrt::bo(my_device, size_in_bytes, XCL_BO_FLAGS_NONE, krnl.group_id(0)); //input 0 - auto bo1 = xrt::bo(my_device, size_in_bytes, XCL_BO_FLAGS_NONE, krnl.group_id(1)); //input 1 - auto bo2 = xrt::bo(my_device, size_in_bytes, XCL_BO_FLAGS_NONE, krnl.group_id(2)); //output - std::cout << STR_PASSED << "auto bo0 = xrt::bo(my_device, size_in_bytes, XCL_BO_FLAGS_NONE, krnl.group_id(0) (=" << krnl.group_id(0) << "))" << std::endl; - std::cout << STR_PASSED << "auto bo1 = xrt::bo(my_device, size_in_bytes, XCL_BO_FLAGS_NONE, krnl.group_id(1) (=" << krnl.group_id(1) << "))" << std::endl; - std::cout << STR_PASSED << "auto bo2 = xrt::bo(my_device, size_in_bytes, XCL_BO_FLAGS_NONE, krnl.group_id(2) (=" << krnl.group_id(2) << "))" << std::endl; - //Map the contents of the buffer object into host memory - auto bo0_map = bo0.map(); - auto bo1_map = bo1.map(); - auto bo2_map = bo2.map(); - std::fill(bo0_map, bo0_map + DATA_SIZE, 0); - std::fill(bo1_map, bo1_map + DATA_SIZE, 0); - std::fill(bo2_map, bo2_map + DATA_SIZE, 0); - std::cout << STR_PASSED << "auto bo0_map = bo0.map()" << std::endl; - std::cout << STR_PASSED << "auto bo1_map = bo1.map()" << std::endl; - std::cout << STR_PASSED << "auto bo2_map = bo2_map()" << std::endl; - - //setting input data - std::cout << STR_INFO << "Creating random input data" << std::endl; - FILE *fin1=fopen("vector_inputs.txt", "w"); - srand(time(NULL)); // Initialization, should only be called once. - for(int i = 0 ; i< DATA_SIZE; i++) - { - unsigned short int r1 = (unsigned short int) rand(); // Returns a pseudo-random integer between 0 and RAND_MAX. - unsigned short int r2 = (unsigned short int) rand(); // Returns a pseudo-random integer between 0 and RAND_MAX. - bo0_map[i] = r1; - bo1_map[i] = r2; - fprintf(fin1, "%10d\t%10d\n", r1, r2); - } - fclose(fin1); - - // Synchronize buffer content with device side - std::cout << STR_INFO << "synchronize input buffer data to device global memory" << std::endl; - bo0.sync(XCL_BO_SYNC_BO_TO_DEVICE); - std::cout << STR_PASSED << "bo0.sync(XCL_BO_SYNC_BO_TO_DEVICE)" << std::endl; - bo1.sync(XCL_BO_SYNC_BO_TO_DEVICE); - std::cout << STR_PASSED << "bo1.sync(XCL_BO_SYNC_BO_TO_DEVICE)" << std::endl; - - std::cout << STR_INFO << "Execution of the kernel" << std::endl; - auto run = krnl(bo0, bo1, bo2, DATA_SIZE); - // Waiting for all kernels to end - std::cout << std::endl << STR_INFO << "Waiting for kernels to end..." << std::endl << std::endl; - run.wait(); - std::cout << STR_PASSED << "run.wait()" << std::endl; - - // Retrieving the results - bo2.sync(XCL_BO_SYNC_BO_FROM_DEVICE); - std::cout << STR_PASSED << "bo2.sync(XCL_BO_SYNC_BO_FROM_DEVICE)" << std::endl; - - // Verify the result - std::cout << STR_INFO << "Checking the results" << std::endl; - FILE *fin2=fopen("vector_out.txt", "w"); - int match = 0; - for (int i = 0; i < DATA_SIZE; i++) - { - int host_result = bo0_map[i] + bo1_map[i]; - fprintf(fin2, "%10d\t%10d\n", host_result, bo2_map[i]); - if (bo2_map[i] != host_result) - { - printf(error_message.c_str(), i, host_result, bo2_map[i]); - match = 1; - break; - } - } - fclose(fin2); - - std::cout << "TEST " << (match ? "FAILED" : "PASSED") << std::endl; - return (match ? EXIT_FAILURE : EXIT_SUCCESS); - -} - -#endif diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/vect_check_res.m b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/vect_check_res.m deleted file mode 100644 index e161faac0d..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/8_vect_add/vect_check_res.m +++ /dev/null @@ -1,31 +0,0 @@ -% Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -% SPDX-License-Identifier: MIT - -%% -clear all -close all -clc - -%% data - -% load input data -I = load('vector_inputs.txt'); - -% load output data generated by target board -O = load('vector_out.txt'); - -% reference result computed by MATLAB -R = I(:,1) + I(:,2); - -%% check results - -diff_R_O1 = abs(diff(R-O(:,1))); %ref vs. ARM CPU -diff_R_O2 = abs(diff(R-O(:,2))); %ref vs. PL kernel -diff_O1_O2 = abs(diff(O(:,1)-O(:,2))); % ARM CPU vs. PL kernel - -sum_abs_err = sum(diff_R_O1(:)) + sum(diff_R_O2(:)) + sum(diff_O1_O2(:)) - - -figure; plot(diff_O1_O2); grid; title 'diff O1 vs O2' -figure; plot(diff_R_O2); grid; title 'diff M vs O2' -figure; plot(diff_R_O1); grid; title 'diff M vs O1' diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/Makefile b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/Makefile deleted file mode 100644 index aa85fcc0fe..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/Makefile +++ /dev/null @@ -1,78 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -SHELL := /bin/bash - -.PHONY: help hls_kernels hls_clean vck190_all vck190_clean all clean sd_card run show_dir - -#======================================================== -# Source directories -# ========================================================= -RELATIVE_PROJECT_DIR := ./ -PROJECT_DIR := $(shell readlink -f $(RELATIVE_PROJECT_DIR)) - -PROJECT_PL_DIR := $(PROJECT_DIR)/make-flow/vck190/mmult_kernels -PROJECT_PS_DIR := $(PROJECT_DIR)/make-flow/vck190/mmult -PROJECT_HWLINK_DIR := $(PROJECT_DIR)/make-flow/vck190/mmult_system_hw_link -PROJECT_SYSTEM_DIR := $(PROJECT_DIR)/make-flow/vck190/mmult_system - -show_dir: - -@echo " " - -@echo " " - -@echo "from $(realpath .)" - -@echo "RELATIVE PROJECT DIR is: $(RELATIVE_PROJECT_DIR)" - -@echo "CURRENT PROJECT DIR is: $(PROJECT_DIR)" - -@echo "PL KERNELS PROJECT DIR is: $(PROJECT_PL_DIR)" - -@echo "PS ARM HOST PROJECT DIR is: $(PROJECT_PS_DIR)" - -@echo "HW LINK PROJECT DIR is: $(PROJECT_HWLINK_DIR)" - -@echo "SYSTEM PROJECT DIR is: $(PROJECT_SYSTEM_DIR)" - -@echo " " - -@echo " " - - -EMBEDDED_PACKAGE_OUT = $(PROJECT_SYSTEM_DIR)/Hardware/package -EMBEDDED_EXEC_SCRIPT = $(PROJECT_SYSTEM_DIR)/Hardware/embedded_exec.sh -PACKAGE_FILES += $(EMBEDDED_EXEC_SCRIPT) -SD_FILES_WITH_PREFIX = $(foreach sd_file,$(PACKAGE_FILES),--package.sd_file $(sd_file)) - -# ======================================================= -# global variables for this tutorial -# ======================================================= -#RELEASE=2022.2 -RELEASE=2025.1 -BOARD=vck190 -BASE_NUM=202510_1 -#BASE_NUM=202220_1 - -# Platform Selection... -VERSAL_VITIS_PLATFORM = xilinx_${BOARD}\_base_${BASE_NUM} -VITIS_PLATFORM_DIR = ${PLATFORM_REPO_PATHS}/${VERSAL_VITIS_PLATFORM} -export VITIS_PLATFORM_XPFM = ${VITIS_PLATFORM_DIR}/${VERSAL_VITIS_PLATFORM}.xpfm -# Set SysRoot, RootFS and Image -export VITIS_SYSROOTS = ${COMMON_IMAGE_VERSAL}/sysroots/cortexa72-cortexa53-amd-linux -export SDKTARGETSYSROOT = ${VITIS_SYSROOTS} -export KERNEL_IMAGE = ${COMMON_IMAGE_VERSAL}/Image -export ROOTFS = ${COMMON_IMAGE_VERSAL}/rootfs.ext4 -export XLNX_VERSAL = ${COMMON_IMAGE_VERSAL} -export PLATFORM = ${VITIS_PLATFORM_XPFM} - - -hls_clean: - rm -rf *_prj *.log *~ - -hls_kernels: - vitis-run --mode hls --tcl ./run_matrix_mult_script_vck190.tcl - -# REMEMBER THAT VCK190 NEEDS DIFFERENT ENV FROM ZCU102 -vck190_all: - $(MAKE) -C ./make-flow/vck190 all - -vck190_clean: - $(MAKE) -C ./make-flow/vck190 clean - -run: all -sd_card: all - -all: show_dir vck190_all - -clean: show_dir hls_clean vck190_clean diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/check_mmult_results.m b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/check_mmult_results.m deleted file mode 100644 index 28f718e0cb..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/check_mmult_results.m +++ /dev/null @@ -1,68 +0,0 @@ -% Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -% SPDX-License-Identifier: MIT - -%% clean workspace - -clear all; -close all; -clc; - -%% memory allocation - -DIM=32; -matOp1 = zeros([DIM, DIM]); -matOp2 = zeros([DIM, DIM]); -matRef = zeros([DIM, DIM]); - -%% reference matrices with MATLAB - -for r = 0 : DIM -1 - for c = 0 : DIM -1 - r1 = r + c; - r2 = r * c; - matOp1(r+1, c+1) = r1; - matOp2(r+1, c+1) = r2; - end -end -matRef = matOp1 * matOp2; - -%% load files generated by ARM on ZCU102 - -I = load('matrix_inputs.txt'); -Oif = load('matrix_out_i_f.txt'); -Obufs = load('matrix_out_bufs.txt'); - -%reshape data files -in1=I(:,1); -in2=I(:,2); -m1 = reshape(in1, [32,32])'; -m2 = reshape(in2, [32,32])'; -m3 = m1 * m2; % expected result - -%% check differences ARM vs. MATLAB - -diff1 = abs(m1 - matOp1); -sum_abs_diff1 = sum(diff1(:)) -diff2 = abs(m2 - matOp2); -sum_abs_diff2 = sum(diff2(:)) -diff3 = abs(m3 - matRef); -sum_abs_diff3 = sum(diff3(:)) - -%% -Oif_c1 = Oif(:, 1); -mat_Oif_c1 = reshape(Oif_c1, [DIM, DIM])'; -Obufs_c2 = Obufs(:, 2); -mat_Obufs_c2 = reshape(Obufs_c2, [DIM, DIM])'; -diff31 = abs(mat_Oif_c1 - mat_Obufs_c2); -sum_abs_diff31 = sum(diff31(:)) - -Oif_c2 = Oif(:, 2); -mat_Oif_c2 = reshape(Oif_c2, [DIM, DIM])'; -diff32 = abs(m3 - mat_Oif_c2); -sum_abs_diff32 = sum(diff32(:)) - - -Obufs_c1 = Obufs(:, 1); -mat_Obufs_c1 = reshape(Obufs_c1, [DIM, DIM])'; -diff12 = abs(mat_Obufs_c1 - mat_Obufs_c2); -sum_abs_diff12 = sum(diff12(:)) diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/description.json b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/description.json deleted file mode 100644 index 671a9afa7f..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/description.json +++ /dev/null @@ -1,39 +0,0 @@ -{ - "name": "Developer_Contributed-03-HLS_Code_Optimization--matrix_mult_v", - "description": "03-HLS_Code_Optimization--matrix_mult", - "gui": "false", - "flow": "versal", - - "platform_allowlist": [ "vck190"], - "platform_blocklist": [], - - "testinfo": { - "test_name": "CTB_03-HLS_versal", - "jobs": [ - { - "max_memory_MB": 65536 - } - ], - - "targets": [ - "vitis_hw_build", - "vitis_hw_run" - ], - "make_options": [ - "VITIS_PLATFORM_XPFM='${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm'", - "EMBEDDED_PACKAGE_OUT=./make-flow/vck190/mmult_system/Hardware/package", - "EMBEDDED_EXEC_SCRIPT=./embedded_exec.sh" - ], - "custom_build_target": { - "all": "all", - "hw": "sd_card" - }, - "custom_board_target": "run_test", - "tasks": { - "build": { - "pre_exec": "./env_setup_versal.sh" - } - } - - } -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/make-flow/vck190/Makefile b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/make-flow/vck190/Makefile deleted file mode 100644 index b5584a3817..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/make-flow/vck190/Makefile +++ /dev/null @@ -1,86 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -SHELL := /bin/bash - -PHONY = help all clean show_dir -PHONY += kernels hw_link system host vck190_build vck190_prepare -.PHONY: $(PHONY) - - - -#======================================================== -# Source directories -# ========================================================= -RELATIVE_PROJECT_DIR := ./ - -#absolute directory -PROJECT_DIR := $(shell readlink -f $(RELATIVE_PROJECT_DIR)) -PROJECT_PS_DIR := $(PROJECT_DIR)/mmult -PROJECT_PL_DIR := $(PROJECT_PS_DIR)/mmult_kernels -PROJECT_HWLINK_DIR := $(PROJECT_PS_DIR)/mmult_system_hw_link -PROJECT_SYSTEM_DIR := $(PROJECT_PS_DIR)/mmult_system - -show_dir: - -@echo " " - -@echo " " - -@echo "from $(realpath .)" - -@echo "RELATIVE PROJECT DIR is: $(RELATIVE_PROJECT_DIR)" - -@echo "CURRENT PROJECT DIR is: $(PROJECT_DIR)" - -@echo "PL KERNELS PROJECT DIR is: $(PROJECT_PL_DIR)" - -@echo "PS ARM HOST PROJECT DIR is: $(PROJECT_PS_DIR)" - -@echo "HW LINK PROJECT DIR is: $(PROJECT_HWLINK_DIR)" - -@echo "SYSTEM PROJECT DIR is: $(PROJECT_SYSTEM_DIR)" - -@echo " " - -@echo " " - - - - - -all: show_dir vck190_prepare vck190_build - -vck190_build: - $(MAKE) kernels - $(MAKE) hw_link - $(MAKE) host - $(MAKE) system - - -clean: - $(MAKE) -C mmult_kernels/Hardware clean - $(MAKE) -C mmult_system_hw_link/Hardware clean - $(MAKE) -C mmult_system/Hardware clean - $(MAKE) -C mmult/Hardware clean - rm -rf ./mmult/src - rm -rf ./mmult_system/src - rm -rf ./mmult_kernels/src - rm -rf ./mmult_system_hw_link/src - rm -f ./muult_system/Hardware/*.log - rm -f ./mmult_system/Hardware/*~ - rm -rf ./mmult_system/Hardware/.ipcache - rm -rf ./mmult_system_hw_link/Hardware/.ipcache - - -vck190_prepare: - mkdir -p $(realpath ../vck190/mmult)/src - mkdir -p $(realpath ../vck190/mmult_kernels)/src - cp -f $(realpath ../../vitis_src)/xrt_mmult_test.cpp $(realpath ./mmult)/src/ - cp -f $(realpath ../../src)/mmult.h $(realpath ./mmult)/src/ - cp -f $(realpath ../../src)/*accel.cpp $(realpath ./mmult_kernels)/src/ - cp -f $(realpath ../../src)/mmult.h $(realpath ./mmult_kernels)/src - cp -f $(realpath ../../vitis_src)/mm2s.cpp $(realpath ./mmult_kernels)/src/ - cp -f $(realpath ../../vitis_src)/s2mm.cpp $(realpath ./mmult_kernels)/src/ - cp -f $(realpath ../../vitis_src)/system.cfg $(realpath ./mmult_system_hw_link)/ - -kernels: - $(MAKE) -C mmult_kernels/Hardware all - -hw_link: - $(MAKE) -C mmult_system_hw_link/Hardware all - -system: - $(MAKE) -C mmult_system/Hardware all - -host: - $(MAKE) -C mmult/Hardware all diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/make-flow/vck190/mmult/Hardware/makefile b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/make-flow/vck190/mmult/Hardware/makefile deleted file mode 100644 index 3a286c2814..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/make-flow/vck190/mmult/Hardware/makefile +++ /dev/null @@ -1,74 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -#relative directory -RELATIVE_PROJECT_DIR := ../ - -#absolute directory -PROJECT_DIR := $(shell readlink -f $(RELATIVE_PROJECT_DIR)) -PROJECT_PS_DIR := $(PROJECT_DIR) -PROJECT_PL_DIR := $(PROJECT_PS_DIR)/../mmult_kernels -PROJECT_HWLINK_DIR := $(PROJECT_PS_DIR)/../mmult_system_hw_link -PROJECT_SYSTEM_DIR := $(PROJECT_PS_DIR)/../mmult_system - -show_dir: - -@echo " " - -@echo " " - -@echo "from $(realpath .)" - -@echo "RELATIVE PROJECT DIR is: $(RELATIVE_PROJECT_DIR)" - -@echo "CURRENT PROJECT DIR is: $(PROJECT_DIR)" - -@echo "PL KERNELS PROJECT DIR is: $(PROJECT_PL_DIR)" - -@echo "PS ARM HOST PROJECT DIR is: $(PROJECT_PS_DIR)" - -@echo "HW LINK PROJECT DIR is: $(PROJECT_HWLINK_DIR)" - -@echo "SYSTEM PROJECT DIR is: $(PROJECT_SYSTEM_DIR)" - -@echo " " - -@echo " " - -BOARD=vck190 - -# compiler tools -HOST_CXX ?= $(XILINX_VITIS)/gnu/aarch64/lin/aarch64-linux/bin/aarch64-linux-gnu-g++ -RM = rm -f -RMDIR = rm -rf - -# compiler flags -CXXFLAGS = -std=c++17 -DVITIS_PLATFORM=$(VERSAL_VITIS_PLATFORM) -D__USE_XOPEN2K8 -I$(XILINX_HLS)/include -I$(COMMON_IMAGE_VERSAL)/sysroots/cortexa72-cortexa53-amd-linux/usr/include/xrt -O2 -g -Wall -c -fmessage-length=0 --sysroot=$(COMMON_IMAGE_VERSAL)/sysroots/cortexa72-cortexa53-amd-linux - -LDFLAGS = -lxilinxopencl -lxrt_core -lxrt_coreutil -lpthread -lrt -ldl -lcrypt -lstdc++ -L$(COMMON_IMAGE_VERSAL)/sysroots/cortexa72-cortexa53-amd-linux/usr/lib --sysroot=$(COMMON_IMAGE_VERSAL)/sysroots/cortexa72-cortexa53-amd-linux - - -# -# host files -# - -HOST_OBJECTS += $(PROJECT_PS_DIR)/src/xrt_mmult_test.o - -HOST_EXE = $(PROJECT_PS_DIR)/Hardware/mmult - - -# -# primary build targets -# - -.PHONY: all clean -all: show_dir $(HOST_EXE) - -clean: - -$(RM) $(HOST_EXE) $(HOST_OBJECTS) *.log guidance.* $(PROJECT_PS_DIR)/src/*.o *~ $(PROJECT_PS_DIR)/Hardware/src/*.o - -.PHONY: incremental -incremental: all - - -nothing: - -# -# host rules -# - -$(PROJECT_PS_DIR)/src/xrt_mmult_test.o: $(PROJECT_PS_DIR)/src/xrt_mmult_test.cpp $(PROJECT_PS_DIR)/src/mmult.h - -@mkdir -p $(@D) - $(HOST_CXX) $(CXXFLAGS) -o "$@" "$<" - -$(HOST_EXE): $(HOST_OBJECTS) - $(HOST_CXX) -o "$@" $(+) $(LDFLAGS) diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/make-flow/vck190/mmult_kernels/Hardware/HLS_accel-compile.cfg b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/make-flow/vck190/mmult_kernels/Hardware/HLS_accel-compile.cfg deleted file mode 100644 index 5167675bd8..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/make-flow/vck190/mmult_kernels/Hardware/HLS_accel-compile.cfg +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -#platform=$VITIS_PLATFORM_PATH -save-temps=1 -kernel=HLS_accel -messageDb=build/HLS_accel.mdb -temp_dir=build -report_dir=build/reports -log_dir=build/logs - -[advanced] -misc=solution_name=HLS_accel diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/make-flow/vck190/mmult_kernels/Hardware/makefile b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/make-flow/vck190/mmult_kernels/Hardware/makefile deleted file mode 100644 index e4842c036b..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/make-flow/vck190/mmult_kernels/Hardware/makefile +++ /dev/null @@ -1,90 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -#relative directory -RELATIVE_PROJECT_DIR := ../ - -#absolute directory -PROJECT_DIR := $(shell readlink -f $(RELATIVE_PROJECT_DIR)) -PROJECT_PL_DIR := $(PROJECT_DIR) -PROJECT_PS_DIR = $(PROJECT_PL_DIR)/../mmult -PROJECT_SYSTEM_DIR = $(PROJECT_PL_DIR)/../mmult_system -PROJECT_HWLINK_DIR = $(PROJECT_PL_DIR)/../mmult_system_hw_link - -show_dir: - -@echo " " - -@echo " " - -@echo "from $(realpath .)" - -@echo "RELATIVE PROJECT DIR is: $(RELATIVE_PROJECT_DIR)" - -@echo "CURRENT PROJECT DIR is: $(PROJECT_DIR)" - -@echo "PL KERNELS PROJECT DIR is: $(PROJECT_PL_DIR)" - -@echo "PS ARM HOST PROJECT DIR is: $(PROJECT_PS_DIR)" - -@echo "HW LINK PROJECT DIR is: $(PROJECT_HWLINK_DIR)" - -@echo "SYSTEM PROJECT DIR is: $(PROJECT_SYSTEM_DIR)" - -@echo " " - -@echo " " - - -BOARD=vck190 - -# compiler tools -VPP ?= ${XILINX_VITIS}/bin/v++ -RM = rm -f -RMDIR = rm -rf - -TARGET = hw -VPP_OPTS = --target $(TARGET) - -# -# Hw kernel files -# - - -BUILD_SUBDIRS = $(PROJECT_PL_DIR)/Hardware/build -HW_KERNEL_OBJS += $(PROJECT_PL_DIR)/Hardware/build/HLS_accel.xo -SRC_KERNEL_OBJS += $(PROJECT_PL_DIR)/Hardware/build/HLS_accel.xo -HW_KERNEL_OBJS += $(PROJECT_PL_DIR)/Hardware/build/mm2s.xo -SRC_KERNEL_OBJS += $(PROJECT_PL_DIR)/Hardware/build/mm2s.xo -HW_KERNEL_OBJS += $(PROJECT_PL_DIR)/Hardware/build/s2mm.xo -SRC_KERNEL_OBJS += $(PROJECT_PL_DIR)/Hardware/build/s2mm.xo - -ALL_MESSAGE_FILES = $(subst .xo,.o,.mdb,$(SRC_KERNEL_OBJS)) - -# -# primary build targets -# - -.PHONY: all clean -all: show_dir $(HW_KERNEL_OBJS) - - -clean: - -$(RM) $(SRC_KERNEL_OBJS) $(ALL_MESSAGE_FILES) *.log *summary* - -$(RMDIR) $(BUILD_SUBDIRS) - -$(RMDIR) .Xil - -.PHONY: incremental -incremental: all - - -nothing: - -# -# Hw Kernels compile; -# - -$(PROJECT_PL_DIR)/Hardware/build/HLS_accel.xo: $(PROJECT_PL_DIR)/src/mmult_accel.cpp $(PROJECT_PL_DIR)/src/mmult.h $(PROJECT_PL_DIR)/Hardware/HLS_accel-compile.cfg - -@mkdir -p $(@D) - -@$(RM) $@ - $(VPP) $(VPP_OPTS) --compile -I"$( binary_container_1.xsa.sh - $(VPP_LINKER) $(VPP_OPTS) --link --config $(PROJECT_HWLINK_DIR)/system.cfg --platform $(VITIS_PLATFORM_XPFM) --config $(PROJECT_HWLINK_DIR)/Hardware/binary_container_1-link.cfg -o"$@" $(BINARY_CONTAINER_1_OBJS) diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/make-flow/vck190/mmult_system_hw_link/system.cfg b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/make-flow/vck190/mmult_system_hw_link/system.cfg deleted file mode 100644 index b167917ade..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/make-flow/vck190/mmult_system_hw_link/system.cfg +++ /dev/null @@ -1,13 +0,0 @@ -# -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -# - -[connectivity] -##comment next 3 lines if you use this file with the Vitis GUI -#nk=mm2s:1 -#nk=s2mm:1 -#nk=HLS_accel:1 - -sc=mm2s_1.s:HLS_accel_1.INPUT_STREAM -sc=HLS_accel_1.OUTPUT_STREAM:s2mm_1.s diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/run_matrix_mult_vck190_script.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/run_matrix_mult_vck190_script.tcl deleted file mode 100644 index cfc2c7b223..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/run_matrix_mult_vck190_script.tcl +++ /dev/null @@ -1,70 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -puts "\n" -puts "************************************************************************" -puts "* EXAMPLE 9) 32x32 REAL MATRIX MULTIPLICATION DEMO" -puts "************************************************************************" -puts "\n" - - -# STANDALONE MATRIX MULTIPLIER HLS PROJECT -########################################################################### - -open_project hls_mmult_prj -set_top standalone_mmult -add_files src/mmult_accel.cpp -add_files -tb src/mmult_test.cpp -open_solution "solution1" -flow_target vivado -set_part {xcvc1902-vsva2197-2MP-e-S} -create_clock -period 3.0 -name default -#config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 0.5 -csim_design -clean -csynth_design - -open_solution "solution2" -flow_target vivado -set_part {xcvc1902-vsva2197-2MP-e-S} -create_clock -period 3.0 -name default -#config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 0.5 -set_directive_pipeline -II 1 "mmult_hw/L2" -csynth_design - -open_solution "solution3" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 3.0 -name default -#config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 0.5 -set_directive_pipeline -II 1 "mmult_hw/L2" -set_directive_array_partition -type block -factor 16 -dim 2 "mmult_hw" a -set_directive_array_partition -type block -factor 16 -dim 1 "mmult_hw" b -csynth_design -#cosim_design - -close_project - - -# WRAPPED AXI4-STREAM MATRIX MULTIPLIER HLS PROJECT -########################################################################### - -open_project hls_wrapped_mmult_prj -set_top HLS_accel -add_files src/mmult_accel.cpp -cflags "-DDB_DEBUG" -add_files -tb src/mmult_test.cpp -cflags "-DDB_DEBUG" -open_solution "solution0" -flow_target vivado -set_part {xcvc1902-vsva2197-2MP-e-S} -create_clock -period 3.0 -name default -set_clock_uncertainty 0.5 -set_directive_inline "mmult_hw" -set_directive_pipeline -II 1 "mmult_hw/L2" -set_directive_array_partition -type block -factor 16 -dim 2 "mmult_hw" a -set_directive_array_partition -type block -factor 16 -dim 1 "mmult_hw" b -csim_design -clean -#-setup -csynth_design -#export_design -evaluate verilog -format ip_catalog -close_project diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/src/mmult.h b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/src/mmult.h deleted file mode 100644 index a482ecc41e..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/src/mmult.h +++ /dev/null @@ -1,194 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - - -/* - void example(hls::stream< ap_axis<32,2,5,6> > &A, - hls::stream< ap_axis<32,2,5,6> > &B) -{ - #pragma HLS INTERFACE axis port=A - #pragma HLS INTERFACE axis port=B - ap_axis<32,2,5,6> tmp; - while(1) - { - A.read(tmp); - tmp.data = tmp.data.to_int() + 5; - B.write(tmp); - if(tmp.last) - { - break; - } - } -*/ - -#include -#include "ap_axi_sdata.h" -#include "hls_stream.h" - -const int DIM = 32; -const int SIZE = (DIM*DIM); - -const int U =2; -const int TI=5; -const int TD=6; - -typedef float T; -typedef ap_axis AXI_VAL; - - - -// function prototypes -void standalone_mmult (float A[DIM][DIM], float B[DIM][DIM], float C[DIM][DIM]); - -int HLS_accel (hls::stream &INPUT_STREAM, hls::stream &OUTPUT_STREAM); - -/* ****************************** C++ TEMPLATES ************************************** */ - -// reference function -template -void matrix_multiply_ref(T a[DIM][DIM], T b[DIM][DIM], T out[DIM][DIM]) -{ - // matrix multiplication of a A*B matrix - for (int ia = 0; ia < DIM; ++ia) - for (int ib = 0; ib < DIM; ++ib) - { - float sum = 0; - for (int id = 0; id < DIM; ++id) - sum += a[ia][id] * b[id][ib]; - out[ia][ib] = sum; - } - return; -} - -// -------------------------------------------------------- -// function to be accelerated in HW -template -void mmult_hw(T a[DIM][DIM], T b[DIM][DIM], T out[DIM][DIM]) -{ - - int const FACTOR = DIM/2; - #pragma HLS INLINE - //#pragma HLS array_partition variable=a block factor=FACTOR dim=2 - //#pragma HLS array_partition variable=b block factor=FACTOR dim=1 - - // matrix multiplication of a A*B matrix - L1:for (int ia = 0; ia < DIM; ++ia) - L2:for (int ib = 0; ib < DIM; ++ib) - { - //#pragma HLS PIPELINE II=1 - T sum = 0; - L3:for (int id = 0; id < DIM; ++id) - sum += a[ia][id] * b[id][ib]; - out[ia][ib] = sum; - } - return; -} - -// -------------------------------------------------------- -// functions to insert and extract elements from an axi stream -// includes conversion to correct data type - -template -T pop_stream(hls::stream< ap_axis> &inp_stream) -{ -#pragma HLS INLINE - - ap_axis e; - inp_stream.read(e); - - assert(sizeof(T) == sizeof(int)); - union - { - int ival; - T oval; - } converter; - converter.ival = e.data; - T ret = converter.oval; - - ap_uint strb = e.strb; - ap_uint keep = e.keep; - ap_uint user = e.user; - ap_uint<1> last = e.last; - //ap_uint id = e.id; - //ap_uint dest = e.dest; - - return ret; -} - -template -void push_stream(T data, bool last, hls::stream< ap_axis> &out_stream) -{ -#pragma HLS INLINE - - ap_axis e; - - assert(sizeof(T) == sizeof(int)); - union - { - int oval; - T ival; - } converter; - converter.ival = data; - e.data = converter.oval; - - // set it to sizeof(T) ones - e.strb = 1; //-1; - e.keep = 1; //15; - e.user = 1; //0; - e.last = last ? 1 : 0; - //e.id = 0; - //e.dest = 0; - - out_stream.write(e); - -} - -// -------------------------------------------------------------------- -// function to be accelerated in HW wrapped with AXI4-Stream interface - -template -int wrapped_mmult_hw (hls::stream> &inp_stream, hls::stream> &out_stream) -{ - -#pragma HLS INLINE - - T a[DIM][DIM]; - T b[DIM][DIM]; - T out[DIM][DIM]; - - assert(sizeof(T)*8 == 32); - - // stream in first matrix - for(int i=0; i(inp_stream); - } - - // stream in second matrix - for(int i=0; i(inp_stream); - } - - // do HW multiplication - mmult_hw(a,b,out); - - // stream out result matrix - for(int i=0; i(out[i][j], last, out_stream); - } - return 0; - -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/src/mmult_accel.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/src/mmult_accel.cpp deleted file mode 100644 index 149de9e9e7..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/src/mmult_accel.cpp +++ /dev/null @@ -1,33 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#include -#include - -#include "mmult.h" - - -// THIS IS THE TOP LEVEL DESIGN THAT WILL BE SYNTHESIZED -#define MCR_SIZE 1024 - - -void standalone_mmult (float A[32][32], float B[32][32], float C[32][32]) -{ - - mmult_hw (A, B, C); - -} - - -int HLS_accel (hls::stream &INPUT_STREAM, hls::stream &OUTPUT_STREAM) -{ -#pragma HLS INTERFACE s_axilite port=return bundle=CONTROL_BUS -#pragma HLS INTERFACE axis port=OUTPUT_STREAM -#pragma HLS INTERFACE axis port=INPUT_STREAM - - int ret = wrapped_mmult_hw (INPUT_STREAM, OUTPUT_STREAM); - - return ret; -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/src/mmult_test.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/src/mmult_test.cpp deleted file mode 100644 index 73ec152101..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/src/mmult_test.cpp +++ /dev/null @@ -1,165 +0,0 @@ -/* -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -*/ - -#include -#include - -#include "mmult.h" - -void mmult_sw(T a[DIM][DIM], T b[DIM][DIM], T out[DIM][DIM]) -{ - // matrix multiplication of a A*B matrix - for (int ia = 0; ia < DIM; ++ia) - for (int ib = 0; ib < DIM; ++ib) - { - - float sum = 0; - - for (int id = 0; id < DIM; ++id) - - sum += a[ia][id] * b[id][ib]; - - out[ia][ib] = sum; - } -} - - -#ifdef DB_DEBUG - - -// test the functions -template -int test_matrix_mult(void) -{ - int i,j, err; - - T matOp1[DIM][DIM]; - T matOp2[DIM][DIM]; - T matMult_sw[DIM][DIM]; - T matMult_hw[DIM][DIM]; - int SIZE = DIM*DIM; - - /** Matrix Initiation */ - for(i = 0; i inp_stream, out_stream; - - assert(sizeof(T)*8 == 32); - // stream in the first input matrix - for(int i=0; i(matOp1[i][j],0, inp_stream); - } - // stream in the second input matrix - for(int i=0; i(matOp2[i][j],k == (SIZE-1), inp_stream); - } - - - //call the DUT - //wrapped_mmult_hw(inp_stream, out_stream); - int res= HLS_accel(inp_stream, out_stream); - - - // extract the output matrix from the out stream - for(int i=0; i(out_stream); - } - - - /* reference Matrix Multiplication */ - matrix_multiply_ref(matOp1, matOp2, matMult_sw); - - /** Matrix comparison */ - err = 0; - for (i = 0; (i(); - return ret_val; - -} - -#else - -int main(void) -{ - - int ret_val = 0; - - int i,j, err; - - T matOp1[DIM][DIM]; - T matOp2[DIM][DIM]; - T matMult_sw[DIM][DIM]; - T matMult_hw[DIM][DIM]; - - /** Matrix Initiation */ - for(i = 0; i -#include -#include - -#define WORD_SIZE 32 - -extern "C" { - -void mm2s(ap_int* mem, hls::stream, 0, 0, 0>>& s, int size) { -#pragma HLS INTERFACE m_axi port=mem offset=slave bundle=gmem - -#pragma HLS INTERFACE axis port=s - -#pragma HLS INTERFACE s_axilite port=mem bundle=control -#pragma HLS INTERFACE s_axilite port=size bundle=control -#pragma HLS INTERFACE s_axilite port=return bundle=control - - for(int i = 0; i < size; i++) { -#pragma HLS PIPELINE II=1 - hls::axis, 0, 0, 0> x; - x.data = mem[i]; - x.keep = -1; - s.write(x); - } - -} - -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/vitis_src/s2mm.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/vitis_src/s2mm.cpp deleted file mode 100644 index 80012ae353..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/vitis_src/s2mm.cpp +++ /dev/null @@ -1,31 +0,0 @@ -// Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -// SPDX-License-Identifier: MIT - -#include -#include -#include - -#define WORD_SIZE 32 - -extern "C" { - -//void s2mm(ap_int* mem, hls::stream >& s, int size) { -void s2mm(ap_int* mem, hls::stream >& s, int size) { -#pragma HLS INTERFACE m_axi port=mem offset=slave bundle=gmem - -#pragma HLS interface axis port=s - -#pragma HLS INTERFACE s_axilite port=mem bundle=control -#pragma HLS INTERFACE s_axilite port=size bundle=control -#pragma HLS interface s_axilite port=return bundle=control - - for(int i = 0; i < size; i++) { -#pragma HLS PIPELINE II=1 - //qdma_axis x = s.read(); - ap_axis x = s.read(); - mem[i] = x.data; - } - -} - -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/vitis_src/system.cfg b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/vitis_src/system.cfg deleted file mode 100644 index b167917ade..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/vitis_src/system.cfg +++ /dev/null @@ -1,13 +0,0 @@ -# -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT -# - -[connectivity] -##comment next 3 lines if you use this file with the Vitis GUI -#nk=mm2s:1 -#nk=s2mm:1 -#nk=HLS_accel:1 - -sc=mm2s_1.s:HLS_accel_1.INPUT_STREAM -sc=HLS_accel_1.OUTPUT_STREAM:s2mm_1.s diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/vitis_src/xrt_mmult_test.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/vitis_src/xrt_mmult_test.cpp deleted file mode 100644 index 9449739796..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_v/vitis_src/xrt_mmult_test.cpp +++ /dev/null @@ -1,274 +0,0 @@ -// Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -// SPDX-License-Identifier: MIT - -#include -#include -#include -#include -#include -#include -#include -#include -#include - -#include "mmult.h" - -#define TYPE_DATA signed int - -static const char* STR_ERROR = "ERROR: "; -static const char* STR_FAILED = "FAILED: "; -static const char* STR_PASSED = "PASSED: "; -static const char* STR_INFO = "INFO: "; -static const char* STR_USAGE = "USAGE: "; - -/* -static const char* STR_CHRONO = "CHRONO: "; -static const int CHRONO_CAL_ITERATIONS = 2000; - -void chrono_spend( - int chrono_diff, - const char* str -) { - if(chrono_diff >= 10000) { - std::cout << STR_CHRONO << (int) (chrono_diff / 1000) << "ms -> " << str << std::endl; - } else { - std::cout << STR_CHRONO << (int) (chrono_diff) << "us -> " << str << std::endl; - } -} -*/ - -int main(int argc, char* argv[]) { - - // Check command line - if(argc < 2) { - std::cout << STR_USAGE << argv[0] <<" " << std::endl; - return EXIT_FAILURE; - } - - int wSizeIn = 2*SIZE; - int bSizeIn = wSizeIn * sizeof(TYPE_DATA); - int wSizeOut = SIZE; - int bSizeOut = wSizeOut * sizeof(TYPE_DATA); - -// std::cout << STR_INFO << "ARM sizeof(char) = " << sizeof(char) << std::endl; -// std::cout << STR_INFO << "ARM sizeof(short int) = " << sizeof(short int) << std::endl; -// std::cout << STR_INFO << "ARM sizeof(int) = " << sizeof(int) << std::endl; -// std::cout << STR_INFO << "ARM sizeof(long int) = " << sizeof(long int) << std::endl; -// std::cout << STR_INFO << "ARM sizeof(long long int) = " << sizeof(long long int) << std::endl; -// std::cout << STR_INFO << "ARM sizeof(float) = " << sizeof(float) << std::endl; -// std::cout << STR_INFO << "ARM sizeof(double) = " << sizeof(double) << std::endl; -/* - INFO: ARM sizeof(char) = 1 - INFO: ARM sizeof(short int) = 2 - INFO: ARM sizeof(int) = 4 - INFO: ARM sizeof(long int) = 8 - INFO: ARM sizeof(long long int) = 8 - INFO: ARM sizeof(float) = 4 - INFO: ARM sizeof(double) = 8 -*/ - std::cout << STR_INFO << "wSizeIn = " << wSizeIn << std::endl; - std::cout << STR_INFO << "wSizeOut = " << wSizeOut << std::endl; - std::cout << STR_INFO << "bSizeIn = " << bSizeIn << std::endl; - std::cout << STR_INFO << "bSizeOut = " << bSizeOut << std::endl; - - /* - // Chrono Timer Calibration - auto chrono_t0 = std::chrono::high_resolution_clock::now(); - auto chrono_t1 = std::chrono::high_resolution_clock::now(); - std::chrono::duration chrono_diff(0); - std::chrono::duration chrono_average_calibration(0); - for(int cnt = 0; cnt < CHRONO_CAL_ITERATIONS; cnt++) { - chrono_t0 = std::chrono::high_resolution_clock::now(); - chrono_t1 = std::chrono::high_resolution_clock::now(); - chrono_diff = chrono_t1 - chrono_t0; - chrono_average_calibration += chrono_diff; - } - chrono_average_calibration /= CHRONO_CAL_ITERATIONS; - std::cout << STR_CHRONO << "Average Calibration = " << chrono_average_calibration.count() << std::endl; - */ - - // Loading the xclbin - char* xclbinFilename = argv[1]; - unsigned int dev_index = 0; - auto my_device = xrt::device(dev_index); - std::cout << STR_PASSED << "auto my_device = xrt::device(" << dev_index << ")" << std::endl; - auto xclbin_uuid = my_device.load_xclbin(xclbinFilename); - std::cout << STR_PASSED << "auto xclbin_uuid = my_device.load_xclbin(" << xclbinFilename << ")" << std::endl; - - // Input mm2s kernel - std::cout << STR_INFO << "Opening the Input mm2s Kernel..." << std::endl; - auto in_0 = xrt::kernel(my_device, xclbin_uuid, "mm2s:{mm2s_1}"); - std::cout << STR_PASSED << "auto in_0 = xrt::kernel(my_device, xclbin_uuid, \"mm2s:{mm2s_1}\")" << std::endl; - auto in_0_bo = xrt::bo(my_device, bSizeIn, XCL_BO_FLAGS_NONE, in_0.group_id(0)); - std::cout << STR_PASSED << "auto in_0_bo = xrt::bo(my_device, bSizeIn, XCL_BO_FLAGS_NONE, in_0.group_id(0) (=" << in_0.group_id(0) << "))" << std::endl; - auto in_0_bo_mapped = in_0_bo.map(); - std::cout << STR_PASSED << "auto in_0_bo_mapped = in_0_bo.map()" << std::endl; - - // Populating Input Buffer with random data - std::cout << STR_INFO << "Setting Input Data " << std::endl; - TYPE_DATA *matOp1 = (TYPE_DATA *) malloc(bSizeIn); - TYPE_DATA *matOp2; matOp2 = matOp1 + wSizeIn/2; - TYPE_DATA *matRef = (TYPE_DATA *) malloc(bSizeOut); - union //PS: this conversion does not work if you used unsigned - { - TYPE_DATA i_val; - T f_val; - } converter; - FILE *fin1=fopen("matrix_inputs.txt", "w"); - srand(time(NULL)); // Initialization, should only be called once. - for(int r = 0; r(); - std::cout << STR_PASSED << "auto out_0_bo_mapped = out_0_bo.map()" << std::endl; - memset(out_0_bo_mapped, 0x0, bSizeOut); - - // Opening the matrix multiplier kernel - std::cout << STR_INFO << "Opening HLS Accel kernel " << std::endl; - auto my_krnl = xrt::kernel(my_device, xclbin_uuid, "HLS_accel"); - std::cout << STR_PASSED << "auto my_krnl = xrt::kernel(my_device, xclbin_uuid, \"HLS_accel\")" << std::endl; - - /* - chrono_t0 = std::chrono::high_resolution_clock::now(); - */ - // Start Input mm2s Kernel - std::cout << STR_INFO << "Starting Input mm2s Kernel..." << std::endl; - auto in_0_run = in_0(in_0_bo, nullptr, wSizeIn); - std::cout << STR_PASSED << "auto in_0_run = in_0(in_0_bo, nullptr, " << wSizeIn << ")" << std::endl; - // Starting the Output s2mm Kernels - std::cout << STR_INFO << "Starting Output s2mm Kernel..." << std::endl; - auto out_0_run = out_0(out_0_bo, nullptr, wSizeOut); - std::cout << STR_PASSED << "auto out_0_run = out(out_0_bo, nullptr, " << wSizeOut << ")" << std::endl; - // Starting the matrix multiplier kernel - std::cout << STR_INFO << "starting HLS Accel kernel " << std::endl; - auto my_krnl_run = my_krnl(nullptr, nullptr); - std::cout << STR_PASSED << "my_krnl_run" << std::endl; - - // Waiting for all kernels to end - std::cout << std::endl << STR_INFO << "Waiting for kernels to end..." << std::endl << std::endl; - in_0_run.wait(); - std::cout << STR_PASSED << "in_0_run.wait()" << std::endl; - my_krnl_run.wait(); - std::cout << STR_PASSED << "my_krnl_run.wait()" << std::endl; - out_0_run.wait(); - std::cout << STR_PASSED << "out_0_run.wait()" << std::endl; - - // Sync Output Buffers - std::cout << STR_INFO << "Sync Output Buffer..." << std::endl; - out_0_bo.sync(XCL_BO_SYNC_BO_FROM_DEVICE); - std::cout << STR_PASSED << "out_0_bo.sync(XCL_BO_SYNC_BO_FROM_DEVICE)" << std::endl; - - /* - chrono_t1 = std::chrono::high_resolution_clock::now(); - chrono_diff = chrono_t1 - chrono_t0 - chrono_average_calibration; - chrono_spend(chrono_diff.count(), "Run+Wait Kernels & Sync Output Buffer"); - */ - - // Verifying the results - std::cout << std::endl << STR_INFO << "Verifying output data vs. golden ones " << std::endl << std::endl; - FILE *fin3=fopen("matrix_out_bufs.txt", "w"); - int error_cnt = 0; - TYPE_DATA *golden; golden = matRef; - for(int i = 0; i < wSizeOut; i++) - { - if(out_0_bo_mapped[i] != golden[i]) - { - printf("Error found: @ %d, %d != %d\n", i, out_0_bo_mapped[i], golden[i]); - error_cnt++; - } - fprintf(fin3, "%d %d\n", out_0_bo_mapped[i], golden[i]); - } - fclose(fin3); - - //free memory - free(matRef); - free(matOp1); - - //close program - std::cout << std::endl << ( (error_cnt>0) ? STR_FAILED : STR_PASSED) << argv[0] << std::endl << std::endl; - return ( (error_cnt>0) ? EXIT_FAILURE : EXIT_SUCCESS ); -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/Makefile b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/Makefile deleted file mode 100644 index b997af7200..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/Makefile +++ /dev/null @@ -1,80 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -SHELL := /bin/bash - -.PHONY: help hls_kernels hls_clean zcu102_all zcu102_clean all clean sd_card run show_dir - -#======================================================== -# Source directories -# ========================================================= -RELATIVE_PROJECT_DIR := ./ -PROJECT_DIR := $(shell readlink -f $(RELATIVE_PROJECT_DIR)) - -PROJECT_PL_DIR := $(PROJECT_DIR)/make-flow/zcu102/mmult_kernels -PROJECT_PS_DIR := $(PROJECT_DIR)/make-flow/zcu102/mmult -PROJECT_HWLINK_DIR := $(PROJECT_DIR)/make-flow/zcu102/mmult_system_hw_link -PROJECT_SYSTEM_DIR := $(PROJECT_DIR)/make-flow/zcu102/mmult_system - - -show_dir: - -@echo " " - -@echo " " - -@echo "from $(realpath .)" - -@echo "RELATIVE PROJECT DIR is: $(RELATIVE_PROJECT_DIR)" - -@echo "CURRENT PROJECT DIR is: $(PROJECT_DIR)" - -@echo "PL KERNELS PROJECT DIR is: $(PROJECT_PL_DIR)" - -@echo "PS ARM HOST PROJECT DIR is: $(PROJECT_PS_DIR)" - -@echo "HW LINK PROJECT DIR is: $(PROJECT_HWLINK_DIR)" - -@echo "SYSTEM PROJECT DIR is: $(PROJECT_SYSTEM_DIR)" - -@echo " " - -@echo " " - - -EMBEDDED_PACKAGE_OUT = $(PROJECT_SYSTEM_DIR)/Hardware/package -EMBEDDED_EXEC_SCRIPT = $(PROJECT_SYSTEM_DIR)/Hardware/embedded_exec.sh -PACKAGE_FILES += $(EMBEDDED_EXEC_SCRIPT) -SD_FILES_WITH_PREFIX = $(foreach sd_file,$(PACKAGE_FILES),--package.sd_file $(sd_file)) - -# ======================================================= -# global variables for this tutorial -# ======================================================= -#RELEASE=2022.2 -RELEASE=2025.1 -BOARD=zcu102 -BASE_NUM=202510_1 -#BASE_NUM=202220_1 - -# Platform Selection... -ZYNQMP_VITIS_PLATFORM = xilinx_${BOARD}\_base_${BASE_NUM} -VITIS_PLATFORM_DIR = ${PLATFORM_REPO_PATHS}/${ZYNQMP_VITIS_PLATFORM} -export VITIS_PLATFORM_XPFM = ${VITIS_PLATFORM_DIR}/${ZYNQMP_VITIS_PLATFORM}.xpfm -# Set SysRoot, RootFS and Image -export VITIS_SYSROOTS = ${COMMON_IMAGE_ZYNQMP}/sysroots/cortexa72-cortexa53-amd-linux -export SDKTARGETSYSROOT = ${VITIS_SYSROOTS} -export KERNEL_IMAGE = ${COMMON_IMAGE_ZYNQMP}/Image -export ROOTFS = ${COMMON_IMAGE_ZYNQMP}/rootfs.ext4 -export XLNX_VERSAL = ${COMMON_IMAGE_ZYNQMP} -export PLATFORM = ${VITIS_PLATFORM_XPFM} - - - - -hls_clean: - rm -rf *_prj *.log *~ ./logs - -hls_kernels: - vitis-run --mode hls --tcl ./run_matrix_mult_script_zcu102.tcl - -zcu102_all: - $(MAKE) -C ./make-flow/zcu102 all - -zcu102_clean: - $(MAKE) -C ./make-flow/zcu102 clean - -run: all -sd_card: all - -kernels: hls_kernels -all: show_dir zcu102_all -clean: show_dir hls_clean zcu102_clean diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/check_mmult_results.m b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/check_mmult_results.m deleted file mode 100644 index 28f718e0cb..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/check_mmult_results.m +++ /dev/null @@ -1,68 +0,0 @@ -% Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -% SPDX-License-Identifier: MIT - -%% clean workspace - -clear all; -close all; -clc; - -%% memory allocation - -DIM=32; -matOp1 = zeros([DIM, DIM]); -matOp2 = zeros([DIM, DIM]); -matRef = zeros([DIM, DIM]); - -%% reference matrices with MATLAB - -for r = 0 : DIM -1 - for c = 0 : DIM -1 - r1 = r + c; - r2 = r * c; - matOp1(r+1, c+1) = r1; - matOp2(r+1, c+1) = r2; - end -end -matRef = matOp1 * matOp2; - -%% load files generated by ARM on ZCU102 - -I = load('matrix_inputs.txt'); -Oif = load('matrix_out_i_f.txt'); -Obufs = load('matrix_out_bufs.txt'); - -%reshape data files -in1=I(:,1); -in2=I(:,2); -m1 = reshape(in1, [32,32])'; -m2 = reshape(in2, [32,32])'; -m3 = m1 * m2; % expected result - -%% check differences ARM vs. MATLAB - -diff1 = abs(m1 - matOp1); -sum_abs_diff1 = sum(diff1(:)) -diff2 = abs(m2 - matOp2); -sum_abs_diff2 = sum(diff2(:)) -diff3 = abs(m3 - matRef); -sum_abs_diff3 = sum(diff3(:)) - -%% -Oif_c1 = Oif(:, 1); -mat_Oif_c1 = reshape(Oif_c1, [DIM, DIM])'; -Obufs_c2 = Obufs(:, 2); -mat_Obufs_c2 = reshape(Obufs_c2, [DIM, DIM])'; -diff31 = abs(mat_Oif_c1 - mat_Obufs_c2); -sum_abs_diff31 = sum(diff31(:)) - -Oif_c2 = Oif(:, 2); -mat_Oif_c2 = reshape(Oif_c2, [DIM, DIM])'; -diff32 = abs(m3 - mat_Oif_c2); -sum_abs_diff32 = sum(diff32(:)) - - -Obufs_c1 = Obufs(:, 1); -mat_Obufs_c1 = reshape(Obufs_c1, [DIM, DIM])'; -diff12 = abs(mat_Obufs_c1 - mat_Obufs_c2); -sum_abs_diff12 = sum(diff12(:)) diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/description.json b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/description.json deleted file mode 100644 index ead4e9f9c9..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/description.json +++ /dev/null @@ -1,39 +0,0 @@ -{ - "name": "Developer_Contributed-03-HLS_Code_Optimization--matrix_mult_z", - "description": "03-HLS_Code_Optimization--matrix_mult", - "gui": "false", - "flow": "vitis", - - "platform_allowlist": [ "zcu102"], - "platform_blocklist": [], - - "testinfo": { - "test_name": "CTB_03-HLS_zynqmp", - "jobs": [ - { - "max_memory_MB": 65536 - } - ], - - "targets": [ - "vitis_hw_build", - "vitis_hw_run" - ], - "make_options": [ - "VITIS_PLATFORM_XPFM='${PLATFORM_REPO_PATHS}/xilinx_zcu102_base_202510_1/xilinx_zcu102_base_202510_1.xpfm'", - "EMBEDDED_PACKAGE_OUT=./make-flow/zcu102/mmult_system/Hardware/package", - "EMBEDDED_EXEC_SCRIPT=./embedded_exec.sh" - ], - "custom_build_target": { - "all": "all", - "hw": "sd_card" - }, - "custom_board_target": "run_test", - "tasks": { - "build": { - "pre_exec": "./env_setup_zynqmp.sh" - } - } - - } -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/make-flow/zcu102/Makefile b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/make-flow/zcu102/Makefile deleted file mode 100644 index 521ecb7bb2..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/make-flow/zcu102/Makefile +++ /dev/null @@ -1,86 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -SHELL := /bin/bash - -PHONY = help kernels hw_link system host all clean show_dir -PHONY += zcu102_build zcu102_prepare -.PHONY: $(PHONY) - - - -#======================================================== -# Source directories -# ========================================================= -RELATIVE_PROJECT_DIR := ./ -PROJECT_DIR := $(shell readlink -f $(RELATIVE_PROJECT_DIR)) - -PROJECT_PL_DIR := $(PROJECT_DIR)/mmult_kernels -PROJECT_PS_DIR := $(PROJECT_DIR)/mmult -PROJECT_HWLINK_DIR := $(PROJECT_DIR)/mmult_system_hw_link -PROJECT_SYSTEM_DIR := $(PROJECT_DIR)/mmult_system - - -show_dir: - -@echo " " - -@echo " " - -@echo "from $(realpath .)" - -@echo "RELATIVE PROJECT DIR is: $(RELATIVE_PROJECT_DIR)" - -@echo "CURRENT PROJECT DIR is: $(PROJECT_DIR)" - -@echo "PL KERNELS PROJECT DIR is: $(PROJECT_PL_DIR)" - -@echo "PS ARM HOST PROJECT DIR is: $(PROJECT_PS_DIR)" - -@echo "HW LINK PROJECT DIR is: $(PROJECT_HWLINK_DIR)" - -@echo "SYSTEM PROJECT DIR is: $(PROJECT_SYSTEM_DIR)" - -@echo " " - -@echo " " - - - - -all: zcu102_prepare zcu102_build show_dir - -#source $(realpath ../../../../scripts)/set_proj_env_2022v2_zcu102.sh -zcu102_build: - $(MAKE) kernels - $(MAKE) hw_link - $(MAKE) host - $(MAKE) system - - -clean: - $(MAKE) -C mmult_kernels/Hardware clean - $(MAKE) -C mmult_system_hw_link/Hardware clean - $(MAKE) -C mmult_system/Hardware clean - $(MAKE) -C mmult/Hardware clean - rm -rf ./mmult/src - rm -rf ./mmult_system/src - rm -rf ./mmult_kernels/src - rm -rf ./mmult_system_hw_link/src - rm -f ./muult_system/Hardware/*.log - rm -f ./mmult_system/Hardware/*~ - rm -rf ./mmult_system/Hardware/.ipcache - rm -rf ./mmult_system_hw_link/Hardware/.ipcache - - -zcu102_prepare: - mkdir -p $(realpath ../zcu102/mmult)/src - mkdir -p $(realpath ../zcu102/mmult_kernels)/src - cp -f $(realpath ../../vitis_src)/xrt_mmult_test.cpp $(realpath ./mmult)/src/ - cp -f $(realpath ../../src)/mmult.h $(realpath ./mmult)/src/ - cp -f $(realpath ../../src)/*accel.cpp $(realpath ./mmult_kernels)/src/ - cp -f $(realpath ../../src)/mmult.h $(realpath ./mmult_kernels)/src - cp -f $(realpath ../../vitis_src)/mm2s.cpp $(realpath ./mmult_kernels)/src/ - cp -f $(realpath ../../vitis_src)/s2mm.cpp $(realpath ./mmult_kernels)/src/ - cp -f $(realpath ../../vitis_src)/system.cfg $(realpath ./mmult_system_hw_link)/ - -kernels: - $(MAKE) -C $(PROJECT_PL_DIR)/Hardware all - -hw_link: - $(MAKE) -C $(PROJECT_HWLINK_DIR)/Hardware all - -system: - $(MAKE) -C $(PROJECT_SYSTEM_DIR)/Hardware all - -host: - $(MAKE) -C $(PROJECT_PS_DIR)/Hardware all diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/make-flow/zcu102/mmult/Hardware/makefile b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/make-flow/zcu102/mmult/Hardware/makefile deleted file mode 100644 index ead0df3c0b..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/make-flow/zcu102/mmult/Hardware/makefile +++ /dev/null @@ -1,76 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -#relative directory -RELATIVE_PROJECT_DIR := ../ - -#absolute directory -PROJECT_DIR := $(shell readlink -f $(RELATIVE_PROJECT_DIR)) -PROJECT_PS_DIR := $(PROJECT_DIR) -PROJECT_PL_DIR := $(PROJECT_PS_DIR)/../mmult_kernels -PROJECT_HWLINK_DIR := $(PROJECT_PS_DIR)/../mmult_system_hw_link -PROJECT_SYSTEM_DIR := $(PROJECT_PS_DIR)/../mmult_system - -show_dir: - -@echo " " - -@echo " " - -@echo "from $(realpath .)" - -@echo "RELATIVE PROJECT DIR is: $(RELATIVE_PROJECT_DIR)" - -@echo "CURRENT PROJECT DIR is: $(PROJECT_DIR)" - -@echo "PL KERNELS PROJECT DIR is: $(PROJECT_PL_DIR)" - -@echo "PS ARM HOST PROJECT DIR is: $(PROJECT_PS_DIR)" - -@echo "HW LINK PROJECT DIR is: $(PROJECT_HWLINK_DIR)" - -@echo "SYSTEM PROJECT DIR is: $(PROJECT_SYSTEM_DIR)" - -@echo " " - -@echo " " - - -BOARD=zcu102 - -# compiler tools -HOST_CXX ?= $(XILINX_VITIS)/gnu/aarch64/lin/aarch64-linux/bin/aarch64-linux-gnu-g++ -RM = rm -f -RMDIR = rm -rf - -# compiler flags -CXXFLAGS = -std=c++17 -DVITIS_PLATFORM=$(ZYNQMP_VITIS_PLATFORM) -D__USE_XOPEN2K8 -I$(XILINX_HLS)/include -I$(COMMON_IMAGE_ZYNQMP)/sysroots/cortexa72-cortexa53-amd-linux/usr/include/xrt -O2 -g -Wall -c -fmessage-length=0 --sysroot=$(COMMON_IMAGE_ZYNQMP)/sysroots/cortexa72-cortexa53-amd-linux - -LDFLAGS = -lxilinxopencl -lxrt_core -lxrt_coreutil -lpthread -lrt -ldl -lcrypt -lstdc++ -L$(COMMON_IMAGE_ZYNQMP)/sysroots/cortexa72-cortexa53-amd-linux/usr/lib --sysroot=$(COMMON_IMAGE_ZYNQMP)/sysroots/cortexa72-cortexa53-amd-linux - - -# -# host files -# - -HOST_OBJECTS += $(PROJECT_PS_DIR)/src/xrt_mmult_test.o - -HOST_EXE = $(PROJECT_PS_DIR)/Hardware/mmult - - -# -# primary build targets -# - -.PHONY: all clean -all: show_dir $(HOST_EXE) - -clean: - -$(RM) $(HOST_EXE) $(HOST_OBJECTS) *.log guidance.* $(PROJECT_PS_DIR)/src/*.o *~ - -$(RMDIR) $(PROJECT_PS_DIR)/Hardware/src - -.PHONY: incremental -incremental: all - - -nothing: - -# -# host rules -# - -$(PROJECT_PS_DIR)/src/xrt_mmult_test.o: $(PROJECT_PS_DIR)/src/xrt_mmult_test.cpp $(PROJECT_PS_DIR)/src/mmult.h - -@mkdir -p $(@D) - $(HOST_CXX) $(CXXFLAGS) -o "$@" "$<" - -$(HOST_EXE): $(HOST_OBJECTS) - $(HOST_CXX) -o "$@" $(+) $(LDFLAGS) diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/make-flow/zcu102/mmult_kernels/Hardware/HLS_accel-compile.cfg b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/make-flow/zcu102/mmult_kernels/Hardware/HLS_accel-compile.cfg deleted file mode 100644 index 1199a3d350..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/make-flow/zcu102/mmult_kernels/Hardware/HLS_accel-compile.cfg +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -#platform=/media/danieleb/DATA/2022.2/tools/Xilinx/Vitis/2022.2/base_platforms/xilinx_zcu102_base_202220_1/xilinx_zcu102_base_202220_1.xpfm -save-temps=1 -kernel=HLS_accel -messageDb=build/HLS_accel.mdb -temp_dir=build -report_dir=build/reports -log_dir=build/logs - -[advanced] -misc=solution_name=HLS_accel diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/make-flow/zcu102/mmult_kernels/Hardware/makefile b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/make-flow/zcu102/mmult_kernels/Hardware/makefile deleted file mode 100644 index b3cb5275cf..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/make-flow/zcu102/mmult_kernels/Hardware/makefile +++ /dev/null @@ -1,90 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -#relative directory -RELATIVE_PROJECT_DIR := ../ - -#absolute directory -PROJECT_DIR := $(shell readlink -f $(RELATIVE_PROJECT_DIR)) -PROJECT_PL_DIR := $(PROJECT_DIR) -PROJECT_PS_DIR = $(PROJECT_PL_DIR)/../mmult -PROJECT_SYSTEM_DIR = $(PROJECT_PL_DIR)/../mmult_system -PROJECT_HWLINK_DIR = $(PROJECT_PL_DIR)/../mmult_system_hw_link - -show_dir: - -@echo " " - -@echo " " - -@echo "from $(realpath .)" - -@echo "RELATIVE PROJECT DIR is: $(RELATIVE_PROJECT_DIR)" - -@echo "CURRENT PROJECT DIR is: $(PROJECT_DIR)" - -@echo "PL KERNELS PROJECT DIR is: $(PROJECT_PL_DIR)" - -@echo "PS ARM HOST PROJECT DIR is: $(PROJECT_PS_DIR)" - -@echo "HW LINK PROJECT DIR is: $(PROJECT_HWLINK_DIR)" - -@echo "SYSTEM PROJECT DIR is: $(PROJECT_SYSTEM_DIR)" - -@echo " " - -@echo " " - - -BOARD=zcu102 - -# compiler tools -VPP ?= ${XILINX_VITIS}/bin/v++ -RM = rm -f -RMDIR = rm -rf - -TARGET = hw -VPP_OPTS = --target $(TARGET) - -# -# Hw kernel files -# - - -BUILD_SUBDIRS = $(PROJECT_PL_DIR)/Hardware/build -HW_KERNEL_OBJS += $(PROJECT_PL_DIR)/Hardware/build/HLS_accel.xo -SRC_KERNEL_OBJS += $(PROJECT_PL_DIR)/Hardware/build/HLS_accel.xo -HW_KERNEL_OBJS += $(PROJECT_PL_DIR)/Hardware/build/mm2s.xo -SRC_KERNEL_OBJS += $(PROJECT_PL_DIR)/Hardware/build/mm2s.xo -HW_KERNEL_OBJS += $(PROJECT_PL_DIR)/Hardware/build/s2mm.xo -SRC_KERNEL_OBJS += $(PROJECT_PL_DIR)/Hardware/build/s2mm.xo - -ALL_MESSAGE_FILES = $(subst .xo,.o,.mdb,$(SRC_KERNEL_OBJS)) - -# -# primary build targets -# - -.PHONY: all clean -all: show_dir $(HW_KERNEL_OBJS) - - -clean: - -$(RM) $(SRC_KERNEL_OBJS) $(ALL_MESSAGE_FILES) - -$(RMDIR) $(BUILD_SUBDIRS) - -$(RMDIR) .Xil guidance.* *.log *~ - -.PHONY: incremental -incremental: all - - -nothing: - -# -# Hw Kernels compile; -# - -$(PROJECT_PL_DIR)/Hardware/build/HLS_accel.xo: $(PROJECT_PL_DIR)/src/mmult_accel.cpp $(PROJECT_PL_DIR)/src/mmult.h $(PROJECT_PL_DIR)/Hardware/HLS_accel-compile.cfg - -@mkdir -p $(@D) - -@$(RM) $@ - $(VPP) $(VPP_OPTS) --compile -I"$( binary_container_1.xsa.sh - $(VPP_LINKER) $(VPP_OPTS) --link --config $(PROJECT_HWLINK_DIR)/system.cfg --platform $(VITIS_PLATFORM_XPFM) --config $(PROJECT_HWLINK_DIR)/Hardware/binary_container_1-link.cfg -o"$@" $(BINARY_CONTAINER_1_OBJS) diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/make-flow/zcu102/mmult_system_hw_link/system.cfg b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/make-flow/zcu102/mmult_system_hw_link/system.cfg deleted file mode 100644 index fae908b74e..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/make-flow/zcu102/mmult_system_hw_link/system.cfg +++ /dev/null @@ -1,11 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -[connectivity] -##comment next 3 lines if you use this file with the Vitis GUI -#nk=mm2s:1 -#nk=s2mm:1 -#nk=HLS_accel:1 - -sc=mm2s_1.s:HLS_accel_1.INPUT_STREAM -sc=HLS_accel_1.OUTPUT_STREAM:s2mm_1.s diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/run_matrix_mult_zcu102_script.tcl b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/run_matrix_mult_zcu102_script.tcl deleted file mode 100644 index 2178c01222..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/run_matrix_mult_zcu102_script.tcl +++ /dev/null @@ -1,71 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -puts "\n" -puts "************************************************************************" -puts "* EXAMPLE 9) 32x32 REAL MATRIX MULTIPLICATION DEMO" -puts "************************************************************************" -puts "\n" - - -# STANDALONE MATRIX MULTIPLIER HLS PROJECT -########################################################################### - -open_project hls_mmult_prj -set_top standalone_mmult -add_files src/mmult_accel.cpp -add_files -tb src/mmult_test.cpp -open_solution "solution1" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 3.0 -name default -#config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 0.5 -csim_design -clean -csynth_design - -open_solution "solution2" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 3.0 -name default -#config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 0.5 -set_directive_pipeline -II 1 "mmult_hw/L2" -csynth_design - -open_solution "solution3" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 3.0 -name default -#config_interface -m_axi_latency 0 -config_export -format ip_catalog -rtl vhdl -set_clock_uncertainty 0.5 -set_directive_pipeline -II 1 "mmult_hw/L2" -set_directive_array_partition -type block -factor 16 -dim 2 "mmult_hw" a -set_directive_array_partition -type block -factor 16 -dim 1 "mmult_hw" b -csynth_design -#cosim_design - -close_project - - -# WRAPPED AXI4-STREAM MATRIX MULTIPLIER HLS PROJECT -########################################################################### - -open_project hls_wrapped_mmult_prj -set_top HLS_accel -add_files src/mmult_accel.cpp -cflags "-DDB_DEBUG" -add_files -tb src/mmult_test.cpp -cflags "-DDB_DEBUG" -open_solution "solution0" -flow_target vivado -set_part {xczu9eg-ffvb1156-2-i} -create_clock -period 3.0 -name default -set_clock_uncertainty 0.5 -set_directive_inline "mmult_hw" -set_directive_pipeline -II 1 "mmult_hw/L2" -set_directive_array_partition -type block -factor 16 -dim 2 "mmult_hw" a -set_directive_array_partition -type block -factor 16 -dim 1 "mmult_hw" b -csim_design -clean -#-setup -csynth_design -#export_design -evaluate verilog -format ip_catalog -close_project diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/src/mmult.h b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/src/mmult.h deleted file mode 100644 index 9aa59acff6..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/src/mmult.h +++ /dev/null @@ -1,194 +0,0 @@ -/* -Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -SPDX-License-Identifier: MIT -*/ - - -/* - void example(hls::stream< ap_axis<32,2,5,6> > &A, - hls::stream< ap_axis<32,2,5,6> > &B) -{ - #pragma HLS INTERFACE axis port=A - #pragma HLS INTERFACE axis port=B - ap_axis<32,2,5,6> tmp; - while(1) - { - A.read(tmp); - tmp.data = tmp.data.to_int() + 5; - B.write(tmp); - if(tmp.last) - { - break; - } - } -*/ - -#include -#include "ap_axi_sdata.h" -#include "hls_stream.h" - -const int DIM = 32; -const int SIZE = (DIM*DIM); - -const int U =2; -const int TI=5; -const int TD=6; - -typedef float T; -typedef ap_axis AXI_VAL; - - - -// function prototypes -void standalone_mmult (float A[DIM][DIM], float B[DIM][DIM], float C[DIM][DIM]); - -int HLS_accel (hls::stream &INPUT_STREAM, hls::stream &OUTPUT_STREAM); - -/* ****************************** C++ TEMPLATES ************************************** */ - -// reference function -template -void matrix_multiply_ref(T a[DIM][DIM], T b[DIM][DIM], T out[DIM][DIM]) -{ - // matrix multiplication of a A*B matrix - for (int ia = 0; ia < DIM; ++ia) - for (int ib = 0; ib < DIM; ++ib) - { - float sum = 0; - for (int id = 0; id < DIM; ++id) - sum += a[ia][id] * b[id][ib]; - out[ia][ib] = sum; - } - return; -} - -// -------------------------------------------------------- -// function to be accelerated in HW -template -void mmult_hw(T a[DIM][DIM], T b[DIM][DIM], T out[DIM][DIM]) -{ - - int const FACTOR = DIM/2; - #pragma HLS INLINE - //#pragma HLS array_partition variable=a block factor=FACTOR dim=2 - //#pragma HLS array_partition variable=b block factor=FACTOR dim=1 - - // matrix multiplication of a A*B matrix - L1:for (int ia = 0; ia < DIM; ++ia) - L2:for (int ib = 0; ib < DIM; ++ib) - { - //#pragma HLS PIPELINE II=1 - T sum = 0; - L3:for (int id = 0; id < DIM; ++id) - sum += a[ia][id] * b[id][ib]; - out[ia][ib] = sum; - } - return; -} - -// -------------------------------------------------------- -// functions to insert and extract elements from an axi stream -// includes conversion to correct data type - -template -T pop_stream(hls::stream< ap_axis> &inp_stream) -{ -#pragma HLS INLINE - - ap_axis e; - inp_stream.read(e); - - assert(sizeof(T) == sizeof(int)); - union - { - int ival; - T oval; - } converter; - converter.ival = e.data; - T ret = converter.oval; - - ap_uint strb = e.strb; - ap_uint keep = e.keep; - ap_uint user = e.user; - ap_uint<1> last = e.last; - //ap_uint id = e.id; - //ap_uint dest = e.dest; - - return ret; -} - -template -void push_stream(T data, bool last, hls::stream< ap_axis> &out_stream) -{ -#pragma HLS INLINE - - ap_axis e; - - assert(sizeof(T) == sizeof(int)); - union - { - int oval; - T ival; - } converter; - converter.ival = data; - e.data = converter.oval; - - // set it to sizeof(T) ones - e.strb = 1; //-1; - e.keep = 1; //15; - e.user = 1; //0; - e.last = last ? 1 : 0; - //e.id = 0; - //e.dest = 0; - - out_stream.write(e); - -} - -// -------------------------------------------------------------------- -// function to be accelerated in HW wrapped with AXI4-Stream interface - -template -int wrapped_mmult_hw (hls::stream> &inp_stream, hls::stream> &out_stream) -{ - -#pragma HLS INLINE - - T a[DIM][DIM]; - T b[DIM][DIM]; - T out[DIM][DIM]; - - assert(sizeof(T)*8 == 32); - - // stream in first matrix - for(int i=0; i(inp_stream); - } - - // stream in second matrix - for(int i=0; i(inp_stream); - } - - // do HW multiplication - mmult_hw(a,b,out); - - // stream out result matrix - for(int i=0; i(out[i][j], last, out_stream); - } - return 0; - -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/src/mmult_accel.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/src/mmult_accel.cpp deleted file mode 100644 index a40b7ad632..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/src/mmult_accel.cpp +++ /dev/null @@ -1,31 +0,0 @@ -// Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -// SPDX-License-Identifier: MIT - -#include -#include - -#include "mmult.h" - - -// THIS IS THE TOP LEVEL DESIGN THAT WILL BE SYNTHESIZED -#define MCR_SIZE 1024 - - -void standalone_mmult (float A[32][32], float B[32][32], float C[32][32]) -{ - - mmult_hw (A, B, C); - -} - - -int HLS_accel (hls::stream &INPUT_STREAM, hls::stream &OUTPUT_STREAM) -{ -#pragma HLS INTERFACE s_axilite port=return bundle=CONTROL_BUS -#pragma HLS INTERFACE axis port=OUTPUT_STREAM -#pragma HLS INTERFACE axis port=INPUT_STREAM - - int ret = wrapped_mmult_hw (INPUT_STREAM, OUTPUT_STREAM); - - return ret; -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/src/mmult_test.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/src/mmult_test.cpp deleted file mode 100644 index 087fc53cd9..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/src/mmult_test.cpp +++ /dev/null @@ -1,165 +0,0 @@ -/* -Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -SPDX-License-Identifier: MIT -*/ - -#include -#include - -#include "mmult.h" - -void mmult_sw(T a[DIM][DIM], T b[DIM][DIM], T out[DIM][DIM]) -{ - // matrix multiplication of a A*B matrix - for (int ia = 0; ia < DIM; ++ia) - for (int ib = 0; ib < DIM; ++ib) - { - - float sum = 0; - - for (int id = 0; id < DIM; ++id) - - sum += a[ia][id] * b[id][ib]; - - out[ia][ib] = sum; - } -} - - -#ifdef DB_DEBUG - - -// test the functions -template -int test_matrix_mult(void) -{ - int i,j, err; - - T matOp1[DIM][DIM]; - T matOp2[DIM][DIM]; - T matMult_sw[DIM][DIM]; - T matMult_hw[DIM][DIM]; - int SIZE = DIM*DIM; - - /** Matrix Initiation */ - for(i = 0; i inp_stream, out_stream; - - assert(sizeof(T)*8 == 32); - // stream in the first input matrix - for(int i=0; i(matOp1[i][j],0, inp_stream); - } - // stream in the second input matrix - for(int i=0; i(matOp2[i][j],k == (SIZE-1), inp_stream); - } - - - //call the DUT - //wrapped_mmult_hw(inp_stream, out_stream); - int res= HLS_accel(inp_stream, out_stream); - - - // extract the output matrix from the out stream - for(int i=0; i(out_stream); - } - - - /* reference Matrix Multiplication */ - matrix_multiply_ref(matOp1, matOp2, matMult_sw); - - /** Matrix comparison */ - err = 0; - for (i = 0; (i(); - return ret_val; - -} - -#else - -int main(void) -{ - - int ret_val = 0; - - int i,j, err; - - T matOp1[DIM][DIM]; - T matOp2[DIM][DIM]; - T matMult_sw[DIM][DIM]; - T matMult_hw[DIM][DIM]; - - /** Matrix Initiation */ - for(i = 0; i -#include -#include - -#define WORD_SIZE 32 - -extern "C" { - -void mm2s(ap_int* mem, hls::stream, 0, 0, 0>>& s, int size) { -#pragma HLS INTERFACE m_axi port=mem offset=slave bundle=gmem - -#pragma HLS INTERFACE axis port=s - -#pragma HLS INTERFACE s_axilite port=mem bundle=control -#pragma HLS INTERFACE s_axilite port=size bundle=control -#pragma HLS INTERFACE s_axilite port=return bundle=control - - for(int i = 0; i < size; i++) { -#pragma HLS PIPELINE II=1 - hls::axis, 0, 0, 0> x; - x.data = mem[i]; - x.keep = -1; - s.write(x); - } - -} - -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/vitis_src/s2mm.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/vitis_src/s2mm.cpp deleted file mode 100644 index 80012ae353..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/vitis_src/s2mm.cpp +++ /dev/null @@ -1,31 +0,0 @@ -// Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -// SPDX-License-Identifier: MIT - -#include -#include -#include - -#define WORD_SIZE 32 - -extern "C" { - -//void s2mm(ap_int* mem, hls::stream >& s, int size) { -void s2mm(ap_int* mem, hls::stream >& s, int size) { -#pragma HLS INTERFACE m_axi port=mem offset=slave bundle=gmem - -#pragma HLS interface axis port=s - -#pragma HLS INTERFACE s_axilite port=mem bundle=control -#pragma HLS INTERFACE s_axilite port=size bundle=control -#pragma HLS interface s_axilite port=return bundle=control - - for(int i = 0; i < size; i++) { -#pragma HLS PIPELINE II=1 - //qdma_axis x = s.read(); - ap_axis x = s.read(); - mem[i] = x.data; - } - -} - -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/vitis_src/system.cfg b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/vitis_src/system.cfg deleted file mode 100644 index fae908b74e..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/vitis_src/system.cfg +++ /dev/null @@ -1,11 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -[connectivity] -##comment next 3 lines if you use this file with the Vitis GUI -#nk=mm2s:1 -#nk=s2mm:1 -#nk=HLS_accel:1 - -sc=mm2s_1.s:HLS_accel_1.INPUT_STREAM -sc=HLS_accel_1.OUTPUT_STREAM:s2mm_1.s diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/vitis_src/xrt_mmult_test.cpp b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/vitis_src/xrt_mmult_test.cpp deleted file mode 100644 index 9449739796..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/9_matrix_mult_z/vitis_src/xrt_mmult_test.cpp +++ /dev/null @@ -1,274 +0,0 @@ -// Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -// SPDX-License-Identifier: MIT - -#include -#include -#include -#include -#include -#include -#include -#include -#include - -#include "mmult.h" - -#define TYPE_DATA signed int - -static const char* STR_ERROR = "ERROR: "; -static const char* STR_FAILED = "FAILED: "; -static const char* STR_PASSED = "PASSED: "; -static const char* STR_INFO = "INFO: "; -static const char* STR_USAGE = "USAGE: "; - -/* -static const char* STR_CHRONO = "CHRONO: "; -static const int CHRONO_CAL_ITERATIONS = 2000; - -void chrono_spend( - int chrono_diff, - const char* str -) { - if(chrono_diff >= 10000) { - std::cout << STR_CHRONO << (int) (chrono_diff / 1000) << "ms -> " << str << std::endl; - } else { - std::cout << STR_CHRONO << (int) (chrono_diff) << "us -> " << str << std::endl; - } -} -*/ - -int main(int argc, char* argv[]) { - - // Check command line - if(argc < 2) { - std::cout << STR_USAGE << argv[0] <<" " << std::endl; - return EXIT_FAILURE; - } - - int wSizeIn = 2*SIZE; - int bSizeIn = wSizeIn * sizeof(TYPE_DATA); - int wSizeOut = SIZE; - int bSizeOut = wSizeOut * sizeof(TYPE_DATA); - -// std::cout << STR_INFO << "ARM sizeof(char) = " << sizeof(char) << std::endl; -// std::cout << STR_INFO << "ARM sizeof(short int) = " << sizeof(short int) << std::endl; -// std::cout << STR_INFO << "ARM sizeof(int) = " << sizeof(int) << std::endl; -// std::cout << STR_INFO << "ARM sizeof(long int) = " << sizeof(long int) << std::endl; -// std::cout << STR_INFO << "ARM sizeof(long long int) = " << sizeof(long long int) << std::endl; -// std::cout << STR_INFO << "ARM sizeof(float) = " << sizeof(float) << std::endl; -// std::cout << STR_INFO << "ARM sizeof(double) = " << sizeof(double) << std::endl; -/* - INFO: ARM sizeof(char) = 1 - INFO: ARM sizeof(short int) = 2 - INFO: ARM sizeof(int) = 4 - INFO: ARM sizeof(long int) = 8 - INFO: ARM sizeof(long long int) = 8 - INFO: ARM sizeof(float) = 4 - INFO: ARM sizeof(double) = 8 -*/ - std::cout << STR_INFO << "wSizeIn = " << wSizeIn << std::endl; - std::cout << STR_INFO << "wSizeOut = " << wSizeOut << std::endl; - std::cout << STR_INFO << "bSizeIn = " << bSizeIn << std::endl; - std::cout << STR_INFO << "bSizeOut = " << bSizeOut << std::endl; - - /* - // Chrono Timer Calibration - auto chrono_t0 = std::chrono::high_resolution_clock::now(); - auto chrono_t1 = std::chrono::high_resolution_clock::now(); - std::chrono::duration chrono_diff(0); - std::chrono::duration chrono_average_calibration(0); - for(int cnt = 0; cnt < CHRONO_CAL_ITERATIONS; cnt++) { - chrono_t0 = std::chrono::high_resolution_clock::now(); - chrono_t1 = std::chrono::high_resolution_clock::now(); - chrono_diff = chrono_t1 - chrono_t0; - chrono_average_calibration += chrono_diff; - } - chrono_average_calibration /= CHRONO_CAL_ITERATIONS; - std::cout << STR_CHRONO << "Average Calibration = " << chrono_average_calibration.count() << std::endl; - */ - - // Loading the xclbin - char* xclbinFilename = argv[1]; - unsigned int dev_index = 0; - auto my_device = xrt::device(dev_index); - std::cout << STR_PASSED << "auto my_device = xrt::device(" << dev_index << ")" << std::endl; - auto xclbin_uuid = my_device.load_xclbin(xclbinFilename); - std::cout << STR_PASSED << "auto xclbin_uuid = my_device.load_xclbin(" << xclbinFilename << ")" << std::endl; - - // Input mm2s kernel - std::cout << STR_INFO << "Opening the Input mm2s Kernel..." << std::endl; - auto in_0 = xrt::kernel(my_device, xclbin_uuid, "mm2s:{mm2s_1}"); - std::cout << STR_PASSED << "auto in_0 = xrt::kernel(my_device, xclbin_uuid, \"mm2s:{mm2s_1}\")" << std::endl; - auto in_0_bo = xrt::bo(my_device, bSizeIn, XCL_BO_FLAGS_NONE, in_0.group_id(0)); - std::cout << STR_PASSED << "auto in_0_bo = xrt::bo(my_device, bSizeIn, XCL_BO_FLAGS_NONE, in_0.group_id(0) (=" << in_0.group_id(0) << "))" << std::endl; - auto in_0_bo_mapped = in_0_bo.map(); - std::cout << STR_PASSED << "auto in_0_bo_mapped = in_0_bo.map()" << std::endl; - - // Populating Input Buffer with random data - std::cout << STR_INFO << "Setting Input Data " << std::endl; - TYPE_DATA *matOp1 = (TYPE_DATA *) malloc(bSizeIn); - TYPE_DATA *matOp2; matOp2 = matOp1 + wSizeIn/2; - TYPE_DATA *matRef = (TYPE_DATA *) malloc(bSizeOut); - union //PS: this conversion does not work if you used unsigned - { - TYPE_DATA i_val; - T f_val; - } converter; - FILE *fin1=fopen("matrix_inputs.txt", "w"); - srand(time(NULL)); // Initialization, should only be called once. - for(int r = 0; r(); - std::cout << STR_PASSED << "auto out_0_bo_mapped = out_0_bo.map()" << std::endl; - memset(out_0_bo_mapped, 0x0, bSizeOut); - - // Opening the matrix multiplier kernel - std::cout << STR_INFO << "Opening HLS Accel kernel " << std::endl; - auto my_krnl = xrt::kernel(my_device, xclbin_uuid, "HLS_accel"); - std::cout << STR_PASSED << "auto my_krnl = xrt::kernel(my_device, xclbin_uuid, \"HLS_accel\")" << std::endl; - - /* - chrono_t0 = std::chrono::high_resolution_clock::now(); - */ - // Start Input mm2s Kernel - std::cout << STR_INFO << "Starting Input mm2s Kernel..." << std::endl; - auto in_0_run = in_0(in_0_bo, nullptr, wSizeIn); - std::cout << STR_PASSED << "auto in_0_run = in_0(in_0_bo, nullptr, " << wSizeIn << ")" << std::endl; - // Starting the Output s2mm Kernels - std::cout << STR_INFO << "Starting Output s2mm Kernel..." << std::endl; - auto out_0_run = out_0(out_0_bo, nullptr, wSizeOut); - std::cout << STR_PASSED << "auto out_0_run = out(out_0_bo, nullptr, " << wSizeOut << ")" << std::endl; - // Starting the matrix multiplier kernel - std::cout << STR_INFO << "starting HLS Accel kernel " << std::endl; - auto my_krnl_run = my_krnl(nullptr, nullptr); - std::cout << STR_PASSED << "my_krnl_run" << std::endl; - - // Waiting for all kernels to end - std::cout << std::endl << STR_INFO << "Waiting for kernels to end..." << std::endl << std::endl; - in_0_run.wait(); - std::cout << STR_PASSED << "in_0_run.wait()" << std::endl; - my_krnl_run.wait(); - std::cout << STR_PASSED << "my_krnl_run.wait()" << std::endl; - out_0_run.wait(); - std::cout << STR_PASSED << "out_0_run.wait()" << std::endl; - - // Sync Output Buffers - std::cout << STR_INFO << "Sync Output Buffer..." << std::endl; - out_0_bo.sync(XCL_BO_SYNC_BO_FROM_DEVICE); - std::cout << STR_PASSED << "out_0_bo.sync(XCL_BO_SYNC_BO_FROM_DEVICE)" << std::endl; - - /* - chrono_t1 = std::chrono::high_resolution_clock::now(); - chrono_diff = chrono_t1 - chrono_t0 - chrono_average_calibration; - chrono_spend(chrono_diff.count(), "Run+Wait Kernels & Sync Output Buffer"); - */ - - // Verifying the results - std::cout << std::endl << STR_INFO << "Verifying output data vs. golden ones " << std::endl << std::endl; - FILE *fin3=fopen("matrix_out_bufs.txt", "w"); - int error_cnt = 0; - TYPE_DATA *golden; golden = matRef; - for(int i = 0; i < wSizeOut; i++) - { - if(out_0_bo_mapped[i] != golden[i]) - { - printf("Error found: @ %d, %d != %d\n", i, out_0_bo_mapped[i], golden[i]); - error_cnt++; - } - fprintf(fin3, "%d %d\n", out_0_bo_mapped[i], golden[i]); - } - fclose(fin3); - - //free memory - free(matRef); - free(matOp1); - - //close program - std::cout << std::endl << ( (error_cnt>0) ? STR_FAILED : STR_PASSED) << argv[0] << std::endl << std::endl; - return ( (error_cnt>0) ? EXIT_FAILURE : EXIT_SUCCESS ); -} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/Makefile b/Developer_Contributed/03-HLS_Code_Optimization/files/examples/Makefile deleted file mode 100644 index 9707d76290..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/examples/Makefile +++ /dev/null @@ -1,103 +0,0 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -SHELL := /bin/bash - -PHONY = clean all help -PHONY += hls_kernels hls_clean hls_all -PHONY += vadd_zcu012 mmult_zcu012 mmult_vck190 -PHONY += vadd_clean mmult_zclean mmult_vclean build_mult -.PHONY : $(PHONY) - - -ECHO = @echo -help:: - $(ECHO) "Makefile Usage:" - $(ECHO) " make all" - $(ECHO) " Command to generate everything for this design (both 9 Vitis HLS and 3 Vitis designs)" - $(ECHO) "" - $(ECHO) " make clean" - $(ECHO) " Command to remove all the above generated files." - $(ECHO) "" - $(ECHO) " make hls_all" - $(ECHO) " Command to run Vitis HLS only on the 9 examples." - $(ECHO) "" - $(ECHO) " make hls_clean" - $(ECHO) " Command to remove all the HLS generated files on the 9 examples." - $(ECHO) "" - $(ECHO) " make vadd_zcu102" - $(ECHO) " Command to build example8 VADD with Vitis flow for ZCU102." - $(ECHO) "" - $(ECHO) " make vadd_clean" - $(ECHO) " Command to clean the Vitis project of VADD." - $(ECHO) "" - $(ECHO) " make mmult_zcu102" - $(ECHO) " Command to build example9 MATRIX MULT with Vitis flow for ZCU102." - $(ECHO) "" - $(ECHO) " make mmult_zclean" - $(ECHO) " Command to clean the Vitis project of MATRIX MULT for ZCU102." - $(ECHO) "" - $(ECHO) " make mmult_vck190" - $(ECHO) " Command to build example9 MATRIX MULT with Vitis flow for VCK190." - $(ECHO) "" - $(ECHO) " make mmult_vclean" - $(ECHO) " Command to clean the Vitis project of MATRIX MULT for VCK190." - $(ECHO) "" - -vck190_clean: mmult_vclean -zcu102_clean: vadd_zclean mmult_zclean -clean: hls_clean zcu102_clean -#all: mmult_zcu102 hls_kernels vadd_zcu102 -all: hls_kernels2 -#vadd_zcu102 - -hls_clean: - $(MAKE) -C ./1_fix_fir_filter clean - $(MAKE) -C ./2_float_fir_filter clean - $(MAKE) -C ./3_img_median_filter clean - $(MAKE) -C ./4_dependency clean - $(MAKE) -C ./5_img_histEq clean - $(MAKE) -C ./6_sqrt clean - $(MAKE) -C ./7_atan2 clean - $(MAKE) -C ./8_vect_add clean - $(MAKE) -C ./9_matrix_mult_z clean - -hls_kernels: - $(MAKE) -C ./1_fix_fir_filter kernels - $(MAKE) -C ./2_float_fir_filter kernels - $(MAKE) -C ./3_img_median_filter kernels - $(MAKE) -C ./5_img_histEq kernels - $(MAKE) -C ./6_sqrt kernels - $(MAKE) -C ./7_atan2 kernels - $(MAKE) -C ./8_vect_add kernels - $(MAKE) -C ./9_matrix_mult_z kernels -#$(MAKE) -C ./4_dependency kernels - -hls_kernels2: - $(MAKE) -C ./8_vect_add hls_kernels - $(MAKE) -C ./9_matrix_mult_z hls_kernels - -vadd_zclean: - $(MAKE) -C ./8_vect_add zcu102_clean - -vadd_zcu102: - $(MAKE) -C ./8_vect_add zcu102_all - -mmult_zclean: - $(MAKE) -C ./9_matrix_mult_z zcu102_clean - -mmult_zcu102: - $(MAKE) -C ./9_matrix_mult_z zcu102_all - -show_dir_zcu102: - $(MAKE) -C ./9_matrix_mult_z show_dir - -# REMEMBER THAT VCK190 NEEDS DIFFERENT ENV FROM ZCU102 -mmult_vclean: - $(MAKE) -C ./9_matrix_mult_v vck190_clean - -mmult_vck190: - $(MAKE) -C ./9_matrix_mult_v vck190_all - -show_dir_vck190: - $(MAKE) -C ./9_matrix_mult_v show_dir diff --git 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./examples/8_vect_add/hls_vadd_prj/solution_vivado/.autopilot/db/load_input_1_Pipeline_mem_rd.compgen.dataonly.tcl to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/.autopilot/db/load_input_1_Pipeline_mem_rd.compgen.tcl to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/.autopilot/db/load_input_1.compgen.dataonly.tcl to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/.autopilot/db/load_input_1.compgen.tcl to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/.autopilot/db/compute_add_Pipeline_execute.compgen.dataonly.tcl to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/.autopilot/db/compute_add_Pipeline_execute.compgen.tcl to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/.autopilot/db/loop_info.csv to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/.autopilot/db/mapper_krnl_vadd.cpp to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/.autopilot/db/process_info.csv to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/.autopilot/db/store_result.compgen.dataonly.tcl to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/.autopilot/db/store_result.compgen.tcl to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/.autopilot/db/hls_design_meta.cpp to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/impl/misc/drivers/krnl_vadd_v1_0/src/xkrnl_vadd.c to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/impl/misc/drivers/krnl_vadd_v1_0/src/xkrnl_vadd_linux.c to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/impl/misc/drivers/krnl_vadd_v1_0/src/xkrnl_vadd_sinit.c to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/sim/autowrap/systemc/apatb_krnl_vadd.cpp to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/sim/autowrap/testbench/hls_krnl_vadd.cpp_pre.cpp to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/sim/autowrap/testbench/hls_krnl_vadd.cpp_pre.cpp.tb.cpp to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/sim/autowrap/testbench/hls_tb_vadd.cpp_pre.cpp to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/sim/autowrap/testbench/hls_tb_vadd.cpp_pre.cpp.tb.cpp to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/sim/wrapc/apatb_krnl_vadd.cpp to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/sim/wrapc/hls_krnl_vadd.cpp_pre.cpp.tb.cpp to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/sim/wrapc/hls_tb_vadd.cpp_pre.cpp.tb.cpp to Unix format... -dos2unix: Binary symbol 0x02 found at line 1 -dos2unix: Skipping binary file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/sim/wrapc/obj/hls_krnl_vadd.cpp_pre.cpp.tb.o -dos2unix: Binary symbol 0x02 found at line 1 -dos2unix: Skipping binary file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/sim/wrapc/obj/hls_tb_vadd.cpp_pre.cpp.tb.o -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/sim/wrapc_pc/apatb_krnl_vadd.cpp to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/sim/wrapc_pc/hls_krnl_vadd.cpp_pre.cpp.tb.cpp to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/sim/wrapc_pc/hls_tb_vadd.cpp_pre.cpp.tb.cpp to Unix format... -dos2unix: Binary symbol 0x02 found at line 1 -dos2unix: Skipping binary file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/sim/wrapc_pc/obj/hls_krnl_vadd.cpp_pre.cpp.tb.o -dos2unix: Binary symbol 0x02 found at line 1 -dos2unix: Skipping binary file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/sim/wrapc_pc/obj/hls_tb_vadd.cpp_pre.cpp.tb.o -dos2unix: converting file ./examples/8_vect_add/make-flow/zcu102_vadd_kernels/Hardware/krnl_vadd-compile.cfg to Unix format... -dos2unix: converting file ./examples/8_vect_add/make-flow/zcu102_vadd_system/Hardware/package.cfg to Unix format... -dos2unix: converting file ./examples/8_vect_add/make-flow/zcu102_vadd_system_hw_link/Hardware/binary_container_1-link.cfg to Unix format... -dos2unix: converting file ./examples/8_vect_add/src/hls/hls_krnl_vadd.cpp to Unix format... -dos2unix: converting file ./examples/8_vect_add/src/hls/hls_tb_vadd.cpp to Unix format... -dos2unix: converting file 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to Unix format... -dos2unix: converting file ./examples/1_fix_fir_filter/src/data/run_fir_filter.m to Unix format... -dos2unix: converting file ./examples/3_img_median_filter/src/test_data/medFilt_test_results.m to Unix format... -dos2unix: converting file ./examples/5_img_histEq/common/test_data/histEq_test_results.m to Unix format... -dos2unix: converting file ./examples/5_img_histEq/common/test_data/test_results.m to Unix format... -dos2unix: converting file ./examples/7_atan2/M/db_cordic_atan2.m to Unix format... -dos2unix: converting file ./examples/7_atan2/M/short_cpf_atan2.m to Unix format... -dos2unix: converting file ./examples/7_atan2/test_data/atan2_check_res.m to Unix format... -dos2unix: converting file ./examples/7_atan2/test_data/check_res.m to Unix format... -dos2unix: converting file ./examples/8_vect_add/vect_check_res.m to Unix format... -dos2unix: converting file ./examples/9_matrix_mult_v/check_mmult_results.m to Unix format... -dos2unix: converting file 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converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/.autopilot/db/entry_procap_header.systemc.txt.ap_header.txt to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/.autopilot/db/entry_procap_header.verilog.txt.ap_header.txt to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/.autopilot/db/entry_procap_header.vhdl.txt.ap_header.txt to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/csim/build/vector_inputs.txt to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/csim/build/vector_out.txt to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/sim/wrapc/vector_inputs.txt to Unix format... -dos2unix: converting file ./examples/8_vect_add/hls_vadd_prj/solution_vivado/sim/wrapc/vector_out.txt to Unix format... diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/run_all.sh b/Developer_Contributed/03-HLS_Code_Optimization/files/run_all.sh deleted file mode 100644 index 715e08837d..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/run_all.sh +++ /dev/null @@ -1,31 +0,0 @@ -#!/bin/bash - -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - - -# where you are -echo " " -echo "STARTING DIR IS: " $PWD -echo " " - -# clean file text formatting -rm -f ${PWD}/scripts/*~ -rm -f ${PWD}/examples/*~ -rm -f ${PWD}/*~ -rm -f ${PWD}/*.log -rm -f ${PWD}/scripts/#* - -: ' -dos2unix ${PWD}/run_all.sh -source ${PWD}/scripts/dos2unix_all.sh - - -export LIBRARY_PATH=/usr/lib/x86_64-linux-gnu - -## ZCU102 -source ${PWD}/scripts/zcu102_run_all.sh # XILINX-AMD GUUP SERVER - -## VCK190 -source ${PWD}/scripts/vck190_run_all.sh # XILINX-AMD GUUP SERVER -' diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/desktop_vck190_sample_env_setup.sh b/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/desktop_vck190_sample_env_setup.sh deleted file mode 100644 index 766121d8aa..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/desktop_vck190_sample_env_setup.sh +++ /dev/null @@ -1,143 +0,0 @@ -#!/bin/bash - -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -# Author: Daniele Bagni -# Date: 26 May 20223 - -###################################################################################### -# WARNING: THIS SCRIPT IS AN EXAMPLE FOR VERSAL ENV SETUP on A LINUX DESKTOP -###################################################################################### - - -# ======================================================= -# global variables for this tutorial -# ======================================================= -RELEASE=2025.1 -BOARD=vck190 -#BASE_NUM=202510_1 -BASE_NUM=202220_1 - -#TUTORIAL=AIE_DSP_with_Makefile_and_GUI_2023 -export TUTORIAL=03-HLS_Code_Optimization - -#export WRK_DIR=/media/danieleb/DATA/${RELEASE}/Vitis-Tutorials-${RELEASE}/Developer_Contributed -export WRK_DIR=/media/danieleb/DATA/2025.1/Vitis-Tutorials-2025.1/Developer_Contributed - - -# ======================================================= -# Set Platform, Vitis and Petalinux repo -# ======================================================= -#export PLATFORM_REPO_PATHS = -export PLATFORM_REPO_PATHS=/media/danieleb/DATA/${RELEASE}/tools/Xilinx/Vitis/${RELEASE}/base_platforms - -#export XILINX_VITIS = -export XILINX_VITIS=/media/danieleb/DATA/${RELEASE}/tools/Xilinx/Vitis/${RELEASE} - -#export PETALINUX = -export PETALINUX=/tools/Xilinx/PetaLinux/${RELEASE} - -# ================================================================================== -# Set Versal Common Image repo (OR eventually install it into /tmp) -# This local foldr must not be a "NFS" hard disk drive, only "ext4" is supported -# ================================================================================== - -# export TMP DIRECTORY= -mkdir -p /tmp/danieleb -export TMPDIR=/tmp/danieleb - - -##export COMMON_IMAGE_VERSAL= -export COMMON_IMAGE_VERSAL=${HOME}/common/xilinx-versal-common-v${RELEASE} - -: ' -## clean versal common image local folder content -rm -rf ${COMMON_IMAGE_VERSAL} -mkdir -p ${COMMON_IMAGE_VERSAL} - -## set the folder of Versal Common Image source files -##VERSAL_COMMON_2023v1=${PETALINUX}/../../bsp/internal/xilinx-versal-common-v${RELEASE}/ #only for GUUP -VERSAL_COMMON_2023v1=/opt/xilinx/common/xilinx-versal-common-v${RELEASE} -cd ${VERSAL_COMMON_2023v1} -## install Versal SDK on $HOME/common -./sdk.sh -y -p -d ${COMMON_IMAGE_VERSAL} -#copy the other files -cp bl31.elf boot.scr Image README.txt rootfs.ext4 rootfs.manifest u-boot.elf ${COMMON_IMAGE_VERSAL} -' - -##back to the wrk dir -cd ${WRK_DIR}/${TUTORIAL}/files/ - - -# ==================================================== -# Source Versal Image, Vitis and Aietools -# ==================================================== -unset LD_LIBRARY_PATH -source ${COMMON_IMAGE_VERSAL}/environment-setup-cortexa72-cortexa53-amd-linux -# Run the below command to setup environment and CXX -source ${XILINX_VITIS}/settings64.sh - -# ======================================================== -# Set DSP Library for Vitis -# ======================================================== -#export DSPLIB_ROOT= -export DSPLIB_VITIS=/media/danieleb/DATA/${RELEASE}/Vitis_Libraries-main -export DSPLIB_ROOT=${DSPLIB_VITIS}/dsp - - -# ========================================================= -# Platform Selection... -# ========================================================= -#tgt_plat=xilinx_vck190_base_202220_1 -#export PLATFORM=$PLATFORM_REPO_PATHS/$tgt_plat/$tgt_plat\.xpfm - -export VERSAL_VITIS_PLATFORM=xilinx_${BOARD}\_base_${BASE_NUM} -export VITIS_PLATFORM_DIR=${PLATFORM_REPO_PATHS}/${VERSAL_VITIS_PLATFORM} -export VITIS_PLATFORM_XPFM=${VITIS_PLATFORM_DIR}/${VERSAL_VITIS_PLATFORM}.xpfm - -# ======================================================== -# Set SysRoot, RootFS and Image -# ======================================================== -export VITIS_SYSROOTS=${COMMON_IMAGE_VERSAL}/sysroots/cortexa72-cortexa53-amd-linux -export SDKTARGETSYSROOT=${VITIS_SYSROOTS} -export KERNEL_IMAGE=${COMMON_IMAGE_VERSAL}/Image -export ROOTFS=${COMMON_IMAGE_VERSAL}/rootfs.ext4 - -# ======================================================== -# for compatibility with official Vitis Tutorials -# ======================================================== -export XLNX_VERSAL=${COMMON_IMAGE_VERSAL} -export PLATFORM=${VITIS_PLATFORM_XPFM} - - -# ======================================================== -# check env variables -# ======================================================== -echo " " -echo "Vitis/Petalinux GUUP Environmental variables" -echo " " -echo "LD_LIBRARY_PATH " $LD_LIBRARY_PATH -echo "XILINX_VITIS " $XILINX_VITIS -echo "BSP_DIR " $BSP_DIR -#echo "PETALINUX_VER " $PETALINUX_VER -echo "PLATFORM_REPO_PATHS " $PLATFORM_REPO_PATHS -echo "XILINX_XRT " $XILINX_XRT -echo "XILINX_VIVADO " $XILINX_VIVADO -#echo "XILINXD_LICENSE_FILE " $XILINXD_LICENSE_FILE -echo "XILINX_HLS " $XILINX_HLS -#echo "XSCT_TOOLCHAIN" $XSCT_TOOLCHAIN -#echo "XDG_DATA_DIRS " $XDG_DATA_DIRS -#echo "GUUP_ROOT " $GUUP_ROOT -echo "SHELL " $SHELL -#echo "LM_LICENSE_FILE " $LM_LICENSE_FILE -#echo "PYTHONPATH " $PYTHONPATH -#echo "PETALINUX_MAJOR_VER " $PETALINUX_MAJOR_VER -echo "PETALINUX " $PETALINUX -echo "SDKTARGETSYSROOT " ${VITIS_SYSROOTS} -echo "VERSAL_COMMON_2023v1 " ${VERSAL_COMMOM_2023v1} -echo "COMMON_IMAGE_VERSAL " ${COMMON_IMAGE_VERSAL} -echo "KERNEL_IMAGE " ${KERNEL_IMAGE} -echo "ROOTFS " ${ROOTFS} -echo "VITIS_PLATFORM_XPFM " ${VITIS_PLATFORM_XPFM} -#echo "PATH " ${PATH} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/desktop_zcu102_sample_env_setup.sh b/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/desktop_zcu102_sample_env_setup.sh deleted file mode 100644 index 1d2c083bdc..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/desktop_zcu102_sample_env_setup.sh +++ /dev/null @@ -1,144 +0,0 @@ -#!/bin/bash - -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -# Author: Daniele Bagni -# Date: 26 May 20223 - -###################################################################################### -# WARNING: THIS SCRIPT IS AN EXAMPLE FOR ZCU102 ENV SETUP on A LINUX DESKTOP -###################################################################################### - - - -# ======================================================= -# global variables for this tutorial -# ======================================================= -RELEASE=2025.1 -BOARD=zcu102 -#BASE_NUM=202510_1 -BASE_NUM=202220_1 - -#TUTORIAL=AIE_DSP_with_Makefile_and_GUI_2023 -export TUTORIAL=03-HLS_Code_Optimization - -#export WRK_DIR=/media/danieleb/DATA/${RELEASE}/Vitis-Tutorials-${RELEASE}/Developer_Contributed -export WRK_DIR=/media/danieleb/DATA/2025.1/Vitis-Tutorials-2025.1/Developer_Contributed - - -# ======================================================= -# Set Platform, Vitis and Petalinux repo -# ======================================================= -#export PLATFORM_REPO_PATHS = -export PLATFORM_REPO_PATHS=/media/danieleb/DATA/${RELEASE}/tools/Xilinx/Vitis/${RELEASE}/base_platforms - -#export XILINX_VITIS = -export XILINX_VITIS=/media/danieleb/DATA/${RELEASE}/tools/Xilinx/Vitis/${RELEASE} - -#export PETALINUX = -export PETALINUX=/tools/Xilinx/PetaLinux/${RELEASE} - -# ================================================================================== -# Set Versal Common Image repo (OR eventually install it into /tmp) -# This local foldr must not be a "NFS" hard disk drive, only "ext4" is supported -# ================================================================================== - -# export TMP DIRECTORY= -mkdir -p /tmp/danieleb -export TMPDIR=/tmp/danieleb - - -##export COMMON_IMAGE_ZYNQMP= -export COMMON_IMAGE_ZYNQMP=${HOME}/common/xilinx-zynqmp-common-v${RELEASE} - -: ' -## clean ZYNQMP common image local folder content -rm -rf ${COMMON_IMAGE_ZYNQMP} -mkdir -p ${COMMON_IMAGE_ZYNQMP} - -## set the folder of ZYNQMP Common Image source files -##ZYNQMP_COMMON_2023v1=${PETALINUX}/../../bsp/internal/xilinx-zynqmp-common-v${RELEASE}/ #only for GUUP -ZYNQMP_COMMON_2023v1=/opt/xilinx/common/xilinx-zynqmp-common-v${RELEASE} -cd ${ZYNQMP_COMMON_2023v1} -## install ZYNQMP SDK on $HOME/common -./sdk.sh -y -p -d ${COMMON_IMAGE_ZYNQMP} -#copy the other files -cp bl31.elf boot.scr Image README.txt rootfs.ext4 rootfs.manifest u-boot.elf ${COMMON_IMAGE_ZYNQMP} -' - -##back to the wrk dir -cd ${WRK_DIR}/${TUTORIAL}/files/ - - -# ==================================================== -# Source Versal Image, Vitis and Aietools -# ==================================================== -unset LD_LIBRARY_PATH -source ${COMMON_IMAGE_ZYNQMP}/environment-setup-cortexa72-cortexa53-amd-linux -# Run the below command to setup environment and CXX -source ${XILINX_VITIS}/settings64.sh - -# ======================================================== -# Set DSP Library for Vitis -# ======================================================== -#export DSPLIB_ROOT= -export DSPLIB_VITIS=/media/danieleb/DATA/${RELEASE}/Vitis_Libraries-main -export DSPLIB_ROOT=${DSPLIB_VITIS}/dsp - - -# ========================================================= -# Platform Selection... -# ========================================================= -#tgt_plat=xilinx_vck190_base_202220_1 -#export PLATFORM=$PLATFORM_REPO_PATHS/$tgt_plat/$tgt_plat\.xpfm - -export ZYNQMP_VITIS_PLATFORM=xilinx_${BOARD}\_base_${BASE_NUM} -export VITIS_PLATFORM_DIR=${PLATFORM_REPO_PATHS}/${ZYNQMP_VITIS_PLATFORM} -export VITIS_PLATFORM_XPFM=${VITIS_PLATFORM_DIR}/${ZYNQMP_VITIS_PLATFORM}.xpfm - -# ======================================================== -# Set SysRoot, RootFS and Image -# ======================================================== -export VITIS_SYSROOTS=${COMMON_IMAGE_ZYNQMP}/sysroots/cortexa72-cortexa53-amd-linux -export SDKTARGETSYSROOT=${VITIS_SYSROOTS} -export KERNEL_IMAGE=${COMMON_IMAGE_ZYNQMP}/Image -export ROOTFS=${COMMON_IMAGE_ZYNQMP}/rootfs.ext4 - -# ======================================================== -# for compatibility with official Vitis Tutorials -# ======================================================== -export XLNX_ZYNQMP=${COMMON_IMAGE_ZYNQMP} -export PLATFORM=${VITIS_PLATFORM_XPFM} - - -# ======================================================== -# check env variables -# ======================================================== -echo " " -echo "Vitis/Petalinux GUUP Environmental variables" -echo " " -echo "LD_LIBRARY_PATH " $LD_LIBRARY_PATH -echo "XILINX_VITIS " $XILINX_VITIS -echo "BSP_DIR " $BSP_DIR -#echo "PETALINUX_VER " $PETALINUX_VER -echo "PLATFORM_REPO_PATHS " $PLATFORM_REPO_PATHS -echo "XILINX_XRT " $XILINX_XRT -echo "XILINX_VIVADO " $XILINX_VIVADO -#echo "XILINXD_LICENSE_FILE " $XILINXD_LICENSE_FILE -echo "XILINX_HLS " $XILINX_HLS -#echo "XSCT_TOOLCHAIN" $XSCT_TOOLCHAIN -#echo "XDG_DATA_DIRS " $XDG_DATA_DIRS -#echo "GUUP_ROOT " $GUUP_ROOT -echo "SHELL " $SHELL -#echo "LM_LICENSE_FILE " $LM_LICENSE_FILE -#echo "PYTHONPATH " $PYTHONPATH -#echo "PETALINUX_MAJOR_VER " $PETALINUX_MAJOR_VER -echo "PETALINUX " $PETALINUX -echo "SDKTARGETSYSROOT " ${VITIS_SYSROOTS} -echo "ZYNQMP_COMMON_2023v1 " ${ZYNQMP_COMMOM_2023v1} -echo "COMMON_IMAGE_ZYNQMP " ${COMMON_IMAGE_ZYNQMP} -echo "KERNEL_IMAGE " ${KERNEL_IMAGE} -echo "ROOTFS " ${ROOTFS} -echo "VITIS_PLATFORM_XPFM " ${VITIS_PLATFORM_XPFM} -#echo "PATH " ${PATH} diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/dos2unix_all.sh b/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/dos2unix_all.sh deleted file mode 100644 index 9de817b392..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/dos2unix_all.sh +++ /dev/null @@ -1,15 +0,0 @@ -#!/bin/bash - -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -# Dos2Unix conversion just to avoid any trouble with file formats -for file in $(find . -name "*.sh" ); do dos2unix ${file}; done -for file in $(find . -name "*.tcl"); do dos2unix ${file}; done -for file in $(find . -name "*.h" ); do dos2unix ${file}; done -for file in $(find . -name "config" ); do dos2unix ${file}; done -for file in $(find . -name "*.c*" ); do dos2unix ${file}; done -for file in $(find . -name "*.m" ); do dos2unix ${file}; done -for file in $(find . -name "*.dat" ); do dos2unix ${file}; done -for file in $(find . -name "*.txt" ); do dos2unix ${file}; done -for file in $(find . -name "*akefile" ); do dos2unix ${file}; done diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/env_setup.sh b/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/env_setup.sh deleted file mode 100644 index 0ca865fba2..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/env_setup.sh +++ /dev/null @@ -1,34 +0,0 @@ -#!/bin/bash - -# Report current shell -current_shell=$(echo $0) -echo "[env_setup.sh] Current shell: $current_shell" -if [ "$current_shell" = "-bash" ]; then - # Print Bash version - echo "[env_setup.sh] Bash version: $BASH_VERSION" -fi - -# Vitis Libraries -#export DSPLIB_VITIS=/proj/xtools/xilinx_central_repo/Vitis_Libraries -# Point to the Vitis Libraries HEAD -# DB: commented by me -#export DSPLIB_VITIS=/proj/xtools/xilinx_central_repo/FaaSApps_next -#export DSPLIB_ROOT=${DSPLIB_VITIS}/dsp - -# GHE Repo URL for CI -export DEVICE_TREE_REPO=https://gitenterprise.xilinx.com/Linux/device-tree-xlnx.git -export ATF_REPO=https://gitenterprise.xilinx.com/Linux/arm-trusted-firmware.git -export UBOOT_REPO=https://github.com/Xilinx/u-boot-xlnx -#REPO for Embd_Sw/F/01 -export ATF_CHECKOUT=master -export UBOOT_CHECKOUT=master - -# Add CMake to PATH -export PATH=${XILINX_VITIS}/tps/lnx64/cmake-3.3.2/bin:$PATH - -# Add git to PATH -export PATH=${XILINX_VITIS}/tps/lnx64/git-2.41.0/bin:$PATH - -# Update Perl Version -source perl.sh - diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/env_setup_petalinux.sh b/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/env_setup_petalinux.sh deleted file mode 100644 index 9f6b405fdc..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/env_setup_petalinux.sh +++ /dev/null @@ -1,29 +0,0 @@ -#!/bin/bash -# ------------------------- -# Setup common environments -# - Vitis Library Path -# ------------------------- -#source env_setup.sh - - - -# ------------------------------- -# Environment Setup for PetaLinux -# ------------------------------- - -# A tutorial either uses the pre-built SDK toolchain or the PetaLinux to build things from scratch. - -export BSP_DIR=/proj/petalinux/2025.1/petalinux-v2025.1_daily_latest/bsp/release -export PETALINUX=/proj/petalinux/2025.1/petalinux-v2025.1_daily_latest/tool/petalinux-v2025.1-final - - -source $PETALINUX/settings.sh - - -# ------------------------- -# The following Env Var are provided by Regression Framework. No need to setup manually -# - XILINX_VITIS -# - XILINX_VIVADO -# - XILINX_HLS -# - PLATFORM_REPO_PATHS -# ------------------------- diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/env_setup_petalinux_versal.sh b/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/env_setup_petalinux_versal.sh deleted file mode 100644 index 305e750cd3..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/env_setup_petalinux_versal.sh +++ /dev/null @@ -1,42 +0,0 @@ -#!/bin/bash -#!/bin/bash -# ------------------------- -# Use PetaLinux toolset -# Setup common image path COMMON_IMAGE_VERSAL -# ------------------------- - - - - - -# ------------------------- -# Setup common environments -# - Vitis Library Path -# ------------------------- -source env_setup.sh - - - -# ------------------------------- -# Environment Setup for PetaLinux -# ------------------------------- - -# A tutorial either uses the pre-built SDK toolchain or the PetaLinux to build things from scratch. - -source env_setup_petalinux.sh - -# ------------------------------- -# Versal Common Image Path -# ------------------------------- - -export COMMON_IMAGE_VERSAL=/proj/xbb/xrt-embedded/2025.1/sw/latest/sysroot/versal/xilinx-versal-common-v2025.1 -echo Setting Up COMMON_IMAGE_VERSAL=$COMMON_IMAGE_VERSAL - - -# ------------------------- -# The following Env Var are provided by Regression Framework. No need to setup manually -# - XILINX_VITIS -# - XILINX_VIVADO -# - XILINX_HLS -# - PLATFORM_REPO_PATHS -# ------------------------- diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/env_setup_petalinux_zynqmp.sh b/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/env_setup_petalinux_zynqmp.sh deleted file mode 100644 index 27bb58603e..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/env_setup_petalinux_zynqmp.sh +++ /dev/null @@ -1,40 +0,0 @@ -#!/bin/bash -# ------------------------- -# Use PetaLinux toolset -# Setup common image path COMMON_IMAGE_ZYNQMP -# ------------------------- - - - - -# ------------------------- -# Setup common environments -# - Vitis Library Path -# ------------------------- -source env_setup.sh - - - -# ------------------------------- -# Environment Setup for PetaLinux -# ------------------------------- - -# A tutorial either uses the pre-built SDK toolchain or the PetaLinux to build things from scratch. - -source env_setup_petalinux.sh - -# ------------------------------- -# Versal Common Image Path -# ------------------------------- - -export COMMON_IMAGE_ZYNQMP=/proj/xbb/xrt-embedded/2025.1/sw/latest/sysroot/zynqmp/xilinx-zynqmp-common-v2025.1 -echo Setting Up COMMON_IMAGE_ZYNQMP=$COMMON_IMAGE_ZYNQMP - - -# ------------------------- -# The following Env Var are provided by Regression Framework. No need to setup manually -# - XILINX_VITIS -# - XILINX_VIVADO -# - XILINX_HLS -# - PLATFORM_REPO_PATHS -# ------------------------- diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/guupServer_vck190_sample_env_setup.sh b/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/guupServer_vck190_sample_env_setup.sh deleted file mode 100644 index 8b3f8d4de6..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/guupServer_vck190_sample_env_setup.sh +++ /dev/null @@ -1,133 +0,0 @@ -#!/bin/bash - -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -# Author: Daniele Bagni -# Date: 03 Sep 2024 - -###################################################################################### -# WARNING: THIS SCRIPT IS VALID ONLY FOR VCK190 on AMD/XILINX GUUP (LINUX) SERVERS -###################################################################################### - -# ======================================================= -# GUUP Environment Setup: -# set Platform, Vitis and Petalinux repo -# ======================================================= -#ts 2025.1_daily_latest -petalinux petalinux-v2025.1_daily_latest -#ts 2025.1_released -petalinux petalinux-v2025.1_daily_latest - - -export CUR_DIR=$PWD - -# ======================================================= -# global variables for this tutorial -# ======================================================= -#RELEASE= -RELEASE=2025.1 -BOARD=vck190 -BASE_NUM=202510_1 -#BASE_NUM=202510_1 - -export WRK_DIR=/group/xirguup/danieleb/ide2025.1/Vitis-Tutorials/Developer_Contributed -export TUTORIAL=03-HLS_Code_Optimization - - -# ======================================================= -# to emulate SPRITE regression env in GUUP Servers -# ======================================================= -#cd ${WRK_DIR}/../Vitis-Tutorials-Admin-2025.1_next -source ./env_setup_petalinux_versal.sh -##back to the wrk dir -#cd ${WRK_DIR}/${TUTORIAL}/files/ - -#================================================================================== -# Set Versal Common Image repo (OR eventually install it into /tmp) -# This local foldr must not be a "NFS" hard disk drive, only "ext4" is supported -# ================================================================================== - -# export TMP DIRECTORY= -mkdir -p /tmp/danieleb -export TMPDIR=/tmp/danieleb - -# PETALINUX and VERSAL COMMON IMAGE -export COMMON_IMAGE_VERSAL=${HOME}/common/xilinx-versal-common-v2025.1 - -: ' -# do it only once -# clean versal folder content -rm -rf ${COMMON_IMAGE_VERSAL} -# install SDK -export VERSAL_COMMON_2023v2=$PETALINUX/../../bsp/internal/xilinx-versal-common-v2025.1/ -cd ${VERSAL_COMMON_2023v2} -bash ./sdk.sh -y -p -d ${COMMON_IMAGE_VERSAL} -cp bl31.elf boot.scr Image README.txt rootfs.ext4 rootfs.manifest u-boot.elf ${COMMON_IMAGE_VERSAL}/ -' -cd ${WRK_DIR}/${TUTORIAL}/files - - -# ======================================================== -# Set DSP Library for Vitis -# ======================================================== -## already set in "env_setup.sh" but not yet available in EMEA servers -#export DSPLIB_ROOT= -export DSPLIB_VITIS=/group/xirguup/danieleb/ide2025.1/Vitis_Libraries -#export DSPLIB_VITIS=/group/xirguup/danieleb/ide2022.2/Vitis_Libraries -export DSPLIB_ROOT=${DSPLIB_VITIS}/dsp - - -# ========================================================= -# Platform Selection... -# ========================================================= -export VERSAL_VITIS_PLATFORM=xilinx_${BOARD}\_base_${BASE_NUM} -export VITIS_PLATFORM_DIR=${PLATFORM_REPO_PATHS}/${VERSAL_VITIS_PLATFORM} -export VITIS_PLATFORM_XPFM=${VITIS_PLATFORM_DIR}/${VERSAL_VITIS_PLATFORM}.xpfm - -# ======================================================== -# Set SysRoot, RootFS and Image -# ======================================================== -export VITIS_SYSROOTS=${COMMON_IMAGE_VERSAL}/sysroots/cortexa72-cortexa53-amd-linux -export SDKTARGETSYSROOT=${VITIS_SYSROOTS} -export KERNEL_IMAGE=${COMMON_IMAGE_VERSAL}/Image -export ROOTFS=${COMMON_IMAGE_VERSAL}/rootfs.ext4 - -# ======================================================== -# for compatibility with official Vitis Tutorials -# ======================================================== -export XLNX_VERSAL=${COMMON_IMAGE_VERSAL} -export PLATFORM=${VITIS_PLATFORM_XPFM} - -# ======================================================== -# check env variables -# ======================================================== -echo " " -echo "Vitis/Petalinux GUUP Environmental variables" -echo " " -echo "LD_LIBRARY_PATH " $LD_LIBRARY_PATH -echo "XILINX_VITIS " $XILINX_VITIS -echo "BSP_DIR " $BSP_DIR -#echo "PETALINUX_VER " $PETALINUX_VER -echo "PLATFORM_REPO_PATHS " $PLATFORM_REPO_PATHS -echo "XILINX_XRT " $XILINX_XRT -echo "XILINX_VIVADO " $XILINX_VIVADO -#echo "XILINXD_LICENSE_FILE " $XILINXD_LICENSE_FILE -echo "XILINX_HLS " $XILINX_HLS -#echo "XSCT_TOOLCHAIN" $XSCT_TOOLCHAIN -#echo "XDG_DATA_DIRS " $XDG_DATA_DIRS -#echo "GUUP_ROOT " $GUUP_ROOT -echo "SHELL " $SHELL -#echo "LM_LICENSE_FILE " $LM_LICENSE_FILE -#echo "PYTHONPATH " $PYTHONPATH -#echo "PETALINUX_MAJOR_VER " $PETALINUX_MAJOR_VER -echo "PETALINUX " $PETALINUX -echo "SDKTARGETSYSROOT " ${VITIS_SYSROOTS} -echo "VERSAL_COMMON_2023v1 " ${VERSAL_COMMOM_2023v1} -echo "COMMON_IMAGE_VERSAL " ${COMMON_IMAGE_VERSAL} -echo "SDKTARGETSYSROOT " ${VITIS_SYSROOTS} -echo "VITIS_PLATFORM_XPFM " ${VITIS_PLATFORM_XPFM} -echo "KERNEL_IMAGE " ${KERNEL_IMAGE} -echo "ROOTFS " ${ROOTFS} -echo "VITIS_PLATFORM_XPFM " ${VITIS_PLATFORM_XPFM} -echo "PLATFORM_REPO_PATHS " ${PLATFORM_REPO_PATHS} -#echo "PATH " ${PATH} -echo "DSPLIB_ROOT " ${DSPLIB_VITIS}/dsp diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/guupServer_zcu102_sample_env_setup.sh b/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/guupServer_zcu102_sample_env_setup.sh deleted file mode 100644 index 59f703315c..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/guupServer_zcu102_sample_env_setup.sh +++ /dev/null @@ -1,130 +0,0 @@ -#!/bin/bash - -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -# Author: Daniele Bagni -# Date: 03 Sep 2024 - -###################################################################################### -# WARNING: THIS SCRIPT IS VALID ONLY FOR ZCU102 on AMD/XILINX GUUP (LINUX) SERVERS -###################################################################################### - -# ======================================================= -# GUUP Environment Setup: -# set Platform, Vitis and Petalinux repo -# ======================================================= -#ts 2025.1_daily_latest -petalinux petalinux-v2025.1_daily_latest - -export CUR_DIR=$PWD - -# ======================================================= -# global variables for this tutorial -# ======================================================= -#RELEASE= -RELEASE=2025.1 -BOARD=zcu102 -BASE_NUM=202510_1 -#BASE_NUM=202510_1 - -export WRK_DIR=/group/xirguup/danieleb/ide2025.1/Vitis-Tutorials/Developer_Contributed -export TUTORIAL=03-HLS_Code_Optimization - -# ======================================================= -# to emulate SPRITE regression env in GUUP Servers -# ======================================================= -#cd ${WRK_DIR}/../../Vitis-Tutorials-Admin -source ./env_setup_petalinux_zynqmp.sh -##back to the wrk dir -#cd ${WRK_DIR}/${TUTORIAL}/files - -#================================================================================== -# Set ZCU102 Common Image repo (OR eventually install it into /tmp) -# This local foldr must not be a "NFS" hard disk drive, only "ext4" is supported -# ================================================================================== - -# export TMP DIRECTORY= -mkdir -p /tmp/danieleb -export TMPDIR=/tmp/danieleb - -# PETALINUX and ZYNQMP COMMON IMAGE -export COMMON_IMAGE_ZYNQMP=${HOME}/common/xilinx-zynqmp-common-v2025.1 - -: ' -# install Versal SDK on $HOME/common -echo " " -echo "NOW INSTALLING ZCU102 SDK in $HOME/common " -echo " " -export ZYNQMP_COMMON_2023v2=$PETALINUX/../../bsp/internal/xilinx-zynqmp-common-v2025.1/ -# clean zynqmp folder content -rm -rf ${COMMON_IMAGE_ZYNQMP} -# install SDK -cd ${ZYNQMP_COMMON_2023v2} -bash ./sdk.sh -y -p -d ${COMMON_IMAGE_ZYNQMP} -cp bl31.elf boot.scr Image README.txt rootfs.ext4 rootfs.manifest u-boot.elf ${COMMON_IMAGE_ZYNQMP}/ -' - -# ======================================================== -# Set DSP Library for Vitis -# ======================================================== -## already set in "env_setup.sh" but not yet available in EMEA servers -#export DSPLIB_ROOT= -export DSPLIB_VITIS=/group/xirguup/danieleb/ide2025.1/Vitis_Libraries -export DSPLIB_ROOT=${DSPLIB_VITIS}/dsp - - -# ========================================================= -# Platform Selection... -# ========================================================= -export ZYNQMP_VITIS_PLATFORM=xilinx_${BOARD}\_base_${BASE_NUM} -export VITIS_PLATFORM_DIR=${PLATFORM_REPO_PATHS}/${VERSAL_VITIS_PLATFORM} -export VITIS_PLATFORM_XPFM=${VITIS_PLATFORM_DIR}/${VERSAL_VITIS_PLATFORM}.xpfm - -# ======================================================== -# Set SysRoot, RootFS and Image -# ======================================================== -export VITIS_SYSROOTS=${COMMON_IMAGE_VERSAL}/sysroots/cortexa72-cortexa53-amd-linux -export SDKTARGETSYSROOT=${VITIS_SYSROOTS} -export KERNEL_IMAGE=${COMMON_IMAGE_VERSAL}/Image -export ROOTFS=${COMMON_IMAGE_VERSAL}/rootfs.ext4 - -# ======================================================== -# for compatibility with official Vitis Tutorials -# ======================================================== -#export XLNX_VERSAL=${COMMON_IMAGE_VERSAL} -export PLATFORM=${VITIS_PLATFORM_XPFM} - -# ======================================================== -# check env variables -# ======================================================== -echo " " -echo "Vitis/Petalinux GUUP Environmental variables" -echo " " -echo "LD_LIBRARY_PATH " $LD_LIBRARY_PATH -echo "XILINX_VITIS " $XILINX_VITIS -echo "BSP_DIR " $BSP_DIR -#echo "PETALINUX_VER " $PETALINUX_VER -echo "PLATFORM_REPO_PATHS " $PLATFORM_REPO_PATHS -echo "XILINX_XRT " $XILINX_XRT -echo "XILINX_VIVADO " $XILINX_VIVADO -#echo "XILINXD_LICENSE_FILE " $XILINXD_LICENSE_FILE -echo "XILINX_HLS " $XILINX_HLS -#echo "XSCT_TOOLCHAIN" $XSCT_TOOLCHAIN -#echo "XDG_DATA_DIRS " $XDG_DATA_DIRS -#echo "GUUP_ROOT " $GUUP_ROOT -echo "SHELL " $SHELL -#echo "LM_LICENSE_FILE " $LM_LICENSE_FILE -#echo "PYTHONPATH " $PYTHONPATH -#echo "PETALINUX_MAJOR_VER " $PETALINUX_MAJOR_VER -echo "PETALINUX " $PETALINUX -echo "SDKTARGETSYSROOT " ${VITIS_SYSROOTS} -echo "ZYNQMP_COMMON_2023v1 " ${ZYNQMP_COMMOM_2023v1} -echo "COMMON_IMAGE_ZYNQMP " ${COMMON_IMAGE_ZYNQMP} -echo "SDKTARGETSYSROOT " ${VITIS_SYSROOTS} -echo "VITIS_PLATFORM_XPFM " ${VITIS_PLATFORM_XPFM} -echo "KERNEL_IMAGE " ${KERNEL_IMAGE} -echo "ROOTFS " ${ROOTFS} -echo "VITIS_PLATFORM_XPFM " ${VITIS_PLATFORM_XPFM} -echo "PLATFORM_REPO_PATHS " ${PLATFORM_REPO_PATHS} -#echo "PATH " ${PATH} -echo "DSPLIB_ROOT " ${DSPLIB_VITIS}/dsp diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/vck190_run_all.sh b/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/vck190_run_all.sh deleted file mode 100644 index b23c638af6..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/vck190_run_all.sh +++ /dev/null @@ -1,22 +0,0 @@ -#!/bin/bash - -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -# clean file text formatting -##source ./scripts/dos2unix_all.sh -#echo " " -#echo "CURRENT DIR IS: " $PWD -#echo " " - -# set the environment (GUUP) for VCK190 -#source ${PWD}/scripts/desktop_vck190_sample_env_setup.sh # XILINX-AMD GUUP SERVER -cd ${PWD}/scripts -source ./guupServer_vck190_sample_env_setup.sh - -cd ${PWD}/examples -#make mmult_vclean -make mmult_vck190 - -# to finish -cd .. diff --git a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/zcu102_run_all.sh b/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/zcu102_run_all.sh deleted file mode 100644 index bb9128ffa7..0000000000 --- a/Developer_Contributed/03-HLS_Code_Optimization/files/scripts/zcu102_run_all.sh +++ /dev/null @@ -1,31 +0,0 @@ -#!/bin/bash - -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -# ZCU102 -# set the environment (GUUP) for ZCU102 -#source ${PWD}/scripts/desktop_zcu102_sample_env_setup.sh # XILINX-AMD GUUP SERVER -cd ${PWD}/scripts - -source ./guupServer_zcu102_sample_env_setup.sh - - -# run all HLS examples -cd ${PWD}/../examples -make clean -make hls_kernels - -# Vitis Acceleration designs -cd ${PWD}/examples - -# vector add -make vadd_zclean -make vadd_zcu102 - -# matrix mult -#make mmult_zclean -make mmult_zcu102 - -# to finish -cd .. diff --git a/Embedded_Software/Embedded_Software.rst b/Embedded_Software/Embedded_Software.rst index 1b44ef7409..d778d8cc37 100644 --- a/Embedded_Software/Embedded_Software.rst +++ b/Embedded_Software/Embedded_Software.rst @@ -60,27 +60,28 @@ The :doc:`./docs/Feature_Tutorials/Feature_Tutorials` illustrate specific featur * - Feature Tutorial - Design Target - * - :doc:`./docs/Feature_Tutorials/03-vitis_classic_to_unified_migration/README` + * - :doc:`User Managed Mode in Vitis Unified IDE <./docs/Feature_Tutorials/01-user_managed_mode/README>` + - Introduces how command line users can make use of Vitis Unified IDE to debug their applications in GUI and how to quickly call makefile actions. + + * - :doc:`Migrating from classic Vitis IDE to Vitis Unified IDE <./docs/Feature_Tutorials/03-vitis_classic_to_unified_migration/README>` - Demonstrates the migration steps and deep dive into the details about hardware to software handoff metadata, how to migrate libraries and drivers. - * - :doc:`./docs/Feature_Tutorials/04-vitis_scripting_flows/README` + * - :doc:`Vitis Embedded Scripting Flow <./docs/Feature_Tutorials/04-vitis_scripting_flows/README>` - Demonstrates how to automate GUI steps with scripts for both project management and debugging. - - * - :doc:`./docs/Feature_Tutorials/01-user_managed_mode/README` - - Introduces how command line users can make use of Vitis Unified IDE to debug their applications in GUI and how to quickly call makefile actions. - - * - :doc:`./docs/Feature_Tutorials/02-Debugging/README` + + * - :doc:`Vitis Embedded Software Debugging Guide <./docs/Feature_Tutorials/02-Debugging/README>` - This tutorial demonstrates different debugging features available within the Vitis Embedded software development flow for bare-metal and Linux applications. It also introduces the flow to create a debuggable FSBL and how to do cross triggering in the Vitis Unified IDE. + * - :doc:`Vitis Version Control Guide <./docs/Feature_Tutorials/05-vitis_version_control/README>` + - This tutorial demonstrates the available version control features in the Vitis Unified IDE. It introduces how you can use git to manage your Vitis workspace and share your projects between teams. -.. sidebar:: More Information - - See AMD Vitis™ Development Environment on `xilinx.com `_ +.. sidebar:: More Information + See Vitis™ Development Environment on `amd.com `_ -.. Copyright © 2020–2024 Advanced Micro Devices, Inc +.. Copyright © 2020–2025 Advanced Micro Devices, Inc -.. `Terms and Conditions `_. \ No newline at end of file +.. `Terms and Conditions `_. diff --git a/Embedded_Software/Feature_Tutorials/01-user_managed_mode/README.md b/Embedded_Software/Feature_Tutorials/01-user_managed_mode/README.md index adf0247135..9aa500eff1 100644 --- a/Embedded_Software/Feature_Tutorials/01-user_managed_mode/README.md +++ b/Embedded_Software/Feature_Tutorials/01-user_managed_mode/README.md @@ -13,7 +13,7 @@ # User Managed Mode in Vitis Unified Embedded IDE -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** This is a new feature with the Vitis Unified Embedded IDE, where users can add a makefile and argument that can be used to create custom builds. This allows the user more control over their project builds instead of letting the tools generate the components. @@ -28,17 +28,15 @@ This tutorial describes three use cases for the **User Managed Mode**. ### Let’s get started -Launch Vitis 2025.1, select **open_workspace**, and navigate to the `Vitis-Tutorials/Embedded_Software/Feature_Tutorials/01-user_managed_mode` directory - -Select the **Open Explorer View** +Launch Vitis 2025.2, select **open_workspace**, and navigate to the `Vitis-Tutorials/Embedded_Software/Feature_Tutorials/01-user_managed_mode` directory. The workspace will load in the 'User Maged Mode' view. ![](./images/user_managed_mode.PNG) ### Generating Build Configuration -In this use case, we shall be using the Python script introduced in the *04-vitis_scripting_flows* to build a workspace and with a simple Hello World application template. However, users can also utilize the Python script `logs/workspace_journal.py` that gets generated for every Vitis Unified IDE workspace. Make sure you have copied the **unified_workspace.py** python file to your workspace. +In this use case, we shall be using the Python script introduced in the *04-vitis_scripting_flows* to build a workspace and with a simple Hello World application template. Therefore firstly, you will want to copy the `unified_workspace.py` and `create_xsa.tcl` files to your *01-user_managed_mode* workspace.However, users can also utilize the Python script `logs/workspace_journal.py` that gets generated for every Vitis Unified IDE workspace. Make sure you have already executed the **create_xsa.tcl** to create the hardware design. -On the left hand side you should see the **User Managed Mode View**. If the **User Managed Mode View** is not there then select the three dots in the explorer view and select **folders** which will load the **User Managed Mode View**. +On the left hand side you should see the **User Managed Mode View**. If the **User Managed Mode View** is not there then select the three dots in the explorer view and select **User Managed** which will load the **User Managed Mode View**. ![](./images/three_dots.png) @@ -84,7 +82,7 @@ In this use case, we can build the example using the scripts given [here](https: ### Lets get started -Launch Vitis 2025.1, select **open_workspace**, and navigate to the `Vitis-Tutorials/Embedded_Software/Feature_Tutorials/01-user_managed_mode` directory +Launch Vitis 2025.2, select **open_workspace**, and navigate to the `Vitis-Tutorials/Embedded_Software/Feature_Tutorials/01-user_managed_mode` directory Select the **Open Explorer View** @@ -125,7 +123,7 @@ Each section above can be built independently. For example, if users want to mak ### Lets get started -Launch Vitis 2025.1, select **open_workspace**, and navigate to the `Vitis-Tutorials/Embedded_Software/Feature_Tutorials/01-user_managed_mode` directory +Launch Vitis 2025.2, select **open_workspace**, and navigate to the `Vitis-Tutorials/Embedded_Software/Feature_Tutorials/01-user_managed_mode` directory Select the **Open Explorer View** diff --git a/Embedded_Software/Feature_Tutorials/01-user_managed_mode/images/three_dots.png b/Embedded_Software/Feature_Tutorials/01-user_managed_mode/images/three_dots.png index 9a5e990149..7766010263 100644 Binary files a/Embedded_Software/Feature_Tutorials/01-user_managed_mode/images/three_dots.png and b/Embedded_Software/Feature_Tutorials/01-user_managed_mode/images/three_dots.png differ diff --git a/Embedded_Software/Feature_Tutorials/01-user_managed_mode/images/user_managed_mode.PNG b/Embedded_Software/Feature_Tutorials/01-user_managed_mode/images/user_managed_mode.PNG index 5024d26548..f44f55143b 100644 Binary files a/Embedded_Software/Feature_Tutorials/01-user_managed_mode/images/user_managed_mode.PNG and b/Embedded_Software/Feature_Tutorials/01-user_managed_mode/images/user_managed_mode.PNG differ diff --git a/Embedded_Software/Feature_Tutorials/01-user_managed_mode/images/ws_build_config.PNG b/Embedded_Software/Feature_Tutorials/01-user_managed_mode/images/ws_build_config.PNG index dd2e846b50..4e0d93ea94 100755 Binary files a/Embedded_Software/Feature_Tutorials/01-user_managed_mode/images/ws_build_config.PNG and b/Embedded_Software/Feature_Tutorials/01-user_managed_mode/images/ws_build_config.PNG differ diff --git a/Embedded_Software/Feature_Tutorials/01-user_managed_mode/scripts/Makefile b/Embedded_Software/Feature_Tutorials/01-user_managed_mode/scripts/Makefile index ec043e9052..d5c2319ca0 100755 --- a/Embedded_Software/Feature_Tutorials/01-user_managed_mode/scripts/Makefile +++ b/Embedded_Software/Feature_Tutorials/01-user_managed_mode/scripts/Makefile @@ -7,18 +7,18 @@ .PHONY: all clean_all clean_atf clean_dtb clean_boot_script clean_platform clean_uboot create_xsa dtb make_platform SHELL := /bin/bash -VERSION ?= 2025.1 +VERSION ?= 2025.2 BOARD ?= zcu102-rev1.0 XSA ?= ./zcu102/design_1_wrapper.xsa ATF_REPO ?= https://github.com/Xilinx/arm-trusted-firmware.git -ATF_CHECKOUT ?= xilinx-v2024.2 +ATF_CHECKOUT ?= xilinx-v2025.1 UBOOT_REPO ?= https://github.com/Xilinx/u-boot-xlnx.git -UBOOT_CHECKOUT ?= xilinx-v2024.2 +UBOOT_CHECKOUT ?= xilinx-v2025.1 SDT_OUT ?= sdt_out USER_DTSI ?= prebuilt_linux/user_dts/system-user.dtsi -all: create_xsa make_platform dtb atf uboot +all: create_xsa make_platform dtb dtc atf uboot u-boot-xlnx: git clone --branch $(UBOOT_CHECKOUT) $(UBOOT_REPO) @@ -41,7 +41,25 @@ dtb: gen_sdt gen_sdt: $(RM) -rf $(SDT_OUT) $(info "DTB generation started using stdgen+lopper") - sdtgen -eval "sdtgen set_dt_param -dir $(SDT_OUT) -xsa $(XSA) -board_dts $(BOARD) -zocl enable -include_dts $(USER_DTSI); sdtgen generate_sdt" + sdtgen -eval "sdtgen set_dt_param -dir $(SDT_OUT) -xsa $(XSA) -board_dts $(BOARD); sdtgen generate_sdt" + +dtc: dtc_clone dtc_build dtc_compile + +dtc_clone: + if [ ! -d "dtc" ]; then \ + git clone https://git.kernel.org/pub/scm/utils/dtc/dtc.git; \ + fi + +dtc_build: + cd dtc && \ + make clean && \ + make && \ + make install DESTDIR=$(shell pwd)/dtc_install PREFIX=/usr + +dtc_compile: dtc_build + export PATH="$(shell pwd)/dtc_install/usr/bin:$(shell pwd)/dtc:$$PATH" && \ + gcc -I my_dts -E -nostdinc -I include -undef -D__DTS__ -x assembler-with-cpp -o system.dts sdt_out/system-top.dts && \ + $(shell pwd)/dtc/dtc -I dts -O dtb -o system.dtb system.dts atf: arm-trusted-firmware $(XSA) xsct_script.py $(MAKE) -C arm-trusted-firmware clean @@ -53,8 +71,10 @@ uboot: u-boot-xlnx $(XSA) export CROSS_COMPILE=aarch64-linux-gnu- && \ export ARCH=aarch64 && \ export CC=aarch64-linux-gnu-gcc && \ - export PATH=$$PATH:$(shell pwd)/dtc && \ - vitis -s ./xsct_script.py build_uboot $(XSA) + export PATH="$(shell pwd)/dtc_install/usr/bin:$(shell pwd)/dtc:$$PATH" && \ + cd u-boot-xlnx && \ + make xilinx_zynqmp_virt_defconfig && \ + make -f Makefile all -f 32 generate_boot_script: $(RM) -rf boot_script.py diff --git a/Embedded_Software/Feature_Tutorials/01-user_managed_mode/scripts/xsct_script.py b/Embedded_Software/Feature_Tutorials/01-user_managed_mode/scripts/xsct_script.py index 496d06300c..da3f23adb3 100644 --- a/Embedded_Software/Feature_Tutorials/01-user_managed_mode/scripts/xsct_script.py +++ b/Embedded_Software/Feature_Tutorials/01-user_managed_mode/scripts/xsct_script.py @@ -10,8 +10,7 @@ import os import subprocess import re - - +import sys def make_platform(xsa): extension = os.path.splitext(xsa)[1] @@ -99,9 +98,15 @@ def build_uboot(xsa): defconfig = "xilinx_zynqmp_virt_defconfig" if arch == "versal": print("Using xilinx_versal_virt_defconfig") - defconfig = "xilinx_versal_virt_defconfig" - result = subprocess.run(["cd u-boot-xlnx && make "+defconfig+" && make -f Makefile all -j 32"], shell=True, capture_output=True, text=True) + defconfig = "xilinx_versal_virt_defconfig" + result = subprocess.run(["make", defconfig], cwd="u-boot-xlnx", capture_output=True, text=True) print(result.stdout) + print(result.stderr) + + result2 = subprocess.run(["make", "-f", "Makefile", "all", "-j", "32"], cwd="u-boot-xlnx", capture_output=True, text=True) + print(result2.stdout) + print(result2.stderr) + def build_atf(xsa): extension = os.path.splitext(xsa)[1] diff --git a/Embedded_Software/Feature_Tutorials/02-Debugging/1-debugging-bare-metal-applications/README.md b/Embedded_Software/Feature_Tutorials/02-Debugging/1-debugging-bare-metal-applications/README.md index e570fd324a..9fd650fcca 100755 --- a/Embedded_Software/Feature_Tutorials/02-Debugging/1-debugging-bare-metal-applications/README.md +++ b/Embedded_Software/Feature_Tutorials/02-Debugging/1-debugging-bare-metal-applications/README.md @@ -13,7 +13,7 @@ # Debugging Bare-Metal Applications -***Version: Vitis 2024.2*** +***Version: Vitis 2025.2*** This section showcases the different debugging features available within the AMD Vitis™ embedded software development flow for bare-metal applications. Using an example application project with intentional bugs, the debug guide goes through each issue and leverages the different windows and features available in the application debug session to highlight the potential usage of debug features in a real world scenario. @@ -27,7 +27,7 @@ The example design targets the Xilinx® ZCU102 evaluation platform and implement ## Build XSA -Launch AMD Vivado™ 2024.2 and source run the following command from the TCL console: +Launch AMD Vivado™ 2025.2 and source run the following command from the TCL console: ``` cd scripts @@ -67,11 +67,11 @@ Open the XSDB window in the Vitis IDE and execute each command line in the scrip Running each command one by one lets you to see that the issue in this particular test case is in the download process of the ``testapp_a53`` application to memory. See the [dow](https://docs.amd.com/r/en-US/ug1400-vitis-embedded/dow) command for more information. -In this case, the error message has already pointed out the root cause of the issue. There is a memory write error at 0xFFFB0000 that does not belong to a memory region according to the _Zynq Ultrascale+ MPSoC Technical Reference Manual_ ([UG1085](https://www.xilinx.com/support/documentation/user_guides/ug1085-zynq-ultrascale-trm.pdf#G12.407191)). Checking the linker script in the Vitis IDE confirms that there is a mistake in the OCM memory region description because the base address is not correct. +In this case, the error message has already pointed out the root cause of the issue. There is a memory write error at 0xA0000000 that does not belong to a memory region according to the _Zynq Ultrascale+ MPSoC Technical Reference Manual_ ([UG1085](https://www.xilinx.com/support/documentation/user_guides/ug1085-zynq-ultrascale-trm.pdf#G12.407191)). Checking the linker script in the Vitis IDE confirms that there is a mistake in the DDR memory region description because the base address is not correct. ![Linker file wrong](./images/004.png) -Open the linker script in a text editor and modify the base address of the OCM memory region to match with the correct address. +Open the linker script in a text editor and modify the base address of the DDR memory region to match with the correct address. ![Linker file correct](./images/005.png) @@ -98,25 +98,32 @@ Select the **Cortex-A53#0** target in the Debug window and check that the interr Open ``main.c`` in the file editor and correctly add the ADMA_CH0 interrupt ID. ``` - Status = XSetupInterruptSystem(&ZDma, &XZDma_IntrHandler, +Status = XSetupInterruptSystem(ZdmaInstPtr, &XZDma_IntrHandler, Config->IntrId, Config->IntrParent, XINTERRUPT_DEFAULT_PRIORITY); ``` +and remove these lines +``` +u32 wrong_interrupt_id = 0; +Status = XSetupInterruptSystem(ZdmaInstPtr, &XZDma_IntrHandler, + wrong_interrupt_id, Config->IntrParent, + XINTERRUPT_DEFAULT_PRIORITY); +``` Build the application and launch the initially created debug session again. This time, the application is executed completely and the exit point is reached, confirming that the DMA transfer is completed. -![DMA finished](./images/011.png) +![DMA finished](./images/010.png) ## Error 3: Unexpected DMA Transfer Result Despite the successful DMA transfer, the serial output of the application shows that there is an unexpected result, because the destination buffer does not match with the source buffer. -![DMA transfer failure](./images/012.png) +![DMA transfer failure](./images/011.png) Launch the debug session and place a breakpoint in the ``return XST_FAILURE`` line for the DMA transfer, so that the execution is halted when the transfer failure is detected and the memory is inspected for further analysis. -![Hit breakpoint](./images/013.png) +![Hit breakpoint](./images/012.png) The Vitis IDE provides the following main methods of inspecting the memory content: @@ -128,14 +135,16 @@ These tabs are all context aware, meaning that they display content based on the The index variable value indicates that the first element of the destination array does not match with the first element on the source buffer. Because both the ZDmaSrcBuf and ZDmaDstBuf variables are static, they are not displayed in the **Variable** window, so you can use the **Expressions** window to inspect them. Select the **Expressions** tab and add both buffers to the list. The displayed expressions confirm that the destination buffer is populated with the default values. -![Expressions window](./images/014.png) +![Expressions window](./images/013.png) When a processor core accesses cacheable memory, the read value may not be the value in the physical memory. You can use the Vitis IDE to access the same memory address from a different target not subject to the cache. Targets such as the APU cluster or PSU are not subject to the cache, but they do not have an associated symbol file either, so the Variables and Expressions tables do not apply. -![Invalid expression](./images/015.png) +![Invalid expression](./images/014.png) Use the memory window and add the address of both ZDmaSrcBuf (0xB180) and ZDmaDstBuf (0xB1C0). Check the values on ZDmaDstBuf to verify that the DMA transfer is performed properly and the destination buffer is identical to the source buffer. +![Memory window](./images/015.png) + ![Memory window](./images/016.png) The process of accessing the memory from the APU generates cache maintenance operations, so the A53#0 core is able to get the correct values from the destination buffer moving forward. Select the A53#0 core again, and right-click in the **Expressions** tab to refresh the values. The values in the destination buffer now match the sources. @@ -144,7 +153,17 @@ The process of accessing the memory from the APU generates cache maintenance ope The debugging effort detailed above confirms that there is a cache maintenance operation missing in the application; specifically, cache invalidation prior to reading back the destination buffer after the DMA operation is performed. This operation would ensure that the physical memory is read instead of whatever the cache might have. -Open ``main.c`` in the file editor and add `Xil_DCacheInvalidateRange((INTPTR)ZDmaDstBuf, SIZE);` after the DMA transfer is performed and prior to reading the destination buffer. +Open ``main.c`` in the file editor and uncomment the below code. + +``` +if (!Config->IsCacheCoherent) { + Xil_DCacheInvalidateRange((INTPTR)ZDmaDstBuf, SIZE); + } else { + xil_printf("Debug: System is cache coherent, no manual invalidation needed\n\r"); + } +``` + +After the DMA transfer is performed and prior to reading the destination buffer. ![Enable DMA interrupt](./images/018.png) @@ -197,7 +216,7 @@ Modify the comparison statement to include the correct boundaries for uppercase Build the application and launch the debug session again. This time, the application is executed completely, and the original string is lowercased properly in the destination buffer. -![Success](./images/025.png) +![Success](./images/024.png)

Copyright © 2020–2025 Advanced Micro Devices, Inc.

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b/Embedded_Software/Feature_Tutorials/02-Debugging/1-debugging-bare-metal-applications/scripts/Makefile index b15c1a328b..e64d80afeb 100755 --- a/Embedded_Software/Feature_Tutorials/02-Debugging/1-debugging-bare-metal-applications/scripts/Makefile +++ b/Embedded_Software/Feature_Tutorials/02-Debugging/1-debugging-bare-metal-applications/scripts/Makefile @@ -6,7 +6,7 @@ SHELL := /bin/bash TOOLS ?= "" -VERSION ?= 2025.1 +VERSION ?= 2025.2 all: create_xsa unified_workspace diff --git a/Embedded_Software/Feature_Tutorials/02-Debugging/1-debugging-bare-metal-applications/scripts/src/lscript.ld b/Embedded_Software/Feature_Tutorials/02-Debugging/1-debugging-bare-metal-applications/scripts/src/lscript.ld index 393abec8cc..bbf1df234f 100755 --- a/Embedded_Software/Feature_Tutorials/02-Debugging/1-debugging-bare-metal-applications/scripts/src/lscript.ld +++ b/Embedded_Software/Feature_Tutorials/02-Debugging/1-debugging-bare-metal-applications/scripts/src/lscript.ld @@ -14,9 +14,9 @@ _EL2_STACK_SIZE = DEFINED(_EL2_STACK_SIZE) ? _EL2_STACK_SIZE : 1024; MEMORY { - psu_ddr_0_MEM_0 : ORIGIN = 0x0, LENGTH = 0x7FF00000 + psu_ddr_0_MEM_0 : ORIGIN = 0xA0000000, LENGTH = 0x7FF00000 psu_ddr_1_MEM_0 : ORIGIN = 0x800000000, LENGTH = 0x80000000 - psu_ocm_ram_0_MEM_0 : ORIGIN = 0xFFFB0000, LENGTH = 0x40000 + psu_ocm_ram_0_MEM_0 : ORIGIN = 0xFFFC0000, LENGTH = 0x40000 psu_qspi_linear_0_MEM_0 : ORIGIN = 0xC0000000, LENGTH = 0x20000000 } @@ -41,23 +41,23 @@ SECTIONS *(.glue_7t) *(.ARM.extab) *(.gnu.linkonce.armextab.*) -} > psu_ocm_ram_0_MEM_0 +} > psu_ddr_0_MEM_0 .init (ALIGN(64)) : { KEEP (*(.init)) -} > psu_ocm_ram_0_MEM_0 +} > psu_ddr_0_MEM_0 .fini (ALIGN(64)) : { KEEP (*(.fini)) -} > psu_ocm_ram_0_MEM_0 +} > psu_ddr_0_MEM_0 .interp : { KEEP (*(.interp)) -} > psu_ocm_ram_0_MEM_0 +} > psu_ddr_0_MEM_0 .note-ABI-tag : { KEEP (*(.note-ABI-tag)) -} > psu_ocm_ram_0_MEM_0 +} > psu_ddr_0_MEM_0 .rodata : { . = ALIGN(64); @@ -128,7 +128,7 @@ SECTIONS .note.gnu.build-id : { KEEP (*(.note.gnu.build-id)) -} > psu_ocm_ram_0_MEM_0 +} > psu_ddr_0_MEM_0 .ctors : { . = ALIGN(64); @@ -314,4 +314,3 @@ _SDA2_BASE_ = __sdata2_start + ((__sbss2_end - __sdata2_start) / 2 ); _end = .; } - diff --git a/Embedded_Software/Feature_Tutorials/02-Debugging/1-debugging-bare-metal-applications/scripts/src/main.c b/Embedded_Software/Feature_Tutorials/02-Debugging/1-debugging-bare-metal-applications/scripts/src/main.c index 323ce370ff..1de986b21f 100755 --- a/Embedded_Software/Feature_Tutorials/02-Debugging/1-debugging-bare-metal-applications/scripts/src/main.c +++ b/Embedded_Software/Feature_Tutorials/02-Debugging/1-debugging-bare-metal-applications/scripts/src/main.c @@ -1,5 +1,5 @@ /****************************************************************************** -* Copyright (c) 2018 - 2020 Xilinx, Inc. All rights reserved. +* Copyright (c) 2025 Advanced Micro Devices, Inc. All rights reserved. * SPDX-License-Identifier: MIT ******************************************************************************/ @@ -19,13 +19,9 @@ #endif #endif -#define SIZE 32 +/************************** Constant Definitions ******************************/ + -/* - * The following constants map to the XPAR parameters created in the - * xparameters.h file. They are defined here such that a user can easily - * change all the needed parameters in one place. - */ #ifndef SDT #define ZDMA_DEVICE_ID XPAR_XZDMA_0_DEVICE_ID /* ZDMA device Id */ #ifdef XPAR_INTC_0_DEVICE_ID @@ -41,19 +37,35 @@ #endif #ifndef TESTAPP_GEN -XZDma ZDma; /** 65) && (bufptr[idx] < 90)) { @@ -62,81 +74,141 @@ static void lowercase(u8* bufptr, u32 size) } } -static volatile int Done = 0; -static void DoneHandler(void *CallBackRef) -{ - Done = 1; -} +/************************** Variable Definitions *****************************/ + +#ifndef TESTAPP_GEN +XZDma ZDma; /**BaseAddress); if (Status != XST_SUCCESS) { + xil_printf("ZDMA Simple Example Failed\r\n"); return XST_FAILURE; } - /* Configure GIC */ + xil_printf("Successfully ran ZDMA Simple Example\r\n"); + + xil_printf("DMA transfer succeed\r\n"); + xil_printf("Src string: %s\r\n", ZDmaSrcBuf); + xil_printf("Dst string: %s\r\n", ZDmaDstBuf); + + lowercase(ZDmaDstBuf, SIZE); + + xil_printf("Lowercase : %s\r\n", ZDmaDstBuf); + + return XST_SUCCESS; +} +#endif + #ifndef SDT - IntcConfig = XScuGic_LookupConfig(XPAR_SCUGIC_SINGLE_DEVICE_ID); +int XZDma_SimpleExample(INTC *IntcInstPtr, XZDma *ZdmaInstPtr, + u16 DeviceId, u16 IntrId) #else - IntcConfig = XScuGic_LookupConfig(XPAR_XSCUGIC_0_BASEADDR); +int XZDma_SimpleExample(XZDma *ZdmaInstPtr, UINTPTR BaseAddress) #endif - if (NULL == IntcConfig) { +{ + int Status; + XZDma_Config *Config; + XZDma_DataConfig Configure; /* Configuration values */ + XZDma_Transfer Data; + u32 Index; + u32 Value; + +#ifndef SDT + Config = XZDma_LookupConfig(DeviceId); +#else + Config = XZDma_LookupConfig(BaseAddress); +#endif + if (NULL == Config) { return XST_FAILURE; } -#ifndef SDT - Status = XScuGic_CfgInitialize(&ScuGic, IntcConfig, IntcConfig->CpuBaseAddress); + Status = XZDma_CfgInitialize(ZdmaInstPtr, Config, Config->BaseAddress); if (Status != XST_SUCCESS) { return XST_FAILURE; } - - /* Enable exception and register GIC interrupt handler */ - Xil_ExceptionRegisterHandler(XIL_EXCEPTION_ID_INT, (Xil_ExceptionHandler) XScuGic_InterruptHandler, &ScuGic); - Xil_ExceptionEnableMask(XIL_EXCEPTION_IRQ); - - /* Register DMA interrupt handler in the GIC */ - Status = XScuGic_Connect(&ScuGic, XPAR_XADMAPS_0_INTR , (Xil_ExceptionHandler) XZDma_IntrHandler, (void *) &ZDma); + /* + * Performs the self-test to check hardware build. + */ + Status = XZDma_SelfTest(ZdmaInstPtr); if (Status != XST_SUCCESS) { return XST_FAILURE; } -#else - Status = XSetupInterruptSystem(&ZDma, &XZDma_IntrHandler, - Config->IntrId, Config->IntrParent, - XINTERRUPT_DEFAULT_PRIORITY); -#endif + + /* Filling the buffer for data transfer */ + const char *message = "asdBqSet kWsdfiQZzlkgiwEd"; + u32 len = strlen(message) + 1; // Include null terminator + + memset(ZDmaSrcBuf, 0, SIZE); + memcpy(ZDmaSrcBuf, message, len); + memset(ZDmaDstBuf, 0xAB, SIZE); + + /* + * Invalidating destination address and flushing + * source address in cache + */ + Xil_DCacheFlushRange((INTPTR)ZDmaSrcBuf, SIZE); + Xil_DCacheInvalidateRange((INTPTR)ZDmaDstBuf, SIZE); + volatile u8 dummy; + for (u32 i = 0; i < SIZE; i++) { + dummy = ZDmaDstBuf[i]; + } + (void)dummy; + + Status = XZDma_SetMode(ZdmaInstPtr, FALSE, XZDMA_NORMAL_MODE); if (Status != XST_SUCCESS) { return XST_FAILURE; } - - /* Set DMA interrupt handler callback and enable interrupt */ - XZDma_SetCallBack(&ZDma, XZDMA_HANDLER_DONE, (void *)DoneHandler, &ZDma); - XZDma_EnableIntr(&ZDma, (XZDMA_IXR_ALL_INTR_MASK)); + XZDma_SetCallBack(ZdmaInstPtr, XZDMA_HANDLER_DONE, + (void *)DoneHandler, ZdmaInstPtr); + XZDma_SetCallBack(ZdmaInstPtr, XZDMA_HANDLER_ERROR, + (void *)ErrorHandler, ZdmaInstPtr); - /* Configure DMA mode */ - Status = XZDma_SetMode(&ZDma, FALSE, XZDMA_NORMAL_MODE); +#ifndef SDT + Status = SetupInterruptSystem(IntcInstPtr, ZdmaInstPtr, + IntrId); +#else + + u32 wrong_interrupt_id = 0; + Status = XSetupInterruptSystem(ZdmaInstPtr, &XZDma_IntrHandler, + wrong_interrupt_id, Config->IntrParent, + XINTERRUPT_DEFAULT_PRIORITY); + + /* ERROR 2 FIX - Using correct interrupt ID: */ + /*Status = XSetupInterruptSystem(ZdmaInstPtr, &XZDma_IntrHandler, + Config->IntrId, Config->IntrParent, + XINTERRUPT_DEFAULT_PRIORITY);*/ +#endif if (Status != XST_SUCCESS) { return XST_FAILURE; } @@ -148,36 +220,228 @@ int main(void) Configure.SrcBurstLen = 0xF; Configure.DstBurstType = XZDMA_INCR_BURST; Configure.DstBurstLen = 0xF; - XZDma_SetChDataConfig(&ZDma, &Configure); + Configure.SrcCache = 0x3; + Configure.DstCache = 0x3; + + Configure.SrcQos = 0; + Configure.DstQos = 0; - /* Transfer elements */ + XZDma_SetChDataConfig(ZdmaInstPtr, &Configure); + /* + * Transfer elements + */ Data.DstAddr = (UINTPTR)ZDmaDstBuf; + Data.DstCoherent = 0; Data.Pause = 0; Data.SrcAddr = (UINTPTR)ZDmaSrcBuf; - Data.Size = SIZE; + Data.SrcCoherent = 0; + Data.Size = len; + + /* Enable required interrupts */ + XZDma_EnableIntr(ZdmaInstPtr, (XZDMA_IXR_ALL_INTR_MASK)); - /* Initialize the source buffer */ - sprintf(ZDmaSrcBuf, "asdBqSet kWsdfiQZzlkgiwEd\r\n"); - Xil_DCacheFlush(); + xil_printf("Debug: Starting DMA transfer...\n\r"); + + XZDma_Start(ZdmaInstPtr, &Data, 1); + + while (Done == 0); + + xil_printf("Debug: DMA transfer completed successfully (Done flag set by interrupt)\n\r"); + Status = XST_SUCCESS; + + /* Enable required interrupts */ + XZDma_DisableIntr(ZdmaInstPtr, (XZDMA_IXR_ALL_INTR_MASK)); + + if (ErrorStatus) { + if (ErrorStatus & XZDMA_IXR_AXI_WR_DATA_MASK) { + xil_printf("Error occurred on write data channel\n\r"); + } + if (ErrorStatus & XZDMA_IXR_AXI_RD_DATA_MASK) { + xil_printf("Error occurred on read data channel\n\r"); + } + return XST_FAILURE; + } - /* Perform DMA transfer */ - XZDma_Start(&ZDma, &Data, 1); - while(0==Done); + /*if (!Config->IsCacheCoherent) { + Xil_DCacheInvalidateRange((INTPTR)ZDmaDstBuf, SIZE); + } else { + xil_printf("Debug: System is cache coherent, no manual invalidation needed\n\r"); + }*/ /* Checking the data transferred */ - for (Index = 0; Index < SIZE; Index++) { + for (Index = 0; Index < len; Index++) { if (ZDmaSrcBuf[Index] != ZDmaDstBuf[Index]) { - xil_printf("DMA transfer failure, 0x%0X != 0x%0X\r\n", ZDmaSrcBuf[Index], ZDmaDstBuf[Index]); + xil_printf("Data mismatch at index %d: expected 0x%02x, got 0x%02x\n\r", + Index, ZDmaSrcBuf[Index], ZDmaDstBuf[Index]); return XST_FAILURE; } } - xil_printf("DMA transfer succeed\r\n"); - xil_printf("Src string: %s", ZDmaSrcBuf); - xil_printf("Dst string: %s", ZDmaDstBuf); + Done = 0; - lowercase(ZDmaDstBuf, SIZE); - xil_printf("Lowercase : %s", ZDmaDstBuf); + /* Reset the DMA to remove all configurations done in this example */ + XZDma_Reset(ZdmaInstPtr); return XST_SUCCESS; } +#ifndef SDT +/*****************************************************************************/ +/** +* This function sets up the interrupt system so interrupts can occur for the +* ZDMA. This function is application-specific. The user should modify this +* function to fit the application. +* +* @param IntcInstancePtr is a pointer to the instance of the INTC. +* @param InstancePtr contains a pointer to the instance of the ZDMA +* driver which is going to be connected to the interrupt +* controller. +* @param IntrId is the interrupt Id and is typically +* XPAR__INTR value from xparameters.h. +* +* @return +* - XST_SUCCESS if successful +* - XST_FAILURE if failed +* +* @note None. +* +****************************************************************************/ +int SetupInterruptSystem(INTC *IntcInstancePtr, + XZDma *InstancePtr, + u16 IntrId) +{ + int Status; + +#ifdef XPAR_INTC_0_DEVICE_ID +#ifndef TESTAPP_GEN + /* Initialize the interrupt controller and connect the ISRs */ + Status = XIntc_Initialize(IntcInstancePtr, ZDMA_INTC_DEVICE_ID); + if (Status != XST_SUCCESS) { + + xil_printf("Failed init intc\r\n"); + return XST_FAILURE; + } +#endif + /* + * Connect the driver interrupt handler + */ + Status = XIntc_Connect(IntcInstancePtr, IntrId, + (XInterruptHandler)XZDma_IntrHandler, InstancePtr); + if (Status != XST_SUCCESS) { + + xil_printf("Failed connect intc\r\n"); + return XST_FAILURE; + } +#ifndef TESTAPP_GEN + /* + * Start the interrupt controller such that interrupts are enabled for + * all devices that cause interrupts. + */ + Status = XIntc_Start(IntcInstancePtr, XIN_REAL_MODE); + if (Status != XST_SUCCESS) { + return XST_FAILURE; + } +#endif + + /* + * Enable the interrupt for the ZDMA device. + */ + XIntc_Enable(IntcInstancePtr, IntrId); +#ifndef TESTAPP_GEN + Xil_ExceptionInit(); + Xil_ExceptionRegisterHandler(XIL_EXCEPTION_ID_INT, + (Xil_ExceptionHandler)XIntc_InterruptHandler, + (void *)IntcInstancePtr); +#endif +#else +#ifndef TESTAPP_GEN + XScuGic_Config *IntcConfig; /* Config for interrupt controller */ + + /* + * Initialize the interrupt controller driver + */ + IntcConfig = XScuGic_LookupConfig(ZDMA_INTC_DEVICE_ID); + if (NULL == IntcConfig) { + return XST_FAILURE; + } + + Status = XScuGic_CfgInitialize(IntcInstancePtr, IntcConfig, + IntcConfig->CpuBaseAddress); + if (Status != XST_SUCCESS) { + return XST_FAILURE; + } + + /* + * Connect the interrupt controller interrupt handler to the + * hardware interrupt handling logic in the processor. + */ + Xil_ExceptionRegisterHandler(XIL_EXCEPTION_ID_INT, + (Xil_ExceptionHandler) XScuGic_InterruptHandler, + IntcInstancePtr); +#endif + + /* + * Connect a device driver handler that will be called when an + * interrupt for the device occurs, the device driver handler + * performs the specific interrupt processing for the device + */ + Status = XScuGic_Connect(IntcInstancePtr, IntrId, + (Xil_ExceptionHandler) XZDma_IntrHandler, + (void *) InstancePtr); + if (Status != XST_SUCCESS) { + return XST_FAILURE; + } + + /* + * Enable the interrupt for the device + */ + XScuGic_Enable(IntcInstancePtr, IntrId); +#endif +#ifndef TESTAPP_GEN + + /* + * Enable interrupts + */ + Xil_ExceptionEnableMask(XIL_EXCEPTION_IRQ); +#endif + + + return XST_SUCCESS; +} +#endif + +/*****************************************************************************/ +/** +* This static function handles ZDMA Done interrupts. +* +* @param CallBackRef is the callback reference passed from the interrupt +* handler, which in our case is a pointer to the driver instance. +* +* @return None. +* +* @note None. +* +******************************************************************************/ +static void DoneHandler(void *CallBackRef) +{ + Xil_AssertVoid(CallBackRef != NULL); + Done = 1; + +} +/*****************************************************************************/ +/** +* This static function handles ZDMA error interrupts. +* +* @param CallBackRef is the callback reference passed from the interrupt +* handler, which in our case is a pointer to the driver instance. +* @param Mask specifies which interrupts were occurred. +* +* @return None. +* +* @note None. +* +******************************************************************************/ +static void ErrorHandler(void *CallBackRef, u32 Mask) +{ + Xil_AssertVoid(CallBackRef != NULL); + ErrorStatus = Mask; +} \ No newline at end of file diff --git a/Embedded_Software/Feature_Tutorials/02-Debugging/2-debugging-linux-applications/README.md b/Embedded_Software/Feature_Tutorials/02-Debugging/2-debugging-linux-applications/README.md index 9155cfcc67..e2c8412b58 100755 --- a/Embedded_Software/Feature_Tutorials/02-Debugging/2-debugging-linux-applications/README.md +++ b/Embedded_Software/Feature_Tutorials/02-Debugging/2-debugging-linux-applications/README.md @@ -13,7 +13,7 @@ # Debugging Linux Applications -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** The AMD Vitis™ IDE provides a familiar environment for debugging Linux applications for a target platform. This section covers the following Linux application debug features: @@ -281,13 +281,13 @@ It is required to configure the PetaLinux project to support Linux application d 1. Create the PetaLinux project: ``` - petalinux-create project --template zynqMP -n ./xilinx-zcu102-v2025.1 --tmpdir /tmp/${USER}/zcu102/petalinux + petalinux-create project --template zynqMP -n ./xilinx-zcu102-v2025.2 --tmpdir /tmp/${USER}/zcu102/petalinux ``` 2. Configure the hardware description: ``` - cd xilinx-zcu102-2025.1 + cd xilinx-zcu102-2025.2 petalinux-config --get-hw-description ``` diff --git a/Embedded_Software/Feature_Tutorials/02-Debugging/2-debugging-linux-applications/scripts/Makefile b/Embedded_Software/Feature_Tutorials/02-Debugging/2-debugging-linux-applications/scripts/Makefile index 9228c0f31f..e5939ea5e6 100755 --- a/Embedded_Software/Feature_Tutorials/02-Debugging/2-debugging-linux-applications/scripts/Makefile +++ b/Embedded_Software/Feature_Tutorials/02-Debugging/2-debugging-linux-applications/scripts/Makefile @@ -6,7 +6,7 @@ SHELL := /bin/bash TOOLS ?= "" -VERSION ?= 2025.1 +VERSION ?= 2025.2 LINUX_TMP_DIR ?= /tmp/${USER}/${VERSION}/zcu102/petalinux all: create_xsa sysroots unified_workspace @@ -16,17 +16,17 @@ create_xsa: vivado -mode tcl -source create_xsa.tcl sysroots: - $(RM) -rf ./xilinx-zcu102-v2025.1 ${LINUX_TMP_DIR} - petalinux-create project --template zynqMP -n ./xilinx-zcu102-v2025.1 --tmpdir ${LINUX_TMP_DIR} - cd ./xilinx-zcu102-v2025.1 && petalinux-config --get-hw-description=../zcu102/design_1_wrapper.xsa --silentconfig - sed -i 's/template/zcu102-rev1.0/' ./xilinx-zcu102-v2025.1/project-spec/configs/config - cd ./xilinx-zcu102-v2025.1 && petalinux-build - cd ./xilinx-zcu102-v2025.1 && petalinux-build --sdk - ./xilinx-zcu102-v2025.1/images/linux/sdk.sh -y -d sysroot + $(RM) -rf ./xilinx-zcu102-v2025.2 ${LINUX_TMP_DIR} + petalinux-create project --template zynqMP -n ./xilinx-zcu102-v2025.2 --tmpdir ${LINUX_TMP_DIR} + cd ./xilinx-zcu102-v2025.2 && petalinux-config --get-hw-description=../zcu102/design_1_wrapper.xsa --silentconfig + sed -i 's/template/zcu102-rev1.0/' ./xilinx-zcu102-v2025.2/project-spec/configs/config + cd ./xilinx-zcu102-v2025.2 && petalinux-build + cd ./xilinx-zcu102-v2025.2 && petalinux-build --sdk + cd xilinx-zcu102-v2025.2/images/linux/ && unset LD_LIBRARY_PATH && ./sdk.sh -y -d sysroot unified_workspace: $(RM) -rf ./unified_workspace vitis -s unified_workspace.py ./zcu102/design_1_wrapper.xsa clean: - $(RM) -rf ./zcu102 ./classic_workspace ./unified_workspace ./xilinx-zcu102-v2025.1 + $(RM) -rf ./zcu102 ./classic_workspace ./unified_workspace ./xilinx-zcu102-v2025.2 diff --git a/Embedded_Software/Feature_Tutorials/02-Debugging/2-debugging-linux-applications/scripts/unified_workspace.py b/Embedded_Software/Feature_Tutorials/02-Debugging/2-debugging-linux-applications/scripts/unified_workspace.py index d133c991f7..643a6460c5 100755 --- a/Embedded_Software/Feature_Tutorials/02-Debugging/2-debugging-linux-applications/scripts/unified_workspace.py +++ b/Embedded_Software/Feature_Tutorials/02-Debugging/2-debugging-linux-applications/scripts/unified_workspace.py @@ -32,7 +32,7 @@ platform = client.get_component(name="zcu102_platform") status = platform.build() - sysroots = os.path.join(os.getcwd(), "./sysroot/sysroots/cortexa72-cortexa53-amd-linux") + sysroots = os.path.join(os.getcwd(), "./xilinx-zcu102-v2025.2/sysroot/sysroots/cortexa72-cortexa53-amd-linux") sysroots = os.path.normpath(sysroots) status = client.set_preference(level = "WORKSPACE", device = "ZynqMP", key = "Sysroot", value = sysroots) diff --git a/Embedded_Software/Feature_Tutorials/02-Debugging/3-debuggable-fsbl/README.md b/Embedded_Software/Feature_Tutorials/02-Debugging/3-debuggable-fsbl/README.md index 85acf857db..c10e716011 100755 --- a/Embedded_Software/Feature_Tutorials/02-Debugging/3-debuggable-fsbl/README.md +++ b/Embedded_Software/Feature_Tutorials/02-Debugging/3-debuggable-fsbl/README.md @@ -13,7 +13,7 @@ # Creating a Debuggable First Stage Boot Loader -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** First Stage Boot Loader (FSBL) can initialize the SoC device, load the required application or data to memory, and launch applications on the target the CPU core. FSBL is optimized for size because it must fit in the OCM, which has limited space on the device. Size based optimization introduces some trouble, if you want to debug FSBL when you add customized code into FSBL. This chapter explains how you can use AMD Vitis™ Unified IDE to debug FSBL step by step. diff --git a/Embedded_Software/Feature_Tutorials/02-Debugging/4-cross-triggering/README.md b/Embedded_Software/Feature_Tutorials/02-Debugging/4-cross-triggering/README.md index 20a3ce3aea..ee4996b95e 100755 --- a/Embedded_Software/Feature_Tutorials/02-Debugging/4-cross-triggering/README.md +++ b/Embedded_Software/Feature_Tutorials/02-Debugging/4-cross-triggering/README.md @@ -13,7 +13,7 @@ # Cross Triggering in Vitis Unified Embedded IDE -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** Embedded systems can be complex, that may contain multiple processors. You can also debug across software and hardware domains and can use PS-PL cross triggering. However, In this simple tutorial, you learn how we can debug over multiple processors using cross triggering. @@ -22,7 +22,7 @@ Embedded systems can be complex, that may contain multiple processors. You can a There is a script delivered with this tutorial to build the the HW from scratch, or use the prebuilt hardware (default). To do this use the command below ``` -cd Vitis_Cross_Probing/scripts +cd scripts make build_hw ``` ## Processor to Processor Cross Triggering @@ -30,7 +30,7 @@ make build_hw In this Lab, we will learn how we can Cross Trigger across two processors. To build use the command below ``` -cd Vitis_Cross_Probing/scripts +cd scripts make build_sw LAB=1 ``` @@ -62,7 +62,7 @@ int main() } ``` -Launch AMD Vitis™ Unified embedded tool in 2025.1 and open the **lab1** workspace. +Launch AMD Vitis™ Unified embedded tool in 2025.2 and open the **lab1** workspace. ![](./images/applications.PNG) @@ -87,7 +87,7 @@ Launch AMD Vitis™ Unified embedded tool in 2025.1 and open the **lab1** worksp Another very useful feature is the ability to debug between the hardware and software domains. To build use the command below ``` -cd Vitis_Cross_Probing/scripts +cd scripts make build_sw LAB=2 ``` @@ -150,7 +150,7 @@ Alternatively, users can setup the cross triggering to trigger the System ILA wh For example, I used the same hardware design as above. However, I updated the software application to write to the AXI GPIO. To build use the command below ``` -cd Vitis_Cross_Probing/scripts +cd scripts make build_sw LAB=3 ``` diff --git a/Embedded_Software/Feature_Tutorials/02-Debugging/4-cross-triggering/scripts/Makefile b/Embedded_Software/Feature_Tutorials/02-Debugging/4-cross-triggering/scripts/Makefile index 7f25e78753..af4979c9e1 100644 --- a/Embedded_Software/Feature_Tutorials/02-Debugging/4-cross-triggering/scripts/Makefile +++ b/Embedded_Software/Feature_Tutorials/02-Debugging/4-cross-triggering/scripts/Makefile @@ -5,7 +5,7 @@ # Author: Stephen MacMahon SHELL := /bin/bash -VERSION ?= 2025.1 +VERSION ?= 2025.2 REMOTE ?= localhost PREBUILT ?= 0 LAB ?= 1 diff --git a/Embedded_Software/Feature_Tutorials/02-Debugging/4-cross-triggering/scripts/create_xsa.tcl b/Embedded_Software/Feature_Tutorials/02-Debugging/4-cross-triggering/scripts/create_xsa.tcl index 0b2138e6ca..082c388613 100644 --- a/Embedded_Software/Feature_Tutorials/02-Debugging/4-cross-triggering/scripts/create_xsa.tcl +++ b/Embedded_Software/Feature_Tutorials/02-Debugging/4-cross-triggering/scripts/create_xsa.tcl @@ -20,7 +20,7 @@ set script_folder [_tcl::get_script_folder] ################################################################ # Check if script is running in correct Vivado version. ################################################################ -set scripts_vivado_version 2025.1 +set scripts_vivado_version 2025.2 set current_vivado_version [version -short] if { [string first $scripts_vivado_version $current_vivado_version] == -1 } { diff --git a/Embedded_Software/Feature_Tutorials/03-vitis_classic_to_unified_migration/README.md b/Embedded_Software/Feature_Tutorials/03-vitis_classic_to_unified_migration/README.md index dd29d31017..4f238a0256 100644 --- a/Embedded_Software/Feature_Tutorials/03-vitis_classic_to_unified_migration/README.md +++ b/Embedded_Software/Feature_Tutorials/03-vitis_classic_to_unified_migration/README.md @@ -13,7 +13,7 @@ # Vitis Classic to Unified Project Migration -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** >**Note**: The content of this tutorial is also available as an on-demand video, featuring a demo walkthrough from the ["Advancing Embedded Development: Migrating to AMD Vitis™ Unified IDE and Exploring Backend Innovations"](https://webinar.amd.com/Advancing-Embedded-Development-Migrating-to-AMD-Vitis-tm-Unified-IDE-and-Exploring-Backend-Innovations/en) webinar. @@ -31,6 +31,7 @@ There is also a migration utility in the Vitis Classic that users can use to por * External repositories will not be reflected. Meaning if you have a custom driver in an external repo, then this driver will not be ported * Modification made to BSP will not be reflected * Build Configurations are not copied over to Unified. Users will need to generate this via the launnch configuration GUI +* Only works for version's untill 2024.2 (Manual migration is recommended) ## Metadata transfer Methodology change from Hardware to Software @@ -271,11 +272,11 @@ In Vitis Classic, the bsp parameters were populated for the MLD and MSS file. In cmake_minimum_required(VERSION 3.3) find_package(common) -set(lwip213_api_mode RAW_API CACHE STRING "Mode of operation for lwIP (RAW API/Sockets API)") -set_property(CACHE lwip213_api_mode PROPERTY STRINGS RAW_API SOCKET_API) -option(lwip213_no_sys_no_timers "Drops support for sys_timeout when NO_SYS==1" ON) -set(lwip213_socket_mode_thread_prio 2 CACHE STRING "Priority of threads in socket mode") -option(lwip213_tcp_keepalive "Enable keepalive processing with default interval" OFF) +set(lwip220_api_mode RAW_API CACHE STRING "Mode of operation for lwIP (RAW API/Sockets API)") +set_property(CACHE lwip220_api_mode PROPERTY STRINGS RAW_API SOCKET_API) +option(lwip220_no_sys_no_timers "Drops support for sys_timeout when NO_SYS==1" ON) +set(lwip220_socket_mode_thread_prio 2 CACHE STRING "Priority of threads in socket mode") +option(lwip220_tcp_keepalive "Enable keepalive processing with default interval" OFF) set(sgmii_fixed_link 0 CACHE STRING "Enable fixed link for GEM SGMII at 1Gbps") set_property(CACHE sgmii_fixed_link PROPERTY STRINGS 0 1) ... @@ -359,7 +360,7 @@ Below I have a trivial Block Design for the Zynq Ultrascale+ MPSoC which was cre ![](./images/2023.2_block_design.PNG) -1. Load Vivado 2025.1 tools +1. Load Vivado 2025.2 tools 2. Select 'Open Project' and choose the 2023.2 project to be migrated ![](./images/open_project.PNG) @@ -376,7 +377,7 @@ To upgrade the IP select 'Report IP Status' and then scroll to the bottom of the ![](./images/upgradable_ip.PNG) -5. Export the hardware (XSA) and use it to recreate your platform in Vitis Unified 2025.1 +5. Export the hardware (XSA) and use it to recreate your platform in Vitis Unified 2025.2 ### Vitis Classic to Unified Migration Utility @@ -388,6 +389,7 @@ Launch XSCT, and use the command below cd scripts make all ``` +**Note:** The scripting flow provided in the tutorial will only work in versions (2023.2 - 2024.2) as the classic IDE is no longer provided in the install from version 2025.1. This will create the platform xsa file and the **classic_workspace** workspace. Launch Vitis Classic, and navigate to the workspace created above. diff --git a/Embedded_Software/Feature_Tutorials/03-vitis_classic_to_unified_migration/images/custom_lib.PNG b/Embedded_Software/Feature_Tutorials/03-vitis_classic_to_unified_migration/images/custom_lib.PNG index ae955f8430..b8d54f0e9d 100755 Binary files a/Embedded_Software/Feature_Tutorials/03-vitis_classic_to_unified_migration/images/custom_lib.PNG and b/Embedded_Software/Feature_Tutorials/03-vitis_classic_to_unified_migration/images/custom_lib.PNG differ diff --git a/Embedded_Software/Feature_Tutorials/03-vitis_classic_to_unified_migration/scripts/Makefile b/Embedded_Software/Feature_Tutorials/03-vitis_classic_to_unified_migration/scripts/Makefile index fb08c62068..97747997b2 100755 --- a/Embedded_Software/Feature_Tutorials/03-vitis_classic_to_unified_migration/scripts/Makefile +++ b/Embedded_Software/Feature_Tutorials/03-vitis_classic_to_unified_migration/scripts/Makefile @@ -6,7 +6,7 @@ SHELL := /bin/bash TOOLS ?= "" -VERSION ?= 2025.1 +VERSION ?= 2025.2 all: create_xsa classic_workspace diff --git a/Embedded_Software/Feature_Tutorials/04-vitis_scripting_flows/README.md b/Embedded_Software/Feature_Tutorials/04-vitis_scripting_flows/README.md index fd5b359a4b..f9e1a4eb74 100755 --- a/Embedded_Software/Feature_Tutorials/04-vitis_scripting_flows/README.md +++ b/Embedded_Software/Feature_Tutorials/04-vitis_scripting_flows/README.md @@ -11,7 +11,7 @@ -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** # Vitis Embedded Scripting Flows @@ -29,7 +29,7 @@ There are commandline API for creating Vitis components, API for extracting the There is a script attached to this tutorial if users want to rebuild the XSA used in this tutorial. -Launch Vivado 2025.1 and use the TCL commands below +Launch Vivado 2025.2 and use the TCL commands below ``` cd scripts @@ -170,7 +170,7 @@ domain = platform.add_domain(cpu = "psu_cortexa53_0",os = "standalone",name = "m When we generate a platform, the metadata is extracted from the XSA, and this is used to generate the S-DT. This will also rebuild any domains within the platform ``` -platform.update_hw(hw = "path to new XSA") +platform.update_hw(hw_design = "path to new XSA") ``` ### Building Platform @@ -438,8 +438,8 @@ RP_ID_INFO string true RP_INST_NAME string true SPEEDGRADE string true -2 SW_REPOSITORIES string* true [] -TIMESTAMP string true Mon Apr 28 16:18:04 2025 -VIVADO_VERSION string true 2025.1 +TIMESTAMP string true Thu Sep 25 05:38:26 2025 +VIVADO_VERSION string true 2025.2 ``` Users can return a specific property, such as the `FAMILY` @@ -747,9 +747,9 @@ Vitis [0]: jtag = session.jtag_targets() ``` ``` - 1 Digilent JTAG-SMT2NC 210308A7B222 () - 2 xczu9 (idcode 24738093 irlen 12 fpga) - 3 arm_dap (idcode 5ba00477 irlen 4) +1 Digilent JTAG-SMT2NC 210308A46CA1 + 2 xczu9 (idcode 24738093 irlen 12 fpga) + 3 arm_dap (idcode 5ba00477 irlen 4) ``` Users can filter on the JTAG Targets diff --git a/Embedded_Software/Feature_Tutorials/04-vitis_scripting_flows/scripts/Makefile b/Embedded_Software/Feature_Tutorials/04-vitis_scripting_flows/scripts/Makefile index ce74780227..7543341076 100755 --- a/Embedded_Software/Feature_Tutorials/04-vitis_scripting_flows/scripts/Makefile +++ b/Embedded_Software/Feature_Tutorials/04-vitis_scripting_flows/scripts/Makefile @@ -5,7 +5,7 @@ # Author: Stephen MacMahon SHELL := /bin/bash -VERSION ?= 2025.1 +VERSION ?= 2025.2 all: clean create_xsa unified_workspace diff --git a/Embedded_Software/Feature_Tutorials/05-vitis_version_control/README.md b/Embedded_Software/Feature_Tutorials/05-vitis_version_control/README.md index 928268421d..a2fd39cc17 100644 --- a/Embedded_Software/Feature_Tutorials/05-vitis_version_control/README.md +++ b/Embedded_Software/Feature_Tutorials/05-vitis_version_control/README.md @@ -8,7 +8,7 @@ # Version Control in Vitis Unified IDE -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** This guide is designed to help you understand and efficently use the built-in version control tools integrated within the Vitis Unified IDE. Version control among different teams is a key concept and therefore this tutorial will guide you through the essential workflows to streamline the development process within your own team. We will look at three different version control techniques within the Vitis Unified IDE @@ -101,7 +101,7 @@ Note: You can see what git commands are being executed under the hood by selecti ### Step 1: Initialising the Git Repository -Launch Vitis 2025.1, select **open workspace**, and select the workspace we have just created. Then we will need to intialise our workspace as a Git workspace. So once the workspace has loaded select **Terminal** -> **New Terminal** +Launch Vitis 2025.2, select **open workspace**, and select the workspace we have just created. Then we will need to intialise our workspace as a Git workspace. So once the workspace has loaded select **Terminal** -> **New Terminal** ![](./images/select_terminal.PNG) @@ -196,7 +196,7 @@ Now that we have created a project and pushed it to Git we can clone that reposi 3. Select the version control icon on the left side, select the three dots beside Git and select **clone**. -![](./images/select_git_clone.PNG) +![](./images/git_clone.PNG) 4. You will be prompted to enter the URL of your remote repository. 5. After entering the URL you will be prompted to enter your Git credentials./ diff --git a/Embedded_Software/Feature_Tutorials/05-vitis_version_control/images/git_clone.PNG b/Embedded_Software/Feature_Tutorials/05-vitis_version_control/images/git_clone.PNG new file mode 100644 index 0000000000..7a9f4a8f2d Binary files /dev/null and b/Embedded_Software/Feature_Tutorials/05-vitis_version_control/images/git_clone.PNG differ diff --git a/Embedded_Software/Feature_Tutorials/05-vitis_version_control/images/select_git_clone.png b/Embedded_Software/Feature_Tutorials/05-vitis_version_control/images/select_git_clone.png deleted file mode 100644 index a7538f331d..0000000000 Binary files a/Embedded_Software/Feature_Tutorials/05-vitis_version_control/images/select_git_clone.png and /dev/null differ diff --git a/Embedded_Software/Feature_Tutorials/05-vitis_version_control/scripts/Makefile b/Embedded_Software/Feature_Tutorials/05-vitis_version_control/scripts/Makefile index cf3834e99f..ee223a9ad5 100644 --- a/Embedded_Software/Feature_Tutorials/05-vitis_version_control/scripts/Makefile +++ b/Embedded_Software/Feature_Tutorials/05-vitis_version_control/scripts/Makefile @@ -5,7 +5,7 @@ # Author: Luke Millar SHELL := /bin/bash -VERSION ?= 2025.1 +VERSION ?= 2025.2 all: clean create_git_repo create_working_folder push_working_folder clone_and_rebuild diff --git a/Embedded_Software/Feature_Tutorials/Feature_Tutorials.rst b/Embedded_Software/Feature_Tutorials/Feature_Tutorials.rst index 80b5061053..eaa80a4d9b 100644 --- a/Embedded_Software/Feature_Tutorials/Feature_Tutorials.rst +++ b/Embedded_Software/Feature_Tutorials/Feature_Tutorials.rst @@ -1,10 +1,10 @@ -############################################################################## +############################################################################## Embedded Software: Feature Tutorials ############################################################################## -These tutorials illustrate specific features of the Vitis Embedded Software development flow. Some features might not be required by all designs but are still useful for some use cases. +These tutorials illustrate specific features of the AMD Vitis™ Embedded Software development flow. Some features might not be required by all designs but are still useful for some use cases. .. toctree:: @@ -44,10 +44,10 @@ These tutorials illustrate specific features of the Vitis Embedded Software deve .. sidebar:: More Information - See AMD Vitis™ Development Environment on `xilinx.com `_ + See Vitis Development Environment on `amd.com `_ -.. Copyright © 2020–2024 Advanced Micro Devices, Inc +.. Copyright © 2020–2025 Advanced Micro Devices, Inc -.. `Terms and Conditions `_. \ No newline at end of file +.. `Terms and Conditions `_. diff --git a/Embedded_Software/Getting_Started/README.md b/Embedded_Software/Getting_Started/README.md index f9cdf913ec..120010c7a9 100644 --- a/Embedded_Software/Getting_Started/README.md +++ b/Embedded_Software/Getting_Started/README.md @@ -14,7 +14,7 @@ # Getting Started in Vitis Unified Embedded IDE -***Version: 2025.1*** +***Version: 2025.2*** This tutorial should act as the start point, or a refresher to the AMD Vitis™ Unified Embedded flows. The concepts will be kept simple to allow the user to navigate through the IDE with minimal steps to get started. We will accomplish the following tasks in this tutorial: @@ -24,8 +24,25 @@ This tutorial should act as the start point, or a refresher to the AMD Vitis™ **Note** -The example design in this tutorial is based on ZCU102 evaluation board, which uses MPSoC UltraScale+. The concept can apply to all SoC devices such as ZYNQ-7000 and Versal. +The example design in this tutorial is based on ZCU102 evaluation board, which uses MPSoC UltraScale+. The concept can apply to all SoC devices such as ZYNQ-7000 and Versal. You can also carry out this tutorial for versal boards such as: +* vck190 +* vek280 +* vek385 + +Furthermore, you can also automate the workspace build (HW and SW) by using the Makefile included in this tutorial. + +``` +make +``` +## Board Setup + +Documentation on preparing the hardware for each board can be found here: + +* ZCU102 +* VCK190 +* VEK280 +* VEK385 ## Get Started @@ -129,15 +146,21 @@ We are now ready to build our application. To do this, select the Build icon in ![missing image](./images/build_application.PNG) -Select Debug in the Flow view, and user will be prompted to create a new configuration (if one does not previously exist). +You will be prompted with the below build options to choose from: -![missing image](./images/debug_config.PNG) +1. Always build platform with application +- Platform build will always take place automatically before application build + +2. Only build application (manually build platform if needed) +- Platform build wont take place automatically before application build -Select New Launch Configuration. +![missing image](./images/build_settings.PNG) + +Select Debug in the Flow view, and user will be prompted to create a new configuration (if one does not previously exist). ![missing image](./images/new_config.PNG) -The Launch configuration will be auto-populated with the boot artifact components in the platform. +Select New Launch Configuration. The Launch configuration will be auto-populated with the boot artifact components in the platform. ![missing image](./images/debug_config.PNG) @@ -180,7 +203,7 @@ Make sure that the Program Flash is successful. We can verify, by setting the bo The Vitis Unified IDE will capture all the Vitis Python API used to create or modify the Vitis workspace in a python file in the logs folder. This can be then source in the Vitis CLI to rebuild the workspace. For example, the script that was generated in Vitis using the steps above is attached to this git repository with minimal changes to set the PWD. ``` -vitis -s build_workspace.py +vitis -s build_workspace.py -b zcu102 ```

Copyright © 2020–2023 Advanced Micro Devices, Inc.

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-# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. # SPDX-License-Identifier: MIT # -# Author: Stephen MacMahon +# Author: Luke Millar SHELL := /bin/bash -VERSION ?= 2025.1 +VERSION ?= 2025.2 -all: clean unified_workspace +all: clean zcu102 + +zcu102: + vivado -mode batch -source create_zcu102_xsa.tcl + vitis -s build_workspace.py -s zcu102 + +vck190: + vivado -mode batch -source create_vck190_xsa.tcl + vitis -s build_workspace.py -s vck190 + +vek280: + vivado -mode batch -source create_vek280_xsa.tcl + vitis -s build_workspace.py -s vek280 + +vek385: + vivado -mode batch -source create_vek385_xsa.tcl + vitis -s build_workspace.py -s vek385 -unified_workspace: - vitis -s build_workspace.py clean: $(RM) -rf ./unified_workspace diff --git a/Embedded_Software/Getting_Started/scripts/build_workspace.py b/Embedded_Software/Getting_Started/scripts/build_workspace.py index facd25c13a..b166d773d3 100644 --- a/Embedded_Software/Getting_Started/scripts/build_workspace.py +++ b/Embedded_Software/Getting_Started/scripts/build_workspace.py @@ -1,12 +1,17 @@ # -# Copyright (C) 2024, Advanced Micro Devices, Inc. All rights reserved. +# Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. # SPDX-License-Identifier: MIT # -# Author: Stephen MacMahon +# Author: Luke Millar import vitis import os import shutil +import argparse + +parser = argparse.ArgumentParser(description="Vitis Workspace Setup") +parser.add_argument("-b", "--board", type=str, required=True, choices=["zcu102", "vck190", "vek280", "vek385"], help="The board in use (zcu102, vck190, vek280, vek385)") +args = parser.parse_args() WORKSPACE_DIR = "unified_workspace" @@ -21,13 +26,36 @@ client = vitis.create_client() client.set_workspace(workspace) -platform = client.create_platform_component(name="zcu102_platform", hw_design="zcu102", os="standalone", cpu="psu_cortexa53_0", domain_name="standalone_psu_cortexa53_0") +platform_dict = {"board_name": args.board, "hw_design": "null", "os": "null", "cpu": "null", "domain_name": "null"} + +if args.board == "zcu102": + platform_dict["hw_design"] = "zcu102/design_1_wrapper.xsa"; + platform_dict["os"] = "standalone"; + platform_dict["cpu"] = "psu_cortexa53_0"; + platform_dict["domain_name"] = "standalone_psu_cortexa53_0"; +elif args.board == "vck190": + platform_dict["hw_design"] = "vck190/design_1_wrapper.xsa"; + platform_dict["os"] = "standalone"; + platform_dict["cpu"] = "psv_cortexa72_0"; + platform_dict["domain_name2"] = "standalone_psv_cortexa72_0" +elif args.board == "vek280": + platform_dict["hw_design"] = "vek280/design_1_wrapper.xsa"; + platform_dict["os"] = "standalone"; + platform_dict["cpu"] = "psv_cortexa72_0"; + platform_dict["domain_name"] = "standalone_psv_cortexa72_0" +elif args.board == "vek385": + platform_dict["hw_design"] = "vek385/design_1_wrapper.xsa"; + platform_dict["os"] = "standalone"; + platform_dict["cpu"] = "cortexa78_0"; + platform_dict["domain_name"] = "standalone_cortexa78_0" + -xpfm = os.path.join(os.getcwd(), f"./{WORKSPACE_DIR}/zcu102_platform/export/zcu102_platform/zcu102_platform.xpfm") +platform = client.create_platform_component(name=platform_dict["board_name"],hw_design=platform_dict["hw_design"], os=platform_dict["os"], cpu=platform_dict["cpu"], domain_name=platform_dict["domain_name"]) +xpfm = os.path.join(workspace, platform_dict["board_name"], "export", platform_dict["board_name"], f"{platform_dict['board_name']}.xpfm") xpfm = os.path.normpath(xpfm) -comp = client.create_app_component(name="hello_world", platform=xpfm, domain="standalone_psu_cortexa53_0", template="hello_world") +comp = client.create_app_component(name="hello_world", platform=xpfm, domain=platform_dict["domain_name"], template="hello_world") -platform = client.get_component(name="zcu102_platform") +platform = client.get_component(name=platform_dict["board_name"]) status = platform.build() status = platform.build() diff --git a/Embedded_Software/Getting_Started/scripts/create_vck190_xsa.tcl b/Embedded_Software/Getting_Started/scripts/create_vck190_xsa.tcl new file mode 100644 index 0000000000..5ef7c0e4b5 --- /dev/null +++ b/Embedded_Software/Getting_Started/scripts/create_vck190_xsa.tcl @@ -0,0 +1,25 @@ +# +# Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Luke Millar + +set implement 0 + +create_project vck190 vck190 -part xcvc1902-vsva2197-2MP-e-S + +set_property board_part xilinx.com:vck190:part0:3.4 [current_project] +create_bd_design "ext_platform" -mode batch + +instantiate_example_design -template xilinx.com:design:ext_platform:1.0 -design ext_platform -options { Include_AIE.VALUE true Include_BDC.Value false } + +generate_target all [get_files vck190/vck190.srcs/sources_1/bd/ext_platform/ext_platform.bd] + +if {$implement == 1} { + launch_runs impl_1 -to_step write_bitstream + write_hw_platform -include_bit -fixed -force -file vck190/design_1_wrapper.xsa + exit +} else { + write_hw_platform -fixed -force -file vck190/design_1_wrapper.xsa + exit +} diff --git a/Embedded_Software/Getting_Started/scripts/create_vek280_xsa.tcl b/Embedded_Software/Getting_Started/scripts/create_vek280_xsa.tcl new file mode 100644 index 0000000000..86d82df788 --- /dev/null +++ b/Embedded_Software/Getting_Started/scripts/create_vek280_xsa.tcl @@ -0,0 +1,25 @@ +# +# Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Luke Millar + +set implement 0 + +create_project vek280 vek280 -part xcve2802-vsvh1760-2MP-e-S + +set_property board_part xilinx.com:vek280:part0:1.2 [current_project] +create_bd_design "versal_comn_platform" -mode batch + +instantiate_example_design -template xilinx.com:design:versal_comn_platform:2.0 -design versal_comn_platform -options { Include_AIE.VALUE true } + +generate_target all [get_files vek280/vek280.srcs/sources_1/bd/versal_comn_platform/versal_comn_platform.bd] + +if {$implement == 1} { + launch_runs impl_1 -to_step write_bitstream + write_hw_platform -include_bit -fixed -force -file vek280/design_1_wrapper.xsa + exit +} else { + write_hw_platform -fixed -force -file vek280/design_1_wrapper.xsa + exit +} diff --git a/Embedded_Software/Getting_Started/scripts/create_vek385_xsa.tcl b/Embedded_Software/Getting_Started/scripts/create_vek385_xsa.tcl new file mode 100644 index 0000000000..f2e533df54 --- /dev/null +++ b/Embedded_Software/Getting_Started/scripts/create_vek385_xsa.tcl @@ -0,0 +1,25 @@ +# +# Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Luke Millar + +set implement 0 + +create_project vek385 vek385 -part xc2ve3858-ssva2112-2MP-e-S + +set_property board_part xilinx.com:vek385:part0:1.1 [current_project] +create_bd_design "versal_comn_platform" -mode batch + +instantiate_example_design -template xilinx.com:design:versal_comn_platform:2.0 -design versal_comn_platform -options { Include_AIE.VALUE true } + +generate_target all [get_files vek385/vek385.srcs/sources_1/bd/versal_comn_platform/versal_comn_platform.bd] + +if {$implement == 1} { + launch_runs impl_1 -to_step write_bitstream + write_hw_platform -include_bit -fixed -force -file vek385/design_1_wrapper.xsa + exit +} else { + write_hw_platform -fixed -force -file vek385/design_1_wrapper.xsa + exit +} diff --git a/Embedded_Software/Getting_Started/scripts/create_zcu102_xsa.tcl b/Embedded_Software/Getting_Started/scripts/create_zcu102_xsa.tcl new file mode 100644 index 0000000000..661a8a9bd8 --- /dev/null +++ b/Embedded_Software/Getting_Started/scripts/create_zcu102_xsa.tcl @@ -0,0 +1,25 @@ +# +# Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# +# Author: Luke Millar + +set implement 0 + +create_project zcu102 zcu102 -part xczu9eg-ffvb1156-2-e + +set_property board_part xilinx.com:zcu102:part0:3.4 [current_project] +create_bd_design "mpsoc_preset" -mode batch + +instantiate_example_design -template xilinx.com:design:mpsoc_preset:1.0 -design mpsoc_preset -options { Preset.VALUE MPSoC_PL} + +generate_target all [get_files zcu102/zcu102.srcs/sources_1/bd/mpsoc_preset/mpsoc_preset.bd] + +if {$implement == 1} { + launch_runs impl_1 -to_step write_bitstream + write_hw_platform -include_bit -fixed -force -file zcu102/design_1_wrapper.xsa + exit +} else { + write_hw_platform -fixed -force -file zcu102/design_1_wrapper.xsa + exit +} diff --git a/Getting_Started/Vitis/HLS_Kernels/Makefile b/Getting_Started/Vitis/HLS_Kernels/Makefile index 3c1237da70..cf3e2998d8 100644 --- a/Getting_Started/Vitis/HLS_Kernels/Makefile +++ b/Getting_Started/Vitis/HLS_Kernels/Makefile @@ -1,7 +1,7 @@ #Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT -PLATFORM = $(PLATFORM_REPO_PATHS)/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm +PLATFORM = $(PLATFORM_REPO_PATHS)/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm s2mm = ./s2mm/s2mm.xo diff --git a/Getting_Started/Vitis/README.md b/Getting_Started/Vitis/README.md index 8100d0efc1..d74fbb9d7b 100644 --- a/Getting_Started/Vitis/README.md +++ b/Getting_Started/Vitis/README.md @@ -14,7 +14,7 @@ # Vitis Introduction and Getting Started Tutorial -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** Welcome to Vitis Getting Started! @@ -29,7 +29,7 @@ Please read the tutorial in the same order as listed here to better understand t ## Prerequisites -1. Source Vitis 2025.1: +1. Source Vitis 2025.2: ``` source /settings64.sh @@ -38,7 +38,7 @@ Please read the tutorial in the same order as listed here to better understand t 2. Export the following variable: ``` - export COMMON_IMAGE_VERSAL= + export COMMON_IMAGE_VERSAL= ``` 3. To compile the binaries: diff --git a/Getting_Started/Vitis/Vitis_ToolFlow.md b/Getting_Started/Vitis/Vitis_ToolFlow.md index 80443928c9..7f38e3880a 100644 --- a/Getting_Started/Vitis/Vitis_ToolFlow.md +++ b/Getting_Started/Vitis/Vitis_ToolFlow.md @@ -28,7 +28,7 @@ AMD Vitis Unified Software Platform offers range of libraries along with compile The first and foremost component to get started with Vitis Acceleration flow is an **extensible hardware platform**. The XSA file generated from Vivado is an extensible hardware platform, the word extensible means the platform is not complete yet and more logic will be added later to the platform. Also, to quickly get started with Versal designing, AMD provides platforms targeted to the respective boards. -For customer platfoms and steps to create an extensible hardware platform, please refer to the [Platform Tutorial](https://github.com/Xilinx/Vitis-Tutorials/blob/2025.1/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/step1.md) +For customer platfoms and steps to create an extensible hardware platform, please refer to the [Platform Tutorial](../../Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/) ```mermaid graph TD; diff --git a/Getting_Started/Vitis/vitis_dir/Makefile b/Getting_Started/Vitis/vitis_dir/Makefile index 49473eaaaf..40d1b3e91b 100644 --- a/Getting_Started/Vitis/vitis_dir/Makefile +++ b/Getting_Started/Vitis/vitis_dir/Makefile @@ -5,7 +5,7 @@ all: linker packager TARGET ?= hw_emu -PLATFORM = $(PLATFORM_REPO_PATHS)/xilinx_vck190_base_202510_1/xilinx_vck190_base_202510_1.xpfm +PLATFORM = $(PLATFORM_REPO_PATHS)/xilinx_vck190_base_202520_1/xilinx_vck190_base_202520_1.xpfm # Rootfs and Image @@ -26,6 +26,7 @@ linker: $(s2mm) $(mm2s) $(libadf) packager: v++ --package --target ${TARGET} \ + --platform ${PLATFORM} \ --config pack.cfg \ --package.defer_aie_run \ --package.kernel_image=${IMAGE} \ diff --git a/Getting_Started/Vitis/vitis_dir/README.md b/Getting_Started/Vitis/vitis_dir/README.md index 7c48a55655..bfdfbc9328 100644 --- a/Getting_Started/Vitis/vitis_dir/README.md +++ b/Getting_Started/Vitis/vitis_dir/README.md @@ -24,7 +24,7 @@ As discussed in the tutorial introduction page, the Vitis linker inputs are kern 2. `mm2s.xo` and `s2mm.xo`: HLS/PL kernels 3. `xilinx_vck190_base_202510_1.xpfm`: AMD provided platform -> **Important Note:** This tutorial uses the AMD provided platform. For custom platform flow details, please check tutorials under [Vitis_Platform_Creation](https://github.com/Xilinx/Vitis-Tutorials/tree/2025.1/Vitis_Platform_Creation) +> **Important Note:** This tutorial uses the AMD provided platform. For custom platform flow details, please check tutorials under [Vitis_Platform_Creation](../../../Vitis_Platform_Creation/) With the input kernels and platform ready, we need to define the connection of these kernel using a configuration file, let's call it system.cfg. @@ -116,9 +116,9 @@ save-temps=1 [package] boot_mode=sd out_dir=pack_out_dir -rootfs=/xilinx-versal-common-v2025.1/rootfs.ext4 +rootfs=/xilinx-versal-common-v2025.2/rootfs.ext4 image_format=ext4 -kernel_image=/xilinx-versal-common-v2025.1/Image +kernel_image=/xilinx-versal-common-v2025.2/Image sd_file=host.exe ``` diff --git a/Getting_Started/Vitis/vitis_dir/pack.cfg b/Getting_Started/Vitis/vitis_dir/pack.cfg index 82dcf05c1d..fdfbaf5a96 100644 --- a/Getting_Started/Vitis/vitis_dir/pack.cfg +++ b/Getting_Started/Vitis/vitis_dir/pack.cfg @@ -1,4 +1,3 @@ -platform=xilinx_vck190_base_202510_1 save-temps=1 [package] diff --git a/Getting_Started/Vitis_HLS/README.md b/Getting_Started/Vitis_HLS/README.md index 84856dd184..5bcf72b053 100644 --- a/Getting_Started/Vitis_HLS/README.md +++ b/Getting_Started/Vitis_HLS/README.md @@ -13,7 +13,7 @@ # Vitis HLS Analysis and Optimization -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Introduction @@ -24,18 +24,18 @@ Vitis High-Level Synthesis (HLS) enables you to compile C/C++ code into RTL code The labs in this tutorial use: * BASH Linux shell commands. -* 2025.1 Vitis core development kit release. +* Vitis core development kit release. >**IMPORTANT:** > -> * Before running any of the examples, make sure you have installed the Vitis core development kit as described in [Installation](https://docs.amd.com/r/en-US/ug1393-vitis-application-acceleration/Installation) in the Vitis Unified Software Platform Documentation: Application Acceleration Development (UG1393). +> * Before running any of the examples, make sure you have installed the Vitis Software Platform as described in Vitis release notes [Installing the Vitis](https://docs.amd.com/r/en-US/ug1742-vitis-release-notes/Vitis-Software-Platform-Installation). ### Setup the environment to run Vitis To configure the environment to run Vitis, run the following scripts which set up the environment to run in a specific command shell. ```bash -source /Vitis/2025.1/settings64.sh +source /settings64.sh source /opt/xilinx/xrt/setup.sh ``` diff --git a/Getting_Started/Vitis_Libraries/README.md b/Getting_Started/Vitis_Libraries/README.md index 5cea767540..3013117950 100644 --- a/Getting_Started/Vitis_Libraries/README.md +++ b/Getting_Started/Vitis_Libraries/README.md @@ -14,18 +14,18 @@ # Getting Started With Vitis Libraries -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** This tutorial focuses on how to leverage the AMD Vitis™ Libraries to build your own design. The tutorial will use FFT's L1 library as an example. It contains instructions from cloning the library, compile, and simulate on its own till instantiate it into top-level design. ## Before You Begin ### Setup Environment -Before playing with the libraries, set up the Vitis environment first. For instructions on setting up the Vitis environment, refer to [Setting Up the Vitis Environment](https://docs.amd.com/r/en-US/ug1393-vitis-application-acceleration/Setting-Up-the-Vitis-Environment). +Before playing with the libraries, set up the Vitis environment first. For instructions on setting up the Vitis environment, refer to [Setting Up the Vitis Environment](https://docs.amd.com/r/en-US/ug1742-vitis-release-notes/Setting-Up-the-Environment-to-Run-the-Vitis-Software-Platform). Below are the example scripts to set up Vitis and XRT, and to specify the location of the platforms you have installed. ``` -$ source /Vitis/2025.1/settings64.sh +$ source /settings64.sh $ source /opt/xilinx/xrt/setup.sh $ export PLATFORM_REPO_PATHS= @@ -53,128 +53,115 @@ Vitis_Libraries/ ├── LICENSE.txt ├── README.md ├── blas/ -├── codec/ -├── data_analytics/ -├── data_compression/ ├── data_mover/ -├── database/ ├── dsp/ -├── graph/ -├── hpc/ ├── motor_control/ -├── quantitative_finance/ ├── security/ ├── solver/ -├── sparse/ ├── ultrasond/ ├── utils/ └── vision/ ~~~ -Libraries are written in C++ and typically contain three levels of abstractions: +Vitis library is organized into L1, L2, and L3 folders, each relating to a different stage of application development. -* L1: Module level, it provides optimized hardware implementation of the core LZ based and data compression specific modules like lz4 compress and snappy compress. -* L2: Kernel level, a demo on lz4, snappy, zlib, and zstd data compression algorithms are shown via kernel, which internally uses the optimized hardware modules. -* L3: The software API level wraps the details of offloading acceleration with prebuilt binary (overlay) and allows users to accelerate data compression tasks on the AMD Alveo™ cards without hardware development. +* L1 : Makefiles and sources in L1 facilitate HLS based flow for quick checks. Tasks at this level include: +* L2 : Makefiles and sources in L2 facilitate building XCLBIN file from various sources (HDL, HLS or XO files) of kernels with host code written in OpenCL/XRT framework targeting a device. This flow supports: +* L3 : Makefiles and sources in L3 demonstrate applications developed involving multiple kernels in pipeline. These Makefiles can be used for executing tasks, as with the L2 Makefiles. In this lab, you are going to use the **dsp** library. So enter the the sub-directory *dsp*, and you can find following directory structure. ~~~ dsp/ +├── docs +│   ├── Doxyfile +│   ├── Makefile +│   ├── README.md +│   └── src +├── ext +│   ├── make_utility +│   ├── README.md +│   └── xcl2 ├── Jenkinsfile -├── L1/ -│ ├── README.md -│ ├── examples/ -│ ├── include/ -│ ├── meta/ -│ ├── src/ -│ └── tests/ -├── L2/ -│ ├── README.md -│ ├── benchmarks/ -│ ├── examples/ -│ ├── include/ -│ ├── meta/ -│ └── tests/ +├── L1 +│   ├── examples +│   ├── include +│   ├── meta +│   ├── README.md +│   ├── src +│   └── tests +├── L2 +│   ├── benchmarks +│   ├── examples +│   ├── include +│   ├── meta +│   ├── README.md +│   └── tests +├── library.json ├── LICENSE.txt ├── README.md -├── docs/ -│ ├── Doxyfile -│ ├── Makefile -│ ├── Makefile.sphinx -│ ├── README.md -│ └── src/ -├── ext/ -│ ├── README.md -│ ├── make_utility/ -│ └── xcl2/ -└── library.json + ~~~ ## Create and run an HLS Component -In this step, you are going to create an HLS component by using the files provided in the [1Dfix_impulse](https://github.com/Xilinx/Vitis_Libraries/tree/main/dsp/L1/examples/1Dfix_impulse) L1 examples of the Vitis `dsp` library. The source files and script file are all located under this folder. Here, it is assumed that you have cloned the Vitis Libraries into */Vitis_Libraries* directory. - -1. Go into the `/Vitis_libraries/dsp/L1/examples/1Dfix_impulse` folder, create a directory to use as a workspace, and launch the Vitis unified IDE to create an HLS component as described in [Building and Running an HLS Component](https://docs.amd.com/r/en-US/ug1399-vitis-hls/Building-and-Running-an-HLS-Component). +In this step, you are going to create an HLS component by using the files provided in the [1Dfix_impulse](https://github.com/Xilinx/Vitis_Libraries/tree/main/dsp/L1/examples/1Dfix_impulse) L1 examples of the Vitis `dsp` library. The source files and script file are all located under this folder. -``` - mkdir myProject - vitis -w myProject -``` - -The Vitis unified IDE opens as shown below. - - ![Welcome Screen](images/welcome-screen.png) - - 2. Select **File > New Component > HLS** to create a new HLS component. +1. Launch Vitis Unified IDE + ``` + vitis + ``` +2. Select **File > New Component > HLS** to create a new HLS component. - This opens the **Name and Location** page of the **Create HLS Component** wizard - * Enter the **Component name:** `implTest` - * Enter the **Component location:** *Leave as set for the workspace* - * Click **Next** to move forward - - This opens the **Configuration File** page - * Select the **Empty File** radio button - * Leave the **New configuration file name** as the default: `hls_config` - * Click **Next** to move forward - - This opens the **Add Source Files** page - * Under **Design Files** select the **Add Files** command icon, - * Browse to the `examples/1Dfix_impulse/src` folder, select the `top_module.cpp` file, and click **Open** to add the file and close the dialog. - * In the **CFLAGS** entry field next to the `top_module.cpp` file, paste the following text to provide an include path: - `-I/Vitis_Libraries/dsp/L1/include/hw/vitis_fft/fixed` - - * Select **Browse** next to **Top Function** - * Select the `fft_top(int * int *)` top module, and select **OK** to close the dialog box - - * Under **Test Bench Files** select the **Add Files** command icon - * Browse to `examples/1Dfix_impulse/src` folder, select the `main.cpp` file, and click **Open** to add the file and close the dialog. - * In the **CFLAGS** entry field next to the `main.cpp` file, paste the following text to provide an include path: - `-I/Vitis_Libraries/dsp/L1/include/hw/vitis_fft/fixed` - * Click **Next** to move forward. - - ![Add Source Files](images/hls-component-sources.png) + This opens the **Name and Location** page of the **Create HLS Component** wizard + * Enter the **Component name:** `implTest` + * Enter the **Component location:** *Point to the folder serves as workspace. e.g. myProject* + * Click **Next** to move forward - This opens the **Hardware** page - * Click **Next** to accept the default part and move forward. - - This opens the **Settings** page. - * Click **Next** to accept all defaults and move forward. - - This opens the **Summary** page. - * Review the page contents and click **Finish** to create the HLS component as defined. - + ![Add Source Files](./images/create_hls_comp.png) + + This opens the **Configuration File** page + * Select the **Empty File** radio button + * Leave the **New configuration file name** as the default: `hls_config` + * Click **Next** to move forward + + This opens the **Add Source Files** page + * Under **Design Files** select the **Add Files** command icon, + * Browse to the `/Vitis_Libraries/dsp/L1/examples/1Dfix_impulse/src` folder, select the `top_module.cpp` file, and click **Open** to add the file and close the dialog. + * In the **CFLAGS** entry field next to the `top_module.cpp` file, paste the following text to provide an include path: `-I./` + + * Select **Browse** next to **Top Function** + * Select the `fft_top(int * int *)` top module, and select **OK** to close the dialog box + + * Under **Test Bench Files** select the **Add Files** command icon + * Browse to `examples/1Dfix_impulse/src` folder, select the `main.cpp` file, and click **Open** to add the file and close the dialog. + * In the **CFLAGS** entry field next to the `main.cpp` file, paste the following text to provide an include path: `-I./` + * Click **Next** to move forward. + + ![Add Source Files](images/hls-component-sources.png) + + This opens the **Hardware** page + * Click **Next** to accept the default part and move forward. + + This opens the **Settings** page. + * Click **Next** to accept all defaults and move forward. + + This opens the **Summary** page. + * Review the page contents and click **Finish** to create the HLS component as defined. - 3. The HLS component is created in the Vitis unified IDE and opened in the Flow Navigator. - - ![Flow Navigator](images/hls-component-flow.png) - You can browse into the Settings, view the and open the `top_module.cpp` file by selecting the source file in the Vitis Components Explorer view. The `top_module.cpp` calls the FFT library and the parameters are defined in the `data_path.hpp` file. For detailed instructions on using the FFT library, refer to the [Vitis Library](https://docs.amd.com/r/en-US/Vitis_Libraries/dsp/index.html). +3. The HLS component is created in the Vitis unified IDE and opened in the Flow Navigator. Now we need to set the relative_roots for the include path. +* Open the `hls_config.cfg` configuration file by selecting it under the Settings heading in the Vitis Components Explorer view, or by selecting it from the open `vitis-comp.json` file for the HLS component. +* From **All Settings** > **General**, Click **Add item** under hls.relative_roots, input `/Vitis_Libraries/dsp/L1/include/hw/vitis_fft/fixed` - * In Flow Navigator select **Run** under the **C Simulation** heading - * Select **Run** under the **C Synthesis** heading - * Select **Run** under the **C/RTL Co-simulation** heading + ![Flow Navigator](./images/relative_roots.png) + You can browse into the Settings, view and open the `top_module.cpp` file by selecting the source file in the Vitis Explorer view. The `top_module.cpp` calls the FFT library and the parameters are defined in the `data_path.hpp` file. For detailed instructions on using the FFT library, refer to the [Vitis DSP Library](https://docs.amd.com/r/en-US/Vitis_Libraries/dsp/index.html). + + * In Flow Navigator select **Run** under the **C Simulation** + * Select **Run** under the **C Synthesis** + * Select **Run** under the **C/RTL Co-simulation** + After C/RTL Co-Simulation, the following results are returned. ~~~ ... @@ -227,10 +214,10 @@ The testbench uses a single pulse signal as input to the FFT and the output shou 4. View the Waveform during C/RTL Co-Simulation (optional) - Open the `hls_config.cfg` configuration file by selecting it under the Settings heading in the Vitis Components Explorer view, or by selecting it from the open `vitis-comp.json` file for the HLS component. + Open the `hls_config.cfg` configuration file * Scrool down to the **C/RTL Cosimulation** section of the Config File editor - * Under **trace_level** select **all** - * Enable the **wave_debug** option + * Under **hls.cosim.trace_level** select **all** + * Enable the **hls.cosim.wave_debug** option * In the Flow Navigator select **Run** under the **C/RTL Co-simulation** heading In this way, you get the simulation waveform, such as the following example for a single SSR stream port: @@ -336,7 +323,7 @@ At this point the tutorial is complete. You can `Run Implementation` from Flow N In this tutorial, you learned how to leverage a L1 Vitis library element to build your own HLS component and export a Vivado IP. The FFT example is selected for explanation, and you can follow a similar flow to use other library elements. -**Note:** The [Makefile](./Makefile) is provided as a reference if you'd like to explore the CLI flow. +**Note:** The [Makefile](./Makefile) is provided as a reference if you'd like to explore the CLI flow. There are multiple ways to run the command-line flow, and the provided Makefile may not represent the optimal approach. ## Reference diff --git a/Getting_Started/Vitis_Libraries/images/create_hls_comp.png b/Getting_Started/Vitis_Libraries/images/create_hls_comp.png new file mode 100644 index 0000000000..98393ac045 Binary files /dev/null and b/Getting_Started/Vitis_Libraries/images/create_hls_comp.png differ diff --git a/Getting_Started/Vitis_Libraries/images/hls-component-flow.png b/Getting_Started/Vitis_Libraries/images/hls-component-flow.png deleted file mode 100644 index 2a5652637a..0000000000 Binary files a/Getting_Started/Vitis_Libraries/images/hls-component-flow.png and /dev/null differ diff --git a/Getting_Started/Vitis_Libraries/images/hls-component-sources.png b/Getting_Started/Vitis_Libraries/images/hls-component-sources.png index f833c53a00..0868ede655 100644 Binary files a/Getting_Started/Vitis_Libraries/images/hls-component-sources.png and b/Getting_Started/Vitis_Libraries/images/hls-component-sources.png differ diff --git a/Getting_Started/Vitis_Libraries/images/relative_roots.png b/Getting_Started/Vitis_Libraries/images/relative_roots.png new file mode 100644 index 0000000000..b84593747e Binary files /dev/null and b/Getting_Started/Vitis_Libraries/images/relative_roots.png differ diff --git a/Getting_Started/Vitis_Libraries/images/welcome-screen.png b/Getting_Started/Vitis_Libraries/images/welcome-screen.png deleted file mode 100644 index 7f0721c3c9..0000000000 Binary files a/Getting_Started/Vitis_Libraries/images/welcome-screen.png and /dev/null differ diff --git a/Getting_Started/Vitis_Libraries/src/datain.txt b/Getting_Started/Vitis_Libraries/src/datain.txt deleted file mode 100644 index 2a3a4b9a8a..0000000000 --- a/Getting_Started/Vitis_Libraries/src/datain.txt +++ /dev/null @@ -1,17 +0,0 @@ -00004000 -00000000 -00000000 -00000000 -00000000 -00000000 -00000000 -00000000 -00000000 -00000000 -00000000 -00000000 -00000000 -00000000 -00000000 -00000000 - diff --git a/Getting_Started/Vitis_Libraries/src/dataref.txt b/Getting_Started/Vitis_Libraries/src/dataref.txt deleted file mode 100644 index 3764201d20..0000000000 --- a/Getting_Started/Vitis_Libraries/src/dataref.txt +++ /dev/null @@ -1,17 +0,0 @@ -00004000 -00004000 -00004000 -00004000 -00004000 -00004000 -00004000 -00004000 -00004000 -00004000 -00004000 -00004000 -00004000 -00004000 -00004000 -00004000 - diff --git a/Getting_Started/Vitis_Libraries/src/fft_tb.v b/Getting_Started/Vitis_Libraries/src/fft_tb.v deleted file mode 100644 index 7fbf7b8272..0000000000 --- a/Getting_Started/Vitis_Libraries/src/fft_tb.v +++ /dev/null @@ -1,175 +0,0 @@ -/* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -SPDX-License-Identifier: X11 -*/ - - -module fft_tb; - - - reg clk; - reg rst; - reg start; - wire done; - wire idle; - wire ready; - - wire inData_0_ce; - wire inData_1_ce; - wire inData_2_ce; - wire inData_3_ce; - - wire [31:0] inData_0; - wire [31:0] inData_1; - wire [31:0] inData_2; - wire [31:0] inData_3; - - wire outData_0_we; - wire outData_1_we; - wire outData_2_we; - wire outData_3_we; - - wire [41:0] outData_0; - wire [41:0] outData_1; - wire [41:0] outData_2; - wire [41:0] outData_3; - - reg [31:0] data_in [0:15]; - reg [41:0] data_out [0:15]; - reg [41:0] data_ref [0:15]; - - reg [7:0] inAddr_0; - reg [7:0] inAddr_1; - reg [7:0] inAddr_2; - reg [7:0] inAddr_3; - - reg [7:0] outAddr_0; - reg [7:0] outAddr_1; - reg [7:0] outAddr_2; - reg [7:0] outAddr_3; - - integer i, error; - - fft_wrap DUT ( - .inData_0_ce (inData_0_ce), - .inData_1_ce (inData_1_ce), - .inData_2_ce (inData_2_ce), - .inData_3_ce (inData_3_ce), - .inData_0 (inData_0), - .inData_1 (inData_1), - .inData_2 (inData_2), - .inData_3 (inData_3), - .outData_0_we (outData_0_we), - .outData_1_we (outData_1_we), - .outData_2_we (outData_2_we), - .outData_3_we (outData_3_we), - .outData_0 (outData_0), - .outData_1 (outData_1), - .outData_2 (outData_2), - .outData_3 (outData_3), - - .clk (clk), - .rst (rst), - .start (start), - .done (done), - .idle (idle), - .ready (ready) - -); - - // Clock gen - initial begin - clk = 1'b0; - forever #2.5 clk = !clk; - end - - // reset logic - initial begin - rst = 1'b1; - #100 rst = 1'b0; - end - - // start logic - initial begin - start = 1'b0; - wait (rst == 1'b0); - #100 @(posedge clk) start = 1'b1; - wait (done == 1'b1); - @(posedge clk) start = 1'b0; - end - - // data input stream logic - assign inData_0 = data_in[inAddr_0]; - assign inData_1 = data_in[inAddr_1]; - assign inData_2 = data_in[inAddr_2]; - assign inData_3 = data_in[inAddr_3]; - - initial begin - $readmemh("datain.txt", data_in); - $readmemh("dataref.txt", data_ref); - inAddr_0 = 0; - inAddr_1 = 4; - inAddr_2 = 8; - inAddr_3 = 12; - forever @ (posedge clk) fork - if (inData_0_ce) inAddr_0 = inAddr_0 + 1; - if (inData_1_ce) inAddr_1 = inAddr_1 + 1; - if (inData_2_ce) inAddr_2 = inAddr_2 + 1; - if (inData_3_ce) inAddr_3 = inAddr_3 + 1; - join - end - - // data output stream logic - initial begin - outAddr_0 = 0; - outAddr_1 = 4; - outAddr_2 = 8; - outAddr_3 = 12; - forever @ (posedge clk) fork - if (outData_0_we) begin - data_out [outAddr_0] <= outData_0; - outAddr_0 <= outAddr_0 + 1; - end - - if (outData_1_we) begin - data_out [outAddr_1] <= outData_1; - outAddr_1 <= outAddr_1 + 1; - end - - if (outData_2_we) begin - data_out [outAddr_2] <= outData_2; - outAddr_2 <= outAddr_2 + 1; - end - - if (outData_3_we) begin - data_out [outAddr_3] <= outData_3; - outAddr_3 <= outAddr_3 + 1; - end - - join - end - - // data validation - initial begin - error = 0; - #100 - @ (negedge done); - #100 - for (i = 0; i < 16; i = i + 1) begin - if (data_out[i] !== data_ref[i]) begin - error = error + 1; - end - end - if (error != 0) begin - $display("Result verification FAILED!"); - end else begin - $display("Result verification SUCCEED!"); - end - - #300 $display("Simulation finished."); - $finish; - - end - - -endmodule diff --git a/Getting_Started/Vitis_Libraries/src/fft_wrap.v b/Getting_Started/Vitis_Libraries/src/fft_wrap.v deleted file mode 100644 index c69f432789..0000000000 --- a/Getting_Started/Vitis_Libraries/src/fft_wrap.v +++ /dev/null @@ -1,72 +0,0 @@ -/* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -SPDX-License-Identifier: X11 -*/ - -`timescale 1ns / 1ps - -module fft_wrap ( - output inData_0_ce, - output inData_1_ce, - output inData_2_ce, - output inData_3_ce, - - input [31:0] inData_0, - input [31:0] inData_1, - input [31:0] inData_2, - input [31:0] inData_3, - - output outData_0_we, - output outData_1_we, - output outData_2_we, - output outData_3_we, - - output [41:0] outData_0, - output [41:0] outData_1, - output [41:0] outData_2, - output [41:0] outData_3, - - input clk, - input rst, - input start, - output done, - output idle, - output ready - -); - - fft_top_0 fft_core ( - .ap_clk (clk), - .ap_rst (rst), - .ap_start (start), - .ap_done (done), - .ap_idle (idle), - .ap_ready (ready), - - .p_inData_0_dout (inData_0), - .p_inData_0_empty_n (1'b1), - .p_inData_0_read (inData_0_ce), - .p_inData_1_dout (inData_1), - .p_inData_1_empty_n (1'b1), - .p_inData_1_read (inData_1_ce), - .p_inData_2_dout (inData_2), - .p_inData_2_empty_n (1'b1), - .p_inData_2_read (inData_2_ce), - .p_inData_3_dout (inData_3), - .p_inData_3_empty_n (1'b1), - .p_inData_3_read (inData_3_ce), - .p_outData_0_din (outData_0), - .p_outData_0_full_n (1'b1), - .p_outData_0_write (outData_0_we), - .p_outData_1_din (outData_1), - .p_outData_1_full_n (1'b1), - .p_outData_1_write (outData_1_we), - .p_outData_2_din (outData_2), - .p_outData_2_full_n (1'b1), - .p_outData_2_write (outData_2_we), - .p_outData_3_din (outData_3), - .p_outData_3_full_n (1'b1), - .p_outData_3_write (outData_3_we) -); - -endmodule diff --git a/Getting_Started/Vitis_Platform/README.md b/Getting_Started/Vitis_Platform/README.md index 91ff167d98..5f87a249ea 100644 --- a/Getting_Started/Vitis_Platform/README.md +++ b/Getting_Started/Vitis_Platform/README.md @@ -14,7 +14,7 @@ # Versal Platform Creation Quick Start -***Vitis Unified IDE 2025.1***, ***Vivado 2025.1*** +***Vitis Unified IDE 2025.2***, ***Vivado 2025.2*** ***Board: VCK190 VEK280*** @@ -22,7 +22,7 @@ In this module, we will get started with three steps to quickly create a platfor This time, we will utilize the AMD Versal™ extensible platform from the CED example, using a pre-built Linux common image and a device tree file generated with the Platform Creation. Next, we will create an embedded Versal acceleration platform using the AMD Vitis™ Unified IDE. Finally, we will validate this platform using the Vector Addition example. -This is a quick start guide for Versal platform creation. If you have questions about specific steps or settings, or if you need to create a platform for a customer's board, please refer to[Versal Custom Platform Creation Tutorial](https://github.com/Xilinx/Vitis-Tutorials/tree/2025.1/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190). Besides, if you need to customize the Linux system image, refer to the [PetaLinux customization page](https://github.com/Xilinx/Vitis-Tutorials/tree/2025.1/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization) for reference. +This is a quick start guide for Versal platform creation. If you have questions about specific steps or settings, or if you need to create a platform for a customer's board, please refer to[Versal Custom Platform Creation Tutorial](https://github.com/Xilinx/Vitis-Tutorials/tree/2025.2/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190). Besides, if you need to customize the Linux system image, refer to the [PetaLinux customization page](https://github.com/Xilinx/Vitis-Tutorials/tree/2025.2/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization) for reference. ## Step 1: Create Vivado Design and Generate XSA @@ -110,12 +110,12 @@ This is a quick start guide for Versal platform creation. If you have questions 1. Download Versal common image from [AMD website download page](https://www.xilinx.com/support/download.html), place it under your `WorkSpace` directory, and extract the common image. ```bash - tar xvf ../xilinx-versal-common-v2025.1.tar.gz . + tar xvf ../xilinx-versal-common-v2025.2.tar.gz . ``` 2. Create Vitis platform - - Install SDK tool by typing `sh xilinx-versal-common-v2025.1/sdk.sh -d xilinx-versal-common-v2025.1/ -y` in console. Option `-d` is to specify the directory where to install. Option `-y` means confirmation. So it gets installed in `xilinx-versal-common-v2025.1/` folder. + - Install SDK tool by typing `sh xilinx-versal-common-v2025.2/sdk.sh -d xilinx-versal-common-v2025.2/ -y` in console. Option `-d` is to specify the directory where to install. Option `-y` means confirmation. So it gets installed in `xilinx-versal-common-v2025.2/` folder. >Note: The SDK installation is not required for platform creation; it is needed for application compilation. You can install it later as needed. @@ -145,7 +145,7 @@ This is a quick start guide for Versal platform creation. If you have questions ![vitis_platform_config](images/vitis_platform_config.PNG) - - **Pre-Built Image Directory**: Browse to extracted common image path directory: `xilinx-versal-common-v2025.1/` and click OK. Bootgen looks for boot components referred by BIF in this directory to generate `BOOT.BIN`. + - **Pre-Built Image Directory**: Browse to extracted common image path directory: `xilinx-versal-common-v2025.2/` and click OK. Bootgen looks for boot components referred by BIF in this directory to generate `BOOT.BIN`. - **DTB file**: It will be generated automatically and populated in this area. - **FAT32 Partition Directory**: if you have additional file to be stored in FAT32 partition diretory you can browse to the file. If not please omit this. - **QEMU Data**: This Directory is used to add additional file for emulation. User can set it according to your requirement. @@ -168,9 +168,9 @@ This is a quick start guide for Versal platform creation. If you have questions >Note: If you target VEK280, please select `vek280_custom` platform. -- Input **Sysroot** path: `xilinx-versal-common-v2025.1/sysroots/cortexa72-cortexa53-amd-linux` -- Input **RootFS** path: `xilinx-versal-common-v2025.1/rootfs.ext4` -- Input **Kernel Image** path: `xilinx-versal-common-v2025.1/Image` and click **Next**. +- Input **Sysroot** path: `xilinx-versal-common-v2025.2/sysroots/cortexa72-cortexa53-amd-linux` +- Input **RootFS** path: `xilinx-versal-common-v2025.2/rootfs.ext4` +- Input **Kernel Image** path: `xilinx-versal-common-v2025.2/Image` and click **Next**. - Review the project summary and click **Finish**. After seconds, the project is created. diff --git a/Getting_Started/Vitis_Platform/images/vivado_download_example.png b/Getting_Started/Vitis_Platform/images/vivado_download_example.png index 476c19e6bc..78b4a4447c 100644 Binary files a/Getting_Started/Vitis_Platform/images/vivado_download_example.png and b/Getting_Started/Vitis_Platform/images/vivado_download_example.png differ diff --git a/Getting_Started/Vitis_Platform/ref_files/vck190/Makefile b/Getting_Started/Vitis_Platform/ref_files/vck190/Makefile index dc79968496..44e078d790 100644 --- a/Getting_Started/Vitis_Platform/ref_files/vck190/Makefile +++ b/Getting_Started/Vitis_Platform/ref_files/vck190/Makefile @@ -1,5 +1,5 @@ #/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +#Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT #*/ @@ -10,7 +10,7 @@ ABS_HW_PATH=$(ABS_BUILD_PATH)/vivado BD_TCL=run.tcl ABS_BD_TCL=$(ROOT_DIR)/$(BD_TCL) -VERSION=2025.1 +VERSION=2025.2 COMMON_IMAGE_VERSAL ?=${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v$(VERSION)/ SYSROOT=$(COMMON_IMAGE_VERSAL)/sysroots/cortexa72-cortexa53-amd-linux/ XSA_NAME=vck190_custom diff --git a/Getting_Started/Vitis_Platform/ref_files/vck190/makefile_aie b/Getting_Started/Vitis_Platform/ref_files/vck190/makefile_aie index f61a875b24..423ef98d20 100644 --- a/Getting_Started/Vitis_Platform/ref_files/vck190/makefile_aie +++ b/Getting_Started/Vitis_Platform/ref_files/vck190/makefile_aie @@ -1,5 +1,5 @@ #/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +#Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT #*/ diff --git a/Getting_Started/Vitis_Platform/ref_files/vck190/makefile_vadd b/Getting_Started/Vitis_Platform/ref_files/vck190/makefile_vadd index 9a94d81832..9959ed2352 100644 --- a/Getting_Started/Vitis_Platform/ref_files/vck190/makefile_vadd +++ b/Getting_Started/Vitis_Platform/ref_files/vck190/makefile_vadd @@ -1,5 +1,5 @@ #/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +#Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT #*/ diff --git a/Getting_Started/Vitis_Platform/ref_files/vck190/run.tcl b/Getting_Started/Vitis_Platform/ref_files/vck190/run.tcl index 7705f2a428..d57e0f1097 100644 --- a/Getting_Started/Vitis_Platform/ref_files/vck190/run.tcl +++ b/Getting_Started/Vitis_Platform/ref_files/vck190/run.tcl @@ -1,5 +1,5 @@ #/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +#Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT #*/ diff --git a/Getting_Started/Vitis_Platform/ref_files/vck190/system-user.dtsi b/Getting_Started/Vitis_Platform/ref_files/vck190/system-user.dtsi index 778a52f8fd..a964b34ebb 100644 --- a/Getting_Started/Vitis_Platform/ref_files/vck190/system-user.dtsi +++ b/Getting_Started/Vitis_Platform/ref_files/vck190/system-user.dtsi @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: MIT */ diff --git a/Getting_Started/Vitis_Platform/ref_files/vek280/Makefile b/Getting_Started/Vitis_Platform/ref_files/vek280/Makefile index 57732b8bac..3a1ac25d7c 100644 --- a/Getting_Started/Vitis_Platform/ref_files/vek280/Makefile +++ b/Getting_Started/Vitis_Platform/ref_files/vek280/Makefile @@ -1,5 +1,5 @@ #/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +#Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT #*/ @@ -9,7 +9,7 @@ ABS_BUILD_PATH=$(ROOT_DIR)/build ABS_HW_PATH=$(ABS_BUILD_PATH)/vivado BD_TCL=run.tcl ABS_BD_TCL=$(ROOT_DIR)/$(BD_TCL) -VERSION=2025.1 +VERSION=2025.2 COMMON_IMAGE_VERSAL ?=${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v$(VERSION)/ SYSROOT=$(COMMON_IMAGE_VERSAL)/sysroots/cortexa72-cortexa53-amd-linux/ XSA_NAME=vek280_custom @@ -87,4 +87,4 @@ clean: ultraclean: clean -rm -rf $(ABS_BUILD_PATH) device-tree-xlnx/ logs tmp ws -rm -rf $(VADD_WORK) - make ultraclean -C $(AIE_WORK) \ No newline at end of file + make ultraclean -C $(AIE_WORK) diff --git a/Getting_Started/Vitis_Platform/ref_files/vek280/aieml_system_design/host/host.cpp b/Getting_Started/Vitis_Platform/ref_files/vek280/aieml_system_design/host/host.cpp index ece849305a..dfb93e8005 100644 --- a/Getting_Started/Vitis_Platform/ref_files/vek280/aieml_system_design/host/host.cpp +++ b/Getting_Started/Vitis_Platform/ref_files/vek280/aieml_system_design/host/host.cpp @@ -10,6 +10,7 @@ SPDX-License-Identifier: X11 #include "experimental/xrt_kernel.h" #include "experimental/xrt_graph.h" #include "../aie_src/src/system_settings.h" +#include template int load_data_file(std::string fname,T * data,int L) @@ -30,7 +31,7 @@ int load_data_file(std::string fname,T * data,int L) } -void MatrixMultiply(int8_t* A,int8_t * B, int * C, int M, int K, int N,int Display) +void MatrixMultiply(int8_t* A,int8_t * B, int * C, int M, int K, int N) { for(int i=0;iCopyright © 2020–2025 Advanced Micro Devices, Inc.

diff --git a/Jenkinsfile b/Jenkinsfile index 71888ce5d6..a45109fcee 100644 --- a/Jenkinsfile +++ b/Jenkinsfile @@ -5,8 +5,8 @@ VitisLibPipeline (libname: 'Vitis-Tutorials', additional_json:'add_tutorials.json', NEW_GENERATE:"true", allowed_modes:"sw_emu,hw_emu,hw", - yml:'2025.1/tutorial.yml', tql:'2025.1/tutorial.tql', - TOOLVERSION: '2025.1_daily_latest', + yml:'2025.2/tutorial.yml', tql:'2025.2/tutorial.tql', + TOOLVERSION: '2025.2_daily_latest', CheckFileSystem:"false", CheckCodingStyle:"false", CheckMakefile:"false", diff --git a/README.md b/README.md index 6eca5b777b..4a15807f73 100755 --- a/README.md +++ b/README.md @@ -45,10 +45,10 @@ The default branch always reflects the latest Vitis release. If you need a diffe Alternatively, you can download the repository as a ZIP file. This includes only the selected branch and is smaller than a full clone. To download a ZIP file of a specific branch, do one of the following: - From a browser, select the desired branch. Next, click the green `Code` button and select `Download ZIP`. -- From a terminal, execute the following command. The following uses the 2025.1 branch as an example. +- From a terminal, execute the following command. The following uses the 2025.2 branch as an example. ```code -wget https://github.com/Xilinx/Vitis-Tutorials/archive/refs/heads/2025.1.zip && unzip 2025.1.zip +wget https://github.com/Xilinx/Vitis-Tutorials/archive/refs/heads/2025.2.zip && unzip 2025.2.zip ``` If you already know exactly which tutorials or folders you need, `git sparse-checkout` is an option to download only those parts. Please refer to Git documentation for usage details. @@ -97,6 +97,37 @@ If you already know exactly which tutorials or folders you need, `git sparse-che + + + + + + + + + + + + + + + + + +
+ AI Engine Development on AIE-MLv2 :new: +
+ Learn how to target, develop, and deploy advanced algorithms using Versal AIE-MLv2 architecture in conjunction with PL IP/kernels and software applications running on the embedded processors. +
+ Feature Tutorials + + Design Tutorials +
+ A to Z AIE Bare-metal Flow for VEK385 :new: + + Radio-ML on AIE-MLv2 :new: +
+ @@ -164,23 +195,23 @@ If you already know exactly which tutorials or folders you need, `git sparse-che AIE Compiler Features @@ -336,7 +367,7 @@ If you already know exactly which tutorials or folders you need, `git sparse-che + + + + + + @@ -369,7 +411,7 @@ If you already know exactly which tutorials or folders you need, `git sparse-che @@ -387,16 +429,16 @@ If you already know exactly which tutorials or folders you need, `git sparse-che @@ -458,28 +500,22 @@ If you already know exactly which tutorials or folders you need, `git sparse-che - - - - - @@ -524,18 +560,16 @@ If you already know exactly which tutorials or folders you need, `git sparse-che - + + - diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/README.md b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/README.md deleted file mode 100644 index 70edd28b12..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/README.md +++ /dev/null @@ -1,468 +0,0 @@ -
- Matrix Compute with Vitis Libraries :new: + Matrix Compute with Vitis Libraries Versal Custom Thin Platform Extensible System - Polyphase Channelizer on AIE-ML using Vitis Libraries :new: + Polyphase Channelizer on AIE-ML using Vitis Libraries
- Tiling Parameter Programming :new: + Tiling Parameter Programming - MNIST ConvNet on AIE-ML :new: + MNIST ConvNet on AIE-ML
- AIE Independent Graphs :new: + AIE Independent Graphs RTL / AI Engine interfacing Examples @@ -350,16 +381,27 @@ If you already know exactly which tutorials or folders you need, `git sparse-che
- AIE Kernel Optimization :new: + AIE Kernel Optimization AI Engine Kernel Programming :new: - Time-Division Multiplexed Mixer :new: + Time-Division Multiplexed Mixer - Back-Projection SAR on AIE :new: + Back-Projection SAR on AIE +
+ System Timeline Tutorial :new: + + +
- Vitis System Design :new: + Vitis System Design
- Vitis Functional Simulation :new: + Vitis Functional Simulation - Vitis Subsystem Simulation :new: + Vitis Subsystem Simulation Versal Custom Thin Platform Extensible System - Versal Custom Platform Integration using Vitis Subsystem :new: + Versal Custom Platform Integration using Vitis Subsystem
+ Vitis High-Level Synthesis (HLS) lets you compile C/C++ code into RTL code. These tutorials offer a broader introduction to the Vitis HLS flows and use cases.
+ Feature Tutorials + Design Tutorials
- Using Code Analyzer from Vitis Unified IDE - HLS Micro-Optimization Tutorial using Beamformer IP - Polyvec NTT Tutorial using Code Analyzer - Adaptive Beamforming for Radar
- Custom Platform Creation on KV260 - - Vitis Export to Vivado Flow :new: + Versal Custom DFX Platform Creation Tutorial + + Vitis Export to Vivado Flow
- Versal Custom DFX Platform Creation Tutorial - Versal Extensible Hardware Design Validation
- - - -
- - - AMD logo - -

AMD Vitis™ HLS Tutorials

- See Vitis™ Development Environment on amd.com -
- -# Polynomial Vectorization using Number Theoretic Transforms: A Real World Case Study Using Vitis HLS Code Analyzer - -***Version: Vitis 2025.1*** - ->**Note**: The content of this tutorial is also available as an on-demand video, featuring a demo walkthrough from the [Adapt Your C++ Algorithms for Outstanding Results with Vitis™ HLS](https://webinar.amd.com/Adapt-Your-C-Algorithms-for-Outstanding-Results-with-Vitis-tm-HLS/en) webinar. - -## Introduction - -Cryptography algorithms are fundamental computing algorithms which are crucial in securing network transmissions and stored data. The emergence of quantum computing has necessitated the development of new algorithms which cannot be broken by quantum computers, called Post-Quantum Cryptography, or PQC. One such algorithm which the [National Institute of Standards and Technology (NIST)](https://www.nist.gov/) has announced will be standardized for public-key encryption is called [CRYSTALS-Kyber](https://pq-crystals.org/kyber/). - -Traditional public key cryptography algorithms, such as RSA, rely on the asymmetric complexity of factoring large prime numbers. Take Equation 1 for example: - -Equation 1: - -```math -N = p1 \cdot p2 -``` - -It used to be that if one knew $N$ and wanted to calculate $p1$ and $p2$, the computation was too complex to solve if size of $p1$ and $p2$ were significantly large prime numbers. However, determining the prime factorization turns out to be quite a simple algorithm for quantum computers. As such, Kyber instead relies on the asymmetric complexity of factoring polynomial vectors, like those shown in Equation 2: - -Equation 2: - -```math - -\begin{bmatrix} - p_{11} \times x_{11}^{2} & p_{12} \times x_{12}^{2} & \ldots & p_{1n} \times x_{1n}^{2} \\ - p_{21} \times x_{21}^{2} & p_{22} \times x_{22}^{2} & \ldots & p_{2n} \times x_{2n}^{2} \\ - \vdots & \vdots & \ddots & \vdots \\ - p_{m1} \times x_{m1}^{2} & p_{m2} \times x_{m2}^{2} & \ldots & p_{mn} \times x_{mn}^{2} \\ -\end{bmatrix} -= -\begin{bmatrix} - 0 \\ - 0 \\ - \vdots \\ - 0 -\end{bmatrix} - -``` - -Where: - -- $p_{nm}$ are sufficiently large prime numbers. - -It is easy to see why prime factorization of polynomial vectors is orders of magnitude more computationally complex than prime factorization of a set of numbers. As such, algorithms based on this new paradigm can be made safe from attack from quantum computers; To date, there is no known way for an adversary with a quantum computer to decrypt messages encoded with Kyber. - -One downside, however, is that the increase in the complexity of decrypting these equations also precipitates an increase in the complexity on the encryption side. This makes these next generation PQC algorithms prime candidates for acceleration on an AMD FPGA or SoC. The Digital Signal Processing (DSP) slices in particular excel at vector processing, and these algorithms utilize large amounts of multiply and accumulate operations which FPGAs can process in a highly efficient and parallel nature. - -At the core of this algorithm lie Number Theoretic Transforms (NTTs). NNTs are a variant of the the Fast Fourier Transform (FFT) which transform polynomials modulo a prime number. It is therefore a crucial part of polynomial vectorization and algorithms such as Kyber which rely on this technique. - -In this tutorial, we will show how to accelerate the NTT using AMD Versal™ Adaptive SoCs and Vitis™ HLS. Because C++ code that implements these common and open source algorithms is widely available on the internet, we can use HLS C Synthesis to rapidly transform that code into RTL for the programmable logic (PL) on an AMD FPGA. - -However, tailoring this C code into highly optimized HLS C code requires expertise and time. When optimizing for any hardware architecture, code changes are required for optimal results. This is true from the largest distributed systems to the smallest embedded devices. Optimizing C code to target the PL of an AMD FPGA with Vitis HLS is no exception. The HLS programming model and design principles must be understood and applied with intent to the C code. - -The HLS Code Analyzer can help to optimize HLS C by generating a visualization of the C code and providing guidance on it. It simulates and analyzes code, then uses that information to generate a visualization of the code with measured and estimated performance metrics. Modifications to the visualization can be made to estimate the performance impact of restructuring the code without manual code modifications. - -## Setting up the Example Project - -Before beginning, [download](https://www.xilinx.com/support/download.html) the Vitis Unified Installer, [install](https://docs.xilinx.com/r/en-US/ug1400-vitis-embedded/Installation) the Vitis Software Platform, and [acquire](https://www.xilinx.com/support/licensing_solution_center.html) the Vitis HLS license. - -In this tutorial, we'll be using a snippet of code from the [Kyber GitHub project](https://github.com/pq-crystals/kyber/tree/main). The code in the Vitis Tutorials has been trimmed down to just the Polyvec and NTT functions and made synthesizable for HLS. To start, if you've already sourced the settings script to setup Vitis, the following command will bring up this workspace (Click **Update** if a **Update Workspace** window pops up after executing the command): - -``` -cd /Vitis-Tutorials/Vitis_HLS/Design_Tutorials/01_Polynomial_Vectorization -vitis -w workspace -``` - -1. Open the workspace `Workspace` in the `01_Polynomial_Vectorization` directory. - -![Workspace](images/Workspace.png) - -There are four components in the workspace that appears. Each implements the same polynomial vectorization functionality and uses the same testbench code. - -## Version0 - -The component `Version0` is a golden standard which has not been refactored. -This is our baseline version. -Let's use it to learn more about the code structure and see what Code Analyzer can show us for this design. - -Let's begin by simulating the `Version0` code. - -1. Select Run under C Simulation in the Flow pane. - - After this, a standard off the shelf C compiler will run, confirming that the C test bench compiles and runs. Monitor the output to ensure this completes without encountering any errors. Look for the line `C-simulation finished successfully`. You will also see a green check mark icon appear next to the Run command, confirming the C Simulation was successful. If a red X icon is shown, check the output for the source of the error. - - The next thing we want to do is enable the HLS Code Analyzer. The Code Analyzer is enabled from the HLS Component Settings window, so navigate to that window. Then, scroll down until you find the `code_analyzer` option. - -2. In the Vitis Components pane, expand `Version0`, then expand Settings and select `hls_config.cfg` - -3. On the right hand side of the Settings window that appears, select C Simulation. Then, check the box next to Enable Code Analyzer. - - ![Enable Code Analyzer](./images/Capture4.png) - - Now that the Code Analyzer is enabled, it will run when C simulation is run. When it completes, the Code Analyzer view will be enabled for selection under the C simulation reports. - -4. Select Run under C Simulation in the Flow pane again. - -5. When it completes, expand the Reports dropdown in the Flow pane and click Code Analyzer. - - The Code Analyzer graph will appear and show the top level hardware functions for synthesis, but here the top function `polyvec_ntt` only contains one extracted process called `polyvec_ntt_loop`. - - ![version0_polyvec_ntt](./images/Capture5.png) - - The view for this top level function is not very interesting as there is only one extracted process; the transaction interval of this process is shown on the right hand-side of the process. - - > The estimated transaction interval of the top level function is 51.5 millions clock cycles. - - You can expand the dropdown arrow on the left side of the process to reveal the contents of the process: it contains one loop labelled `polyvec_ntt_loop` (which became the process name) that calls a function named `poly_ntt`. - - ![version0_polyvec_ntt](./images/Capture5_expand.png) - - Let's keep drilling into the subfunction `poly_ntt`: - - - Use the arrows on the left of the expanded process window, or - - Use the function dropdown at the top of the Code Analyzer window, and select the function `poly_ntt`. - - Using either methods, we will again see little information, as `poly_ntt` is only calling `ntt`. - - > **Note**: The screenshot for the `poly_ntt` function is not shown. - - The function `ntt` is where the bulk of the Number Theoretic Transform code is contained. Let's see what is inside. - -6. Open the function `ntt` and wait for HLS to analyze this code. - -Upon selecting `ntt`, the HLS tool will process and display a detailed graph representing the function's internal operations and their interdependencies: - -![Code Analyzer view of ntt](./images/Capture6_v0_ntt.png) - -The graph illustrates the single processes that comprise the `ntt` function and we can see the 3 nested loops and the dependencies therein in the channel table. - -In our function `ntt`, the loop body of the nested loops implement the different sequential stages of the algorithm. -> The estimated transaction interval of the `ntt` function is 402 thousands clock cycles. Let's record this metric in a table: - -| Version | polyvec_ntt TI | ntt TI | -|:-------:|:--------------:|:-------:| -| Version0: baseline code | 51.5M | 402k | - -Furthermore, at the bottom of the screen, by selecting "Channels" you can view an additional aspect of the analysis: - -![Code Analyzer view of ntt's channels](./images/Capture6_v0_ntt_channels.png) - -The "Channels" pane lists every data transaction that was analyzed. A variable might show up in the list twice if multiple transactions occurred on that variable. The chart also provides data on each transaction, like the bitwidth, throughput, and total volume of data being passed. - -It is clear that the folded triple-nested-loop contains the bulk of the computations and that in order to extract parallelism we need to unroll the outer loop. - -As a first attempt to extract parallelism, we have created `Version1` based on the same code and testbench as `Version0`; now let's switch to this new component. - -## Version1 - -`Version1` is based on `Version0` and the only code changes made so far are that we've manually unrolled the loop named `ntt_stage_outer` in the function `ntt`, the previous code is looking like this: - -``` - ntt_stage_outer:for(len = K; len >= 2; len >>= 1) { - for(start=0;... - for(j=start;... - // loop body -``` - -and after unrolling `ntt_stage_outer` with induction variable `len`, the code is changed into: - -``` - // Stage 0 - len = K; // K is defined to be 128, so len is 128 - for(start=0;... - for(j=start;... - // loop body - - // Stage 1 - len >>= 1; // len is now 64 - for(start=0;... - for(j=start;... - // loop body - - [..repeat..] - - // Stage 6 - len >>= 1; // len is now 2 - for(start=0;... - for(j=start;... - // loop body - - // manual unrolling stops here: - // the original loop condition is len >= 2 so the next iteration will not happen. -``` - -Let's begin by simulating the code provided in `Version1`. - -1. Run C Simulation in the Flow pane with Code Analyzer. - - Similar to before, run C Simulation but let's start directly with Code Analyzer enabled, that's the way the new versions are setup (you can disable Code Analyzer in the settings in the Component Settings window). - -2. Select Run under C Simulation in the Flow pane again. - - Let's start C simulation and wait until it is run. When it completes, the Code Analyzer view will be enabled for selection under the C simulation reports. - -3. When it completes, expand the Reports dropdown in the Flow pane and click Code Analyzer. - - The Code Analyzer graph report will appear and show the top level hardware function for synthesis, `polyvec_ntt`. Similarly to the previous version, this function does not bring more insights to us. Let's note the TI value of 804k cycles in a table for later reference and discussion. Let's expand the process body and drill down the function hierarchy: we enter `poly_ntt` which calls `ntt` and we note its estimated TI value of 6281 clock. - - | Version | polyvec_ntt TI | ntt TI | - |:-------:|:--------------:|:-------:| - | Version0: baseline code | 51.5M | 402k | - | Version1: manual unroll | 804k | 6281 | - - We can be pleased with this is a huge improvement over the previous version by explicitly exposing the parallelism. - -4. Use the Function dropdown to select `ntt` and wait for HLS to analyze this code. - - Upon selecting `ntt`, the HLS tool will process and display a detailed graph representing the function's internal operations and their interdependencies. - - ![Code Analyzer view of ntt](./images/Capture8_80pc.png) - - The graph illustrates the processes that comprise the function and the dependencies therein. Each node in the graph represents a computational process. In our function `ntt`, most of the nodes in this graph represent the sequential stages of the algorithm. The edges denote data dependencies between the processes, where the data in one array is accessed by multiple processes. - - At the bottom of the screen, there's an additional panel where additional details on the processes and channels can be found: - - ![Code Analyzer ntt processes](./images/Capture9.png) - - This "Processes" pane provides a list of all processes in the function. In addition, the transaction interval (TI) is provided as an estimate of performance, and code guidance can provide a suggestion for how one might refactor the code to improve performance, if applicable. The TI of each stages are in the range 643-1154 and are listed both in the graph and in the table. - - Furthermore, by selecting "Channels," you can view an additional aspect of the analysis: - - ![Code Analyzer ntt channels](./images/Capture10.png) - - The "Channels" pane lists every data transaction that was analyzed. A variable might show up in the list twice if multiple transactions occurred on that variable. The chart also provides data on each transaction, like the bitwidth, throughput, and total volume of data being passed. - - One thing is clear from these three views provided by the code analyzer; there is a multitude of dependencies which span several processes. We can dive in on the channel view to get more information. - - We can observe that array `p` is used several times. Let's make use the search function to show only uses of `p[*]`: - -5. Select the search box and type `p[*]` to show only this array in the table. We've highlighted the first few lines of the table with their matching edges from the graph shown, they are also annotated in red on the screenshot. - - ![Code Analyzer ntt channels](./images/Capture10_filter_p.png) - -In the main graph, we can expand any of the processes labelled `ntt_stageN` to investigate the source of the problem. In each of the stages of this algorithm, the data accesses that same variable `p`. This is fine on a sequential processor like a CPU but will restrict performance on a parallel architecture. - -In the next section, we'll address this dependency on `p` and show one simple way to eliminate this contention and pave the way for acceleration. - -## Version2 - -There are two steps we need to take to improve the situation of several processes needing for access to the variable `p`. You can certainly make these changes manually, but you might find it easier to open a version of the code that has already been factored. - -1. Select `Version2` in the Component dropdown of the Flow pane. - - The first change will be to the signature of the function `ntt`. We want to separate the input and output. This will allow inputs and outputs to proceed in parallel, without contention. These code changes can be seen in the following diff output: - - ``` - polyvec.h - -void ntt(uint16_t p[N]); - +void ntt(uint16_t p_in[N], uint16_t p_out[N]); - ``` - - ``` - polyvec.cpp - -void ntt(uint16_t p[N]) { - +void ntt(uint16_t p_in[N], uint16_t p_out[N]) { - ``` - - The other change is similar in that we basically want to separate the input and output of each loop statement within the `ntt` function. To do that, we'll simply declare several arrays internally: - - ``` - uint16_t p_stage1[N]; - uint16_t p_stage2[N]; - uint16_t p_stage3[N]; - uint16_t p_stage4[N]; - uint16_t p_stage5[N]; - uint16_t p_stage6[N]; - ``` - - And then each stage must then be modified to use those new arrays. For example Stage 3 reads inputs from `p_stage2[]` and generate outputs into `p_stage3[]`: - - ``` - // Stage 3 - len >>= 1;// = 32; - ntt_stage3: for(start = 0; start < N; start = j + len) { - int16_t zeta = zetas[k++]; - ntt_stage3i: for(j = start; j < start + len; j++) { - #pragma HLS PIPELINE - int16_t t = fqmul(zeta, p_stage2[j + len]); - p_stage3[j + len] = p_stage2[j] - t; - p_stage3[j] = p_stage2[j] + t; - } - } - ``` - - Now, we should have resolved the memory access conflicts. We can check and confirm this by re-running the Code Analyzer. - -2. Run C Simulation on this component and open the HLS Code Analyzer, then open the graph for the function `ntt`: - - ![Code Analyzer ntt dependencies removed](./images/Capture11.png) - -With the dependencies removed, a clear structure emerges. What we now see is a sequence of processes with purely feed forward data transfer occurring in the region. - -The TI of each stages have decreased again and are now in the range 135-578. - -| Version | polyvec_ntt TI | ntt TI | -|:-------:|:--------------:|:-------:| -| Version0: baseline code | 51.5M | 402k | -| Version1: manual unroll | 804k | 6281 | -| Version2: remove p[] dependencies | 230k | 1540| - -In addition, we can see that each data transfer is independent of any other, and has a write to read access mode (in the table below we searched to display only names with "p_"): - -![Code Analyzer Channels ntt with dependencies removed](./images/Capture12.png) - -All of this is to say that this function is an excellent candidate for optimization using the dataflow pragma. We'll do that now, in the next section: add dataflow pragma to enable the task level parallelism. - -## Version3 - -Dataflow is an optimization in HLS that creates various processing stages from a sequence of functions, where the output of one stage is stored in a buffer to become the input of the next stage. In this way, we implement a Task Level Parallelism (TLP), where several computational tasks operate simultaneously. - -Returning to the context of NTT, what we want to do is create a dataflow region where each of the stages is a task. Thus, each of the processes shown in the graph above, which are currently each 2 nested loops, need to be encapsulated in their own function: we created a function template; the different function instances in the software will infer different modules in the hardware and we use the template parameter for the stage number. - -```cpp -//using a template parameter to instanciate multiple different functions -> different hardware modules -template -void ntt_stage(uint16_t p_in[N], uint16_t p_out[N]){ - unsigned int start=0, j=0; - unsigned int len = K >> stage; - unsigned int k = 1 << stage; - - ntt_stage_loop1: for(start = 0; start < N; start = j + len) { - int16_t zeta = zetas[k]; k++; - ntt_stage_loop2: for(j = start; j < start + len; j++) { - #pragma HLS PIPELINE - int16_t t = fqmul(zeta, p_in[j + len]); - p_out[j + len] = p_in[j] - t; - p_out[j] = p_in[j] + t; - } - } -} - -void ntt(uint16_t p_in[N], uint16_t p_out[N]) { - uint16_t p_stage1[N]; - uint16_t p_stage2[N]; - uint16_t p_stage3[N]; - uint16_t p_stage4[N]; - uint16_t p_stage5[N]; - uint16_t p_stage6[N]; -#pragma HLS DATAFLOW - ntt_stage<0>(p_in, p_stage1); - ntt_stage<1>(p_stage1, p_stage2); - ntt_stage<2>(p_stage2, p_stage3); - ntt_stage<3>(p_stage3, p_stage4); - ntt_stage<4>(p_stage4, p_stage5); - ntt_stage<5>(p_stage5, p_stage6); - ntt_stage<6>(p_stage6, p_out ); -} -``` - -Two further changes were made to the code compared to `Version2`: - -- Use dataflow in the `polyvec_ntt()` function: as we expect the `ntt()` function to have a smaller initiation interval (II) than its full latency, now that `ntt()` runs in dataflow mode, then we can restart the `ntt()` function earlier and because it is called from within a loop, then this loop inside the `polyvec_ntt()` function needs to also run in dataflow. If it is not running in dataflow mode then the loop will wait the full latency of the `ntt()` function to start the next loop iteration which is not efficient given the code changes performed. -- Separate the input and output arrays: this saves the copy time that we had in the previous version and further removes dependencies. - -```cpp -void polyvec_ntt(polyvec *vin, polyvec *vout) { - polyvec_ntt_loop:for( unsigned int i = 0; i < K; ++i) { - #pragma HLS DATAFLOW - poly_ntt(vin->vec+i, vout->vec+i); - } -} - -``` - -As before, these code modifications have already been completed, so you can switch to the next component to switch to the final `version 3` of the code and run analysis one final time. - -1. Select `Version3` in the Component dropdown of the Flow pane, run C Simulation on this component, open the HLS Code Analyzer, and select function `ntt` to show the following analysis results: - - ![Code Analyzer ntt with Dataflow](./images/Capture13_v3_ntt.png) - - In this final version of the code, the analyzer view shows just the 7 functions which implement the 7 stages and the channels that transfer data between them. This confirms the applicability of the code to the dataflow optimization. - - The TI of each stages are similar to the previous version because the code didn't change and are now in the range 136-451. - - | Version | polyvec_ntt TI | ntt TI | - |:-------:|:--------------:|:-------:| - | Version0: baseline code | 51.5M | 402k | - | Version1: manual unroll | 804k | 6281 | - | Version2: remove p[] dependencies | 230k | 1540| - | Version3: function template + dataflow + independent IO | 199k | 1552 | - - To confirm that we can check the successful application of the dataflow optimization, the Dataflow Viewer but this requires that C-Synthesis is run. - -2. In the Flow panel, under C Synthesis, press Run - -3. Once that completes, expand reports and select Dataflow Viewer. - - You need to expand the box of the process `nnt2_U0` so get to this representation: - - ![Dataflow Viewer ntt](./images/Capture14.png) - -Whereas the Code Analyzer analyzes C code to estimate synthesis results to provide early guidance, this Dataflow Viewer is now using the results of the synthesis to confirm those expectations. As shown in the view above, we can now confirm visually that the dataflow optimization is being applied to this code. It has automatically created 7 tasks and inferred Parallel In Parallel Out (PIPO) buffers to store the results in between each task. Now that we have confirmed the presence of Task Level Parallelism in the code, we will check the performance improvement afford by this optimization in the final section. - -## Performance and Utilization - -To understand the efficacy of the optimizations we've made so far we will compare the performance and utilization results for the different versions of the code. For each version of the code, we will synthesize the component for implementation on a Versal Premium Series xcvp1202 -1 speed grade AMD Adaptive SoC device. Then we will create a table and compare the results after each stage of optimization. - -### Version 3 Performance - -We've already run the C Synthesis for `Version3`, so let's first investigate and understand the results of the Synthesis Report. - -1. Under C Synthesis, expand reports and select Synthesis. - -![V3 Synthesis Results](./images/Capture15.png) - -This view shows the synthesis results. The first section shows the Timing Estimate, and the conservative clock period of 100 MHz was easily achieved. The second section shows the Performance and Resource Estimates. In this section, we can see the performance and utilization of each function, sub-function, and/or loop in the code. Two key performance metrics are latency and interval. Latency measures the time from the beginning to the end of the process. Interval is measures the minimum amount of time between successive calls to the module, making it a better measurement for throughput. In addition, we can see a number of utilization metrics are provided, such as BRAM, DSP, FF, and LUT. - -During this tutorial, we optimized the function `ntt`, and the performance and utilization for that function is provided in the 4th row. We can focus on the cycle performance: - -- The II is 770 and is matching the longest II of its subfunctions/ processes which is `ntt_stage6()`, -- Its Latency is 2114 which is the sum of all the latencies of its subfunctions/ processes. - -For polyvec_ntt_loop, the loop tripcount is 128 as expected and we call the `ntt()` function, we can see that the latency is 99905 which is coming from the computation 127*770+2114+1. Because the tripcount is 128, we need 127 restarts of the iteration at II=770 and the last iteration we need to wait the full latency of 2114 cycles to get all the outputs. - -### Comparison of all versions - -By using Code Analyzer, we were able to rapidly analyze and improve the design without running C Synthesis, so let's now compare the estimation results from Code Analyzer against the estimations from C Synthesis: - -| Version | CA: polyvec_ntt TI | CA: ntt TI | C-Synth
polyvec_ntt
latency=interval | -|:-------------------------------------------------------------|:------------------:|:----------:|:---------------:| -| Version0: baseline code | 51.5M | 402k | not computed | -| Version1: manual unroll | 804k | 6281 | 688k | -| Version2: remove p[] dependencies | 230k | 1540 | 295k | -| Version3: function template
+ dataflow + independent IO | 199k | 1552 | 100k | - -The estimations from Code Analyzer were guiding us to do the correct code changes and despite the estimations not matching exactly those from C Synthesis, they are showing the same trend and order of magnitude which is what allowed us making rapid changes. - -For the change between `Version2` and `Version3`, we can also notice the advantage of optimizing this function with the DATAFLOW pragma and task-level parallelism as it becomes obvious when viewed this way. Without dataflow, both the latency and the interval of `ntt` are equal to the sum of the functions it calls. With dataflow, the initiation interval of `ntt` becomes equal to the maximum interval of one of NTT's sub stages. So whilst the latencies are the same in both versions, the initiation interval is much better: C Synthesis shows the latency to be 2114 cycles and the II to be 770 which is about a third, because each of these stages is running concurrently on a different iteration of data. when compounded all together the `Version3` is running about 3 times faster than `Version2`; -This is the advantage of the dataflow pragma and task-level parallelism. - -The Resources Estimations table below from C-Synthesis using a Versal Premium (xcvp1202-vsva2785-1LP-i-L) further shows that the design resources didn't bloat between the initial and final version. The biggest changes are the DSP resources to perform the computations in parallel and the BRAM to implement the needed intermediate ping-pong buffers. - -| Version | latency | BRAM | DSP | FF | LUT | -|:-----------------------------------------------|:------------:|:-------:|:--------:|:-----------:|:------------:| -| Version0: baseline code | not computed | 1 (~0%)| 3 (~0%)| 20844 (1%) | 23036 (2%) | -| Version1: manual unroll | 688k | 1 (~0%)| 21 (~0%)| 115896 (6%) | 134623 (14%)| -| Version2: remove p[] dependencies | 295k | 9 (~0%)| 21 (~0%)| 9449 (~0%)| 11701 (1%) | -| Version3: function template +
dataflow + independent IO | 100k | 19 (~0%)| 21 (~0%)| 13720 (~0%)| 17940 (1%) | - -## Conclusion - -In this tutorial, we demonstrated how to optimize C code for Vitis HLS using Code Analyzer. We presented a case study based on the CRYSTALS-Kyber algorithm, polynomial vectorization, and number-theoretic transforms. - -We used the Code Analyzer to glean helpful insights about the algorithm, then applied those insights through actionable code changes. - -Finally, we measured the performance impact and observed how the dataflow optimization enabled task-level parallelism to deliver a sizeable performance gain. - -The example shown in this tutorial serves as a reference for how these concepts can be used to write high performance IP for AMD FPGAs in a fraction of the time needed compared to a pure RTL flow. - -
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diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version0/Makefile b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version0/Makefile deleted file mode 100644 index 1f74b24c0c..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version0/Makefile +++ /dev/null @@ -1,39 +0,0 @@ -####################################################################################### -.PHONY: help -help: - @echo "Makefile Usage:" - @echo " make all" - @echo " Command to run all target csim & csynth in turn." - @echo "" - @echo " make csim" - @echo " make csynth" - @echo " Command to run only one step of Vitis HLS. Note csim forces clean first." - @echo "" - @echo " make clean" - @echo " Command to remove the generated files." - @echo "" - @echo " make help" - @echo " Print this help." - @echo "" -####################################################################################### - -SHELL := bash -SOURCES := polyvec.cpp polyvec.h -SOURCES_TB := ${SOURCES} polyvec_tb.cpp - -CONFIG := hls_config.cfg -WORK_DIR := polyvec_ntt -COMMON_OPTIONS := --mode hls --config ${CONFIG} --work_dir ${WORK_DIR} - -all: csim csynth ;#cosim - -csynth: ${SOURCES} ${CONFIG} - v++ --compile ${COMMON_OPTIONS} - -csim: clean # clean before csim ! -csim cosim: ${SOURCES_TB} ${CONFIG} - vitis-run --$@ ${COMMON_OPTIONS} - -.PHONY: clean -clean: - rm -rf ${WORK_DIR} vitis_c++/ .Xil/ xcd.log diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version0/description.json b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version0/description.json deleted file mode 100644 index ec6357f13e..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version0/description.json +++ /dev/null @@ -1,30 +0,0 @@ -{ - "name": "VHLS_D_01-polyvec", - "description": "VHLS_D_01-polyvec", - "gui": "false", - "flow": "hls", - - "platform_allowlist": [ "u200"], - - "testinfo": { - "test_name": "VHLS_D_01-polyvec_ver0", - "disable": false, - "jobs": [ - { - "max_memory_MB": 76800, - "max_time_min": { - "vitis_sw_emu": 60 - } - } - ], - "targets": [ - "hls_csim", - "hls_csynth" - ], - "category": "canary", - "custom_build_target": - { - "all": "all" - } - } -} diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version0/hls_config.cfg b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version0/hls_config.cfg deleted file mode 100644 index 02a510f9dd..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version0/hls_config.cfg +++ /dev/null @@ -1,12 +0,0 @@ -part=xcvp1202-vsva2785-1LP-i-L - -[hls] -flow_target=vivado -package.output.format=ip_catalog -package.output.syn=false -tb.file=polyvec_tb.cpp -syn.file=polyvec.cpp -syn.file=polyvec.h -syn.top=polyvec_ntt -csim.code_analyzer=0 -csim.clean=true diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version0/polyvec.cpp b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version0/polyvec.cpp deleted file mode 100644 index b810a6c8c8..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version0/polyvec.cpp +++ /dev/null @@ -1,64 +0,0 @@ -#include "polyvec.h" // Include the header file that contains the function declarations - -// Define zetas array as constant -const int16_t zetas[K] = { - -1044, -758, -359, -1517, 1493, 1422, 287, 202, - -171, 622, 1577, 182, 962, -1202, -1474, 1468, - 573, -1325, 264, 383, -829, 1458, -1602, -130, - -681, 1017, 732, 608, -1542, 411, -205, -1571, - 1223, 652, -552, 1015, -1293, 1491, -282, -1544, - 516, -8, -320, -666, -1618, -1162, 126, 1469, - -853, -90, -271, 830, 107, -1421, -247, -951, - -398, 961, -1508, -725, 448, -1065, 677, -1275, - -1103, 430, 555, 843, -1251, 871, 1550, 105, - 422, 587, 177, -235, -291, -460, 1574, 1653, - -246, 778, 1159, -147, -777, 1483, -602, 1119, - -1590, 644, -872, 349, 418, 329, -156, -75, - 817, 1097, 603, 610, 1322, -1285, -1465, 384, - -1215, -136, 1218, -1335, -874, 220, -1187, -1659, - -1185, -1530, -1278, 794, -1510, -854, -870, 478, - -108, -308, 996, 991, 958, -1460, 1522, 1628 -}; - -void polyvec_ntt(polyvec *v) { - polyvec_ntt_loop:for( unsigned int i = 0; i < K; ++i) - poly_ntt(v->vec+i); -} - -void poly_ntt(poly *a) { - ntt(a->coeff); -} - - // Implementation of Montgomery reduction -int16_t montgomery_reduce(int32_t a) { -#pragma HLS INLINE - int16_t t1, t2; - t1 = (int16_t)a*QINV; - t2 = (a - (int32_t)t1*Q) >> 16; - return t2; -} - -int16_t fqmul(int16_t a, int16_t b) { -#pragma HLS INLINE - return montgomery_reduce((int32_t)a*b); -} - -void ntt(uint16_t p[N]) { - #pragma HLS INLINE OFF - unsigned int len, start, j, k; - int16_t t, zeta; - - k = 1; - ntt_stage_outer:for(len = K; len >= 2; len >>= 1) { - ntt_stage_loop:for(start = 0; start < 256; start = j + len) { - zeta = zetas[k++]; - ntt_stage_inner:for(j = start; j < start + len; j++) { - // #pragma HLS LOOP_TRIPCOUNT max=256+128 - #pragma HLS PIPELINE - t = fqmul(zeta, p[j + len]); - p[j + len] = p[j] - t; - p[j] = p[j] + t; - } - } - } -} diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version0/polyvec.h b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version0/polyvec.h deleted file mode 100644 index 3f106fa97d..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version0/polyvec.h +++ /dev/null @@ -1,30 +0,0 @@ -// polyvec.h - -#ifndef POLYVEC_H -#define POLYVEC_H - -#include -#include // for std::cout - -#include - -#define N 256 // Replace 'N' with the appropriate value -#define K 128 // Replace 'K' with the appropriate value - -#define Q 3329 // Replace 'Q' with the appropriate value -#define QINV -3327 // q^-1 mod 2^16 - -typedef struct { - uint16_t coeff[N]; -} poly; - -typedef struct { - poly vec[K]; -} polyvec; - -void polyvec_ntt(polyvec *v); -void poly_ntt(poly *a); -void ntt(uint16_t p[N]); -//uint16_t montgomery_reduce(int32_t a); - -#endif // POLYVEC_H diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version0/polyvec_tb.cpp b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version0/polyvec_tb.cpp deleted file mode 100644 index ca10223984..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version0/polyvec_tb.cpp +++ /dev/null @@ -1,62 +0,0 @@ -// test_polyvec.c - -#include "polyvec.h" // Include the header file that contains the function declarations - -// Define a helper function to print the elements of a poly data structure -void print_poly(const poly *a) { - printf("("); - for (int i = 0; i < N - 1; i++) { - printf("%d, ", a->coeff[i]); - } - printf("%d)\n", a->coeff[N - 1]); -} - -int main() { - - // Create some sample test data - poly a, b; - uint16_t a_golden[N]= {5758, 65052, 3754, 63002, 5194, 63563, 7282, 31, 2483, 2197, 2725, 64875, 2707, 3846, 4817, 2194, 1971, 4132, 4251, 3560, 2319, 613, 1075, 3935, 3635, 65350, 4709, 2718, 4484, 531, 7476, 63793, 2874, 155, 304, 63649, 64826, 63919, 64376, 61037, 1479, 64841, 65071, 64221, 1679, 65407, 3431, 1923, 1603, 558, 681, 316, 517, 931, 63939, 1999, 2024, 1094, 2276, 64366, 2187, 64180, 2637, 61036, 5702, 198, 2986, 62454, 1482, 62656, 4486, 60168, 1057, 64427, 4453, 1019, 3729, 2206, 1225, 64440, 1376, 65087, 2664, 62821, 64167, 1974, 65141, 64886, 65067, 2217, 61775, 65441, 1905, 3365, 64513, 2145, 219, 581, 65207, 63585, 61270, 2835, 63892, 1091, 63261, 64357, 543, 65399, 61396, 3246, 64484, 570, 239, 64729, 63045, 64197, 126, 64844, 126, 818, 3232, 63282, 940, 742, 2617, 62837, 3979, 64983, 61484, 482, 61086, 868, 60827, 2149, 58615, 5225, 61874, 64513, 62270, 883, 64670, 1313, 64158, 2999, 62304, 64013, 61708, 64311, 63978, 64660, 370, 64812, 871, 1467, 64633, 1985, 64570, 658, 63222, 62862, 62708, 62871, 63456, 65327, 106, 65307, 1274, 1919, 1890, 64354, 64168, 64156, 1738, 461, 2772, 63477, 65302, 64296, 63258, 61454, 63835, 63942, 62073, 60912, 62862, 62731, 65402, 59779, 2007, 63626, 157, 61212, 2344, 65032, 634, 850, 64730, 2642, 672, 1604, 216, 3280, 63524, 4234, 1165, 1532, 3059, 4106, 62449, 63959, 64259, 533, 63213, 64065, 64543, 1183, 63863, 63875, 60915, 65153, 64391, 1048, 62311, 65032, 63084, 111, 63570, 1989, 64202, 62866, 12, 506, 63758, 64229, 62090, 1591, 63844, 2330, 63832, 65002, 62981, 70, 63209, 3194, 63135, 987, 61595, 3005, 58432, 62356, 61472, 65312, 64709, 2134, 61595, 64510}; - uint16_t b_golden[N]= {65086, 62209, 64084, 64797, 61475, 768, 62519, 63814, 2906, 731, 65234, 64619, 65225, 1133, 62951, 2849, 61528, 5778, 62668, 3100, 65031, 1574, 64409, 1376, 153, 889, 62897, 4271, 64449, 1759, 409, 2349, 1437, 979, 3481, 415, 65181, 64307, 2749, 1359, 2404, 64705, 1432, 63739, 2504, 64723, 3380, 1573, 61344, 708, 64212, 63668, 64130, 3777, 866, 639, 1012, 1526, 1138, 64524, 64965, 64801, 61861, 63581, 2851, 1796, 1493, 64688, 741, 2164, 2243, 5040, 64400, 63627, 562, 64831, 3529, 928, 2277, 63966, 688, 3326, 1332, 1900, 4309, 2590, 1467, 88, 4759, 4384, 3113, 2926, 5946, 3493, 4482, 1069, 1774, 3982, 1500, 4344, 1196, 1912, 64714, 2486, 3856, 64853, 1936, 1101, 4588, 1286, 6132, 1340, 63991, 63342, 419, 62596, 63, 1074, 63, 65496, 1616, 963, 470, 64511, 2973, 65215, 325, 2507, 63510, 65240, 1104, 62290, 64846, 1755, 63740, 65263, 1498, 2318, 1696, 1006, 65103, 135, 64847, 1609, 63920, 63519, 63622, 65415, 64757, 1581, 185, 481, 60978, 62282, 63420, 65054, 61724, 60685, 61050, 61447, 64122, 61909, 64496, 64305, 53, 59954, 637, 62924, 945, 63546, 2645, 63160, 869, 65274, 63593, 1768, 65419, 62127, 64397, 59399, 814, 62046, 3262, 62500, 64199, 60100, 65469, 63208, 61546, 59404, 63950, 59656, 63379, 1639, 317, 1499, 65133, 4116, 62543, 4294, 108, 2226, 64530, 2474, 64454, 1455, 62072, 4129, 62328, 2094, 59904, 1122, 62710, 3701, 60046, 4427, 828, 64439, 64890, 64947, 63299, 64387, 62259, 1371, 2103, 64514, 64553, 63028, 2662, 61752, 6, 64998, 2440, 63357, 1606, 63371, 64690, 1124, 64684, 65128, 62594, 65395, 62708, 64723, 464, 1265, 65230, 3837, 65313, 5472, 1297, 2506, 1251, 1450, 3023, 1264}; - - for (int i = 0; i < N; i++) - a.coeff[i] = i; - - for (int i = 0; i < N; i++) - b.coeff[i] = a.coeff[( (i % 2 == 0) ? i / 2 : N - 1 - i / 2 )]; - - // Print the input - printf("Input Polynomial 'a': "); - print_poly(&a); - - printf("Input Polynomial 'b': "); - print_poly(&b); - - // Perform NTT on the poly data structures - polyvec v; - v.vec[0] = a; - v.vec[1] = b; - - // Perform the NTT on the vector of polynomials - polyvec_ntt(&v); - - // Print the results - printf("Output Polynomial 'a' after NTT: "); - print_poly(&v.vec[0]); - - printf("Output Polynomial 'b' after NTT: "); - print_poly(&v.vec[1]); - - for (int i = 0; i < N; i++) { - if(a_golden[i] != v.vec[0].coeff[i]) { - printf("mismatch on a[%d]/v.vec[0].coeff[%d], expected %d got %d\n",i,i,a_golden[i], v.vec[0].coeff[i]); - return 1; - } - if(b_golden[i] != v.vec[1].coeff[i]) { - printf("mismatch on b[%d]/v.vec[1].coeff[%d], expected %d got %d\n",i,i,b_golden[i], v.vec[1].coeff[i]); - return 2; - } - } - printf("Self-checking tests complete: OKAY"); - return 0; -} - diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version0/vitis-comp.json b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version0/vitis-comp.json deleted file mode 100644 index a6b622198c..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version0/vitis-comp.json +++ /dev/null @@ -1,10 +0,0 @@ -{ - "name": "Version0", - "type": "HLS", - "configuration": { - "componentType": "HLS", - "configFiles": [ - "hls_config.cfg" - ] - } -} diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version1/Makefile b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version1/Makefile deleted file mode 100644 index 1f74b24c0c..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version1/Makefile +++ /dev/null @@ -1,39 +0,0 @@ -####################################################################################### -.PHONY: help -help: - @echo "Makefile Usage:" - @echo " make all" - @echo " Command to run all target csim & csynth in turn." - @echo "" - @echo " make csim" - @echo " make csynth" - @echo " Command to run only one step of Vitis HLS. Note csim forces clean first." - @echo "" - @echo " make clean" - @echo " Command to remove the generated files." - @echo "" - @echo " make help" - @echo " Print this help." - @echo "" -####################################################################################### - -SHELL := bash -SOURCES := polyvec.cpp polyvec.h -SOURCES_TB := ${SOURCES} polyvec_tb.cpp - -CONFIG := hls_config.cfg -WORK_DIR := polyvec_ntt -COMMON_OPTIONS := --mode hls --config ${CONFIG} --work_dir ${WORK_DIR} - -all: csim csynth ;#cosim - -csynth: ${SOURCES} ${CONFIG} - v++ --compile ${COMMON_OPTIONS} - -csim: clean # clean before csim ! -csim cosim: ${SOURCES_TB} ${CONFIG} - vitis-run --$@ ${COMMON_OPTIONS} - -.PHONY: clean -clean: - rm -rf ${WORK_DIR} vitis_c++/ .Xil/ xcd.log diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version1/description.json b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version1/description.json deleted file mode 100644 index 0f817acf13..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version1/description.json +++ /dev/null @@ -1,30 +0,0 @@ -{ - "name": "VHLS_D_01-polyvec", - "description": "VHLS_D_01-polyvec", - "gui": "false", - "flow": "hls", - - "platform_allowlist": [ "u200"], - - "testinfo": { - "test_name": "VHLS_D_01-polyvec_ver1", - "disable": false, - "jobs": [ - { - "max_memory_MB": 76800, - "max_time_min": { - "vitis_sw_emu": 60 - } - } - ], - "targets": [ - "hls_csim", - "hls_csynth" - ], - "category": "canary", - "custom_build_target": - { - "all": "all" - } - } -} diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version1/hls_config.cfg b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version1/hls_config.cfg deleted file mode 100644 index 7a41a2899b..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version1/hls_config.cfg +++ /dev/null @@ -1,12 +0,0 @@ -part=xcvp1202-vsva2785-1LP-i-L - -[hls] -flow_target=vivado -package.output.format=ip_catalog -package.output.syn=false -tb.file=polyvec_tb.cpp -syn.file=polyvec.cpp -syn.file=polyvec.h -syn.top=polyvec_ntt -csim.code_analyzer=1 -csim.clean=true \ No newline at end of file diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version1/polyvec.cpp b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version1/polyvec.cpp deleted file mode 100644 index 05db171911..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version1/polyvec.cpp +++ /dev/null @@ -1,136 +0,0 @@ -#include "polyvec.h" // Include the header file that contains the function declarations - -// Define zetas array as constant -const int16_t zetas[K] = { - -1044, -758, -359, -1517, 1493, 1422, 287, 202, - -171, 622, 1577, 182, 962, -1202, -1474, 1468, - 573, -1325, 264, 383, -829, 1458, -1602, -130, - -681, 1017, 732, 608, -1542, 411, -205, -1571, - 1223, 652, -552, 1015, -1293, 1491, -282, -1544, - 516, -8, -320, -666, -1618, -1162, 126, 1469, - -853, -90, -271, 830, 107, -1421, -247, -951, - -398, 961, -1508, -725, 448, -1065, 677, -1275, - -1103, 430, 555, 843, -1251, 871, 1550, 105, - 422, 587, 177, -235, -291, -460, 1574, 1653, - -246, 778, 1159, -147, -777, 1483, -602, 1119, - -1590, 644, -872, 349, 418, 329, -156, -75, - 817, 1097, 603, 610, 1322, -1285, -1465, 384, - -1215, -136, 1218, -1335, -874, 220, -1187, -1659, - -1185, -1530, -1278, 794, -1510, -854, -870, 478, - -108, -308, 996, 991, 958, -1460, 1522, 1628 -}; - -void polyvec_ntt(polyvec *v) { - unsigned int i = 0; - polyvec_ntt_loop:for( unsigned int i = 0; i < K; ++i) - poly_ntt(v->vec+i); -} - -void poly_ntt(poly *a) { - ntt(a->coeff); -} - - // Implementation of Montgomery reduction -int16_t montgomery_reduce(int32_t a) { -#pragma HLS INLINE - int16_t t1, t2; - t1 = (int16_t)a*QINV; - t2 = (a - (int32_t)t1*Q) >> 16; - return t2; -} - -int16_t fqmul(int16_t a, int16_t b) { -#pragma HLS INLINE - return montgomery_reduce((int32_t)a*b); -} - -void ntt(uint16_t p[N]) { - unsigned int start=0, j=0, len=0, k=0; - - k = 1; - len = K; - - //Stage 1 - ntt_stage1: for(start = 0; start < N; start = j + len) { - int16_t zeta = zetas[k++]; - ntt_stage1i: for(j = start; j < start + len; j++) { - #pragma HLS PIPELINE - int16_t t = fqmul(zeta, p[j + len]); - p[j + len] = p[j] - t; - p[j] = p[j] + t; - } - } - - // Stage 2 - len >>= 1;// = 64; - ntt_stage2: for(start = 0; start < N; start = j + len) { - int16_t zeta = zetas[k++]; - ntt_stage2i: for(j = start; j < start + len; j++) { - #pragma HLS PIPELINE - int16_t t = fqmul(zeta, p[j + len]); - p[j + len] = p[j] - t; - p[j] = p[j] + t; - } - } - - // Stage 3 - len >>= 1;// = 32; - ntt_stage3: for(start = 0; start < N; start = j + len) { - int16_t zeta = zetas[k++]; - ntt_stage3i: for(j = start; j < start + len; j++) { - #pragma HLS PIPELINE - int16_t t = fqmul(zeta, p[j + len]); - p[j + len] = p[j] - t; - p[j] = p[j] + t; - } - } - - // Stage 4 - len >>= 1;// = 16; - ntt_stage4: for(start = 0; start < N; start = j + len) { - int16_t zeta = zetas[k++]; - ntt_stage4i: for(j = start; j < start + len; j++) { - #pragma HLS PIPELINE - int16_t t = fqmul(zeta, p[j + len]); - p[j + len] = p[j] - t; - p[j] = p[j] + t; - } - } - - // Stage 5 - len >>= 1;// = 8; - ntt_stage5: for(start = 0; start < N; start = j + len) { - int16_t zeta = zetas[k++]; - ntt_stage5i: for(j = start; j < start + len; j++) { - #pragma HLS PIPELINE - int16_t t = fqmul(zeta, p[j + len]); - p[j + len] = p[j] - t; - p[j] = p[j] + t; - } - } - - // Stage 6 - len >>= 1;// = 4; - ntt_stage6: for(start = 0; start < N; start = j + len) { - int16_t zeta = zetas[k++]; - ntt_stage6i: for(j = start; j < start + len; j++) { - #pragma HLS PIPELINE - int16_t t = fqmul(zeta, p[j + len]); - p[j + len] = p[j] - t; - p[j] = p[j] + t; - } - } - - // Stage 7 - len >>= 1;// = 2; - ntt_stage7: for(start = 0; start < N; start = j + len) { - int16_t zeta = zetas[k++]; - ntt_stage7i: for(j = start; j < start + len; j++) { - #pragma HLS PIPELINE - int16_t t = fqmul(zeta, p[j + len]); - p[j + len] = p[j] - t; - p[j] = p[j] + t; - } - } -} - diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version1/polyvec.h b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version1/polyvec.h deleted file mode 100644 index 3f106fa97d..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version1/polyvec.h +++ /dev/null @@ -1,30 +0,0 @@ -// polyvec.h - -#ifndef POLYVEC_H -#define POLYVEC_H - -#include -#include // for std::cout - -#include - -#define N 256 // Replace 'N' with the appropriate value -#define K 128 // Replace 'K' with the appropriate value - -#define Q 3329 // Replace 'Q' with the appropriate value -#define QINV -3327 // q^-1 mod 2^16 - -typedef struct { - uint16_t coeff[N]; -} poly; - -typedef struct { - poly vec[K]; -} polyvec; - -void polyvec_ntt(polyvec *v); -void poly_ntt(poly *a); -void ntt(uint16_t p[N]); -//uint16_t montgomery_reduce(int32_t a); - -#endif // POLYVEC_H diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version1/polyvec_tb.cpp b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version1/polyvec_tb.cpp deleted file mode 100644 index ca10223984..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version1/polyvec_tb.cpp +++ /dev/null @@ -1,62 +0,0 @@ -// test_polyvec.c - -#include "polyvec.h" // Include the header file that contains the function declarations - -// Define a helper function to print the elements of a poly data structure -void print_poly(const poly *a) { - printf("("); - for (int i = 0; i < N - 1; i++) { - printf("%d, ", a->coeff[i]); - } - printf("%d)\n", a->coeff[N - 1]); -} - -int main() { - - // Create some sample test data - poly a, b; - uint16_t a_golden[N]= {5758, 65052, 3754, 63002, 5194, 63563, 7282, 31, 2483, 2197, 2725, 64875, 2707, 3846, 4817, 2194, 1971, 4132, 4251, 3560, 2319, 613, 1075, 3935, 3635, 65350, 4709, 2718, 4484, 531, 7476, 63793, 2874, 155, 304, 63649, 64826, 63919, 64376, 61037, 1479, 64841, 65071, 64221, 1679, 65407, 3431, 1923, 1603, 558, 681, 316, 517, 931, 63939, 1999, 2024, 1094, 2276, 64366, 2187, 64180, 2637, 61036, 5702, 198, 2986, 62454, 1482, 62656, 4486, 60168, 1057, 64427, 4453, 1019, 3729, 2206, 1225, 64440, 1376, 65087, 2664, 62821, 64167, 1974, 65141, 64886, 65067, 2217, 61775, 65441, 1905, 3365, 64513, 2145, 219, 581, 65207, 63585, 61270, 2835, 63892, 1091, 63261, 64357, 543, 65399, 61396, 3246, 64484, 570, 239, 64729, 63045, 64197, 126, 64844, 126, 818, 3232, 63282, 940, 742, 2617, 62837, 3979, 64983, 61484, 482, 61086, 868, 60827, 2149, 58615, 5225, 61874, 64513, 62270, 883, 64670, 1313, 64158, 2999, 62304, 64013, 61708, 64311, 63978, 64660, 370, 64812, 871, 1467, 64633, 1985, 64570, 658, 63222, 62862, 62708, 62871, 63456, 65327, 106, 65307, 1274, 1919, 1890, 64354, 64168, 64156, 1738, 461, 2772, 63477, 65302, 64296, 63258, 61454, 63835, 63942, 62073, 60912, 62862, 62731, 65402, 59779, 2007, 63626, 157, 61212, 2344, 65032, 634, 850, 64730, 2642, 672, 1604, 216, 3280, 63524, 4234, 1165, 1532, 3059, 4106, 62449, 63959, 64259, 533, 63213, 64065, 64543, 1183, 63863, 63875, 60915, 65153, 64391, 1048, 62311, 65032, 63084, 111, 63570, 1989, 64202, 62866, 12, 506, 63758, 64229, 62090, 1591, 63844, 2330, 63832, 65002, 62981, 70, 63209, 3194, 63135, 987, 61595, 3005, 58432, 62356, 61472, 65312, 64709, 2134, 61595, 64510}; - uint16_t b_golden[N]= {65086, 62209, 64084, 64797, 61475, 768, 62519, 63814, 2906, 731, 65234, 64619, 65225, 1133, 62951, 2849, 61528, 5778, 62668, 3100, 65031, 1574, 64409, 1376, 153, 889, 62897, 4271, 64449, 1759, 409, 2349, 1437, 979, 3481, 415, 65181, 64307, 2749, 1359, 2404, 64705, 1432, 63739, 2504, 64723, 3380, 1573, 61344, 708, 64212, 63668, 64130, 3777, 866, 639, 1012, 1526, 1138, 64524, 64965, 64801, 61861, 63581, 2851, 1796, 1493, 64688, 741, 2164, 2243, 5040, 64400, 63627, 562, 64831, 3529, 928, 2277, 63966, 688, 3326, 1332, 1900, 4309, 2590, 1467, 88, 4759, 4384, 3113, 2926, 5946, 3493, 4482, 1069, 1774, 3982, 1500, 4344, 1196, 1912, 64714, 2486, 3856, 64853, 1936, 1101, 4588, 1286, 6132, 1340, 63991, 63342, 419, 62596, 63, 1074, 63, 65496, 1616, 963, 470, 64511, 2973, 65215, 325, 2507, 63510, 65240, 1104, 62290, 64846, 1755, 63740, 65263, 1498, 2318, 1696, 1006, 65103, 135, 64847, 1609, 63920, 63519, 63622, 65415, 64757, 1581, 185, 481, 60978, 62282, 63420, 65054, 61724, 60685, 61050, 61447, 64122, 61909, 64496, 64305, 53, 59954, 637, 62924, 945, 63546, 2645, 63160, 869, 65274, 63593, 1768, 65419, 62127, 64397, 59399, 814, 62046, 3262, 62500, 64199, 60100, 65469, 63208, 61546, 59404, 63950, 59656, 63379, 1639, 317, 1499, 65133, 4116, 62543, 4294, 108, 2226, 64530, 2474, 64454, 1455, 62072, 4129, 62328, 2094, 59904, 1122, 62710, 3701, 60046, 4427, 828, 64439, 64890, 64947, 63299, 64387, 62259, 1371, 2103, 64514, 64553, 63028, 2662, 61752, 6, 64998, 2440, 63357, 1606, 63371, 64690, 1124, 64684, 65128, 62594, 65395, 62708, 64723, 464, 1265, 65230, 3837, 65313, 5472, 1297, 2506, 1251, 1450, 3023, 1264}; - - for (int i = 0; i < N; i++) - a.coeff[i] = i; - - for (int i = 0; i < N; i++) - b.coeff[i] = a.coeff[( (i % 2 == 0) ? i / 2 : N - 1 - i / 2 )]; - - // Print the input - printf("Input Polynomial 'a': "); - print_poly(&a); - - printf("Input Polynomial 'b': "); - print_poly(&b); - - // Perform NTT on the poly data structures - polyvec v; - v.vec[0] = a; - v.vec[1] = b; - - // Perform the NTT on the vector of polynomials - polyvec_ntt(&v); - - // Print the results - printf("Output Polynomial 'a' after NTT: "); - print_poly(&v.vec[0]); - - printf("Output Polynomial 'b' after NTT: "); - print_poly(&v.vec[1]); - - for (int i = 0; i < N; i++) { - if(a_golden[i] != v.vec[0].coeff[i]) { - printf("mismatch on a[%d]/v.vec[0].coeff[%d], expected %d got %d\n",i,i,a_golden[i], v.vec[0].coeff[i]); - return 1; - } - if(b_golden[i] != v.vec[1].coeff[i]) { - printf("mismatch on b[%d]/v.vec[1].coeff[%d], expected %d got %d\n",i,i,b_golden[i], v.vec[1].coeff[i]); - return 2; - } - } - printf("Self-checking tests complete: OKAY"); - return 0; -} - diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version1/vitis-comp.json b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version1/vitis-comp.json deleted file mode 100644 index 8d22ca65ea..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version1/vitis-comp.json +++ /dev/null @@ -1,10 +0,0 @@ -{ - "name": "Version1", - "type": "HLS", - "configuration": { - "componentType": "HLS", - "configFiles": [ - "hls_config.cfg" - ] - } -} diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version2/Makefile b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version2/Makefile deleted file mode 100644 index 1f74b24c0c..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version2/Makefile +++ /dev/null @@ -1,39 +0,0 @@ -####################################################################################### -.PHONY: help -help: - @echo "Makefile Usage:" - @echo " make all" - @echo " Command to run all target csim & csynth in turn." - @echo "" - @echo " make csim" - @echo " make csynth" - @echo " Command to run only one step of Vitis HLS. Note csim forces clean first." - @echo "" - @echo " make clean" - @echo " Command to remove the generated files." - @echo "" - @echo " make help" - @echo " Print this help." - @echo "" -####################################################################################### - -SHELL := bash -SOURCES := polyvec.cpp polyvec.h -SOURCES_TB := ${SOURCES} polyvec_tb.cpp - -CONFIG := hls_config.cfg -WORK_DIR := polyvec_ntt -COMMON_OPTIONS := --mode hls --config ${CONFIG} --work_dir ${WORK_DIR} - -all: csim csynth ;#cosim - -csynth: ${SOURCES} ${CONFIG} - v++ --compile ${COMMON_OPTIONS} - -csim: clean # clean before csim ! -csim cosim: ${SOURCES_TB} ${CONFIG} - vitis-run --$@ ${COMMON_OPTIONS} - -.PHONY: clean -clean: - rm -rf ${WORK_DIR} vitis_c++/ .Xil/ xcd.log diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version2/description.json b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version2/description.json deleted file mode 100644 index 432707dbb0..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version2/description.json +++ /dev/null @@ -1,30 +0,0 @@ -{ - "name": "VHLS_D_01-polyvec", - "description": "VHLS_D_01-polyvec", - "gui": "false", - "flow": "hls", - - "platform_allowlist": [ "u200"], - - "testinfo": { - "test_name": "VHLS_D_01-polyvec_ver2", - "disable": false, - "jobs": [ - { - "max_memory_MB": 76800, - "max_time_min": { - "vitis_sw_emu": 60 - } - } - ], - "targets": [ - "hls_csim", - "hls_csynth" - ], - "category": "canary", - "custom_build_target": - { - "all": "all" - } - } -} diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version2/hls_config.cfg b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version2/hls_config.cfg deleted file mode 100644 index acf5343004..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version2/hls_config.cfg +++ /dev/null @@ -1,12 +0,0 @@ -part=xcvp1202-vsva2785-1LP-i-L - -[hls] -flow_target=vivado -package.output.format=ip_catalog -package.output.syn=false -tb.file=polyvec_tb.cpp -syn.file=polyvec.cpp -syn.file=polyvec.h -syn.top=polyvec_ntt -csim.code_analyzer=1 -csim.clean=true diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version2/polyvec.cpp b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version2/polyvec.cpp deleted file mode 100644 index 349dd3fe85..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version2/polyvec.cpp +++ /dev/null @@ -1,154 +0,0 @@ -#include "polyvec.h" // Include the header file that contains the function declarations - -// Define zetas array as constant -const int16_t zetas[K] = { - -1044, -758, -359, -1517, 1493, 1422, 287, 202, - -171, 622, 1577, 182, 962, -1202, -1474, 1468, - 573, -1325, 264, 383, -829, 1458, -1602, -130, - -681, 1017, 732, 608, -1542, 411, -205, -1571, - 1223, 652, -552, 1015, -1293, 1491, -282, -1544, - 516, -8, -320, -666, -1618, -1162, 126, 1469, - -853, -90, -271, 830, 107, -1421, -247, -951, - -398, 961, -1508, -725, 448, -1065, 677, -1275, - -1103, 430, 555, 843, -1251, 871, 1550, 105, - 422, 587, 177, -235, -291, -460, 1574, 1653, - -246, 778, 1159, -147, -777, 1483, -602, 1119, - -1590, 644, -872, 349, 418, 329, -156, -75, - 817, 1097, 603, 610, 1322, -1285, -1465, 384, - -1215, -136, 1218, -1335, -874, 220, -1187, -1659, - -1185, -1530, -1278, 794, -1510, -854, -870, 478, - -108, -308, 996, 991, 958, -1460, 1522, 1628 -}; - -void polyvec_ntt(polyvec *v) { - polyvec_ntt_loop:for( unsigned int i = 0; i < K; ++i) - poly_ntt(v->vec+i); -} - -void poly_ntt(poly *a) { - // Create array to hold the output results - uint16_t temp[N]; - - // Call ntt() with the temporary arrays - ntt(a->coeff, temp); - - // Copy the result back to the output polynomial - for (unsigned int i = 0; i < N; i++) { -#pragma HLS pipeline - a->coeff[i] = temp[i]; - } -} - - // Implementation of Montgomery reduction -int16_t montgomery_reduce(int32_t a) { -#pragma HLS INLINE - int16_t t1, t2; - t1 = (int16_t)a*QINV; - t2 = (a - (int32_t)t1*Q) >> 16; - return t2; -} - -int16_t fqmul(int16_t a, int16_t b) { -#pragma HLS INLINE - return montgomery_reduce((int32_t)a*b); -} - -void ntt(uint16_t p_in[N], uint16_t p_out[N]) { - unsigned int start=0, j=0, len=0, k=0; - - uint16_t p_stage1[N]; - uint16_t p_stage2[N]; - uint16_t p_stage3[N]; - uint16_t p_stage4[N]; - uint16_t p_stage5[N]; - uint16_t p_stage6[N]; - - // it's the first version where #pragma HLS DATAFLOW could be used. - - k = 1; - len = K; - - //Stage 1 - ntt_stage1: for(start = 0; start < N; start = j + len) { - int16_t zeta = zetas[k++]; - ntt_stage1i: for(j = start; j < start + len; j++) { - #pragma HLS PIPELINE - int16_t t = fqmul(zeta, p_in[j + len]); - p_stage1[j + len] = p_in[j] - t; - p_stage1[j] = p_in[j] + t; - } - } - - // Stage 2 - len >>= 1;// = 64; - ntt_stage2: for(start = 0; start < N; start = j + len) { - int16_t zeta = zetas[k++]; - ntt_stage2i: for(j = start; j < start + len; j++) { - #pragma HLS PIPELINE - int16_t t = fqmul(zeta, p_stage1[j + len]); - p_stage2[j + len] = p_stage1[j] - t; - p_stage2[j] = p_stage1[j] + t; - } - } - - // Stage 3 - len >>= 1;// = 32; - ntt_stage3: for(start = 0; start < N; start = j + len) { - int16_t zeta = zetas[k++]; - ntt_stage3i: for(j = start; j < start + len; j++) { - #pragma HLS PIPELINE - int16_t t = fqmul(zeta, p_stage2[j + len]); - p_stage3[j + len] = p_stage2[j] - t; - p_stage3[j] = p_stage2[j] + t; - } - } - - // Stage 4 - len >>= 1;// = 16; - ntt_stage4: for(start = 0; start < N; start = j + len) { - int16_t zeta = zetas[k++]; - ntt_stage4i: for(j = start; j < start + len; j++) { - #pragma HLS PIPELINE - int16_t t = fqmul(zeta, p_stage3[j + len]); - p_stage4[j + len] = p_stage3[j] - t; - p_stage4[j] = p_stage3[j] + t; - } - } - - // Stage 5 - len >>= 1;// = 8; - ntt_stage5: for(start = 0; start < N; start = j + len) { - int16_t zeta = zetas[k++]; - ntt_stage5i: for(j = start; j < start + len; j++) { - #pragma HLS PIPELINE - int16_t t = fqmul(zeta, p_stage4[j + len]); - p_stage5[j + len] = p_stage4[j] - t; - p_stage5[j] = p_stage4[j] + t; - } - } - - // Stage 6 - len >>= 1;// = 4; - ntt_stage6: for(start = 0; start < N; start = j + len) { - int16_t zeta = zetas[k++]; - ntt_stage6i: for(j = start; j < start + len; j++) { - #pragma HLS PIPELINE - int16_t t = fqmul(zeta, p_stage5[j + len]); - p_stage6[j + len] = p_stage5[j] - t; - p_stage6[j] = p_stage5[j] + t; - } - } - - // Stage 7 - len >>= 1;// = 2; - ntt_stage7: for(start = 0; start < N; start = j + len) { - int16_t zeta = zetas[k++]; - ntt_stage7i: for(j = start; j < start + len; j++) { - #pragma HLS PIPELINE - int16_t t = fqmul(zeta, p_stage6[j + len]); - p_out[j + len] = p_stage6[j] - t; - p_out[j] = p_stage6[j] + t; - } - } -} - diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version2/polyvec.h b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version2/polyvec.h deleted file mode 100644 index cfe405570c..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version2/polyvec.h +++ /dev/null @@ -1,30 +0,0 @@ -// polyvec.h - -#ifndef POLYVEC_H -#define POLYVEC_H - -#include -#include // for std::cout - -#include - -#define N 256 // Replace 'N' with the appropriate value -#define K 128 // Replace 'K' with the appropriate value - -#define Q 3329 // Replace 'Q' with the appropriate value -#define QINV -3327 // q^-1 mod 2^16 - -typedef struct { - uint16_t coeff[N]; -} poly; - -typedef struct { - poly vec[K]; -} polyvec; - -void polyvec_ntt(polyvec *v); -void poly_ntt(poly *a); -void ntt(uint16_t p_in[N], uint16_t p_out[N]); -//uint16_t montgomery_reduce(int32_t a); - -#endif // POLYVEC_H diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version2/polyvec_tb.cpp b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version2/polyvec_tb.cpp deleted file mode 100644 index 165b6396b2..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version2/polyvec_tb.cpp +++ /dev/null @@ -1,62 +0,0 @@ -// test_polyvec.c - -#include "polyvec.h" // Include the header file that contains the function declarations - -// Define a helper function to print the elements of a poly data structure -void print_poly(const poly *a) { - printf("("); - for (int i = 0; i < N - 1; i++) { - printf("%d, ", a->coeff[i]); - } - printf("%d)\n", a->coeff[N - 1]); -} - -int main() { - - // Create some sample test data - poly a, b; - uint16_t a_golden[N]= {5758, 65052, 3754, 63002, 5194, 63563, 7282, 31, 2483, 2197, 2725, 64875, 2707, 3846, 4817, 2194, 1971, 4132, 4251, 3560, 2319, 613, 1075, 3935, 3635, 65350, 4709, 2718, 4484, 531, 7476, 63793, 2874, 155, 304, 63649, 64826, 63919, 64376, 61037, 1479, 64841, 65071, 64221, 1679, 65407, 3431, 1923, 1603, 558, 681, 316, 517, 931, 63939, 1999, 2024, 1094, 2276, 64366, 2187, 64180, 2637, 61036, 5702, 198, 2986, 62454, 1482, 62656, 4486, 60168, 1057, 64427, 4453, 1019, 3729, 2206, 1225, 64440, 1376, 65087, 2664, 62821, 64167, 1974, 65141, 64886, 65067, 2217, 61775, 65441, 1905, 3365, 64513, 2145, 219, 581, 65207, 63585, 61270, 2835, 63892, 1091, 63261, 64357, 543, 65399, 61396, 3246, 64484, 570, 239, 64729, 63045, 64197, 126, 64844, 126, 818, 3232, 63282, 940, 742, 2617, 62837, 3979, 64983, 61484, 482, 61086, 868, 60827, 2149, 58615, 5225, 61874, 64513, 62270, 883, 64670, 1313, 64158, 2999, 62304, 64013, 61708, 64311, 63978, 64660, 370, 64812, 871, 1467, 64633, 1985, 64570, 658, 63222, 62862, 62708, 62871, 63456, 65327, 106, 65307, 1274, 1919, 1890, 64354, 64168, 64156, 1738, 461, 2772, 63477, 65302, 64296, 63258, 61454, 63835, 63942, 62073, 60912, 62862, 62731, 65402, 59779, 2007, 63626, 157, 61212, 2344, 65032, 634, 850, 64730, 2642, 672, 1604, 216, 3280, 63524, 4234, 1165, 1532, 3059, 4106, 62449, 63959, 64259, 533, 63213, 64065, 64543, 1183, 63863, 63875, 60915, 65153, 64391, 1048, 62311, 65032, 63084, 111, 63570, 1989, 64202, 62866, 12, 506, 63758, 64229, 62090, 1591, 63844, 2330, 63832, 65002, 62981, 70, 63209, 3194, 63135, 987, 61595, 3005, 58432, 62356, 61472, 65312, 64709, 2134, 61595, 64510}; - uint16_t b_golden[N]= {65086, 62209, 64084, 64797, 61475, 768, 62519, 63814, 2906, 731, 65234, 64619, 65225, 1133, 62951, 2849, 61528, 5778, 62668, 3100, 65031, 1574, 64409, 1376, 153, 889, 62897, 4271, 64449, 1759, 409, 2349, 1437, 979, 3481, 415, 65181, 64307, 2749, 1359, 2404, 64705, 1432, 63739, 2504, 64723, 3380, 1573, 61344, 708, 64212, 63668, 64130, 3777, 866, 639, 1012, 1526, 1138, 64524, 64965, 64801, 61861, 63581, 2851, 1796, 1493, 64688, 741, 2164, 2243, 5040, 64400, 63627, 562, 64831, 3529, 928, 2277, 63966, 688, 3326, 1332, 1900, 4309, 2590, 1467, 88, 4759, 4384, 3113, 2926, 5946, 3493, 4482, 1069, 1774, 3982, 1500, 4344, 1196, 1912, 64714, 2486, 3856, 64853, 1936, 1101, 4588, 1286, 6132, 1340, 63991, 63342, 419, 62596, 63, 1074, 63, 65496, 1616, 963, 470, 64511, 2973, 65215, 325, 2507, 63510, 65240, 1104, 62290, 64846, 1755, 63740, 65263, 1498, 2318, 1696, 1006, 65103, 135, 64847, 1609, 63920, 63519, 63622, 65415, 64757, 1581, 185, 481, 60978, 62282, 63420, 65054, 61724, 60685, 61050, 61447, 64122, 61909, 64496, 64305, 53, 59954, 637, 62924, 945, 63546, 2645, 63160, 869, 65274, 63593, 1768, 65419, 62127, 64397, 59399, 814, 62046, 3262, 62500, 64199, 60100, 65469, 63208, 61546, 59404, 63950, 59656, 63379, 1639, 317, 1499, 65133, 4116, 62543, 4294, 108, 2226, 64530, 2474, 64454, 1455, 62072, 4129, 62328, 2094, 59904, 1122, 62710, 3701, 60046, 4427, 828, 64439, 64890, 64947, 63299, 64387, 62259, 1371, 2103, 64514, 64553, 63028, 2662, 61752, 6, 64998, 2440, 63357, 1606, 63371, 64690, 1124, 64684, 65128, 62594, 65395, 62708, 64723, 464, 1265, 65230, 3837, 65313, 5472, 1297, 2506, 1251, 1450, 3023, 1264}; - - for (int i = 0; i < N; i++) - a.coeff[i] = i; - - for (int i = 0; i < N; i++) - b.coeff[i] = a.coeff[( (i % 2 == 0) ? i / 2 : N - 1 - i / 2 )]; - - // Print the input - printf("(Info) Input Polynomial 'a': "); - print_poly(&a); - - printf("(Info) Input Polynomial 'b': "); - print_poly(&b); - - // Perform NTT on the poly data structures - polyvec v; - v.vec[0] = a; - v.vec[1] = b; - - // Perform the NTT on the vector of polynomials - polyvec_ntt(&v); - - // Print the results - printf("(Info) Output Polynomial 'a' after NTT: "); - print_poly(&v.vec[0]); - - printf("(Info) Output Polynomial 'b' after NTT: "); - print_poly(&v.vec[1]); - - for (int i = 0; i < N; i++) { - if(a_golden[i] != v.vec[0].coeff[i]) { - printf("(Error) Mismatch on a[%d]/v.vec[0].coeff[%d], expected %d got %d\n",i,i,a_golden[i], v.vec[0].coeff[i]); - return 1; - } - if(b_golden[i] != v.vec[1].coeff[i]) { - printf("(Error) Mismatch on b[%d]/v.vec[1].coeff[%d], expected %d got %d\n",i,i,b_golden[i], v.vec[1].coeff[i]); - return 2; - } - } - printf("(Info) Self-checking tests complete: OKAY"); - return 0; -} - diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version2/vitis-comp.json b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version2/vitis-comp.json deleted file mode 100644 index d653333fbf..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version2/vitis-comp.json +++ /dev/null @@ -1,10 +0,0 @@ -{ - "name": "Version2", - "type": "HLS", - "configuration": { - "componentType": "HLS", - "configFiles": [ - "hls_config.cfg" - ] - } -} diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version3/Makefile b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version3/Makefile deleted file mode 100644 index 1f74b24c0c..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version3/Makefile +++ /dev/null @@ -1,39 +0,0 @@ -####################################################################################### -.PHONY: help -help: - @echo "Makefile Usage:" - @echo " make all" - @echo " Command to run all target csim & csynth in turn." - @echo "" - @echo " make csim" - @echo " make csynth" - @echo " Command to run only one step of Vitis HLS. Note csim forces clean first." - @echo "" - @echo " make clean" - @echo " Command to remove the generated files." - @echo "" - @echo " make help" - @echo " Print this help." - @echo "" -####################################################################################### - -SHELL := bash -SOURCES := polyvec.cpp polyvec.h -SOURCES_TB := ${SOURCES} polyvec_tb.cpp - -CONFIG := hls_config.cfg -WORK_DIR := polyvec_ntt -COMMON_OPTIONS := --mode hls --config ${CONFIG} --work_dir ${WORK_DIR} - -all: csim csynth ;#cosim - -csynth: ${SOURCES} ${CONFIG} - v++ --compile ${COMMON_OPTIONS} - -csim: clean # clean before csim ! -csim cosim: ${SOURCES_TB} ${CONFIG} - vitis-run --$@ ${COMMON_OPTIONS} - -.PHONY: clean -clean: - rm -rf ${WORK_DIR} vitis_c++/ .Xil/ xcd.log diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version3/description.json b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version3/description.json deleted file mode 100644 index c3a1a036ed..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version3/description.json +++ /dev/null @@ -1,30 +0,0 @@ -{ - "name": "VHLS_D_01-polyvec", - "description": "VHLS_D_01-polyvec", - "gui": "false", - "flow": "hls", - - "platform_allowlist": [ "u200"], - - "testinfo": { - "test_name": "VHLS_D_01-polyvec_ver3", - "disable": false, - "jobs": [ - { - "max_memory_MB": 76800, - "max_time_min": { - "vitis_sw_emu": 60 - } - } - ], - "targets": [ - "hls_csim", - "hls_csynth" - ], - "category": "canary", - "custom_build_target": - { - "all": "all" - } - } -} diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version3/hls_config.cfg b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version3/hls_config.cfg deleted file mode 100644 index a62ccca5ec..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version3/hls_config.cfg +++ /dev/null @@ -1,16 +0,0 @@ -part=xcvp1202-vsva2785-1LP-i-L - -[hls] -flow_target=vivado -package.output.format=ip_catalog -package.output.syn=false -tb.file=polyvec_tb.cpp -syn.file=polyvec.cpp -syn.file=polyvec.h -syn.top=polyvec_ntt -csim.code_analyzer=1 -csim.clean=true -csim.sanitize_address=0 -csim.sanitize_undefined=0 -syn.csimflags=-Wall -tb.cflags=-Wall \ No newline at end of file diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version3/polyvec.cpp b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version3/polyvec.cpp deleted file mode 100644 index 382ff4e7a7..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version3/polyvec.cpp +++ /dev/null @@ -1,84 +0,0 @@ -#include "polyvec.h" // Include the header file that contains the function declarations -#include - -// Define zetas array as constant -const int16_t zetas[K] = { - -1044, -758, -359, -1517, 1493, 1422, 287, 202, - -171, 622, 1577, 182, 962, -1202, -1474, 1468, - 573, -1325, 264, 383, -829, 1458, -1602, -130, - -681, 1017, 732, 608, -1542, 411, -205, -1571, - 1223, 652, -552, 1015, -1293, 1491, -282, -1544, - 516, -8, -320, -666, -1618, -1162, 126, 1469, - -853, -90, -271, 830, 107, -1421, -247, -951, - -398, 961, -1508, -725, 448, -1065, 677, -1275, - -1103, 430, 555, 843, -1251, 871, 1550, 105, - 422, 587, 177, -235, -291, -460, 1574, 1653, - -246, 778, 1159, -147, -777, 1483, -602, 1119, - -1590, 644, -872, 349, 418, 329, -156, -75, - 817, 1097, 603, 610, 1322, -1285, -1465, 384, - -1215, -136, 1218, -1335, -874, 220, -1187, -1659, - -1185, -1530, -1278, 794, -1510, -854, -870, 478, - -108, -308, 996, 991, 958, -1460, 1522, 1628 -}; - -void polyvec_ntt(polyvec *vin, polyvec *vout) { - polyvec_ntt_loop:for( unsigned int i = 0; i < K; ++i) { - #pragma HLS DATAFLOW - poly_ntt(vin->vec+i, vout->vec+i); - } -} - -void poly_ntt(poly *ain, poly *aout) { - #pragma HLS INLINE - ntt(ain->coeff, aout->coeff); -} - - // Implementation of Montgomery reduction -int16_t montgomery_reduce(int32_t a) { -#pragma HLS INLINE - int16_t t1, t2; - t1 = (int16_t)a*QINV; - t2 = (a - (int32_t)t1*Q) >> 16; - return t2; -} - -int16_t fqmul(int16_t a, int16_t b) { -#pragma HLS INLINE - return montgomery_reduce((int32_t)a*b); -} - -//using a template parameter to instanciate multiple different functions -> different hardware modules -template -void ntt_stage(uint16_t p_in[N], uint16_t p_out[N]){ - unsigned int start=0, j=0; - unsigned int len = K >> stage; - unsigned int k = 1 << stage; - - ntt_stage_loop1: for(start = 0; start < N; start = j + len) { - int16_t zeta = zetas[k]; k++; - ntt_stage_loop2: for(j = start; j < start + len; j++) { - #pragma HLS PIPELINE - int16_t t = fqmul(zeta, p_in[j + len]); - p_out[j + len] = p_in[j] - t; - p_out[j] = p_in[j] + t; - } - } -} - -void ntt(uint16_t p_in[N], uint16_t p_out[N]) { - uint16_t p_stage1[N]; - uint16_t p_stage2[N]; - uint16_t p_stage3[N]; - uint16_t p_stage4[N]; - uint16_t p_stage5[N]; - uint16_t p_stage6[N]; -#pragma HLS DATAFLOW - ntt_stage<0>(p_in, p_stage1); - ntt_stage<1>(p_stage1, p_stage2); - ntt_stage<2>(p_stage2, p_stage3); - ntt_stage<3>(p_stage3, p_stage4); - ntt_stage<4>(p_stage4, p_stage5); - ntt_stage<5>(p_stage5, p_stage6); - ntt_stage<6>(p_stage6, p_out ); -} - diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version3/polyvec.h b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version3/polyvec.h deleted file mode 100644 index 78506b03a6..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version3/polyvec.h +++ /dev/null @@ -1,30 +0,0 @@ -// polyvec.h - -#ifndef POLYVEC_H -#define POLYVEC_H - -#include -#include // for std::cout - -#include - -#define N 256 // Replace 'N' with the appropriate value -#define K 128 // Replace 'K' with the appropriate value - -#define Q 3329 // Replace 'Q' with the appropriate value -#define QINV -3327 // q^-1 mod 2^16 - -typedef struct { - uint16_t coeff[N]; -} poly; - -typedef struct { - poly vec[K]; -} polyvec; - -void polyvec_ntt(polyvec *vin,polyvec *vout); -void poly_ntt(poly *ain,poly *aout); -void ntt(uint16_t p_in[N], uint16_t p_out[N]); -//uint16_t montgomery_reduce(int32_t a); - -#endif // POLYVEC_H diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version3/polyvec_tb.cpp b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version3/polyvec_tb.cpp deleted file mode 100644 index 1f54bdbc4a..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version3/polyvec_tb.cpp +++ /dev/null @@ -1,62 +0,0 @@ -// test_polyvec.c - -#include "polyvec.h" // Include the header file that contains the function declarations - -// Define a helper function to print the elements of a poly data structure -void print_poly(const poly *a) { - printf("("); - for (int i = 0; i < N - 1; i++) { - printf("%d, ", a->coeff[i]); - } - printf("%d)\n", a->coeff[N - 1]); -} - -int main() { - - // Create some sample test data - poly a, b; - uint16_t a_golden[N]= {5758, 65052, 3754, 63002, 5194, 63563, 7282, 31, 2483, 2197, 2725, 64875, 2707, 3846, 4817, 2194, 1971, 4132, 4251, 3560, 2319, 613, 1075, 3935, 3635, 65350, 4709, 2718, 4484, 531, 7476, 63793, 2874, 155, 304, 63649, 64826, 63919, 64376, 61037, 1479, 64841, 65071, 64221, 1679, 65407, 3431, 1923, 1603, 558, 681, 316, 517, 931, 63939, 1999, 2024, 1094, 2276, 64366, 2187, 64180, 2637, 61036, 5702, 198, 2986, 62454, 1482, 62656, 4486, 60168, 1057, 64427, 4453, 1019, 3729, 2206, 1225, 64440, 1376, 65087, 2664, 62821, 64167, 1974, 65141, 64886, 65067, 2217, 61775, 65441, 1905, 3365, 64513, 2145, 219, 581, 65207, 63585, 61270, 2835, 63892, 1091, 63261, 64357, 543, 65399, 61396, 3246, 64484, 570, 239, 64729, 63045, 64197, 126, 64844, 126, 818, 3232, 63282, 940, 742, 2617, 62837, 3979, 64983, 61484, 482, 61086, 868, 60827, 2149, 58615, 5225, 61874, 64513, 62270, 883, 64670, 1313, 64158, 2999, 62304, 64013, 61708, 64311, 63978, 64660, 370, 64812, 871, 1467, 64633, 1985, 64570, 658, 63222, 62862, 62708, 62871, 63456, 65327, 106, 65307, 1274, 1919, 1890, 64354, 64168, 64156, 1738, 461, 2772, 63477, 65302, 64296, 63258, 61454, 63835, 63942, 62073, 60912, 62862, 62731, 65402, 59779, 2007, 63626, 157, 61212, 2344, 65032, 634, 850, 64730, 2642, 672, 1604, 216, 3280, 63524, 4234, 1165, 1532, 3059, 4106, 62449, 63959, 64259, 533, 63213, 64065, 64543, 1183, 63863, 63875, 60915, 65153, 64391, 1048, 62311, 65032, 63084, 111, 63570, 1989, 64202, 62866, 12, 506, 63758, 64229, 62090, 1591, 63844, 2330, 63832, 65002, 62981, 70, 63209, 3194, 63135, 987, 61595, 3005, 58432, 62356, 61472, 65312, 64709, 2134, 61595, 64510}; - uint16_t b_golden[N]= {65086, 62209, 64084, 64797, 61475, 768, 62519, 63814, 2906, 731, 65234, 64619, 65225, 1133, 62951, 2849, 61528, 5778, 62668, 3100, 65031, 1574, 64409, 1376, 153, 889, 62897, 4271, 64449, 1759, 409, 2349, 1437, 979, 3481, 415, 65181, 64307, 2749, 1359, 2404, 64705, 1432, 63739, 2504, 64723, 3380, 1573, 61344, 708, 64212, 63668, 64130, 3777, 866, 639, 1012, 1526, 1138, 64524, 64965, 64801, 61861, 63581, 2851, 1796, 1493, 64688, 741, 2164, 2243, 5040, 64400, 63627, 562, 64831, 3529, 928, 2277, 63966, 688, 3326, 1332, 1900, 4309, 2590, 1467, 88, 4759, 4384, 3113, 2926, 5946, 3493, 4482, 1069, 1774, 3982, 1500, 4344, 1196, 1912, 64714, 2486, 3856, 64853, 1936, 1101, 4588, 1286, 6132, 1340, 63991, 63342, 419, 62596, 63, 1074, 63, 65496, 1616, 963, 470, 64511, 2973, 65215, 325, 2507, 63510, 65240, 1104, 62290, 64846, 1755, 63740, 65263, 1498, 2318, 1696, 1006, 65103, 135, 64847, 1609, 63920, 63519, 63622, 65415, 64757, 1581, 185, 481, 60978, 62282, 63420, 65054, 61724, 60685, 61050, 61447, 64122, 61909, 64496, 64305, 53, 59954, 637, 62924, 945, 63546, 2645, 63160, 869, 65274, 63593, 1768, 65419, 62127, 64397, 59399, 814, 62046, 3262, 62500, 64199, 60100, 65469, 63208, 61546, 59404, 63950, 59656, 63379, 1639, 317, 1499, 65133, 4116, 62543, 4294, 108, 2226, 64530, 2474, 64454, 1455, 62072, 4129, 62328, 2094, 59904, 1122, 62710, 3701, 60046, 4427, 828, 64439, 64890, 64947, 63299, 64387, 62259, 1371, 2103, 64514, 64553, 63028, 2662, 61752, 6, 64998, 2440, 63357, 1606, 63371, 64690, 1124, 64684, 65128, 62594, 65395, 62708, 64723, 464, 1265, 65230, 3837, 65313, 5472, 1297, 2506, 1251, 1450, 3023, 1264}; - - for (int i = 0; i < N; i++) - a.coeff[i] = i; - - for (int i = 0; i < N; i++) - b.coeff[i] = a.coeff[( (i % 2 == 0) ? i / 2 : N - 1 - i / 2 )]; - - // Print the input - printf("Input Polynomial 'a': "); - print_poly(&a); - - printf("Input Polynomial 'b': "); - print_poly(&b); - - // Perform NTT on the poly data structures - polyvec v,x; - v.vec[0] = a; - v.vec[1] = b; - - // Perform the NTT on the vector of polynomials - polyvec_ntt(&v,&x); - - // Print the results - printf("Output Polynomial 'a' after NTT: "); - print_poly(&x.vec[0]); - - printf("Output Polynomial 'b' after NTT: "); - print_poly(&x.vec[1]); - - for (int i = 0; i < N; i++) { - if(a_golden[i] != x.vec[0].coeff[i]) { - printf("mismatch on a[%d]/v.vec[0].coeff[%d], expected %d got %d\n",i,i,a_golden[i], v.vec[0].coeff[i]); - return 1; - } - if(b_golden[i] != x.vec[1].coeff[i]) { - printf("mismatch on b[%d]/v.vec[1].coeff[%d], expected %d got %d\n",i,i,b_golden[i], v.vec[1].coeff[i]); - return 2; - } - } - printf("Self-checking tests complete: OKAY\n"); - return 0; -} - diff --git a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version3/vitis-comp.json b/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version3/vitis-comp.json deleted file mode 100644 index 6230b2af3d..0000000000 --- a/Vitis_HLS/Design_Tutorials/01-Polynomial_Vectorization/workspace/Version3/vitis-comp.json +++ /dev/null @@ -1,10 +0,0 @@ -{ - "name": "Version3", - "type": "HLS", - "configuration": { - "componentType": "HLS", - "configFiles": [ - "hls_config.cfg" - ] - } -} diff --git a/Vitis_HLS/Design_Tutorials/02-Beamformer/README.md b/Vitis_HLS/Design_Tutorials/02-Beamformer/README.md index 8a243dd48e..092e900285 100644 --- a/Vitis_HLS/Design_Tutorials/02-Beamformer/README.md +++ b/Vitis_HLS/Design_Tutorials/02-Beamformer/README.md @@ -13,7 +13,7 @@ # Adaptive Beamforming for Radar: Floating-Point QRD+WBS in an FPGA -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## ABSTRACT diff --git a/Vitis_HLS/Design_Tutorials/Design_Tutorials.rst b/Vitis_HLS/Design_Tutorials/Design_Tutorials.rst index 6e90036336..3120f75723 100644 --- a/Vitis_HLS/Design_Tutorials/Design_Tutorials.rst +++ b/Vitis_HLS/Design_Tutorials/Design_Tutorials.rst @@ -11,22 +11,16 @@ Design tutorials illustrate higher-level Vitis™ HLS concepts or design flows, :caption: Design Tutorials :hidden: - Polynomial Vectorization using Number Theoretic Transforms <./01-Polynomial_Vectorization/README.md> Adaptive Beamforming for Radar <./02-Beamformer/README.md> - - .. list-table:: :widths: 20 80 :header-rows: 1 * - Tutorial - Description - - * - :doc:`Polynomial Vectorization using Number Theoretic Transforms <./01-Polynomial_Vectorization/README>` - - Demonstrates how to use Code Analyzer to optimize C/C++ code for Vitis HLS. The case study is based on the CRYSTALS-Kyber algorithm, polynomial vectorization, and number theoretic transforms. * - :doc:`Adaptive Beamforming for Radar <./02-Beamformer/README>` - This design example discusses beamforming, its applications to radar, and the optimization of floating-point QRD+WBS on an AMD FPGA. diff --git a/Vitis_HLS/Design_Tutorials/README.md b/Vitis_HLS/Design_Tutorials/README.md index da0e64ac9f..52a2ae8a06 100644 --- a/Vitis_HLS/Design_Tutorials/README.md +++ b/Vitis_HLS/Design_Tutorials/README.md @@ -22,10 +22,6 @@ Design tutorials illustrate higher-level Vitis™ HLS concepts or design flows, Description - Polynomial Vectorization using Number Theoretic Transforms:
A Real World Case Study Using Vitis HLS Code Analyzer - This tutorial demonstrates how to use Code Analyzer to optimize C/C++ code for Vitis HLS. The case study is based on the CRYSTALS-Kyber algorithm, polynomial vectorization, and number theoretic transforms. - - Adaptive Beamforming for Radar:
Floating-Point QRD+WBS in an FPGA This design example discusses beamforming, its applications to radar, and the optimization of floating-point QRD+WBS on an AMD FPGA. diff --git a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/README.md b/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/README.md deleted file mode 100644 index 401076da29..0000000000 --- a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/README.md +++ /dev/null @@ -1,297 +0,0 @@ - - - - -
- - - AMD logo - -

AMD Vitis™ HLS Tutorials

- See Vitis™ Development Environment on amd.com -
- -# Using Code Analyzer from Vitis Unified IDE - -***Version: Vitis 2025.1*** - -## Tutorial Overview - -This tutorial shows you how to use the pre-synthesis feature called Code Analyzer for the Vitis High-Level Synthesis tool flow. - -It is assumed that you are familiar with the Vitis High-Level Synthesis (shortened Vitis HLS or VHLS) tool flow. Code Analyzer requires the same setup as for C-Simulation for an HLS component so you can follow the [getting started with Vitis HLS Components tutorial](https://docs.amd.com/r/en-US/Vitis-Tutorials-Getting-Started/Vitis-HLS) to familiarize yourself with this process. - -Vitis Code Analyzer helps you investigate your design efficiency and get a performance estimation before running the VHLS C-Synthesis compilation. It uses a C-Testbench from the C-Simulation setup to dynamically analyze your design and extract data volume and movement as well as estimate transaction interval to investigate the performance; the data is presented as a graph. - -The documentation about Code Analyzer can be found in the *Vitis High-Level Synthesis User Guide* ([UG1399](https://docs.amd.com/r/en-US/ug1399-vitis-hls)). - -## Before You Begin - -It is assumed that the Vitis tools are installed and set up. - -The labs in this tutorial use: - -- One component named `tutorial_example` that is the initial design which we are going to investigate with Code Analyzer. -- One component named `tutorial_example_final` which based on the above and has been optimized when following the tutorial. We use it for reference in the last section so that the tutorial matches with this second component. -- If necessary, the tutorial can be easily changed to other device or platforms. - -### Accessing the Tutorial Reference Files - -1. To access the reference files, type the following into a terminal: `$ git clone https://github.com/Xilinx/Vitis-Tutorials` -1. Navigate to `./Vitis-Tutorials/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files` directory. -1. You need an Vitis Unified IDE workspace. If you don't have one yet, you can create a new one, for example `$ mkdir ~/myworkspace`; that's the name we're going to use in this tutorial: change to match your preference. -1. Copy the 2 components into your Vitis Unified IDE workspace. `$ cp -r tutorial_example/ tutorial_example_final/ ~/myworkspace` -1. You are now ready. We will start the Vitis Unified IDE in the next section. - -## Investigate `tutorial_example` using Code Analyzer - -Launch the new Vitis Unified IDE to open directly your workspace `$ vitis --workspace ~/myworkspace` - -The IDE starts from the Welcome page, you can close it if you wish. We can change the color scheme via `file` > `preferences` > `color theme`. We used the light color theme to get the screenshots in this tutorial. - -![Vitis Welcome Screen](./images/vitis_welcome.png "Vitis Welcome Screen") - -Select the component named `tutorial_example` in the `VITIS COMPONENTS` upper left-hand panel. - -Notice [HLS] in grey, indicating an HLS component. - -Hover on the `C SIMULATION` line to reveal the gear icon and click it to open the settings. - -The screenshot below shows that Vitis HLS Code Analyzer is enabled. Notice that when enabled, other options are disabled because they are not compatible with Code Analyzer (namely O (optimization), profile and setup). - -![Vitis CSIM Screen](./images/CSIM_settings.png "Vitis CSIM Screen") - -Let’s observe the lower left-hand panel: it's named `FLOW`. - -Under `C SIMULATION` notice that we have 3 options: `Run`, `Debug` and `REPORTS`, but the REPORTS option is greyed-out. Let’s click `Run` to execute the C-Simulation. If you examine the console output you can read the message **Executing Code Analyzer instead of classic HLS C simulation** - -After a few moments, the console reports **C-simulation finished successfully** and you can notice that the `REPORTS` section is now selectable. Expand the `REPORTS` and click on `Code Analyzer`. - -You get presented with a graph view: - -![Code Analyzer first screen](./images/CA_view1.png "Code Analyzer first screen") - -This view helps you convert your design into the dataflow form and assists you in its optimization. - -Your C/C++ code is represented here as a dataflow design even if it is currently written in a sequential form. Dataflow processes are deduced from the top-level statements in the selected function body and their dependencies are turned into channels. Performance estimates are computed for the presented dataflow design, ignoring potential canonicalization issues. - -With this graph view you get a lot of information immediately: - -- Nodes represent dataflow processes with their names being function names or loops labels (unnamed loops are named "Process #N"). Estimated Transaction Intervals are also presented next to the node name. When you expand the node using the arrow-head button, you can see a snippet of the function call site or loop code. -- Edges are the communication channel extracted from the variables of the design. You can see their names, the volume of data and the average throughout, expressed by default in bits per second, both estimated from the C-TB run. - -Transaction Interval is the minimal delay between two executions of a process. -Remember that Code Analyzer assumes that the top level region contains processes executing independently, and as such the region's performance is limited by the slowest process, the one with the largest TI number estimate. It is the process highlighted in red. - -You can select other functions to investigate by selecting the function drop-down menu in the toolbar, but you can also iteratively drill down the function calls and loops in the different processes to achieve the same effect. This can be achieved by clicking on the right-pointing arrows next to lines of codes in processes. - -![Code Analyzer select function to analyzer](./images/CA_select_function.png "Code Analyzer select function to analyzer") - -Below the graph, a table on the lower half of the view shows the processes and channels with more details. We will review this later in the tutorial. - -The figure below illustrates how every node in the graph relates to top-level statements in the function being analyzed. - -![Code Analyzer process to code matching](./images/CA_process_to_code_matching.png "Code Analyzer process to code matching") - -The graph also allows users to perform graph-only transformations by merging processes together so that the graph nodes and edges are recomputed, and the new performance of the merged process can be investigated. The merge operation is performed with the move icon on the process: left-click the icon, hold, and start dragging the process and the graph will show the possible target processes by changing their borders into dashed lines. The screenshot below shows that we can merge `Process 2` with the process `loop1` directly before, and the process `loop3` directly after, but not `loop4` or `computeD()`. - -![Code Analyzer process merge](./images/CA_process_merge.png "Code Analyzer process merge") - -Let's go ahead and merge `Process 2` with `loop3` by releasing the mouse button. The tool computes the updated metrics and updates the graph; here notice the `loop3` process is not present anymore. Now we can also try the reverse operation, the split operation, on the merged process: first, expand the process with the arrow-head icon. A horizontal dashed line shows the split location with the original code for `Process 2` and `loop3` on each side. A split button appears when you hover the mouse on the split line. Select the split button with the mouse to perform the split. - -![Code Analyzer process split](./images/CA_process_split.png "Code Analyzer process split") - -More complex code might have more processes on the graph than what you might expect from the source code because class constructors or initialization might be extracted as processes. In those situations, Code Analyzer estimates that they will take some clock cycles at runtime. - -### Process Table - -Let’s look at the process table which shows process names and their pre-synthesis Transaction Interval estimation value. Recall that the Transaction Interval is the minimal delay between two executions of a process. It's worth investigating processes with the largest values because they are the bottle neck but in the context of this tutorial let’s take 2 other examples. - -![Code Analyzer process-table only](./images/CA_process_table_only.png "Code Analyzer process-table only") - -#### `Process 2` analysis - -Focusing on `Process 2`, let's check how we arrive to a `TI=258`. - -On the node representing `Process 2`, use the down pointing arrow on the left to show the code. - -![Code Analyzer Process 2 folded](./images/CA_process_2_process_folded.png "Code Analyzer Process 2 folded") - -We can make the following observations: - -1. The code is using a double nested loop to clear array `C[16][16]`. -1. The performance analysis of Code Analyzer is overlaid in the code snippet, here this is shown between lines 1 and 2 and lines 2 and 3, right at the start of the regions defined by the for-loops. Let's look into the numbers. -1. Code Analyzer estimates the performance of the innermost-loop first: Initiation Interval of 1 clock cycle can be achieved to start the next iteration, so `II=1` is reported. -1. Each for-loop is counting from 0 to 15 because constant N=16 is used, so `TRIPCOUNT=16` is reported. -1. The Transaction Interval is `TI=TRIPCOUNT*II`, so for the innermost-loop we get `TI=16*1=16`. -1. We repeat the investigations hierarchically up into the parent loop: we compute the sum of all TI(s) of all the statements in the loop body. The TI sum becomes the II of the loop, since we have only the innermost-loop in the loop body we have an `II=16`, and with `TRIPCOUNT=16`, so their product gives us `TI=16*16=256`. -1. As the loops are the only statements from the extracted process itself, we add 2 extra cycles for the state machine of the process which gives the overall Transaction Interval for `Process 2` of `TI=256+2=258` - -![Code Analyzer Process 2 investigations](./images/CA_process_2_investigations.png "Code Analyzer Process 2 investigations") - -> **NOTE**: Performance analysis numbers are shown at the beginning of a loop, within its curly braces `{}`, or right after a function call site. - -##### Reported Tripcount Values - -1. If loop bounds are compile-time constants, they are reported in Code Analyzer; -1. Otherwise, if a tripcount pragma is provided, this value is used by Code Analyzer; -1. Otherwise, the tripcount value is measured when running the C-testbench. - -In any case, the reported tripcounts account for the loop unrolling: loop tripcounts are divided by unrolling factors. Fully unrolled loops will always have a reported tripcount of 1. - -#### `loop3` analysis - -For loop 3: there is also a double nested loop with same tripcount for all loops. - -However, with this example, Code Analyzer estimates that `II=2`. - -![Code Analyzer process loop3 investigations](./images/CA_process_loop3_investigations.png "Code Analyzer process loop3 investigations") - -A similar analysis and computation to the previous section can be performed and arrive to the conclusion that the innermost-loop has `TI=TRIPCOUNT*II=16*2=32` and the outermost-loop has an overall `TI=TRIPCOUNT*II=16*32=512`, finally adding 2 extra cycles for the state machine gives `TI=512+2=514`. - -#### Pipelining `loop3` and new analysis - -Let's try to improve the performance of `loop3` by using a pipeline pragma on the innermost-loop: on the graph, right click on the process and select "goto source", this brings you to the call site. - -![Code Analyzer process loop3 goto source](./images/CA_process_loop3_goto_source.png "Code Analyzer process loop3 goto source") - -Insert a new line after the for statement of the innermost loop and type `#pragma HLS PIPELINE II=1`. You can see that the editor suggest you the possible completions as you type. Save the file (note: it should be saved automatically) and run again `C SIMULATION`, then open Code Analyzer in the report section. Notice the updated Transaction Interval estimation `TI=290`. Expand the code by using the down pointing arrow. - -![Code Analyzer process loop3 after pipeline](./images/CA_process_loop3_after_pipeline.png "Code Analyzer process loop3 after pipeline") - -We can observe that Code Analyzer took into account the Pipeline Pragma and estimated that `II=1` was now achievable. Similar to before, this means the innermost loop now achieves `TI=TRIPCOUNT*II=16*1=16`. - -Because the innermost loop is pipelined, this means the hardware module generated is independent from the outermost loop module and the innermost loop will have its own finite state machine (FSM). The outermost loop will also have its own FSM, so it will take an extra 2 clock cycles to enter and exit the inner loop FSM; for this reason, the outermost loop's II is not only the sum of all TI from statements like in the previous situation but we need to add those 2 more cycles, `II=16+2=18`. - -You don't need to remember all the details but it's good to have a good understanding of the estimations and the way they are computed and influence their parent hierarchy. - -The Transaction Internal of the outermost loop will be `TI=TRIPCOUNT*II=16*18=288`. - -For the extracted process itself, we add 2 extra cycles for the finite state machine of the process which gives the overall Transaction Interval for the pipelined `loop3` of `TI=288+2=290`. - -We can check and analyze the other processes but there are some simplifications and optimizations that we can do perform. Let's look at the Channel table to see how it can help us. - -#### Guidance messages when pipeline is not possible - -At this point, you might think that we can also pipeline the outer loop, so let's just add the pipeline pragma: there is a placeholder in the source code that you can uncomment. -By the comments in the source code, you understand this is not possible, but why? Let's see what messages Code Analyzer gives. - -![Code Analyzer process loop3 pipeline too much](./images/CA_process_loop3_pipeline_too_far.png "Code Analyzer process loop3 pipeline too much") - -After the code change and running `C SIMULATION` let's see the output from Code Analyzer: - -1. The process table shows a guidance message relating to process `loop3` : *Some variables are accessed by more instructions than their hardware implementation can sustain in a single cycle, preventing some loops from being accelerated. Partition these variables to accelerate your design.* -2. We can expand the code of process `loop3`, to see what it relates to, along with other details. -3. The overlay for the TI computations shows the word `Details` which is a clickable button, let's click, -4. A side information panel opens which shows the details about the II issue: too many accesses for the arrays. - -![Code Analyzer process loop3 pipeline too much](./images/CA_process_loop3_pipeline_too_far_guidance_message.png "Code Analyzer process loop3 pipeline too much") - -Comment out the pipeline pragma and **keep only the pragma in the innermost-loop**. - -### Channel table - -A Channel is the flow data going into and out of each Processes. Channels are named after the variable defining them in the C source code, they are usually arrays, pointers or hls::streams. The Channel table describes each Channel in a separate row. - -![Code Analyzer Channel Table](./images/CA_channel_table_only.png "Code Analyzer Channel Table") - -The details available on each row are: - -- Channel name -- C/C++ declaration -- Data volume expected to be delivered over the channel - measured from C-Simulation run -- Estimated throughput: data volume divided by the estimated Transaction Interval of the current region -- Channel's bitwidth -- Access mode from producer process to consumer process -- Producer and Consumer processes names - -The Channel table rows and graph edges are cross-linked: selecting one select will the other and vice-versa. You can highlight multiple channels with CTRL+CLICK. It is also possible to sort the table columns or search in the table. - -> **NOTE**: The average throughput is the channel volume divided by the region’s transaction interval, so it is meaningful to compare with other channels throughput values, for one given dataset and implementation. However, changing the C code or C-TB inputs might change transaction intervals or volume and hence change the throughput values, so be careful when comparing throughput of different runs. - -### Investigations Based on TI and Processes - -The transaction interval (TI) of dataflow processes heavily influences the throughput of the dataflow region. In fact, for dataflow regions (using the dataflow pragma), the TI of the region in steady-state execution is defined by the maximum TI of its processes. The predicted TI of the processes in Code Analyzer thus allows you to identify the performance bottlenecks in your design: you should accelerate the processes with the highest TI first. - -In our example, we investigate computeD() which showed TI = 2051 clock cycles - -On the graph, right-click the process, and then select **goto source**. This brings you to the call site then use CTRL+CLICK to go to definition. - -![Code Analyzer goto source 1](./images/CA_goto_source_step1.png "Code Analyzer goto source 1") -→ -![Code Analyzer goto source 2](./images/CA_goto_source_step2.png "Code Analyzer goto source 2") -→ -![Code Analyzer goto source 3](./images/CA_goto_source_step3.png "Code Analyzer goto source 3") - -We can see this behavior: "acc" is always cleared as we enter the i-j double loop nest and is updated only at the end of the t-loop before starting a new iteration. But it is cleared again at the start of a new t-loop iteration, so we can see 2 issues: - -1. Despite being updated, "acc" is never different from zero when it is read, so it has no effects and can be removed from the code. -2. The t-loop is unnecessary because the array D[][] is just updated 4 times with the same values. We can remove the t-loop as well. - -We can rerun c-simulation for the design to confirm it’s still functionally correct. - -### Investigations based on channels table - -#### Focus on A - -Looking at the channel table and sorting by name, we can focus on the top-level argument A. - -Remember that, in contrary to the Dataflow Viewer available after synthesis, Code Analyzer presents you with a dataflow view of your design even if it cannot yet be synthesized in its dataflow form. The channel table contains all the properties required to determine if your design is a synthesizable dataflow design. For instance, you can use it to spot back edges, unsupported accesses to variables, or multiple producer/consumer violations. - -The channels created by the variable A in our example lead to multiple producer/consumer violations because it is used 4 times. In the screenshot below, we have sorted the Channel table by name and selected (CTRL+LEFT_CLICK) the 4 channels "A" to get them also highlighted on the graph. We can further notice that only one row of the table has a volume of ~8 kbits which is matching the size of the whole arrays because it is `int [16][16] type: 16*16*32=8192 bits`; the other 3 lines with a lower volume might be source of potential issues because the whole volume is not consumed – in practice this would indicate partial reads so the user needs to investigate further if FIFO is possible or if an array is the only possible implementation. - -![Code Analyzer focus on A](./images/CA_focus_A.png "Code Analyzer focus on A") - -We can notice: - -1. loop1 updates F from A -2. F is not used -3. So loop1 is not necessary. - -Only loop4 makes sense and the path is START -> loop4 -> END for A. - -If you look more closely at what happens in loop4 you can see that A is incremented by the value 5 for 15 times – because inner j-loop iterates from 1 to 15. So, this could be further simplified as A[i][0] += 15 * 5 without using the "buffer" array. - -#### Focus on C - -![Code Analyzer focus on C](./images/CA_focus_C.png "Code Analyzer focus on C") - -Similarly, we can see that something is not right with C because this top-level argument is used in 4 communication channels between processes. This is the observed behavior: - -1. Loop2 visits every location and clears them -2. Loop3 does accumulation on each individual location -3. In short, if we were to merge the 2 loops then each location is cleared and is followed by a single addition, not an accumulation - - Consequences: - -4. loop2 is not necessary -5. loop3 can do C[i][j] = B[i][j] * E[i][j]; - -We can simplify the code to solve these issues. - -After the code updates we can check the new version. - -## Compare optimized with original version - -For this tutorial, we have the version of the updated code in the component named `tutorial_example_final`. We can select this component and run `C SIMULATION`. After a few moments, the console reports "C_simulation finished successfully". Expand the `REPORTS` and click on `Code Analyzer`. -It contains the updates previously mentioned and pipelines directives for the innermost-loops, and a pragma dataflow at the top to make sure that we are using dataflow. `C-Synthesis` will confirm that when we run it. - -The screenshot below shows the Code Analyzer graph for `tutorial_example` on the left and the Code Analyzer graph for `tutorial_example_final` on the right. - -At a glance, we can see that we have fewer processes and fewer channels as predicted by our investigations. - -We also show the `Dataflow Viewer` output on the bottom right after running `C SYNTHESIS`: you can notice the process extracted are the same. - -![Code Analyzer side-by-side compare of original vs final](./images/CA_side_by_side_compare.png "Code Analyzer side-by-side compare of original vs final") - -## Conclusion - -The `Code Analyzer` view gives us an overview of our design as if it was dataflow: we identified and fixed problems related to performance and legality, and now, we can now run C-synthesis. - -We did all this without having to perform C-Synthesis and C-RTL Co-Simulation, significantly accelerating our work. - -
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a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/images/vitis_welcome.png b/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/images/vitis_welcome.png deleted file mode 100755 index 4fa81da09b..0000000000 Binary files a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/images/vitis_welcome.png and /dev/null differ diff --git a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example/Makefile b/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example/Makefile deleted file mode 100644 index ea16a61c64..0000000000 --- a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example/Makefile +++ /dev/null @@ -1,40 +0,0 @@ -####################################################################################### -.PHONY: help -help: - @echo "Makefile Usage:" - @echo " make all" - @echo " Command to run all target csim & csynth & cosim in turn." - @echo "" - @echo " make csim" - @echo " make csynth" - @echo " make cosim" - @echo " Command to run only one step of Vitis HLS. Note csim forces clean first." - @echo "" - @echo " make clean" - @echo " Command to remove the generated files." - @echo "" - @echo " make help" - @echo " Print this help." - @echo "" -####################################################################################### - -SHELL := bash -SOURCES := hw.cpp hw.h -SOURCES_TB := ${SOURCES} tb.cpp - -CONFIG := hls_config.cfg -WORK_DIR := top -COMMON_OPTIONS := --mode hls --config ${CONFIG} --work_dir ${WORK_DIR} - -all: csim csynth cosim - -csynth: ${SOURCES} ${CONFIG} - v++ --compile ${COMMON_OPTIONS} - -csim: clean # clean before csim ! -csim cosim: ${SOURCES_TB} ${CONFIG} - vitis-run --$@ ${COMMON_OPTIONS} - -.PHONY: clean -clean: - rm -rf ${WORK_DIR} vitis_c++/ .Xil/ xcd.log diff --git a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example/description.json b/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example/description.json deleted file mode 100644 index 5a2bf83759..0000000000 --- a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example/description.json +++ /dev/null @@ -1,31 +0,0 @@ -{ - "name": "VHLS_F_01-using-CA", - "description": "VHLS_F_01-using-CA", - "gui": "false", - "flow": "hls", - - "platform_allowlist": [ "u200"], - - "testinfo": { - "test_name": "VHLS_F_01-using-CA", - "disable": false, - "jobs": [ - { - "max_memory_MB": 76800, - "max_time_min": { - "vitis_sw_emu": 60 - } - } - ], - "targets": [ - "hls_csim", - "hls_csynth", - "hls_cosim" - ], - "category": "canary", - "custom_build_target": - { - "all": "all" - } - } -} diff --git a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example/hls_config.cfg b/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example/hls_config.cfg deleted file mode 100644 index 0c5ff1cb3b..0000000000 --- a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example/hls_config.cfg +++ /dev/null @@ -1,10 +0,0 @@ -part=xcvu9p-flga2104-2-i - -[hls] -flow_target=vivado -package.output.format=rtl -package.output.syn=false -syn.file=hw.cpp -syn.top=top -tb.file=tb.cpp -csim.code_analyzer=1 diff --git a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example/hw.cpp b/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example/hw.cpp deleted file mode 100755 index b09ffeb586..0000000000 --- a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example/hw.cpp +++ /dev/null @@ -1,63 +0,0 @@ -/* -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: X11 -*/ - -#include "hw.h" - -void computeD(int D[N][N], int E[N][N]) { - int acc; -loop_d1: - for (int t = 0; t < 4; ++t) { - acc = 0; - for (int i = 0; i < N; ++i) { - for (int j = 0; j < N; ++j) { - D[i][j] = 2 * E[i][j] + acc; - } - } - acc += D[0][0]; - } -} - -int top(int A[N][N], int B[N][N], int C[N][N], int D[N][N], int E[N][N]) { - int F[N][N], buffer[N][N]; - -loop1: - for (int i = 0; i < N; ++i) { - for (int j = 0; j < N; ++j) { - F[i][j] = i * A[i][j]; - } - } -// this loop is not named and will show up as process 2 - for (int i = 0; i < N; ++i) { - for (int j = 0; j < N; ++j) { - C[i][j] = 0; - } - } - -loop3: - for (int i = 0; i < N; ++i) { - // pipelining this loop with II=1 is not possible - // Code Analyzer will give a performance guidance message - // #pragma HLS PIPELINE II=1 -L31: - for (int j = 0; j < N; ++j) { - C[i][j] += B[i][j] * E[i][j]; - } - } - -loop4: - for (int i = 0; i < N; ++i) { - buffer[i][0] = A[i][0]; - for (int j = 1; j < N; ++j) { - buffer[i][j] = buffer[i][j - 1] + 5; - } - A[i][0] = buffer[i][N - 1]; - } - - computeD(D, E); - - return 0; -} - - diff --git a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example/hw.h b/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example/hw.h deleted file mode 100755 index 4f610a84a5..0000000000 --- a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example/hw.h +++ /dev/null @@ -1,13 +0,0 @@ -/* -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: X11 -*/ - -#ifndef HW_H -#define HW_H - -#define N 16 - -int top(int A[N][N], int B[N][N], int C[N][N], int D[N][N], int E[N][N]); - -#endif diff --git a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example/tb.cpp b/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example/tb.cpp deleted file mode 100755 index a1a4bbb0b8..0000000000 --- a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example/tb.cpp +++ /dev/null @@ -1,36 +0,0 @@ -/* -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: X11 -*/ - -#include -#include - -#include "hw.h" - -int main(int argc, char**argv) { - int A[N][N], B[N][N], C[N][N], D[N][N], E[N][N]; - int A_ref[N][N], C_ref[N][N], D_ref[N][N]; - - for (int i = 0; i < N; ++i) { - for (int j = 0; j < N; ++j) { - A[i][j] = i; - B[i][j] = 1; - C[i][j] = 0; - D[i][j] = 0; - E[i][j] = i+j; - D_ref[i][j] = 2 * E[i][j]; - C_ref[i][j] = B[i][j] * E[i][j]; - A_ref[i][j] = A[i][j] + (j==0?5*15:0); - } - } - - top(A, B, C, D, E); - int errors=0; - if ( std::memcmp(A,A_ref,N*N*sizeof(A[0][0])) != 0 ) {errors++;} - if ( std::memcmp(C,C_ref,N*N*sizeof(C[0][0])) != 0 ) {errors++;} - if ( std::memcmp(D,D_ref,N*N*sizeof(D[0][0])) != 0 ) {errors++;} - std::cout << "from " __FILE__ ": got "<0; -} diff --git a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example/vitis-comp.json b/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example/vitis-comp.json deleted file mode 100644 index 1c21aba1a3..0000000000 --- a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example/vitis-comp.json +++ /dev/null @@ -1,12 +0,0 @@ -{ - "name": "tutorial_example", - "type": "HLS", - "configuration": { - "componentType": "HLS", - "configFiles": [ - "hls_config.cfg" - ], - "work_dir": "tutorial_example" - }, - "previousBuildStatusMap": {} -} diff --git a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example_final/hls_config.cfg b/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example_final/hls_config.cfg deleted file mode 100644 index 0c5ff1cb3b..0000000000 --- a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example_final/hls_config.cfg +++ /dev/null @@ -1,10 +0,0 @@ -part=xcvu9p-flga2104-2-i - -[hls] -flow_target=vivado -package.output.format=rtl -package.output.syn=false -syn.file=hw.cpp -syn.top=top -tb.file=tb.cpp -csim.code_analyzer=1 diff --git a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example_final/hw.cpp b/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example_final/hw.cpp deleted file mode 100755 index 9afd2c5775..0000000000 --- a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example_final/hw.cpp +++ /dev/null @@ -1,40 +0,0 @@ -/* -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: X11 -*/ - -#include "hw.h" - -void computeD(int D[N][N], int E[N][N]) { - // removed un-needed loop 4 times and accum which was always 0 when used - for (int i = 0; i < N; ++i) { - for (int j = 0; j < N; ++j) { - #pragma HLS PIPELINE II=1 - D[i][j] = 2 * E[i][j]; - } - } -} - -int top(int A[N][N], int B[N][N], int C[N][N], int D[N][N], int E[N][N]) { - int buffer[N][N]; -#pragma HLS DATAFLOW - -loop23: // combined loop2 and loop3 - for (int i = 0; i < N; ++i) { - for (int j = 0; j < N; ++j) { - #pragma HLS PIPELINE II=1 - C[i][j] = B[i][j] * E[i][j]; - } - } -loop4: - for (int i = 0; i < N; ++i) { - // the original code was basically adding 15 times - // the value 5 onto A[i][0] in a convoluted manner - #pragma HLS PIPELINE II=1 - A[i][0] += 15 * 5; - } - - computeD(D, E); - - return 0; -} diff --git a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example_final/hw.h b/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example_final/hw.h deleted file mode 100755 index 4f610a84a5..0000000000 --- a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example_final/hw.h +++ /dev/null @@ -1,13 +0,0 @@ -/* -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: X11 -*/ - -#ifndef HW_H -#define HW_H - -#define N 16 - -int top(int A[N][N], int B[N][N], int C[N][N], int D[N][N], int E[N][N]); - -#endif diff --git a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example_final/tb.cpp b/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example_final/tb.cpp deleted file mode 100755 index a1a4bbb0b8..0000000000 --- a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example_final/tb.cpp +++ /dev/null @@ -1,36 +0,0 @@ -/* -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: X11 -*/ - -#include -#include - -#include "hw.h" - -int main(int argc, char**argv) { - int A[N][N], B[N][N], C[N][N], D[N][N], E[N][N]; - int A_ref[N][N], C_ref[N][N], D_ref[N][N]; - - for (int i = 0; i < N; ++i) { - for (int j = 0; j < N; ++j) { - A[i][j] = i; - B[i][j] = 1; - C[i][j] = 0; - D[i][j] = 0; - E[i][j] = i+j; - D_ref[i][j] = 2 * E[i][j]; - C_ref[i][j] = B[i][j] * E[i][j]; - A_ref[i][j] = A[i][j] + (j==0?5*15:0); - } - } - - top(A, B, C, D, E); - int errors=0; - if ( std::memcmp(A,A_ref,N*N*sizeof(A[0][0])) != 0 ) {errors++;} - if ( std::memcmp(C,C_ref,N*N*sizeof(C[0][0])) != 0 ) {errors++;} - if ( std::memcmp(D,D_ref,N*N*sizeof(D[0][0])) != 0 ) {errors++;} - std::cout << "from " __FILE__ ": got "<0; -} diff --git a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example_final/vitis-comp.json b/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example_final/vitis-comp.json deleted file mode 100644 index adeae84d7d..0000000000 --- a/Vitis_HLS/Feature_Tutorials/01-using_code_analyzer/reference-files/tutorial_example_final/vitis-comp.json +++ /dev/null @@ -1,12 +0,0 @@ -{ - "name": "tutorial_example_final", - "type": "HLS", - "configuration": { - "componentType": "HLS", - "configFiles": [ - "hls_config.cfg" - ], - "work_dir": "tutorial_example_final" - }, - "previousBuildStatusMap": {} -} diff --git a/Vitis_HLS/Feature_Tutorials/02-Beamformer_Analysis/README.md b/Vitis_HLS/Feature_Tutorials/02-Beamformer_Analysis/README.md index e1b9d0b832..b8101b9c5b 100644 --- a/Vitis_HLS/Feature_Tutorials/02-Beamformer_Analysis/README.md +++ b/Vitis_HLS/Feature_Tutorials/02-Beamformer_Analysis/README.md @@ -13,7 +13,7 @@ # HLS Micro-Optimization Tutorial using Beamformer IP -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** ## Tutorial Overview diff --git a/Vitis_HLS/Feature_Tutorials/Feature_Tutorials.rst b/Vitis_HLS/Feature_Tutorials/Feature_Tutorials.rst index d8556b840c..7712936de9 100644 --- a/Vitis_HLS/Feature_Tutorials/Feature_Tutorials.rst +++ b/Vitis_HLS/Feature_Tutorials/Feature_Tutorials.rst @@ -11,7 +11,6 @@ Feature tutorials illustrate specific features of Vitis HLS development flow. So :caption: Feature Tutorials :hidden: - Using Code Analyzer <./01-using_code_analyzer/README.md> Beamformer Analysis <./02-Beamformer_Analysis/README.md> @@ -23,9 +22,6 @@ Feature tutorials illustrate specific features of Vitis HLS development flow. So * - Tutorial - Description - - * - :doc:`Using Code Analyzer <./01-using_code_analyzer/README>` - - Use the pre-synthesis feature called Code Analyzer for the Vitis High-Level Synthesis tool flow. * - :doc:`Beamformer Analysis <./02-Beamformer_Analysis/README>` - Use HLS analysis tools to make low-level optimizations on a subset of the beamformer algorithm. @@ -38,4 +34,4 @@ Feature tutorials illustrate specific features of Vitis HLS development flow. So .. Copyright © 2020–2024 Advanced Micro Devices, Inc -.. `Terms and Conditions `_. \ No newline at end of file +.. `Terms and Conditions `_. diff --git a/Vitis_HLS/Feature_Tutorials/README.md b/Vitis_HLS/Feature_Tutorials/README.md index 9ff9c7f383..7874ea5acb 100644 --- a/Vitis_HLS/Feature_Tutorials/README.md +++ b/Vitis_HLS/Feature_Tutorials/README.md @@ -23,10 +23,6 @@ Feature tutorials illustrate specific features of the Vitis™ HLS development f Description - Using Code Analyzer from Vitis Unified IDE - Use the pre-synthesis feature called Code Analyzer for the Vitis High-Level Synthesis tool flow. - - HLS Micro-Optimization Tutorial using Beamformer IP Use HLS analysis tools to make low-level optimizations on a subset of the beamformer algorithm. diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/01-Edge-KV260.rst b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/01-Edge-KV260.rst deleted file mode 100644 index d9c13ace3c..0000000000 --- a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/01-Edge-KV260.rst +++ /dev/null @@ -1,5 +0,0 @@ -####################################################### -Version: Vitis 2022.2 -####################################################### - -To view the source files for this tutorial, click `here `_. \ No newline at end of file diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/Iteration_guideline.md b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/Iteration_guideline.md deleted file mode 100644 index 17d1cdb7cc..0000000000 --- a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/Iteration_guideline.md +++ /dev/null @@ -1,39 +0,0 @@ - - - - -
- - - AMD logo - -

AMD Vitis™ Platform Creation Tutorials

- See Vitis™ Development Environment on amd.com -
- -# Iteration Guidelines - -When using Vitis flow to create platform and develop acceleration applications, iteration could be divided into three cases: hardware updates, software update and application. Iteration steps should obey from the following steps. - -1. Hardware updates - - - Re-export the **XSA** file if you update the Hardware design in [Step1](step1.md) - - Update the Hardware specification in [Step2](step2.md). Right click the platform and select **Update Hardware Specification**, then choose the updated **XSA** file and rebuild the platform. - - Clean the Application and rebuild the Application in [Step3](step3.md) - -2. Software component updates - - - Copy the software component to boot or sd_dir directory if you update the boot components in [step2](step2.md). Then clean the platform and rebuild the platform. For example, if DTB is updated, please copy new DTB to boot directory. Then clean the platform and rebuild it again. You would get updated platform. - - Clean the Application and rebuild the Application in [Step3](step3.md) - -3. Application updates - - - If user update the host code, they just need to clean the host first and then rebuild the host. After copying the host ELF to the fat partition of the sd card. - - If user update the Kernel code, they just need to clean the kernel and hardware link first and then rebuild the kernel and hardware link. After coping the XCLBIN file to the fat partition of the sd card. - -When using Vitis export to Vivado flow to develop acceleration application, please follow [Vitis Export to Vivdao](../../Feature_Tutorials/03_Vitis_Export_To_Vivado/README.md) to do iteration. - - -

Copyright © 2020–2025 Advanced Micro Devices, Inc.

- -

Terms and Conditions

diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/README.md b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/README.md deleted file mode 100644 index 0487c5d911..0000000000 --- a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/README.md +++ /dev/null @@ -1,90 +0,0 @@ - - - - -
- - - AMD logo - -

AMD Vitis™ Platform Creation Tutorials

- See Vitis™ Development Environment on amd.com -
- -# Vitis Custom Embedded Platform Creation Example on KV260 - -***Version: Vitis 2025.1*** - -The [AMD Kria™ KV260 Vision AI Starter Kit](https://www.xilinx.com/products/som/kria/kv260-vision-starter-kit.html) is the development platform for Kria K26 SOM. The KV260 is built for advanced vision application development without requiring complex hardware design knowledge. It is based on the AMD UltraScale+™ MPSoC technology similar to ZCU104 evaluation board. In this example, you will extend the [ZCU104 custom embedded platform creation example](../02-Edge-AI-ZCU104/README.md) to KV260 Vision AI Starter Kit. - -To highlight the differences between KV260 and ZCU104, this example will simplify the descriptions of general steps that are shared between all MPSoC platforms, but add more KV260 specific contents. If you have question in some steps, cross reference [ZCU104 custom embedded platform creation example](../02-Edge-AI-ZCU104/README.md), or ask questions in Github Issues page. - -For your reference, The structure of this example system is shown in the following figure.. - -![missing image](./images/structure.svg) - -## Custom Platform Planning - -The platform you create should be able to run these applications: - -- Vitis acceleration examples like Vector Addition. - -The hardware design of the platform would provide basic support for Vitis acceleration. It is similar to the ZCU104 example. - -In regards of software setup, you will use the common image because it can expedite the process of platform creation. - -## Kria SOM Architecture and Vitis Acceleration Considerations - -Kria SOM has some ease-of-use designs for application developers. It provides software-like development experience on FPGA and SoC, such as real time reloading applications without rebooting the system. In order to allow updating PL design without rebooting Linux, it boots Linux from Arm® Cortex®-A53 and loads the FPGA bitstream using Linux. To ensure the board can always boot successfully and prevent the board get into brick status by accidental mistakes, the Kria SOM boot flow forces to boot Linux from QSPI mode and the boot firmware in QSPI is read-only. Linux will mount rootfs in the SD card. You can update the rootfs in the SD Card. - -Vitis platform and application development can be divided into these parts: - -1. Platform hardware creation in the AMD Vivado™ Design Suite. It exports an XSA file with clock, reset, AXI interface, and interrupt signals and properties. -2. Platform software preparation with common image or using PetaLinux tool, including Linux kernel, rootfs, device tree, and boot components. -3. Platform creation in the Vitis to combine all hardware and software components and generate XPFM description. -4. Create applications in Vitis against the platform. Vitis generates host application, xclbin and `sd_card.img`. -5. Write the `sd_card.img` to SD card or update host application and xclbin to an existing SD card. - -Because the Kria SOM Starter Kit provides an off-the-shelf boot image and has its enhanced boot sequence, Vitis platform developers and application developers can skip some steps above. Here is a summary for what needs to be done by Kria platform and acceleration application developers. - -![Missing Image](./images/kv260_tutorial_workflow.svg) - -| Procedure | Required Actions | Output | Skipped Actions | -| ---------------------- | ------------------------------------------------------------------------------------------ | ------------------------- | ------------------------------- | -| Platform Hardware | Same as step 1 | XSA | N/A | -| Platform Creation | Same as step 2; generate the device tree overlay for platform programmable logic (PL) of XSA; create Vitis platform | pl.dtbo, sysroot and XPFM | Skip adding the boot components | -| Application Creation | Same as step 3; Create application | Host App, XCLBIN | skip generating the sd_card.img | -| Transfer files and run | Use scp to copy generated files to Linux partition on SD card | | skip writing sd_card.img | - -> **NOTE:** In step 2, after extracting the common image there are a lot of output components, the only valuable output product in this case is sysroot. It is used for host application cross-compilation. Because the boot images of KV260 Starter Kit is fixed, you do not need to generate any boot components, e.g., FSBL, etc. -> -> **NOTE:** In this case, we assume you start to do this experiment after you have already had your board booted up successfully. If you do not, refer to [kv260 getting started page](https://www.xilinx.com/products/som/kria/kv260-vision-starter-kit/kv260-getting-started/getting-started.html). - -The following chapters will explain the details about these steps. - -## Step-by-Step Tutorial - -The platform creation steps are introduced in the following pages. Each page describes one major step in the platform creation process. - -- [Step 1: Create the Vivado Hardware Design and Generate XSA](./step1.md) -- [Step 2: Create the Vitis Platform](./step2.md) -- [Step 3: Test the Platform](./step3.md) -- [Iteration Guidelines](./Iteration_guideline.md) - -***Start from [Step 1: Vivado Design](./step1.md).*** - -## References - -- *Vitis Unified Software Platform Documentation: Application Acceleration Development* ([UG1702](https://docs.amd.com/r/en-US/ug1701-vitis-accelerated-embedded/Developing-Vitis-Kernels-and-Applications)) - - [Platform Creation General Rules](https://docs.amd.com/access/sources/dita/topic?Doc_Version=2023.2%20English&url=ug1393-vitis-application-acceleration&resourceid=vcm1596051749044.html) - - [Setting Up the Vitis Environment](https://docs.amd.com/access/sources/dita/topic?Doc_Version=2023.2%20English&url=ug1393-vitis-application-acceleration&resourceid=zks1565446519267.html) - - [Installing Xilinx Runtime](https://docs.amd.com/access/sources/dita/topic?Doc_Version=2023.2%20English&url=ug1393-vitis-application-acceleration&resourceid=pjr1542153622642.html) -- Platform Examples - - [zcu102](https://github.com/Xilinx/Vitis_Embedded_Platform_Source/tree/2024.2/Xilinx_Official_Platforms/xilinx_zcu102_base) and [zcu104](https://github.com/Xilinx/Vitis_Embedded_Platform_Source/tree/2023.2/Xilinx_Official_Platforms/xilinx_zcu104_base) base platform source code in [Vitis Embedded Platform Source Github Repository](https://github.com/Xilinx/Vitis_Embedded_Platform_Source) -- [Xilinx Runtime (XRT)](https://xilinx.github.io/XRT/master/html/index.html) -- [Vitis-AI GitHub Repository](https://github.com/Xilinx/Vitis-AI) - - -

Copyright © 2020–2025 Advanced Micro Devices, Inc.

- -

Terms and Conditions

diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/LPD.PNG b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/LPD.PNG deleted file mode 100644 index 557aaf0939..0000000000 Binary files a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/LPD.PNG and /dev/null differ diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/address.PNG b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/address.PNG deleted file mode 100644 index dc309e0e4a..0000000000 Binary files a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/address.PNG and /dev/null differ diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/block_automation_result.png b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/block_automation_result.png deleted file mode 100644 index 4296acd1d1..0000000000 Binary files a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/block_automation_result.png and /dev/null differ diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/build_binary.PNG b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/build_binary.PNG deleted file mode 100644 index 7915e43c56..0000000000 Binary files a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/build_binary.PNG and /dev/null differ diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/build_component.PNG b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/build_component.PNG deleted file mode 100644 index f7b917e0f2..0000000000 Binary files a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/build_component.PNG and /dev/null differ diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/build_vitis_platform.png b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/build_vitis_platform.png deleted file mode 100644 index 8c33aae915..0000000000 Binary files a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/build_vitis_platform.png and /dev/null differ diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/clk_rst_connection.png b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/clk_rst_connection.png deleted file mode 100644 index e3972e6297..0000000000 Binary files a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/clk_rst_connection.png and /dev/null differ diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/clock_settings.png b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/clock_settings.png deleted file mode 100644 index ed26e58608..0000000000 Binary files a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/clock_settings.png and /dev/null differ diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/example.PNG b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/example.PNG deleted file mode 100644 index a53b8a682c..0000000000 Binary files a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/example.PNG and /dev/null differ diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/ipi_fully_connection.png b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/ipi_fully_connection.png deleted file mode 100644 index 30091fb424..0000000000 Binary files a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/ipi_fully_connection.png and /dev/null differ diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/kv260_cc.png b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/kv260_cc.png deleted file mode 100644 index 6723a42fa4..0000000000 Binary files a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/kv260_cc.png and /dev/null differ diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/kv260_tutorial_workflow.svg b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/kv260_tutorial_workflow.svg deleted file mode 100644 index f4aa64a8f4..0000000000 --- a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/kv260_tutorial_workflow.svg +++ /dev/null @@ -1 +0,0 @@ -VivadoPetalinuxVitis/XSCTSTEP1STEP2Vitisxclbinelfbinshell.jsonSTEP3Platform CreationApplication DevelopmentCommon Image createdtsXSAxpfmdtboSysrootcan be generated from Petalinuxor extracted from common image. We suggest using sysrootfrom the common image as it can expedite the process ofplatform creationsysroot \ No newline at end of file diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/platform_clock.png b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/platform_clock.png deleted file mode 100644 index 01d99a022d..0000000000 Binary files a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/platform_clock.png and /dev/null differ diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/platform_generation_dts.jpg b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/platform_generation_dts.jpg deleted file mode 100644 index bf6ec083fc..0000000000 Binary files a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/platform_generation_dts.jpg and /dev/null differ diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/platform_setup_interfaces.png b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/platform_setup_interfaces.png deleted file mode 100644 index e30c7f224c..0000000000 Binary files a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/platform_setup_interfaces.png and /dev/null differ diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/structure.svg b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/structure.svg deleted file mode 100644 index 847103bef7..0000000000 --- a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/structure.svg +++ /dev/null @@ -1 +0,0 @@ -3PLHardwareSoftwareARM Trusted FirmwareAXI interruptDPU……EthernetEMMCUARTSDUSBDPHDMIButtonLEDSWITCHGPIO DriverZOL/XRT DriverInterrupt DriverUSB DriverSD DriverI2C DriverEthernet DriverQSPI DriverDDR Driver XRTVector AdditionAPP ClockgeneratorUserKernelSTEP3STEP2STEP1ARM resourcesPL resourcesData & control stream KV260DDR4DPU is kernel added and linked by V++ in step3. Bottom left below the application is the platform created in step1 and step2.SOM K26A53*4R5F*2QSPI \ No newline at end of file diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/vitis_linux_config.png b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/vitis_linux_config.png deleted file mode 100644 index 26a06d36e5..0000000000 Binary files a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/vitis_linux_config.png and /dev/null differ diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/vitis_platform_output.png b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/vitis_platform_output.png deleted file mode 100644 index 61d6dbf7d7..0000000000 Binary files a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/vitis_platform_output.png and /dev/null differ diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/vivado_project_type.png b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/vivado_project_type.png deleted file mode 100644 index 33c7b5eab1..0000000000 Binary files a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/images/vivado_project_type.png and /dev/null differ diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/Makefile b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/Makefile deleted file mode 100644 index 427c1de959..0000000000 --- a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/Makefile +++ /dev/null @@ -1,44 +0,0 @@ -#/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -#SPDX-License-Identifier: MIT -#*/ - -VERSION ?=2025.1 -COMMON_IMAGE_ZYNQMP ?=${PLATFORM_REPO_PATHS}/sw/zynqmp/xilinx-zynqmp-common-v$(VERSION)/ - -.PHONY: help - -help: - @echo "Makefile usage" - @echo "make all COMMON_IMAGE_ZYNQMP= ## Generate platform with pre-built software components and compile the vadd application to test this platform " - - -all: check-common-image step1 step2 step3 - -#target : check whether the common image is ready -check-common-image: -ifeq ($(wildcard $(COMMON_IMAGE_ZYNQMP)/Image),) - @echo "'COMMON_IMAGE_ZYNQMP' is not accessible, please download common image from Xilinx Downloads website and set this flag to specify the common image path." - @make help - @echo "exit ....." && exit 1 -endif - -all: step1 step2 step3 -build_platform: step1 step2 -step1: - $(MAKE) -C step1_vivado all - -step2: - $(MAKE) -C step2_pfm all - -step3: - $(MAKE) -C step3_validate all - - -clean: - $(MAKE) -C step1_vivado clean - $(MAKE) -C step2_pfm clean - $(MAKE) -C step3_validate clean -ultraclean:clean - $(MAKE) -C step2_pfm ultraclean - $(MAKE) -C step3_validate ultraclean diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/description.json b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/description.json deleted file mode 100644 index ea0c6e9ce0..0000000000 --- a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/description.json +++ /dev/null @@ -1,36 +0,0 @@ - -{ - "name": "Vitis_Platform_Creation-Design_Tutorials-01-Edge-KV260", - "description": "Creating a custom kv260 platform from scratch", - "gui": "false", - "flow": "vitis", - "platform_allowlist": ["zcu"], - "platform_blocklist": [], - "testinfo": { - "test_name": "PFM_D_01-KV260", - "disable": "true", - "tasks": { - "build": { - "pre_exec": "./env_setup_zynqmp_notoolchain.sh" - }, - "board": { - "pre_exec": "./env_setup_zynqmp_notoolchain.sh" - } - }, - "jobs": [ - { - "max_memory_MB": 32768, - "max_time_min": { - "vitis_hw_emu": 200 - } - } - ], - "targets": [ - "vitis_hw_build" - ], - "custom_build_target": - { - "all": "build_platform" - } - } -} diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step1_vivado/Makefile b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step1_vivado/Makefile deleted file mode 100644 index 9416191b91..0000000000 --- a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step1_vivado/Makefile +++ /dev/null @@ -1,26 +0,0 @@ -#/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -#SPDX-License-Identifier: MIT -#*/ - -ROOT_DIR=$(realpath $(dir $(lastword $(MAKEFILE_LIST)))) -ABS_BUILD_PATH=$(ROOT_DIR)/build -ABS_HW_PATH=$(ABS_BUILD_PATH)/vivado -BD_TCL=system_step1.tcl -ABS_BD_TCL=$(ROOT_DIR)/$(BD_TCL) - -.PHONY: help - -help: - @echo "Makefile usage" - @echo "make all ## Generate hw platform and export XSA file" - -all: hw - -hw: - mkdir -p $(ABS_HW_PATH) - cd $(ABS_HW_PATH); vivado -mode batch -notrace -source $(ABS_BD_TCL) -source ../../export_xsa.tcl - - -clean: - $(RM) -r $(ABS_BUILD_PATH) vivado*.log vivado*.jou diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step1_vivado/export_xsa.tcl b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step1_vivado/export_xsa.tcl deleted file mode 100644 index 18f207f923..0000000000 --- a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step1_vivado/export_xsa.tcl +++ /dev/null @@ -1,62 +0,0 @@ -#/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -#SPDX-License-Identifier: MIT -#*/ - -proc numberOfCPUs {} { - # Windows puts it in an environment variable - global tcl_platform env - if {$tcl_platform(platform) eq "windows"} { - return $env(NUMBER_OF_PROCESSORS) - } - - # Check for sysctl (OSX, BSD) - set sysctl [auto_execok "sysctl"] - if {[llength $sysctl]} { - if {![catch {exec {*}$sysctl -n "hw.ncpu"} cores]} { - return $cores - } - } - - # Assume Linux, which has /proc/cpuinfo, but be careful - if {![catch {open "/proc/cpuinfo"} f]} { - set cores [regexp -all -line {^processor\s} [read $f]] - close $f - if {$cores > 0} { - return $cores - } - } - - # No idea what the actual number of cores is; exhausted all our options - # Fall back to returning 1; there must be at least that because we're running on it! - return 1 -} - -add_files -norecurse [make_wrapper -files [get_files -norecurse *.bd] -top] -update_compile_order -fileset sources_1 - -# For Emulation Support -set_property SELECTED_SIM_MODEL tlm [get_bd_cells /zynq_ultra_ps_e_0] - - -# Setup Platform Properties -set_property pfm_name {xilinx:kv260:kv260_hardware_Platform:0.0} [get_files -norecurse *.bd] -set_property platform.default_output_type "sd_card" [current_project] -set_property platform.design_intent.embedded "true" [current_project] -set_property platform.design_intent.server_managed "false" [current_project] -set_property platform.design_intent.external_host "false" [current_project] -set_property platform.design_intent.datacenter "false" [current_project] - -# Generate Block Design -generate_target all [get_files [current_bd_design].bd] - - -# Write expandable XSA to vivado directory -# update_compile_order -fileset sources_1 -# launch_runs impl_1 -to_step write_bitstream -jobs [numberOfCPUs] -# wait_on_run impl_1 -# open_run impl_1 -# write_hw_platform -include_bit -force -file ./kv260_hardware_platform.xsa -write_hw_platform -force -file ./kv260_hardware_platform.xsa - - diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step1_vivado/system_step1.tcl b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step1_vivado/system_step1.tcl deleted file mode 100644 index 8c9d6f229a..0000000000 --- a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step1_vivado/system_step1.tcl +++ /dev/null @@ -1,1314 +0,0 @@ -#/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -#SPDX-License-Identifier: MIT -#*/ - -################################################################ -# This is a generated script based on design: system -# -# Though there are limitations about the generated script, -# the main purpose of this utility is to make learning -# IP Integrator Tcl commands easier. -################################################################ - -namespace eval _tcl { -proc get_script_folder {} { - set script_path [file normalize [info script]] - set script_folder [file dirname $script_path] - return $script_folder -} -} -variable script_folder -set script_folder [_tcl::get_script_folder] - -################################################################ -# START -################################################################ - -# To test this script, run the following commands from Vivado Tcl console: -# source system_script.tcl - -# If there is no project opened, this script will create a -# project, but make sure you do not have an existing project -# <./myproj/project_1.xpr> in the current working folder. - -set list_projs [get_projects -quiet] -if { $list_projs eq "" } { - create_project project_1 myproj -part xck26-sfvc784-2LV-c - set_property board_part xilinx.com:kv260_som:part0:1.4 [current_project] -} - - -# CHANGE DESIGN NAME HERE -variable design_name -set design_name system - -# If you do not already have an existing IP Integrator design open, -# you can create a design using the following command: -# create_bd_design $design_name - -# Creating design if needed -set errMsg "" -set nRet 0 - -set cur_design [current_bd_design -quiet] -set list_cells [get_bd_cells -quiet] - -if { ${design_name} eq "" } { - # USE CASES: - # 1) Design_name not set - - set errMsg "Please set the variable to a non-empty value." - set nRet 1 - -} elseif { ${cur_design} ne "" && ${list_cells} eq "" } { - # USE CASES: - # 2): Current design opened AND is empty AND names same. - # 3): Current design opened AND is empty AND names diff; design_name NOT in project. - # 4): Current design opened AND is empty AND names diff; design_name exists in project. - - if { $cur_design ne $design_name } { - common::send_gid_msg -ssname BD::TCL -id 2001 -severity "INFO" "Changing value of from <$design_name> to <$cur_design> since current design is empty." - set design_name [get_property NAME $cur_design] - } - common::send_gid_msg -ssname BD::TCL -id 2002 -severity "INFO" "Constructing design in IPI design <$cur_design>..." - -} elseif { ${cur_design} ne "" && $list_cells ne "" && $cur_design eq $design_name } { - # USE CASES: - # 5) Current design opened AND has components AND same names. - - set errMsg "Design <$design_name> already exists in your project, please set the variable to another value." - set nRet 1 -} elseif { [get_files -quiet ${design_name}.bd] ne "" } { - # USE CASES: - # 6) Current opened design, has components, but diff names, design_name exists in project. - # 7) No opened design, design_name exists in project. - - set errMsg "Design <$design_name> already exists in your project, please set the variable to another value." - set nRet 2 - -} else { - # USE CASES: - # 8) No opened design, design_name not in project. - # 9) Current opened design, has components, but diff names, design_name not in project. - - common::send_gid_msg -ssname BD::TCL -id 2003 -severity "INFO" "Currently there is no design <$design_name> in project, so creating one..." - - create_bd_design $design_name - - common::send_gid_msg -ssname BD::TCL -id 2004 -severity "INFO" "Making design <$design_name> as current_bd_design." - current_bd_design $design_name - -} - -common::send_gid_msg -ssname BD::TCL -id 2005 -severity "INFO" "Currently the variable is equal to \"$design_name\"." - -if { $nRet != 0 } { - catch {common::send_gid_msg -ssname BD::TCL -id 2006 -severity "ERROR" $errMsg} - return $nRet -} - -set bCheckIPsPassed 1 -################################################################## -# CHECK IPs -################################################################## -set bCheckIPs 1 -if { $bCheckIPs == 1 } { - set list_check_ips "\ -xilinx.com:ip:zynq_ultra_ps_e:3.5\ -xilinx.com:ip:clk_wiz:6.0\ -xilinx.com:ip:proc_sys_reset:5.0\ -xilinx.com:ip:axi_intc:4.1\ -" - - set list_ips_missing "" - common::send_gid_msg -ssname BD::TCL -id 2011 -severity "INFO" "Checking if the following IPs exist in the project's IP catalog: $list_check_ips ." - - foreach ip_vlnv $list_check_ips { - set ip_obj [get_ipdefs -all $ip_vlnv] - if { $ip_obj eq "" } { - lappend list_ips_missing $ip_vlnv - } - } - - if { $list_ips_missing ne "" } { - catch {common::send_gid_msg -ssname BD::TCL -id 2012 -severity "ERROR" "The following IPs are not found in the IP Catalog:\n $list_ips_missing\n\nResolution: Please add the repository containing the IP(s) to the project." } - set bCheckIPsPassed 0 - } - -} - -if { $bCheckIPsPassed != 1 } { - common::send_gid_msg -ssname BD::TCL -id 2023 -severity "WARNING" "Will not continue with creation of design due to the error(s) above." - return 3 -} - -################################################################## -# DESIGN PROCs -################################################################## - - - -# Procedure to create entire design; Provide argument to make -# procedure reusable. If parentCell is "", will use root. -proc create_root_design { parentCell } { - - variable script_folder - variable design_name - - if { $parentCell eq "" } { - set parentCell [get_bd_cells /] - } - - # Get object for parentCell - set parentObj [get_bd_cells $parentCell] - if { $parentObj == "" } { - catch {common::send_gid_msg -ssname BD::TCL -id 2090 -severity "ERROR" "Unable to find parent cell <$parentCell>!"} - return - } - - # Make sure parentObj is hier blk - set parentType [get_property TYPE $parentObj] - if { $parentType ne "hier" } { - catch {common::send_gid_msg -ssname BD::TCL -id 2091 -severity "ERROR" "Parent <$parentObj> has TYPE = <$parentType>. Expected to be ."} - return - } - - # Save current instance; Restore later - set oldCurInst [current_bd_instance .] - - # Set parent object as current - current_bd_instance $parentObj - - - # Create interface ports - - # Create ports - - # Create instance: zynq_ultra_ps_e_0, and set properties - set zynq_ultra_ps_e_0 [ create_bd_cell -type ip -vlnv xilinx.com:ip:zynq_ultra_ps_e:3.5 zynq_ultra_ps_e_0 ] - set_property -dict [list \ - CONFIG.CAN0_BOARD_INTERFACE {custom} \ - CONFIG.CAN1_BOARD_INTERFACE {custom} \ - CONFIG.CSU_BOARD_INTERFACE {custom} \ - CONFIG.DP_BOARD_INTERFACE {custom} \ - CONFIG.GEM0_BOARD_INTERFACE {custom} \ - CONFIG.GEM1_BOARD_INTERFACE {custom} \ - CONFIG.GEM2_BOARD_INTERFACE {custom} \ - CONFIG.GEM3_BOARD_INTERFACE {custom} \ - CONFIG.GPIO_BOARD_INTERFACE {custom} \ - CONFIG.IIC0_BOARD_INTERFACE {custom} \ - CONFIG.IIC1_BOARD_INTERFACE {custom} \ - CONFIG.NAND_BOARD_INTERFACE {custom} \ - CONFIG.PCIE_BOARD_INTERFACE {custom} \ - CONFIG.PJTAG_BOARD_INTERFACE {custom} \ - CONFIG.PMU_BOARD_INTERFACE {custom} \ - CONFIG.PSU_BANK_0_IO_STANDARD {LVCMOS18} \ - CONFIG.PSU_BANK_1_IO_STANDARD {LVCMOS18} \ - CONFIG.PSU_BANK_2_IO_STANDARD {LVCMOS18} \ - CONFIG.PSU_BANK_3_IO_STANDARD {LVCMOS18} \ - CONFIG.PSU_DDR_RAM_HIGHADDR {0xFFFFFFFF} \ - CONFIG.PSU_DDR_RAM_HIGHADDR_OFFSET {0x800000000} \ - CONFIG.PSU_DDR_RAM_LOWADDR_OFFSET {0x80000000} \ - CONFIG.PSU_IMPORT_BOARD_PRESET {} \ - CONFIG.PSU_MIO_0_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_0_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_0_SLEW {slow} \ - CONFIG.PSU_MIO_10_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_10_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_10_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_10_SLEW {slow} \ - CONFIG.PSU_MIO_11_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_11_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_11_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_11_SLEW {slow} \ - CONFIG.PSU_MIO_12_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_12_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_12_POLARITY {Default} \ - CONFIG.PSU_MIO_12_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_12_SLEW {slow} \ - CONFIG.PSU_MIO_13_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_13_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_13_POLARITY {Default} \ - CONFIG.PSU_MIO_13_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_13_SLEW {slow} \ - CONFIG.PSU_MIO_14_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_14_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_14_POLARITY {Default} \ - CONFIG.PSU_MIO_14_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_14_SLEW {slow} \ - CONFIG.PSU_MIO_15_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_15_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_15_POLARITY {Default} \ - CONFIG.PSU_MIO_15_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_15_SLEW {slow} \ - CONFIG.PSU_MIO_16_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_16_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_16_POLARITY {Default} \ - CONFIG.PSU_MIO_16_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_16_SLEW {slow} \ - CONFIG.PSU_MIO_17_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_17_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_17_POLARITY {Default} \ - CONFIG.PSU_MIO_17_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_17_SLEW {slow} \ - CONFIG.PSU_MIO_18_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_18_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_18_POLARITY {Default} \ - CONFIG.PSU_MIO_18_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_18_SLEW {slow} \ - CONFIG.PSU_MIO_19_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_19_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_19_POLARITY {Default} \ - CONFIG.PSU_MIO_19_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_19_SLEW {slow} \ - CONFIG.PSU_MIO_1_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_1_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_1_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_1_SLEW {slow} \ - CONFIG.PSU_MIO_20_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_20_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_20_POLARITY {Default} \ - CONFIG.PSU_MIO_20_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_20_SLEW {slow} \ - CONFIG.PSU_MIO_21_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_21_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_21_POLARITY {Default} \ - CONFIG.PSU_MIO_21_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_21_SLEW {slow} \ - CONFIG.PSU_MIO_22_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_22_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_22_POLARITY {Default} \ - CONFIG.PSU_MIO_22_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_22_SLEW {slow} \ - CONFIG.PSU_MIO_23_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_23_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_23_POLARITY {Default} \ - CONFIG.PSU_MIO_23_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_23_SLEW {slow} \ - CONFIG.PSU_MIO_24_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_24_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_24_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_24_SLEW {slow} \ - CONFIG.PSU_MIO_25_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_25_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_25_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_25_SLEW {slow} \ - CONFIG.PSU_MIO_26_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_26_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_27_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_27_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_27_SLEW {slow} \ - CONFIG.PSU_MIO_28_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_28_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_29_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_29_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_29_SLEW {slow} \ - CONFIG.PSU_MIO_2_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_2_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_2_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_2_SLEW {slow} \ - CONFIG.PSU_MIO_30_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_30_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_31_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_31_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_32_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_32_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_32_POLARITY {Default} \ - CONFIG.PSU_MIO_32_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_32_SLEW {slow} \ - CONFIG.PSU_MIO_33_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_33_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_33_POLARITY {Default} \ - CONFIG.PSU_MIO_33_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_33_SLEW {slow} \ - CONFIG.PSU_MIO_34_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_34_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_34_POLARITY {Default} \ - CONFIG.PSU_MIO_34_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_34_SLEW {slow} \ - CONFIG.PSU_MIO_35_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_35_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_35_SLEW {slow} \ - CONFIG.PSU_MIO_36_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_36_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_36_SLEW {slow} \ - CONFIG.PSU_MIO_37_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_37_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_38_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_38_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_38_POLARITY {Default} \ - CONFIG.PSU_MIO_38_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_38_SLEW {slow} \ - CONFIG.PSU_MIO_39_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_39_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_39_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_39_SLEW {slow} \ - CONFIG.PSU_MIO_3_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_3_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_3_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_3_SLEW {slow} \ - CONFIG.PSU_MIO_40_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_40_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_40_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_40_SLEW {slow} \ - CONFIG.PSU_MIO_41_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_41_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_41_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_41_SLEW {slow} \ - CONFIG.PSU_MIO_42_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_42_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_42_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_42_SLEW {slow} \ - CONFIG.PSU_MIO_43_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_43_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_43_SLEW {slow} \ - CONFIG.PSU_MIO_44_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_44_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_44_POLARITY {Default} \ - CONFIG.PSU_MIO_44_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_44_SLEW {slow} \ - CONFIG.PSU_MIO_45_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_45_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_46_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_46_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_46_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_46_SLEW {slow} \ - CONFIG.PSU_MIO_47_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_47_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_47_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_47_SLEW {slow} \ - CONFIG.PSU_MIO_48_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_48_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_48_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_48_SLEW {slow} \ - CONFIG.PSU_MIO_49_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_49_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_49_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_49_SLEW {slow} \ - CONFIG.PSU_MIO_4_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_4_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_4_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_4_SLEW {slow} \ - CONFIG.PSU_MIO_50_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_50_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_50_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_50_SLEW {slow} \ - CONFIG.PSU_MIO_51_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_51_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_51_SLEW {slow} \ - CONFIG.PSU_MIO_52_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_52_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_53_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_53_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_54_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_54_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_54_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_54_SLEW {slow} \ - CONFIG.PSU_MIO_55_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_55_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_56_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_56_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_56_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_56_SLEW {slow} \ - CONFIG.PSU_MIO_57_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_57_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_57_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_57_SLEW {slow} \ - CONFIG.PSU_MIO_58_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_58_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_58_SLEW {slow} \ - CONFIG.PSU_MIO_59_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_59_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_59_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_59_SLEW {slow} \ - CONFIG.PSU_MIO_5_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_5_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_5_SLEW {slow} \ - CONFIG.PSU_MIO_60_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_60_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_60_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_60_SLEW {slow} \ - CONFIG.PSU_MIO_61_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_61_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_61_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_61_SLEW {slow} \ - CONFIG.PSU_MIO_62_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_62_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_62_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_62_SLEW {slow} \ - CONFIG.PSU_MIO_63_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_63_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_63_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_63_SLEW {slow} \ - CONFIG.PSU_MIO_64_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_64_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_64_SLEW {slow} \ - CONFIG.PSU_MIO_65_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_65_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_65_SLEW {slow} \ - CONFIG.PSU_MIO_66_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_66_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_66_SLEW {slow} \ - CONFIG.PSU_MIO_67_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_67_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_67_SLEW {slow} \ - CONFIG.PSU_MIO_68_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_68_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_68_SLEW {slow} \ - CONFIG.PSU_MIO_69_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_69_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_69_SLEW {slow} \ - CONFIG.PSU_MIO_6_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_6_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_6_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_6_SLEW {slow} \ - CONFIG.PSU_MIO_70_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_70_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_71_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_71_PULLUPDOWN {disable} \ - CONFIG.PSU_MIO_72_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_72_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_73_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_73_PULLUPDOWN {disable} \ - CONFIG.PSU_MIO_74_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_74_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_75_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_75_PULLUPDOWN {disable} \ - CONFIG.PSU_MIO_76_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_76_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_76_SLEW {slow} \ - CONFIG.PSU_MIO_77_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_77_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_77_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_77_SLEW {slow} \ - CONFIG.PSU_MIO_7_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_7_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_7_POLARITY {Default} \ - CONFIG.PSU_MIO_7_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_7_SLEW {slow} \ - CONFIG.PSU_MIO_8_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_8_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_8_POLARITY {Default} \ - CONFIG.PSU_MIO_8_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_8_SLEW {slow} \ - CONFIG.PSU_MIO_9_DRIVE_STRENGTH {4} \ - CONFIG.PSU_MIO_9_INPUT_TYPE {cmos} \ - CONFIG.PSU_MIO_9_PULLUPDOWN {pullup} \ - CONFIG.PSU_MIO_9_SLEW {slow} \ - CONFIG.PSU_MIO_TREE_PERIPHERALS {Quad SPI Flash#Quad SPI Flash#Quad SPI Flash#Quad SPI Flash#Quad SPI Flash#Quad SPI Flash#SPI 1#GPIO0 MIO#GPIO0 MIO#SPI 1#SPI 1#SPI 1#GPIO0 MIO#GPIO0 MIO#GPIO0 MIO#GPIO0\ -MIO#GPIO0 MIO#GPIO0 MIO#GPIO0 MIO#GPIO0 MIO#GPIO0 MIO#GPIO0 MIO#GPIO0 MIO#GPIO0 MIO#I2C 1#I2C 1#PMU GPI 0#DPAUX#DPAUX#DPAUX#DPAUX#PMU GPI 5#GPIO1 MIO#GPIO1 MIO#GPIO1 MIO#PMU GPO 3#UART 1#UART 1#GPIO1 MIO#SD\ -1#SD 1#SD 1#SD 1#SD 1#GPIO1 MIO#SD 1#SD 1#SD 1#SD 1#SD 1#SD 1#SD 1#USB 0#USB 0#USB 0#USB 0#USB 0#USB 0#USB 0#USB 0#USB 0#USB 0#USB 0#USB 0#Gem 3#Gem 3#Gem 3#Gem 3#Gem 3#Gem 3#Gem 3#Gem 3#Gem 3#Gem 3#Gem\ -3#Gem 3#MDIO 3#MDIO 3} \ - CONFIG.PSU_MIO_TREE_SIGNALS {sclk_out#miso_mo1#mo2#mo3#mosi_mi0#n_ss_out#sclk_out#gpio0[7]#gpio0[8]#n_ss_out[0]#miso#mosi#gpio0[12]#gpio0[13]#gpio0[14]#gpio0[15]#gpio0[16]#gpio0[17]#gpio0[18]#gpio0[19]#gpio0[20]#gpio0[21]#gpio0[22]#gpio0[23]#scl_out#sda_out#gpi[0]#dp_aux_data_out#dp_hot_plug_detect#dp_aux_data_oe#dp_aux_data_in#gpi[5]#gpio1[32]#gpio1[33]#gpio1[34]#gpo[3]#txd#rxd#gpio1[38]#sdio1_data_out[4]#sdio1_data_out[5]#sdio1_data_out[6]#sdio1_data_out[7]#sdio1_bus_pow#gpio1[44]#sdio1_cd_n#sdio1_data_out[0]#sdio1_data_out[1]#sdio1_data_out[2]#sdio1_data_out[3]#sdio1_cmd_out#sdio1_clk_out#ulpi_clk_in#ulpi_dir#ulpi_tx_data[2]#ulpi_nxt#ulpi_tx_data[0]#ulpi_tx_data[1]#ulpi_stp#ulpi_tx_data[3]#ulpi_tx_data[4]#ulpi_tx_data[5]#ulpi_tx_data[6]#ulpi_tx_data[7]#rgmii_tx_clk#rgmii_txd[0]#rgmii_txd[1]#rgmii_txd[2]#rgmii_txd[3]#rgmii_tx_ctl#rgmii_rx_clk#rgmii_rxd[0]#rgmii_rxd[1]#rgmii_rxd[2]#rgmii_rxd[3]#rgmii_rx_ctl#gem3_mdc#gem3_mdio_out}\ -\ - CONFIG.PSU_PERIPHERAL_BOARD_PRESET {} \ - CONFIG.PSU_SD0_INTERNAL_BUS_WIDTH {8} \ - CONFIG.PSU_SD1_INTERNAL_BUS_WIDTH {8} \ - CONFIG.PSU_SMC_CYCLE_T0 {NA} \ - CONFIG.PSU_SMC_CYCLE_T1 {NA} \ - CONFIG.PSU_SMC_CYCLE_T2 {NA} \ - CONFIG.PSU_SMC_CYCLE_T3 {NA} \ - CONFIG.PSU_SMC_CYCLE_T4 {NA} \ - CONFIG.PSU_SMC_CYCLE_T5 {NA} \ - CONFIG.PSU_SMC_CYCLE_T6 {NA} \ - CONFIG.PSU_USB3__DUAL_CLOCK_ENABLE {1} \ - CONFIG.PSU_VALUE_SILVERSION {3} \ - CONFIG.PSU__ACPU0__POWER__ON {1} \ - CONFIG.PSU__ACPU1__POWER__ON {1} \ - CONFIG.PSU__ACPU2__POWER__ON {1} \ - CONFIG.PSU__ACPU3__POWER__ON {1} \ - CONFIG.PSU__ACTUAL__IP {1} \ - CONFIG.PSU__ACT_DDR_FREQ_MHZ {1066.656006} \ - CONFIG.PSU__AUX_REF_CLK__FREQMHZ {33.333} \ - CONFIG.PSU__CAN0_LOOP_CAN1__ENABLE {0} \ - CONFIG.PSU__CAN0__PERIPHERAL__ENABLE {0} \ - CONFIG.PSU__CAN1__PERIPHERAL__ENABLE {0} \ - CONFIG.PSU__CRF_APB__ACPU_CTRL__ACT_FREQMHZ {1333.333008} \ - CONFIG.PSU__CRF_APB__ACPU_CTRL__FREQMHZ {1333.333} \ - CONFIG.PSU__CRF_APB__ACPU_CTRL__SRCSEL {APLL} \ - CONFIG.PSU__CRF_APB__ACPU__FRAC_ENABLED {1} \ - CONFIG.PSU__CRF_APB__AFI0_REF_CTRL__ACT_FREQMHZ {667} \ - CONFIG.PSU__CRF_APB__AFI0_REF_CTRL__DIVISOR0 {2} \ - CONFIG.PSU__CRF_APB__AFI0_REF_CTRL__FREQMHZ {667} \ - CONFIG.PSU__CRF_APB__AFI0_REF_CTRL__SRCSEL {DPLL} \ - CONFIG.PSU__CRF_APB__AFI0_REF__ENABLE {0} \ - CONFIG.PSU__CRF_APB__AFI1_REF_CTRL__ACT_FREQMHZ {667} \ - CONFIG.PSU__CRF_APB__AFI1_REF_CTRL__DIVISOR0 {2} \ - CONFIG.PSU__CRF_APB__AFI1_REF_CTRL__FREQMHZ {667} \ - CONFIG.PSU__CRF_APB__AFI1_REF_CTRL__SRCSEL {DPLL} \ - CONFIG.PSU__CRF_APB__AFI1_REF__ENABLE {0} \ - CONFIG.PSU__CRF_APB__AFI2_REF_CTRL__ACT_FREQMHZ {667} \ - CONFIG.PSU__CRF_APB__AFI2_REF_CTRL__DIVISOR0 {2} \ - CONFIG.PSU__CRF_APB__AFI2_REF_CTRL__FREQMHZ {667} \ - CONFIG.PSU__CRF_APB__AFI2_REF_CTRL__SRCSEL {DPLL} \ - CONFIG.PSU__CRF_APB__AFI2_REF__ENABLE {0} \ - CONFIG.PSU__CRF_APB__AFI3_REF_CTRL__ACT_FREQMHZ {667} \ - CONFIG.PSU__CRF_APB__AFI3_REF_CTRL__DIVISOR0 {2} \ - CONFIG.PSU__CRF_APB__AFI3_REF_CTRL__FREQMHZ {667} \ - CONFIG.PSU__CRF_APB__AFI3_REF_CTRL__SRCSEL {DPLL} \ - CONFIG.PSU__CRF_APB__AFI3_REF__ENABLE {0} \ - CONFIG.PSU__CRF_APB__AFI4_REF_CTRL__ACT_FREQMHZ {667} \ - CONFIG.PSU__CRF_APB__AFI4_REF_CTRL__DIVISOR0 {2} \ - CONFIG.PSU__CRF_APB__AFI4_REF_CTRL__FREQMHZ {667} \ - CONFIG.PSU__CRF_APB__AFI4_REF_CTRL__SRCSEL {DPLL} \ - CONFIG.PSU__CRF_APB__AFI4_REF__ENABLE {0} \ - CONFIG.PSU__CRF_APB__AFI5_REF_CTRL__ACT_FREQMHZ {667} \ - CONFIG.PSU__CRF_APB__AFI5_REF_CTRL__DIVISOR0 {2} \ - CONFIG.PSU__CRF_APB__AFI5_REF_CTRL__FREQMHZ {667} \ - CONFIG.PSU__CRF_APB__AFI5_REF_CTRL__SRCSEL {DPLL} \ - CONFIG.PSU__CRF_APB__AFI5_REF__ENABLE {0} \ - CONFIG.PSU__CRF_APB__APLL_CTRL__FRACFREQ {1333.333} \ - CONFIG.PSU__CRF_APB__APLL_CTRL__SRCSEL {PSS_REF_CLK} \ - CONFIG.PSU__CRF_APB__APLL_FRAC_CFG__ENABLED {1} \ - CONFIG.PSU__CRF_APB__APM_CTRL__ACT_FREQMHZ {1} \ - CONFIG.PSU__CRF_APB__APM_CTRL__DIVISOR0 {1} \ - CONFIG.PSU__CRF_APB__APM_CTRL__FREQMHZ {1} \ - CONFIG.PSU__CRF_APB__DBG_FPD_CTRL__ACT_FREQMHZ {249.997498} \ - CONFIG.PSU__CRF_APB__DBG_FPD_CTRL__FREQMHZ {250} \ - CONFIG.PSU__CRF_APB__DBG_FPD_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRF_APB__DBG_TRACE_CTRL__ACT_FREQMHZ {250} \ - CONFIG.PSU__CRF_APB__DBG_TRACE_CTRL__FREQMHZ {250} \ - CONFIG.PSU__CRF_APB__DBG_TRACE_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRF_APB__DBG_TSTMP_CTRL__ACT_FREQMHZ {249.997498} \ - CONFIG.PSU__CRF_APB__DBG_TSTMP_CTRL__FREQMHZ {250} \ - CONFIG.PSU__CRF_APB__DBG_TSTMP_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRF_APB__DDR_CTRL__ACT_FREQMHZ {533.328003} \ - CONFIG.PSU__CRF_APB__DDR_CTRL__FREQMHZ {1200} \ - CONFIG.PSU__CRF_APB__DDR_CTRL__SRCSEL {DPLL} \ - CONFIG.PSU__CRF_APB__DPDMA_REF_CTRL__ACT_FREQMHZ {444.444336} \ - CONFIG.PSU__CRF_APB__DPDMA_REF_CTRL__FREQMHZ {600} \ - CONFIG.PSU__CRF_APB__DPDMA_REF_CTRL__SRCSEL {APLL} \ - CONFIG.PSU__CRF_APB__DPLL_CTRL__FRACFREQ {27.138} \ - CONFIG.PSU__CRF_APB__DPLL_CTRL__SRCSEL {PSS_REF_CLK} \ - CONFIG.PSU__CRF_APB__DP_AUDIO_REF_CTRL__ACT_FREQMHZ {24.242182} \ - CONFIG.PSU__CRF_APB__DP_AUDIO_REF_CTRL__FREQMHZ {25} \ - CONFIG.PSU__CRF_APB__DP_AUDIO_REF_CTRL__SRCSEL {RPLL} \ - CONFIG.PSU__CRF_APB__DP_AUDIO__FRAC_ENABLED {0} \ - CONFIG.PSU__CRF_APB__DP_STC_REF_CTRL__ACT_FREQMHZ {26.666401} \ - CONFIG.PSU__CRF_APB__DP_STC_REF_CTRL__FREQMHZ {27} \ - CONFIG.PSU__CRF_APB__DP_STC_REF_CTRL__SRCSEL {RPLL} \ - CONFIG.PSU__CRF_APB__DP_VIDEO_REF_CTRL__ACT_FREQMHZ {299.997009} \ - CONFIG.PSU__CRF_APB__DP_VIDEO_REF_CTRL__FREQMHZ {300} \ - CONFIG.PSU__CRF_APB__DP_VIDEO_REF_CTRL__SRCSEL {VPLL} \ - CONFIG.PSU__CRF_APB__DP_VIDEO__FRAC_ENABLED {0} \ - CONFIG.PSU__CRF_APB__GDMA_REF_CTRL__ACT_FREQMHZ {533.328003} \ - CONFIG.PSU__CRF_APB__GDMA_REF_CTRL__FREQMHZ {600} \ - CONFIG.PSU__CRF_APB__GDMA_REF_CTRL__SRCSEL {DPLL} \ - CONFIG.PSU__CRF_APB__GPU_REF_CTRL__ACT_FREQMHZ {499.994995} \ - CONFIG.PSU__CRF_APB__GPU_REF_CTRL__FREQMHZ {600} \ - CONFIG.PSU__CRF_APB__GPU_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRF_APB__GTGREF0_REF_CTRL__ACT_FREQMHZ {-1} \ - CONFIG.PSU__CRF_APB__GTGREF0_REF_CTRL__DIVISOR0 {-1} \ - CONFIG.PSU__CRF_APB__GTGREF0_REF_CTRL__FREQMHZ {-1} \ - CONFIG.PSU__CRF_APB__GTGREF0_REF_CTRL__SRCSEL {NA} \ - CONFIG.PSU__CRF_APB__GTGREF0__ENABLE {NA} \ - CONFIG.PSU__CRF_APB__PCIE_REF_CTRL__ACT_FREQMHZ {250} \ - CONFIG.PSU__CRF_APB__SATA_REF_CTRL__ACT_FREQMHZ {250} \ - CONFIG.PSU__CRF_APB__TOPSW_LSBUS_CTRL__ACT_FREQMHZ {99.999001} \ - CONFIG.PSU__CRF_APB__TOPSW_LSBUS_CTRL__FREQMHZ {100} \ - CONFIG.PSU__CRF_APB__TOPSW_LSBUS_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRF_APB__TOPSW_MAIN_CTRL__ACT_FREQMHZ {533.328003} \ - CONFIG.PSU__CRF_APB__TOPSW_MAIN_CTRL__FREQMHZ {533.33} \ - CONFIG.PSU__CRF_APB__TOPSW_MAIN_CTRL__SRCSEL {DPLL} \ - CONFIG.PSU__CRF_APB__VPLL_CTRL__FRACFREQ {27.138} \ - CONFIG.PSU__CRF_APB__VPLL_CTRL__SRCSEL {PSS_REF_CLK} \ - CONFIG.PSU__CRL_APB__ADMA_REF_CTRL__ACT_FREQMHZ {499.994995} \ - CONFIG.PSU__CRL_APB__ADMA_REF_CTRL__FREQMHZ {500} \ - CONFIG.PSU__CRL_APB__ADMA_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__AFI6_REF_CTRL__ACT_FREQMHZ {500} \ - CONFIG.PSU__CRL_APB__AFI6_REF_CTRL__FREQMHZ {500} \ - CONFIG.PSU__CRL_APB__AFI6_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__AFI6__ENABLE {0} \ - CONFIG.PSU__CRL_APB__AMS_REF_CTRL__ACT_FREQMHZ {49.999500} \ - CONFIG.PSU__CRL_APB__AMS_REF_CTRL__FREQMHZ {50} \ - CONFIG.PSU__CRL_APB__AMS_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__CAN0_REF_CTRL__ACT_FREQMHZ {100} \ - CONFIG.PSU__CRL_APB__CAN0_REF_CTRL__FREQMHZ {100} \ - CONFIG.PSU__CRL_APB__CAN0_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__CAN1_REF_CTRL__ACT_FREQMHZ {100} \ - CONFIG.PSU__CRL_APB__CAN1_REF_CTRL__FREQMHZ {100} \ - CONFIG.PSU__CRL_APB__CAN1_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__CPU_R5_CTRL__ACT_FREQMHZ {533.328003} \ - CONFIG.PSU__CRL_APB__CPU_R5_CTRL__FREQMHZ {533.333} \ - CONFIG.PSU__CRL_APB__CPU_R5_CTRL__SRCSEL {RPLL} \ - CONFIG.PSU__CRL_APB__CSU_PLL_CTRL__ACT_FREQMHZ {180} \ - CONFIG.PSU__CRL_APB__CSU_PLL_CTRL__DIVISOR0 {3} \ - CONFIG.PSU__CRL_APB__CSU_PLL_CTRL__SRCSEL {SysOsc} \ - CONFIG.PSU__CRL_APB__DBG_LPD_CTRL__ACT_FREQMHZ {249.997498} \ - CONFIG.PSU__CRL_APB__DBG_LPD_CTRL__FREQMHZ {250} \ - CONFIG.PSU__CRL_APB__DBG_LPD_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__DEBUG_R5_ATCLK_CTRL__ACT_FREQMHZ {1000} \ - CONFIG.PSU__CRL_APB__DEBUG_R5_ATCLK_CTRL__DIVISOR0 {6} \ - CONFIG.PSU__CRL_APB__DEBUG_R5_ATCLK_CTRL__FREQMHZ {1000} \ - CONFIG.PSU__CRL_APB__DEBUG_R5_ATCLK_CTRL__SRCSEL {RPLL} \ - CONFIG.PSU__CRL_APB__DLL_REF_CTRL__ACT_FREQMHZ {1499.984985} \ - CONFIG.PSU__CRL_APB__DLL_REF_CTRL__FREQMHZ {1500} \ - CONFIG.PSU__CRL_APB__DLL_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__GEM0_REF_CTRL__ACT_FREQMHZ {125} \ - CONFIG.PSU__CRL_APB__GEM0_REF_CTRL__FREQMHZ {125} \ - CONFIG.PSU__CRL_APB__GEM0_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__GEM1_REF_CTRL__ACT_FREQMHZ {125} \ - CONFIG.PSU__CRL_APB__GEM1_REF_CTRL__FREQMHZ {125} \ - CONFIG.PSU__CRL_APB__GEM1_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__GEM2_REF_CTRL__ACT_FREQMHZ {125} \ - CONFIG.PSU__CRL_APB__GEM2_REF_CTRL__FREQMHZ {125} \ - CONFIG.PSU__CRL_APB__GEM2_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__GEM3_REF_CTRL__ACT_FREQMHZ {124.998749} \ - CONFIG.PSU__CRL_APB__GEM3_REF_CTRL__FREQMHZ {125} \ - CONFIG.PSU__CRL_APB__GEM3_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__GEM_TSU_REF_CTRL__ACT_FREQMHZ {249.997498} \ - CONFIG.PSU__CRL_APB__GEM_TSU_REF_CTRL__FREQMHZ {250} \ - CONFIG.PSU__CRL_APB__GEM_TSU_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__I2C0_REF_CTRL__ACT_FREQMHZ {100} \ - CONFIG.PSU__CRL_APB__I2C0_REF_CTRL__FREQMHZ {100} \ - CONFIG.PSU__CRL_APB__I2C0_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__I2C1_REF_CTRL__ACT_FREQMHZ {99.999001} \ - CONFIG.PSU__CRL_APB__I2C1_REF_CTRL__FREQMHZ {100} \ - CONFIG.PSU__CRL_APB__I2C1_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__IOPLL_CTRL__FRACFREQ {27.138} \ - CONFIG.PSU__CRL_APB__IOPLL_CTRL__SRCSEL {PSS_REF_CLK} \ - CONFIG.PSU__CRL_APB__IOU_SWITCH_CTRL__ACT_FREQMHZ {249.997498} \ - CONFIG.PSU__CRL_APB__IOU_SWITCH_CTRL__FREQMHZ {250} \ - CONFIG.PSU__CRL_APB__IOU_SWITCH_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__LPD_LSBUS_CTRL__ACT_FREQMHZ {99.999001} \ - CONFIG.PSU__CRL_APB__LPD_LSBUS_CTRL__FREQMHZ {100} \ - CONFIG.PSU__CRL_APB__LPD_LSBUS_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__LPD_SWITCH_CTRL__ACT_FREQMHZ {499.994995} \ - CONFIG.PSU__CRL_APB__LPD_SWITCH_CTRL__FREQMHZ {500} \ - CONFIG.PSU__CRL_APB__LPD_SWITCH_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__NAND_REF_CTRL__ACT_FREQMHZ {100} \ - CONFIG.PSU__CRL_APB__NAND_REF_CTRL__FREQMHZ {100} \ - CONFIG.PSU__CRL_APB__NAND_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__OCM_MAIN_CTRL__ACT_FREQMHZ {500} \ - CONFIG.PSU__CRL_APB__OCM_MAIN_CTRL__DIVISOR0 {3} \ - CONFIG.PSU__CRL_APB__OCM_MAIN_CTRL__FREQMHZ {500} \ - CONFIG.PSU__CRL_APB__OCM_MAIN_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__PCAP_CTRL__ACT_FREQMHZ {187.498123} \ - CONFIG.PSU__CRL_APB__PCAP_CTRL__FREQMHZ {200} \ - CONFIG.PSU__CRL_APB__PCAP_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__PL0_REF_CTRL__ACT_FREQMHZ {99.999001} \ - CONFIG.PSU__CRL_APB__PL0_REF_CTRL__FREQMHZ {100} \ - CONFIG.PSU__CRL_APB__PL0_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__PL1_REF_CTRL__ACT_FREQMHZ {99.999001} \ - CONFIG.PSU__CRL_APB__PL1_REF_CTRL__FREQMHZ {100} \ - CONFIG.PSU__CRL_APB__PL1_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__PL2_REF_CTRL__ACT_FREQMHZ {100} \ - CONFIG.PSU__CRL_APB__PL3_REF_CTRL__ACT_FREQMHZ {100} \ - CONFIG.PSU__CRL_APB__QSPI_REF_CTRL__ACT_FREQMHZ {124.998749} \ - CONFIG.PSU__CRL_APB__QSPI_REF_CTRL__FREQMHZ {125} \ - CONFIG.PSU__CRL_APB__QSPI_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__RPLL_CTRL__FRACFREQ {27.138} \ - CONFIG.PSU__CRL_APB__RPLL_CTRL__SRCSEL {PSS_REF_CLK} \ - CONFIG.PSU__CRL_APB__SDIO0_REF_CTRL__ACT_FREQMHZ {200} \ - CONFIG.PSU__CRL_APB__SDIO0_REF_CTRL__FREQMHZ {200} \ - CONFIG.PSU__CRL_APB__SDIO0_REF_CTRL__SRCSEL {RPLL} \ - CONFIG.PSU__CRL_APB__SDIO1_REF_CTRL__ACT_FREQMHZ {187.498123} \ - CONFIG.PSU__CRL_APB__SDIO1_REF_CTRL__FREQMHZ {200} \ - CONFIG.PSU__CRL_APB__SDIO1_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__SPI0_REF_CTRL__ACT_FREQMHZ {214} \ - CONFIG.PSU__CRL_APB__SPI0_REF_CTRL__FREQMHZ {200} \ - CONFIG.PSU__CRL_APB__SPI0_REF_CTRL__SRCSEL {RPLL} \ - CONFIG.PSU__CRL_APB__SPI1_REF_CTRL__ACT_FREQMHZ {187.498123} \ - CONFIG.PSU__CRL_APB__SPI1_REF_CTRL__FREQMHZ {200} \ - CONFIG.PSU__CRL_APB__SPI1_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__TIMESTAMP_REF_CTRL__ACT_FREQMHZ {99.999001} \ - CONFIG.PSU__CRL_APB__TIMESTAMP_REF_CTRL__FREQMHZ {100} \ - CONFIG.PSU__CRL_APB__TIMESTAMP_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__UART0_REF_CTRL__ACT_FREQMHZ {100} \ - CONFIG.PSU__CRL_APB__UART0_REF_CTRL__FREQMHZ {100} \ - CONFIG.PSU__CRL_APB__UART0_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__UART1_REF_CTRL__ACT_FREQMHZ {99.999001} \ - CONFIG.PSU__CRL_APB__UART1_REF_CTRL__FREQMHZ {100} \ - CONFIG.PSU__CRL_APB__UART1_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__USB0_BUS_REF_CTRL__ACT_FREQMHZ {249.997498} \ - CONFIG.PSU__CRL_APB__USB0_BUS_REF_CTRL__FREQMHZ {250} \ - CONFIG.PSU__CRL_APB__USB0_BUS_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__USB1_BUS_REF_CTRL__ACT_FREQMHZ {250} \ - CONFIG.PSU__CRL_APB__USB1_BUS_REF_CTRL__FREQMHZ {250} \ - CONFIG.PSU__CRL_APB__USB1_BUS_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__USB3_DUAL_REF_CTRL__ACT_FREQMHZ {19.999800} \ - CONFIG.PSU__CRL_APB__USB3_DUAL_REF_CTRL__FREQMHZ {20} \ - CONFIG.PSU__CRL_APB__USB3_DUAL_REF_CTRL__SRCSEL {IOPLL} \ - CONFIG.PSU__CRL_APB__USB3__ENABLE {1} \ - CONFIG.PSU__CSUPMU__PERIPHERAL__VALID {1} \ - CONFIG.PSU__CSU__CSU_TAMPER_0__ENABLE {0} \ - CONFIG.PSU__CSU__CSU_TAMPER_10__ENABLE {0} \ - CONFIG.PSU__CSU__CSU_TAMPER_11__ENABLE {0} \ - CONFIG.PSU__CSU__CSU_TAMPER_12__ENABLE {0} \ - CONFIG.PSU__CSU__CSU_TAMPER_1__ENABLE {0} \ - CONFIG.PSU__CSU__CSU_TAMPER_2__ENABLE {0} \ - CONFIG.PSU__CSU__CSU_TAMPER_3__ENABLE {0} \ - CONFIG.PSU__CSU__CSU_TAMPER_4__ENABLE {0} \ - CONFIG.PSU__CSU__CSU_TAMPER_5__ENABLE {0} \ - CONFIG.PSU__CSU__CSU_TAMPER_6__ENABLE {0} \ - CONFIG.PSU__CSU__CSU_TAMPER_7__ENABLE {0} \ - CONFIG.PSU__CSU__CSU_TAMPER_8__ENABLE {0} \ - CONFIG.PSU__CSU__CSU_TAMPER_9__ENABLE {0} \ - CONFIG.PSU__CSU__PERIPHERAL__ENABLE {0} \ - CONFIG.PSU__DDRC__AL {0} \ - CONFIG.PSU__DDRC__BG_ADDR_COUNT {1} \ - CONFIG.PSU__DDRC__BRC_MAPPING {ROW_BANK_COL} \ - CONFIG.PSU__DDRC__BUS_WIDTH {64 Bit} \ - CONFIG.PSU__DDRC__CL {16} \ - CONFIG.PSU__DDRC__CLOCK_STOP_EN {0} \ - CONFIG.PSU__DDRC__COMPONENTS {Components} \ - CONFIG.PSU__DDRC__CWL {14} \ - CONFIG.PSU__DDRC__DDR4_ADDR_MAPPING {0} \ - CONFIG.PSU__DDRC__DDR4_CAL_MODE_ENABLE {0} \ - CONFIG.PSU__DDRC__DDR4_CRC_CONTROL {0} \ - CONFIG.PSU__DDRC__DDR4_MAXPWR_SAVING_EN {0} \ - CONFIG.PSU__DDRC__DDR4_T_REF_MODE {0} \ - CONFIG.PSU__DDRC__DDR4_T_REF_RANGE {Normal (0-85)} \ - CONFIG.PSU__DDRC__DEVICE_CAPACITY {8192 MBits} \ - CONFIG.PSU__DDRC__DM_DBI {DM_NO_DBI} \ - CONFIG.PSU__DDRC__DRAM_WIDTH {16 Bits} \ - CONFIG.PSU__DDRC__ECC {Disabled} \ - CONFIG.PSU__DDRC__ECC_SCRUB {0} \ - CONFIG.PSU__DDRC__ENABLE {1} \ - CONFIG.PSU__DDRC__ENABLE_2T_TIMING {0} \ - CONFIG.PSU__DDRC__ENABLE_DP_SWITCH {0} \ - CONFIG.PSU__DDRC__EN_2ND_CLK {0} \ - CONFIG.PSU__DDRC__FGRM {1X} \ - CONFIG.PSU__DDRC__FREQ_MHZ {1} \ - CONFIG.PSU__DDRC__LPDDR3_DUALRANK_SDP {0} \ - CONFIG.PSU__DDRC__LP_ASR {manual normal} \ - CONFIG.PSU__DDRC__MEMORY_TYPE {DDR 4} \ - CONFIG.PSU__DDRC__PARITY_ENABLE {0} \ - CONFIG.PSU__DDRC__PER_BANK_REFRESH {0} \ - CONFIG.PSU__DDRC__PHY_DBI_MODE {0} \ - CONFIG.PSU__DDRC__PLL_BYPASS {0} \ - CONFIG.PSU__DDRC__PWR_DOWN_EN {0} \ - CONFIG.PSU__DDRC__RANK_ADDR_COUNT {0} \ - CONFIG.PSU__DDRC__RD_DQS_CENTER {0} \ - CONFIG.PSU__DDRC__ROW_ADDR_COUNT {16} \ - CONFIG.PSU__DDRC__SELF_REF_ABORT {0} \ - CONFIG.PSU__DDRC__SPEED_BIN {DDR4_2400R} \ - CONFIG.PSU__DDRC__STATIC_RD_MODE {0} \ - CONFIG.PSU__DDRC__TRAIN_DATA_EYE {1} \ - CONFIG.PSU__DDRC__TRAIN_READ_GATE {1} \ - CONFIG.PSU__DDRC__TRAIN_WRITE_LEVEL {1} \ - CONFIG.PSU__DDRC__T_FAW {30.0} \ - CONFIG.PSU__DDRC__T_RAS_MIN {33} \ - CONFIG.PSU__DDRC__T_RC {47.06} \ - CONFIG.PSU__DDRC__T_RCD {16} \ - CONFIG.PSU__DDRC__T_RP {16} \ - CONFIG.PSU__DDRC__VIDEO_BUFFER_SIZE {0} \ - CONFIG.PSU__DDRC__VREF {1} \ - CONFIG.PSU__DDR_HIGH_ADDRESS_GUI_ENABLE {1} \ - CONFIG.PSU__DDR_QOS_ENABLE {0} \ - CONFIG.PSU__DDR_QOS_HP0_RDQOS {} \ - CONFIG.PSU__DDR_QOS_HP0_WRQOS {} \ - CONFIG.PSU__DDR_QOS_HP1_RDQOS {} \ - CONFIG.PSU__DDR_QOS_HP1_WRQOS {} \ - CONFIG.PSU__DDR_QOS_HP2_RDQOS {} \ - CONFIG.PSU__DDR_QOS_HP2_WRQOS {} \ - CONFIG.PSU__DDR_QOS_HP3_RDQOS {} \ - CONFIG.PSU__DDR_QOS_HP3_WRQOS {} \ - CONFIG.PSU__DDR_SW_REFRESH_ENABLED {1} \ - CONFIG.PSU__DDR__INTERFACE__FREQMHZ {600.000} \ - CONFIG.PSU__DEVICE_TYPE {EV} \ - CONFIG.PSU__DISPLAYPORT__LANE0__ENABLE {1} \ - CONFIG.PSU__DISPLAYPORT__LANE0__IO {GT Lane1} \ - CONFIG.PSU__DISPLAYPORT__LANE1__ENABLE {1} \ - CONFIG.PSU__DISPLAYPORT__LANE1__IO {GT Lane0} \ - CONFIG.PSU__DISPLAYPORT__PERIPHERAL__ENABLE {1} \ - CONFIG.PSU__DLL__ISUSED {1} \ - CONFIG.PSU__DPAUX__PERIPHERAL__ENABLE {1} \ - CONFIG.PSU__DPAUX__PERIPHERAL__IO {MIO 27 .. 30} \ - CONFIG.PSU__DP__LANE_SEL {Dual Lower} \ - CONFIG.PSU__DP__REF_CLK_FREQ {27} \ - CONFIG.PSU__DP__REF_CLK_SEL {Ref Clk0} \ - CONFIG.PSU__ENABLE__DDR__REFRESH__SIGNALS {0} \ - CONFIG.PSU__ENET0__PERIPHERAL__ENABLE {0} \ - CONFIG.PSU__ENET1__PERIPHERAL__ENABLE {0} \ - CONFIG.PSU__ENET2__PERIPHERAL__ENABLE {0} \ - CONFIG.PSU__ENET3__FIFO__ENABLE {0} \ - CONFIG.PSU__ENET3__GRP_MDIO__ENABLE {1} \ - CONFIG.PSU__ENET3__GRP_MDIO__IO {MIO 76 .. 77} \ - CONFIG.PSU__ENET3__PERIPHERAL__ENABLE {1} \ - CONFIG.PSU__ENET3__PERIPHERAL__IO {MIO 64 .. 75} \ - CONFIG.PSU__ENET3__PTP__ENABLE {0} \ - CONFIG.PSU__ENET3__TSU__ENABLE {0} \ - CONFIG.PSU__EN_AXI_STATUS_PORTS {0} \ - CONFIG.PSU__EN_EMIO_TRACE {0} \ - CONFIG.PSU__EP__IP {0} \ - CONFIG.PSU__EXPAND__CORESIGHT {0} \ - CONFIG.PSU__EXPAND__FPD_SLAVES {0} \ - CONFIG.PSU__EXPAND__GIC {0} \ - CONFIG.PSU__EXPAND__LOWER_LPS_SLAVES {0} \ - CONFIG.PSU__EXPAND__UPPER_LPS_SLAVES {0} \ - CONFIG.PSU__FPD_SLCR__WDT1__ACT_FREQMHZ {99.999001} \ - CONFIG.PSU__FPGA_PL0_ENABLE {1} \ - CONFIG.PSU__FPGA_PL1_ENABLE {1} \ - CONFIG.PSU__FPGA_PL2_ENABLE {0} \ - CONFIG.PSU__FPGA_PL3_ENABLE {0} \ - CONFIG.PSU__FP__POWER__ON {1} \ - CONFIG.PSU__FTM__CTI_IN_0 {0} \ - CONFIG.PSU__FTM__CTI_IN_1 {0} \ - CONFIG.PSU__FTM__CTI_IN_2 {0} \ - CONFIG.PSU__FTM__CTI_IN_3 {0} \ - CONFIG.PSU__FTM__CTI_OUT_0 {0} \ - CONFIG.PSU__FTM__CTI_OUT_1 {0} \ - CONFIG.PSU__FTM__CTI_OUT_2 {0} \ - CONFIG.PSU__FTM__CTI_OUT_3 {0} \ - CONFIG.PSU__FTM__GPI {0} \ - CONFIG.PSU__FTM__GPO {0} \ - CONFIG.PSU__GEM3_COHERENCY {0} \ - CONFIG.PSU__GEM3_ROUTE_THROUGH_FPD {0} \ - CONFIG.PSU__GEM__TSU__ENABLE {0} \ - CONFIG.PSU__GEN_IPI_0__MASTER {APU} \ - CONFIG.PSU__GEN_IPI_10__MASTER {NONE} \ - CONFIG.PSU__GEN_IPI_1__MASTER {RPU0} \ - CONFIG.PSU__GEN_IPI_2__MASTER {RPU1} \ - CONFIG.PSU__GEN_IPI_3__MASTER {PMU} \ - CONFIG.PSU__GEN_IPI_4__MASTER {PMU} \ - CONFIG.PSU__GEN_IPI_5__MASTER {PMU} \ - CONFIG.PSU__GEN_IPI_6__MASTER {PMU} \ - CONFIG.PSU__GEN_IPI_7__MASTER {NONE} \ - CONFIG.PSU__GEN_IPI_8__MASTER {NONE} \ - CONFIG.PSU__GEN_IPI_9__MASTER {NONE} \ - CONFIG.PSU__GPIO0_MIO__IO {MIO 0 .. 25} \ - CONFIG.PSU__GPIO0_MIO__PERIPHERAL__ENABLE {1} \ - CONFIG.PSU__GPIO1_MIO__IO {MIO 26 .. 51} \ - CONFIG.PSU__GPIO1_MIO__PERIPHERAL__ENABLE {1} \ - CONFIG.PSU__GPIO2_MIO__PERIPHERAL__ENABLE {0} \ - CONFIG.PSU__GPIO_EMIO_WIDTH {1} \ - CONFIG.PSU__GPIO_EMIO__PERIPHERAL__ENABLE {0} \ - CONFIG.PSU__GPIO_EMIO__WIDTH {[94:0]} \ - CONFIG.PSU__GPU_PP0__POWER__ON {1} \ - CONFIG.PSU__GPU_PP1__POWER__ON {1} \ - CONFIG.PSU__GT_REF_CLK__FREQMHZ {33.333} \ - CONFIG.PSU__GT__LINK_SPEED {HBR} \ - CONFIG.PSU__GT__PRE_EMPH_LVL_4 {0} \ - CONFIG.PSU__GT__VLT_SWNG_LVL_4 {0} \ - CONFIG.PSU__HPM0_FPD__NUM_READ_THREADS {4} \ - CONFIG.PSU__HPM0_FPD__NUM_WRITE_THREADS {4} \ - CONFIG.PSU__HPM0_LPD__NUM_READ_THREADS {4} \ - CONFIG.PSU__HPM0_LPD__NUM_WRITE_THREADS {4} \ - CONFIG.PSU__HPM1_FPD__NUM_READ_THREADS {4} \ - CONFIG.PSU__HPM1_FPD__NUM_WRITE_THREADS {4} \ - CONFIG.PSU__I2C0_LOOP_I2C1__ENABLE {0} \ - CONFIG.PSU__I2C0__GRP_INT__ENABLE {0} \ - CONFIG.PSU__I2C0__PERIPHERAL__ENABLE {0} \ - CONFIG.PSU__I2C1__GRP_INT__ENABLE {0} \ - CONFIG.PSU__I2C1__PERIPHERAL__ENABLE {1} \ - CONFIG.PSU__I2C1__PERIPHERAL__IO {MIO 24 .. 25} \ - CONFIG.PSU__IOU_SLCR__IOU_TTC_APB_CLK__TTC0_SEL {APB} \ - CONFIG.PSU__IOU_SLCR__IOU_TTC_APB_CLK__TTC1_SEL {APB} \ - CONFIG.PSU__IOU_SLCR__IOU_TTC_APB_CLK__TTC2_SEL {APB} \ - CONFIG.PSU__IOU_SLCR__IOU_TTC_APB_CLK__TTC3_SEL {APB} \ - CONFIG.PSU__IOU_SLCR__TTC0__ACT_FREQMHZ {100.000000} \ - CONFIG.PSU__IOU_SLCR__TTC1__ACT_FREQMHZ {100.000000} \ - CONFIG.PSU__IOU_SLCR__TTC2__ACT_FREQMHZ {100.000000} \ - CONFIG.PSU__IOU_SLCR__TTC3__ACT_FREQMHZ {100.000000} \ - CONFIG.PSU__IOU_SLCR__WDT0__ACT_FREQMHZ {99.999001} \ - CONFIG.PSU__IRQ_P2F_ADMA_CHAN__INT {0} \ - CONFIG.PSU__IRQ_P2F_AIB_AXI__INT {0} \ - CONFIG.PSU__IRQ_P2F_AMS__INT {0} \ - CONFIG.PSU__IRQ_P2F_APM_FPD__INT {0} \ - CONFIG.PSU__IRQ_P2F_APU_COMM__INT {0} \ - CONFIG.PSU__IRQ_P2F_APU_CPUMNT__INT {0} \ - CONFIG.PSU__IRQ_P2F_APU_CTI__INT {0} \ - CONFIG.PSU__IRQ_P2F_APU_EXTERR__INT {0} \ - CONFIG.PSU__IRQ_P2F_APU_IPI__INT {0} \ - CONFIG.PSU__IRQ_P2F_APU_L2ERR__INT {0} \ - CONFIG.PSU__IRQ_P2F_APU_PMU__INT {0} \ - CONFIG.PSU__IRQ_P2F_APU_REGS__INT {0} \ - CONFIG.PSU__IRQ_P2F_ATB_LPD__INT {0} \ - CONFIG.PSU__IRQ_P2F_CLKMON__INT {0} \ - CONFIG.PSU__IRQ_P2F_CSUPMU_WDT__INT {0} \ - CONFIG.PSU__IRQ_P2F_DDR_SS__INT {0} \ - CONFIG.PSU__IRQ_P2F_DPDMA__INT {0} \ - CONFIG.PSU__IRQ_P2F_DPORT__INT {0} \ - CONFIG.PSU__IRQ_P2F_EFUSE__INT {0} \ - CONFIG.PSU__IRQ_P2F_ENT3_WAKEUP__INT {0} \ - CONFIG.PSU__IRQ_P2F_ENT3__INT {0} \ - CONFIG.PSU__IRQ_P2F_FPD_APB__INT {0} \ - CONFIG.PSU__IRQ_P2F_FPD_ATB_ERR__INT {0} \ - CONFIG.PSU__IRQ_P2F_FP_WDT__INT {0} \ - CONFIG.PSU__IRQ_P2F_GDMA_CHAN__INT {0} \ - CONFIG.PSU__IRQ_P2F_GPIO__INT {0} \ - CONFIG.PSU__IRQ_P2F_GPU__INT {0} \ - CONFIG.PSU__IRQ_P2F_I2C1__INT {0} \ - CONFIG.PSU__IRQ_P2F_LPD_APB__INT {0} \ - CONFIG.PSU__IRQ_P2F_LPD_APM__INT {0} \ - CONFIG.PSU__IRQ_P2F_LP_WDT__INT {0} \ - CONFIG.PSU__IRQ_P2F_OCM_ERR__INT {0} \ - CONFIG.PSU__IRQ_P2F_PCIE_DMA__INT {0} \ - CONFIG.PSU__IRQ_P2F_PCIE_LEGACY__INT {0} \ - CONFIG.PSU__IRQ_P2F_PCIE_MSC__INT {0} \ - CONFIG.PSU__IRQ_P2F_PCIE_MSI__INT {0} \ - CONFIG.PSU__IRQ_P2F_PL_IPI__INT {0} \ - CONFIG.PSU__IRQ_P2F_QSPI__INT {0} \ - CONFIG.PSU__IRQ_P2F_R5_CORE0_ECC_ERR__INT {0} \ - CONFIG.PSU__IRQ_P2F_R5_CORE1_ECC_ERR__INT {0} \ - CONFIG.PSU__IRQ_P2F_RPU_IPI__INT {0} \ - CONFIG.PSU__IRQ_P2F_RPU_PERMON__INT {0} \ - CONFIG.PSU__IRQ_P2F_RTC_ALARM__INT {0} \ - CONFIG.PSU__IRQ_P2F_RTC_SECONDS__INT {0} \ - CONFIG.PSU__IRQ_P2F_SATA__INT {0} \ - CONFIG.PSU__IRQ_P2F_SDIO1_WAKE__INT {0} \ - CONFIG.PSU__IRQ_P2F_SDIO1__INT {0} \ - CONFIG.PSU__IRQ_P2F_SPI1__INT {0} \ - CONFIG.PSU__IRQ_P2F_TTC0__INT0 {0} \ - CONFIG.PSU__IRQ_P2F_TTC0__INT1 {0} \ - CONFIG.PSU__IRQ_P2F_TTC0__INT2 {0} \ - CONFIG.PSU__IRQ_P2F_TTC1__INT0 {0} \ - CONFIG.PSU__IRQ_P2F_TTC1__INT1 {0} \ - CONFIG.PSU__IRQ_P2F_TTC1__INT2 {0} \ - CONFIG.PSU__IRQ_P2F_TTC2__INT0 {0} \ - CONFIG.PSU__IRQ_P2F_TTC2__INT1 {0} \ - CONFIG.PSU__IRQ_P2F_TTC2__INT2 {0} \ - CONFIG.PSU__IRQ_P2F_TTC3__INT0 {0} \ - CONFIG.PSU__IRQ_P2F_TTC3__INT1 {0} \ - CONFIG.PSU__IRQ_P2F_TTC3__INT2 {0} \ - CONFIG.PSU__IRQ_P2F_UART1__INT {0} \ - CONFIG.PSU__IRQ_P2F_USB3_ENDPOINT__INT0 {0} \ - CONFIG.PSU__IRQ_P2F_USB3_ENDPOINT__INT1 {0} \ - CONFIG.PSU__IRQ_P2F_USB3_OTG__INT0 {0} \ - CONFIG.PSU__IRQ_P2F_USB3_OTG__INT1 {0} \ - CONFIG.PSU__IRQ_P2F_USB3_PMU_WAKEUP__INT {0} \ - CONFIG.PSU__IRQ_P2F_XMPU_FPD__INT {0} \ - CONFIG.PSU__IRQ_P2F_XMPU_LPD__INT {0} \ - CONFIG.PSU__IRQ_P2F__INTF_FPD_SMMU__INT {0} \ - CONFIG.PSU__IRQ_P2F__INTF_PPD_CCI__INT {0} \ - CONFIG.PSU__L2_BANK0__POWER__ON {1} \ - CONFIG.PSU__LPDMA0_COHERENCY {0} \ - CONFIG.PSU__LPDMA1_COHERENCY {0} \ - CONFIG.PSU__LPDMA2_COHERENCY {0} \ - CONFIG.PSU__LPDMA3_COHERENCY {0} \ - CONFIG.PSU__LPDMA4_COHERENCY {0} \ - CONFIG.PSU__LPDMA5_COHERENCY {0} \ - CONFIG.PSU__LPDMA6_COHERENCY {0} \ - CONFIG.PSU__LPDMA7_COHERENCY {0} \ - CONFIG.PSU__LPD_SLCR__CSUPMU_WDT_CLK_SEL__SELECT {APB} \ - CONFIG.PSU__LPD_SLCR__CSUPMU__ACT_FREQMHZ {100.000000} \ - CONFIG.PSU__MAXIGP2__DATA_WIDTH {32} \ - CONFIG.PSU__M_AXI_GP0_SUPPORTS_NARROW_BURST {1} \ - CONFIG.PSU__M_AXI_GP1_SUPPORTS_NARROW_BURST {1} \ - CONFIG.PSU__M_AXI_GP2_SUPPORTS_NARROW_BURST {1} \ - CONFIG.PSU__NAND__PERIPHERAL__ENABLE {0} \ - CONFIG.PSU__NAND__READY_BUSY__ENABLE {0} \ - CONFIG.PSU__NUM_FABRIC_RESETS {1} \ - CONFIG.PSU__OCM_BANK0__POWER__ON {1} \ - CONFIG.PSU__OCM_BANK1__POWER__ON {1} \ - CONFIG.PSU__OCM_BANK2__POWER__ON {1} \ - CONFIG.PSU__OCM_BANK3__POWER__ON {1} \ - CONFIG.PSU__OVERRIDE_HPX_QOS {0} \ - CONFIG.PSU__OVERRIDE__BASIC_CLOCK {0} \ - CONFIG.PSU__PCIE__ACS_VIOLAION {0} \ - CONFIG.PSU__PCIE__AER_CAPABILITY {0} \ - CONFIG.PSU__PCIE__CLASS_CODE_BASE {} \ - CONFIG.PSU__PCIE__CLASS_CODE_INTERFACE {} \ - CONFIG.PSU__PCIE__CLASS_CODE_SUB {} \ - CONFIG.PSU__PCIE__DEVICE_ID {} \ - CONFIG.PSU__PCIE__INTX_GENERATION {0} \ - CONFIG.PSU__PCIE__MSIX_CAPABILITY {0} \ - CONFIG.PSU__PCIE__MSI_CAPABILITY {0} \ - CONFIG.PSU__PCIE__PERIPHERAL__ENABLE {0} \ - CONFIG.PSU__PCIE__PERIPHERAL__ENDPOINT_ENABLE {1} \ - CONFIG.PSU__PCIE__PERIPHERAL__ROOTPORT_ENABLE {0} \ - CONFIG.PSU__PCIE__RESET__POLARITY {Active Low} \ - CONFIG.PSU__PCIE__REVISION_ID {} \ - CONFIG.PSU__PCIE__SUBSYSTEM_ID {} \ - CONFIG.PSU__PCIE__SUBSYSTEM_VENDOR_ID {} \ - CONFIG.PSU__PCIE__VENDOR_ID {} \ - CONFIG.PSU__PJTAG__PERIPHERAL__ENABLE {0} \ - CONFIG.PSU__PL_CLK0_BUF {TRUE} \ - CONFIG.PSU__PL_CLK1_BUF {TRUE} \ - CONFIG.PSU__PL__POWER__ON {1} \ - CONFIG.PSU__PMU_COHERENCY {0} \ - CONFIG.PSU__PMU__AIBACK__ENABLE {0} \ - CONFIG.PSU__PMU__EMIO_GPI__ENABLE {0} \ - CONFIG.PSU__PMU__EMIO_GPO__ENABLE {0} \ - CONFIG.PSU__PMU__GPI0__ENABLE {1} \ - CONFIG.PSU__PMU__GPI0__IO {MIO 26} \ - CONFIG.PSU__PMU__GPI1__ENABLE {0} \ - CONFIG.PSU__PMU__GPI2__ENABLE {0} \ - CONFIG.PSU__PMU__GPI3__ENABLE {0} \ - CONFIG.PSU__PMU__GPI4__ENABLE {0} \ - CONFIG.PSU__PMU__GPI5__ENABLE {1} \ - CONFIG.PSU__PMU__GPI5__IO {MIO 31} \ - CONFIG.PSU__PMU__GPO0__ENABLE {0} \ - CONFIG.PSU__PMU__GPO1__ENABLE {0} \ - CONFIG.PSU__PMU__GPO2__ENABLE {0} \ - CONFIG.PSU__PMU__GPO3__ENABLE {1} \ - CONFIG.PSU__PMU__GPO3__IO {MIO 35} \ - CONFIG.PSU__PMU__GPO3__POLARITY {low} \ - CONFIG.PSU__PMU__GPO4__ENABLE {0} \ - CONFIG.PSU__PMU__GPO5__ENABLE {0} \ - CONFIG.PSU__PMU__PERIPHERAL__ENABLE {1} \ - CONFIG.PSU__PMU__PLERROR__ENABLE {0} \ - CONFIG.PSU__PRESET_APPLIED {1} \ - CONFIG.PSU__PROTECTION__DDR_SEGMENTS {NONE} \ - CONFIG.PSU__PROTECTION__ENABLE {0} \ - CONFIG.PSU__PROTECTION__FPD_SEGMENTS {SA:0xFD1A0000; SIZE:1280; UNIT:KB; RegionTZ:Secure; WrAllowed:Read/Write; subsystemId:PMU Firmware | SA:0xFD000000; SIZE:64; UNIT:KB; RegionTZ:Secure; WrAllowed:Read/Write;\ -subsystemId:PMU Firmware | SA:0xFD010000; SIZE:64; UNIT:KB; RegionTZ:Secure; WrAllowed:Read/Write; subsystemId:PMU Firmware | SA:0xFD020000; SIZE:64; UNIT:KB; RegionTZ:Secure; WrAllowed:Read/Write;\ -subsystemId:PMU Firmware | SA:0xFD030000; SIZE:64; UNIT:KB; RegionTZ:Secure; WrAllowed:Read/Write; subsystemId:PMU Firmware | SA:0xFD040000; SIZE:64; UNIT:KB; RegionTZ:Secure; WrAllowed:Read/Write;\ -subsystemId:PMU Firmware | SA:0xFD050000; SIZE:64; UNIT:KB; RegionTZ:Secure; WrAllowed:Read/Write; subsystemId:PMU Firmware | SA:0xFD610000; SIZE:512; UNIT:KB; RegionTZ:Secure; WrAllowed:Read/Write;\ -subsystemId:PMU Firmware | SA:0xFD5D0000; SIZE:64; UNIT:KB; RegionTZ:Secure; WrAllowed:Read/Write; subsystemId:PMU Firmware | SA:0xFD1A0000 ; SIZE:1280; UNIT:KB; RegionTZ:Secure ; WrAllowed:Read/Write;\ -subsystemId:Secure Subsystem} \ - CONFIG.PSU__PROTECTION__LPD_SEGMENTS {SA:0xFF980000; SIZE:64; UNIT:KB; RegionTZ:Secure; WrAllowed:Read/Write; subsystemId:PMU Firmware| SA:0xFF5E0000; SIZE:2560; UNIT:KB; RegionTZ:Secure; WrAllowed:Read/Write;\ -subsystemId:PMU Firmware| SA:0xFFCC0000; SIZE:64; UNIT:KB; RegionTZ:Secure; WrAllowed:Read/Write; subsystemId:PMU Firmware| SA:0xFF180000; SIZE:768; UNIT:KB; RegionTZ:Secure; WrAllowed:Read/Write; subsystemId:PMU\ -Firmware| SA:0xFF410000; SIZE:640; UNIT:KB; RegionTZ:Secure; WrAllowed:Read/Write; subsystemId:PMU Firmware| SA:0xFFA70000; SIZE:64; UNIT:KB; RegionTZ:Secure; WrAllowed:Read/Write; subsystemId:PMU Firmware|\ -SA:0xFF9A0000; SIZE:64; UNIT:KB; RegionTZ:Secure; WrAllowed:Read/Write; subsystemId:PMU Firmware|SA:0xFF5E0000 ; SIZE:2560; UNIT:KB; RegionTZ:Secure ; WrAllowed:Read/Write; subsystemId:Secure Subsystem|SA:0xFFCC0000\ -; SIZE:64; UNIT:KB; RegionTZ:Secure ; WrAllowed:Read/Write; subsystemId:Secure Subsystem|SA:0xFF180000 ; SIZE:768; UNIT:KB; RegionTZ:Secure ; WrAllowed:Read/Write; subsystemId:Secure Subsystem|SA:0xFF9A0000\ -; SIZE:64; UNIT:KB; RegionTZ:Secure ; WrAllowed:Read/Write; subsystemId:Secure Subsystem} \ - CONFIG.PSU__PROTECTION__MASTERS {USB1:NonSecure;0|USB0:NonSecure;1|S_AXI_LPD:NA;0|S_AXI_HPC1_FPD:NA;0|S_AXI_HPC0_FPD:NA;0|S_AXI_HP3_FPD:NA;0|S_AXI_HP2_FPD:NA;0|S_AXI_HP1_FPD:NA;0|S_AXI_HP0_FPD:NA;0|S_AXI_ACP:NA;0|S_AXI_ACE:NA;0|SD1:NonSecure;1|SD0:NonSecure;0|SATA1:NonSecure;0|SATA0:NonSecure;0|RPU1:Secure;1|RPU0:Secure;1|QSPI:NonSecure;1|PMU:NA;1|PCIe:NonSecure;0|NAND:NonSecure;0|LDMA:NonSecure;1|GPU:NonSecure;1|GEM3:NonSecure;1|GEM2:NonSecure;0|GEM1:NonSecure;0|GEM0:NonSecure;0|FDMA:NonSecure;1|DP:NonSecure;1|DAP:NA;1|Coresight:NA;1|CSU:NA;1|APU:NA;1}\ -\ - CONFIG.PSU__PROTECTION__MASTERS_TZ {GEM0:NonSecure|SD1:NonSecure|GEM2:NonSecure|GEM1:NonSecure|GEM3:NonSecure|PCIe:NonSecure|DP:NonSecure|NAND:NonSecure|GPU:NonSecure|USB1:NonSecure|USB0:NonSecure|LDMA:NonSecure|FDMA:NonSecure|QSPI:NonSecure|SD0:NonSecure}\ -\ - CONFIG.PSU__PROTECTION__OCM_SEGMENTS {NONE} \ - CONFIG.PSU__PROTECTION__PRESUBSYSTEMS {NONE} \ - CONFIG.PSU__PROTECTION__SLAVES {LPD;USB3_1_XHCI;FE300000;FE3FFFFF;0|LPD;USB3_1;FF9E0000;FF9EFFFF;0|LPD;USB3_0_XHCI;FE200000;FE2FFFFF;1|LPD;USB3_0;FF9D0000;FF9DFFFF;1|LPD;UART1;FF010000;FF01FFFF;1|LPD;UART0;FF000000;FF00FFFF;0|LPD;TTC3;FF140000;FF14FFFF;1|LPD;TTC2;FF130000;FF13FFFF;1|LPD;TTC1;FF120000;FF12FFFF;1|LPD;TTC0;FF110000;FF11FFFF;1|FPD;SWDT1;FD4D0000;FD4DFFFF;1|LPD;SWDT0;FF150000;FF15FFFF;1|LPD;SPI1;FF050000;FF05FFFF;1|LPD;SPI0;FF040000;FF04FFFF;0|FPD;SMMU_REG;FD5F0000;FD5FFFFF;1|FPD;SMMU;FD800000;FDFFFFFF;1|FPD;SIOU;FD3D0000;FD3DFFFF;1|FPD;SERDES;FD400000;FD47FFFF;1|LPD;SD1;FF170000;FF17FFFF;1|LPD;SD0;FF160000;FF16FFFF;0|FPD;SATA;FD0C0000;FD0CFFFF;0|LPD;RTC;FFA60000;FFA6FFFF;1|LPD;RSA_CORE;FFCE0000;FFCEFFFF;1|LPD;RPU;FF9A0000;FF9AFFFF;1|LPD;R5_TCM_RAM_GLOBAL;FFE00000;FFE3FFFF;1|LPD;R5_1_Instruction_Cache;FFEC0000;FFECFFFF;1|LPD;R5_1_Data_Cache;FFED0000;FFEDFFFF;1|LPD;R5_1_BTCM_GLOBAL;FFEB0000;FFEBFFFF;1|LPD;R5_1_ATCM_GLOBAL;FFE90000;FFE9FFFF;1|LPD;R5_0_Instruction_Cache;FFE40000;FFE4FFFF;1|LPD;R5_0_Data_Cache;FFE50000;FFE5FFFF;1|LPD;R5_0_BTCM_GLOBAL;FFE20000;FFE2FFFF;1|LPD;R5_0_ATCM_GLOBAL;FFE00000;FFE0FFFF;1|LPD;QSPI_Linear_Address;C0000000;DFFFFFFF;1|LPD;QSPI;FF0F0000;FF0FFFFF;1|LPD;PMU_RAM;FFDC0000;FFDDFFFF;1|LPD;PMU_GLOBAL;FFD80000;FFDBFFFF;1|FPD;PCIE_MAIN;FD0E0000;FD0EFFFF;0|FPD;PCIE_LOW;E0000000;EFFFFFFF;0|FPD;PCIE_HIGH2;8000000000;BFFFFFFFFF;0|FPD;PCIE_HIGH1;600000000;7FFFFFFFF;0|FPD;PCIE_DMA;FD0F0000;FD0FFFFF;0|FPD;PCIE_ATTRIB;FD480000;FD48FFFF;0|LPD;OCM_XMPU_CFG;FFA70000;FFA7FFFF;1|LPD;OCM_SLCR;FF960000;FF96FFFF;1|OCM;OCM;FFFC0000;FFFFFFFF;1|LPD;NAND;FF100000;FF10FFFF;0|LPD;MBISTJTAG;FFCF0000;FFCFFFFF;1|LPD;LPD_XPPU_SINK;FF9C0000;FF9CFFFF;1|LPD;LPD_XPPU;FF980000;FF98FFFF;1|LPD;LPD_SLCR_SECURE;FF4B0000;FF4DFFFF;1|LPD;LPD_SLCR;FF410000;FF4AFFFF;1|LPD;LPD_GPV;FE100000;FE1FFFFF;1|LPD;LPD_DMA_7;FFAF0000;FFAFFFFF;1|LPD;LPD_DMA_6;FFAE0000;FFAEFFFF;1|LPD;LPD_DMA_5;FFAD0000;FFADFFFF;1|LPD;LPD_DMA_4;FFAC0000;FFACFFFF;1|LPD;LPD_DMA_3;FFAB0000;FFABFFFF;1|LPD;LPD_DMA_2;FFAA0000;FFAAFFFF;1|LPD;LPD_DMA_1;FFA90000;FFA9FFFF;1|LPD;LPD_DMA_0;FFA80000;FFA8FFFF;1|LPD;IPI_CTRL;FF380000;FF3FFFFF;1|LPD;IOU_SLCR;FF180000;FF23FFFF;1|LPD;IOU_SECURE_SLCR;FF240000;FF24FFFF;1|LPD;IOU_SCNTRS;FF260000;FF26FFFF;1|LPD;IOU_SCNTR;FF250000;FF25FFFF;1|LPD;IOU_GPV;FE000000;FE0FFFFF;1|LPD;I2C1;FF030000;FF03FFFF;1|LPD;I2C0;FF020000;FF02FFFF;0|FPD;GPU;FD4B0000;FD4BFFFF;1|LPD;GPIO;FF0A0000;FF0AFFFF;1|LPD;GEM3;FF0E0000;FF0EFFFF;1|LPD;GEM2;FF0D0000;FF0DFFFF;0|LPD;GEM1;FF0C0000;FF0CFFFF;0|LPD;GEM0;FF0B0000;FF0BFFFF;0|FPD;FPD_XMPU_SINK;FD4F0000;FD4FFFFF;1|FPD;FPD_XMPU_CFG;FD5D0000;FD5DFFFF;1|FPD;FPD_SLCR_SECURE;FD690000;FD6CFFFF;1|FPD;FPD_SLCR;FD610000;FD68FFFF;1|FPD;FPD_DMA_CH7;FD570000;FD57FFFF;1|FPD;FPD_DMA_CH6;FD560000;FD56FFFF;1|FPD;FPD_DMA_CH5;FD550000;FD55FFFF;1|FPD;FPD_DMA_CH4;FD540000;FD54FFFF;1|FPD;FPD_DMA_CH3;FD530000;FD53FFFF;1|FPD;FPD_DMA_CH2;FD520000;FD52FFFF;1|FPD;FPD_DMA_CH1;FD510000;FD51FFFF;1|FPD;FPD_DMA_CH0;FD500000;FD50FFFF;1|LPD;EFUSE;FFCC0000;FFCCFFFF;1|FPD;Display\ -Port;FD4A0000;FD4AFFFF;1|FPD;DPDMA;FD4C0000;FD4CFFFF;1|FPD;DDR_XMPU5_CFG;FD050000;FD05FFFF;1|FPD;DDR_XMPU4_CFG;FD040000;FD04FFFF;1|FPD;DDR_XMPU3_CFG;FD030000;FD03FFFF;1|FPD;DDR_XMPU2_CFG;FD020000;FD02FFFF;1|FPD;DDR_XMPU1_CFG;FD010000;FD01FFFF;1|FPD;DDR_XMPU0_CFG;FD000000;FD00FFFF;1|FPD;DDR_QOS_CTRL;FD090000;FD09FFFF;1|FPD;DDR_PHY;FD080000;FD08FFFF;1|DDR;DDR_LOW;0;7FFFFFFF;1|DDR;DDR_HIGH;800000000;87FFFFFFF;1|FPD;DDDR_CTRL;FD070000;FD070FFF;1|LPD;Coresight;FE800000;FEFFFFFF;1|LPD;CSU_DMA;FFC80000;FFC9FFFF;1|LPD;CSU;FFCA0000;FFCAFFFF;1|LPD;CRL_APB;FF5E0000;FF85FFFF;1|FPD;CRF_APB;FD1A0000;FD2DFFFF;1|FPD;CCI_REG;FD5E0000;FD5EFFFF;1|LPD;CAN1;FF070000;FF07FFFF;0|LPD;CAN0;FF060000;FF06FFFF;0|FPD;APU;FD5C0000;FD5CFFFF;1|LPD;APM_INTC_IOU;FFA20000;FFA2FFFF;1|LPD;APM_FPD_LPD;FFA30000;FFA3FFFF;1|FPD;APM_5;FD490000;FD49FFFF;1|FPD;APM_0;FD0B0000;FD0BFFFF;1|LPD;APM2;FFA10000;FFA1FFFF;1|LPD;APM1;FFA00000;FFA0FFFF;1|LPD;AMS;FFA50000;FFA5FFFF;1|FPD;AFI_5;FD3B0000;FD3BFFFF;1|FPD;AFI_4;FD3A0000;FD3AFFFF;1|FPD;AFI_3;FD390000;FD39FFFF;1|FPD;AFI_2;FD380000;FD38FFFF;1|FPD;AFI_1;FD370000;FD37FFFF;1|FPD;AFI_0;FD360000;FD36FFFF;1|LPD;AFIFM6;FF9B0000;FF9BFFFF;1|FPD;ACPU_GIC;F9010000;F907FFFF;1}\ -\ - CONFIG.PSU__PROTECTION__SUBSYSTEMS {PMU Firmware:PMU|Secure Subsystem:} \ - CONFIG.PSU__PSS_ALT_REF_CLK__ENABLE {0} \ - CONFIG.PSU__PSS_ALT_REF_CLK__FREQMHZ {33.333} \ - CONFIG.PSU__PSS_REF_CLK__FREQMHZ {33.333} \ - CONFIG.PSU__QSPI_COHERENCY {0} \ - CONFIG.PSU__QSPI_ROUTE_THROUGH_FPD {0} \ - CONFIG.PSU__QSPI__GRP_FBCLK__ENABLE {0} \ - CONFIG.PSU__QSPI__PERIPHERAL__DATA_MODE {x4} \ - CONFIG.PSU__QSPI__PERIPHERAL__ENABLE {1} \ - CONFIG.PSU__QSPI__PERIPHERAL__IO {MIO 0 .. 5} \ - CONFIG.PSU__QSPI__PERIPHERAL__MODE {Single} \ - CONFIG.PSU__REPORT__DBGLOG {0} \ - CONFIG.PSU__RPU_COHERENCY {0} \ - CONFIG.PSU__RPU__POWER__ON {1} \ - CONFIG.PSU__SATA__PERIPHERAL__ENABLE {0} \ - CONFIG.PSU__SD0__CLK_100_SDR_OTAP_DLY {0x3} \ - CONFIG.PSU__SD0__CLK_200_SDR_OTAP_DLY {0x3} \ - CONFIG.PSU__SD0__CLK_50_DDR_ITAP_DLY {0x3D} \ - CONFIG.PSU__SD0__CLK_50_DDR_OTAP_DLY {0x4} \ - CONFIG.PSU__SD0__CLK_50_SDR_ITAP_DLY {0x15} \ - CONFIG.PSU__SD0__CLK_50_SDR_OTAP_DLY {0x5} \ - CONFIG.PSU__SD0__PERIPHERAL__ENABLE {0} \ - CONFIG.PSU__SD0__RESET__ENABLE {0} \ - CONFIG.PSU__SD1_COHERENCY {0} \ - CONFIG.PSU__SD1_ROUTE_THROUGH_FPD {0} \ - CONFIG.PSU__SD1__CLK_100_SDR_OTAP_DLY {0x3} \ - CONFIG.PSU__SD1__CLK_200_SDR_OTAP_DLY {0x3} \ - CONFIG.PSU__SD1__CLK_50_DDR_ITAP_DLY {0x3D} \ - CONFIG.PSU__SD1__CLK_50_DDR_OTAP_DLY {0x4} \ - CONFIG.PSU__SD1__CLK_50_SDR_ITAP_DLY {0x15} \ - CONFIG.PSU__SD1__CLK_50_SDR_OTAP_DLY {0x5} \ - CONFIG.PSU__SD1__DATA_TRANSFER_MODE {8Bit} \ - CONFIG.PSU__SD1__GRP_CD__ENABLE {1} \ - CONFIG.PSU__SD1__GRP_CD__IO {MIO 45} \ - CONFIG.PSU__SD1__GRP_POW__ENABLE {1} \ - CONFIG.PSU__SD1__GRP_POW__IO {MIO 43} \ - CONFIG.PSU__SD1__GRP_WP__ENABLE {0} \ - CONFIG.PSU__SD1__PERIPHERAL__ENABLE {1} \ - CONFIG.PSU__SD1__PERIPHERAL__IO {MIO 39 .. 51} \ - CONFIG.PSU__SD1__SLOT_TYPE {SD 3.0} \ - CONFIG.PSU__SPI0_LOOP_SPI1__ENABLE {0} \ - CONFIG.PSU__SPI0__PERIPHERAL__ENABLE {0} \ - CONFIG.PSU__SPI1__GRP_SS0__IO {MIO 9} \ - CONFIG.PSU__SPI1__GRP_SS1__ENABLE {0} \ - CONFIG.PSU__SPI1__GRP_SS2__ENABLE {0} \ - CONFIG.PSU__SPI1__PERIPHERAL__ENABLE {1} \ - CONFIG.PSU__SPI1__PERIPHERAL__IO {MIO 6 .. 11} \ - CONFIG.PSU__SWDT0__CLOCK__ENABLE {0} \ - CONFIG.PSU__SWDT0__PERIPHERAL__ENABLE {1} \ - CONFIG.PSU__SWDT0__PERIPHERAL__IO {NA} \ - CONFIG.PSU__SWDT0__RESET__ENABLE {0} \ - CONFIG.PSU__SWDT1__CLOCK__ENABLE {0} \ - CONFIG.PSU__SWDT1__PERIPHERAL__ENABLE {1} \ - CONFIG.PSU__SWDT1__PERIPHERAL__IO {NA} \ - CONFIG.PSU__SWDT1__RESET__ENABLE {0} \ - CONFIG.PSU__TCM0A__POWER__ON {1} \ - CONFIG.PSU__TCM0B__POWER__ON {1} \ - CONFIG.PSU__TCM1A__POWER__ON {1} \ - CONFIG.PSU__TCM1B__POWER__ON {1} \ - CONFIG.PSU__TESTSCAN__PERIPHERAL__ENABLE {0} \ - CONFIG.PSU__TRACE__INTERNAL_WIDTH {32} \ - CONFIG.PSU__TRACE__PERIPHERAL__ENABLE {0} \ - CONFIG.PSU__TRISTATE__INVERTED {1} \ - CONFIG.PSU__TSU__BUFG_PORT_PAIR {0} \ - CONFIG.PSU__TTC0__CLOCK__ENABLE {0} \ - CONFIG.PSU__TTC0__PERIPHERAL__ENABLE {1} \ - CONFIG.PSU__TTC0__PERIPHERAL__IO {NA} \ - CONFIG.PSU__TTC0__WAVEOUT__ENABLE {0} \ - CONFIG.PSU__TTC1__CLOCK__ENABLE {0} \ - CONFIG.PSU__TTC1__PERIPHERAL__ENABLE {1} \ - CONFIG.PSU__TTC1__PERIPHERAL__IO {NA} \ - CONFIG.PSU__TTC1__WAVEOUT__ENABLE {0} \ - CONFIG.PSU__TTC2__CLOCK__ENABLE {0} \ - CONFIG.PSU__TTC2__PERIPHERAL__ENABLE {1} \ - CONFIG.PSU__TTC2__PERIPHERAL__IO {NA} \ - CONFIG.PSU__TTC2__WAVEOUT__ENABLE {0} \ - CONFIG.PSU__TTC3__CLOCK__ENABLE {0} \ - CONFIG.PSU__TTC3__PERIPHERAL__ENABLE {1} \ - CONFIG.PSU__TTC3__PERIPHERAL__IO {NA} \ - CONFIG.PSU__TTC3__WAVEOUT__ENABLE {0} \ - CONFIG.PSU__UART0_LOOP_UART1__ENABLE {0} \ - CONFIG.PSU__UART0__PERIPHERAL__ENABLE {0} \ - CONFIG.PSU__UART1__BAUD_RATE {115200} \ - CONFIG.PSU__UART1__MODEM__ENABLE {0} \ - CONFIG.PSU__UART1__PERIPHERAL__ENABLE {1} \ - CONFIG.PSU__UART1__PERIPHERAL__IO {MIO 36 .. 37} \ - CONFIG.PSU__USB0_COHERENCY {0} \ - CONFIG.PSU__USB0__PERIPHERAL__ENABLE {1} \ - CONFIG.PSU__USB0__PERIPHERAL__IO {MIO 52 .. 63} \ - CONFIG.PSU__USB0__REF_CLK_FREQ {26} \ - CONFIG.PSU__USB0__REF_CLK_SEL {Ref Clk1} \ - CONFIG.PSU__USB1__PERIPHERAL__ENABLE {0} \ - CONFIG.PSU__USB2_0__EMIO__ENABLE {0} \ - CONFIG.PSU__USB3_0__EMIO__ENABLE {0} \ - CONFIG.PSU__USB3_0__PERIPHERAL__ENABLE {1} \ - CONFIG.PSU__USB3_0__PERIPHERAL__IO {GT Lane2} \ - CONFIG.PSU__USB__RESET__MODE {Boot Pin} \ - CONFIG.PSU__USB__RESET__POLARITY {Active Low} \ - CONFIG.PSU__USE__ADMA {0} \ - CONFIG.PSU__USE__APU_LEGACY_INTERRUPT {0} \ - CONFIG.PSU__USE__AUDIO {0} \ - CONFIG.PSU__USE__CLK {0} \ - CONFIG.PSU__USE__CLK0 {0} \ - CONFIG.PSU__USE__CLK1 {0} \ - CONFIG.PSU__USE__CLK2 {0} \ - CONFIG.PSU__USE__CLK3 {0} \ - CONFIG.PSU__USE__CROSS_TRIGGER {0} \ - CONFIG.PSU__USE__DDR_INTF_REQUESTED {0} \ - CONFIG.PSU__USE__DEBUG__TEST {0} \ - CONFIG.PSU__USE__EVENT_RPU {0} \ - CONFIG.PSU__USE__FABRIC__RST {1} \ - CONFIG.PSU__USE__FTM {0} \ - CONFIG.PSU__USE__GDMA {0} \ - CONFIG.PSU__USE__IRQ {0} \ - CONFIG.PSU__USE__IRQ0 {1} \ - CONFIG.PSU__USE__IRQ1 {0} \ - CONFIG.PSU__USE__M_AXI_GP0 {0} \ - CONFIG.PSU__USE__M_AXI_GP1 {0} \ - CONFIG.PSU__USE__M_AXI_GP2 {1} \ - CONFIG.PSU__USE__PROC_EVENT_BUS {0} \ - CONFIG.PSU__USE__RPU_LEGACY_INTERRUPT {0} \ - CONFIG.PSU__USE__RST0 {0} \ - CONFIG.PSU__USE__RST1 {0} \ - CONFIG.PSU__USE__RST2 {0} \ - CONFIG.PSU__USE__RST3 {0} \ - CONFIG.PSU__USE__RTC {0} \ - CONFIG.PSU__USE__STM {0} \ - CONFIG.PSU__USE__S_AXI_ACE {0} \ - CONFIG.PSU__USE__S_AXI_ACP {0} \ - CONFIG.PSU__USE__S_AXI_GP0 {0} \ - CONFIG.PSU__USE__S_AXI_GP1 {0} \ - CONFIG.PSU__USE__S_AXI_GP2 {0} \ - CONFIG.PSU__USE__S_AXI_GP3 {0} \ - CONFIG.PSU__USE__S_AXI_GP4 {0} \ - CONFIG.PSU__USE__S_AXI_GP5 {0} \ - CONFIG.PSU__USE__S_AXI_GP6 {0} \ - CONFIG.PSU__USE__USB3_0_HUB {0} \ - CONFIG.PSU__USE__USB3_1_HUB {0} \ - CONFIG.PSU__USE__VIDEO {0} \ - CONFIG.PSU__VIDEO_REF_CLK__ENABLE {0} \ - CONFIG.PSU__VIDEO_REF_CLK__FREQMHZ {33.333} \ - CONFIG.QSPI_BOARD_INTERFACE {custom} \ - CONFIG.SATA_BOARD_INTERFACE {custom} \ - CONFIG.SD0_BOARD_INTERFACE {custom} \ - CONFIG.SD1_BOARD_INTERFACE {custom} \ - CONFIG.SPI0_BOARD_INTERFACE {custom} \ - CONFIG.SPI1_BOARD_INTERFACE {custom} \ - CONFIG.SUBPRESET1 {Custom} \ - CONFIG.SUBPRESET2 {Custom} \ - CONFIG.SWDT0_BOARD_INTERFACE {custom} \ - CONFIG.SWDT1_BOARD_INTERFACE {custom} \ - CONFIG.TRACE_BOARD_INTERFACE {custom} \ - CONFIG.TTC0_BOARD_INTERFACE {custom} \ - CONFIG.TTC1_BOARD_INTERFACE {custom} \ - CONFIG.TTC2_BOARD_INTERFACE {custom} \ - CONFIG.TTC3_BOARD_INTERFACE {custom} \ - CONFIG.UART0_BOARD_INTERFACE {custom} \ - CONFIG.UART1_BOARD_INTERFACE {custom} \ - CONFIG.USB0_BOARD_INTERFACE {custom} \ - CONFIG.USB1_BOARD_INTERFACE {custom} \ - ] $zynq_ultra_ps_e_0 - - - set_property SELECTED_SIM_MODEL tlm $zynq_ultra_ps_e_0 - - # Create instance: clk_wiz_0, and set properties - set clk_wiz_0 [ create_bd_cell -type ip -vlnv xilinx.com:ip:clk_wiz:6.0 clk_wiz_0 ] - set_property -dict [list \ - CONFIG.CLKOUT1_JITTER {115.833} \ - CONFIG.CLKOUT1_PHASE_ERROR {87.181} \ - CONFIG.CLKOUT2_JITTER {102.087} \ - CONFIG.CLKOUT2_PHASE_ERROR {87.181} \ - CONFIG.CLKOUT2_REQUESTED_OUT_FREQ {200.000} \ - CONFIG.CLKOUT2_USED {true} \ - CONFIG.CLKOUT3_JITTER {90.075} \ - CONFIG.CLKOUT3_PHASE_ERROR {87.181} \ - CONFIG.CLKOUT3_REQUESTED_OUT_FREQ {400.000} \ - CONFIG.CLKOUT3_USED {true} \ - CONFIG.MMCM_CLKOUT1_DIVIDE {6} \ - CONFIG.MMCM_CLKOUT2_DIVIDE {3} \ - CONFIG.NUM_OUT_CLKS {3} \ - CONFIG.RESET_PORT {resetn} \ - CONFIG.RESET_TYPE {ACTIVE_LOW} \ - ] $clk_wiz_0 - - - # Create instance: proc_sys_reset_1, and set properties - set proc_sys_reset_1 [ create_bd_cell -type ip -vlnv xilinx.com:ip:proc_sys_reset:5.0 proc_sys_reset_1 ] - - # Create instance: proc_sys_reset_2, and set properties - set proc_sys_reset_2 [ create_bd_cell -type ip -vlnv xilinx.com:ip:proc_sys_reset:5.0 proc_sys_reset_2 ] - - # Create instance: proc_sys_reset_3, and set properties - set proc_sys_reset_3 [ create_bd_cell -type ip -vlnv xilinx.com:ip:proc_sys_reset:5.0 proc_sys_reset_3 ] - - # Create instance: axi_intc_0, and set properties - set axi_intc_0 [ create_bd_cell -type ip -vlnv xilinx.com:ip:axi_intc:4.1 axi_intc_0 ] - set_property CONFIG.C_IRQ_CONNECTION {1} $axi_intc_0 - - - # Create instance: ps8_0_axi_periph, and set properties - set ps8_0_axi_periph [ create_bd_cell -type ip -vlnv xilinx.com:ip:axi_interconnect:2.1 ps8_0_axi_periph ] - set_property CONFIG.NUM_MI {1} $ps8_0_axi_periph - - - # Create interface connections - connect_bd_intf_net -intf_net ps8_0_axi_periph_M00_AXI [get_bd_intf_pins ps8_0_axi_periph/M00_AXI] [get_bd_intf_pins axi_intc_0/s_axi] - connect_bd_intf_net -intf_net zynq_ultra_ps_e_0_M_AXI_HPM0_LPD [get_bd_intf_pins zynq_ultra_ps_e_0/M_AXI_HPM0_LPD] [get_bd_intf_pins ps8_0_axi_periph/S00_AXI] - - # Create port connections - connect_bd_net -net axi_intc_0_irq [get_bd_pins axi_intc_0/irq] [get_bd_pins zynq_ultra_ps_e_0/pl_ps_irq0] - connect_bd_net -net clk_wiz_0_clk_out1 [get_bd_pins clk_wiz_0/clk_out1] [get_bd_pins proc_sys_reset_1/slowest_sync_clk] - connect_bd_net -net clk_wiz_0_clk_out2 [get_bd_pins clk_wiz_0/clk_out2] [get_bd_pins axi_intc_0/s_axi_aclk] [get_bd_pins proc_sys_reset_2/slowest_sync_clk] [get_bd_pins ps8_0_axi_periph/ACLK] [get_bd_pins ps8_0_axi_periph/S00_ACLK] [get_bd_pins ps8_0_axi_periph/M00_ACLK] [get_bd_pins zynq_ultra_ps_e_0/maxihpm0_lpd_aclk] - connect_bd_net -net clk_wiz_0_clk_out3 [get_bd_pins clk_wiz_0/clk_out3] [get_bd_pins proc_sys_reset_3/slowest_sync_clk] - connect_bd_net -net clk_wiz_0_locked [get_bd_pins clk_wiz_0/locked] [get_bd_pins proc_sys_reset_1/dcm_locked] [get_bd_pins proc_sys_reset_2/dcm_locked] [get_bd_pins proc_sys_reset_3/dcm_locked] - connect_bd_net -net proc_sys_reset_2_peripheral_aresetn [get_bd_pins proc_sys_reset_2/peripheral_aresetn] [get_bd_pins axi_intc_0/s_axi_aresetn] [get_bd_pins ps8_0_axi_periph/ARESETN] [get_bd_pins ps8_0_axi_periph/S00_ARESETN] [get_bd_pins ps8_0_axi_periph/M00_ARESETN] - connect_bd_net -net zynq_ultra_ps_e_0_pl_clk0 [get_bd_pins zynq_ultra_ps_e_0/pl_clk0] [get_bd_pins clk_wiz_0/clk_in1] - connect_bd_net -net zynq_ultra_ps_e_0_pl_resetn0 [get_bd_pins zynq_ultra_ps_e_0/pl_resetn0] [get_bd_pins clk_wiz_0/resetn] [get_bd_pins proc_sys_reset_1/ext_reset_in] [get_bd_pins proc_sys_reset_2/ext_reset_in] [get_bd_pins proc_sys_reset_3/ext_reset_in] - - # Create address segments - assign_bd_address -offset 0x80000000 -range 0x00010000 -target_address_space [get_bd_addr_spaces zynq_ultra_ps_e_0/Data] [get_bd_addr_segs axi_intc_0/S_AXI/Reg] -force - - - # Restore current instance - current_bd_instance $oldCurInst - - # Create PFM attributes - set_property PFM_NAME {xilinx:kv260:kv260_hardware_Platform:0.0} [get_files [current_bd_design].bd] - set_property PFM.AXI_PORT {M_AXI_HPM0_FPD {memport "M_AXI_GP" sptag "" memory "" is_range "false"} M_AXI_HPM1_FPD {memport "M_AXI_GP" sptag "" memory "" is_range "false"} S_AXI_HPC0_FPD {memport "S_AXI_HP" sptag "HP2" memory "" is_range "false"} S_AXI_HPC1_FPD {memport "S_AXI_HP" sptag "HP3" memory "" is_range "false"} S_AXI_HP0_FPD {memport "S_AXI_HP" sptag "HPC0" memory "" is_range "false"} S_AXI_HP1_FPD {memport "S_AXI_HP" sptag "HPC1" memory "" is_range "false"} S_AXI_HP2_FPD {memport "S_AXI_HP" sptag "HP0" memory "" is_range "false"} S_AXI_HP3_FPD {memport "S_AXI_HP" sptag "HP1" memory "" is_range "false"}} [get_bd_cells /zynq_ultra_ps_e_0] - set_property PFM.CLOCK {clk_out1 {id "0" is_default "false" proc_sys_reset "/proc_sys_reset_1" status "fixed" freq_hz "100000000"} clk_out2 {id "1" is_default "true" proc_sys_reset "/proc_sys_reset_2" status "fixed" freq_hz "200000000"} clk_out3 {id "2" is_default "false" proc_sys_reset "/proc_sys_reset_3" status "fixed" freq_hz "400000000"}} [get_bd_cells /clk_wiz_0] - set_property PFM.IRQ {intr { id 0 range 32 }} [get_bd_cells /axi_intc_0] - set_property PFM.AXI_PORT {M01_AXI {memport "M_AXI_GP" sptag "" memory "" is_range "false"} M02_AXI {memport "M_AXI_GP" sptag "" memory "" is_range "false"} M03_AXI {memport "M_AXI_GP" sptag "" memory "" is_range "false"} M04_AXI {memport "M_AXI_GP" sptag "" memory "" is_range "false"} M05_AXI {memport "M_AXI_GP" sptag "" memory "" is_range "false"} M06_AXI {memport "M_AXI_GP" sptag "" memory "" is_range "false"} M07_AXI {memport "M_AXI_GP" sptag "" memory "" is_range "false"}} [get_bd_cells /ps8_0_axi_periph] - - - save_bd_design -} -# End of create_root_design() - - -################################################################## -# MAIN FLOW -################################################################## - -create_root_design "" - - -common::send_gid_msg -ssname BD::TCL -id 2053 -severity "WARNING" "This Tcl script was generated from a block design that has not been validated. It is possible that design <$design_name> may result in errors during validation." - diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step2_pfm/Makefile b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step2_pfm/Makefile deleted file mode 100644 index d5866268b8..0000000000 --- a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step2_pfm/Makefile +++ /dev/null @@ -1,48 +0,0 @@ -#/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -#SPDX-License-Identifier: MIT -#*/ - -ROOT_DIR=$(realpath $(dir $(lastword $(MAKEFILE_LIST)))) -PLATFORM_NAME=kv260_custom - -XSA_NAME=kv260_hardware_platform -VERSION=2025.1 -COMMON_IMAGE_ZYNQMP ?=${PLATFORM_REPO_PATHS}/sw/zynqmp/xilinx-zynqmp-common-v$(VERSION)/ - - - - -.PHONY: help - -help: - @echo "Makefile usage" - @echo "make all COMMON_IMAGE_ZYNQMP= ## Generate platform with pre-built software components" - - -all: check-common-image pfm - -#target : check whether the common image is ready -check-common-image: -ifeq ($(wildcard $(COMMON_IMAGE_ZYNQMP)/Image),) - @echo "'COMMON_IMAGE_ZYNQMP' is not accessible, please download common image from Xilinx Downloads website and set this flag to specify the common image path." - @make help - @echo "exit ....." && exit 1 -endif - - - -#create platfrom -pfm: - - @echo "INFO: Creating Platform $(PLATFORM_NAME)" - mkdir -p tmp && export XILINX_VITIS_DATA_DIR="./tmp" && vitis -s platform_creation.py --platform_name $(PLATFORM_NAME) --xsa_path ../step1_vivado/build/vivado/$(XSA_NAME).xsa --boot $(COMMON_IMAGE_ZYNQMP) - @echo "INFO: Checking created platforms:" && find . -name "*.xpfm" - - - -clean: - rm -rf IDE.log $(PLATFORM_NAME) $(DT_PLAT_NAME) - -ultraclean: clean - rm -rf device-tree-xlnx tmp logs ws diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step2_pfm/platform_creation.py b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step2_pfm/platform_creation.py deleted file mode 100644 index 91dd108d6e..0000000000 --- a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step2_pfm/platform_creation.py +++ /dev/null @@ -1,35 +0,0 @@ -#/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -#SPDX-License-Identifier: MIT -#*/ - -# 2023-04-02T21:02:13.258137 -import vitis -import argparse -import os - -print("Platform generation") -parser = argparse.ArgumentParser() -parser.add_argument("--platform_name", type=str, dest="platform_name") -parser.add_argument("--xsa_path", type=str, dest="xsa_path") -parser.add_argument("--boot", type=str, dest="boot") - -args = parser.parse_args() -platform_name=args.platform_name -xsa_path=args.xsa_path - -boot=args.boot -print('args',args) -client = vitis.create_client() -workspace_path = os.getcwd() + "/ws" -client.set_workspace(path=workspace_path) -advanced_options = client.create_advanced_options_dict(dt_overlay="1",dt_zocl="1") -platform = client.create_platform_component(name = platform_name, hw_design =xsa_path, os = "linux",cpu = "psu_cortexa53",generate_dtb = True,advanced_options = advanced_options ) -platform = client.get_component(name=platform_name) -domain = platform.get_domain(name="linux_psu_cortexa53") -status = domain.update_name(new_name="xrt") -status = domain.generate_bif() -status = domain.set_boot_dir(path=boot) - - -status = platform.build() diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step3_validate/Makefile b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step3_validate/Makefile deleted file mode 100644 index 69b0e13f7b..0000000000 --- a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step3_validate/Makefile +++ /dev/null @@ -1,65 +0,0 @@ -#/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -#SPDX-License-Identifier: MIT -#*/ - -ROOT_DIR=$(realpath $(dir $(lastword $(MAKEFILE_LIST)))) -PLATFORM_NAME=kv260_custom -PLATFORM= $(ROOT_DIR)/../step2_pfm/ws/$(PLATFORM_NAME)/export/$(PLATFORM_NAME)/$(PLATFORM_NAME).xpfm - -VERSION=2025.1 -COMMON_IMAGE_ZYNQMP ?=${PLATFORM_REPO_PATHS}/sw/zynqmp/xilinx-zynqmp-common-v$(VERSION)/ -SYSROOT := $(COMMON_IMAGE_ZYNQMP)/sysroots/cortexa72-cortexa53-amd-linux -VADD_WORK=$(ROOT_DIR)/vadd_work - -.PHONY: help - -help: - @echo "Makefile usage" - @echo "make all ## Generate and package application related files" - -all: getplatforminfo vadd_hw_package - - -getplatforminfo: - $(MAKE) -C platforminfo/ all -cpVaddCode: - mkdir -p vadd_work - cp $(XILINX_VITIS)/samples/vadd/* vadd_work -a - cp makefile_vadd vadd_work/Makefile - -# vadd_hw is a place-holder for manual build and test on hardware -$(VADD_WORK)/simple_vadd: vadd_hw -vadd_hw: cpVaddCode $(PLATFORM) - $(MAKE) -C $(VADD_WORK) sd_card TARGET=hw PLATFORM=$(PLATFORM) DEV_ARCH=versal HOST_ARCH=aarch64 EDGE_COMMON_SW=$(COMMON_IMAGE_ZYNQMP) SYSROOT=$(SYSROOT)/ -# vadd_hw generates the files for running on hardware. User needs to pick the files required by KV260, rename thr file and transfer them to the board -# Do not use the generated sd_card.img - -$(VADD_WORK)/shell.json: - cd $(VADD_WORK) && printf '{\n "shell_type" : "XRT_FLAT",\n "num_slots": "1"\n}' > shell.json - -vadd_hw_package: $(VADD_WORK)/simple_vadd $(VADD_WORK)/shell.json - @echo "INFO: Packaging Completed" - mkdir -p vadd - cp ../step2_pfm//ws/kv260_custom/export/kv260_custom/sw/boot/pl.dtbo vadd/ - cp $(VADD_WORK)/shell.json vadd/ - cp $(VADD_WORK)/build_dir.hw//vadd.link.xclbin vadd//vadd.bin - cp $(VADD_WORK)/simple_vadd vadd/ - @echo "Please copy vadd to /lib/firmware/xilinx/ on target board" - @echo "then use xmutil to load hardware." - @echo "xmutil unloadapp" - @echo "xmutil loadapp vadd" - @echo "Go to /lib/firmware/xilinx/vadd directory and run application" - @echo "$ ./simple_vadd .//vadd.bin" - -getplatforminfo: - $(MAKE) -C platforminfo/ all - - -clean: - -$(MAKE) -C $(VADD_WORK) clean - -$(MAKE) -C platforminfo/ clean - rm -rf vadd/ - -ultraclean:clean - rm -rf $(VADD_WORK) diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step3_validate/makefile_vadd b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step3_validate/makefile_vadd deleted file mode 100644 index eb5d1850d1..0000000000 --- a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step3_validate/makefile_vadd +++ /dev/null @@ -1,172 +0,0 @@ -#/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -#SPDX-License-Identifier: MIT -#*/ - - -############################## Setting up Project Variables ############################## -TARGET := hw -SYSROOT := $(EDGE_COMMON_SW)/sysroots/cortexa72-cortexa53-amd-linux -SD_IMAGE_FILE := $(EDGE_COMMON_SW)/Image -VPP_LDFLAGS := - - -TEMP_DIR := ./_x.$(TARGET) -BUILD_DIR := ./build_dir.$(TARGET) - -LINK_OUTPUT := $(BUILD_DIR)/vadd.link.xclbin - -EMU_PS := QEMU -ifeq ($(TARGET), sw_emu) -EMU_PS := X86 -endif - -# SoC variables -RUN_APP_SCRIPT = run_vadd.sh -PACKAGE_OUT = ./package.$(TARGET) - -LAUNCH_EMULATOR = $(PACKAGE_OUT)/launch_$(TARGET).sh -RESULT_STRING = TEST PASSED - -VPP_PFLAGS := -CMD_ARGS = $(BUILD_DIR)/vadd.xclbin -SD_CARD := $(PACKAGE_OUT) - - -ifeq ($(EMU_PS), X86) -CXXFLAGS += -I$(XILINX_XRT)/include -I$(XILINX_VIVADO)/include -Wall -O0 -g -std=c++17 -LDFLAGS += -L$(XILINX_XRT)/lib -pthread -lOpenCL -else -CXXFLAGS += -I$(XILINX_VITIS)/include -Wall -O0 -g -std=c++17 -CXXFLAGS += -I$(SYSROOT)/usr/include/xrt -CXXFLAGS += -I$(SYSROOT)/usr/include -Wall -Wextra -O0 -g3 -std=c++17 -MD -MT -CXXFLAGS += -Isrc/ -LDFLAGS += -L$(SYSROOT)/usr/lib -luuid -lxrt_coreutil -lxilinxopencl -lpthread -lrt -lstdc++ -endif - -ifeq ($(TARGET),$(filter $(TARGET),sw_emu)) -VPP_PFLAGS+= --package.emu_ps qemu -endif - -#Check for EMU_PS -ifeq ($(TARGET), $(filter $(TARGET),hw_emu hw)) -ifeq ($(EMU_PS), X86) -$(error For hw_emu and hw, the design has to run on QEMU. Thus, please give EMU_PS=QEMU for these targets.) -endif -endif - -########################## Checking if PLATFORM in allowlist ####################### -PLATFORM_BLOCKLIST += nodma -############################## Setting up Host Variables ############################## -#Include Required Host Source Files -HOST_SRCS += src/host.cpp -HOST_SRCS += src/cmdlineparser.cpp -HOST_SRCS += src/logger.cpp -# Host compiler global settings -CXXFLAGS += -fmessage-length=0 -LDFLAGS += -lrt -lstdc++ -ifneq ($(EMU_PS), X86) -LDFLAGS += --sysroot=$(SYSROOT) -endif -############################## Setting up Kernel Variables ############################## -# Kernel compiler global settings -VPP_FLAGS += --save-temps - - -EXECUTABLE = ./simple_vadd -EMCONFIG_DIR = $(TEMP_DIR) - -############################## Setting Targets ############################## -.PHONY: all clean cleanall docs emconfig -ifeq ($(EMU_PS), X86) -all: $(EXECUTABLE) $(LINK_OUTPUT) emconfig -else -all: $(EXECUTABLE) $(LINK_OUTPUT) sd_card -endif - -.PHONY: host -host: $(EXECUTABLE) - -.PHONY: build -build: $(LINK_OUTPUT) - -.PHONY: xclbin -xclbin: build - - -############################## Setting Rules for Binary Containers (Building Kernels) ############################## -$(TEMP_DIR)/vadd.xo: src/vadd.cpp - mkdir -p $(TEMP_DIR) - v++ -c $(VPP_FLAGS) -t $(TARGET) --platform $(PLATFORM) -k vadd --temp_dir $(TEMP_DIR) -I'$( platforminfo.txt - -clean: - rm platforminfo.txt \ No newline at end of file diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/step1.md b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/step1.md deleted file mode 100644 index 9d9811f199..0000000000 --- a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/step1.md +++ /dev/null @@ -1,312 +0,0 @@ - - - - -
- - - AMD logo - -

AMD Vitis™ Platform Creation Tutorials

- See Vitis™ Development Environment on amd.com -
- -# Step 1: Create the Vivado Hardware Design and Generate XSA - -In this step, you will create the hardware design for the KV260 Vitis acceleration platform. You will start from a KV260 preset design, add platform required peripherals, and configure them. After everything is set, You will export the hardware design to XSA. - -## Create Base Vivado Project from Preset - -1. Create a workspace and launch the AMD Vivado™ Design Suite. - - Run the following commands in Linux console. - - ```bash - mkdir WorkSpace - cd WorkSpace - source /settings64.sh - vivado & - ``` - -2. Create a Vivado project named **kv260_hardware_platform**. - - - Select **File->Project->New**, Click **Next**. - - In Project Name dialog, set Project name to **kv260_hardware_platform**, and keep **Create project subdirectory** checked. Then, click **Next**. - - Enable **Project is an extensible Vitis platform**. Click **Next**. - - ![vivado_project_type.png](./images/vivado_project_type.png) - - - Select **Boards** tab. - - Click **Refresh** button to load the latest list of boards. - - Select **Kria KV260 Vision AI Starter Kit**. - - Click **Connections**, click drop-down button and select **Vision AI Starter Kit carrier card**, click OK. - ![Missing Image](./images/kv260_cc.png) - - - Click **Next**. - - Review project summary and click **Finish** - - > **NOTE:** If you need to change an existing Vivado project to an extensible platform project, you can go to **Settings** in **Flow Navigator** in an opened Vivado design, go to **General** and enable **project is an extensible Vitis platform** - -3. Create a block design. - - - In **Project Manager**, under **IP INTEGRATOR**, select **Create Block Design**. - - (Optional) Change the design name to **system**. - - Click **OK**. - -4. Add MPSoC IP, and run block automation to configure it. - - - Right-click the Diagram view, and select **Add IP**. - - Search for `zynq`, and then double-click the **Zynq UltraScale+ MPSoC** from the IP search results. - - Click the **Run Block Automation** link to apply the board presets. - In the Run Block Automation dialog, ensure the following is marked: - - - All Automation - - Zynq_ultra_ps_e_0 - - Apply Board Presets - - - Click **OK**. You should get MPSoC block configured similar to the following: - - ![block_automation_result.png](./images/block_automation_result.png) - -**What Just Happened?** - -At this stage, the Vivado block automation has added an AMD Zynq™ UltraScale+™ MPSoC block and applied all board presets for the KV260. The presets includes MPSoC PS block configurations and pin assignments. - -### Customize System Design for Clock and Reset - -V++ linker can automatically link the clock signals between kernel and platform. The available clock signals in the platform are exported by **PFM.CLK** property. - -For simple designs, interrupt signals can be sourced by processor's **pl_clk**. The limitation is that the processor has maximum four `pl_clks` and their phase is not aligned. - -To supply more interrupt signals, or to supply phase aligned clocks, you can use **Clocking Wizard**. - -You will add the **Clocking Wizard** to the block diagram and enable clock signals for the platform. - -1. Add the clocking wizard block to generate three clocks: - - - Right-click Diagram view, and select **Add IP**. - - Search for, and add a **Clocking Wizard** from the IP Search dialog. - - Double-click the **clk_wiz_0** IP block to open the Re-Customize IP dialog box. - - Click the **Output Clocks** tab. - - Enable clk_out1 through clk_out3 in the Output Clock column. Set the **Requested Output Freq** as follows: - - - **clk_out1** to **100** MHz - - **clk_out2** to **200** MHz - - **clk_out3** to **400** MHz - - - At the bottom of the dialog box, set the **Reset Type** to **Active Low**. - - ![clock_settings.png](./images/clock_settings.png) - - - Click **OK** to close the dialog. - - >**NOTE:** Now you have set up the clock system for your design. This clock wizard uses the `pl_clk` as input clock and generates clocks needed for the whole logic design. In this straightforward design, you would use 100 MHz clock as the axi_lite control bus clock. 200 MHz and 400 MHz clocks are reserved for data-processing unit (DPU) AXI interface clock and DPU core clock during design linking phase. You are free to change the clock quantities and frequency to fit your target design. You will setup the clock export in future steps. First, you need to create reset signals for each clock because they are needed in clock export setup. - -1. Add three Processor System Reset blocks corresponding to the three clocks: - - - Right-click Diagram view, and select **Add IP**. - - Search for and add a **Processor System Reset** from the IP Search dialog. - - Rename the reset block to **proc_sys_reset_1** so that it is easy to understand the relationship between reset modules and the clock signals. - - Select the **proc_sys_reset_1** block, type Ctrl-C and Ctrl-V to replicate two modules. They are named as **proc_sys_reset_2** and **proc_sys_reset_3** by default. - -1. Connect the clocks and resets: - - - Click **Run Connection Automation**, which will open a dialog that will help connect the `proc_sys_reset` blocks to the clocking wizard clock outputs. - - Enable All Automation on the left side of the Run Connection Automation dialog box. - - Select **clk_in1** on `clk_wiz_0`, and set the Clock Source to **/zynq_ultra_ps_e_0/pl_clk0**. - - For each **proc_sys_reset** instance, select the **slowest_sync_clk**, and set the Clock Source as follows: - - - **proc_sys_reset_1** with **/clk_wiz_0/clk_out1** - - **proc_sys_reset_2** with **/clk_wiz_0/clk_out2** - - **proc_sys_reset_3** with **/clk_wiz_0/clk_out3** - - - On each `proc_sys_reset` instance, select the **ext_reset_in**, set **Board Part Interface** to **Custom**, and set the **Select Manual Source** to **/zynq_ultra_ps_e_0/pl_resetn0**. - - Make sure all checkboxes are enabled, and click **OK** to close the dialog and create the connections. - - Connect all the **dcm_locked** signals on each `proc_sys_reset` instance to the locked signal on **clk_wiz_0**. - - ![clk_rst_connection.png](./images/clk_rst_connection.png) - -1. Enable clocks for the platform - - - Go to **Platform Setup** tab. If it is not opened yet, select **Window -> Platform Setup** to open it. - - Click **Clock** tab - - Enable all clocks under clk_wiz_0: **clk_out1**, **clk_out2**, **clk_out3**. - - Change their ID to **0**, **1** and **2**. - - Set a default clock: click **Is Default** for **clk_out2**. - - After everything is setup, it should report **Info: No problem with Clock interface**. - - ![Platform Setup - Clock](images/platform_clock.png) - - >**NOTE:** There should be one and only one default clock in the platform. The v++ linker will use the default clock to connect the IP blocks if there are no user assignments for link configuration. - -### Add Interrupt Support - -The v++ linker can automatically link the interrupt signals between kernel and platform. The available interrupt signals in the platform are exported by **PFM.IRQ** property. - -For simple designs, interrupt signals can be sourced by processor's **pl_ps_irq**. The limitation is that it can only supply maximum 16 interrupt signals. To supply more interrupt signals, you can use **AXI Interrupt Controller**. You will enable **AXI HPM0 LPD** to control the **AXI Interrupt Controller**, add the **AXI Interrupt Controller** and enable interrupt signals for **PFM.IRQ**. - -1. Enable **AXI HPM0 LPD** to control the **AXI Interrupt Controller** - - - In the block diagram, double-click the **Zynq UltraScale+ MPSoC** block. - - Select **PS-PL Configuration > PS-PL interfaces > Master interface**. - - Enable the **AXI HPM0 LPD** option. - - Expand the arrow before **AXI HPM0 LPD**. Check the **AXI HPM0 LPD Data width** settings and keep it as default **32**. - - Disable **AXI HPM0 FPD** and **AXI HPM1 FPD** - - Click **OK** to finish the configuration. - - >**NOTE:** - > - >- Use **AXI HPM0 LPD** for controlling purpose. It would read and write 32-bit control registers. If the interface is more than 32, AXI Interconnect or SmartConnect will do AXI bus width conversion using PL logic. It would cost logic resource and introduce unnecessary latency. - > - Reserve **AXI HPM0 FPD** and **AXI HPM1 FPD** for kernel usage. Disabling them from the block diagram can prevent auto connection to use it by accident. You can export the unused AXI interfaces in Platform Setup, no matter it is visible in the block diagram or not. - -2. Add the **AXI Interrupt Controller** and configure it. - - - Right-click Diagram view, and select **Add IP**, search and add **AXI Interrupt Controller** IP. It is instantiated as **axi_intc_0**. - - Double-click the AXI Interrupt Controller block, change **Interrupt Output Connection** to **Single** so that it can be connected to PS IRQ interface. - - Click **OK**. - -3. Connect AXI Interfaces of `axi_intc_0` to AXI HPM0 LPD of PS. - - - Click **Run Connection Automation**. - - Review the settings (**axi_intc_0** is enabled, **s_axi** Master interface is to be connect to **/zynq_ultra_ps_e_0/M_AXI_HPM0_LPD**). - - Set **Clock Source for Slave Interface** and **Clock Source for Master Interface** to **/clk_wiz_0/clk_out2(200 MHz)**. - - Click **OK**. - - >**NOTE:** You wish interrupt controller and most kernel IRQ signals are synchronous to one clock. It is best for stability. But do not worry about the asynchronous IRQ if kernels are running at different clocks. The interrupt controller can manage asynchronous IRQ with level interrupt signals as well. - -4. Connect irq of the Interrupt Controller - - - Connect **axi_intc_0.irq** to **zynq_ultra_ps_e_0.pl_ps_irq[0:0]** - - The IPI design connection would like the following until now: - - ![ipi_fully_connection.png](./images/ipi_fully_connection.png) - - > **NOTE:** If you have more than one `irq` signals to connect to `pl_ps_irq` of PS, use a **concat** IP to concatenate them to a bus and then connect the bus to `pl_ps_irq`. - -5. Enable interrupt signals for the platform. - - - Go to the Platform Setup tab. - - Go to the Interrupt tab. - - Enable intr under axi_intc_0. - -### Enable AXI Interfaces for the Platform - -1. Enable AXI Master interfaces from the processing system (PS). - - - Go to **Platform Setup** tab. - - Go to **AXI Port** tab in Platform Setup. - - Under **zynq_ultra_ps_e_0**, enable **M_AXI_HPM0_FPD** and **M_AXI_HPM1_FPD**. Keep the Memport and sptag default to M_AXI_GP and empty. - - >**NOTE:** - > - >- M_AXI_GP means general purpose AXI Master interface. - >- sptag is only applicable to AXI slave interfaces. - >- The v++ linker will instantiate AXI Interconnect automatically to connect between PS AXI Master interfaces and slave interfaces of acceleration kernels. One AXI Master interface will connect up to 16 kernels. - -2. Enable AXI Master interfaces from AXI Interconnect. - - - Under ps8_0_axi_periph, click M01_AXI, press Shift and click M07_AXI to multi-select master interfaces from M01_AXI to M07_AXI. - - Right click the selection and click on **Enable**. - - Keep the Memport and sptag default to M_AXI_GP and empty. - - >**NOTE:** - > - >- v++ will not cascade another level of AXI Interconnect if the AXI master interface is exported from AXI Interconnect IP. - >- AXI Master interfaces from PS and AXI Interconnect are functionally equivalent to the platform. - >- In general, platform designer should export as many as AXI interfaces to the platform. The application developer should decide which interface to use. - -3. Enable AXI Slave interfaces from PS to allow kernels access DDR memory. - - - Under zynq_ultra_ps_e_0, multi-select all AXI slave interfaces: press **Ctrl** and click **S_AXI_HPC0_FPD**, **S_AXI_HPC1_FPD**, **S_AXI_HP0_FPD**, **S_AXI_HP1_FPD**, **S_AXI_HP2_FPD**, **S_AXI_HP3_FPD**. - - Right click the selections and select **enable**. - - Change Memport of **S_AXI_HPC0_FPD** and **S_AXI_HPC1_FPD** to **S_AXI_HP** because we will not use any coherent features for these interfaces. - - Type in simple sptag names for these interfaces so that they can be selected by v++ configuration during linking phase. **HPC0**, **HPC1**, **HP0**, **HP1**, **HP2**, **HP3**. - - ![Platform Setup - AXI Ports](images/platform_setup_interfaces.png) - -### Modify the IP address in address editor (Optional) - - >Note: This step is not mandatory for platform creation. Please refer to it according to your requirement. - - If users need to modify the IP address please go through following steps. - 1. Check the location address space of your IP - 2. Go to address editor by clicking **Window**-> **Address editor** to open it. - - Next, we will use the example of modifying the interrupt controller IP address to illustrate how to modify the IP address in the address editor. - - - As the interrupt controller is connected with **M_AXI_HPM0_LPD** domain, we need check LPD domain supported address space. Please check the [ZYNQMP Technical Reference Manual](https://docs.amd.com/r/en-US/ug1085-zynq-ultrascale-trm/PL-AXI-Interface). You could find following address range. That means the IP connected to LPD domain could be placed in 0x8000_0000-0x9FFF_FFFF address space. But conflict is not allowed. - - ![Platform Setup - AXI Ports](images/LPD.PNG) - - - Go to address editor, modify the interrupt controller IP base address according to your requirement. - - ![Platform Setup - AXI Ports](images/address.PNG) - - >Note: The modified base address should be in the LPD address space and the high address should also be in the LPD address space. -### Export Hardware XSA - -1. Validate the block design - - - Click the **Validate Design** button in the block design Diagram window - - **Note**: During validation, Vivado reports a critical warning that **/axi_intc_0/intr** is not connected. This warning can be safely ignored because v++ linker will link kernel interrupt signals to this floating intr signal. - - ```bash - CRITICAL WARNING: [BD 41-759] The input pins (listed below) are either not connected or do not have a source port, and they do not have a tie-off specified. These pins are tied-off to all 0's to avoid error in Implementation flow. - Please check your design and connect them as needed: - /axi_intc_0/intr - ``` - -2. Create a top module wrapper for the block design. - - - In **Source** tab, right click **system.bd** in Design Sources group - - Select **Create HDL Wrapper...**. - - Select **Let Vivado manage wrapper and auto-update**. - - Click **OK** to generate wrapper for block design. - -3. Generate the design. - - - Select **Generate Block Design** from Flow Navigator. - - Select **Synthesis Options** to **Global**. It will skip IP synthesis during generation. - - Click **Generate**. - - Click **Generate Bitstream** in Flow Navigator window. - - Click **Yes**. - -4. Export the platform. - - - Click menu **File -> Export -> Export Platform** to launch the **Export Hardware Platform** wizard. This wizard can also be launched by **Export Platform** button in **Flow Navigator** or **Platform Setup** window. - - Click Next in the first information page. - - Select Platform Type: **Hardware and Hardware Emulation**, click Next. If you skipped the emulation setup previously, select **Hardware** here. - - Select Platform State: **Pre-synthesis**, enable **Include Bitstream**, click Next - - Input Platform Properties and click **Next**. For example, - - Name: kv260_hardware_platform - - Vendor: xilinx - - Board: kv260 - - Version: 0.0 - - Description: This platform provides high PS DDR bandwidth and three clocks: 100MHz, 200MHz and 400MHz. - - Fill in XSA file name: **kv260_hardware_platform** and keep the export directory as default. - - Click **Finish**. **kv260_hardware_platform.xsa** will be generated. The export path is reported in the Tcl console. - - >**NOTE:** You enable Include Bitstream to fulfill the requirement of the `fpga-manager-util` package in PetaLinux. - - Alternatively, the above export can be done in Tcl scripts - - ```tcl - # Setting platform properties - set_property platform.default_output_type "sd_card" [current_project] - set_property platform.design_intent.embedded "true" [current_project] - set_property platform.design_intent.server_managed "false" [current_project] - set_property platform.design_intent.external_host "false" [current_project] - set_property platform.design_intent.datacenter "false" [current_project] - # Write pre-synthesis expandable XSA - write_hw_platform -include_bit -force -file ./kv260_hardware_platform.xsa - ``` - -### Next Step - -Now you finish the Hardware platform creation flow, then you should go to the [Step 2: Vitis Platform Creation](./step2.md) - -

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diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/step2.md b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/step2.md deleted file mode 100644 index 3bfab326d7..0000000000 --- a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/step2.md +++ /dev/null @@ -1,186 +0,0 @@ - - - - -
- - - AMD logo - -

AMD Vitis™ Platform Creation Tutorials

- See Vitis™ Development Environment on amd.com -
-# Step 2: Create the Vitis Platform - -In this step, you will create a Vitis platform running a Linux operation system. The Vitis platform requires several software components which need to be prepared in advance. Due to the boot flow differences between KV260 and base platforms for AMD evaluation boards like ZCU104, platform developer needs to prepare one additional DTBO file besides the normal software components for Vitis platforms because device tree file of programmable logic (PL) side depends on the hardware design and is loaded after Linux boots up. In addition, application developers need to add this DTBO file to the application deployment package as well. The other software components generation flow is similar to the flow described in the [ZCU104 tutorial](../02-Edge-AI-ZCU104/step2.md). However, in this case, the valuable software component is sysroot,which is used for host application cross-compilation. So you will go on utilizing the common image which provides the sysroot and expedite the process of platform creation. - -### Prepare the Common Image - -1. Download common image from [Xilinx website download page.](https://www.xilinx.com/support/download.html). Go to the **WorkSpace** folder you created in step 1, and place the image package in **WorkSpace** folder. - - ```bash - cd WorkSpace - tree -L 1 # to see the directory hierarchy - ├── kv260_hardware_platform - └── xilinx-zynqmp-common-v2025.1.tar.gz - ``` - -2. Extract the common image. - - - ```bash - cd WorkSpace - tar xvf ../xilinx-zynqmp-common-v2025.1.tar.gz -C . - ``` - - You can see **xilinx-zynqmp-common-v2025.1** folder which contains the components located in **WrokSpace** folder. - - ```bash - tree -L 2 - ├── xilinx-zynqmp-common-v2025.1 - │   ├── bl31.elf - │   ├── boot.scr - │   ├── Image - │   ├── README.txt - │   ├── rootfs.ext4 - │   ├── rootfs.manifest - │   ├── rootfs.tar.gz - │   ├── sdk.sh - │   └── u-boot.elf - ``` - -From the above picture, you can see SDK tool and other components are ready. - -### Generate Software Components from the KV260 Starter Kit BSP(Optional) - -If you need to do system customization, take the following steps as reference. For more advanced tweaks, like kernel or uboot customization, refer to the [PetaLinux customization page](../../Feature_Tutorials/02_petalinux_customization/README.md) for reference. - -
- -Click for Detailed Steps - -1. Check the [AMD Kria™ K26 SOM wiki](https://xilinx-wiki.atlassian.net/wiki/spaces/A/pages/1641152513/Kria+K26+SOM), and download the BSP package from the following link: - - Save it to **WorkSpace** directory. - -2. Set up the PetaLinux environment. - - ```bash - cd WorkSpace - mkdir kv260_petalinux - cd kv260_petalinux - source /settings.sh - ``` - -3. Update the PetaLinux eSDK to enable the recipes needed by the Starter Kit SOM BSP. - - ```bash - petalinux-upgrade -u 'http://petalinux.xilinx.com/sswreleases/rel-v2004/sdkupdate/' -p 'aarch64' - ``` - -4. Create PetaLinux with the Starter Kit SOM BSP, and the XSA export from step 1. - - ```bash - petalinux-create --type project -s xilinx-kv260-starterkit-v2024.1-final.bsp - cd xilinx-kv260-starterkit-2024.1 - petalinux-config --get-hw-description= --silent - ``` - -5. Add XRT to rootfs. - - KV260 PetaLinux BSP does not enable Xilinx Runtime (XRT) because it installs XRT with an overlay. To create sysroot for application developer cross compiling, enable XRT in the rootfs. All the XRT required libraries are packaged into one group. - - - Run `petalinux-config -c rootfs` to launch rootfs configuration window. - - Go to **Petalinux Package Groups -> packagegroup-petalinux-vitis-acceleration-essential**. - - Enable `packagegroup-petalinux-vitis-acceleration-essential` and `packagegroup-petalinux-vitis-acceleration-dbg`. - - Press **Exit** to exit configuration. Press Save to save the configuration. - -6. Build PetaLinux and generate SDK. - - ```bash - petalinux-build - petalinux-build --sdk - ``` - - The PetaLinux image files and sysroot sdk.sh will be generated in `/images/linux` directory. You will use them in the next step. - -
- -### Create the Vitis Platform - -1. Install sysroot. - - - Go to `` directory. - - Type `./sdk.sh -d ` to install PetaLinux SDK. Use the `-d` option to provide a full pathname to the output directory. For example: `./sdk.sh -d .`. **.** means the current directory. - >**NOTE:** The environment variable **LD_LIBRARY_PATH** must not be set when running this command. - - - >Note: Sysroot is not mandatory components for the platform itself. It is the cross compile tool prepared for applications compilation. - -2. Create a Vitis platform. - - For this example, you will use the Vitis Unifeid IDE to create the Vitis Platform. Got to `WorkSpace` directory and follow steps below to create the platform. - - 1. Run Vitis by typing `vitis -w .` in the console. `-w` is to specify the workspace. `.` means the current workspace directory. - 2. In the Vitis Unified IDE, from menu select **File > New Component > Platform** to create a platform component. - 3. On the **Create Platform Component** setup dialog - - Enter the component name and location. For this example, type `kv260_custom` and use default location. Click **Next**. - - Click **Browse** button, select the XSA file generated by the Vivado. In this case, it is `kv260_hardware_platform.xsa`. - - Expand the **Advanced Options** and set the items as following: - - ![Created Vitis Platform](images/platform_generation_dts.jpg) - - SDT Source Repo: This is used to replace the built-in SDT tool. For this tutorial, leave it empty. - - Board DTSI: Specify the board machine name, which is used to retrieve the board-level DTSI file. For this tutorial, leave it empty. To check the board machine name, refer to [UG1144 Machine Name Checking](https://docs.amd.com/r/en-US/ug1144-petalinux-tools-reference-guide/Importing-a-Hardware-Configuration) - - User DTSI: Allows you to specify a custom DTSI file. For this tutorial, leave it empty. - - DT ZOCL: Enables Zocl node generation for the XRT driver. Ensure this option is enabled, then click **Next**. - - Set the operating system to **Linux**.
- - Set the processor to **psu_cortexa53**.
- - Check the option **Generate boot artifacts**. Then click **Next**.
- >Note: Enabling this option will trigger the tool to automatically generate a PMU firmware domain and an FSBL (First Stage Boot Loader) domain into the platform - - Enable and expand the **Generate Device Tree Blob (DTB)** option, and check the **DT Overlay** option. This option is used to generrate DTB and device tree blob overlay for SOM application. Then click **Next**.
- - Review the summary and click **Finish**. - >Note: After a few moments, the platform component will be prepared and available in the component view. Simultaneously, the platform configuration file, `vitis-comp.json`, will be automatically displayed in the main view. Users can access the `vitis-comp.json` file by expanding the Settings section under the platform component. - -3. Set up the software settings in the Platform configuration view by clicking the **Linux On psu_cortexa53** domain, browse to the locations and select the directory or file needed to complete the dialog box for the following: - - - **Display Name**: update it as `xrt` - - **Bif file**: Click the button to generate bif file or click **Browse** to select existing bif file. - - >**Note:** The filenames in `<>` are placeholders in the bif file. Vitis will replace the placeholders with the relative path to platform during platform packaging. V++ packager, which runs when building the final application#, would expand it further to the full path during image packaging. Filename placeholders point to the files in boot components directory. The filenames in boot directory need to match with placeholders in BIF file. `` is a reserved keyword. V++ packager will replace it with the final system bit file. - - - **Pre-Built Image Directory**: Browse to **xilinx-zynqmp-common-v2025.1** and click **OK**. - - - **DTB File**: It will be generated automatically and populated in this area. Then click **OK**. - >Note: If the directory you specified for Pre-build image directory already contains DTB file, this DTB field will be automatically updated. - - - **FAT32 Partition Directory**: This directory is used to add additional file to the fat32 partition. User can set it according to your requirement. - - - **QEMU Data**: This Directory is used to add additional file for emulation. User can set it accordingly. - - ![vitis_linux_config.PNG](./images/vitis_linux_config.png) - - >**Note:**: **Qemu Args File** and **Pmu Args File** are populated by the tool automatically. If there are additional QEMU settings, please update it accordingly. - -4. Select **kv260_custom** platform component in the flow navigator, then click the **Build** button to build the platform. - - ![missing image](./images/build_vitis_platform.png) - - >**Note:** The generated platform is placed in the export directory. BSP and source files are also provided for rebuilding the FSBL, if required, and are associated with the platform. The platform is ready to be used for application development. - - ![missing image](./images/vitis_platform_output.png) - - >Note: Once the compilation is complete, users can find the XPFM file by expanding the Output directory, which offers a structured view of the output. The actual file path of platform file is located in the `WorkSapce/kv260_custom/export/kv260_custom/` directory. Additionally, users can access the full path of the platform file by hovering the mouse pointer over the XPFM file. - - >Note: The Vitis Unified IDE will find the boot-related files mentioned in the software components in begin of this step from Pre-buit image directory and place them in the boot folder of the platform. - - If you create a Vitis application component in the same workspace as this platform component, you can find this platform available in the platform selection page in the application Creation wizard. If you want to reuse this platform in another workspace, add its path to the `PLATFORM_REPO_PATHS` environment variable before launching the Vitis GUI, or use the "Add" button on the platform selection page of the Vitis GUI to add its path. - - - -### Next Step - -Next, try to [build applications on this platform and test them.](./step3.md) - -

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diff --git a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/step3.md b/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/step3.md deleted file mode 100644 index 09eb393430..0000000000 --- a/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/step3.md +++ /dev/null @@ -1,259 +0,0 @@ - - - - -
- - - AMD logo - -

AMD Vitis™ Platform Creation Tutorials

- See Vitis™ Development Environment on amd.com -
- -# Step 3: Test the Platform - -- [Step 3: Test the Platform](#step-3-test-the-platform) - - [Test 1: Read Platform Info](#test-1-read-platform-info) - - [Test 2: Run Vector Addition Application](#test-2-run-vector-addition-application) - - [Congratulations](#congratulations) - - [Fast Track](#fast-track) - - [Next Steps](#next-steps) - -## Test 1: Read Platform Info - -With the Vitis environment setup, the **platforminfo** tool can report XPFM platform information. - -
- -Click for detailed logs - -```bash -# in kv260_custom_pkg directory -platforminfo ./kv260_custom/export/kv260_custom/kv260_custom.xpfm -========================== -Basic Platform Information -========================== -Platform: kv260_custom -File: /Vitis-Tutorials/Vitis_Platform_Creation/Design_Tutorials/01-Edge-KV260/ref_files/step2_pfm/kv260_custom/export/kv260_custom/kv260_custom.xpfm -Description: - -===================================== -Hardware Platform (Shell) Information -===================================== -Vendor: xilinx -Board: kv260_hardware_Platform -Name: kv260_hardware_Platform -Version: 0.0 -Generated Version: 2025.1 -Hardware: 1 -Software Emulation: 1 -Hardware Emulation: 1 -Hardware Emulation Platform: 0 -FPGA Family: zynquplus -FPGA Device: xck26 -Board Vendor: xilinx.com -Board Name: xilinx.com:kv260_som:1.4 -Board Part: xck26-sfvc784-2LV-c - -================= -Clock Information -================= - Default Clock Index: 1 - Clock Index: 0 - Frequency: 99.999000 - Clock Index: 1 - Frequency: 199.998000 - Clock Index: 2 - Frequency: 399.996000 - -================== -Memory Information -================== - Bus SP Tag: HP0 - Bus SP Tag: HP1 - Bus SP Tag: HP2 - Bus SP Tag: HP3 - Bus SP Tag: HPC0 - Bus SP Tag: HPC1 - -============================= -Software Platform Information -============================= -Number of Runtimes: 1 -Default System Configuration: kv260_custom -System Configurations: - System Config Name: kv260_custom - System Config Description: - System Config Default Processor Group: linux_psu_cortexa53 - System Config Default Boot Image: standard - System Config Is QEMU Supported: 1 - System Config Processor Groups: - Processor Group Name: linux_psu_cortexa53 - Processor Group CPU Type: cortex-a53 - Processor Group OS Name: xrt - System Config Boot Images: - Boot Image Name: standard - Boot Image Type: - Boot Image BIF: boot/linux.bif - Boot Image Data: linux_psu_cortexa53/image - Boot Image Boot Mode: - Boot Image RootFileSystem: - Boot Image Mount Path: - Boot Image Read Me: - Boot Image QEMU Args: qemu/pmu_args.txt:qemu/qemu_args.txt - Boot Image QEMU Boot: - Boot Image QEMU Dev Tree: -Supported Runtimes: - Runtime: C/C++ -``` - -
- -You can verify clock information and memory information are set as expected. - -### Test 2: Run Vector Addition Application - -Vector addition is the simplest acceleration PL kernel. Vitis Unified IDE can create this application automatically. Running this test can check the AXI control bus, memory interface, and interrupt setting in platform are working properly. - -1. Create a Vector Addition Application. - - - Go to `WorkSpace` directory created in step1 - - Run Vitis by typing `vitis -w .` in the console. `-w` is to specify the workspace. `.` means the current workspace directory. Close the welcome tab after Vitis launches. - - Go to example view by clicking the example button and click **Simple Vector Addition**. - - ![example.PNG](./images/example.PNG) - - - Click **Create Application from Template**. The project creation wizard would pop up. - - Input the **System project name** as `vadd` and use the default location for **System project location**. Then click **Next**. - - Select **kv260_custom** platform, click **Next**. - >Note: If the platform component is not in the current workspace user could click **+** button to add the platform component. - - Set **Sysroot** to ```xilinx-zynqmp-common-v2025.1/sysroots/cortexa72-cortexa53-amd-linux```. Then click **Next**. - - Review the summary of your `vadd` system project and click **Finish**. - - >**NOTE:** In this step, the addition of the kernel image and rootfs is omitted since it is recommended to use the official sd_card.img from AMD's download center. Furthermore, V++ does not incorporate the kernel image and rootfs in the generation of the sd_card.img for the SOM. - - After seconds the vadd system project, vadd host component and vadd kernel component will be ready in the component view. - -2. Building Vector Addition Application - - Vadd system project supports three targets: Software emulation, Hardware emulation and Hardware. User could select the target accordingly following steps below. As SOM has different development flow, we will only generate XCLBIN file and host application for hardware. - - - Navigate to the Flow Navigator, select vadd system project, then expand the **LINK-binary_container_1** under **HARDWARE** target. - - ![build_application.PNG](./images/build_binary.PNG) - - - Click **Build Binary Container** - - >Note: Once the compilation is complete, users can find the `binary_container_1.xclbin` by expanding the Output directory, which offers a structured view of the output. The actual file path of `binary_container_1.xclbin` is located in the `WorkSpace/vadd/build/hw/hw_link/` directory. Additionally, users can access the full path of the `binary_container_1.xclbin` file by hovering the mouse pointer over the image file. - - - - Navigate to the Flow Navigator, select the vadd_host application component, and then click **Build** under the **HARDWARE** target.. - - ![build_application.PNG](./images/build_component.PNG) - - >Note: Once the compilation is complete, users can find the `vadd_host` executable file by expanding the Output directory, which offers a structured view of the output. The actual file path of `vadd_host` is located in the `WorkSpace/vadd_host/build/hw/` directory. Additionally, users can access the full path of the `vadd_host` file by hovering the mouse pointer over the image file. - -3. Prepare the files to be transferred to the board. - - The AMD Kria™ SOM uses `xmutil` to load applications dynamically. The load process includes downloading binary file and loading device tree overlay. `xmutil` requires the application files to be stored in `/lib/firmware/xilinx` directory. - - The files related to this application need to have specified extensions. They are `dtbo`, `bin`, and `json`. Therefore, the final content in the directory on the board would look like the following. - - ```bash - # On target board - ls /lib/firmware/xilinx/vadd - pl.dtbo #DTB overlay file - binary_container_1.bin #Acceleration binary container for XRT configuration. Also includes system.bit and metadata that describes the kernels. - shell.json #Description file - ``` - - The `dtbo` file is prepared in step 2 in the `dtg_output` folder. `Binary_container_1.bin` can be renamed from `binary_container_1.xclbin`. For `shell.json`, you can copy it from other applications or create one with the following contents. - - ```json - { - "shell_type" : "XRT_FLAT", - "num_slots": "1" - } - ``` - -4. Transfer the files to the board. - - Make sure the Ethernet cable of SOM Starter Kit is connected. Use SCP or SFTP to upload the files from host to target board. - - ```bash - # Running on host machine - scp pl.dtbo binary_container_1.bin shell.json vadd_host petalinux@:/home/petalinux - ``` - -5. Load the hardware. - - ```bash - # Running on target board - sudo mkdir /lib/firmware/xilinx/vadd - cd /home/petalinux - cp pl.dtbo binary_container_1.bin shell.json /lib/firmware/xilinx/vadd - sudo xmutil listapps - sudo xmutil unloadapp - sudo xmutil loadapp vadd - ``` - - If the application required files are loaded successfully, the following log is expected: - - ```bash - Nov 8 06:20:28 xilinx-kv260-starterkit-20242 kernel: OF: overlay: WARNING: memory leak will occur if overlay removed, property: /fpga-full/firmware-name - Nov 8 06:20:28 xilinx-kv260-starterkit-20242 kernel: OF: overlay: WARNING: memory leak will occur if overlay removed, property: /fpga-full/pid - Nov 8 06:20:28 xilinx-kv260-starterkit-20242 kernel: OF: overlay: WARNING: memory leak will occur if overlay removed, property: /fpga-full/resets - Nov 8 06:20:28 xilinx-kv260-starterkit-20242 kernel: OF: overlay: WARNING: memory leak will occur if overlay removed, property: /fpga-full/uid - Nov 8 06:20:28 xilinx-kv260-starterkit-20242 kernel: OF: overlay: WARNING: memory leak will occur if overlay removed, property: /__symbols__/afi0 - Nov 8 06:20:28 xilinx-kv260-starterkit-20242 kernel: OF: overlay: WARNING: memory leak will occur if overlay removed, property: /__symbols__/clocking0 - Nov 8 06:20:28 xilinx-kv260-starterkit-20242 kernel: OF: overlay: WARNING: memory leak will occur if overlay removed, property: /__symbols__/clocking1 - Nov 8 06:20:28 xilinx-kv260-starterkit-20242 kernel: OF: overlay: WARNING: memory leak will occur if overlay removed, property: /__symbols__/axi_intc_0 - Nov 8 06:20:28 xilinx-kv260-starterkit-20242 kernel: OF: overlay: WARNING: memory leak will occur if overlay removed, property: /__symbols__/misc_clk_0 - Nov 8 06:20:28 xilinx-kv260-starterkit-20242 kernel: irq-xilinx: mismatch in kind-of-intr param - Nov 8 06:20:28 xilinx-kv260-starterkit-20242 kernel: zocl-drm axi:zyxclmm_drm: error -ENXIO: IRQ index 32 not found - vadd: loaded to slot 0 - ``` - -5. Running vector addition application on the board. - - - Run vadd application. - - ```bash - chmod +x ./vadd_host - ./vadd_host binary_container_1.bin - ``` - - - It should show program prints. - - ``` - xilinx-k26-starterkit-20242:~$ ./vadd_host binary_container_1.bin - INFO: Reading binary_container_1.bin - Loading: 'binary_container_1.bin' - TEST PASSED - ``` - -> **NOTE:** If you get errors like "error while loading shared libraries: libxilinxopencl.so.2: cannot open shared object file: No such file -or directory", it is because XRT is not installed in KV260 default rootfs. Run `sudo dnf install xrt` to install XRT. - -### Congratulations - -You have completed creating a custom platform from scratch and verifying it with a simple vadd application. - -Feel free to check more tutorials in this repository. - -### Fast Track - -If you encounter any issues when creating the custom platform and the validation application in this tutorial, you can run `make all COMMON_IMAGE_ZYNQMP=` in the `ref_files` directory to generate the reference design and compare with your design. COMMON_IMAGE_ZYNQMP is a flag to specify the common image path. Please download common image from [Xilinx website download page](https://www.xilinx.com/support/download.html) and give the path to the flag. - -The command line flow has slight differences comparing to Vitis IDE flow. - -- The vector addition application is called `vadd_host` and `binary_container_1.xclbin` in Vitis Unified IDE flow. The generated files in command line flow are called `simple_vadd` and `krnl_vadd.xclbin`. - -### Next Steps - -If user need to do iteration for your project, you could go through the [Iteration Guidelines](./Iteration_guideline.md) to do iterations. - -

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diff --git a/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/README.md b/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/README.md index bd9bdbf0ec..37a640be0c 100644 --- a/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/README.md +++ b/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/README.md @@ -13,7 +13,7 @@ # Vitis Custom Embedded Platform Creation Example on ZCU104 -***Version: Vitis 2025.1 and Vivado 2025.1*** +***Version: Vitis 2025.2 and Vivado 2025.2*** In this module, you will create a custom Vitis embedded platform for ZCU104 capable of running ***Vitis acceleration applications***. Additionally, this platform is versatile enough to support general **embedded software applications**. The diagram below illustrates the structure of this example system. diff --git a/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/ref_files/Makefile b/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/ref_files/Makefile index 7c6cff7223..21ea6cf2e9 100755 --- a/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/ref_files/Makefile +++ b/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/ref_files/Makefile @@ -5,7 +5,7 @@ XSA=step1_vivado/build/vivado/zcu104_custom_platform_hw.xsa XPFM=step2_pfm/zcu104_custom/export/zcu104_custom/zcu104_custom.xpfm -VERSION ?=2025.1 +VERSION ?=2025.2 COMMON_IMAGE_ZYNQMP ?=${PLATFORM_REPO_PATHS}/sw/zynqmp/xilinx-zynqmp-common-v$(VERSION)/ TARGET= .PHONY: help diff --git a/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/ref_files/step2_pfm/Makefile b/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/ref_files/step2_pfm/Makefile index 609043aa05..8d3c572cce 100644 --- a/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/ref_files/step2_pfm/Makefile +++ b/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/ref_files/step2_pfm/Makefile @@ -6,7 +6,7 @@ ROOT_DIR=$(realpath $(dir $(lastword $(MAKEFILE_LIST)))) XSA_NAME=zcu104_custom_platform PLATFORM_NAME=zcu104_custom -VERSION=2025.1 +VERSION=2025.2 COMMON_IMAGE_ZYNQMP ?=${PLATFORM_REPO_PATHS}/sw/zynqmp/xilinx-zynqmp-common-v$(VERSION)/ DTB=$(ROOT_DIR)/mydevice/psu_cortexa53_0/device_tree_domain/bsp/system.dtb SYSROOT=$(ROOT_DIR)/sysroot diff --git a/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/ref_files/step3_validate/Makefile b/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/ref_files/step3_validate/Makefile index 2eb986d82f..13d720d2bd 100755 --- a/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/ref_files/step3_validate/Makefile +++ b/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/ref_files/step3_validate/Makefile @@ -9,7 +9,7 @@ PLATFORM ?= $(ROOT_DIR)/../step2_pfm/ws/$(PLATFORM_NAME)/export/$(PLATFORM_NAME) TARGET ?=hw_emu COMMON_IMAGE_ZYNQMP ?=${PLATFORM_REPO_PATHS}/sw/zynqmp/xilinx-zynqmp-common-v$(VERSION)/ SRC=$(XILINX_VITIS)/samples/vadd/ -VERSION=2025.1 +VERSION=2025.2 SYSROOT := $(COMMON_IMAGE_ZYNQMP)/sysroots/cortexa72-cortexa53-amd-linux SD_IMAGE_FILE := $(COMMON_IMAGE_ZYNQMP)/Image VPP_LDFLAGS := diff --git a/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/step2.md b/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/step2.md index 2dbd62fb1e..bdae2a67ec 100644 --- a/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/step2.md +++ b/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/step2.md @@ -48,7 +48,7 @@ As most of the components are extracted from the common image package, we will p cd WorkSpace tree -L 1 # to see the directory hierarchy . - ├── xilinx-zynqmp-common-v2025.1.tar.gz + ├── xilinx-zynqmp-common-v2025.2.tar.gz └── zcu104_custom_platform ``` @@ -58,14 +58,14 @@ As most of the components are extracted from the common image package, we will p ```bash cd WorkSpace - tar xvf xilinx-zynqmp-common-v2025.1.tar.gz -C . + tar xvf xilinx-zynqmp-common-v2025.2.tar.gz -C . ``` -You can see the ``xilinx-zynqmp-common-v2025.1`` folder which contains some components located in the ``WorkSpace`` folder as shown below: +You can see the ``xilinx-zynqmp-common-v2025.2`` folder which contains some components located in the ``WorkSpace`` folder as shown below: ``` tree -L 2 - ├── xilinx-zynqmp-common-v2025.1 + ├── xilinx-zynqmp-common-v2025.2 │   ├── bl31.elf │   ├── boot.scr │   ├── Image @@ -83,7 +83,7 @@ From the above directory structure, you can see that the boot file, kernel image 1. Install the sysroot - - Go to common image extracted directory ``. + - Go to common image extracted directory ``. - Type ``./sdk.sh -d `` to install the PetaLinux SDK. Use the `-d` option to provide a full pathname to the output directory **.** (This is an example. **.** means current directory. ) and confirm. The environment variable **LD_LIBRARY_PATH** must not be set when running this command. @@ -124,7 +124,7 @@ From the above directory structure, you can see that the boot file, kernel image >**Note:** The filenames in `<>` are placeholders in the bif file. Vitis will replace the placeholders with the relative path to platform during platform packaging. V++ packager, which runs when building the final application#, would expand it further to the full path during image packaging. Filename placeholders point to the files in boot components directory. The filenames in boot directory need to match with placeholders in BIF file. `` is a reserved keyword. V++ packager will replace it with the final system bit file. - - **Pre-Built Image Directory**: Browse to **xilinx-zynqmp-common-v2025.1** and click **OK**. + - **Pre-Built Image Directory**: Browse to **xilinx-zynqmp-common-v2025.2** and click **OK**. - **DTB File**: It will be generated automatically and populated in this area. diff --git a/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/step3.md b/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/step3.md index f246cae67b..8baa097259 100644 --- a/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/step3.md +++ b/Vitis_Platform_Creation/Design_Tutorials/02-Edge-AI-ZCU104/step3.md @@ -137,9 +137,9 @@ Vector addition is the simplest acceleration PL kernel. The Vitis Unified IDE ca - Input the **System project name** as `vadd` and use the default location for **System project location**. Then click **Next**. - Select **zcu104_custom** platform, click **Next**. >Note: If the platform component is not in the current workspace user could click **+** button to add the platform component. - - Set **Kernel Image** to ```xilinx-zynqmp-common-v2025.1/Image```. - - Set **Root FS** to ```xilinx-zynqmp-common-v2025.1/rootfs.ext4```. - - Set **Sysroot** to ```zcu104_software_platform/xilinx-zynqmp-common-v2025.1/sysroots/cortexa72-cortexa53-amd-linux```. Then click **Next**. + - Set **Kernel Image** to ```xilinx-zynqmp-common-v2025.2/Image```. + - Set **Root FS** to ```xilinx-zynqmp-common-v2025.2/rootfs.ext4```. + - Set **Sysroot** to ```zcu104_software_platform/xilinx-zynqmp-common-v2025.2/sysroots/cortexa72-cortexa53-amd-linux```. Then click **Next**. - Review the summary of your `vadd` system project and click **Finish**. After seconds the vadd system project, vadd host component and vadd kernel component will be ready in the component view. diff --git a/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/README.md b/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/README.md index 39fad9f9fb..4690e5e873 100644 --- a/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/README.md +++ b/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/README.md @@ -13,7 +13,7 @@ # Versal Custom Platform Creation Tutorial -***Version: 2025.1*** +***Version: 2025.2*** In this module, we treat the VCK190 board as a customized solution tailored to our customer's specific needs. We leverage the AMD Versal™ Adaptive SoC Extensible Part Support Example Design, a pre-built Linux common image, and the Device Tree Blob generated during the platform creation process to produce essential software components. These components form the foundation of a dedicated embedded Versal acceleration platform tailored for the customer’s board. Finally, you will test this platform by running several applications. diff --git a/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/ref_files/Makefile b/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/ref_files/Makefile index 88d3b41085..845ae0163d 100644 --- a/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/ref_files/Makefile +++ b/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/ref_files/Makefile @@ -5,7 +5,7 @@ XSA=step1_vivado/build/vivado/custom_hardware_platform_hw.xsa XPFM=step2_pfm/custom_platform/export/custom_platform/custom_platform.xpfm -VERSION ?=2025.1 +VERSION ?=2025.2 COMMON_IMAGE_VERSAL ?=${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v$(VERSION)/ .PHONY: help diff --git a/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/ref_files/step2_pfm/Makefile b/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/ref_files/step2_pfm/Makefile index 2a94580e35..f0949f04aa 100644 --- a/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/ref_files/step2_pfm/Makefile +++ b/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/ref_files/step2_pfm/Makefile @@ -4,7 +4,7 @@ #*/ ROOT_DIR=$(realpath $(dir $(lastword $(MAKEFILE_LIST)))) -VERSION=2025.1 +VERSION=2025.2 COMMON_IMAGE_VERSAL ?=${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v$(VERSION)/ SYSROOT=$(ROOT_DIR)/sysroot XSA_PATH=$(ROOT_DIR)/../step1_vivado/build/vivado/ diff --git a/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/ref_files/step3_application/Makefile b/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/ref_files/step3_application/Makefile index 6e41a5e11f..2428b9b64e 100644 --- a/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/ref_files/step3_application/Makefile +++ b/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/ref_files/step3_application/Makefile @@ -7,7 +7,7 @@ ROOT_DIR=$(realpath $(dir $(lastword $(MAKEFILE_LIST)))) PLATFORM_NAME=custom_platform PLATFORM = $(ROOT_DIR)/../step2_pfm/ws/$(PLATFORM_NAME)/export/$(PLATFORM_NAME)/$(PLATFORM_NAME).xpfm -VERSION=2025.1 +VERSION=2025.2 COMMON_IMAGE_VERSAL ?=${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v$(VERSION)/ SYSROOT=$(COMMON_IMAGE_VERSAL)/sysroots/cortexa72-cortexa53-amd-linux/ diff --git a/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/step2.md b/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/step2.md index af1a4fedde..7ef391d087 100644 --- a/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/step2.md +++ b/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/step2.md @@ -41,7 +41,7 @@ As most of the components are extracted from the common image package, we will p tree -L 1 # to see the directory hierarchy . ├── custom_hardware_platform - └── xilinx-versal-common-v2025.1.tar.gz + └── xilinx-versal-common-v2025.2.tar.gz ``` 2. Extract the common image. @@ -50,15 +50,15 @@ As most of the components are extracted from the common image package, we will p ```bash cd WrokSpace - tar xvf ../xilinx-versal-common-v2025.1.tar.gz -C . + tar xvf ../xilinx-versal-common-v2025.2.tar.gz -C . ``` - You can see the **xilinx-versal-common-v2025.1** folder which contains some components located in **WorkSpace** folder as shown below. + You can see the **xilinx-versal-common-v2025.2** folder which contains some components located in **WorkSpace** folder as shown below. ```bash tree -L 2 . - ├── xilinx-versal-common-v2025.1 + ├── xilinx-versal-common-v2025.2 │   ├── bl31.elf │   ├── boot.scr │   ├── Image @@ -77,7 +77,7 @@ From the above picture, you can see boot file, kernel image, rootfs, and SDK too 1. Install the sysroot - - Go to common image extracted directory . + - Go to common image extracted directory . - Type `./sdk.sh -d ` to install the PetaLinux SDK. Use the `-d` option to provide a full pathname to the output directory. (This is an example. `.` means current directory) and confirm. >Note: The environment variable LD_LIBRARY_PATH must not be set when running this command. @@ -113,7 +113,7 @@ From the above picture, you can see boot file, kernel image, rootfs, and SDK too ![vitis_platform_config](images/step2/vitis_linux_config.png) - - **Pre-Built Image Directory**: Browse to extracted common image path directory: `xilinx-versal-common-v2025.1/` and click OK. Bootgen looks for boot components referred by BIF in this directory to generate `BOOT.BIN`. + - **Pre-Built Image Directory**: Browse to extracted common image path directory: `xilinx-versal-common-v2025.2/` and click OK. Bootgen looks for boot components referred by BIF in this directory to generate `BOOT.BIN`. - **DTB file**: DTB will be generated automatically and populated in this area. - **FAT32 Partition Directory**: if you have additional file to be stored in FAT32 partition diretory you can browse to the file. If not please omit this. - **QEMU Data**: This Directory is used to add additional file for emulation. User can set it according to your requirement. diff --git a/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/step3.md b/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/step3.md index 6b9b7ffe51..9a80ac7889 100644 --- a/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/step3.md +++ b/Vitis_Platform_Creation/Design_Tutorials/03_Edge_VCK190/step3.md @@ -26,9 +26,9 @@ You will create an acceleration application with PL kernel running on the platfo - Input the **System project name** as `vadd` and use the default location for **System project location**. Then click **Next**. - Select **custom_platform** platform, click **Next**. >Note If the platform component is not in the current workspace user could click **+** button to add the platform component. - - Set **Kernel Image** to ```xilinx-versal-common-v2025.1/Image```. - - Set **Root FS** to ```xilinx-versal-common-v2025.1/rootfs.ext4```. - - Set **Sysroot** to ```xilinx-versal-common-v2025.1/sysroots/cortexa72-cortexa53-amd-linux```. Then click **Next**. + - Set **Kernel Image** to ```xilinx-versal-common-v2025.2/Image```. + - Set **Root FS** to ```xilinx-versal-common-v2025.2/rootfs.ext4```. + - Set **Sysroot** to ```xilinx-versal-common-v2025.2/sysroots/cortexa72-cortexa53-amd-linux```. Then click **Next**. - Review the summary of your `vadd` system project and click **Finish**. >Note: In the platform selecting page if the platform you want to use is not in the current list, you can click **+** button to add the platform to the list. @@ -175,9 +175,9 @@ To verify the platform functionality, you will create a project with AIE + PL ke - Use the default setting for **System project name** and **System project location**. Then click **Next**. - Select **custom_platform** platform, click **Next**. >Note If the platform component is not in the current workspace user could click **+** button to add the platform component. - - Set **Kernel Image** to ```xilinx-versal-common-v2025.1/Image```. - - Set **Root FS** to ```xilinx-versal-common-v2025.1/rootfs.ext4```. - - Set **Sysroot** to ```xilinx-versal-common-v2025.1/sysroots/cortexa72-cortexa53-amd-linux```. Then click **Next**. + - Set **Kernel Image** to ```xilinx-versal-common-v2025.2/Image```. + - Set **Root FS** to ```xilinx-versal-common-v2025.2/rootfs.ext4```. + - Set **Sysroot** to ```xilinx-versal-common-v2025.2/sysroots/cortexa72-cortexa53-amd-linux```. Then click **Next**. - Review the summary of your `vadd` system project and click **Finish**. >Note: In the platform selecting page if the platform you want to use is not in the current list, you can click **+** button to add the platform to the list. diff --git a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/README.md b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/README.md index 00e6105126..6dd62a1bf5 100644 --- a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/README.md +++ b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/README.md @@ -13,7 +13,7 @@ # AMD Versal Custom DFX Platform Creation Tutorial -***Version: 2024.2*** +***Version: 2025.2*** In this module, you will create a custom Dynamic Function eXchange (DFX) platform to run acceleration applications for VCK190 evaluation board. Platforms that support DFX features allows you to reload acceleration kernels during runtime. @@ -21,7 +21,7 @@ You can define one reconfigurable partition (RP) region and create multiple reco ![DFX Diagram](./images/dfx_rp_rm.svg) -This tutorial assumes that you understand the basics of the AMD Versal™ Custom Platform creation steps, for example, creating AMD Vivado™ designs from Vivado Customizable Example Design template, setting up software components with common images or PetaLinux, creating AMD Vitis™ platforms, and creating basic acceleration applications for platform validation. This tutorial will focus on the differences between the DFX platforms and the normal flat platforms. +This tutorial assumes that you understand the basics of the AMD Versal™ Custom Platform creation steps, for example, creating AMD Vivado™ designs from Vivado Customizable Example Design template, setting up software components with common images, creating AMD Vitis™ platforms, and creating basic acceleration applications for platform validation. This tutorial will focus on the differences between the DFX platforms and the normal flat platforms. In a general Vitis acceleration platform design, you start from building a base bootable design, then add platform required components and properties to it. You must validate each step before going to the next step to prevent error propagating. This workflow is described in the following diagram. @@ -49,7 +49,7 @@ This tutorial design uses VCK190 production board for demonstration. The methodo This design requires a Linux host machine with Internet access. The Linux OS needs to support the Vitis software and PetaLinux. -This tutorial assumes that you are familiar with Vitis platform creation flow. If not, refer to VCK190 Platform Creation Tutorial and *Vitis Acceleration Flow User Guide* [(UG1393)](https://docs.amd.com/access/sources/dita/map?isLatest=true&ft:locale=en-US&url=ug1393-vitis-application-acceleration) for more information. +This tutorial assumes that you are familiar with Vitis platform creation flow. If not, refer to VCK190 Platform Creation Tutorial and *Vitis Acceleration Flow User Guide* [(UG1701)](https://docs.amd.com/r/en-US/ug1701-vitis-accelerated-embedded/Getting-Started-with-Vitis-Unified-Software-Platform) for more information. ## What's Next @@ -65,6 +65,17 @@ Start with [Step 1](./step1.md). ## Changelog +### 2025.2 + +- Update system-user.dtsi as per CED design. +- Update Makefile as per new Python CLI support and python scripts. + +### 2025.1 + +- Update system-user.dtsi as per CED design. +- Update Makefile as per new VADD applications. +- Update platform settings to change selection of default clock to 156.25Mhz + ### 2023.1 - Hardware emulation XSA file is no longer mandatory required to create a platform diff --git a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/images/step1/vitis_region_platorm_setup.svg b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/images/step1/vitis_region_platorm_setup.svg new file mode 100755 index 0000000000..d89695015f --- /dev/null +++ b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/images/step1/vitis_region_platorm_setup.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/images/step1/vivado_ced_config.png b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/images/step1/vivado_ced_config.png deleted file mode 100644 index 18c554fedb..0000000000 Binary files a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/images/step1/vivado_ced_config.png and /dev/null differ diff --git a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/images/step1/vivado_ced_config.svg b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/images/step1/vivado_ced_config.svg new file mode 100755 index 0000000000..65fd77ec49 --- /dev/null +++ b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/images/step1/vivado_ced_config.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/description.json b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/description.json index f784986987..fbdd28ec6b 100755 --- a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/description.json +++ b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/description.json @@ -8,19 +8,13 @@ "platform_blocklist": [], "testinfo": { "test_name": "PFM_D_04_VCK190_DFX", - "tasks": { - "build": { - "pre_exec": "./env_setup_versal.sh" - }, - "board": { - "pre_exec": "./env_setup_versal.sh" - } - }, "jobs": [ { - "max_memory_MB": 32768, + "max_memory_MB": 65536, "max_time_min": { - "vitis_hw_emu": 200 + "vitis_hw_emu": 120, + "vitis_hw_build": 300, + "vitis_hw_run": 30 } } ], @@ -29,14 +23,11 @@ "vitis_hw_build", "vitis_hw_run" ], + "category": "canary", "make_options": [ - "CXX=${XILINX_VITIS}/gnu/aarch64/lin/aarch64-linux/bin/aarch64-linux-gnu-g++", - "HOST_ARCH=aarch64", - "EDGE_COMMON_SW=${EDGE_COMMON_SW}", - "ROOTFS=${EDGE_COMMON_SW}/rootfs.ext4", - "IMAGE=${EDGE_COMMON_SW}/Image", "EMU_CMD=\\\"./launch_hw_emu.sh -run-app run_aie.sh\\\"", "EMBEDDED_PACKAGE_OUT=./step3_validate/aie_work/package.hw/", + "EMBEDDED_EXEC_SCRIPT=./run_vadd.sh", "EMBEDDED_EXEC_SCRIPT=./run_aie.sh" ], "custom_build_target": @@ -44,8 +35,16 @@ "all": "all", "hw" : "sd_card" }, - "custom_board_target": "run_test" + "custom_board_target": "run_test", + "tasks": { + "board" : { + "pre_exec" : ["./env_setup_versal.sh"] + }, + "build": { + "pre_exec": ["./env_setup_versal.sh"] + } } } +} diff --git a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step1_hw/run.tcl b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step1_hw/run.tcl index 44f1315a79..af2384ffd3 100755 --- a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step1_hw/run.tcl +++ b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step1_hw/run.tcl @@ -49,7 +49,7 @@ set my_board [get_board_parts *${BOARD}:part0* -latest_file_version] create_project project_1 ./project_1 -part xcvc1902-vsva2197-2MP-e-S -force set_property board_part $my_board [current_project] create_bd_design "versal_dfx_platform" -mode batch -instantiate_example_design -template xilinx.com:design:versal_dfx_platform:1.0 -design versal_dfx_platform -options { Include_AIE.VALUE true Include_DDR.VALUE true} +instantiate_example_design -template xilinx.com:design:versal_dfx_platform:1.0 -design versal_dfx_platform -options { Clock_Options.VALUE {clk_out1 104.167 0 false clk_out2 156.250 1 true clk_out3 312.500 2 false clk_out4 78.125 3 false clk_out5 208.330 4 false clk_out6 416.670 5 false clk_out7 625.000 6 false} Include_AIE.VALUE true Include_DDR.VALUE true IRQS.VALUE 63 Include_LPDDR.VALUE true} update_compile_order -fileset sources_1 generate_target all [get_files project_1/project_1.srcs/sources_1/bd/versal_dfx_platform/versal_dfx_platform.bd] update_compile_order -fileset sources_1 diff --git a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step2_sw/Makefile b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step2_sw/Makefile index dd383b5b71..b2a3b5818a 100755 --- a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step2_sw/Makefile +++ b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step2_sw/Makefile @@ -7,7 +7,7 @@ XSA_NAME=vck190_custom_dfx DTB_PLT_NAME=vck190_custom_dt PLATFORM_NAME=vck190_custom_dfx - +PLATFORM := $(ROOT_DIR)/$(PLATFORM_NAME)/export/$(PLATFORM_NAME)/$(PLATFORM_NAME).xpfm # User editing area end # ------------------- @@ -16,11 +16,10 @@ ABS_BUILD_PATH=$(ROOT_DIR)/build STATIC_XSA=$(ROOT_DIR)/../step1_hw/build/vivado/$(XSA_NAME)_static.xsa RP_XSA=$(ROOT_DIR)/../step1_hw/build/vivado/$(XSA_NAME)_rp.xsa HW_EMU_XSA=$(ROOT_DIR)/../step1_hw/build/vivado/$(XSA_NAME)_hw_emu.xsa -DT_PATH=$(ABS_BUILD_PATH)/$(DTB_PLT_NAME)/psv_cortexa72_0/device_tree_domain/bsp -DTB_FILE=$(DT_PATH)/system.dtb BOOT_DIR=$(ABS_BUILD_PATH)/boot SD_DIR=$(ABS_BUILD_PATH)/sd_dir -VERSION=2025.1 +USER_DTSI=$(ROOT_DIR)/system-user.dtsi +VERSION=2025.2 COMMON_IMAGE_VERSAL ?=${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v$(VERSION)/ SW_COMP_PATH=$(ABS_BUILD_PATH)/sw_comp @@ -28,12 +27,9 @@ SYSROOT_DIR=$(SW_COMP_PATH)/sysroot SYSROOT=$(SYSROOT_DIR) BOOT_BIN_DIR=$(ABS_BUILD_PATH)/boot_bin -BOOT_IMAGE=$(ABS_BUILD_PATH)/boot_bin/BOOT.BIN +BOOT_IMAGE=$(ABS_BUILD_PATH)/boot/BOOT.BIN SW_FILES=$(SD_DIR)/boot.scr $(BOOT_DIR)/u-boot.elf $(BOOT_DIR)/bl31.elf -PDI_FILE=$(BOOT_BIN_DIR)/boot_static.pdi -PLATFORM_OUT_PATH=$(ABS_BUILD_PATH)/pfm - - +PLATFORM_OUT_PATH=$(ABS_BUILD_PATH) DEVICE_TREE_REPO ?= @@ -48,7 +44,7 @@ endif # sysroot: install sysroot from sdk.sh # -------------------------------------- -all: $(DTB_FILE) sw_comp pfm sysroot +all: sw_comp pfm sysroot sd_card: all help: @@ -63,26 +59,15 @@ ifeq ($(wildcard $(COMMON_IMAGE_VERSAL)/Image),) @make help @echo "exit ....." && exit 1 endif - @echo "INFO: Using COMMON_IMAGE_VERSAL=$(COMMON_IMAGE_VERSAL)" - -# Target: dtb -# generate the device tree blob -dtb: $(DTB_FILE) -#echo command is to avoid the return error code caused by the createdts command warning -$(DTB_FILE): $(STATIC_XSA) system-user.dtsi - $(info executing createdts to generate dts file) - xsct -eval "createdts -hw $(STATIC_XSA) -out $(ABS_BUILD_PATH) -zocl -platform-name $(DTB_PLT_NAME) -git-branch xlnx_rel_v2024.2 -board versal-vck190-reva-x-ebm-01-reva -dtsi system-user.dtsi -compile" - - + @ec:who "INFO: Using COMMON_IMAGE_VERSAL=$(COMMON_IMAGE_VERSAL)" # target :software components # copy software components to local directory sw_comp: $(SW_FILES) -$(SW_FILES): $(DTB_FILE) +$(SW_FILES): @echo "INFO: Copying components from common image and dtb output to boot and SD dir for FAT32 partition" mkdir -p $(BOOT_DIR) $(SD_DIR) $(SW_COMP_PATH) - cp -f $(DTB_FILE) $(BOOT_DIR) cp -f $(COMMON_IMAGE_VERSAL)/bl31.elf $(BOOT_DIR) cp -f $(COMMON_IMAGE_VERSAL)/u-boot.elf $(BOOT_DIR) cp -f $(COMMON_IMAGE_VERSAL)/boot.scr $(SD_DIR) @@ -90,39 +75,34 @@ $(SW_FILES): $(DTB_FILE) cp -f $(COMMON_IMAGE_VERSAL)/rootfs.ext4 $(SW_COMP_PATH) - -#---------- -$(PDI_FILE): $(STATIC_XSA) - $(info "Extracting PDI from static XSA") - mkdir -p $(BOOT_BIN_DIR) - cp $(STATIC_XSA) $(BOOT_BIN_DIR) - cd $(BOOT_BIN_DIR) && xsct -eval "openhw $(XSA_NAME)_static.xsa" && mv *.pdi boot_static.pdi +pfm: + @echo "INFO: Creating Platform $(PLATFORM_NAME) in mode: $(MODE)" + rm -rf $(PLATFORM_NAME) + @echo "Set place for Vitis to store configuration files" + @mkdir -p tmp && export XILINX_VITIS_DATA_DIR="tmp" + mkdir -p $(PLATFORM_OUT_PATH) + vitis -s generate_platform.py \ + --platform_name $(PLATFORM_NAME) \ + --static_xsa_path $(STATIC_XSA) \ + --emu_xsa_path "${HW_EMU_XSA}" \ + --platform_out "${PLATFORM_OUT_PATH}" \ + --boot_dir_path "${BOOT_DIR}" \ + --sd_dir_path "${SD_DIR}" \ + --rp_xsa_path "${RP_XSA}" \ + --user_dtsi "$(USER_DTSI)" + @echo "INFO: Platform created:" && find . -name "*.xpfm" + + $(info "Generating BOOT image for platforms") + cp -rf $(ROOT_DIR)/$(PLATFORM_NAME)/hw/linux_dt/system.dtb $(BOOT_DIR) + bootgen -arch versal -image $(ROOT_DIR)/bootgen.bif -o $(BOOT_IMAGE) -w + + @echo 'Platform build started' + vitis -s ./build_platform.py --platform_name $(PLATFORM_NAME) --platform_out $(ROOT_DIR) --boot_image $(BOOT_IMAGE) + + @echo 'Platform build complete' - -pdi: $(PDI_FILE) - -$(BOOT_IMAGE): $(PDI_FILE) $(SW_FILES) $(DTB_FILE) - $(info "BOOT image for platforms") - bootgen -arch versal -image bootgen.bif -o $(BOOT_IMAGE) -w; - -bootimage: $(BOOT_IMAGE) -#---------- - - -# -pfm: $(STATIC_XSA) $(RP_XSA) $(SW_FILES) ${BOOT_IMAGE} - $(info Creating Platform $(XSA_NAME)) - xsct xsct_create_pfm.tcl platform_name "${PLATFORM_NAME}" \ - static_xsa_path "${STATIC_XSA}" \ - rp_xsa_path "${RP_XSA}" \ - boot_dir_path "${BOOT_DIR}" \ - boot_bin "${BOOT_IMAGE}" \ - emu_xsa_path "${HW_EMU_XSA}" \ - sd_dir_path "${SD_DIR}" \ - platform_out "${PLATFORM_OUT_PATH}" - clean: - $(RM) -r $(ABS_BUILD_PATH)/$(DTB_PLT_NAME) $(BOOT_DIR) $(SD_DIR) $(BOOT_BIN_DIR) $(PLATFORM_OUT_PATH) + $(RM) -r $(ABS_BUILD_PATH)/$(DTB_PLT_NAME) $(BOOT_DIR) $(SD_DIR) $(BOOT_BIN_DIR) $(PLATFORM_OUT_PATH) $(PLATFORM_NAME) ultraclean: $(RM) -r $(ABS_BUILD_PATH) diff --git a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step2_sw/bootgen.bif b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step2_sw/bootgen.bif index 78c3d7549b..5f44a45372 100755 --- a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step2_sw/bootgen.bif +++ b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step2_sw/bootgen.bif @@ -7,7 +7,7 @@ the_ROM_image: { image { - { type=bootimage, file=build/boot_bin/boot_static.pdi } + { type=bootimage, file=./vck190_custom_dfx/hw/sdt/vck190_custom_dfx_static.pdi } } image { id = 0x1c000000, name=apu_subsystem diff --git a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step2_sw/build_platform.py b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step2_sw/build_platform.py new file mode 100644 index 0000000000..fad8098f64 --- /dev/null +++ b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step2_sw/build_platform.py @@ -0,0 +1,43 @@ +#****************************************************************************** +# Copyright (C) 2020-2022 Xilinx, Inc. All rights reserved. +# Copyright (C) 2022-2025 Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +#****************************************************************************** +import vitis +import argparse +import os + +print("Platform generation") +parser = argparse.ArgumentParser() +parser.add_argument("--platform_name", type=str, dest="platform_name") +parser.add_argument("--static_xsa_path", type=str, dest="static_xsa_path") +parser.add_argument("--emu_xsa_path", type=str, dest="emu_xsa_path") +parser.add_argument("--platform_out", type=str, dest="platform_out") +parser.add_argument("--boot_dir_path", type=str, dest="boot_dir_path") +parser.add_argument("--img_dir_path", type=str, dest="img_dir_path") +parser.add_argument("--rp_xsa_path", type=str, dest="rp_xsa_path") +parser.add_argument("--user_dtsi", type=str, dest="user_dtsi") +parser.add_argument("--boot_image", type=str, dest="boot_image") + + +args = parser.parse_args() +static_xsa_path=args.static_xsa_path +platform_name=args.platform_name +emu_xsa_path=args.emu_xsa_path +platform_out=args.platform_out +boot_dir_path=args.boot_dir_path +img_dir_path=args.img_dir_path +rp_xsa_path=args.rp_xsa_path +user_dtsi=args.user_dtsi +boot_image=args.boot_image +print('args',args) +client = vitis.create_client() +client.update_workspace(path=platform_out) + +platform = client.get_component(name = platform_name) + +#update boot_dir_path with boot.bin path +domain = platform.get_domain(name="xrt") +status = domain.update_hw_boot_bin(boot_image) + +status = platform.build() diff --git a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step2_sw/generate_platform.py b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step2_sw/generate_platform.py new file mode 100644 index 0000000000..d2276c1ec6 --- /dev/null +++ b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step2_sw/generate_platform.py @@ -0,0 +1,50 @@ +#****************************************************************************** +# Copyright (C) 2020-2022 Xilinx, Inc. All rights reserved. +# Copyright (C) 2022-2025 Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +#****************************************************************************** +import vitis +import argparse +import os + +print("Platform generation") +parser = argparse.ArgumentParser() +parser.add_argument("--platform_name", type=str, dest="platform_name") +parser.add_argument("--static_xsa_path", type=str, dest="static_xsa_path") +parser.add_argument("--emu_xsa_path", type=str, dest="emu_xsa_path") +parser.add_argument("--platform_out", type=str, dest="platform_out") +parser.add_argument("--boot_dir_path", type=str, dest="boot_dir_path") +parser.add_argument("--sd_dir_path", type=str, dest="sd_dir_path") +parser.add_argument("--rp_xsa_path", type=str, dest="rp_xsa_path") +parser.add_argument("--user_dtsi", type=str, dest="user_dtsi") + +args = parser.parse_args() + +# Extract variables +platform_name=args.platform_name +static_xsa_path=args.static_xsa_path +emu_xsa_path=args.emu_xsa_path +platform_out=args.platform_out +boot_dir_path=args.boot_dir_path +sd_dir_path=args.sd_dir_path +rp_xsa_path=args.rp_xsa_path +user_dtsi=args.user_dtsi + +print('args',args) +client = vitis.create_client() + +current_path = os.getcwd() +print(current_path) +client.update_workspace(path=current_path) +client.set_workspace(path=current_path) + +advanced_options = client.create_advanced_options_dict(board_dtsi="versal-vck190-reva-x-ebm-01-reva",user_dtsi=user_dtsi,dt_overlay="0",dt_zocl="1") +rp_info_args = client.add_rp_info_args(rp_xsa_path=rp_xsa_path) + +platform = client.create_platform_component(name = platform_name,hw_design = static_xsa_path,os = "linux",cpu = "psv_cortexa72",domain_name = "xrt",emu_design = emu_xsa_path,generate_dtb = True, rp_info_args = rp_info_args, advanced_options = advanced_options ) +platform = client.get_component(name = platform_name) +domain = platform.add_domain(cpu = "ai_engine",os = "aie_runtime",name = "aiengine",display_name = "aiengine") +domain = platform.get_domain(name = "xrt") +domain.set_sd_dir(path = sd_dir_path) +status = domain.set_boot_dir(path=boot_dir_path) +status = domain.generate_bif() diff --git a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step2_sw/system-user.dtsi b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step2_sw/system-user.dtsi index 3aade7f0e4..49595ca33f 100755 --- a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step2_sw/system-user.dtsi +++ b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step2_sw/system-user.dtsi @@ -9,6 +9,10 @@ chosen { }; }; +&cpm_pciea { + status = "disabled"; +}; + &amba_pl { ai_engine@20000000000 { #address-cells = <0x02>; @@ -16,7 +20,7 @@ chosen { clock-names = "aclk0"; clocks = <0x13>; compatible = "xlnx,ai-engine-2.0\0xlnx,ai-engine-v2.0"; - power-domains = <0x07 0x18224072>; + power-domains = <0x8d 0x18800000>; ranges; reg = <0x200 0x00 0x01 0x00>; xlnx,aie-gen = [01]; @@ -30,7 +34,7 @@ chosen { interrupt-names = "interrupt1\0interrupt2\0interrupt3"; interrupt-parent = <0x05>; interrupts = <0x00 0x94 0x04 0x00 0x95 0x04 0x00 0x96 0x04>; - power-domains = <0x07 0x18224072>; + power-domains = <0x8d 0x18800000>; reg = <0x200 0x00 0x01 0x00>; xlnx,columns = <0x00 0x32>; xlnx,node-id = <0x18800000>; diff --git a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step3_validate/Makefile b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step3_validate/Makefile index 641e6683a2..57e5937e69 100755 --- a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step3_validate/Makefile +++ b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step3_validate/Makefile @@ -5,8 +5,8 @@ ROOT_DIR=$(realpath $(dir $(lastword $(MAKEFILE_LIST)))) XSA_NAME=vck190_custom_dfx -CUSTOM_PLATFORM=$(ROOT_DIR)/../step2_sw/build/pfm/$(XSA_NAME)/export/$(XSA_NAME)/$(XSA_NAME).xpfm -VERSION=2025.1 +CUSTOM_PLATFORM=$(ROOT_DIR)/../step2_sw/$(XSA_NAME)/export/$(XSA_NAME)/$(XSA_NAME).xpfm +VERSION=2025.2 COMMON_IMAGE_VERSAL ?=${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v$(VERSION)/ SYSROOT=$(COMMON_IMAGE_VERSAL)/sysroots/cortexa72-cortexa53-amd-linux/ @@ -18,7 +18,7 @@ AIE_WORK=$(ROOT_DIR)/aie_work .PHONY: all vadd aie_adder platforminfo clean ultraclean #all: To support emulation all: platforminfo vadd_emu aie_adder_emu -sd_card:platforminfo aie_adder_hw +sd_card:platforminfo vadd_hw aie_adder_hw cpAieCode: @@ -28,7 +28,7 @@ cpAieCode: cpVaddCode: mkdir -p vadd_work - cp $(XILINX_VITIS)/examples/vadd/* vadd_work + cp -rf $(XILINX_VITIS)/samples/vadd/* vadd_work/ cp makefile_vadd vadd_work/Makefile diff --git a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step3_validate/makefile_vadd b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step3_validate/makefile_vadd index a342375216..2d13a6fd24 100644 --- a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step3_validate/makefile_vadd +++ b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/ref_files/step3_validate/makefile_vadd @@ -10,73 +10,44 @@ TARGET := hw SYSROOT := $(EDGE_COMMON_SW)/sysroots/cortexa72-cortexa53-amd-linux SD_IMAGE_FILE := $(EDGE_COMMON_SW)/Image VPP_LDFLAGS := - - TEMP_DIR := ./_x.$(TARGET) -BUILD_DIR := ./build_dir.$(TARGET) - -LINK_OUTPUT := $(BUILD_DIR)/krnl_vadd.link.xsa - -EMU_PS := QEMU -ifeq ($(TARGET), sw_emu) -EMU_PS := X86 -endif +BUILD_DIR := ./build_dir.$(TARGET).$(XSA) +LINK_OUTPUT := $(BUILD_DIR)/vadd.link.xsa +SDKTARGETSYSROOT ?= ${SYSROOT} dfx_hw=true # SoC variables RUN_APP_SCRIPT = ./run_vadd.sh PACKAGE_OUT = ./package.$(TARGET) - LAUNCH_EMULATOR = $(PACKAGE_OUT)/launch_$(TARGET).sh RESULT_STRING = TEST PASSED - VPP_PFLAGS := -CMD_ARGS = $(BUILD_DIR)/krnl_vadd.xclbin +CMD_ARGS = $(BUILD_DIR)/vadd.xclbin SD_CARD := $(PACKAGE_OUT) -ifeq ($(EMU_PS), X86) -CXXFLAGS += -I$(XILINX_XRT)/include -I$(XILINX_VIVADO)/include -Wall -O0 -g -std=c++17 -LDFLAGS += -L$(XILINX_XRT)/lib -pthread -lOpenCL -else -CXXFLAGS += -I$(SYSROOT)/usr/include/xrt -I$(XILINX_VIVADO)/include -Wall -O0 -g -std=c++17 +CXXFLAGS += --sysroot=${SYSROOT} -I${SDKTARGETSYSROOT}/usr/include/xrt/ -I$(XILINX_VIVADO)/include -I$(XILINX_VITIS)/include -I${XILINX_VITIS}/aietools/include ${HOST_INC} -Wall -O0 -g -std=c++17 LDFLAGS += -L$(SYSROOT)/usr/lib -pthread -lxilinxopencl -endif - -ifeq ($(TARGET),$(filter $(TARGET),sw_emu)) -VPP_PFLAGS+= --package.emu_ps qemu -endif - -#Check for EMU_PS -ifeq ($(TARGET), $(filter $(TARGET),hw_emu hw)) -ifeq ($(EMU_PS), X86) -$(error For hw_emu and hw, the design has to run on QEMU. Thus, please give EMU_PS=QEMU for these targets.) -endif -endif ########################## Checking if PLATFORM in allowlist ####################### PLATFORM_BLOCKLIST += nodma ############################## Setting up Host Variables ############################## #Include Required Host Source Files -HOST_SRCS += vadd.cpp +HOST_SRCS += ./src/host.cpp ./src/cmdlineparser.cpp ./src/logger.cpp # Host compiler global settings CXXFLAGS += -fmessage-length=0 -LDFLAGS += -lrt -lstdc++ -ifneq ($(EMU_PS), X86) -LDFLAGS += --sysroot=$(SYSROOT) -endif +LDFLAGS += -lrt -lstdc++ -luuid -lxrt_coreutil ############################## Setting up Kernel Variables ############################## # Kernel compiler global settings VPP_FLAGS += --save-temps - EXECUTABLE = ./simple_vadd EMCONFIG_DIR = $(TEMP_DIR) - ############################## Setting Targets ############################## -.PHONY: all clean cleanall docs emconfig -ifeq ($(EMU_PS), X86) -all: $(EXECUTABLE) $(LINK_OUTPUT) emconfig +.PHONY: all clean cleanall docs + +ifeq ($(TARGET), hw_emu) +all: $(EXECUTABLE) $(BUILD_DIR)/vadd.xclbin sd_card else -all: $(EXECUTABLE) $(LINK_OUTPUT) sd_card +all: $(EXECUTABLE) $(LINK_OUTPUT) sd_card endif .PHONY: host @@ -85,78 +56,48 @@ host: $(EXECUTABLE) .PHONY: build build: $(LINK_OUTPUT) +.PHONY: build +build: check-vitis check-device $(BUILD_DIR)/vadd.xclbin + .PHONY: xclbin xclbin: build ############################## Setting Rules for Binary Containers (Building Kernels) ############################## -$(TEMP_DIR)/krnl_vadd.xo: krnl_vadd.cpp +$(TEMP_DIR)/vadd.xo: src/vadd.cpp mkdir -p $(TEMP_DIR) - v++ -c $(VPP_FLAGS) -t $(TARGET) --platform $(PLATFORM) -k krnl_vadd --temp_dir $(TEMP_DIR) -I'$( Open Block design +Go to Platform Setup -> Clock and make clk_out2 which is 156.25Mhz clock output as default clock. +![Platform Setup](./images/step1/vitis_region_platorm_setup.svg) + + ### DFX Platform Design Submodule Explanation The following sections provide the platform hardware submodule explanation with diagrams. In the diagrams, the Vitis region is the dynamic area (RP). Blocks outside of the Vitis Region are in the static region. They will be loaded at boot time and won't be reconfigured. diff --git a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/step2.md b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/step2.md index fa816084a4..983c4ecbac 100644 --- a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/step2.md +++ b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/step2.md @@ -19,7 +19,7 @@ The unique requirements from DFX platforms are from the device tree. ## Generating Device Tree -Use the static XSA to generate the base device tree with device tree generator (DTG). The generated device tree (.dts and .dtsi) only includes IP information in the static region. If any IP in the dynamic region needs driver support, you should add them to the device tree manually. AI Engine is an example that needs driver support. Add its information to ``system-user.dtsi``. +We need to use the static XSA to generate the base device tree with sdtgen and lopper. With Vitis Unified ID flow, The device tree generation (.dts and .dtsi) is automatic that includes IP information in the static region. If any IP in the dynamic region needs driver support, you should add them to the device tree manually. AI Engine is an example that needs driver support. Add its information to ``system-user.dtsi``. >**Note:** Only one DFX region is supported at the moment; therefore, the ZOCL driver and device tree only supports one dfx_decoupler IP address. @@ -35,7 +35,7 @@ Use the static XSA to generate the base device tree with device tree generator ( clock-names = "aclk0"; clocks = <0x13>; compatible = "xlnx,ai-engine-2.0\0xlnx,ai-engine-v2.0"; - power-domains = <0x07 0x18224072>; + power-domains = <0x8d 0x18800000>; ranges; reg = <0x200 0x00 0x01 0x00>; xlnx,aie-gen = [01]; @@ -49,7 +49,7 @@ Use the static XSA to generate the base device tree with device tree generator ( interrupt-names = "interrupt1\0interrupt2\0interrupt3"; interrupt-parent = <0x05>; interrupts = <0x00 0x94 0x04 0x00 0x95 0x04 0x00 0x96 0x04>; - power-domains = <0x07 0x18224072>; + power-domains = <0x8d 0x18800000>; reg = <0x200 0x00 0x01 0x00>; xlnx,columns = <0x00 0x32>; xlnx,node-id = <0x18800000>; @@ -64,35 +64,22 @@ Use the static XSA to generate the base device tree with device tree generator ( }; ``` -A prepared [system-user.dtsi](ref_file/step2_sw/system-user.dtsi) file is ready for use. +A prepared [system-user.dtsi](./ref_file/step2_sw/system-user.dtsi) file is ready for use. If you updated the AI Engine clock frequency, please update the `clock-frequency` of `aie_core_ref_clk_0`. -### Generate the Base Device Tree from the Static XSA - -```bash -createdts -hw \ - -zocl\ - -out . \ - -platform-name vck190_custom_dt \ - -git-branch xlnx_rel_v2024.2 \ - -dtsi system-user.dtsi \ - -board versal-vck190-reva-x-ebm-01-reva \ - -compile -``` - -The generated device tree files are located in ``build/vck190_custom_dt/psv_cortexa72_0/device_tree_domain/bsp`` path. You can find the ``system.dtb`` file in ``step2_sw/build/vck190_custom_dt/psv_cortexa72_0/device_tree_domain/bsp/`` directory. - -> **NOTE**: Device tree knowledge is a common know-how. Please refer to [AMD Device tree WIKI page](https://xilinx-wiki.atlassian.net/wiki/spaces/A/pages/862421121/Device+Trees) or [Device Tree WIKI page](https://en.wikipedia.org/wiki/Devicetree#Linux) for more information if you are not familiar with it. - ### Creating the Vitis Platform The Vitis platform creation workflow for DFX platforms is almost identical to the flat platform with the following exceptions -- The platform creation can only be created with XSCT. Vitis IDE does not support to create DFX platforms. +- The platform creation can be created with python CLI flow only. Vitis IDE does not support to create DFX platforms. - When creating the DFX platform, both static XSA and RP XSA are required. Static XSA will be used to create ``boot.bin``. RP XSA is used to link acceleration kernels. +- The device tree generation is automatic with help of sdtgen and lopper part of Vitis tool chain. + +- Using [generate_platform.py](./ref_files/step2_sw/generate_platform.py) and [build_platform.py](./ref_files/step2_sw/build_platform.py) we create and build the platform with python CLI flow. + ### Prepare for Platform Packaging You should prepare the following components before creating the platform. @@ -182,9 +169,9 @@ tree -L 3 --charset ascii A DFX platform can boot the static region during power on. The static boot image can include static region PDI for hardware configuration, Arm® Trusted Firmware `bl31.elf`, `u-boot.elf`, and device tree for U-Boot. -When creating a DFX platform, static `boot.bin` is required. You generate this boot image before creating the platform. +When creating a DFX platform, static `boot.bin` is required. You generate this boot image before building the platform. -Static PDI is included in the static region XSA. You can use the XSCT command `openhw $(XSA_NAME)_static.xsa` to extract the XSA and find the PDI. +In between generate platform and build platform we need to create a BOOT.bin component using bootgen, which is showed how to be done in the [Makefile.](./ref_files/step2_sw/Makefile) Run bootgen command to create the boot.bin. @@ -211,57 +198,22 @@ image { ### Platform Packaging -Use XSCT command line tool to create the Vitis DFX platform. +Use Python command line tool to create the Vitis DFX platform. >**Note:** Vitis IDE support for creating Vitis DFX platforms will be added in the future. -Create a tcl file with XSCT commands. - -```Tcl # Create a platform project -platform create -name vck190_dfx_custom \ - -desc "A custom VCK190 DFX platform" \ - -hw .xsa \ - -rp {id 0 hw .xsa hw_emu .xsa} \ - -out \ - -no-boot-bsp - -# AIE domain -domain create -name aiengine -os aie_runtime -proc ai_engine -domain config -qemu-data ./boot - -# Add Linux domain -domain create -name xrt -proc psv_cortexa72 -os linux -sd-dir {./sd_dir} -domain config -hw-boot-bin -domain config -boot {./boot} -domain config -generate-bif -domain config -qemu-data ./boot - -platform write -platform generate -``` - ->**Note:** Replace the file name and directory name in the script with your project file location. If you do not need to support hardware emulation, you can omit the option `-hw_emu` and its value for the command `platform create`. - -The `platform create` command needs the following input values: - -- `-name`: Platform name -- `-hw`: Static Hardware XSA file location -- `-rp`: The reconfigurable partition info with ID, XSA and hardware emulation XSA info. ID is reserved for multi-partition DFX. For now only one partition is supported. Please use `id 0`. -- `-out`: Platform output path. In this example, we set output directory to ``step2_sw/build/pfm``. -- `-sd-dir`: The directory that contains the files to be included in the FAT32 partition of the SD card image. - -The `domain` command will set up one AI Engine domain and one Linux domain. The Linux domain has SD boot mode. The DFX platform Linux domain requires you to provide the `boot.bin` to boot the static region. It will use files in the `./sd_dir` directory to form the FAT32 partition of the SD card image. You have stored the required files in these directories in [Prepare for Platform Packaging](#prepare-for-platform-packaging) step. - -You can pass the values to the script directly by replacing the variable with the actual value, or define them in the header of the Tcl script, or pass the value to XSCT when calling this script. - -Here is an example of calling XSCT if you hard code all contents in `xsct_create_pfm.tcl`. - -```bash -xsct xsct_create_pfm.tcl -``` - -To support better generalization, the example [Makefile](./ref_files/step2_sw/Makefile) and [xsct_create_pfm.tcl](./ref_files/step2_sw/xsct_create_pfm.tcl) in the `ref_files` directory uses variables to represent the file names and directory location. Refer to them if you would like to get more programmability in your scripts. + vitis -s generate_platform.py \ + --platform_name $(PLATFORM_NAME) \ + --static_xsa_path $(STATIC_XSA) \ + --emu_xsa_path "${HW_EMU_XSA}" \ + --platform_out "${PLATFORM_OUT_PATH}" \ + --boot_dir_path "${BOOT_DIR}" \ + --sd_dir_path "${SD_DIR}" \ + --rp_xsa_path "${RP_XSA}" \ + --user_dtsi "$(USER_DTSI)" + +# Refer [generate_platform.py](./ref_files/step2_sw/generate_platform.py) and [build_platform.py](./ref_files/step2_sw/build_platform.py) for more details. ### Next Step diff --git a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/step3.md b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/step3.md index 0fadc6a3ec..20e71b6a35 100644 --- a/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/step3.md +++ b/Vitis_Platform_Creation/Design_Tutorials/04_Edge_VCK190_DFX/step3.md @@ -52,7 +52,7 @@ You can verify hardware configuration (clocks, memory) and software configuratio Board: versal_extensible_dfx_platform_base Name: versal_extensible_dfx_platform_base Version: 1.0 - Generated Version: 2024.2 + Generated Version: 2025.2 Hardware: 1 Software Emulation: 1 Hardware Emulation: 0 @@ -150,7 +150,7 @@ The user flow for configuring the XCLBIN to DFX platforms and flat platforms are ```bash mkdir -p ref_files/step3_verify cd ref_files/step3_verify - vitis -workspace ./ & + vitis -w . ``` Close the welcome tab after Vitis launches. diff --git a/Vitis_Platform_Creation/Design_Tutorials/Design_Tutorials.rst b/Vitis_Platform_Creation/Design_Tutorials/Design_Tutorials.rst index 539499b7ae..502ba5cf3f 100644 --- a/Vitis_Platform_Creation/Design_Tutorials/Design_Tutorials.rst +++ b/Vitis_Platform_Creation/Design_Tutorials/Design_Tutorials.rst @@ -18,7 +18,6 @@ Vitis Platform Creation: Design Tutorials Custom Platform Creation Tutorial on MPSoC <./02-Edge-AI-ZCU104/README.md> Custom Platform Creation Tutorial on Versal <./03_Edge_VCK190/README.md> Custom Versal DFX Platform Creation Tutorial <./04_Edge_VCK190_DFX/README.md> - Custom Kria SOM Platform Creation Example <./01-Edge-KV260/README.md> @@ -37,8 +36,5 @@ Vitis Platform Creation: Design Tutorials - This tutorial demonstrates how you can create a custom Vitis platform on VCK190 demo board and validate the platform. * - :doc:`Custom Versal DFX Platform Creation Tutorial <./04_Edge_VCK190_DFX/README>` - - This tutorial demonstrates how you can create a custom Vitis platform on VCK190 demo board and validate the platform. - - * - :doc:`Custom Kria SOM Platform Creation Example <./01-Edge-KV260/README>` - - Extend the :doc:`Custom Platform Creation Tutorial on MPSoC <./02-Edge-AI-ZCU104/README>` to the popular MPSoC board, the AMD Kria™ SOM KV260 Starter Kit. + - This tutorial demonstrates how you can create a custom DFX Vitis platform on VCK190 demo board and validate the platform. diff --git a/Vitis_Platform_Creation/Design_Tutorials/README.md b/Vitis_Platform_Creation/Design_Tutorials/README.md index f6c4d57dbe..1abeebe15c 100644 --- a/Vitis_Platform_Creation/Design_Tutorials/README.md +++ b/Vitis_Platform_Creation/Design_Tutorials/README.md @@ -33,12 +33,6 @@ Custom Versal DFX Platform Creation Tutorial This tutorial demonstrates how you can create a custom DFX platform to run acceleration applications for VCK190 evaluation board. - - - Custom Kria SOM Platform Creation Example - Extend the ZCU104 custom embedded platform creation example to the popular MPSoC board, the AMD Kria™ SOM KV260 Starter Kit. - - diff --git a/Vitis_Platform_Creation/Feature_Tutorials/01_platform_creation_streaming_ip/README.md b/Vitis_Platform_Creation/Feature_Tutorials/01_platform_creation_streaming_ip/README.md index 090cb4c70a..426f738e9c 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/01_platform_creation_streaming_ip/README.md +++ b/Vitis_Platform_Creation/Feature_Tutorials/01_platform_creation_streaming_ip/README.md @@ -13,7 +13,7 @@ # Versal Platform Creation with Custom IP -***Version: Vitis 2024.1*** +***Version: Vitis 2025.2*** This tutorial explains how to add custom IPs into a Versal™ adaptive SoC platform. This tutorial is an 'add-on' to the basic [Versal platform creation tutorial](../../Design_Tutorials/03_Edge_VCK190/README.md). Therefore, for each step, there is a pointer to the corresponding part of that tutorial, as required. diff --git a/Vitis_Platform_Creation/Feature_Tutorials/01_platform_creation_streaming_ip/ref_files/Makefile b/Vitis_Platform_Creation/Feature_Tutorials/01_platform_creation_streaming_ip/ref_files/Makefile index 265a5028c1..25f91b7c5b 100755 --- a/Vitis_Platform_Creation/Feature_Tutorials/01_platform_creation_streaming_ip/ref_files/Makefile +++ b/Vitis_Platform_Creation/Feature_Tutorials/01_platform_creation_streaming_ip/ref_files/Makefile @@ -8,7 +8,7 @@ ABS_BUILD_PATH=$(ROOT_DIR)/build ABS_HW_PATH=$(ABS_BUILD_PATH)/vivado BD_TCL=run.tcl ABS_BD_TCL=$(ROOT_DIR)/$(BD_TCL) -VERSION=2025.1 +VERSION=2025.2 COMMON_IMAGE_VERSAL ?=${PLATFORM_REPO_PATHS}/sw/versal/xilinx-versal-common-v$(VERSION) XSA_PATH=$(ROOT_DIR)/build/vivado/ XSA_NAME=custom_hardware_platform diff --git a/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization/README.md b/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization/README.md index 66102dcbe6..b11ef65485 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization/README.md +++ b/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization/README.md @@ -14,13 +14,13 @@ # PetaLinux Building and System Customization -***Version: PetaLinux 2025.1*** +***Version: PetaLinux 2025.2*** This module demonstrates platform software components customization. Use the PetaLinux tools to create the Linux image and sysroot with XRT support, together with some more advanced tweaks. Among all the customizations, the XRT installation and ZOCL device tree setup are mandatory. Other customizations are optional. The customization purposes are explained and you can pick your desired customization. Yocto or third-party Linux development tools can also be used as long as they produce the same Linux output products as PetaLinux. -As XSA file is the mandatory input for Petalinux project. Users can input XSA file exported from your Vivado project. This time we will leverage ready-made base platform from [Xilinx website download center](https://www.xilinx.com/support/download.html) and take zcu104 base platform as an example to show how to do system customization. Of course, you can download other platforms from that page according to your requirement. +As XSA file is the mandatory input for Petalinux project. Users can input XSA file exported from your Vivado project. This time we will leverage ready-made base platform from [Xilinx website download center](https://www.xilinx.com/support/download.html) and take vck190 base platform as an example to show how to do system customization. Of course, you can download other platforms from that page according to your requirement. ### Prepare the base platform @@ -34,8 +34,8 @@ As XSA file is the mandatory input for Petalinux project. Users can input XSA f 2. Download the base platform and place it under `workspace` folder. Then extract it. If you have already installed the Vitis™ tool, omit this step as AMD Official platforms have already built into the vitis tool installation package. ```bash - unzip xilinx_zcu104_base_202510_1.zip #extract the base platform - cd xilinx_zcu104_base_202510_1 + unzip xilinx_vck190_base_202520_1.zip #extract the base platform + cd xilinx_vck190_base_202520_1 tree -L 2 . ├── hw @@ -43,10 +43,10 @@ As XSA file is the mandatory input for Petalinux project. Users can input XSA f ├── hw_emu │ └── hw_emu.xsa ├── sw - │ ├── xilinx_zcu104_base_202510_1 - │ └── xilinx_zcu104_base_202510_1.spfm + │ ├── xilinx_vck190_base_202520_1 + │ └── xilinx_vck190_base_202520_1.spfm ├── version - └── xilinx_zcu104_base_202510_1.xpfm + └── xilinx_vck190_base_202520_1.xpfm 4 directories, 5 files ``` @@ -58,31 +58,29 @@ As XSA file is the mandatory input for Petalinux project. Users can input XSA f source /settings.sh ``` -2. Create a PetaLinux project named **zcu104_petalinux** and configure the hw option with the XSA file: +2. Create a PetaLinux project named **vck190_petalinux** and configure the hw option with the XSA file: ```bash cd workspace - petalinux-create --type project --template zynqMP --name zcu104_petalinux - cd zcu104_petalinux - petalinux-config --get-hw-description=xilinx_zcu104_base_202510_1/hw/hw.xsa # After you extract the base platform, you can find hw.xsa or hw_emu.xsa under directory. If you want to do emulation you can choose hw_emu.xsa + petalinux-create --type project --template versal --name vck190_petalinux + cd vck190_petalinux + petalinux-config --get-hw-description=xilinx_vck190_base_202520_1/hw/hw.xsa # After you extract the base platform, you can find hw.xsa or hw_emu.xsa under directory. If you want to do emulation you can choose hw_emu.xsa ``` - > Note: `--template` option specifies the chipset. zcu104 board adopts the ZYNQMP™ series chip. Therefore, we specify this option as `zynqMP`. If your platform is using Versal™ chipset, set this option to `versal`. - - > Note: If the user is customizing Linux image for VCK190 board, ensure the XSA file is exported from a normal project (not a Vitis extensible project) and includes the device image. + > Note: `--template` option specifies the chipset. vck190 board adopts the Versal™ series chip. Therefore, we specify this option as `versal`. > Note: PetaLinux will use XSA to generate the device tree. Since hardware XSA and hardware emulation XSA have identical peripherals, providing either of them to PetaLinux is acceptable. When simplifying the hardware design for hardware emulation, it is recommended to keep all the peripherals that need device tree and drivers so that the auto-generated device tree can be reused. If the two designs have different addressable peripherals, you will need to create two sets of device trees for hardware running and hardware emulation, separately. -3. A petalinux-config menu is launched. Set it to use ZCU104 device tree in the configuration window. +3. A petalinux-config menu is launched. Set it to use VCK190 device tree in the configuration window. - Select **DTG Settings->MACHINE_NAME** - - Modify it to ```zcu104-revc```. + - Modify it to ```vck190-versal```. - Select **OK -> Exit -> Exit -> Yes** to close this window. Note: - - If you are using an AMD development board, it is recommended to modify the machine name so that the board configurations would be involved in the DTS auto-generation. You can check the [UG1144 document](https://www.xilinx.com/content/dam/xilinx/support/documentation/sw_manuals/xilinx2021_2/ug1144-petalinux-tools-reference-guide.pdf) for the corresponding machine name. + - If you are using an AMD development board, it is recommended to modify the machine name so that the board configurations would be involved in the DTS auto-generation. You can check the [UG1144 document](https://docs.amd.com/r/en-US/ug1144-petalinux-tools-reference-guide/Design-Flow-Overview) for the corresponding machine name. - If you are using a custom board, you would need to configure the associated settings (e.g. the PHY information DTS node) in **system-user.dtsi** manually. - Device tree is a generic technology in embedded Linux. Search on Google for more information. @@ -153,20 +151,9 @@ Device Tree Generator (DTG) also overrides the interrupt controller (axi_intc_0) You can review the PetaLinux generated device tree in **project-spec/components/device-tree/device-tree/pl.dtsi** file. -You can also add your custom device tree modifications to **project-spec/meta-user/recipes-bsp/device-tree/files/system-user.dtsi**. For example this is how you setup sdhci1 to low speed mode. - -``` -&sdhci1 { - no-1-8-v; - disable-wp; -}; -``` - - - **sdhci1** node decreases SD Card speed for better card compatibility on ZCU104 board. This only relates to ZCU104 and is not a part of Vitis acceleration platform requirements. - - **Note**: an example file [zcu104/system-user.dtsi](ref_files/zcu104/system-user.dtsi) is provided for zcu104 board and [vck190/system-user.dtsi](ref_files/vck190/system-user.dtsi) for VCK190 board. - - +You can also add your custom device tree modifications to **project-spec/meta-user/recipes-bsp/device-tree/files/system-user.dtsi**. + + **Note**: an example file [vck190/system-user.dtsi](ref_files/vck190/system-user.dtsi) for VCK190 board. ### Add EXT4 rootfs support diff --git a/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization/ref_files/vck190/Makefile b/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization/ref_files/vck190/Makefile index 179cc8822b..90f5b0a235 100755 --- a/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization/ref_files/vck190/Makefile +++ b/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization/ref_files/vck190/Makefile @@ -1,5 +1,5 @@ #/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +#Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT #*/ @@ -13,7 +13,7 @@ PETALINUX_ROOTFS_CONFIG=$(PETALINUX_DIR)/project-spec/configs/rootfs_config #XSA_NAME ?=xsa_file_for_petalinux PDI_DIR =pdi_dir #PDI_PATH =$(ROOT_DIR)/$(PDI_DIR) -XSA ?=${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202510_1/hw/hw.xsa +XSA ?=${PLATFORM_REPO_PATHS}/xilinx_vck190_base_202520_1/hw/hw.xsa #PDI=$(wildcard $(PDI_PATH)/*.pdi) IMAGE_DIR=$(ABS_BUILD_PATH)/$(PETALINUX_PROJ_NAME)/images/linux/ # -------------------------------------- diff --git a/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization/ref_files/vck190/run_app.sh b/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization/ref_files/vck190/run_app.sh index d6a498427b..0a77b98f02 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization/ref_files/vck190/run_app.sh +++ b/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization/ref_files/vck190/run_app.sh @@ -1,5 +1,5 @@ #/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +#Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT #* export PATH=$PATH:/sbin diff --git a/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization/ref_files/vck190/system-user.dtsi b/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization/ref_files/vck190/system-user.dtsi index 778a52f8fd..a964b34ebb 100755 --- a/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization/ref_files/vck190/system-user.dtsi +++ b/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization/ref_files/vck190/system-user.dtsi @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: MIT */ diff --git a/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization/ref_files/zcu104/Makefile b/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization/ref_files/zcu104/Makefile index 824cfe380a..00d5a78be5 100755 --- a/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization/ref_files/zcu104/Makefile +++ b/Vitis_Platform_Creation/Feature_Tutorials/02_petalinux_customization/ref_files/zcu104/Makefile @@ -1,5 +1,5 @@ #/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +#Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT #*/ @@ -10,7 +10,7 @@ ABS_SW_PATH=$(ABS_BUILD_PATH)/$(PETALINUX_PROJ_NAME) PETALINUX_DIR=$(ABS_SW_PATH) PETALINUX_CONFIG=$(PETALINUX_DIR)/project-spec/configs/config PETALINUX_ROOTFS_CONFIG=$(PETALINUX_DIR)/project-spec/configs/rootfs_config -XSA ?=${PLATFORM_REPO_PATHS}/xilinx_zcu104_base_202510_1/hw/hw.xsa +XSA ?=${PLATFORM_REPO_PATHS}/xilinx_zcu104_base_202520_1/hw/hw.xsa IMAGE_DIR=$(ABS_BUILD_PATH)/$(PETALINUX_PROJ_NAME)/images/linux/ # -------------------------------------- diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/thin-plat/Makefile b/Vitis_Platform_Creation/Feature_Tutorials/03_Vitis_Export_To_Vivado/Makefile similarity index 69% rename from Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/thin-plat/Makefile rename to Vitis_Platform_Creation/Feature_Tutorials/03_Vitis_Export_To_Vivado/Makefile index 3f3fbd5001..40d77db8e4 100644 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/thin-plat/Makefile +++ b/Vitis_Platform_Creation/Feature_Tutorials/03_Vitis_Export_To_Vivado/Makefile @@ -1,17 +1,15 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -# This makefile replaces the one from origina Thin Platform, to adapt it to this repo -# date: 13 Oct 2023 -# modified by Daniele Bagni - +# +# Copyright (C) 2021-2022, Xilinx, Inc. All rights reserved. +# Copyright (C) 2022-2025, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: X11 +# # Top-level Makefile -- Calls sub-makefiles ECHO = @echo ################################################################################ -# Variables needed for AMD/XILINX tools version checking, PLEASE DO NOT MODIFY # +# Variables needed for AMD tools version checking, PLEASE DO NOT MODIFY # ################################################################################ REQUIRED_VERSION = 2025.1 VIVADO_VERSION := $(shell vivado -version 2>/dev/null | grep "vivado ") @@ -29,16 +27,14 @@ export SW_BUILD_TOOL := petalinux # XPFM_PRE_BUILDS = false (Build xpfm) or true (Use xpfm pre-builds) export XPFM_PRE_BUILDS := false -#false # LINUX_PRE_BUILDS = false (Build linux) or true (Use linux pre-builds) -export LINUX_PRE_BUILDS := true -#false +export LINUX_PRE_BUILDS := false # ILA_EN = 0 (Disabled) or 1 (Enabled) export ILA_EN := 0 -# BOARD_NAME = vck190 (prod) or vek280 (revB) or vek280_es1 (revA) +# BOARD_NAME = vck190 or vek280 or vek280_es1 export BOARD_NAME := vck190 ########################################################### @@ -46,7 +42,7 @@ export BOARD_NAME := vck190 ########################################################### # LINUX_TMP_DIR = Any dir which is not NFS -export LINUX_TMP_DIR := /tmp/${USER}/${REQUIRED_VERSION}/${SW_BUILD_TOOL} +export LINUX_TMP_DIR := /tmp/${USER}/${REQUIRED_VERSION}/${BOARD_NAME}/${SW_BUILD_TOOL} # LINUX_YOCTO_ROOT = Directory where yocto tools are installed # Used ONLY when SW_BUILD_TOOL := yocto! @@ -74,15 +70,16 @@ export PLATFORM_CUSTOM := ${BOARD_NAME}_thin export LINUX_MACHINE := ${BOARD_NAME}-versal ifeq (${BOARD_NAME}, vck190) -export DEVICE_NAME := xcvc1902-vsva2197-2MP-e-S -export PLATFORM_PRE_BUILD := xilinx_vck190_base_202510_1 + export DEVICE_NAME := xcvc1902-vsva2197-2MP-e-S + export PLATFORM_PRE_BUILD := xilinx_vck190_base_202410_1 else ifeq (${BOARD_NAME}, vek280) -export DEVICE_NAME := xcve2802-vsvh1760-2MP-e-S -export PLATFORM_PRE_BUILD := xilinx_vek280_base_202510_1 + export DEVICE_NAME := xcve2802-vsvh1760-2MP-e-S + export PLATFORM_PRE_BUILD := xilinx_vek280_base_202410_1 else -export DEVICE_NAME := xcve2802-vsvh1760-2LP-e-S-es1 -export PLATFORM_PRE_BUILD := xilinx_vek280_base_202510_1 + export DEVICE_NAME := xcvc1902-vsva2197-2MP-e-S + export PLATFORM_PRE_BUILD := xilinx_vck190_base_202410_1 endif +export PART := $(DEVICE_NAME) LINUX_SRC_DIR := ./linux/src LINUX_BUILD_DIR := ./linux/${LINUX_MACHINE} @@ -92,14 +89,14 @@ XSA_DIR := ./vivado/build/xsa_platform XSA_FILE := ${XSA_DIR}/${PLATFORM_CUSTOM}.xsa XSA_PRE_BUILD := ${PLATFORM_REPO_PATHS}/${PLATFORM_PRE_BUILD}/hw/hw.xsa -XPFM_EXPORT := ./vitis/xpfm_export/build/platform/${PLATFORM_CUSTOM}/export/${PLATFORM_CUSTOM} -XPFM_EXPORT_SW := ${XPFM_EXPORT}/sw +#XPFM_EXPORT := ./vitis/xpfm_export/build/platform/${PLATFORM_CUSTOM}/export/${PLATFORM_CUSTOM} +#XPFM_EXPORT_SW := ${XPFM_EXPORT}/sw XPFM_PRE_BUILD := ${PLATFORM_REPO_PATHS}/${PLATFORM_PRE_BUILD} ifeq (${LINUX_PRE_BUILDS}, false) - LINUX_SRC_IMAGES := ${LINUX_BUILD_DIR}/images/linux + export LINUX_SRC_IMAGES := ${LINUX_BUILD_DIR}/images/linux else - LINUX_SRC_IMAGES := ${SDKTARGETSYSROOT}/../.. + export LINUX_SRC_IMAGES := ${SDKTARGETSYSROOT}/../.. endif ifeq (${XPFM_PRE_BUILDS}, false) @@ -122,7 +119,7 @@ LINUX_BUILD_SKIP := false ############## # Build Flow # ############## -.PHONY: clean help all vivado vitis_platform vitis_ip vitis ps_apps linux +.PHONY: clean help all vivado vitis_platform vitis_ip vitis ps_apps linux vss vma_export help:: $(ECHO) "Makefile Usage:" @@ -175,8 +172,8 @@ help:: $(ECHO) " Command to remove all the generated files." -all: version_check vivado_platform vitis_platform linux dtg bif vitis_ip full_impl ps_apps package -all_part1: version_check vivado_platform vitis_platform linux dtg +#all: version_check vivado_platform vitis_platform linux dtg bif vitis_ip full_impl ps_apps package +all: vivado_platform vitis_ip vma_export vivado_fixed linux vitis_platform ps_apps package all_targets: $(MAKE) all TARGET=hw @@ -217,7 +214,7 @@ ifeq (${TARGET}, hw_emu) $(ECHO) "[ERROR] XPFM_PRE_BUILDS = true and TARGET = hw_emu is NOT supported!"; exit 1 endif endif - $(ECHO) "AMD TOOLS & VERSION CHECK SUCCESSFUL" + $(ECHO) "AMD TOOLS & VERSION CHECK SUCCESSFUL" vivado_platform: ifeq (${XPFM_PRE_BUILDS}, true) @@ -242,77 +239,82 @@ endif linux_pre_build: ./linux/sysroot ./linux/sysroot: - ln -s $(abspath ${SDKTARGETSYSROOT}/../..) ./linux/sysroot + ln -s $(abspath ${SDKTARGETSYSROOT}/../..) ./linux/sysroot dtg: -ifeq (${XPFM_PRE_BUILDS}, false) -ifeq (${LINUX_PRE_BUILDS}, true) $(MAKE) all -C linux/dtg -endif -endif +#ifeq (${XPFM_PRE_BUILDS}, false) +#ifeq (${LINUX_PRE_BUILDS}, true) +# $(MAKE) all -C linux/dtg +#endif +#endif vitis_platform: ifeq (${XPFM_PRE_BUILDS}, true) $(MAKE) vitis_platform_pre_build -else - $(MAKE) platform -C vitis/xpfm_export +else + $(MAKE) platform -C vitis endif -vitis_platform_pre_build: ${XPFM_EXPORT} -${XPFM_EXPORT}: - mkdir -p ${XPFM_EXPORT} - cp -rf ${XPFM_PRE_BUILD}/* ${XPFM_EXPORT} - mv -f ${XPFM_EXPORT}/${PLATFORM_PRE_BUILD}.xpfm ${XPFM_EXPORT}/${PLATFORM_CUSTOM}.xpfm - mv -f ${XPFM_EXPORT_BOOT}/* ${XPFM_EXPORT_SW} - rm -rf ${XPFM_EXPORT_SW}/*.bif - -bif: - $(MAKE) ${XPFM_EXPORT_BOOT}/linux.bif -ifeq (${LINUX_PRE_BUILDS}, false) - $(MAKE) ${XPFM_EXPORT_SW}/rootfs.cpio.gz.u-boot -else - $(MAKE) ${XPFM_EXPORT_SW}/rootfs.ext4 -ifeq (${XPFM_PRE_BUILDS}, false) - $(MAKE) ${XPFM_EXPORT_SW}/system.dtb -endif -endif - -${XPFM_EXPORT_BOOT}/linux.bif: ${LINUX_SRC_DIR}/boot_custom.bif - cp -f ${LINUX_SRC_DIR}/boot_custom.bif ${XPFM_EXPORT_BOOT}/linux.bif - -${XPFM_EXPORT_SW}/rootfs.cpio.gz.u-boot: ${LINUX_SRC_IMAGES}/rootfs.cpio.gz.u-boot - cp -f ${LINUX_SRC_IMAGES}/system.dtb ${XPFM_EXPORT_SW}/system.dtb - cp -f ${LINUX_SRC_IMAGES}/u-boot.elf ${XPFM_EXPORT_SW}/u-boot.elf - cp -f ${LINUX_SRC_IMAGES}/bl31.elf ${XPFM_EXPORT_SW}/bl31.elf - cp -f ${LINUX_SRC_IMAGES}/Image ${XPFM_EXPORT_SW}/Image - cp -f ${LINUX_SRC_IMAGES}/rootfs.cpio.gz.u-boot ${XPFM_EXPORT_SW}/rootfs.cpio.gz.u-boot - cp -f ${LINUX_SRC_IMAGES}/boot.scr ${XPFM_EXPORT_XRT_IMAGE}/boot.scr - -${XPFM_EXPORT_SW}/rootfs.ext4: ${LINUX_SRC_IMAGES}/rootfs.ext4 - cp -f ${LINUX_SRC_IMAGES}/Image ${XPFM_EXPORT_SW}/Image - cp -f ${LINUX_SRC_IMAGES}/rootfs.ext4 ${XPFM_EXPORT_SW}/rootfs.ext4 - cp -f ${LINUX_SRC_IMAGES}/boot.scr ${XPFM_EXPORT_XRT_IMAGE}/boot.scr - -${XPFM_EXPORT_SW}/system.dtb: ${LINUX_DTB_DIR}/system-top.dtb - cp -f ${LINUX_DTB_DIR}/system-top.dtb ${XPFM_EXPORT_SW}/system.dtb - cp -f ${LINUX_SRC_IMAGES}/u-boot.elf ${XPFM_EXPORT_SW}/u-boot.elf - cp -f ${LINUX_SRC_IMAGES}/bl31.elf ${XPFM_EXPORT_SW}/bl31.elf +#vitis_platform_pre_build: ${XPFM_EXPORT} +#${XPFM_EXPORT}: +# mkdir -p ${XPFM_EXPORT} +# cp -rf ${XPFM_PRE_BUILD}/* ${XPFM_EXPORT} +# mv -f ${XPFM_EXPORT}/${PLATFORM_PRE_BUILD}.xpfm ${XPFM_EXPORT}/${PLATFORM_CUSTOM}.xpfm +# mv -f ${XPFM_EXPORT_BOOT}/* ${XPFM_EXPORT_SW} +# rm -rf ${XPFM_EXPORT_SW}/*.bif +# +#bif: +# $(MAKE) ${XPFM_EXPORT_BOOT}/linux.bif +#ifeq (${LINUX_PRE_BUILDS}, false) +# $(MAKE) ${XPFM_EXPORT_SW}/rootfs.cpio.gz.u-boot +#else +# $(MAKE) ${XPFM_EXPORT_SW}/rootfs.ext4 +#ifeq (${XPFM_PRE_BUILDS}, false) +# $(MAKE) ${XPFM_EXPORT_SW}/system.dtb +#endif +#endif +# +#${XPFM_EXPORT_BOOT}/linux.bif: ${LINUX_SRC_DIR}/boot_custom.bif +# cp -f ${LINUX_SRC_DIR}/boot_custom.bif ${XPFM_EXPORT_BOOT}/linux.bif +# +#${XPFM_EXPORT_SW}/rootfs.cpio.gz.u-boot: ${LINUX_SRC_IMAGES}/rootfs.cpio.gz.u-boot +# cp -f ${LINUX_SRC_IMAGES}/system.dtb ${XPFM_EXPORT_SW}/system.dtb +# cp -f ${LINUX_SRC_IMAGES}/u-boot.elf ${XPFM_EXPORT_SW}/u-boot.elf +# cp -f ${LINUX_SRC_IMAGES}/bl31.elf ${XPFM_EXPORT_SW}/bl31.elf +# cp -f ${LINUX_SRC_IMAGES}/Image ${XPFM_EXPORT_SW}/Image +# cp -f ${LINUX_SRC_IMAGES}/rootfs.cpio.gz.u-boot ${XPFM_EXPORT_SW}/rootfs.cpio.gz.u-boot +# cp -f ${LINUX_SRC_IMAGES}/boot.scr ${XPFM_EXPORT_XRT_IMAGE}/boot.scr +# +#${XPFM_EXPORT_SW}/rootfs.ext4: ${LINUX_SRC_IMAGES}/rootfs.ext4 +# cp -f ${LINUX_SRC_IMAGES}/Image ${XPFM_EXPORT_SW}/Image +# cp -f ${LINUX_SRC_IMAGES}/rootfs.ext4 ${XPFM_EXPORT_SW}/rootfs.ext4 +# cp -f ${LINUX_SRC_IMAGES}/boot.scr ${XPFM_EXPORT_XRT_IMAGE}/boot.scr +# +#${XPFM_EXPORT_SW}/system.dtb: ${LINUX_DTB_DIR}/system-top.dtb +# cp -f ${LINUX_DTB_DIR}/system-top.dtb ${XPFM_EXPORT_SW}/system.dtb +# cp -f ${LINUX_SRC_IMAGES}/u-boot.elf ${XPFM_EXPORT_SW}/u-boot.elf +# cp -f ${LINUX_SRC_IMAGES}/bl31.elf ${XPFM_EXPORT_SW}/bl31.elf vitis_ip: - $(MAKE) all -C vitis/ip + $(MAKE) vitis_ip -C vitis ps_apps: $(MAKE) all -C ps_apps/linux +vma_export: + $(MAKE) vma_link -C vitis + full_impl: $(MAKE) link -C vitis +vivado_fixed: + $(MAKE) vivado_fixed -C vivado + package: $(MAKE) package_linux -C vitis clean_vitis: - $(MAKE) clean -C vitis/xpfm_export - $(MAKE) clean -C vitis/ip $(MAKE) clean -C ps_apps/linux $(MAKE) clean -C vitis @@ -321,6 +323,7 @@ ultraclean_vitis: $(MAKE) clean_vitis TARGET=hw_emu clean: + $(MAKE) clean -C vitis $(MAKE) clean -C vivado $(MAKE) clean -C linux/${SW_BUILD_TOOL} $(MAKE) clean -C linux/dtg @@ -329,3 +332,4 @@ clean: ultraclean: $(MAKE) clean TARGET=hw $(MAKE) clean TARGET=hw_emu + diff --git a/Vitis_Platform_Creation/Feature_Tutorials/03_Vitis_Export_To_Vivado/README.md b/Vitis_Platform_Creation/Feature_Tutorials/03_Vitis_Export_To_Vivado/README.md index 7d36c0392f..5917f247f7 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/03_Vitis_Export_To_Vivado/README.md +++ b/Vitis_Platform_Creation/Feature_Tutorials/03_Vitis_Export_To_Vivado/README.md @@ -13,7 +13,7 @@ # Vitis Export to Vivado Flow -***Version: Vivado and Vitis 2025.1*** +***Version: Vivado and Vitis 2025.2*** This tutorial has been subject to change for the last couple of releases following the updates and improvements of the tools. @@ -151,12 +151,23 @@ param=project.enableUnifiedAIEFlow=true A cleaned up example for the Vitis linker configuration is provided here: [vitis/src/system.cfg](vitis/src/system.cfg). +## Modifying build recipe +With the vss folder no longer in use, a few references to old locations need to be updated in the build makefiles. +The following files require modification + +| Modified example | Original file from VSS tutorial +| -------- | ---------- +| [./Makefile](./Makefile) | [../../../Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/Makefile](../../../Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/Makefile) +| [./vitis/Makefile](./vitis/Makefile) | [../../../Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/Makefile](../../../Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/Makefile) +| [./ps_apps/linux/aie_dly_test/Makefile](./ps_apps/linux/aie_dly_test/Makefile) | [../../../Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/ps_apps/linux/aie_dly_test/Makefile](../../../Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/ps_apps/linux/aie_dly_test/Makefile) + + ## Building the modified design ### Prerequisites -Setup the Vitis 2025.1 tools +Setup the Vitis tool ``` source /settings64.sh ``` @@ -169,8 +180,7 @@ export SDKTARGETSYSROOT= ### Build instructions -Makefiles are provided to build everything from the top folder. -As the VSS rule is no longer applicable, the `make all` rule needs to be modified to ommit `vss` rule. +Modify or replace the makefiles according to examples and run `make all` from the top folder. Alternatively run step by step, by choosing from the following: ``` @@ -198,7 +208,7 @@ git move vss/python vitis/python **Note:** This require understanding how to create and manage Vivado projects and block designs using Vivado example design as template. The tutorial is prepared to quickly retarget to other boards and devices. This can be achieved by adding more alternatives in the Vivado folder. -If the corresponding board exist [Board Store](https://github.com/Xilinx/XilinxBoardStore/tree/2025.1), then copy either the [vck190](../../../Vitis_System_Design/Design_Tutorial/02-Versal_Vitis_Subsystem_Flow/vivado/vck190) or [vek280](../../../Vitis_System_Design/Design_Tutorial/02-Versal_Vitis_Subsystem_Flow/vivado/vek280) to a new folder matching the board name. +If the corresponding board exist [Board Store](https://github.com/Xilinx/XilinxBoardStore), then copy either the [vck190](../../../Vitis_System_Design/Design_Tutorial/02-Versal_Vitis_Subsystem_Flow/vivado/vck190) or [vek280](../../../Vitis_System_Design/Design_Tutorial/02-Versal_Vitis_Subsystem_Flow/vivado/vek280) to a new folder matching the board name. Then use Vivado example design (Picking an extensible platform) for the specific board and once generated write a new `dr.bd.tcl` file. The `Makefiles` in the top folder and in `vivado` folder will require modifying the `BOARD_NAME` alternatives so the called scripts get parameter arguments matching the selected board. diff --git a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/thin-plat/ps_apps/linux/aie_test/Makefile b/Vitis_Platform_Creation/Feature_Tutorials/03_Vitis_Export_To_Vivado/ps_apps/linux/aie_dly_test/Makefile similarity index 59% rename from Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/thin-plat/ps_apps/linux/aie_test/Makefile rename to Vitis_Platform_Creation/Feature_Tutorials/03_Vitis_Export_To_Vivado/ps_apps/linux/aie_dly_test/Makefile index a1b0443683..43b1f85706 100644 --- a/Developer_Contributed/02-AIE_DSP_with_Makefile_and_GUI/files/src/thin-plat/ps_apps/linux/aie_test/Makefile +++ b/Vitis_Platform_Creation/Feature_Tutorials/03_Vitis_Export_To_Vivado/ps_apps/linux/aie_dly_test/Makefile @@ -1,34 +1,27 @@ -# Copyright © 2023 Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: MIT - -# Date: 13 Oct 2023 -# modified by Daniele Bagni +# +# Copyright (C) 2021-2022, Xilinx, Inc. All rights reserved. +# Copyright (C) 2022-2025, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: X11 +# ECHO := @echo SYSROOT := ../../../linux/sysroot/sysroots/cortexa72-cortexa53-amd-linux -APP_NAME := xrt_host +APP_NAME := aie_dly_test APP_EXE := ../exe/${APP_NAME}.exe APP_SRC := ./src/${APP_NAME}.cpp APP_SRC_DEP := ./src/* -APP_SRC_CTRL := ./../../../vitis/ip/aie/Work/ps/c_rts/aie_control_xrt.cpp +APP_SRC_CTRL := ./../../../vitis/ip/aie/datamove_app_ws/Work/ps/c_rts/aie_control_xrt.cpp GCC ?= aarch64-linux-gnu-g++ -GCC_INCLUDES := -I${SYSROOT}/usr/include \ - -I${SYSROOT}/usr/include/xrt \ - -I${SYSROOT}/usr/include/xaiengine \ - -I${XILINX_VITIS}/aietools/include \ - -I${XILINX_VITIS}/include \ - -I${DSPLIB_ROOT}/L1/include/aie \ - -I${DSPLIB_ROOT}/L1/src/aie \ - -I${DSPLIB_ROOT}/L1/tests/aie/inc \ - -I${DSPLIB_ROOT}/L1/tests/aie/src \ - -I${DSPLIB_ROOT}/L2/include/aie \ - -I$(DSPLIB_ROOT)/L2/tests/aie/common/inc \ - -I../../../vitis/ip/aie/src \ - -I../../../vitis/ip/aie/src/graphs +GCC_INCLUDES := -I${SYSROOT}/usr/include \ + -I${SYSROOT}/usr/include/xrt \ + -I${SYSROOT}/usr/include/xaiengine \ + -I${XILINX_VITIS}/aietools/include \ + -I../../../vitis/ip/aie/src \ + -I../../../vitis/ip/aie/ GCC_C_FLAGS := -O -Wall -std=c++17 -DXAIE_DEBUG \ -pthread \ @@ -57,3 +50,5 @@ $(APP_EXE): $(APP_SRC_DEP) $(APP_SRC_CTRL) ${SYSROOT} clean: rm -rf *.o $(APP_EXE) + + diff --git a/Vitis_Platform_Creation/Feature_Tutorials/03_Vitis_Export_To_Vivado/vitis/Makefile b/Vitis_Platform_Creation/Feature_Tutorials/03_Vitis_Export_To_Vivado/vitis/Makefile new file mode 100644 index 0000000000..53c8727083 --- /dev/null +++ b/Vitis_Platform_Creation/Feature_Tutorials/03_Vitis_Export_To_Vivado/vitis/Makefile @@ -0,0 +1,180 @@ +# +# Copyright (C) 2021-2022, Xilinx, Inc. All rights reserved. +# Copyright (C) 2022-2025, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: X11 +# + +ECHO := @echo + +TARGET ?= hw +BOARD_NAME ?= vck190 +export PLATFORM_CUSTOM ?= ${BOARD_NAME}_thin +LINUX_PRE_BUILDS ?= false + +XSA_PLATFORM := ../vivado/build/xsa_platform/${PLATFORM_CUSTOM}.xsa +export XSA_FIXED := ../vivado/build/xsa_platform/${PLATFORM_CUSTOM}_fixed.xsa + +#XPFM_VIVADO_EXPORT := $(abspath ../vitis/xpfm_export/build/platform/${PLATFORM_CUSTOM}/export/${PLATFORM_CUSTOM}) +PFM_EXPORT := ./build_pfm/pfm/export/pfm +XPFM := ${PFM_EXPORT}/pfm.xpfm +XPFM_XSA := ${PFM_EXPORT}/hw/${PLATFORM_CUSTOM}_fixed.xsa + +LINUX_ABS_PATH := $(abspath ../linux/${LINUX_MACHINE}/images/linux) +LINUX_PATH := ../linux/${LINUX_MACHINE}/images/linux +LINUX_KERNEL := ${LINUX_PATH}/Image +LINUX_DTB := ${LINUX_PATH}/system.dtb +PFM_DTB := ${PFM_EXPORT}/sw/boot/system.dtb +#LINUX_DTB := ${PFM_EXPORT}/hw/sdt/system.dtb +LINUX_BL31 := ${LINUX_PATH}/bl31.elf +LINUX_UBOOT := ${LINUX_PATH}/u-boot.elf +#LINUX_BOOTSCR := ${LINUX_ABS_PATH}/${PLATFORM_FIXED}/xrt/image/boot.scr +LINUX_BOOTSCR := ${LINUX_PATH}/boot.scr + +ifeq (${LINUX_PRE_BUILDS}, false) +LINUX_ROOTFS := ${LINUX_PATH}/rootfs.cpio.gz.u-boot +LINUX_ROOTFS_TYPE := fat32 +else +LINUX_ROOTFS := ${LINUX_PATH}/rootfs.ext4 +LINUX_ROOTFS_TYPE := ext4 +endif + +IP_DIR := ./ip +XO := $(wildcard ${IP_DIR}/xo_hw/*.xo) +VSS ?= vss_top +VSSFILE ?= ../vss/build/${VSS}/${VSS}.vss +XCLBIN := my.xclbin +XSA := ${PLATFORM_CUSTOM}.xsa +VMA := ${PLATFORM_CUSTOM}.vma +LIBADF := $(wildcard ../vitis/${IP_DIR}/aie/*_libadf.a) + +PS_APPS_LINUX_DIR := ../ps_apps/linux +PS_LINUX_EXE := $(wildcard ${PS_APPS_LINUX_DIR}/exe/*.exe) + +SD_CARD_LINUX := ../package_linux_${TARGET} +BUILD_DIR := build_${TARGET} + +ILA_LTX := ${BUILD_DIR}/_x/link/vivado/vpl/prj/probe_0.ltx + +# Force ILA_EN=0 (Disabled) for TARGET=hw_emu +ifeq (${TARGET}, hw_emu) + ILA_EN = 0 +else + ILA_EN ?= 0 +endif + +ifeq (${ILA_EN}, 1) + SYSTEM_CFG := $(wildcard ./src/*.cfg) +else + SYSTEM_CFG := ./src/system.cfg +endif + +.PHONY: clean all vitis_ip platform + +help:: + $(ECHO) "Makefile Usage:" + $(ECHO) " make vitis_ip" + $(ECHO) " Compile and build HLS and RTL blocks for Vitis Region" + $(ECHO) "" + $(ECHO) " make link" + $(ECHO) " Link vitis region to extensible XSA, run synth and implementaion using Vitis Integrated Flow" + $(ECHO) "" + $(ECHO) " make vma_link" + $(ECHO) " Link vitis region to extensible XSA and export a VMA." + $(ECHO) "" + $(ECHO) " make platform" + $(ECHO) " Build a Vitis platform component using fixed XSA" + $(ECHO) "" + $(ECHO) " make package_linux" + $(ECHO) " Package the design and generate SD Card for Linux application" + $(ECHO) "" + $(ECHO) " make clean" + $(ECHO) " Command to remove all the generated files." + +${BUILD_DIR}: + mkdir ${BUILD_DIR} + +vitis_ip: + $(MAKE) all -C ${IP_DIR} + +platform: + vitis -s vitis_platform.py |& tee vitis_pfm.log + +link: ${BUILD_DIR} ${BUILD_DIR}/${XSA} + +vma_link: ${BUILD_DIR} ${BUILD_DIR}/${VMA} + +${BUILD_DIR}/${VMA}: ${XO} ${SYSTEM_CFG} + cd ${BUILD_DIR} && \ + v++ --link --debug --save-temps \ + --target ${TARGET} \ + --platform ../${XSA_PLATFORM} \ + $(addprefix --config ../, ${SYSTEM_CFG}) \ + $(addprefix ../, ${XO}) \ + $(addprefix ../, ${LIBADF}) \ + --export_archive \ + --output ${VMA} \ + |& tee vpp_link.log + +${BUILD_DIR}/${XSA}: ${XO} ${VSSFILE} ${SYSTEM_CFG} + cd ${BUILD_DIR} && \ + v++ --link --debug --save-temps \ + --target ${TARGET} \ + --platform ../${XSA_PLATFORM} \ + $(addprefix --config ../, ${SYSTEM_CFG}) \ + $(addprefix ../, ${XO}) \ + $(addprefix ../, ${VSSFILE}) \ + --export_archive \ + --output ${VMA} \ + |& tee vpp_link.log + +package_linux: ${SD_CARD_LINUX} + +## Package the XCLBIN +${BUILD_DIR}/${XCLBIN}: ${LIBADF} + cd ${BUILD_DIR} && \ + v++ --package \ + --target ${TARGET} \ + --platform $(addprefix ../, ${XPFM}) \ + --package.defer_aie_run \ + $(addprefix ../, ${LIBADF}) \ + -o ${XCLBIN} + |& tee vpp_pack_xclbin.log +# make update_ila + +#${SD_CARD_LINUX}: ${BUILD_DIR}/${XSA} ${PS_LINUX_EXE} ${GRAPH_O} ${LINUX_KERNEL} ${LINUX_ROOTFS} ${LINUX_DTB} +${SD_CARD_LINUX}: ${LIBADF} ${PS_LINUX_EXE} ${LINUX_KERNEL} ${LINUX_ROOTFS} ${PFM_DTB} ${LINUX_BL31} ${LINUX_UBOOT} ${LINUX_BOOTSCR} + cd ${BUILD_DIR} && \ + v++ --package --debug --save-temps \ + --target ${TARGET} \ + --platform $(addprefix ../, ${XPFM}) \ + --package.defer_aie_run \ + --package.out_dir $(addprefix ../,${SD_CARD_LINUX}) \ + --package.boot_mode=sd \ + --package.no_image \ + --package.image_format=${LINUX_ROOTFS_TYPE} \ + --package.sd_file=$(addprefix ../, ${LINUX_KERNEL}) \ + --package.rootfs=$(addprefix ../, ${LINUX_ROOTFS}) \ + --package.dtb=$(addprefix ../, ${PFM_DTB}) \ + --package.bl31_elf=$(addprefix ../, ${LINUX_BL31}) \ + --package.uboot=$(addprefix ../, ${LINUX_UBOOT}) \ + $(addprefix ../, ${LIBADF}) \ + $(addprefix --package.sd_file=../, ${PS_LINUX_EXE}) \ + $(addprefix --package.sd_file=../, ${LINUX_BOOTSCR}) \ + -o ${XCLBIN} \ + |& tee vpp_pack_sd.log + echo ${PLATFORM_CUSTOM} > ${SD_CARD_LINUX}/sd_card/platform_desc.txt +# make update_ila + + + +update_ila: +ifeq (${TARGET}, hw) + if [ -e ${ILA_LTX} ] ; \ + then cp -f ${ILA_LTX} $(SD_CARD)/ ; \ + else echo "no probe_0 ltx file" ; \ + fi +endif + +clean: + $(MAKE) clean -C ip + rm -rf ${SD_CARD_LINUX} ${SD_CARD_BAREMETAL} ${BUILD_DIR} build_pfm diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/README.md b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/README.md index 228fc9c8cb..20a09375e9 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/README.md +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/README.md @@ -13,7 +13,7 @@ # Versal Extensible Hardware Design Validation -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** In this tutorial, you will learn how to validate an AMD Versal® ACAP extensible platform. This tutorial is an 'add-on' to the basic [Versal platform creation tutorial](../../Design_Tutorials/03_Edge_VCK190/README.md). So for each step, there will be a pointer to the corresponding part of that tutorial, as required. @@ -194,7 +194,7 @@ If the PDI can't load successfully, please check the CIPS configuration. #### Test3: Peripheral bare-metal test - Please refer to [Embedded Design Tutorial](https://github.com/Xilinx/Embedded-Design-Tutorials/blob/master/docs/Introduction/Versal-EDT/docs/2-cips-noc-ip-config.rst#creating-a-hello-world-application-for-the-arm-cortex-a72-on-ocm) to create a bare-metal application based on the fixed XSA file and run on board to test the peripherals. + Please refer to [Embedded Design Tutorial](https://github.com/Xilinx/Embedded-Design-Tutorials/blob/master/docs/Getting_Started/Versal-EDT/docs/2-cips-noc-ip-config.rst) to create a bare-metal application based on the fixed XSA file and run on board to test the peripherals. Application templates can choose the Peripheral or memory test: diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/Makefile b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/Makefile index 0a445528de..154c803b11 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/Makefile +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/Makefile @@ -1,5 +1,5 @@ # /* -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +# Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. # SPDX-License-Identifier: MIT # */ EXTENSIBLE_XSA ?= diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/aie.cfg b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/aie.cfg index 74f492492c..ab85a10d83 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/aie.cfg +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/aie.cfg @@ -1,5 +1,5 @@ #/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +#Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT #* include=src @@ -7,4 +7,4 @@ include=src Xchess=main:darts.xargs=-nb log-level=1 stacksize=1024 -heapsize=1024 \ No newline at end of file +heapsize=1024 diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/data/input.txt b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/data/input.txt index a709affbe5..244598ef4e 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/data/input.txt +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/data/input.txt @@ -1,3 +1,7 @@ +# /* +# Copyright (C) 2025, Advanced Micro Devices, Inc. All rights reserved. +# SPDX-License-Identifier: MIT +# */ 1 2 3 diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/mm2s.cfg b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/mm2s.cfg index ca1f1475e9..657859616e 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/mm2s.cfg +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/mm2s.cfg @@ -1,5 +1,5 @@ #/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +#Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT #* [hls] @@ -16,4 +16,4 @@ syn.interface.m_axi_auto_max_ports=0 syn.interface.m_axi_conservative_mode=1 syn.rtl.deadlock_detection=sim syn.rtl.kernel_profile=1 -package.output.syn=true \ No newline at end of file +package.output.syn=true diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/mm2s_1.cpp b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/mm2s_1.cpp index 909378da5e..efad61ba23 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/mm2s_1.cpp +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/mm2s_1.cpp @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: MIT */ #include diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/s2mm.cfg b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/s2mm.cfg index daea99f8d3..a0528c8b52 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/s2mm.cfg +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/s2mm.cfg @@ -1,5 +1,5 @@ #/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +#Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT #* [hls] @@ -16,4 +16,4 @@ syn.interface.m_axi_auto_max_ports=0 syn.interface.m_axi_conservative_mode=1 syn.rtl.deadlock_detection=sim syn.rtl.kernel_profile=1 -package.output.syn=true \ No newline at end of file +package.output.syn=true diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/s2mm_1.cpp b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/s2mm_1.cpp index c52aa59f6f..bf076fc33f 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/s2mm_1.cpp +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/s2mm_1.cpp @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: MIT */ #include diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/src/graph.cpp b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/src/graph.cpp index 0ee69ff590..c18d7d8f2b 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/src/graph.cpp +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/src/graph.cpp @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: MIT */ #include "graph.h" diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/src/graph.h b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/src/graph.h index 326c41b5bf..04613088bf 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/src/graph.h +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/src/graph.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: MIT */ #include diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/src/kernels.h b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/src/kernels.h index 020f0a74d4..0eb04cb18b 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/src/kernels.h +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/src/kernels.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: MIT */ #ifndef KERNEL_H diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/src/loopback.cc b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/src/loopback.cc index 1a06aacc5e..1c3df2ff36 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/src/loopback.cc +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/src/loopback.cc @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: MIT */ #include diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/Makefile b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/Makefile index 9486d9034b..2acddb45fb 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/Makefile +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/Makefile @@ -1,5 +1,5 @@ # /* -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +# Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. # SPDX-License-Identifier: MIT # */ HOST_EXE = ../main.elf diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/golden.h b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/golden.h index 446113a107..c2f59c1256 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/golden.h +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/golden.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: MIT */ #pragma once diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/input.h b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/input.h index 688a472e63..5e32bbc0f0 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/input.h +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/input.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: MIT */ #pragma once diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/lscript.ld b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/lscript.ld index 970535b7b5..692ca85bb1 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/lscript.ld +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/lscript.ld @@ -1,5 +1,5 @@ /* -/*Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +/*Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. /*SPDX-License-Identifier: MIT /**/ diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/main.cpp b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/main.cpp index 06e8c0cd34..6eb34ed572 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/main.cpp +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/main.cpp @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: MIT */ #include diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/platform.cpp b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/platform.cpp index 067a2feb26..8aafcb800c 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/platform.cpp +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/platform.cpp @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: MIT */ #include "xparameters.h" diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/platform.h b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/platform.h index 27466d3f17..fd3a385f33 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/platform.h +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/sw/platform.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: MIT */ #ifndef __PLATFORM_H_ diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/system.cfg b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/system.cfg index 40ec4432e5..181d7fea26 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/system.cfg +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/aie_validation/system.cfg @@ -1,5 +1,5 @@ #/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +#Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT #* [connectivity] diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/Makefile b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/Makefile index e57d4c47d5..30763f41d3 100755 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/Makefile +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/Makefile @@ -1,5 +1,5 @@ # /* -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +# Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. # SPDX-License-Identifier: MIT # */ EXTENSIBLE_XSA ?= @@ -80,4 +80,4 @@ clean: rm -rf _x v++_* ${XOS} *.o.* *.xo.* \ *.xclbin* *.xsa *_log *.log Work Map_Report.csv *.bin mm2s_1 s2mm_1\ BOOT* *.xo emu_qemu_scripts *.cdo *.bif compile_log_pre *.elf *.o launch_hw_emu.sh qemu_args.txt *.xsa xnwOut *.pdi fixed_platform v++.package_summary *.link_summary libadf* lpd* NOC* pmc* plm* sd_card* sim ilpProblem* sol.db drivers .Xil .ipcache package.hw* ext_platform_wrapper_* - make -C sw clean \ No newline at end of file + make -C sw clean diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/mm2s.cfg b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/mm2s.cfg index ca1f1475e9..657859616e 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/mm2s.cfg +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/mm2s.cfg @@ -1,5 +1,5 @@ #/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +#Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT #* [hls] @@ -16,4 +16,4 @@ syn.interface.m_axi_auto_max_ports=0 syn.interface.m_axi_conservative_mode=1 syn.rtl.deadlock_detection=sim syn.rtl.kernel_profile=1 -package.output.syn=true \ No newline at end of file +package.output.syn=true diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/mm2s_1.cpp b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/mm2s_1.cpp index 909378da5e..efad61ba23 100755 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/mm2s_1.cpp +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/mm2s_1.cpp @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: MIT */ #include diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/s2mm.cfg b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/s2mm.cfg index daea99f8d3..a0528c8b52 100644 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/s2mm.cfg +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/s2mm.cfg @@ -1,5 +1,5 @@ #/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +#Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT #* [hls] @@ -16,4 +16,4 @@ syn.interface.m_axi_auto_max_ports=0 syn.interface.m_axi_conservative_mode=1 syn.rtl.deadlock_detection=sim syn.rtl.kernel_profile=1 -package.output.syn=true \ No newline at end of file +package.output.syn=true diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/s2mm_1.cpp b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/s2mm_1.cpp index c52aa59f6f..bf076fc33f 100755 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/s2mm_1.cpp +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/s2mm_1.cpp @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: MIT */ #include diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/sw/Makefile b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/sw/Makefile index f771802b27..899acd52df 100755 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/sw/Makefile +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/sw/Makefile @@ -1,5 +1,5 @@ # /* -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +# Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. # SPDX-License-Identifier: MIT # */ HOST_EXE = ../main.elf diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/sw/input.h b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/sw/input.h index 688a472e63..5e32bbc0f0 100755 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/sw/input.h +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/sw/input.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: MIT */ #pragma once diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/sw/lscript.ld b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/sw/lscript.ld index 970535b7b5..692ca85bb1 100755 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/sw/lscript.ld +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/sw/lscript.ld @@ -1,5 +1,5 @@ /* -/*Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +/*Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. /*SPDX-License-Identifier: MIT /**/ diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/sw/main.cpp b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/sw/main.cpp index 2aa7080522..70520f275f 100755 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/sw/main.cpp +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/sw/main.cpp @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: MIT */ #include diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/sw/platform.h b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/sw/platform.h index 27466d3f17..fd3a385f33 100755 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/sw/platform.h +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/sw/platform.h @@ -1,5 +1,5 @@ /* -Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: MIT */ #ifndef __PLATFORM_H_ diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/system.cfg b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/system.cfg index add0785083..13dfb21d33 100755 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/system.cfg +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/system.cfg @@ -1,5 +1,5 @@ #/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +#Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT #* [connectivity] diff --git a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/utils.mk b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/utils.mk index b9a8f6568b..597d87bf98 100755 --- a/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/utils.mk +++ b/Vitis_Platform_Creation/Feature_Tutorials/04_platform_validation/ref_files/pl_validation/utils.mk @@ -1,5 +1,5 @@ #/* -#Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. +#Copyright (C) 2023-2025, Advanced Micro Devices, Inc. All rights reserved. #SPDX-License-Identifier: MIT #*/ PROFILE := no diff --git a/Vitis_Platform_Creation/README.md b/Vitis_Platform_Creation/README.md index 7809011fcc..3f815b8895 100644 --- a/Vitis_Platform_Creation/README.md +++ b/Vitis_Platform_Creation/README.md @@ -27,7 +27,6 @@ Briefly speaking, a platform is a package that contains the HPFM (`.xsa`) file a - For the **ZYNQMP** device family, refer to [ZCU104 platform tutorial](./Design_Tutorials/02-Edge-AI-ZCU104/) - For the **Versal** device family, refer to [VCK190 platform tutorial](./Design_Tutorials/03_Edge_VCK190/) - For the **DFX** platform, refer to [DFX platform tutorial](./Design_Tutorials/04_Edge_VCK190_DFX/) -- For the **SOM** series, refer to [KV260 platform tutorial](./Design_Tutorials/01-Edge-KV260/) - For the **PetaLinux** customization, refer to [PetaLinux customization](./Feature_Tutorials/02_petalinux_customization/) ## Platform Creation Tutorials @@ -114,22 +113,6 @@ The tutorials under the Vitis Platform Creation category help you learn how to d - - - Custom Kria SOM Platform Creation Example - ZYNQ UltraScale+ MPSoC - KV260 - Flat - Vivado &
Vitis IDE - - Highlights: Kria SOM Platform creation and usage flow -
    -
  • Hardware design: Creating from scratch
    • -
  • Software design: Using Common Image and showing device tree overlay (DTBO) creation flow
    • -
  • Verification: Vector Addition and Kria SOM application loading procedure
    • -
- - ### Feature Tutorials diff --git a/Vitis_Platform_Creation/Vitis_Platform_Creation.rst b/Vitis_Platform_Creation/Vitis_Platform_Creation.rst index c03cac4a9c..b41fb1631c 100644 --- a/Vitis_Platform_Creation/Vitis_Platform_Creation.rst +++ b/Vitis_Platform_Creation/Vitis_Platform_Creation.rst @@ -25,7 +25,6 @@ Platform Creation Example Quick Access * For **ZYNQMP** device family, refer to :doc:`ZCU104 platform tutorial <./docs/Design_Tutorials/02-Edge-AI-ZCU104/README>` * For **Versal** device family, refer to :doc:`VCK190 platform tutorial <./docs/Design_Tutorials/03_Edge_VCK190/README>` * For :term:`DFX`, refer to :doc:`DFX platform tutorial <./docs/Design_Tutorials/04_Edge_VCK190_DFX/README>` -* For :term:`SOM` series, refer to :doc:`KV260 platform tutorial <./docs/Design_Tutorials/01-Edge-KV260/README>` * For **PetaLinux** customization, refer to :doc:`PetaLinux Customization <./docs/Feature_Tutorials/02_petalinux_customization/README>` @@ -138,22 +137,6 @@ Design Tutorials - **Software design**: Using ``createdts`` and Common Image to quick start. - **Verification**: Vector Addition and Vitis-AI. - * - :doc:`Custom Kria SOM Platform Creation Example <./docs/Design_Tutorials/01-Edge-KV260/README>` - - Zynq UltraScale+ MPSoC - - KV260 - - Flat - - - - - Vivado - - Vitis IDE - - - **Highlights**: Kria :term:`SOM` Platform creation and usage flow. - - - **Hardware design**: Creating from scratch. - - **Software design**: Using Common Image and showing device tree binary overlay (:term:`DTBO`) creation flow. - - **Verification**: Vector Addition and Kria :term:`SOM` application loading procedure. - - diff --git a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/Makefile b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/Makefile index 7444f2ee6d..cdf6fbe4a5 100755 --- a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/Makefile +++ b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/Makefile @@ -10,7 +10,7 @@ ECHO = @echo ################################################################################ # Variables needed for AMD tools version checking, PLEASE DO NOT MODIFY # ################################################################################ -REQUIRED_VERSION = 2025.1 +REQUIRED_VERSION = 2025.2 VIVADO_VERSION := $(shell vivado -version 2>/dev/null | grep "vivado ") VITIS_VERSION := $(shell vitis -version 2>/dev/null | grep "Vitis " | sed 's/\*//g') @@ -70,13 +70,13 @@ export LINUX_MACHINE := ${BOARD_NAME}-versal ifeq (${BOARD_NAME}, vck190) export DEVICE_NAME := xcvc1902-vsva2197-2MP-e-S -export PLATFORM_PRE_BUILD := xilinx_vck190_base_202510_1 +export PLATFORM_PRE_BUILD := xilinx_vck190_base_202520_1 else ifeq (${BOARD_NAME}, vek280) export DEVICE_NAME := xcve2802-vsvh1760-2MP-e-S -export PLATFORM_PRE_BUILD := xilinx_vek280_base_202510_1 +export PLATFORM_PRE_BUILD := xilinx_vek280_base_202520_1 else export DEVICE_NAME := xcve2802-vsvh1760-2MP-e-S-es1 -export PLATFORM_PRE_BUILD := xilinx_vek280_base_202510_1 +export PLATFORM_PRE_BUILD := xilinx_vek280_base_202520_1 endif LINUX_SRC_DIR := ./linux/src diff --git a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/README.md b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/README.md index ba5d6781c7..4a64db51d2 100644 --- a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/README.md +++ b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/README.md @@ -14,16 +14,16 @@ # Versal Custom Thin Platform Extensible System -***Version: Vitis 2025.1*** +***Version: Vitis 2025.2*** -This tutorial describes an AMD Versal™ VCK190/VEK280(+es1) System Example Design based on a thin custom platform (minimal clocks and AXI exposed to PL) including HLS/RTL kernels and an AI Engine kernel using a full Makefile build-flow for Vivado™/Petalinux/Yocto/Vitis 2025.1. +This tutorial describes an AMD Versal™ VCK190/VEK280(+es1) System Example Design based on a thin custom platform (minimal clocks and AXI exposed to PL) including HLS/RTL kernels and an AI Engine kernel using a full Makefile build-flow for Vivado™/Petalinux/Yocto/Vitis 2025.2. ## Getting Started ### Build-flow The Versal VCK190/VEK280/VEK280(+es1) System Example Design full Makefile build-flow builds the whole project in the following order: ``` - 1. version_check: Checks if the Vivado, Petalinux and Vitis tools are setup and if the versions are 2025.1 + 1. version_check: Checks if the Vivado, Petalinux and Vitis tools are setup and if the versions are 2025.2 2. vivado_platform: Building the thin platform xsa (only pre-synth) or using the pre-builds 3. vitis_platform: Building the Vitis Platform or using the pre-builds 4. linux: Building linux and sysroot (with Petalinux or Yocto) or using the pre-builds @@ -44,7 +44,7 @@ The following diagram explains the build-flow dependencies. ### Build & Prerequisites In the `[project-root]` you can start the full build with `make all` or `make all_targets` **after** taking following prerequisites into account: - - **Before starting the build, please correctly setup the 2025.1 version of Vivado, Vitis and Petalinux/Yocto** + - **Before starting the build, please correctly setup the 2025.2 version of Vivado, Vitis and Petalinux/Yocto** - If the tools are not setup correctly the build will stop with an ERROR message telling you what is not correctly setup! - **Note**: The Yocto Tool setup is not verified! - **Note**: The Petalinux Tool and Version check is skipped when targetting Yocto! @@ -83,14 +83,14 @@ In the `[project-root]` you can start the full build with `make all` or `make al - `LINUX_PRE_BUILDS`: - `export LINUX_PRE_BUILDS := false` for building linux (default). - `export LINUX_PRE_BUILDS := true` for using the linux pre-builds. - - **Note**: Download the `xilinx-versal-common-v2025.1_xxx.tar.gz` from the Xilinx® Website and... + - **Note**: Download the `xilinx-versal-common-v2025.2_xxx.tar.gz` from the Xilinx® Website and... - Extract it - - `cd xilinx-versal-common-v2025.1` - - `xilinx-versal-common-v2025.1 $ ./sdk.sh` - - Enter target directory for Petalinux tools (default: `/opt/petalinux/2025.1`) + - `cd xilinx-versal-common-v2025.2` + - `xilinx-versal-common-v2025.2 $ ./sdk.sh` + - Enter target directory for Petalinux tools (default: `/opt/petalinux/2025.2`) - Make sure sourcing Vivado `settingsXY.sh` and/or Vitis `settingsXY.sh` first! - - `xilinx-versal-common-v2025.1 $ unset LD_LIBRARY_PATH` - - `xilinx-versal-common-v2025.1 $ source environment-setup-cortexa72-cortexa53-amd-linux` + - `xilinx-versal-common-v2025.2 $ unset LD_LIBRARY_PATH` + - `xilinx-versal-common-v2025.2 $ source environment-setup-cortexa72-cortexa53-amd-linux` - **Note**: The latter 3 items must be executed each time you start in a new terminal or when changing versions! - **Note**: Following `LINUX_X_Y` exports are ignored and do not need setup when `export LINUX_PRE_BUILDS := true`. - **Note**: If `export XPFM_PRE_BUILDS := false` then a device-tree will be generated from the generated xsa. It could be - depending on the generated base platform (xsa) - that changes are needed in the `[project-root]/linux/dtg/src/system-user.dtsi` for a successfull build/boot. @@ -108,8 +108,8 @@ In the `[project-root]` you can start the full build with `make all` or `make al - More information on how to install/setup and build Yocto can be found [here](https://xilinx-wiki.atlassian.net/wiki/spaces/A/pages/18841862/Install+and+Build+with+Xilinx+Yocto). - `LINUX_TMP_DIR`: - Defaults to `export LINUX_TMP_DIR := /tmp/${USER}/${REQUIRED_VERSION}/${SW_BUILD_TOOL}` - - Defaults to `/tmp/${USER}/2025.1/petalinux` when `export SW_BUILD_TOOL := petalinux`. - - Defaults to `/tmp/${USER}/2025.1/yocto` when `export SW_BUILD_TOOL := yocto`. + - Defaults to `/tmp/${USER}/2025.2/petalinux` when `export SW_BUILD_TOOL := petalinux`. + - Defaults to `/tmp/${USER}/2025.2/yocto` when `export SW_BUILD_TOOL := yocto`. - So if you want to place it somewhere else; please replace it with your required location. - Be aware that `LINUX_TMP_DIR` may **NOT** be located on an NFS mounted drive! - If your [project-root] is **NOT** on an NFS mounted drive; you can easily add it in your project with for example `export LINUX_TMP_DIR := $(shell pwd)/linux/tmp` @@ -122,12 +122,12 @@ In the `[project-root]` you can start the full build with `make all` or `make al - `LINUX_LOCAL_DOWNLOADS_DIR`: - **ONLY** used when `export SW_BUILD_TOOL := petalinux` and `export LINUX_BUILD_SOURCES := local`! - Defaults to `export LINUX_LOCAL_DOWNLOADS_DIR := /tmp/plnx-workspace/downloads`. - - Change to the directory where you extracted the [downloads_2025.1.tar.gz](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-design-tools.html). + - Change to the directory where you extracted the [downloads_2025.2.tar.gz](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-design-tools.html). - This can be shared amoungst different users. - `LINUX_LOCAL_SSTATE_DIR`: - **ONLY** used when `export SW_BUILD_TOOL := petalinux` and `export LINUX_BUILD_SOURCES := local`! - - Defaults to `export LINUX_LOCAL_SSTATE_DIR := /tmp/plnx-workspace/sstate_aarch64_2025.1/aarch64`. - - Change to the **WRITABLE** directory where you extracted the [sstate_aarch64_2025.1.tar.gz](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-design-tools.html). + - Defaults to `export LINUX_LOCAL_SSTATE_DIR := /tmp/plnx-workspace/sstate_aarch64_2025.2/aarch64`. + - Change to the **WRITABLE** directory where you extracted the [sstate_aarch64_2025.2.tar.gz](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/embedded-design-tools.html). - This can be shared amoungst different users. - `LINUX_ETH_CONFIG`: - `export LINUX_ETH_CONFIG := DHCP` for Ethernet DHCP Configuration (default). @@ -175,7 +175,7 @@ Each step is sequential (in the order listed - by the `[project-root]/Makefile`)
make version_check - - Checks if the Vivado, Petalinux (Only when `export SW_BUILD_TOOL := petalinux`) and Vitis tools are setup and if the versions are 2025.1. + - Checks if the Vivado, Petalinux (Only when `export SW_BUILD_TOOL := petalinux`) and Vitis tools are setup and if the versions are 2025.2.
@@ -608,7 +608,7 @@ The following are links to the XRT information used by this tutorial: * [XRT AIE API](https://github.com/Xilinx/XRT/blob/master/src/runtime_src/core/include/experimental/xrt_aie.h): Documents the AI Engine XRT API calls -### [2025.1 Vitis Unified Software Development Platform Documentation Landing Page](https://docs.amd.com/v/u/en-US/ug1416-vitis-documentation) +### [2025.2 Vitis Unified Software Development Platform Documentation Landing Page](https://docs.amd.com/v/u/en-US/ug1416-vitis-documentation) The following are links to Vitis related information referenced in this tutorial: * [Embedded Design Development Using Vitis User Guide (UG1701)](https://docs.amd.com/r/en-US/ug1701-vitis-accelerated-embedded/AI-Engine-Kernel-and-Graph-Development) @@ -623,11 +623,11 @@ Click on each item below to see the detailed Revision History:
April 2025 - - Upgrading to 2025.1 + - Upgrading to 2025.2 November 2024 - - Upgrading to 2025.1 + - Upgrading to 2025.2 April 2024 diff --git a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/linux/petalinux/Makefile b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/linux/petalinux/Makefile index 357db04193..22a37fbcc9 100644 --- a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/linux/petalinux/Makefile +++ b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/linux/petalinux/Makefile @@ -10,8 +10,8 @@ LINUX_MACHINE ?= ${BOARD_NAME}-versal LINUX_ETH_CONFIG ?= DHCP LINUX_BUILD_SOURCES ?= network LINUX_LOCAL_DOWNLOADS_DIR ?= /tmp/plnx-workspace/downloads -LINUX_LOCAL_SSTATE_DIR ?= /tmp/plnx-workspace/sstate_aarch64_2025.1/aarch64 -LINUX_TMP_DIR ?= /tmp/${USER}/2025.1/${BOARD_NAME}/petalinux +LINUX_LOCAL_SSTATE_DIR ?= /tmp/plnx-workspace/sstate_aarch64_2025.2/aarch64 +LINUX_TMP_DIR ?= /tmp/${USER}/2025.2/${BOARD_NAME}/petalinux CURR_DIR := $(shell pwd) PROJ_DIR := ${CURR_DIR}/../${LINUX_MACHINE} diff --git a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/linux/yocto/Makefile b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/linux/yocto/Makefile index cf0eb2aa9c..b1e9e03421 100755 --- a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/linux/yocto/Makefile +++ b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/linux/yocto/Makefile @@ -6,7 +6,7 @@ ECHO := @echo LINUX_YOCTO_ROOT ?= ${HOME}/bin -LINUX_TMP_DIR ?= /tmp/${USER}/2025.1/yocto +LINUX_TMP_DIR ?= /tmp/${USER}/2025.2/yocto LINUX_ETH_CONFIG ?= DHCP LINUX_MACHINE ?= vck190-versal diff --git a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vck190/dr.bd.tcl b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vck190/dr.bd.tcl index 7d89b00cfb..6dcfef9f04 100644 --- a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vck190/dr.bd.tcl +++ b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vck190/dr.bd.tcl @@ -20,7 +20,7 @@ set script_folder [_tcl::get_script_folder] ################################################################ # Check if script is running in correct Vivado version. ################################################################ -set scripts_vivado_version 2025.1 +set scripts_vivado_version 2025.2 set current_vivado_version [version -short] if { [string first $scripts_vivado_version $current_vivado_version] == -1 } { diff --git a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280/dr.bd.tcl b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280/dr.bd.tcl index 0f04060551..464c00f5b1 100644 --- a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280/dr.bd.tcl +++ b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280/dr.bd.tcl @@ -20,7 +20,7 @@ set script_folder [_tcl::get_script_folder] ################################################################ # Check if script is running in correct Vivado version. ################################################################ -set scripts_vivado_version 2025.1 +set scripts_vivado_version 2025.2 set current_vivado_version [version -short] if { [string first $scripts_vivado_version $current_vivado_version] == -1 } { diff --git a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/ddr4_dmc_3200_triplet_1.xdc b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/ddr4_dmc_3200_triplet_1.xdc deleted file mode 100644 index 37b299df63..0000000000 --- a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/ddr4_dmc_3200_triplet_1.xdc +++ /dev/null @@ -1,156 +0,0 @@ -# -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: X11 -# - - set_property PACKAGE_PIN AF47 [get_ports "CH0_DDR4_0_0_dqs_t[4]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L0P_XCC_N0P0_M0P0_700 - set_property PACKAGE_PIN AF46 [get_ports "CH0_DDR4_0_0_dqs_c[4]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L0N_XCC_N0P1_M0P1_700 - set_property PACKAGE_PIN AD47 [get_ports "CH0_DDR4_0_0_dq[39]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L5P_N1P4_M0P10_700 - set_property PACKAGE_PIN AE47 [get_ports "CH0_DDR4_0_0_dq[38]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L5N_N1P5_M0P11_700 - set_property PACKAGE_PIN AH43 [get_ports "CH0_DDR4_0_0_dqs_t[5]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L6P_GC_XCC_N2P0_M0P12_700 - set_property PACKAGE_PIN AG44 [get_ports "CH0_DDR4_0_0_dqs_c[5]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L6N_GC_XCC_N2P1_M0P13_700 - set_property PACKAGE_PIN AD44 [get_ports "CH0_DDR4_0_0_dq[43]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L7P_N2P2_M0P14_700 - set_property PACKAGE_PIN AE44 [get_ports "CH0_DDR4_0_0_dq[42]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L7N_N2P3_M0P15_700 - set_property PACKAGE_PIN AJ44 [get_ports "CH0_DDR4_0_0_dq[41]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L8P_N2P4_M0P16_700 - set_property PACKAGE_PIN AJ45 [get_ports "CH0_DDR4_0_0_dq[40]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L8N_N2P5_M0P17_700 - set_property PACKAGE_PIN AH45 [get_ports "CH0_DDR4_0_0_dm_n[5]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L9P_GC_XCC_N3P0_M0P18_700 - set_property PACKAGE_PIN AD45 [get_ports "CH0_DDR4_0_0_dq[35]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L1P_N0P2_M0P2_700 - set_property PACKAGE_PIN AK44 [get_ports "CH0_DDR4_0_0_dq[45]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L10P_N3P2_M0P20_700 - set_property PACKAGE_PIN AK45 [get_ports "CH0_DDR4_0_0_dq[44]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L10N_N3P3_M0P21_700 - set_property PACKAGE_PIN AF44 [get_ports "CH0_DDR4_0_0_dq[47]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L11P_N3P4_M0P22_700 - set_property PACKAGE_PIN AE45 [get_ports "CH0_DDR4_0_0_dq[46]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L11N_N3P5_M0P23_700 - set_property PACKAGE_PIN AF39 [get_ports "CH0_DDR4_0_0_dqs_t[6]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L12P_GC_XCC_N4P0_M0P24_700 - set_property PACKAGE_PIN AF40 [get_ports "CH0_DDR4_0_0_dqs_c[6]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L12N_GC_XCC_N4P1_M0P25_700 - set_property PACKAGE_PIN AC39 [get_ports "CH0_DDR4_0_0_dq[51]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L13P_N4P2_M0P26_700 - set_property PACKAGE_PIN AD40 [get_ports "CH0_DDR4_0_0_dq[50]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L13N_N4P3_M0P27_700 - set_property PACKAGE_PIN AH40 [get_ports "CH0_DDR4_0_0_dq[49]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L14P_N4P4_M0P28_700 - set_property PACKAGE_PIN AH41 [get_ports "CH0_DDR4_0_0_dq[48]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L14N_N4P5_M0P29_700 - set_property PACKAGE_PIN AE46 [get_ports "CH0_DDR4_0_0_dq[34]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L1N_N0P3_M0P3_700 - set_property PACKAGE_PIN AG41 [get_ports "CH0_DDR4_0_0_dm_n[6]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L15P_XCC_N5P0_M0P30_700 - set_property PACKAGE_PIN AH39 [get_ports "CH0_DDR4_0_0_dq[52]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L16P_N5P2_M0P32_700 - set_property PACKAGE_PIN AJ40 [get_ports "CH0_DDR4_0_0_dq[53]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L16N_N5P3_M0P33_700 - set_property PACKAGE_PIN AE40 [get_ports "CH0_DDR4_0_0_dq[55]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L17P_N5P4_M0P34_700 - set_property PACKAGE_PIN AD41 [get_ports "CH0_DDR4_0_0_dq[54]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L17N_N5P5_M0P35_700 - set_property PACKAGE_PIN AE38 [get_ports "CH0_DDR4_0_0_dqs_t[7]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L18P_XCC_N6P0_M0P36_700 - set_property PACKAGE_PIN AF37 [get_ports "CH0_DDR4_0_0_dqs_c[7]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L18N_XCC_N6P1_M0P37_700 - set_property PACKAGE_PIN AC37 [get_ports "CH0_DDR4_0_0_dq[59]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L19P_N6P2_M0P38_700 - set_property PACKAGE_PIN AD37 [get_ports "CH0_DDR4_0_0_dq[58]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L19N_N6P3_M0P39_700 - set_property PACKAGE_PIN AH47 [get_ports "CH0_DDR4_0_0_dq[33]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L2P_N0P4_M0P4_700 - set_property PACKAGE_PIN AG37 [get_ports "CH0_DDR4_0_0_dq[56]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L20P_N6P4_M0P40_700 - set_property PACKAGE_PIN AH38 [get_ports "CH0_DDR4_0_0_dq[57]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L20N_N6P5_M0P41_700 - set_property PACKAGE_PIN AG39 [get_ports "CH0_DDR4_0_0_dm_n[7]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L21P_XCC_N7P0_M0P42_700 - set_property PACKAGE_PIN AH37 [get_ports "CH0_DDR4_0_0_dq[60]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L22P_N7P2_M0P44_700 - set_property PACKAGE_PIN AJ38 [get_ports "CH0_DDR4_0_0_dq[61]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L22N_N7P3_M0P45_700 - set_property PACKAGE_PIN AD38 [get_ports "CH0_DDR4_0_0_dq[63]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L23P_N7P4_M0P46_700 - set_property PACKAGE_PIN AD39 [get_ports "CH0_DDR4_0_0_dq[62]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L23N_N7P5_M0P47_700 - #set_property PACKAGE_PIN AE42 [get_ports "sys_clk0_0_clk_p[0]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L24P_GC_XCC_N8P0_M0P48_700 - #set_property PACKAGE_PIN AF43 [get_ports "sys_clk0_0_clk_n[0]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L24N_GC_XCC_N8P1_M0P49_700 - set_property PACKAGE_PIN AJ47 [get_ports "CH0_DDR4_0_0_dq[32]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L2N_N0P5_M0P5_700 - set_property PACKAGE_PIN AD42 [get_ports "CH0_DDR4_0_0_reset_n[0]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L25P_N8P2_M0P50_700 - #set_property PACKAGE_PIN AD43 [get_ports "CH0_DDR4_0_0_alert_n[0]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L25N_N8P3_M0P51_700 - set_property PACKAGE_PIN AH46 [get_ports "CH0_DDR4_0_0_dm_n[4]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L3P_XCC_N1P0_M0P6_700 - set_property PACKAGE_PIN AK46 [get_ports "CH0_DDR4_0_0_dq[37]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L4P_N1P2_M0P8_700 - set_property PACKAGE_PIN AK47 [get_ports "CH0_DDR4_0_0_dq[36]"] ;# Bank 700 VCCO - VCC1V2_DDR4 - IO_L4N_N1P3_M0P9_700 - #set_property PACKAGE_PIN AP47 [get_ports "CH0_DDR4_0_0_odt[1]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L0N_XCC_N0P1_M0P55_701 - #set_property PACKAGE_PIN AM46 [get_ports "CH0_DDR4_0_0_adr[17]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L5P_N1P4_M0P64_701 - set_property PACKAGE_PIN AN47 [get_ports "CH0_DDR4_0_0_adr[8]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L5N_N1P5_M0P65_701 - set_property PACKAGE_PIN AR46 [get_ports "CH0_DDR4_0_0_ck_t[0]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L6P_GC_XCC_N2P0_M0P66_701 - set_property PACKAGE_PIN AT46 [get_ports "CH0_DDR4_0_0_ck_c[0]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L6N_GC_XCC_N2P1_M0P67_701 - set_property PACKAGE_PIN AP43 [get_ports "CH0_DDR4_0_0_adr[7]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L7P_N2P2_M0P68_701 - set_property PACKAGE_PIN AT44 [get_ports "CH0_DDR4_0_0_adr[9]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L8P_N2P4_M0P70_701 - set_property PACKAGE_PIN AU44 [get_ports "CH0_DDR4_0_0_adr[1]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L8N_N2P5_M0P71_701 - set_property PACKAGE_PIN AT47 [get_ports "CH0_DDR4_0_0_bg[1]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L9P_GC_XCC_N3P0_M0P72_701 - set_property PACKAGE_PIN AR47 [get_ports "CH0_DDR4_0_0_act_n[0]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L9N_GC_XCC_N3P1_M0P73_701 - set_property PACKAGE_PIN AL46 [get_ports "CH0_DDR4_0_0_adr[0]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L1P_N0P2_M0P56_701 - set_property PACKAGE_PIN AU45 [get_ports "CH0_DDR4_0_0_adr[13]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L10P_N3P2_M0P74_701 - #set_property PACKAGE_PIN AU46 [get_ports "CH0_DDR4_0_0_cke[1]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L10N_N3P3_M0P75_701 - set_property PACKAGE_PIN AR44 [get_ports "CH0_DDR4_0_0_adr[2]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L11P_N3P4_M0P76_701 - set_property PACKAGE_PIN AR45 [get_ports "CH0_DDR4_0_0_cke[0]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L11N_N3P5_M0P77_701 - set_property PACKAGE_PIN AK40 [get_ports "CH0_DDR4_0_0_adr[15]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L12P_GC_XCC_N4P0_M0P78_701 - set_property PACKAGE_PIN AK38 [get_ports "CH0_DDR4_0_0_adr[11]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L13N_N4P3_M0P81_701 - set_property PACKAGE_PIN AL41 [get_ports "CH0_DDR4_0_0_adr[4]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L14P_N4P4_M0P82_701 - set_property PACKAGE_PIN AM41 [get_ports "CH0_DDR4_0_0_adr[3]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L14N_N4P5_M0P83_701 - set_property PACKAGE_PIN AL47 [get_ports "CH0_DDR4_0_0_ba[1]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L1N_N0P3_M0P57_701 - set_property PACKAGE_PIN AK39 [get_ports "CH0_DDR4_0_0_adr[14]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L15N_XCC_N5P1_M0P85_701 - set_property PACKAGE_PIN AM39 [get_ports "CH0_DDR4_0_0_odt[0]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L16P_N5P2_M0P86_701 - #set_property PACKAGE_PIN AM40 [get_ports "CH0_DDR4_0_0_cs_n[1]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L16N_N5P3_M0P87_701 - set_property PACKAGE_PIN AL37 [get_ports "CH0_DDR4_0_0_adr[5]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L17P_N5P4_M0P88_701 - set_property PACKAGE_PIN AM38 [get_ports "CH0_DDR4_0_0_adr[6]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L17N_N5P5_M0P89_701 - set_property PACKAGE_PIN AP40 [get_ports "CH0_DDR4_0_0_dqs_t[3]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L18P_XCC_N6P0_M0P90_701 - set_property PACKAGE_PIN AP41 [get_ports "CH0_DDR4_0_0_dqs_c[3]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L18N_XCC_N6P1_M0P91_701 - set_property PACKAGE_PIN AM37 [get_ports "CH0_DDR4_0_0_dq[24]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L19P_N6P2_M0P92_701 - set_property PACKAGE_PIN AN38 [get_ports "CH0_DDR4_0_0_dq[25]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L19N_N6P3_M0P93_701 - #set_property PACKAGE_PIN AM44 [get_ports "CH0_DDR4_0_0_cs_n[3]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L2P_N0P4_M0P58_701 - set_property PACKAGE_PIN AR39 [get_ports "CH0_DDR4_0_0_dq[26]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L20P_N6P4_M0P94_701 - set_property PACKAGE_PIN AT39 [get_ports "CH0_DDR4_0_0_dq[27]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L20N_N6P5_M0P95_701 - set_property PACKAGE_PIN AR42 [get_ports "CH0_DDR4_0_0_dm_n[3]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L21P_XCC_N7P0_M0P96_701 - set_property PACKAGE_PIN AT40 [get_ports "CH0_DDR4_0_0_dq[28]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L22P_N7P2_M0P98_701 - set_property PACKAGE_PIN AT41 [get_ports "CH0_DDR4_0_0_dq[29]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L22N_N7P3_M0P99_701 - set_property PACKAGE_PIN AP39 [get_ports "CH0_DDR4_0_0_dq[30]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L23P_N7P4_M0P100_701 - set_property PACKAGE_PIN AN40 [get_ports "CH0_DDR4_0_0_dq[31]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L23N_N7P5_M0P101_701 - #set_property PACKAGE_PIN AM43 [get_ports "CH0_DDR4_0_0_par[0]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L24P_GC_XCC_N8P0_M0P102_701 - set_property PACKAGE_PIN AN43 [get_ports "CH0_DDR4_0_0_ba[0]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L24N_GC_XCC_N8P1_M0P103_701 - #set_property PACKAGE_PIN AM45 [get_ports "CH0_DDR4_0_0_cs_n[2]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L2N_N0P5_M0P59_701 - set_property PACKAGE_PIN AL42 [get_ports "CH0_DDR4_0_0_adr[10]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L25N_N8P3_M0P105_701 - set_property PACKAGE_PIN AN42 [get_ports "CH0_DDR4_0_0_adr[12]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L26P_N8P4_M0P106_701 - set_property PACKAGE_PIN AP42 [get_ports "CH0_DDR4_0_0_bg[0]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L26N_N8P5_M0P107_701 - #set_property PACKAGE_PIN AP45 [get_ports "CH0_DDR4_0_0_ck_t[1]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L3P_XCC_N1P0_M0P60_701 - #set_property PACKAGE_PIN AN45 [get_ports "CH0_DDR4_0_0_ck_c[1]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L3N_XCC_N1P1_M0P61_701 - set_property PACKAGE_PIN AL43 [get_ports "CH0_DDR4_0_0_cs_n[0]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L4P_N1P2_M0P62_701 - set_property PACKAGE_PIN AL44 [get_ports "CH0_DDR4_0_0_adr[16]"] ;# Bank 701 VCCO - VCC1V2_DDR4 - IO_L4N_N1P3_M0P63_701 - #set_property PACKAGE_PIN AY47 [get_ports "CH0_DDR4_0_0_dqs_t[8]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L0P_XCC_N0P0_M0P108_702 - #set_property PACKAGE_PIN BA46 [get_ports "CH0_DDR4_0_0_dqs_c[8]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L0N_XCC_N0P1_M0P109_702 - #set_property PACKAGE_PIN AY46 [get_ports "CH0_DDR4_0_0_dq[71]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L5P_N1P4_M0P118_702 - #set_property PACKAGE_PIN AW47 [get_ports "CH0_DDR4_0_0_dq[70]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L5N_N1P5_M0P119_702 - set_property PACKAGE_PIN AY45 [get_ports "CH0_DDR4_0_0_dqs_t[2]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L6P_GC_XCC_N2P0_M0P120_702 - set_property PACKAGE_PIN BA44 [get_ports "CH0_DDR4_0_0_dqs_c[2]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L6N_GC_XCC_N2P1_M0P121_702 - set_property PACKAGE_PIN AW44 [get_ports "CH0_DDR4_0_0_dq[19]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L7P_N2P2_M0P122_702 - set_property PACKAGE_PIN AV45 [get_ports "CH0_DDR4_0_0_dq[18]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L7N_N2P3_M0P123_702 - set_property PACKAGE_PIN BC45 [get_ports "CH0_DDR4_0_0_dq[17]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L8P_N2P4_M0P124_702 - set_property PACKAGE_PIN BD45 [get_ports "CH0_DDR4_0_0_dq[16]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L8N_N2P5_M0P125_702 - set_property PACKAGE_PIN BB44 [get_ports "CH0_DDR4_0_0_dm_n[2]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L9P_GC_XCC_N3P0_M0P126_702 - #set_property PACKAGE_PIN AV46 [get_ports "CH0_DDR4_0_0_dq[67]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L1P_N0P2_M0P110_702 - set_property PACKAGE_PIN BD44 [get_ports "CH0_DDR4_0_0_dq[20]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L10P_N3P2_M0P128_702 - set_property PACKAGE_PIN BE45 [get_ports "CH0_DDR4_0_0_dq[21]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L10N_N3P3_M0P129_702 - set_property PACKAGE_PIN AY44 [get_ports "CH0_DDR4_0_0_dq[23]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L11P_N3P4_M0P130_702 - set_property PACKAGE_PIN AW45 [get_ports "CH0_DDR4_0_0_dq[22]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L11N_N3P5_M0P131_702 - set_property PACKAGE_PIN AY42 [get_ports "CH0_DDR4_0_0_dqs_t[1]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L12P_GC_XCC_N4P0_M0P132_702 - set_property PACKAGE_PIN BA43 [get_ports "CH0_DDR4_0_0_dqs_c[1]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L12N_GC_XCC_N4P1_M0P133_702 - set_property PACKAGE_PIN AV42 [get_ports "CH0_DDR4_0_0_dq[10]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L13P_N4P2_M0P134_702 - set_property PACKAGE_PIN AV43 [get_ports "CH0_DDR4_0_0_dq[11]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L13N_N4P3_M0P135_702 - set_property PACKAGE_PIN BC42 [get_ports "CH0_DDR4_0_0_dq[8]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L14P_N4P4_M0P136_702 - set_property PACKAGE_PIN BC43 [get_ports "CH0_DDR4_0_0_dq[9]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L14N_N4P5_M0P137_702 - #set_property PACKAGE_PIN AV47 [get_ports "CH0_DDR4_0_0_dq[66]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L1N_N0P3_M0P111_702 - set_property PACKAGE_PIN BB43 [get_ports "CH0_DDR4_0_0_dm_n[1]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L15P_XCC_N5P0_M0P138_702 - set_property PACKAGE_PIN BD42 [get_ports "CH0_DDR4_0_0_dq[13]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L16P_N5P2_M0P140_702 - set_property PACKAGE_PIN BE42 [get_ports "CH0_DDR4_0_0_dq[12]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L16N_N5P3_M0P141_702 - set_property PACKAGE_PIN AW42 [get_ports "CH0_DDR4_0_0_dq[15]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L17P_N5P4_M0P142_702 - set_property PACKAGE_PIN AW43 [get_ports "CH0_DDR4_0_0_dq[14]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L17N_N5P5_M0P143_702 - set_property PACKAGE_PIN AY41 [get_ports "CH0_DDR4_0_0_dqs_t[0]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L18P_XCC_N6P0_M0P144_702 - set_property PACKAGE_PIN BA41 [get_ports "CH0_DDR4_0_0_dqs_c[0]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L18N_XCC_N6P1_M0P145_702 - set_property PACKAGE_PIN AU41 [get_ports "CH0_DDR4_0_0_dq[3]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L19P_N6P2_M0P146_702 - set_property PACKAGE_PIN AV41 [get_ports "CH0_DDR4_0_0_dq[2]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L19N_N6P3_M0P147_702 - #set_property PACKAGE_PIN BC46 [get_ports "CH0_DDR4_0_0_dq[64]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L2P_N0P4_M0P112_702 - set_property PACKAGE_PIN BE41 [get_ports "CH0_DDR4_0_0_dq[0]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L20P_N6P4_M0P148_702 - set_property PACKAGE_PIN BF41 [get_ports "CH0_DDR4_0_0_dq[1]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L20N_N6P5_M0P149_702 - set_property PACKAGE_PIN BC41 [get_ports "CH0_DDR4_0_0_dm_n[0]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L21P_XCC_N7P0_M0P150_702 - set_property PACKAGE_PIN BG41 [get_ports "CH0_DDR4_0_0_dq[4]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L22P_N7P2_M0P152_702 - set_property PACKAGE_PIN BF42 [get_ports "CH0_DDR4_0_0_dq[5]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L22N_N7P3_M0P153_702 - set_property PACKAGE_PIN AW40 [get_ports "CH0_DDR4_0_0_dq[7]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L23P_N7P4_M0P154_702 - set_property PACKAGE_PIN AW41 [get_ports "CH0_DDR4_0_0_dq[6]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L23N_N7P5_M0P155_702 - #set_property PACKAGE_PIN BC47 [get_ports "CH0_DDR4_0_0_dq[65]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L2N_N0P5_M0P113_702 - #set_property PACKAGE_PIN BB46 [get_ports "CH0_DDR4_0_0_dm_n[8]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L3P_XCC_N1P0_M0P114_702 - #set_property PACKAGE_PIN BE46 [get_ports "CH0_DDR4_0_0_dq[68]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L4P_N1P2_M0P116_702 - #set_property PACKAGE_PIN BD47 [get_ports "CH0_DDR4_0_0_dq[69]"] ;# Bank 702 VCCO - VCC1V2_DDR4 - IO_L4N_N1P3_M0P117_702 - set_property DRIVE 8 [get_ports {CH0_DDR4_0_0_reset_n[0]}] - -##create_clock -name sys_clk0_0_clk_p -period 10 [get_ports {sys_clk0_0_clk_p}] -#set_clock_uncertainty -hold 0.200 [get_clocks clkout1_primitive] - -set_property PACKAGE_PIN AE42 [get_ports sys_clk0_0_clk_p] -set_property PACKAGE_PIN AF43 [get_ports sys_clk0_0_clk_n] - -#set_property IOSTANDARD DIFF_LVSTL_11 [get_ports SYS_CLK1_IN_0_clk_p] -#set_property IOSTANDARD DIFF_LVSTL_11 [get_ports SYS_CLK1_IN_0_clk_n] - - diff --git a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/dr.bd.tcl b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/dr.bd.tcl deleted file mode 100644 index d71b617f7d..0000000000 --- a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/dr.bd.tcl +++ /dev/null @@ -1,631 +0,0 @@ - -################################################################ -# This is a generated script based on design: vek280_es1_thin -# -# Though there are limitations about the generated script, -# the main purpose of this utility is to make learning -# IP Integrator Tcl commands easier. -################################################################ - -namespace eval _tcl { -proc get_script_folder {} { - set script_path [file normalize [info script]] - set script_folder [file dirname $script_path] - return $script_folder -} -} -variable script_folder -set script_folder [_tcl::get_script_folder] - -################################################################ -# Check if script is running in correct Vivado version. -################################################################ -set scripts_vivado_version 2024.2 -set current_vivado_version [version -short] - -if { [string first $scripts_vivado_version $current_vivado_version] == -1 } { - puts "" - if { [string compare $scripts_vivado_version $current_vivado_version] > 0 } { - catch {common::send_gid_msg -ssname BD::TCL -id 2042 -severity "ERROR" " This script was generated using Vivado <$scripts_vivado_version> and is being run in <$current_vivado_version> of Vivado. Sourcing the script failed since it was created with a future version of Vivado."} - - } else { - catch {common::send_gid_msg -ssname BD::TCL -id 2041 -severity "ERROR" "This script was generated using Vivado <$scripts_vivado_version> and is being run in <$current_vivado_version> of Vivado. Please run the script in Vivado <$scripts_vivado_version> then open the design in Vivado <$current_vivado_version>. Upgrade the design by running \"Tools => Report => Report IP Status...\", then run write_bd_tcl to create an updated script."} - - } - - return 1 -} - -################################################################ -# START -################################################################ - -# To test this script, run the following commands from Vivado Tcl console: -# source vek280_es1_thin_script.tcl - -# If there is no project opened, this script will create a -# project, but make sure you do not have an existing project -# <./myproj/project_1.xpr> in the current working folder. - -set list_projs [get_projects -quiet] -if { $list_projs eq "" } { - create_project project_1 myproj -part xcve2802-vsvh1760-2LP-e-S-es1 - set_property BOARD_PART xilinx.com:vek280_es:part0:1.1 [current_project] -} - - -# CHANGE DESIGN NAME HERE -variable design_name -set design_name vek280_es1_thin - -# If you do not already have an existing IP Integrator design open, -# you can create a design using the following command: -# create_bd_design $design_name - -# Creating design if needed -set errMsg "" -set nRet 0 - -set cur_design [current_bd_design -quiet] -set list_cells [get_bd_cells -quiet] - -if { ${design_name} eq "" } { - # USE CASES: - # 1) Design_name not set - - set errMsg "Please set the variable to a non-empty value." - set nRet 1 - -} elseif { ${cur_design} ne "" && ${list_cells} eq "" } { - # USE CASES: - # 2): Current design opened AND is empty AND names same. - # 3): Current design opened AND is empty AND names diff; design_name NOT in project. - # 4): Current design opened AND is empty AND names diff; design_name exists in project. - - if { $cur_design ne $design_name } { - common::send_gid_msg -ssname BD::TCL -id 2001 -severity "INFO" "Changing value of from <$design_name> to <$cur_design> since current design is empty." - set design_name [get_property NAME $cur_design] - } - common::send_gid_msg -ssname BD::TCL -id 2002 -severity "INFO" "Constructing design in IPI design <$cur_design>..." - -} elseif { ${cur_design} ne "" && $list_cells ne "" && $cur_design eq $design_name } { - # USE CASES: - # 5) Current design opened AND has components AND same names. - - set errMsg "Design <$design_name> already exists in your project, please set the variable to another value." - set nRet 1 -} elseif { [get_files -quiet ${design_name}.bd] ne "" } { - # USE CASES: - # 6) Current opened design, has components, but diff names, design_name exists in project. - # 7) No opened design, design_name exists in project. - - set errMsg "Design <$design_name> already exists in your project, please set the variable to another value." - set nRet 2 - -} else { - # USE CASES: - # 8) No opened design, design_name not in project. - # 9) Current opened design, has components, but diff names, design_name not in project. - - common::send_gid_msg -ssname BD::TCL -id 2003 -severity "INFO" "Currently there is no design <$design_name> in project, so creating one..." - - create_bd_design $design_name - - common::send_gid_msg -ssname BD::TCL -id 2004 -severity "INFO" "Making design <$design_name> as current_bd_design." - current_bd_design $design_name - -} - - # Add USER_COMMENTS on $design_name - set_property USER_COMMENTS.comment0 " ======================= >>>>>>>>> An Example Versal Extensible Embedded Platform <<<<<<<<< ======================= - Note: - --> Board preset applied to CIPS and memory controller settings - --> AI Engine control path is connected to CIPS - --> V++ will connect AI Engine data path automatically - --> Execute TCL command : launch_simulation -scripts_only ,to establish the sim_1 source set hierarchy after successful design creation. - --> For Next steps, Refer to README.md https://github.com/Xilinx/XilinxCEDStore/tree/2024.1/ced/Xilinx/IPI/Versal_Extensible_Embedded_Platform/README.md" [get_bd_designs $design_name] - -common::send_gid_msg -ssname BD::TCL -id 2005 -severity "INFO" "Currently the variable is equal to \"$design_name\"." - -if { $nRet != 0 } { - catch {common::send_gid_msg -ssname BD::TCL -id 2006 -severity "ERROR" $errMsg} - return $nRet -} - -set bCheckIPsPassed 1 -################################################################## -# CHECK IPs -################################################################## -set bCheckIPs 1 -if { $bCheckIPs == 1 } { - set list_check_ips "\ -xilinx.com:ip:versal_cips:3.4\ -xilinx.com:ip:axi_intc:4.1\ -xilinx.com:ip:clk_wizard:1.0\ -xilinx.com:ip:axi_noc:1.1\ -xilinx.com:ip:proc_sys_reset:5.0\ -xilinx.com:ip:smartconnect:1.0\ -xilinx.com:ip:ai_engine:2.0\ -" - - set list_ips_missing "" - common::send_gid_msg -ssname BD::TCL -id 2011 -severity "INFO" "Checking if the following IPs exist in the project's IP catalog: $list_check_ips ." - - foreach ip_vlnv $list_check_ips { - set ip_obj [get_ipdefs -all $ip_vlnv] - if { $ip_obj eq "" } { - lappend list_ips_missing $ip_vlnv - } - } - - if { $list_ips_missing ne "" } { - catch {common::send_gid_msg -ssname BD::TCL -id 2012 -severity "ERROR" "The following IPs are not found in the IP Catalog:\n $list_ips_missing\n\nResolution: Please add the repository containing the IP(s) to the project." } - set bCheckIPsPassed 0 - } - -} - -if { $bCheckIPsPassed != 1 } { - common::send_gid_msg -ssname BD::TCL -id 2023 -severity "WARNING" "Will not continue with creation of design due to the error(s) above." - return 3 -} - -################################################################## -# DESIGN PROCs -################################################################## - - - -# Procedure to create entire design; Provide argument to make -# procedure reusable. If parentCell is "", will use root. -proc create_root_design { parentCell } { - - variable script_folder - variable design_name - - if { $parentCell eq "" } { - set parentCell [get_bd_cells /] - } - - # Get object for parentCell - set parentObj [get_bd_cells $parentCell] - if { $parentObj == "" } { - catch {common::send_gid_msg -ssname BD::TCL -id 2090 -severity "ERROR" "Unable to find parent cell <$parentCell>!"} - return - } - - # Make sure parentObj is hier blk - set parentType [get_property TYPE $parentObj] - if { $parentType ne "hier" } { - catch {common::send_gid_msg -ssname BD::TCL -id 2091 -severity "ERROR" "Parent <$parentObj> has TYPE = <$parentType>. Expected to be ."} - return - } - - # Save current instance; Restore later - set oldCurInst [current_bd_instance .] - - # Set parent object as current - current_bd_instance $parentObj - - - # Create interface ports - set ch0_lpddr4_trip1 [ create_bd_intf_port -mode Master -vlnv xilinx.com:interface:lpddr4_rtl:1.0 ch0_lpddr4_trip1 ] - - set ch1_lpddr4_trip1 [ create_bd_intf_port -mode Master -vlnv xilinx.com:interface:lpddr4_rtl:1.0 ch1_lpddr4_trip1 ] - - set lpddr4_clk1 [ create_bd_intf_port -mode Slave -vlnv xilinx.com:interface:diff_clock_rtl:1.0 lpddr4_clk1 ] - set_property -dict [ list \ - CONFIG.FREQ_HZ {200000000} \ - ] $lpddr4_clk1 - - set ch0_lpddr4_trip2 [ create_bd_intf_port -mode Master -vlnv xilinx.com:interface:lpddr4_rtl:1.0 ch0_lpddr4_trip2 ] - - set ch1_lpddr4_trip2 [ create_bd_intf_port -mode Master -vlnv xilinx.com:interface:lpddr4_rtl:1.0 ch1_lpddr4_trip2 ] - - set lpddr4_clk2 [ create_bd_intf_port -mode Slave -vlnv xilinx.com:interface:diff_clock_rtl:1.0 lpddr4_clk2 ] - set_property -dict [ list \ - CONFIG.FREQ_HZ {200000000} \ - ] $lpddr4_clk2 - - set ch0_lpddr4_trip3 [ create_bd_intf_port -mode Master -vlnv xilinx.com:interface:lpddr4_rtl:1.0 ch0_lpddr4_trip3 ] - - set ch1_lpddr4_trip3 [ create_bd_intf_port -mode Master -vlnv xilinx.com:interface:lpddr4_rtl:1.0 ch1_lpddr4_trip3 ] - - set lpddr4_clk3 [ create_bd_intf_port -mode Slave -vlnv xilinx.com:interface:diff_clock_rtl:1.0 lpddr4_clk3 ] - set_property -dict [ list \ - CONFIG.FREQ_HZ {200000000} \ - ] $lpddr4_clk3 - - - # Create ports - - # Create instance: CIPS_0, and set properties - set CIPS_0 [ create_bd_cell -type ip -vlnv xilinx.com:ip:versal_cips:3.4 CIPS_0 ] - set_property -dict [list \ - CONFIG.CLOCK_MODE {Custom} \ - CONFIG.DDR_MEMORY_MODE {Custom} \ - CONFIG.PS_BOARD_INTERFACE {ps_pmc_fixed_io} \ - CONFIG.PS_PL_CONNECTIVITY_MODE {Custom} \ - CONFIG.PS_PMC_CONFIG { \ - CLOCK_MODE {Custom} \ - DDR_MEMORY_MODE {Custom} \ - DESIGN_MODE {1} \ - DEVICE_INTEGRITY_MODE {Sysmon temperature voltage and external IO monitoring} \ - PMC_CRP_PL0_REF_CTRL_FREQMHZ {99.999992} \ - PMC_GPIO0_MIO_PERIPHERAL {{ENABLE 1} {IO {PMC_MIO 0 .. 25}}} \ - PMC_GPIO1_MIO_PERIPHERAL {{ENABLE 1} {IO {PMC_MIO 26 .. 51}}} \ - PMC_MIO12 {{AUX_IO 0} {DIRECTION out} {DRIVE_STRENGTH 8mA} {OUTPUT_DATA default} {PULL pullup} {SCHMITT 0} {SLEW slow} {USAGE GPIO}} \ - PMC_MIO37 {{AUX_IO 0} {DIRECTION out} {DRIVE_STRENGTH 8mA} {OUTPUT_DATA high} {PULL pullup} {SCHMITT 0} {SLEW slow} {USAGE GPIO}} \ - PMC_OSPI_PERIPHERAL {{ENABLE 1} {IO {PMC_MIO 0 .. 11}} {MODE Single}} \ - PMC_REF_CLK_FREQMHZ {33.3333} \ - PMC_SD1 {{CD_ENABLE 1} {CD_IO {PMC_MIO 28}} {POW_ENABLE 1} {POW_IO {PMC_MIO 51}} {RESET_ENABLE 0} {RESET_IO {PMC_MIO 12}} {WP_ENABLE 0} {WP_IO {PMC_MIO 1}}} \ - PMC_SD1_PERIPHERAL {{CLK_100_SDR_OTAP_DLY 0x3} {CLK_200_SDR_OTAP_DLY 0x2} {CLK_50_DDR_ITAP_DLY 0x36} {CLK_50_DDR_OTAP_DLY 0x3} {CLK_50_SDR_ITAP_DLY 0x2C} {CLK_50_SDR_OTAP_DLY 0x4} {ENABLE 1} {IO\ -{PMC_MIO 26 .. 36}}} \ - PMC_SD1_SLOT_TYPE {SD 3.0} \ - PMC_USE_PMC_NOC_AXI0 {1} \ - PS_BOARD_INTERFACE {ps_pmc_fixed_io} \ - PS_ENET0_MDIO {{ENABLE 1} {IO {PS_MIO 24 .. 25}}} \ - PS_ENET0_PERIPHERAL {{ENABLE 1} {IO {PS_MIO 0 .. 11}}} \ - PS_GEN_IPI0_ENABLE {1} \ - PS_GEN_IPI0_MASTER {A72} \ - PS_GEN_IPI1_ENABLE {1} \ - PS_GEN_IPI1_MASTER {A72} \ - PS_GEN_IPI2_ENABLE {1} \ - PS_GEN_IPI2_MASTER {A72} \ - PS_GEN_IPI3_ENABLE {1} \ - PS_GEN_IPI3_MASTER {A72} \ - PS_GEN_IPI4_ENABLE {1} \ - PS_GEN_IPI4_MASTER {A72} \ - PS_GEN_IPI5_ENABLE {1} \ - PS_GEN_IPI5_MASTER {A72} \ - PS_GEN_IPI6_ENABLE {1} \ - PS_GEN_IPI6_MASTER {A72} \ - PS_I2C0_PERIPHERAL {{ENABLE 1} {IO {PMC_MIO 46 .. 47}}} \ - PS_I2C1_PERIPHERAL {{ENABLE 1} {IO {PMC_MIO 44 .. 45}}} \ - PS_I2CSYSMON_PERIPHERAL {{ENABLE 0} {IO {PMC_MIO 39 .. 40}}} \ - PS_IRQ_USAGE {{CH0 1} {CH1 0} {CH10 0} {CH11 0} {CH12 0} {CH13 0} {CH14 0} {CH15 0} {CH2 0} {CH3 0} {CH4 0} {CH5 0} {CH6 0} {CH7 0} {CH8 0} {CH9 0}} \ - PS_MIO7 {{AUX_IO 0} {DIRECTION in} {DRIVE_STRENGTH 8mA} {OUTPUT_DATA default} {PULL disable} {SCHMITT 0} {SLEW slow} {USAGE Reserved}} \ - PS_MIO9 {{AUX_IO 0} {DIRECTION in} {DRIVE_STRENGTH 8mA} {OUTPUT_DATA default} {PULL disable} {SCHMITT 0} {SLEW slow} {USAGE Reserved}} \ - PS_NUM_FABRIC_RESETS {1} \ - PS_PCIE_EP_RESET1_IO {PS_MIO 18} \ - PS_PCIE_EP_RESET2_IO {PS_MIO 19} \ - PS_PCIE_RESET {{ENABLE 1}} \ - PS_PL_CONNECTIVITY_MODE {Custom} \ - PS_TTC0_PERIPHERAL_ENABLE {1} \ - PS_UART0_PERIPHERAL {{ENABLE 1} {IO {PMC_MIO 42 .. 43}}} \ - PS_USB3_PERIPHERAL {{ENABLE 1} {IO {PMC_MIO 13 .. 25}}} \ - PS_USE_FPD_AXI_NOC0 {1} \ - PS_USE_FPD_AXI_NOC1 {1} \ - PS_USE_FPD_CCI_NOC {1} \ - PS_USE_M_AXI_FPD {1} \ - PS_USE_NOC_LPD_AXI0 {1} \ - PS_USE_PMCPL_CLK0 {1} \ - SMON_ALARMS {Set_Alarms_On} \ - SMON_ENABLE_TEMP_AVERAGING {0} \ - SMON_INTERFACE_TO_USE {I2C} \ - SMON_PMBUS_ADDRESS {0x18} \ - SMON_TEMP_AVERAGING_SAMPLES {0} \ - } \ - ] $CIPS_0 - - - # Create instance: axi_intc_0, and set properties - set axi_intc_0 [ create_bd_cell -type ip -vlnv xilinx.com:ip:axi_intc:4.1 axi_intc_0 ] - set_property -dict [list \ - CONFIG.C_ASYNC_INTR {0xFFFFFFFF} \ - CONFIG.C_IRQ_CONNECTION {1} \ - ] $axi_intc_0 - - - # Create instance: clk_wizard_0, and set properties - set clk_wizard_0 [ create_bd_cell -type ip -vlnv xilinx.com:ip:clk_wizard:1.0 clk_wizard_0 ] - set_property -dict [list \ - CONFIG.CE_TYPE {HARDSYNC} \ - CONFIG.CLKOUT_DRIVES {MBUFGCE,BUFG,BUFG,BUFG,BUFG,BUFG,BUFG} \ - CONFIG.CLKOUT_DYN_PS {None,None,None,None,None,None,None} \ - CONFIG.CLKOUT_GROUPING {Auto,Auto,Auto,Auto,Auto,Auto,Auto} \ - CONFIG.CLKOUT_MATCHED_ROUTING {false,false,false,false,false,false,false} \ - CONFIG.CLKOUT_PORT {clk_out1,clk_out2,clk_out3,clk_out4,clk_out5,clk_out6,clk_out7} \ - CONFIG.CLKOUT_REQUESTED_DUTY_CYCLE {50.000,50.000,50.000,50.000,50.000,50.000,50.000} \ - CONFIG.CLKOUT_REQUESTED_OUT_FREQUENCY {500.000,333.33333,300.000,100.000,100.000,100.000,100.000} \ - CONFIG.CLKOUT_REQUESTED_PHASE {0.000,0.000,0.000,0.000,0.000,0.000,0.000} \ - CONFIG.CLKOUT_USED {true,true,false,false,false,false,false} \ - CONFIG.JITTER_SEL {Min_O_Jitter} \ - CONFIG.PRIM_SOURCE {No_buffer} \ - CONFIG.RESET_TYPE {ACTIVE_LOW} \ - CONFIG.USE_PHASE_ALIGNMENT {true} \ - CONFIG.CE_TYPE {HARDSYNC} \ - ] $clk_wizard_0 - - - # Create instance: cips_noc, and set properties - set cips_noc [ create_bd_cell -type ip -vlnv xilinx.com:ip:axi_noc:1.1 cips_noc ] - set_property -dict [list \ - CONFIG.NUM_CLKS {10} \ - CONFIG.NUM_MI {1} \ - CONFIG.NUM_NMI {2} \ - CONFIG.NUM_NSI {0} \ - CONFIG.NUM_SI {8} \ - ] $cips_noc - - - set_property -dict [ list \ - CONFIG.CATEGORY {aie} \ - ] [get_bd_intf_pins /cips_noc/M00_AXI] - - set_property -dict [ list \ - CONFIG.CONNECTIONS {M01_INI { read_bw {128} write_bw {128}} M00_AXI { read_bw {5} write_bw {5} read_avg_burst {4} write_avg_burst {4}} M00_INI { read_bw {128} write_bw {128}} } \ - CONFIG.DEST_IDS {M00_AXI:0x0} \ - CONFIG.NOC_PARAMS {} \ - CONFIG.CATEGORY {ps_cci} \ - ] [get_bd_intf_pins /cips_noc/S00_AXI] - - set_property -dict [ list \ - CONFIG.CONNECTIONS {M01_INI { read_bw {128} write_bw {128}} M00_AXI { read_bw {5} write_bw {5} read_avg_burst {4} write_avg_burst {4}} M00_INI { read_bw {128} write_bw {128}} } \ - CONFIG.DEST_IDS {M00_AXI:0x0} \ - CONFIG.NOC_PARAMS {} \ - CONFIG.CATEGORY {ps_cci} \ - ] [get_bd_intf_pins /cips_noc/S01_AXI] - - set_property -dict [ list \ - CONFIG.CONNECTIONS {M01_INI { read_bw {128} write_bw {128}} M00_AXI { read_bw {5} write_bw {5} read_avg_burst {4} write_avg_burst {4}} M00_INI { read_bw {128} write_bw {128}} } \ - CONFIG.DEST_IDS {M00_AXI:0x0} \ - CONFIG.NOC_PARAMS {} \ - CONFIG.CATEGORY {ps_cci} \ - ] [get_bd_intf_pins /cips_noc/S02_AXI] - - set_property -dict [ list \ - CONFIG.CONNECTIONS {M01_INI { read_bw {128} write_bw {128}} M00_AXI { read_bw {5} write_bw {5} read_avg_burst {4} write_avg_burst {4}} M00_INI { read_bw {128} write_bw {128}} } \ - CONFIG.DEST_IDS {M00_AXI:0x0} \ - CONFIG.NOC_PARAMS {} \ - CONFIG.CATEGORY {ps_cci} \ - ] [get_bd_intf_pins /cips_noc/S03_AXI] - - set_property -dict [ list \ - CONFIG.CONNECTIONS {M01_INI { read_bw {128} write_bw {128}} M00_INI { read_bw {128} write_bw {128}} } \ - CONFIG.DEST_IDS {} \ - CONFIG.NOC_PARAMS {} \ - CONFIG.CATEGORY {ps_nci} \ - ] [get_bd_intf_pins /cips_noc/S04_AXI] - - set_property -dict [ list \ - CONFIG.CONNECTIONS {M01_INI { read_bw {128} write_bw {128}} M00_INI { read_bw {128} write_bw {128}} } \ - CONFIG.DEST_IDS {} \ - CONFIG.NOC_PARAMS {} \ - CONFIG.CATEGORY {ps_nci} \ - ] [get_bd_intf_pins /cips_noc/S05_AXI] - - set_property -dict [ list \ - CONFIG.CONNECTIONS {M01_INI { read_bw {128} write_bw {128}} M00_INI { read_bw {128} write_bw {128}} } \ - CONFIG.DEST_IDS {} \ - CONFIG.NOC_PARAMS {} \ - CONFIG.CATEGORY {ps_rpu} \ - ] [get_bd_intf_pins /cips_noc/S06_AXI] - - set_property -dict [ list \ - CONFIG.CONNECTIONS {M01_INI { read_bw {128} write_bw {128}} M00_AXI { read_bw {5} write_bw {5} read_avg_burst {4} write_avg_burst {4}} M00_INI { read_bw {128} write_bw {128}} } \ - CONFIG.DEST_IDS {M00_AXI:0x0} \ - CONFIG.NOC_PARAMS {} \ - CONFIG.CATEGORY {ps_pmc} \ - ] [get_bd_intf_pins /cips_noc/S07_AXI] - - set_property -dict [ list \ - CONFIG.ASSOCIATED_BUSIF {} \ - ] [get_bd_pins /cips_noc/aclk0] - - set_property -dict [ list \ - CONFIG.ASSOCIATED_BUSIF {S00_AXI} \ - ] [get_bd_pins /cips_noc/aclk1] - - set_property -dict [ list \ - CONFIG.ASSOCIATED_BUSIF {S01_AXI} \ - ] [get_bd_pins /cips_noc/aclk2] - - set_property -dict [ list \ - CONFIG.ASSOCIATED_BUSIF {S02_AXI} \ - ] [get_bd_pins /cips_noc/aclk3] - - set_property -dict [ list \ - CONFIG.ASSOCIATED_BUSIF {S03_AXI} \ - ] [get_bd_pins /cips_noc/aclk4] - - set_property -dict [ list \ - CONFIG.ASSOCIATED_BUSIF {S04_AXI} \ - ] [get_bd_pins /cips_noc/aclk5] - - set_property -dict [ list \ - CONFIG.ASSOCIATED_BUSIF {S05_AXI} \ - ] [get_bd_pins /cips_noc/aclk6] - - set_property -dict [ list \ - CONFIG.ASSOCIATED_BUSIF {S06_AXI} \ - ] [get_bd_pins /cips_noc/aclk7] - - set_property -dict [ list \ - CONFIG.ASSOCIATED_BUSIF {S07_AXI} \ - ] [get_bd_pins /cips_noc/aclk8] - - set_property -dict [ list \ - CONFIG.ASSOCIATED_BUSIF {M00_AXI} \ - ] [get_bd_pins /cips_noc/aclk9] - - # Create instance: noc_lpddr4_0, and set properties - set noc_lpddr4_0 [ create_bd_cell -type ip -vlnv xilinx.com:ip:axi_noc:1.1 noc_lpddr4_0 ] - set_property -dict [list \ - CONFIG.CH0_LPDDR4_0_BOARD_INTERFACE {ch0_lpddr4_trip1} \ - CONFIG.CH1_LPDDR4_0_BOARD_INTERFACE {ch1_lpddr4_trip1} \ - CONFIG.MC_CHANNEL_INTERLEAVING {true} \ - CONFIG.MC_CHAN_REGION1 {DDR_LOW1} \ - CONFIG.MC_CH_INTERLEAVING_SIZE {4K_Bytes} \ - CONFIG.NUM_CLKS {0} \ - CONFIG.NUM_MCP {4} \ - CONFIG.NUM_MI {0} \ - CONFIG.NUM_NSI {1} \ - CONFIG.NUM_SI {0} \ - CONFIG.sys_clk0_BOARD_INTERFACE {lpddr4_clk1} \ - ] $noc_lpddr4_0 - - - set_property -dict [ list \ - CONFIG.CONNECTIONS {MC_0 { read_bw {128} write_bw {128} read_avg_burst {4} write_avg_burst {4}} } \ - ] [get_bd_intf_pins /noc_lpddr4_0/S00_INI] - - # Create instance: proc_sys_reset_0, and set properties - set proc_sys_reset_0 [ create_bd_cell -type ip -vlnv xilinx.com:ip:proc_sys_reset:5.0 proc_sys_reset_0 ] - - # Create instance: proc_sys_reset_1, and set properties - set proc_sys_reset_1 [ create_bd_cell -type ip -vlnv xilinx.com:ip:proc_sys_reset:5.0 proc_sys_reset_1 ] - - # Create instance: smc_0, and set properties - set smc_0 [ create_bd_cell -type ip -vlnv xilinx.com:ip:smartconnect:1.0 smc_0 ] - set_property -dict [list \ - CONFIG.NUM_CLKS {1} \ - CONFIG.NUM_MI {1} \ - CONFIG.NUM_SI {1} \ - ] $smc_0 - - - # Create instance: ai_engine_0, and set properties - set ai_engine_0 [ create_bd_cell -type ip -vlnv xilinx.com:ip:ai_engine:2.0 ai_engine_0 ] - set_property -dict [list \ - CONFIG.CLK_NAMES {} \ - CONFIG.NAME_MI_AXI {} \ - CONFIG.NAME_MI_AXIS {} \ - CONFIG.NAME_SI_AXI {S00_AXI,} \ - CONFIG.NAME_SI_AXIS {} \ - CONFIG.NUM_CLKS {0} \ - CONFIG.NUM_MI_AXI {0} \ - CONFIG.NUM_MI_AXIS {0} \ - CONFIG.NUM_SI_AXI {1} \ - CONFIG.NUM_SI_AXIS {0} \ - ] $ai_engine_0 - - - set_property -dict [ list \ - CONFIG.CATEGORY {NOC} \ - ] [get_bd_intf_pins /ai_engine_0/S00_AXI] - - # Create instance: noc_lpddr4_1, and set properties - set noc_lpddr4_1 [ create_bd_cell -type ip -vlnv xilinx.com:ip:axi_noc:1.1 noc_lpddr4_1 ] - set_property -dict [list \ - CONFIG.CH0_LPDDR4_0_BOARD_INTERFACE {ch0_lpddr4_trip2} \ - CONFIG.CH0_LPDDR4_1_BOARD_INTERFACE {ch0_lpddr4_trip3} \ - CONFIG.CH1_LPDDR4_0_BOARD_INTERFACE {ch1_lpddr4_trip2} \ - CONFIG.CH1_LPDDR4_1_BOARD_INTERFACE {ch1_lpddr4_trip3} \ - CONFIG.MC_CHAN_REGION0 {DDR_CH1} \ - CONFIG.NUM_CLKS {0} \ - CONFIG.NUM_MI {0} \ - CONFIG.NUM_NSI {1} \ - CONFIG.NUM_SI {0} \ - CONFIG.sys_clk0_BOARD_INTERFACE {lpddr4_clk2} \ - CONFIG.sys_clk1_BOARD_INTERFACE {lpddr4_clk3} \ - ] $noc_lpddr4_1 - - - set_property -dict [ list \ - CONFIG.CONNECTIONS {MC_0 { read_bw {1720} write_bw {1720} read_avg_burst {4} write_avg_burst {4}} } \ - ] [get_bd_intf_pins /noc_lpddr4_1/S00_INI] - - # Create interface connections - connect_bd_intf_net -intf_net CIPS_0_FPD_AXI_NOC_0 [get_bd_intf_pins CIPS_0/FPD_AXI_NOC_0] [get_bd_intf_pins cips_noc/S04_AXI] - connect_bd_intf_net -intf_net CIPS_0_FPD_AXI_NOC_1 [get_bd_intf_pins CIPS_0/FPD_AXI_NOC_1] [get_bd_intf_pins cips_noc/S05_AXI] - connect_bd_intf_net -intf_net CIPS_0_FPD_CCI_NOC_0 [get_bd_intf_pins CIPS_0/FPD_CCI_NOC_0] [get_bd_intf_pins cips_noc/S00_AXI] - connect_bd_intf_net -intf_net CIPS_0_FPD_CCI_NOC_1 [get_bd_intf_pins CIPS_0/FPD_CCI_NOC_1] [get_bd_intf_pins cips_noc/S01_AXI] - connect_bd_intf_net -intf_net CIPS_0_FPD_CCI_NOC_2 [get_bd_intf_pins CIPS_0/FPD_CCI_NOC_2] [get_bd_intf_pins cips_noc/S02_AXI] - connect_bd_intf_net -intf_net CIPS_0_FPD_CCI_NOC_3 [get_bd_intf_pins CIPS_0/FPD_CCI_NOC_3] [get_bd_intf_pins cips_noc/S03_AXI] - connect_bd_intf_net -intf_net CIPS_0_LPD_AXI_NOC_0 [get_bd_intf_pins CIPS_0/LPD_AXI_NOC_0] [get_bd_intf_pins cips_noc/S06_AXI] - connect_bd_intf_net -intf_net CIPS_0_M_AXI_GP0 [get_bd_intf_pins CIPS_0/M_AXI_FPD] [get_bd_intf_pins smc_0/S00_AXI] - connect_bd_intf_net -intf_net CIPS_0_PMC_NOC_AXI_0 [get_bd_intf_pins CIPS_0/PMC_NOC_AXI_0] [get_bd_intf_pins cips_noc/S07_AXI] - connect_bd_intf_net -intf_net cips_noc_M00_AXI [get_bd_intf_pins cips_noc/M00_AXI] [get_bd_intf_pins ai_engine_0/S00_AXI] - connect_bd_intf_net -intf_net cips_noc_M00_INI [get_bd_intf_pins cips_noc/M00_INI] [get_bd_intf_pins noc_lpddr4_0/S00_INI] - connect_bd_intf_net -intf_net cips_noc_M01_INI [get_bd_intf_pins cips_noc/M01_INI] [get_bd_intf_pins noc_lpddr4_1/S00_INI] - connect_bd_intf_net -intf_net smc_0_M00_AXI [get_bd_intf_pins axi_intc_0/s_axi] [get_bd_intf_pins smc_0/M00_AXI] - connect_bd_intf_net -intf_net lpddr4_clk1_1 [get_bd_intf_ports lpddr4_clk1] [get_bd_intf_pins noc_lpddr4_0/sys_clk0] - connect_bd_intf_net -intf_net lpddr4_clk2_1 [get_bd_intf_ports lpddr4_clk2] [get_bd_intf_pins noc_lpddr4_1/sys_clk0] - connect_bd_intf_net -intf_net lpddr4_clk3_1 [get_bd_intf_ports lpddr4_clk3] [get_bd_intf_pins noc_lpddr4_1/sys_clk1] - connect_bd_intf_net -intf_net noc_lpddr4_0_CH0_LPDDR4_0 [get_bd_intf_ports ch0_lpddr4_trip1] [get_bd_intf_pins noc_lpddr4_0/CH0_LPDDR4_0] - connect_bd_intf_net -intf_net noc_lpddr4_0_CH1_LPDDR4_0 [get_bd_intf_ports ch1_lpddr4_trip1] [get_bd_intf_pins noc_lpddr4_0/CH1_LPDDR4_0] - connect_bd_intf_net -intf_net noc_lpddr4_1_CH0_LPDDR4_0 [get_bd_intf_ports ch0_lpddr4_trip2] [get_bd_intf_pins noc_lpddr4_1/CH0_LPDDR4_0] - connect_bd_intf_net -intf_net noc_lpddr4_1_CH0_LPDDR4_1 [get_bd_intf_ports ch0_lpddr4_trip3] [get_bd_intf_pins noc_lpddr4_1/CH0_LPDDR4_1] - connect_bd_intf_net -intf_net noc_lpddr4_1_CH1_LPDDR4_0 [get_bd_intf_ports ch1_lpddr4_trip2] [get_bd_intf_pins noc_lpddr4_1/CH1_LPDDR4_0] - connect_bd_intf_net -intf_net noc_lpddr4_1_CH1_LPDDR4_1 [get_bd_intf_ports ch1_lpddr4_trip3] [get_bd_intf_pins noc_lpddr4_1/CH1_LPDDR4_1] - - # Create port connections - connect_bd_net -net CIPS_0_fpd_axi_noc_axi0_clk [get_bd_pins CIPS_0/fpd_axi_noc_axi0_clk] [get_bd_pins cips_noc/aclk5] - connect_bd_net -net CIPS_0_fpd_axi_noc_axi1_clk [get_bd_pins CIPS_0/fpd_axi_noc_axi1_clk] [get_bd_pins cips_noc/aclk6] - connect_bd_net -net CIPS_0_fpd_cci_noc_axi0_clk [get_bd_pins CIPS_0/fpd_cci_noc_axi0_clk] [get_bd_pins cips_noc/aclk1] - connect_bd_net -net CIPS_0_fpd_cci_noc_axi1_clk [get_bd_pins CIPS_0/fpd_cci_noc_axi1_clk] [get_bd_pins cips_noc/aclk2] - connect_bd_net -net CIPS_0_fpd_cci_noc_axi2_clk [get_bd_pins CIPS_0/fpd_cci_noc_axi2_clk] [get_bd_pins cips_noc/aclk3] - connect_bd_net -net CIPS_0_fpd_cci_noc_axi3_clk [get_bd_pins CIPS_0/fpd_cci_noc_axi3_clk] [get_bd_pins cips_noc/aclk4] - connect_bd_net -net CIPS_0_lpd_axi_noc_clk [get_bd_pins CIPS_0/lpd_axi_noc_clk] [get_bd_pins cips_noc/aclk7] - connect_bd_net -net CIPS_0_pl_clk0 [get_bd_pins CIPS_0/pl0_ref_clk] [get_bd_pins clk_wizard_0/clk_in1] - connect_bd_net -net CIPS_0_pl_resetn1 [get_bd_pins CIPS_0/pl0_resetn] [get_bd_pins clk_wizard_0/resetn] [get_bd_pins proc_sys_reset_0/ext_reset_in] [get_bd_pins proc_sys_reset_1/ext_reset_in] - connect_bd_net -net CIPS_0_pmc_axi_noc_axi0_clk [get_bd_pins CIPS_0/pmc_axi_noc_axi0_clk] [get_bd_pins cips_noc/aclk8] - connect_bd_net -net ai_engine_0_s00_axi_aclk [get_bd_pins ai_engine_0/s00_axi_aclk] [get_bd_pins cips_noc/aclk9] - connect_bd_net -net axi_intc_0_irq [get_bd_pins axi_intc_0/irq] [get_bd_pins CIPS_0/pl_ps_irq0] - connect_bd_net -net clk_wizard_0_clk_125 [get_bd_pins clk_wizard_0/clk_out1_o3] - connect_bd_net -net clk_wizard_0_clk_250 [get_bd_pins clk_wizard_0/clk_out1_o2] [get_bd_pins axi_intc_0/s_axi_aclk] [get_bd_pins CIPS_0/m_axi_fpd_aclk] [get_bd_pins cips_noc/aclk0] [get_bd_pins smc_0/aclk] - connect_bd_net -net clk_wizard_0_clk_333 [get_bd_pins clk_wizard_0/clk_out2] [get_bd_pins proc_sys_reset_1/slowest_sync_clk] - connect_bd_net -net clk_wizard_0_clk_500 [get_bd_pins clk_wizard_0/clk_out1_o1] - connect_bd_net -net clk_wizard_0_clk_62_5 [get_bd_pins clk_wizard_0/clk_out1_o4] [get_bd_pins proc_sys_reset_0/slowest_sync_clk] - connect_bd_net -net clk_wizard_0_locked [get_bd_pins clk_wizard_0/locked] [get_bd_pins clk_wizard_0/clk_out1_ce] [get_bd_pins clk_wizard_0/clk_out1_clr_n] [get_bd_pins proc_sys_reset_0/dcm_locked] [get_bd_pins proc_sys_reset_1/dcm_locked] - connect_bd_net -net proc_sys_reset_0_peripheral_aresetn [get_bd_pins proc_sys_reset_0/peripheral_aresetn] [get_bd_pins axi_intc_0/s_axi_aresetn] [get_bd_pins smc_0/aresetn] - - # Create address segments - assign_bd_address -offset 0x00000000 -range 0x80000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_AXI_NOC_0] [get_bd_addr_segs noc_lpddr4_0/S00_INI/C0_DDR_LOW0] -force - assign_bd_address -offset 0x000800000000 -range 0x80000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_AXI_NOC_0] [get_bd_addr_segs noc_lpddr4_0/S00_INI/C0_DDR_LOW1] -force - assign_bd_address -offset 0x050000000000 -range 0x000200000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_AXI_NOC_0] [get_bd_addr_segs noc_lpddr4_1/S00_INI/C0_DDR_CH1x2] -force - assign_bd_address -offset 0x00000000 -range 0x80000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_AXI_NOC_1] [get_bd_addr_segs noc_lpddr4_0/S00_INI/C0_DDR_LOW0] -force - assign_bd_address -offset 0x000800000000 -range 0x80000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_AXI_NOC_1] [get_bd_addr_segs noc_lpddr4_0/S00_INI/C0_DDR_LOW1] -force - assign_bd_address -offset 0x050000000000 -range 0x000200000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_AXI_NOC_1] [get_bd_addr_segs noc_lpddr4_1/S00_INI/C0_DDR_CH1x2] -force - assign_bd_address -offset 0x020000000000 -range 0x000100000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_CCI_NOC_0] [get_bd_addr_segs ai_engine_0/S00_AXI/AIE_ARRAY_0] -force - assign_bd_address -offset 0x00000000 -range 0x80000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_CCI_NOC_0] [get_bd_addr_segs noc_lpddr4_0/S00_INI/C0_DDR_LOW0] -force - assign_bd_address -offset 0x000800000000 -range 0x80000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_CCI_NOC_0] [get_bd_addr_segs noc_lpddr4_0/S00_INI/C0_DDR_LOW1] -force - assign_bd_address -offset 0x050000000000 -range 0x000200000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_CCI_NOC_0] [get_bd_addr_segs noc_lpddr4_1/S00_INI/C0_DDR_CH1x2] -force - assign_bd_address -offset 0x020000000000 -range 0x000100000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_CCI_NOC_1] [get_bd_addr_segs ai_engine_0/S00_AXI/AIE_ARRAY_0] -force - assign_bd_address -offset 0x00000000 -range 0x80000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_CCI_NOC_1] [get_bd_addr_segs noc_lpddr4_0/S00_INI/C0_DDR_LOW0] -force - assign_bd_address -offset 0x000800000000 -range 0x80000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_CCI_NOC_1] [get_bd_addr_segs noc_lpddr4_0/S00_INI/C0_DDR_LOW1] -force - assign_bd_address -offset 0x050000000000 -range 0x000200000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_CCI_NOC_1] [get_bd_addr_segs noc_lpddr4_1/S00_INI/C0_DDR_CH1x2] -force - assign_bd_address -offset 0x020000000000 -range 0x000100000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_CCI_NOC_2] [get_bd_addr_segs ai_engine_0/S00_AXI/AIE_ARRAY_0] -force - assign_bd_address -offset 0x00000000 -range 0x80000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_CCI_NOC_2] [get_bd_addr_segs noc_lpddr4_0/S00_INI/C0_DDR_LOW0] -force - assign_bd_address -offset 0x000800000000 -range 0x80000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_CCI_NOC_2] [get_bd_addr_segs noc_lpddr4_0/S00_INI/C0_DDR_LOW1] -force - assign_bd_address -offset 0x050000000000 -range 0x000200000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_CCI_NOC_2] [get_bd_addr_segs noc_lpddr4_1/S00_INI/C0_DDR_CH1x2] -force - assign_bd_address -offset 0x020000000000 -range 0x000100000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_CCI_NOC_3] [get_bd_addr_segs ai_engine_0/S00_AXI/AIE_ARRAY_0] -force - assign_bd_address -offset 0x00000000 -range 0x80000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_CCI_NOC_3] [get_bd_addr_segs noc_lpddr4_0/S00_INI/C0_DDR_LOW0] -force - assign_bd_address -offset 0x000800000000 -range 0x80000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_CCI_NOC_3] [get_bd_addr_segs noc_lpddr4_0/S00_INI/C0_DDR_LOW1] -force - assign_bd_address -offset 0x050000000000 -range 0x000200000000 -target_address_space [get_bd_addr_spaces CIPS_0/FPD_CCI_NOC_3] [get_bd_addr_segs noc_lpddr4_1/S00_INI/C0_DDR_CH1x2] -force - assign_bd_address -offset 0x00000000 -range 0x80000000 -target_address_space [get_bd_addr_spaces CIPS_0/LPD_AXI_NOC_0] [get_bd_addr_segs noc_lpddr4_0/S00_INI/C0_DDR_LOW0] -force - assign_bd_address -offset 0x000800000000 -range 0x80000000 -target_address_space [get_bd_addr_spaces CIPS_0/LPD_AXI_NOC_0] [get_bd_addr_segs noc_lpddr4_0/S00_INI/C0_DDR_LOW1] -force - assign_bd_address -offset 0x050000000000 -range 0x000200000000 -target_address_space [get_bd_addr_spaces CIPS_0/LPD_AXI_NOC_0] [get_bd_addr_segs noc_lpddr4_1/S00_INI/C0_DDR_CH1x2] -force - assign_bd_address -offset 0xA4000000 -range 0x00010000 -target_address_space [get_bd_addr_spaces CIPS_0/M_AXI_FPD] [get_bd_addr_segs axi_intc_0/S_AXI/Reg] -force - assign_bd_address -offset 0x020000000000 -range 0x000100000000 -target_address_space [get_bd_addr_spaces CIPS_0/PMC_NOC_AXI_0] [get_bd_addr_segs ai_engine_0/S00_AXI/AIE_ARRAY_0] -force - assign_bd_address -offset 0x00000000 -range 0x80000000 -target_address_space [get_bd_addr_spaces CIPS_0/PMC_NOC_AXI_0] [get_bd_addr_segs noc_lpddr4_0/S00_INI/C0_DDR_LOW0] -force - assign_bd_address -offset 0x000800000000 -range 0x80000000 -target_address_space [get_bd_addr_spaces CIPS_0/PMC_NOC_AXI_0] [get_bd_addr_segs noc_lpddr4_0/S00_INI/C0_DDR_LOW1] -force - assign_bd_address -offset 0x050000000000 -range 0x000200000000 -target_address_space [get_bd_addr_spaces CIPS_0/PMC_NOC_AXI_0] [get_bd_addr_segs noc_lpddr4_1/S00_INI/C0_DDR_CH1x2] -force - - - # Restore current instance - current_bd_instance $oldCurInst - - # Create PFM attributes - set_property PFM_NAME {xilinx.com:vek280:vek280_es1_custom:1.0} [get_files [current_bd_design].bd] - set_property PFM.IRQ {intr {id 0 range 15}} [get_bd_cells /axi_intc_0] - set_property PFM.CLOCK {clk_out1_o1 {id "0" is_default "true" proc_sys_reset "/proc_sys_reset_0" status "fixed" freq_hz "500000000"} clk_out1_o2 {id "1" is_default "false" proc_sys_reset "/proc_sys_reset_0" status "fixed" freq_hz "250000000"} clk_out1_o3 {id "2" is_default "false" proc_sys_reset "/proc_sys_reset_0" status "fixed" freq_hz "125000000"} clk_out1_o4 {id "3" is_default "false" proc_sys_reset "/proc_sys_reset_0" status "fixed" freq_hz "62500000"} clk_out2 {id "4" is_default "false" proc_sys_reset "/proc_sys_reset_1" status "fixed" freq_hz "333333333"}} [get_bd_cells /clk_wizard_0] - set_property PFM.AXI_PORT {S00_AXI {memport "S_AXI_NOC" sptag "DDR"} S01_AXI {memport "S_AXI_NOC" sptag "DDR"} S02_AXI {memport "S_AXI_NOC" sptag "DDR"} S03_AXI {memport "S_AXI_NOC" sptag "DDR"} S04_AXI {memport "S_AXI_NOC" sptag "DDR"} S05_AXI {memport "S_AXI_NOC" sptag "DDR"} S06_AXI {memport "S_AXI_NOC" sptag "DDR"} S07_AXI {memport "S_AXI_NOC" sptag "DDR"} S08_AXI {memport "S_AXI_NOC" sptag "DDR"} S09_AXI {memport "S_AXI_NOC" sptag "DDR"} S10_AXI {memport "S_AXI_NOC" sptag "DDR"} S11_AXI {memport "S_AXI_NOC" sptag "DDR"} S12_AXI {memport "S_AXI_NOC" sptag "DDR"} S13_AXI {memport "S_AXI_NOC" sptag "DDR"} S14_AXI {memport "S_AXI_NOC" sptag "DDR"} S15_AXI {memport "S_AXI_NOC" sptag "DDR"} S16_AXI {memport "S_AXI_NOC" sptag "DDR"} S17_AXI {memport "S_AXI_NOC" sptag "DDR"} S18_AXI {memport "S_AXI_NOC" sptag "DDR"} S19_AXI {memport "S_AXI_NOC" sptag "DDR"} S20_AXI {memport "S_AXI_NOC" sptag "DDR"} S21_AXI {memport "S_AXI_NOC" sptag "DDR"} S22_AXI {memport "S_AXI_NOC" sptag "DDR"} S23_AXI {memport "S_AXI_NOC" sptag "DDR"} S24_AXI {memport "S_AXI_NOC" sptag "DDR"} S25_AXI {memport "S_AXI_NOC" sptag "DDR"} S26_AXI {memport "S_AXI_NOC" sptag "DDR"} S27_AXI {memport "S_AXI_NOC" sptag "DDR"}} [get_bd_cells /noc_lpddr4_0] - set_property PFM.AXI_PORT {M01_AXI {memport "M_AXI_GP" sptag "" memory ""} M02_AXI {memport "M_AXI_GP" sptag "" memory ""} M03_AXI {memport "M_AXI_GP" sptag "" memory ""} M04_AXI {memport "M_AXI_GP" sptag "" memory ""} M05_AXI {memport "M_AXI_GP" sptag "" memory ""} M06_AXI {memport "M_AXI_GP" sptag "" memory ""} M07_AXI {memport "M_AXI_GP" sptag "" memory ""} M08_AXI {memport "M_AXI_GP" sptag "" memory ""} M09_AXI {memport "M_AXI_GP" sptag "" memory ""} M10_AXI {memport "M_AXI_GP" sptag "" memory ""} M11_AXI {memport "M_AXI_GP" sptag "" memory ""} M12_AXI {memport "M_AXI_GP" sptag "" memory ""} M13_AXI {memport "M_AXI_GP" sptag "" memory ""} M14_AXI {memport "M_AXI_GP" sptag "" memory ""} M15_AXI {memport "M_AXI_GP" sptag "" memory ""}} [get_bd_cells /smc_0] - set_property PFM.AXI_PORT {S00_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S01_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S02_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S03_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S04_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S05_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S06_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S07_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S08_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S09_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S10_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S11_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S12_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S13_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S14_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S15_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S16_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S17_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S18_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S19_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S20_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S21_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S22_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S23_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S24_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S25_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S26_AXI {memport "S_AXI_NOC" sptag "LPDDR"} S27_AXI {memport "S_AXI_NOC" sptag "LPDDR"}} [get_bd_cells /noc_lpddr4_1] - - - validate_bd_design - save_bd_design -} -# End of create_root_design() - - -################################################################## -# MAIN FLOW -################################################################## - -create_root_design "" - - diff --git a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/post_link_pfm_config.tcl b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/post_link_pfm_config.tcl deleted file mode 100644 index 1b58dcec40..0000000000 --- a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/post_link_pfm_config.tcl +++ /dev/null @@ -1,6 +0,0 @@ -# -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: X11 -# - -# nothing required for this platform diff --git a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/post_physopt.tcl b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/post_physopt.tcl deleted file mode 100644 index e7ff411059..0000000000 --- a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/post_physopt.tcl +++ /dev/null @@ -1,5 +0,0 @@ -# -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: X11 -# -# Not used in this project diff --git a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/post_place.tcl b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/post_place.tcl deleted file mode 100644 index dc60066586..0000000000 --- a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/post_place.tcl +++ /dev/null @@ -1,7 +0,0 @@ -# -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: X11 -# - -source [pwd]/../../prj.srcs/utils_1/imports/qor_scripts/waive_BLI_AIE_timing_violations_postplace.tcl - diff --git a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/post_route.tcl b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/post_route.tcl deleted file mode 100644 index 7b29cfda7d..0000000000 --- a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/post_route.tcl +++ /dev/null @@ -1,6 +0,0 @@ -# -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: X11 -# - -# Not used in this project diff --git a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/pre_place.tcl b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/pre_place.tcl deleted file mode 100644 index 99bc9714c2..0000000000 --- a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/pre_place.tcl +++ /dev/null @@ -1,10 +0,0 @@ -# -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: X11 -# - -source [pwd]/../../prj.srcs/utils_1/imports/qor_scripts/prohibitCascBramAcrossRbrk.tcl -source [pwd]/../../prj.srcs/utils_1/imports/qor_scripts/prohibitCascUramAcrossRbrk.tcl -source [pwd]/../../prj.srcs/utils_1/imports/qor_scripts/prohibitCascDspAcrossRbrk.tcl -source [pwd]/../../prj.srcs/utils_1/imports/qor_scripts/waive_BLI_AIE_timing_violations_preplace.tcl - diff --git a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/prohibitCascBramAcrossRbrk.tcl b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/prohibitCascBramAcrossRbrk.tcl deleted file mode 100644 index 7980b481ab..0000000000 --- a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/prohibitCascBramAcrossRbrk.tcl +++ /dev/null @@ -1,16 +0,0 @@ -# -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: X11 -# - -catch {unset ys} -foreach cr [get_clock_regions {X*Y1 X*Y2 X*Y3}] { - set bram [get_sites -quiet -filter NAME=~RAMB36_X*Y* -of $cr] - if {$bram == {}} { continue } - lappend ys [lindex [lsort -integer -increasing [regsub -all {RAMB36_X\d+Y(\d+)} $bram {\1}]] end] -} -foreach y $ys { - set_property PROHIBIT TRUE [get_sites RAMB36_X*Y$y] - set_property PROHIBIT TRUE [get_sites RAMB18_X*Y[expr 2 * $y]] - set_property PROHIBIT TRUE [get_sites RAMB18_X*Y[expr 2 * $y + 1]] -} diff --git a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/prohibitCascDspAcrossRbrk.tcl b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/prohibitCascDspAcrossRbrk.tcl deleted file mode 100644 index e87c6fc043..0000000000 --- a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/prohibitCascDspAcrossRbrk.tcl +++ /dev/null @@ -1,14 +0,0 @@ -# -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: X11 -# - -catch {unset ys} -foreach cr [get_clock_regions {X*Y1 X*Y2 X*Y3}] { - set dsp [get_sites -quiet -filter NAME=~DSP_X*Y* -of $cr] - if {$dsp == {}} { continue } - lappend ys [lindex [lsort -integer -increasing [regsub -all {DSP_X\d+Y(\d+)} $dsp {\1}]] end] -} -foreach y $ys { - set_property PROHIBIT TRUE [get_sites DSP*_X*Y$y] -} diff --git a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/prohibitCascUramAcrossRbrk.tcl b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/prohibitCascUramAcrossRbrk.tcl deleted file mode 100644 index 6f18b5f0c3..0000000000 --- a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/prohibitCascUramAcrossRbrk.tcl +++ /dev/null @@ -1,14 +0,0 @@ -# -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: X11 -# - -catch {unset ys} -foreach cr [get_clock_regions {X*Y1 X*Y2 X*Y3}] { - set uram [get_sites -quiet -filter NAME=~URAM288_X*Y* -of $cr] - if {$uram == {}} { continue } - lappend ys [lindex [lsort -integer -increasing [regsub -all {URAM288_X\d+Y(\d+)} $uram {\1}]] end] -} -foreach y $ys { - set_property PROHIBIT TRUE [get_sites URAM288_X*Y$y] -} diff --git a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/timing.xdc b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/timing.xdc deleted file mode 100755 index bce76bcdf2..0000000000 --- a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/timing.xdc +++ /dev/null @@ -1,5 +0,0 @@ -# -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: X11 -# - diff --git a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/waive_BLI_AIE_timing_violations_postplace.tcl b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/waive_BLI_AIE_timing_violations_postplace.tcl deleted file mode 100644 index b01e766ada..0000000000 --- a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/waive_BLI_AIE_timing_violations_postplace.tcl +++ /dev/null @@ -1,21 +0,0 @@ -# -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: X11 -# - -# Last update; 2019/09/12 -# Last change: added conditions to prevent ERRORs when no BLI or AIE_PL cells are found after place_design -# - -set bliFD [get_cells -quiet -hier -filter "REF_NAME=~FD* && LOC=~BLI_*"] -if {$bliFD == {}} { puts "Warning - No registers placed on BLI sites found" } - -set aiePL [get_cells -quiet -hier -filter "REF_NAME=~AIE_PL_*"] -if {$aiePL == {}} { puts "Warning - No AIE_PL_* cells found" } - -if {$bliFD != {} && $aiePL != {}} { - set_property IS_LOC_FIXED 1 $bliFD - set_false_path -from $bliFD -to $aiePL - set_false_path -from $aiePL -to $bliFD -} - diff --git a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/waive_BLI_AIE_timing_violations_preplace.tcl b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/waive_BLI_AIE_timing_violations_preplace.tcl deleted file mode 100644 index 4d9d1507e0..0000000000 --- a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/qor_scripts/waive_BLI_AIE_timing_violations_preplace.tcl +++ /dev/null @@ -1,34 +0,0 @@ -# -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: X11 -# - -# Last update; 2019/09/06 -# Last change: checking on AIE_PL BEL location to make sure there is a BLI site available -# -# Last update; 2019/11/20 -# Last change: adding support for 128b interfaces -# - -set debug 0 -foreach aiePL [get_cells -quiet -hier -filter "REF_NAME=~AIE_PL_* && PRIMITIVE_LEVEL!=MACRO"] { - set loc [get_property LOC $aiePL] - if {$loc == ""} { if {$debug} { puts "D - Missing LOC - $aiePL" }; continue } ;# Unplace AIE_PL cell => unsafe to waive timing - set bel [get_property BEL $aiePL] - if {$bel == "AIE_PL.AIE_PL_S_AXIS_3"} { if {$debug} { puts "D - BEL 3 - $aiePL" }; continue } ;# No BLI register site available - if {$bel == "AIE_PL.AIE_PL_S_AXIS_7"} { if {$debug} { puts "D - BEL 7 - $aiePL" }; continue } ;# No BLI register site available - foreach dir {IN OUT} { - set bliFD [get_cells -quiet -filter "REF_NAME=~FD* && BLI==TRUE" -of [get_pins -leaf -of [get_nets -filter "FLAT_PIN_COUNT==2" -of [get_pins -filter "!IS_CLOCK && DIRECTION==$dir" -of $aiePL]]]] - if {$bliFD == {}} { if {$debug} { puts "D - no BLI FD - $dir - $aiePL" }; continue } - set refName [get_property REF_NAME $aiePL] - set locBel "$loc/[regsub {.*\.} $bel {}]" - if {$dir == "IN"} { - puts [format "INFO - Adding False Path waiver from %2s BLI registers to $refName ($locBel) - $aiePL" [llength $bliFD]] - set_false_path -from $bliFD -to $aiePL - } else { - puts [format "INFO - Adding False Path waiver to %2s BLI registers from $refName ($locBel) - $aiePL" [llength $bliFD]] - set_false_path -from $aiePL -to $bliFD - } - } -} - diff --git a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/xsa_platform_classic.tcl b/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/xsa_platform_classic.tcl deleted file mode 100644 index d87d7fa7ef..0000000000 --- a/Vitis_System_Design/Design_Tutorials/01-Versal_Custom_Thin_Platform_Extensible_System/vivado/vek280_es1/xsa_platform_classic.tcl +++ /dev/null @@ -1,164 +0,0 @@ -# -# Copyright (C) 2023, Advanced Micro Devices, Inc. All rights reserved. -# SPDX-License-Identifier: X11 -# - -## =================================================================================== -## Create Platform Vivado Project -## This script takes in two argument: -## PLATFORM_NAME -## DEVICE_NAME (e.g. xcvc1902-vsva2197-1LP-e-S) -## =================================================================================== -namespace eval _tcl { - proc get_script_folder {} { - set script_path [file normalize [info script]] - set script_folder [file dirname $script_path] - return $script_folder - } -} - -variable script_folder -set script_folder [_tcl::get_script_folder] - -#set_param board.repoPaths ../board_repo/boards/Xilinx/vck190 - -## WORKAROUND - Hardcode platform and device name as tcl arguments is not passed properly to Vitis -set BOARD_NAME [lindex $argv 0] -set PLATFORM_NAME [lindex $argv 1] -set PLATFORM_TYPE ${PLATFORM_NAME}_custom -set VER "1.0" -puts "Creating HW Platform project for : \"$PLATFORM_NAME\"" -set DEVICE_NAME [lindex $argv 2] -puts "Using : \"$DEVICE_NAME\"" -set BOARD_LABEL [lindex $argv 4] -set BOARD_VER [lindex $argv 5] -set BUILD_DIR build - -create_project -f ${PLATFORM_NAME} ${BUILD_DIR}/${PLATFORM_NAME}_vivado -part $DEVICE_NAME - -# set board part -set_property BOARD_PART xilinx.com:${BOARD_LABEL}:part0:${BOARD_VER} [current_project] - -set_property preferred_sim_model "tlm" [current_project] - -## =================================================================================== -## Create Block Design -## =================================================================================== -# pass arguments to tcl -#set argv [list $PLATFORM_NAME $DEVICE_NAME] -#set argc 2 -source ./${BOARD_NAME}/dr.bd.tcl - -## =================================================================================== -## Set Platform Properties (e.g. PFM.*) -## =================================================================================== -#source ./${BOARD_NAME}/pfm_decls.tcl - -## =================================================================================== -## Add constraints to DDR4 -## =================================================================================== -#add_files -fileset constrs_1 -norecurse src/ddr4_dmc_3200_triplet_1.xdc - -## =================================================================================== -## Create a wrapper for block design. Set the block design as top-level wrapper. -## =================================================================================== -make_wrapper -files [get_files ${BUILD_DIR}/${PLATFORM_NAME}_vivado/${PLATFORM_NAME}.srcs/sources_1/bd/${PLATFORM_NAME}/${PLATFORM_NAME}.bd] -top -add_files -norecurse ${BUILD_DIR}/${PLATFORM_NAME}_vivado/${PLATFORM_NAME}.srcs/sources_1/bd/${PLATFORM_NAME}/hdl/${PLATFORM_NAME}_wrapper.v -update_compile_order -fileset sources_1 - -## =================================================================================== -## Apply platform specific post-link tcl commands. -## Note: This design does not have have any post-link tcl commands. -## =================================================================================== - -## =================================================================================== -## Apply timing constraints -## =================================================================================== -#add_files -fileset constrs_1 -norecurse src/qor_scripts/timing.xdc - -## =================================================================================== -## Apply scripts to close timing -## =================================================================================== -#import_files -fileset utils_1 -norecurse src/qor_scripts/pre_place.tcl -#import_files -fileset utils_1 -norecurse src/qor_scripts/post_place.tcl -#import_files -fileset utils_1 -norecurse src/qor_scripts/post_route.tcl -#import_files -fileset utils_1 -norecurse src/qor_scripts/post_physopt.tcl -#import_files -fileset utils_1 -norecurse src/qor_scripts/prohibitCascDspAcrossRbrk.tcl -#import_files -fileset utils_1 -norecurse src/qor_scripts/prohibitCascBramAcrossRbrk.tcl -#import_files -fileset utils_1 -norecurse src/qor_scripts/prohibitCascUramAcrossRbrk.tcl -#import_files -fileset utils_1 -norecurse src/qor_scripts/waive_BLI_AIE_timing_violations_postplace.tcl -#import_files -fileset utils_1 -norecurse src/qor_scripts/waive_BLI_AIE_timing_violations_preplace.tcl - -#set_property platform.run.steps.place_design.tcl.pre [get_files pre_place.tcl] [current_project] -#set_property platform.run.steps.place_design.tcl.post [get_files post_place.tcl] [current_project] -#set_property platform.run.steps.route_design.tcl.post [get_files post_route.tcl] [current_project] -#set_property platform.run.steps.phys_opt_design.tcl.post [get_files post_physopt.tcl] [current_project] - -## =================================================================================== -## Set output type to hw_export -## =================================================================================== -set_property platform.default_output_type "sd_card" [current_project] -# Help by explicitly categorizing intended platform -set_property platform.design_intent.server_managed "false" [current_project] -set_property platform.design_intent.external_host "false" [current_project] -set_property platform.design_intent.embedded "true" [current_project] -set_property platform.design_intent.datacenter "false" [current_project] -set_property platform.extensible "true" [current_project] - -## =================================================================================== -## Add hardware emulation support -## =================================================================================== -set_property PLATFORM.LINK_XP_SWITCHES_DEFAULT [list param:hw_emu.enableProfiling=false] [current_project] -#set_property SELECTED_SIM_MODEL tlm [get_bd_cells /Cips] -#set_property SELECTED_SIM_MODEL tlm [get_bd_cells /CipsNoc] -#set_property SELECTED_SIM_MODEL tlm [get_bd_cells /MemoryNoc] -#set_property SELECTED_SIM_MODEL tlm [get_bd_cells /ExtensibleRegion/ControlNoc] -#set_property SELECTED_SIM_MODEL tlm [get_bd_cells /ExtensibleRegion/DDR] - -## =================================================================================== -## Wrap up Vivado Platform Project -## =================================================================================== -update_compile_order -assign_bd_address -regenerate_bd_layout -validate_bd_design -import_files - -## =================================================================================== -## Generate files necessary to support block design through design flow -## =================================================================================== -generate_target all [get_files ${BUILD_DIR}/${PLATFORM_NAME}_vivado/${PLATFORM_NAME}.srcs/sources_1/bd/${PLATFORM_NAME}/${PLATFORM_NAME}.bd] - -variable pre_synth -set pre_synth "" - -if { $argc > 1} { - set pre_synth [lindex $argv 3] -} -#Pre_synth Platform Flow -if {$pre_synth} { - set_property platform.platform_state "pre_synth" [current_project] - write_hw_platform -force ${BUILD_DIR}/xsa_platform/${PLATFORM_NAME}.xsa - validate_hw_platform ${BUILD_DIR}/xsa_platform/${PLATFORM_NAME}.xsa -} else { - set_property generate_synth_checkpoint true [get_files -norecurse *.bd] - ## =================================================================================== - ## Full Synthesis and implementation - ## =================================================================================== - launch_runs -jobs 8 synth_1 - wait_on_run synth_1 - puts "Synthesis done!" - - #launch_runs impl_1 -to_step write_bitstream - launch_runs -jobs 8 impl_1 -to_step write_device_image - wait_on_run impl_1 - puts "Implementation done!" - - # =================================================================================== - # Write the XSA for current design for use as a hardware platform - # =================================================================================== - open_run impl_1 - write_hw_platform -unified -include_bit -force ${BUILD_DIR}/xsa_platform/${PLATFORM_NAME}.xsa - validate_hw_platform ${BUILD_DIR}/xsa_platform/${PLATFORM_NAME}.xsa -} - diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/Makefile b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/Makefile index 61a26603ca..1f348b01dd 100755 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/Makefile +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/Makefile @@ -11,7 +11,7 @@ ECHO = @echo ################################################################################ # Variables needed for AMD tools version checking, PLEASE DO NOT MODIFY # ################################################################################ -REQUIRED_VERSION = 2025.1 +REQUIRED_VERSION = 2025.2 VIVADO_VERSION := $(shell vivado -version 2>/dev/null | grep "vivado ") VITIS_VERSION := $(shell vitis -version 2>/dev/null | grep "Vitis " | sed 's/\*//g') diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/README.md b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/README.md index 81c0556344..2cb41ee41c 100644 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/README.md +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/README.md @@ -14,9 +14,9 @@ # Versal Custom Platform Integration using Vitis Subsystem -***Version: Vivado and Vitis 2025.1*** +***Version: Vivado and Vitis 2025.2*** -This tutorial demonstrates key features in AMD 2025.1 tools for designing and verifying AI Engine and HLS based DSP subsystem and deploy it on a custom platform. +This tutorial demonstrates key features in AMD 2025.2 tools for designing and verifying AI Engine and HLS based DSP subsystem and deploy it on a custom platform. To show the design, verification and integration activities, the tutorial use simple building blocks to make it easy to track the design results and processing data with visual inspection. The example blocks are verified with basic test benches to demonstrate using the verification features, and it's adviced that user complement with more advanced tests to reach acceptable coverage. @@ -121,7 +121,7 @@ This figure describe the order of which the hardware design components are arran ## Getting Started ### Prerequisites -Setup the Vitis 2025.1 tools +Setup the Vitis 2025.2 tools ``` source /settings64.sh ``` diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/linux/dtg/Makefile b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/linux/dtg/Makefile index 04342e9796..8cd545d04b 100755 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/linux/dtg/Makefile +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/linux/dtg/Makefile @@ -11,7 +11,7 @@ BOARD_NAME ?= vck190 PLATFORM_CUSTOM ?= ${BOARD_NAME}_thin DTG := device-tree-xlnx -#DTG_VERSION := xlnx_rel_v2025.1 +#DTG_VERSION := xlnx_rel_v2025.2 DTG_VERSION := master DTC := dtc @@ -71,7 +71,7 @@ build_xsct: build_sdt: $(ECHO) "dtg/build_sdt: Generating the system device tree with zocl enabled" rm -rf sdt_out - xsct -eval "source src/xsct_utils.tcl; run_sdtgen -version 2025.1 -xsa $(XSA_FILE) -sdt_dt_zocl 1" + xsct -eval "source src/xsct_utils.tcl; run_sdtgen -version 2025.2 -xsa $(XSA_FILE) -sdt_dt_zocl 1" lop_procs: $(ECHO) "dtg/lop_procs: Extract the procs from SDT using Lopper" diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/linux/petalinux/Makefile b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/linux/petalinux/Makefile index f40321ba93..417dda8fc9 100644 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/linux/petalinux/Makefile +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/linux/petalinux/Makefile @@ -11,9 +11,9 @@ PLATFORM_CUSTOM ?= ${BOARD_NAME}_thin LINUX_MACHINE ?= ${BOARD_NAME}-versal LINUX_ETH_CONFIG ?= DHCP LINUX_BUILD_SOURCES ?= network -LINUX_LOCAL_DOWNLOADS_DIR ?= /tmp/${USER}/2025.1/${BOARD_NAME}/plnx-workspace/downloads -LINUX_LOCAL_SSTATE_DIR ?= /tmp/${USER}/2025.1/${BOARD_NAME}/plnx-workspace/sstate_aarch64_2024.1/aarch64 -LINUX_TMP_DIR ?= /tmp/${USER}/2025.1/${BOARD_NAME}/petalinux +LINUX_LOCAL_DOWNLOADS_DIR ?= /tmp/${USER}/2025.2/${BOARD_NAME}/plnx-workspace/downloads +LINUX_LOCAL_SSTATE_DIR ?= /tmp/${USER}/2025.2/${BOARD_NAME}/plnx-workspace/sstate_aarch64_2025.2/aarch64 +LINUX_TMP_DIR ?= /tmp/${USER}/2025.2/${BOARD_NAME}/petalinux CURR_DIR := $(shell pwd) PROJ_DIR := ${CURR_DIR}/../${LINUX_MACHINE} diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/ps_apps/README.md b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/ps_apps/README.md index ed6e8a4b33..b92a08a5b1 100644 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/ps_apps/README.md +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/ps_apps/README.md @@ -18,24 +18,27 @@ The host applications are organized per domain. Currently only Linux user space A similar structure can be setup for bare metal applications, with the `exe` folder being replaced by an `elf` folder. To compile and build linux executables, call Makefile from top folder: + ``` make ps_apps ``` ## Description of generated Vitis platform component folders + Each application is selfcontained per folder to make it easy to transfer and reused in other designs. -| Folder | Type | Description -| ---------------------------------|--------|------------------------------------------------- -| [linux/Makefile](./linux/Makefile) | Source | Generalized recipe to find and compile all application folders. -| [linux/exe](./linux/exe) | Generated | Destination of all application executables. This folder is searched by packager to automatically add them to the sd card. -| [linux/aie_dly_test/](./linux/aie_dly_test/) | Workspace | Test application for a small AI Engine + PL system. -| [linux/aie_dly_test/src](./linux/aie_dly_test/src) | Source | Application source code folder. -| [linux/aie_dly_test/Makefile](./linux/aie_dly_test/Makefile) | Source | Application source code. +| Folder | Type | Description | +|----------------------------------------------|------------|--------------------------------------------------------------------------------------------------------------| +| [linux/Makefile](./linux/Makefile) | Source | Generalized recipe to find and compile all application folders. | +| [linux/exe](./linux/exe) | Generated | Destination of all application executables. This folder is searched by the packager to automatically add them to the SD card. | +| [linux/aie_dly_test/](./linux/aie_dly_test/) | Workspace | Test application for a small AI Engine + PL system. | +| [linux/aie_dly_test/src](./linux/aie_dly_test/src) | Source | Application source code folder. | +| [linux/aie_dly_test/Makefile](./linux/aie_dly_test/Makefile) | Source | Application makefile. | ## Next step + - [9. Package the design to SD card](../vitis/Package.md) diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/Makefile b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/Makefile index 8fcf44eb9e..67ad102d3b 100644 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/Makefile +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/Makefile @@ -97,7 +97,7 @@ vitis_ip: $(MAKE) all -C ${IP_DIR} platform: - vitis -s vitis_platform.py |& tee vitis_pfm.log + vitis -s vitis_platform.py 2>&1 | tee vitis_pfm.log link: ${BUILD_DIR} ${BUILD_DIR}/${XSA} @@ -113,7 +113,7 @@ ${BUILD_DIR}/${VMA}: ${XO} ${VSSFILE} ${SYSTEM_CFG} $(addprefix ../, ${VSSFILE}) \ --export_archive \ --output ${VMA} \ - |& tee vpp_link.log + 2>&1 | tee vpp_link.log ${BUILD_DIR}/${XSA}: ${XO} ${VSSFILE} ${SYSTEM_CFG} cd ${BUILD_DIR} && \ @@ -125,7 +125,7 @@ ${BUILD_DIR}/${XSA}: ${XO} ${VSSFILE} ${SYSTEM_CFG} $(addprefix ../, ${VSSFILE}) \ --export_archive \ --output ${VMA} \ - |& tee vpp_link.log + 2>&1 | tee vpp_link.log package_linux: ${SD_CARD_LINUX} @@ -138,7 +138,7 @@ ${BUILD_DIR}/${XCLBIN}: ${LIBADF} --package.defer_aie_run \ $(addprefix ../, ${LIBADF}) \ -o ${XCLBIN} - |& tee vpp_pack_xclbin.log + 2>&1 | tee vpp_pack_xclbin.log # make update_ila #${SD_CARD_LINUX}: ${BUILD_DIR}/${XSA} ${PS_LINUX_EXE} ${GRAPH_O} ${LINUX_KERNEL} ${LINUX_ROOTFS} ${LINUX_DTB} @@ -161,7 +161,7 @@ ${SD_CARD_LINUX}: ${LIBADF} ${PS_LINUX_EXE} ${LINUX_KERNEL} ${LINUX_ROOTFS} ${PF $(addprefix --package.sd_file=../, ${PS_LINUX_EXE}) \ $(addprefix --package.sd_file=../, ${LINUX_BOOTSCR}) \ -o ${XCLBIN} \ - |& tee vpp_pack_sd.log + 2>&1 | tee vpp_pack_sd.log echo ${PLATFORM_CUSTOM} > ${SD_CARD_LINUX}/sd_card/platform_desc.txt # make update_ila diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/Package.md b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/Package.md index 566889ecdb..501f21e9e5 100644 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/Package.md +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/Package.md @@ -12,16 +12,48 @@ -# Package the desing and generate a SD card +# Package the design and generate a SD card for Linux The packaging step prepares and assembles boot artifacts, linux image and file system, and host applications and deploy them to a SD card image or folder. -For convenience with Windows OS, the formatting is set to fat32 so the SD card can be accessed natively by Windows. +For convenience with Windows OS, the formatting is set to FAT32 so the SD card can be accessed natively by Windows. To package the design, call Makefile from top folder: ``` make package ``` +The command will change directory to `build_hw` to keep all logs and outputs in a separate folder. + +**Note** The Linux image, file system and boot artifacts is picked primarily from the generated outputs from Petalinux or Yocto. This is to allow for user to setup reusable linux artifacts to speed up build time. + + +Example of the command: +``` +cd build_hw && \ +v++ --package --debug --save-temps \ + --target hw \ + --platform .././build_pfm/pfm/export/pfm/pfm.xpfm \ + --package.defer_aie_run \ + --package.out_dir ../../package_linux_hw \ + --package.boot_mode=sd \ + --package.no_image \ + --package.image_format=fat32 \ + --package.sd_file=../../linux/vck190-versal/images/linux/Image \ + --package.rootfs=../../linux/vck190-versal/images/linux/rootfs.cpio.gz.u-boot \ + --package.dtb=.././build_pfm/pfm/export/pfm/sw/boot/system.dtb \ + --package.bl31_elf=../../linux/vck190-versal/images/linux/bl31.elf \ + --package.uboot=../../linux/vck190-versal/images/linux/u-boot.elf \ + ../../vss/./ip/aie/datamove_app_libadf.a \ + --package.sd_file=../../ps_apps/linux/exe/aie_dly_test.exe \ + --package.sd_file=../../linux/vck190-versal/images/linux/boot.scr \ + -o my.xclbin \ + 2>&1 | tee vpp_pack_sd.log +echo vck190_thin > ../package_linux_hw/sd_card/platform_desc.txt +``` + +The package command outputs is directed to `package_linux_hw` in the top folder with the FAT32 formatted SD cards files in `package_linux_hw/sd_card`. + +**Note** The [Makefile](./Makefile) identifies host `*.exe` files from `../ps_apps/linux/exe` folder and automatically adds them to the `v++ --package` arguments. ## Next step diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/README.md b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/README.md index e92be9aabf..653c01a1b1 100644 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/README.md +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/README.md @@ -17,36 +17,24 @@ Vitis serves both hardware and software activities. To guide through the design flow, the detailed description use link to previous and next step. #### Overview of Vitis activities -1. Hardware integration +1. Hardware integration 1. [Compile additional Vitis kernels](./ip/README.md). 2. Integrating [VSS component](../vss/README.md) and Vitis kernels to a [custom extensible platform](../vivado/README.md) and export to a VMA. -2. Software / Embedded +2. [Prepate Software / Embedded platform](./Platform.md) 1. Generate board support package / drivers. 2. Apply device tree overlays. 3. Packaging to delivery container - 1. Collect binaries, boot artifacts, OS and host applications and deploy on a SD card. + 1. [Vitis Packaging](./Packaging.md) collect binaries, boot artifacts, OS and host applications and deploy on a SD card. -## Hardware integration - -This step assumes the following pre-requisite steps is completed: -Create VSS component | cint16 - +## 1. Hardware integration ### Adding VSS Component and Vitis Components to an extensible platform This part of the tutorial demonstrates adding a Vitis Subsystem component and additional Vitis PL components to demonstrate integrating both VSS and Vitis kernels onto an extensible platform. - - -## Vitis design description -The design reuses blocks from previous tutorials to make it easier to compare the mechanics for adding and integrating them to a small system. - - -The example will go through the steps of creating a small AMD Versal™ VCK190 System Example Design consisting of: - - [3. Importing and integrating DSP Subsystem to Vitis Unified IDE](./README_INTEGRATE.md) - [Add RTL Subtractor and HLS mm2s and s2mm Components](./ip/README.md) - - Declare connections between VSS Component, Vitis compnents and extensible platform. - [Inspect the config file for the example](../vss/src/vss_conn.cfg) + - Declare connections between VSS Component, Vitis compnents and extensible platform. + [Inspect the config file for the example](./src/system.cfg) - Build System Component and export Vitis Managed Archive (VMA) The VMA archive is generated with v++ using: @@ -62,11 +50,24 @@ From top folder, run: make vitis_ip vma_export ``` +After the VMA export, the design is synthesized and implemented in Vivado: +[Import VMA and finalize the design in Vivado](../vivado/Finalize_Vivado.md) + + +## 2. Prepare Software / Embedded platform +After building the fixed Vivado platform and prepared [Linux build tools (sysroot), Image and filesystem](../linux/README.md), the device tree overlay is applied and BSP/drivers is generated. See [creating Vitis Platform component](./Platform.md) + +## 3. Package to delivery container +Last step in the flow is to package the design to a suitable container. This tutorial use [Vitis Package](./Packaging.md) to create a SD card folder. ## Navigation helper - - [Next step - Import VMA and finalize the design in Vivado](../vivado/Finalize_Vivado.md) - - [Previous step - Develop Custom Vivado Extensible Platform](../vivado/README.md) - [Return to top](../README.md) + - [Vitis Subsystem](../vss/README.md) + - [Vivado hw platform](../vivado/README.md) + - [Prepare Linux](../linux/README.md) + - [Host applications](../ps_apps/README.md) + - [Vitis sw platform](./Platform.md) + - [Vitis Package](./Packaging.md) diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/ip/README.md b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/ip/README.md index 7ce162fddf..0b8239f9d6 100644 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/ip/README.md +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/ip/README.md @@ -21,18 +21,19 @@ The xo_hw folder is excluded from the search, as this is where RTL and HLS kerne The AIE build is treated separately and will result in a libadf.a file located in aie folder. ## Adding or removing HLS and RTL components + A component can be removed from the VSS region by deleting the folder and subfolders, and ensure the corresponding .xo file is removed from [xo_hw](./xo_hw) folder To add a new component, it's easiest to copy one of the below examples and add the corresponding sources files and modify the Makefile and config files accordingly. **Note** Make sure to update the Vitis link configuration according to the changes: [../src/system.cfg](../src/system.cfg) Components used for the Vitis region: -| Component | Type | Description -| ---------------------------------|--------|------------------------------------------------- -| [subtractor](./subtractor/README.md)| RTL | A subtractor acting as endpoint of the counter values passed through AIE datamover kernels. Only two channels are uses via AIE, the others are connected directly to the counter. -| [mm2s](./mm2s/README.md)| HLS | Converts data from DDR memory buffer to the FIR DSP via the AXI Stream data duplicator. The PS application can be used to create the stimuli buffer. -| [s2mm](./s2mm/README.md) | HLS | Converts the AXI Stream output from the vadd_s to DDR memory. Allows the PS application to analyze the output. +| Component | Type | Description | +|-----------------------------------------------------|------|------------------------------------------------------------------------------------------------------------------------------------------------------------| +| [subtractor](./subtractor/README.md) | RTL | A subtractor acting as the endpoint for counter values passed through AIE datamover kernels. Only two channels are used via AIE; the others are connected directly to the counter. | +| [mm2s](./mm2s/README.md) | HLS | Converts data from a DDR memory buffer to the FIR DSP via the AXI Stream data duplicator. The PS application can be used to create the stimulus buffer. | +| [s2mm](./s2mm/README.md) | HLS | Converts the AXI Stream output from the `vadd_s` to DDR memory, enabling the PS application to analyze the output. | [Continue with Vitis integration](../README.md) diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/ip/mm2s/src/mm2s.cpp b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/ip/mm2s/src/mm2s.cpp index a7f5599914..71f3ae3887 100755 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/ip/mm2s/src/mm2s.cpp +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/ip/mm2s/src/mm2s.cpp @@ -8,7 +8,7 @@ #include #include -#define WORD_SIZE 16 +#define WORD_SIZE 32 void mm2s(ap_int* mem, hls::stream, 0, 0, 0>>& s, int size) { #pragma HLS INTERFACE m_axi port=mem offset=slave bundle=gmem diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/ip/s2mm/src/s2mm.cpp b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/ip/s2mm/src/s2mm.cpp index 3d71c87d62..896c9ede67 100755 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/ip/s2mm/src/s2mm.cpp +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/ip/s2mm/src/s2mm.cpp @@ -8,7 +8,7 @@ #include #include -#define WORD_SIZE 16 +#define WORD_SIZE 32 void s2mm(ap_int* mem, hls::stream, 0, 0, 0>> &s, int size) { #pragma HLS INTERFACE m_axi port=mem offset=slave bundle=gmem diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/ip/subtractor/README.md b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/ip/subtractor/README.md index b78a603fc6..7a9eb917e2 100644 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/ip/subtractor/README.md +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/ip/subtractor/README.md @@ -12,8 +12,10 @@ # RTL Subtractor + The subtractor has 5 AXI Stream inputs, each with 64-bit data, and a AXI4-Lite bus interface. -It has 4 subtractors, where the first AXI Stream input is the reference common to all subtractions, and the remaining 4 are individual per subtraction.
+ +It has 4 subtractors, where the first AXI Stream input is the reference common to all subtractions, and the remaining 4 are individual per subtraction. The subtraction use DSP element and is designed to run up to 625 MHz and performs subtraction using the real part from one of the two cint16 samples from the AXI stream. @@ -22,21 +24,24 @@ To reduce timing closure issues, the AXI4-Lite parts are clocked separately usin A simple hold circuit is used before the results are collected by the AXI4-Lite registers. -### Files used for this IP -| File | Type | Description -| ---------------------------------|--------|------------------------------------------------- -| [subtractor.v](./src/subtractor.v)| RTL kernel | Four subtractors with results in AXI4-Lite status register. -| [subtractor_S00_AXI.v](./src/subtractor_S00_AXI.v)| RTL kernel | AXI4-Lite slave using modified code template. -| [my_diff.v](./src/my_diff.v)| RTL kernel | Code to infer a subtractor using DSP58/48. -| [pack_kernel.tcl](./pack_kernel.tcl)| Project tcl | Setup a simple Vivado IP project to manage compilation to packaged `.xo` file. -| [subtractor.xdc](./counter.xdc)| Constraints file | Placeholder file for constraints. Currently no constraints used. +## Files used for this IP + +| File | Type | Description | +|--------------------------------------------------------|-------------------|------------------------------------------------------------------------------------------------------------------| +| [subtractor.v](./src/subtractor.v) | RTL kernel | Implements four subtractors with results stored in an AXI4-Lite status register. | +| [subtractor_S00_AXI.v](./src/subtractor_S00_AXI.v) | RTL kernel | AXI4-Lite slave using a modified code template. | +| [my_diff.v](./src/my_diff.v) | RTL kernel | Code to infer a subtractor using DSP58/DSP48 primitives. | +| [pack_kernel.tcl](./pack_kernel.tcl) | Project Tcl script| Sets up a simple Vivado IP project to compile and package the design as a `.xo` file. | +| [subtractor.xdc](./subtractor.xdc) | Constraints file | Placeholder file for constraints. Currently, no constraints are used. | ### Simulating and checking the RTL IP -The project script will run synthesis and use `report_methodology` as means to check for trivial user errors. It's not required to run synthesis to generate the `xo` for Vitis.
-For real designs, the synthesis step should be replaced with traditional RTL verification.
-**Note** It's encouraged to setup either traditional RTL verification or run hardware emulation to verify this block. +The project script will run synthesis and use `report_methodology` as means to check for trivial user errors. It's not required to run synthesis to generate the `xo` for Vitis. + +For real designs, the synthesis step should be replaced with traditional RTL verification. + +> **Note** It's encouraged to setup either traditional RTL verification or run hardware emulation to verify this block. [Return to Vitis IP](../README.md) diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/ip/subtractor/src/subtractor.v b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/ip/subtractor/src/subtractor.v index beab0f8140..5e809d04e7 100644 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/ip/subtractor/src/subtractor.v +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vitis/ip/subtractor/src/subtractor.v @@ -125,7 +125,9 @@ module subtractor wire [DWIDTH/4-1:0] diff3_q; reg tvalid; reg tlast; - reg my_smpl; + reg s00_axi_aclk_d; + reg s00_axi_aclk_d2; + wire s00_axi_aclk_posedge; // Tie off tready assign s00_axis_tready = true_c; @@ -219,14 +221,19 @@ module subtractor begin if (!aresetn) begin - my_smpl <= false_c; + s00_axi_aclk_d <= false_c; + s00_axi_aclk_d2 <= false_c; end else begin - my_smpl <= !my_smpl; + s00_axi_aclk_d <= s00_axi_aclk; + s00_axi_aclk_d2 <= s00_axi_aclk_d; end end + assign s00_axi_aclk_posedge = s00_axi_aclk_d & !s00_axi_aclk_d2; + + // Simple hold circuit always @(posedge aclk) begin @@ -241,7 +248,7 @@ module subtractor buf3_i <= 0; buf3_q <= 0; end - else if (my_smpl) begin + else if (s00_axi_aclk_posedge) begin buf0_i <= diff0_i; buf0_q <= diff0_q; buf1_i <= diff1_i; diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vivado/Vivado.md b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vivado/Vivado.md index 5c06fcb1ad..0e107a4eee 100644 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vivado/Vivado.md +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vivado/Vivado.md @@ -24,8 +24,10 @@ Focus areas for this part of the example is to ## Background notes on Extensible Platforms + In Vivado there are several Configurable example design that can be used as starting point and modified for custom purpose. The common features they have to make them Extensible by Vitis is the Block Design contains: + - CIPS - AI Engine - NoC (Typically split in logical instance for AXI and DDR Memory Controllers) @@ -38,28 +40,33 @@ The common features they have to make them Extensible by Vitis is the Block Desi ![](../documentation/readme_files/base_platform_bd.png) ### Refining the example Extensible Platform and adding RTL modules + Observing the example platform, the associated resets for each clock was only paritally added. Vitis is capable of inferring missing clocks and resets, but in this case we ensure clocks and reset are properly setup before exporting the platform to Vitis. After this, two RTL modules are imported and the platform properties setup. When Vitis extends a design, it will require access to AIE, NoC, Clock/Resets and AXI SmartConnect/Interrupt Controller. ## Instructions + To give more time to interact with analyzing the Vivado Platform, the provided scripts will generate the Vivado, add RTL Modules, and setup the platform properties. ### 1 Build the Vivado Platform + If this was done with the prebuild instruction, skip to Inspecting the Vivado Platform design. The user is encouraged to modify/change/replace parts after first running through these steps once. ``` make vivado_platform ``` + #### File structure related to the Vivado project [vivado](.) Directory/file structure: -| Directory/file | Description -| ---------------------------------------|------------------------------------------------- -| [Makefile](Makefile) | The vivado platform Makefile -| [vck190/xsa_platform_classic.tcl](vck190/xsa_platform_classic.tcl) | Vivado project, setup design and export XSA for Vitis -| [vck190/dr.bd.tcl](vck190/dr.bd.tcl) | Script to prepare flat block design for VCK190 -| [vck190/finalize_design.tcl](vck190/finalize_design.tcl) | Script that converts the flat design to BDC and adds RTL Modules + +| Directory/File | Description | +|------------------------------------------------------------|----------------------------------------------------------------------------------------------| +| [Makefile](Makefile) | Vivado platform Makefile. | +| [vck190/xsa_platform_classic.tcl](vck190/xsa_platform_classic.tcl) | Vivado project script to set up the design and export the XSA for Vitis. | +| [vck190/dr.bd.tcl](vck190/dr.bd.tcl) | Script to prepare a flat block design for the VCK190 platform. | +| [vck190/finalize_design.tcl](vck190/finalize_design.tcl) | Script that converts the flat design to a BDC and adds RTL modules. | When running the build, a Vivado project will be created under `vivado/build` folder. @@ -69,12 +76,15 @@ make vivado_platform Running the scripts will build the Vivado design in the following steps. ### Create a Vivado Project and configure device and board parts + See details in [xsa_platform_classic.tcl (Line: 26-42)](vck190/xsa_platform_classic.tcl#L26) #### (Optional) Add source code for RTL blocks + Before connecting RTL modules, the source file should be added to the Vivado project. ### 3. Create a flat block design + Calling `dr.bd.tcl` and add mandatory IPI blocks and optional instances and RTL modules. [`xsa_platform_classic.tcl` (line 62)](vck190/xsa_platform_classic.tcl#L62) - It's recommended to start with a configurable example design and modify it for custom requirements. This helps making a bootable design already from start. - Another benefit of editing in Vivado IPI, is you can check the design with `Validate` before saving. @@ -88,48 +98,64 @@ Custom platform example used for VCK190. write_bd_tcl -exclude_pfm new_dr.bd.tcl ``` -#### 3.1 Setup Platform Properties [(Line: 843-862)](vck190/dr.bd.tcl#L843). +#### 3.1 Setup Platform Properties [(Line: 843-862)](vck190/dr.bd.tcl#L843) + ##### Setup of AXI Ports + This figure show how the platform ports are listed in Vivado IPI blockdesign. - ![](./doc_files/pfm_axi.png) +![](./doc_files/pfm_axi.png) + - ##### Setup of AXI Stream Ports + ***This tutorial currently does not use any RTL in the extensible platform.***
***The figure below show how it would be setup if the RTL counter and subtractor is put in the extensible BD.***
**Important** Note the Corresponding names for **SPTAG. These will be used when connecting the RTL with Vitis Subsystem!** ![](./doc_files/pfm_axis.png) -##### Setup of Clocks. +##### Setup of Clocks + **Note** the default is set to 500 MHz clock domain. ![](./doc_files/pfm_clock.png) -##### Setup of Interrupt Controller. +##### Setup of Interrupt Controller + **Note** Don't forget this or you will get a critical warning when validating the design. ![](./doc_files/pfm_intc.png) -##### Setup of Platform Name. +##### Setup of Platform Name + **Important** The choice here will be reflected when you import the XSA to Vitis. ![](./doc_files/pfm_name.png) -### 4. Build Vivado Platform for use with Vitis and Model Composer. +### 4. Build Vivado Platform for use with Vitis and Model Composer + Continuing `xsa_platform_classic.tcl` (Line: 65-) -#### 4.1. Create and set a wrapper for top BD. [(Line: 65-69)](vck190/xsa_platform_classic.tcl#L65). +#### 4.1. Create and set a wrapper for top BD. [(Line: 65-69)](vck190/xsa_platform_classic.tcl#L65) + **Note** It's important that the correct RTL Top is selected when writing the platform. -#### 4.2. Set project properties. [(Line: 95-104)](vck190/xsa_platform_classic.tcl#L95). + +#### 4.2. Set project properties. [(Line: 95-104)](vck190/xsa_platform_classic.tcl#L95) + Sets platform to extensible, default output and design intent. -#### 4.3. Wrap up project and generate target [(Line: 116-150)](vck190/xsa_platform_classic.tcl#L116). + +#### 4.3. Wrap up project and generate target [(Line: 116-150)](vck190/xsa_platform_classic.tcl#L116) + Ensure all files are added, addresses assigned and generate support blocks for the design. -#### 4.5. Write/Export XSA and validate results. [(Line: 155-157)](vck190/xsa_platform_classic.tcl#L155). + +#### 4.5. Write/Export XSA and validate results. [(Line: 155-157)](vck190/xsa_platform_classic.tcl#L155) ### 5. Inspect the Vivado Platform -Open the generated project in Vivado. + +Open the generated project in Vivado. + ``` cd vivado vivado build/vck190_thin_vivado/vck190_thin.xpr ``` + **Note** Launch Vivado in the vivado folder as all instructions later on is relative to this location. Open the `vck190_thin` (top level). @@ -138,9 +164,10 @@ Check the Platform Setup on top BD with the detailed instructions. Once done proceed with next part of the tutorial. ## Navigation helper - - [Next step - Import and integrate VSS and Vitis blocks to extensible platform](../vitis/README.md) - - [Previous step - Create a Vitis Subsystem component](../vss/README.md) - - [Return to top](../README.md) + +- [Next step - Import and integrate VSS and Vitis blocks to extensible platform](../vitis/README.md) +- [Previous step - Create a Vitis Subsystem component](../vss/README.md) +- [Return to top](../README.md) diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vivado/vck190/dr.bd.tcl b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vivado/vck190/dr.bd.tcl index 7d89b00cfb..6dcfef9f04 100644 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vivado/vck190/dr.bd.tcl +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vivado/vck190/dr.bd.tcl @@ -20,7 +20,7 @@ set script_folder [_tcl::get_script_folder] ################################################################ # Check if script is running in correct Vivado version. ################################################################ -set scripts_vivado_version 2025.1 +set scripts_vivado_version 2025.2 set current_vivado_version [version -short] if { [string first $scripts_vivado_version $current_vivado_version] == -1 } { diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vivado/vek280/dr.bd.tcl b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vivado/vek280/dr.bd.tcl index 0c6c344fcb..464c00f5b1 100644 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vivado/vek280/dr.bd.tcl +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vivado/vek280/dr.bd.tcl @@ -20,7 +20,7 @@ set script_folder [_tcl::get_script_folder] ################################################################ # Check if script is running in correct Vivado version. ################################################################ -set scripts_vivado_version 2024.1 +set scripts_vivado_version 2025.2 set current_vivado_version [version -short] if { [string first $scripts_vivado_version $current_vivado_version] == -1 } { diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/Makefile b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/Makefile index 9a968f8287..d0b5389bf8 100644 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/Makefile +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/Makefile @@ -49,7 +49,7 @@ ${BUILD_DIR}/${VSS}: ${VSS_CFG} $(addprefix ../, ${XO}) \ $(addprefix ../, ${LIBADF}) \ --out_dir ${VSS} \ - |& tee vss_link.log + 2>&1 | tee vss_link.log crts: $(MAKE) crts -C cosim AIE_WORK=$(AIE_WORK) diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/README.md b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/README.md index 3ffe82bc2c..63445b8591 100644 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/README.md +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/README.md @@ -19,14 +19,16 @@ To test and verify the AI Engine and HLS components individually and in a small Both Matlab and Python offers rich libraries and toolboxes for creating test vectors, reference modelling and visualizing the results. ## VSS design description + The design reuses blocks from previous tutorials to make it easier to compare the mechanics for adding and integrating them to a small system. Components used for the VSS region: -| Component | Type | Description -| ---------------------------------|--------|------------------------------------------------- -| counter | RTL | Freerunning counter to generate input stimuli for datamovers -| [axis1to2](./ip/axis1to2/README.md)| HLS | Duplicating one axi stream to two ports to copy the inputs to each AIE FIR filter. -| [vadd_s](./ip/vadd_s/README.md) | HLS | Vector adder taking complex int16 stream inputs. Used to demo Python VFS -| [aie](./ip/aie/README.md) | AIE | Top graph consisting of a subgraph with datamover kernels and a subgraph with two FIR filter kernels + +| Component | Type | Description | +|---------------------------------------------------|------|------------------------------------------------------------------------------------------------------------------------| +| counter | RTL | Free-running counter to generate input stimuli for datamovers. | +| [axis1to2](./ip/axis1to2/README.md) | HLS | Duplicates one AXI stream into two ports to copy inputs to each AIE FIR filter. | +| [vadd_s](./ip/vadd_s/README.md) | HLS | Vector adder taking complex int16 stream inputs. Used to demonstrate Python VFS. | +| [aie](./ip/aie/README.md) | AIE | Top-level graph consisting of a subgraph with data mover kernels and a subgraph with two FIR filter kernels. | The AIE datamover subgraph is connected to the counter and leaves placeholder interfaces so the subtractor from Vitis domain can be connected later. The AIE filter subgraph have two instances of a 16 tap FIR filter kernel. By feeding same data to both FIR filters and sum the outputs using vadd_s, @@ -54,23 +56,28 @@ Steps in this part: - [1.6 Verify the VSS using cosimulation in Xsim](./cosim/README.md) ## Integrating the subsystem and generate VSS archive + To integrate the various PL and AIE components, a configuration file is used to declare what components to use and which interfaces to connect. The syntax is similar to how Vitis connects components to an extensible platform, except here we declare what to be added to a vss archive. Specifying the VSS component archive require this syntax: + ``` vss=amd.com:::: ``` + Description of the syntax -| Item | example | Description -| ---------------------------------|--------|------------------------------------------------- -| vss_library_name | my_vss_lib | Identifier name to associate the VSS to a library -| vss_component_name | vss_top | Will be used as VSS archive name and concatenated with instance names to provide unique name when integrating VSS component to an extensible platform -| version_number | 1.0 | To keep track of library/component version -| list_of_instance | counter_0,ai_engine_0 | Comma separated list of instance names. The names need to match kernel names declared with "nk" in config file. **Note** the ai_engine_0 instance name need to match default instance name in Vivado HW platform + +| Item | Example | Description | +|----------------------|--------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| +| `vss_library_name` | `my_vss_lib` | Identifier name to associate the VSS with a library. | +| `vss_component_name` | `vss_top` | Used as the VSS archive name and concatenated with instance names to provide a unique name when integrating the VSS component into an extensible platform. | +| `version_number` | `1.0` | Version number to keep track of the library/component version. | +| `list_of_instance` | `counter_0`, `ai_engine_0` | Comma-separated list of instance names. The names must match kernel names declared with `nk` in the config file. **Note:** The `ai_engine_0` instance name must match the default instance name in the Vivado HW platform. | [Inspect the config file for the example run](./src/vss_conn.cfg) The VSS archive is generated with v++ using: + ``` v++ --link --mode vss --save-temps --part --config ./src/vss_conn.cfg --out_dir ``` @@ -78,6 +85,7 @@ v++ --link --mode vss --save-temps --part --config ./src/vss_conn.cf Makefiles are provided to build everything from the lab top folder. It will automatically compile all required RTL, AIE and HLS components as required by VSS during linking. From top folder, run: + ``` make vss ``` @@ -91,13 +99,13 @@ Once confident with the subsystem design, the next step is to create a vivado pl ## Navigation helper - - [Next step - Develop Custom Vivado Extensible Platform](../vivado/Vivado.md) - - [Creating AIE graphs and kernels](../ip/aie/README.md) - - [Creating RTL counter](../ip/counter/README.md) - - [Creating HLS AXI Stream splitter](../ip/axis1to2/README.md) - - [Creating HLS vector adder](../ip/vadd_s/README.md) - - [Simulating the VSS Component](../cosim/README.md) - - [Return to top](../../../README.md) +- [Next step - Develop Custom Vivado Extensible Platform](../vivado/Vivado.md) +- [Creating AIE graphs and kernels](../ip/aie/README.md) +- [Creating RTL counter](../ip/counter/README.md) +- [Creating HLS AXI Stream splitter](../ip/axis1to2/README.md) +- [Creating HLS vector adder](../ip/vadd_s/README.md) +- [Simulating the VSS Component](../cosim/README.md) +- [Return to top](../../../README.md)

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diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/Makefile b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/Makefile index 579c7d4c22..b0a5a89255 100644 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/Makefile +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/Makefile @@ -24,7 +24,6 @@ SRC_DIR := src # Paths needed by xsim # ========================================================= export AIE_WORK_DIR :=$(AIE_WORK) -export ENABLE_AIE_DBG_TRACE=true export AIESIM_OPTIONS=$(shell pwd)/$(SRC_DIR)/aiesim.txt #export LD_LIBRARY_PATH :=$(XILINX_VITIS)/aietools/lib/lnx64.o:$(LD_LIBRARY_PATH) diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/README.md b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/README.md index a8d7707bfe..6e0fa28041 100644 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/README.md +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/README.md @@ -30,6 +30,10 @@ With the simulation project, we can control and run the design under test and us In addition to the simulation testbench, this example adds basic AXI Stream driver and monitor to exercise data through the design under test. +For the datamover path, in order to verify the subtraction IP outside the VSS, a model is added in the testbench. +To keep the testbench simple, the AXI4-Lite registers is removed from the subtractor IP model, keeping the my_diff instances for subtraction and buffer at the results. +This allow a quick way to check what to expect on hardware. + Advanced testbench design and automatic checkers is up to the user to adapt to be used with this feature. @@ -41,14 +45,19 @@ Advanced testbench design and automatic checkers is up to the user to adapt to b | [testbench.sv](./src/testbench.sv) | RTL | Testbench | [driver_axis.sv](./src/driver_axis.sv) | RTL | Simple driver for AXI Stream testbench stimuli, creates an impulse respone | [monitor_axis.sv](./src/monitor_axis.sv) | RTL | Simple monitor terminating AXI Stream traffic +| [my_diff.v](./src/my_diff.v) | RTL | Code to infer DSP58 subtraction borrowed from [vitis/ip/subtractor](../../vitis/ip/subtractor/src/my_diff.v) +| [my_sub.v](./src/my_sub.v) | RTL | Model to mimic the subtractor from [vitis/ip/subtractor](../../vitis/ip/subtractor) | [tb_top_behav.wcfg](./src/tb_top_behav.wcfg) | Config | Xsim waveform configuration -| [aiesim.txt](./src/aiesim.txt) | Config | Enable VCD dump from connected AIE Simulator. +| [datamovers.wcfg](./src/datamovers.wcfg) | Config | Xsim waveform configuration +| [datamovers2.wcfg](./src/datamovers2.wcfg) | Config | Xsim waveform configuration +| [subtractors.wcfg](./src/subtractors.wcfg) | Config | Xsim waveform configuration +| [fir_filters.wcfg](./src/fir_filters.wcfg) | Config | Xsim waveform configuration +| [aiesim.txt](./src/aiesim.txt) | Config | Enable VCD dump from connected AIE Simulator. **Note:** To let the RTL simulator testbench connect to the AIE Sim and VCD dump, these additional environment variables are set by the makefile: ``` export AIE_WORK_DIR = -export ENABLE_AIE_DBG_TRACE=true export AIESIM_OPTIONS= ``` diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/src/cosim_proj.tcl b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/src/cosim_proj.tcl index 3b08bbd857..2db341883c 100644 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/src/cosim_proj.tcl +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/src/cosim_proj.tcl @@ -50,6 +50,8 @@ update_compile_order -fileset sources_1 #break add_files -fileset sim_1 -norecurse ${script_folder}/driver_axis.sv add_files -fileset sim_1 -norecurse ${script_folder}/monitor_axis.sv +add_files -fileset sim_1 -norecurse ${script_folder}/my_diff.v +add_files -fileset sim_1 -norecurse ${script_folder}/my_sub.v add_files -fileset sim_1 -norecurse ${script_folder}/testbench.sv set_property top tb_top [get_filesets sim_1] update_compile_order -fileset sim_1 @@ -60,7 +62,6 @@ update_compile_order -fileset sim_1 #set_property generate_scripts_only 1 [current_fileset -simset] set_property -name {xsim.simulate.runtime} -value {0us} -objects [get_filesets sim_1] set_property -name {xsim.simulate.xsim.more_options} -value {-testplusarg VERBOSITY_FATAL_TO_WARN} -objects [get_filesets sim_1] -set_property -name {xsim.elaborate.xelab.more_options} -value {-debug sc} -objects [get_filesets sim_1] ## =================================================================================== ## Launch simulation @@ -69,6 +70,7 @@ launch_simulation open_wave_config ${script_folder}/tb_top_behav.wcfg open_wave_config ${script_folder}/datamovers.wcfg open_wave_config ${script_folder}/datamovers2.wcfg +open_wave_config ${script_folder}/subtractor.wcfg open_wave_config ${script_folder}/fir_filters.wcfg log_wave -r * run 5us diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/src/my_diff.v b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/src/my_diff.v new file mode 100644 index 0000000000..4f841d72d2 --- /dev/null +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/src/my_diff.v @@ -0,0 +1,51 @@ +// +// Copyright (C) 2021-2022, Xilinx, Inc. All rights reserved. +// Copyright (C) 2022-2025, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: X11 +// +// Author Derek Hagen + +`timescale 1 ps / 1 ps + +// ONLY TO BE USED FOR STANDALONE RTL DEBUG +// `default_nettype none + +(* use_dsp = "yes" *) module my_diff + # ( + parameter integer SIZEIN = 16 + ) + ( + input wire resetn, + input wire clk, + input wire signed [SIZEIN-1:0] a, + input wire signed [SIZEIN-1:0] b, + output wire signed [SIZEIN-1:0] res + ); + + localparam [SIZEIN:0] one_mul = 1; + reg signed [SIZEIN-1:0] a_reg; + reg signed [SIZEIN-1:0] b_reg; + reg signed [SIZEIN:0] diff_reg; + reg signed [2*SIZEIN-1:0] m_reg; + reg signed [2*SIZEIN-1:0] p_reg; + + assign res = p_reg[SIZEIN-1:0]; + + always @(posedge clk) begin + if (!resetn) begin + a_reg <= 0; + b_reg <= 0; + diff_reg <= 0; + m_reg <= 0; + p_reg <= 0; + end + else begin + a_reg <= a; + b_reg <= b; + diff_reg <= a_reg - b_reg; + m_reg <= diff_reg * one_mul; + p_reg <= m_reg; + end + end + +endmodule diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/src/my_sub.v b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/src/my_sub.v new file mode 100644 index 0000000000..2ae3c15629 --- /dev/null +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/src/my_sub.v @@ -0,0 +1,229 @@ +// +// Copyright (C) 2021-2022, Xilinx, Inc. All rights reserved. +// Copyright (C) 2022-2025, Advanced Micro Devices, Inc. All rights reserved. +// SPDX-License-Identifier: X11 +// +// Author Derek Hagen + +`timescale 1 ps / 1 ps + +// ONLY TO BE USED FOR STANDALONE RTL DEBUG +// `default_nettype none + +module my_sub + # ( + parameter integer DWIDTH = 64 + ) + ( + input wire aresetn, + input wire aclk, + input wire s00_axi_aclk, + input wire s00_axi_aresetn, + // Ports of Axi Slave Bus Interface S00_AXI + //(* X_INTERFACE_INFO = "xilinx.com:interface:axis:1.0 s00_axis TREADY" *) + output wire s00_axis_tready, + //(* X_INTERFACE_INFO = "xilinx.com:interface:axis:1.0 s00_axis TDATA" *) + input wire [DWIDTH-1:0] s00_axis_tdata, + //(* X_INTERFACE_INFO = "xilinx.com:interface:axis:1.0 s00_axis TVALID" *) + input wire s00_axis_tvalid, + //(* X_INTERFACE_INFO = "xilinx.com:interface:axis:1.0 s00_axis TLAST" *) + input wire s00_axis_tlast, + //(* X_INTERFACE_INFO = "xilinx.com:interface:axis:1.0 s01_axis TREADY" *) + output wire s01_axis_tready, + //(* X_INTERFACE_INFO = "xilinx.com:interface:axis:1.0 s01_axis TDATA" *) + input wire [DWIDTH-1:0] s01_axis_tdata, + //(* X_INTERFACE_INFO = "xilinx.com:interface:axis:1.0 s01_axis TVALID" *) + input wire s01_axis_tvalid, + //(* X_INTERFACE_INFO = "xilinx.com:interface:axis:1.0 s01_axis TLAST" *) + input wire s01_axis_tlast, + //(* X_INTERFACE_INFO = "xilinx.com:interface:axis:1.0 s02_axis TREADY" *) + output wire s02_axis_tready, + //(* X_INTERFACE_INFO = "xilinx.com:interface:axis:1.0 s02_axis TDATA" *) + input wire [DWIDTH-1:0] s02_axis_tdata, + //(* X_INTERFACE_INFO = "xilinx.com:interface:axis:1.0 s02_axis TVALID" *) + input wire s02_axis_tvalid, + //(* X_INTERFACE_INFO = "xilinx.com:interface:axis:1.0 s02_axis TLAST" *) + input wire s02_axis_tlast, + //(* X_INTERFACE_INFO = "xilinx.com:interface:axis:1.0 s03_axis TREADY" *) + output wire s03_axis_tready, + //(* X_INTERFACE_INFO = "xilinx.com:interface:axis:1.0 s03_axis TDATA" *) + input wire [DWIDTH-1:0] s03_axis_tdata, + //(* X_INTERFACE_INFO = "xilinx.com:interface:axis:1.0 s03_axis TVALID" *) + input wire s03_axis_tvalid, + //(* X_INTERFACE_INFO = "xilinx.com:interface:axis:1.0 s03_axis TLAST" *) + input wire s03_axis_tlast, + //(* X_INTERFACE_INFO = "xilinx.com:interface:axis:1.0 s04_axis TREADY" *) + output wire s04_axis_tready, + //(* X_INTERFACE_INFO = "xilinx.com:interface:axis:1.0 s04_axis TDATA" *) + input wire [DWIDTH-1:0] s04_axis_tdata, + //(* X_INTERFACE_INFO = "xilinx.com:interface:axis:1.0 s04_axis TVALID" *) + input wire s04_axis_tvalid, + //(* X_INTERFACE_INFO = "xilinx.com:interface:axis:1.0 s04_axis TLAST" *) + input wire s04_axis_tlast, + output wire [DWIDTH/2-1:0] subtract_val0, + output wire [DWIDTH/2-1:0] subtract_val1, + output wire [DWIDTH/2-1:0] subtract_val2, + output wire [DWIDTH/2-1:0] subtract_val3 + ); + + localparam true_c = 1'b1; + localparam false_c = 1'b0; + + reg [DWIDTH/4-1:0] buf0_i; + reg [DWIDTH/4-1:0] buf0_q; + reg [DWIDTH/4-1:0] buf1_i; + reg [DWIDTH/4-1:0] buf1_q; + reg [DWIDTH/4-1:0] buf2_i; + reg [DWIDTH/4-1:0] buf2_q; + reg [DWIDTH/4-1:0] buf3_i; + reg [DWIDTH/4-1:0] buf3_q; + wire [DWIDTH/4-1:0] diff0_i; + wire [DWIDTH/4-1:0] diff0_q; + wire [DWIDTH/4-1:0] diff1_i; + wire [DWIDTH/4-1:0] diff1_q; + wire [DWIDTH/4-1:0] diff2_i; + wire [DWIDTH/4-1:0] diff2_q; + wire [DWIDTH/4-1:0] diff3_i; + wire [DWIDTH/4-1:0] diff3_q; + reg tvalid; + reg tlast; + reg s00_axi_aclk_d; + reg s00_axi_aclk_d2; + wire s00_axi_aclk_posedge; + + // Tie off tready + assign s00_axis_tready = true_c; + assign s01_axis_tready = true_c; + assign s02_axis_tready = true_c; + assign s03_axis_tready = true_c; + assign s04_axis_tready = true_c; + + assign subtract_val0 = {buf0_i, buf0_q}; + assign subtract_val1 = {buf1_i, buf1_q}; + assign subtract_val2 = {buf2_i, buf2_q}; + assign subtract_val3 = {buf3_i, buf3_q}; + + my_diff # ( + .SIZEIN(DWIDTH/4) + ) diff_i0 ( + .resetn (aresetn), + .clk (aclk), + .a (s00_axis_tdata[DWIDTH/2-1:DWIDTH/4]), + .b (s01_axis_tdata[DWIDTH/2-1:DWIDTH/4]), + .res (diff0_i) + ); + + my_diff # ( + .SIZEIN(DWIDTH/4) + ) diff_q0 ( + .resetn (aresetn), + .clk (aclk), + .a (s00_axis_tdata[DWIDTH/4-1:0]), + .b (s01_axis_tdata[DWIDTH/4-1:0]), + .res (diff0_q) + ); + + my_diff # ( + .SIZEIN(DWIDTH/4) + ) diff_i1 ( + .resetn (aresetn), + .clk (aclk), + .a (s00_axis_tdata[DWIDTH/2-1:DWIDTH/4]), + .b (s02_axis_tdata[DWIDTH/2-1:DWIDTH/4]), + .res (diff1_i) + ); + + my_diff # ( + .SIZEIN(DWIDTH/4) + ) diff_q1 ( + .resetn (aresetn), + .clk (aclk), + .a (s00_axis_tdata[DWIDTH/4-1:0]), + .b (s02_axis_tdata[DWIDTH/4-1:0]), + .res (diff1_q) + ); + + my_diff # ( + .SIZEIN(DWIDTH/4) + ) diff_i2 ( + .resetn (aresetn), + .clk (aclk), + .a (s00_axis_tdata[DWIDTH/2-1:DWIDTH/4]), + .b (s03_axis_tdata[DWIDTH/2-1:DWIDTH/4]), + .res (diff2_i) + ); + + my_diff # ( + .SIZEIN(DWIDTH/4) + ) diff_q2 ( + .resetn (aresetn), + .clk (aclk), + .a (s00_axis_tdata[DWIDTH/4-1:0]), + .b (s03_axis_tdata[DWIDTH/4-1:0]), + .res (diff2_q) + ); + + my_diff # ( + .SIZEIN(DWIDTH/4) + ) diff_i3 ( + .resetn (aresetn), + .clk (aclk), + .a (s00_axis_tdata[DWIDTH/2-1:DWIDTH/4]), + .b (s04_axis_tdata[DWIDTH/2-1:DWIDTH/4]), + .res (diff3_i) + ); + + my_diff # ( + .SIZEIN(DWIDTH/4) + ) diff_q3 ( + .resetn (aresetn), + .clk (aclk), + .a (s00_axis_tdata[DWIDTH/4-1:0]), + .b (s04_axis_tdata[DWIDTH/4-1:0]), + .res (diff3_q) + ); + + // Buffer clock for edge detect + always @(posedge aclk) + begin + if (!aresetn) + begin + s00_axi_aclk_d <= false_c; + s00_axi_aclk_d2 <= false_c; + end + else + begin + s00_axi_aclk_d <= s00_axi_aclk; + s00_axi_aclk_d2 <= s00_axi_aclk_d; + end + end + + assign s00_axi_aclk_posedge = s00_axi_aclk_d & !s00_axi_aclk_d2; + + // Simple hold circuit + always @(posedge aclk) + begin + if (!aresetn) + begin + buf0_i <= 0; + buf0_q <= 0; + buf1_i <= 0; + buf1_q <= 0; + buf2_i <= 0; + buf2_q <= 0; + buf3_i <= 0; + buf3_q <= 0; + end + else if (s00_axi_aclk_posedge) begin + buf0_i <= diff0_i; + buf0_q <= diff0_q; + buf1_i <= diff1_i; + buf1_q <= diff1_q; + buf2_i <= diff2_i; + buf2_q <= diff2_q; + buf3_i <= diff3_i; + buf3_q <= diff3_q; + end + end + +endmodule diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/src/subtractor.wcfg b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/src/subtractor.wcfg new file mode 100644 index 0000000000..e54891b0a1 --- /dev/null +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/src/subtractor.wcfg @@ -0,0 +1,368 @@ + + + + + + + + + + + + + + + + + + + + + + + + + AI_ENGINE_0_DM_OUT0_tdata[63:0] + AI_ENGINE_0_DM_OUT0_tdata[63:0] + + + AI_ENGINE_0_DM_OUT0_tkeep + AI_ENGINE_0_DM_OUT0_tkeep + + + AI_ENGINE_0_DM_OUT0_tlast + AI_ENGINE_0_DM_OUT0_tlast + + + AI_ENGINE_0_DM_OUT0_tready + AI_ENGINE_0_DM_OUT0_tready + + + AI_ENGINE_0_DM_OUT0_tvalid + AI_ENGINE_0_DM_OUT0_tvalid + + + AI_ENGINE_0_DM_OUT1_tdata[63:0] + AI_ENGINE_0_DM_OUT1_tdata[63:0] + + + AI_ENGINE_0_DM_OUT1_tkeep + AI_ENGINE_0_DM_OUT1_tkeep + + + AI_ENGINE_0_DM_OUT1_tlast + AI_ENGINE_0_DM_OUT1_tlast + + + AI_ENGINE_0_DM_OUT1_tready + AI_ENGINE_0_DM_OUT1_tready + + + AI_ENGINE_0_DM_OUT1_tvalid + AI_ENGINE_0_DM_OUT1_tvalid + + + AI_ENGINE_0_DM_OUT2_tdata[63:0] + AI_ENGINE_0_DM_OUT2_tdata[63:0] + + + AI_ENGINE_0_DM_OUT2_tkeep + AI_ENGINE_0_DM_OUT2_tkeep + + + AI_ENGINE_0_DM_OUT2_tlast + AI_ENGINE_0_DM_OUT2_tlast + + + AI_ENGINE_0_DM_OUT2_tready + AI_ENGINE_0_DM_OUT2_tready + + + AI_ENGINE_0_DM_OUT2_tvalid + AI_ENGINE_0_DM_OUT2_tvalid + + + AI_ENGINE_0_DM_OUT3_tdata[63:0] + AI_ENGINE_0_DM_OUT3_tdata[63:0] + + + AI_ENGINE_0_DM_OUT3_tkeep + AI_ENGINE_0_DM_OUT3_tkeep + + + AI_ENGINE_0_DM_OUT3_tlast + AI_ENGINE_0_DM_OUT3_tlast + + + AI_ENGINE_0_DM_OUT3_tready + AI_ENGINE_0_DM_OUT3_tready + + + AI_ENGINE_0_DM_OUT3_tvalid + AI_ENGINE_0_DM_OUT3_tvalid + + + AXIS1TO2_0_IN0_tdata[31:0] + AXIS1TO2_0_IN0_tdata[31:0] + + + AXIS1TO2_0_IN0_tready + AXIS1TO2_0_IN0_tready + + + AXIS1TO2_0_IN0_tvalid + AXIS1TO2_0_IN0_tvalid + + + COUNTER_0_M00_AXIS_tdata[63:0] + COUNTER_0_M00_AXIS_tdata[63:0] + + + COUNTER_0_M00_AXIS_tlast + COUNTER_0_M00_AXIS_tlast + + + COUNTER_0_M00_AXIS_tready + COUNTER_0_M00_AXIS_tready + + + COUNTER_0_M00_AXIS_tvalid + COUNTER_0_M00_AXIS_tvalid + + + VADD_S_0_OUT0_tdata[31:0] + VADD_S_0_OUT0_tdata[31:0] + + + VADD_S_0_OUT0_tready + VADD_S_0_OUT0_tready + + + VADD_S_0_OUT0_tvalid + VADD_S_0_OUT0_tvalid + + + aclk_x1 + aclk_x1 + + + aclk_x2 + aclk_x2 + + + aresetn + aresetn + + + true_c + true_c + + + false_c + false_c + + + clk_period_c[31:0] + clk_period_c[31:0] + + + aresetn + aresetn + + + aclk + aclk + + + s00_axi_aclk + s00_axi_aclk + + + s00_axi_aclk_d + s00_axi_aclk_d + + + s00_axi_aclk_d2 + s00_axi_aclk_d2 + + + s00_axi_aclk_posedge + s00_axi_aclk_posedge + + + s00_axis_tready + s00_axis_tready + + + s00_axis_tdata[63:0] + s00_axis_tdata[63:0] + + + s00_axis_tvalid + s00_axis_tvalid + + + s00_axis_tlast + s00_axis_tlast + + + s01_axis_tready + s01_axis_tready + + + s01_axis_tdata[63:0] + s01_axis_tdata[63:0] + + + s01_axis_tvalid + s01_axis_tvalid + + + s01_axis_tlast + s01_axis_tlast + + + s02_axis_tready + s02_axis_tready + + + s02_axis_tdata[63:0] + s02_axis_tdata[63:0] + + + s02_axis_tvalid + s02_axis_tvalid + + + s02_axis_tlast + s02_axis_tlast + + + s03_axis_tready + s03_axis_tready + + + s03_axis_tdata[63:0] + s03_axis_tdata[63:0] + + + s03_axis_tvalid + s03_axis_tvalid + + + s03_axis_tlast + s03_axis_tlast + + + s04_axis_tready + s04_axis_tready + + + s04_axis_tdata[63:0] + s04_axis_tdata[63:0] + + + s04_axis_tvalid + s04_axis_tvalid + + + s04_axis_tlast + s04_axis_tlast + + + subtract_val0 + subtract_val0 + + + subtract_val1 + subtract_val1 + + + subtract_val2 + subtract_val2 + + + subtract_val3 + subtract_val3 + + + buf0_i[15:0] + buf0_i[15:0] + UNSIGNEDDECRADIX + + + buf0_q[15:0] + buf0_q[15:0] + UNSIGNEDDECRADIX + + + buf1_i[15:0] + buf1_i[15:0] + UNSIGNEDDECRADIX + + + buf1_q[15:0] + buf1_q[15:0] + UNSIGNEDDECRADIX + + + buf2_i[15:0] + buf2_i[15:0] + UNSIGNEDDECRADIX + + + buf2_q[15:0] + buf2_q[15:0] + UNSIGNEDDECRADIX + + + buf3_i[15:0] + buf3_i[15:0] + UNSIGNEDDECRADIX + + + buf3_q[15:0] + buf3_q[15:0] + UNSIGNEDDECRADIX + + + diff0_i[15:0] + diff0_i[15:0] + UNSIGNEDDECRADIX + + + diff0_q[15:0] + diff0_q[15:0] + UNSIGNEDDECRADIX + + + diff1_i[15:0] + diff1_i[15:0] + UNSIGNEDDECRADIX + + + diff1_q[15:0] + diff1_q[15:0] + UNSIGNEDDECRADIX + + + diff2_i[15:0] + diff2_i[15:0] + UNSIGNEDDECRADIX + + + diff2_q[15:0] + diff2_q[15:0] + UNSIGNEDDECRADIX + + + diff3_i[15:0] + diff3_i[15:0] + UNSIGNEDDECRADIX + + + diff3_q[15:0] + diff3_q[15:0] + UNSIGNEDDECRADIX + + diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/src/testbench.sv b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/src/testbench.sv index 541007f934..ebe4fc0dfd 100644 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/src/testbench.sv +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/cosim/src/testbench.sv @@ -141,6 +141,40 @@ module tb_top(); ); + // Subtractor + my_sub #( + .DWIDTH(64) + ) my_sub_i0 ( + .aresetn (aresetn), + .aclk (aclk_x2), + .s00_axi_aclk (aclk_x1), + .s00_axis_tdata (COUNTER_0_M00_AXIS_tdata), + .s00_axis_tlast (COUNTER_0_M00_AXIS_tlast), + .s00_axis_tready (COUNTER_0_M00_AXIS_tready), + .s00_axis_tvalid (COUNTER_0_M00_AXIS_tvalid), + .s01_axis_tdata (AI_ENGINE_0_DM_OUT0_tdata), + .s01_axis_tlast (AI_ENGINE_0_DM_OUT0_tlast), + .s01_axis_tready (AI_ENGINE_0_DM_OUT0_tready), + .s01_axis_tvalid (AI_ENGINE_0_DM_OUT0_tvalid), + .s02_axis_tdata (AI_ENGINE_0_DM_OUT1_tdata), + .s02_axis_tlast (AI_ENGINE_0_DM_OUT1_tlast), + .s02_axis_tready (AI_ENGINE_0_DM_OUT1_tready), + .s02_axis_tvalid (AI_ENGINE_0_DM_OUT1_tvalid), + .s03_axis_tdata (AI_ENGINE_0_DM_OUT2_tdata), + .s03_axis_tlast (AI_ENGINE_0_DM_OUT2_tlast), + .s03_axis_tready (AI_ENGINE_0_DM_OUT2_tready), + .s03_axis_tvalid (AI_ENGINE_0_DM_OUT2_tvalid), + .s04_axis_tdata (AI_ENGINE_0_DM_OUT3_tdata), + .s04_axis_tlast (AI_ENGINE_0_DM_OUT3_tlast), + .s04_axis_tready (AI_ENGINE_0_DM_OUT3_tready), + .s04_axis_tvalid (AI_ENGINE_0_DM_OUT3_tvalid), + .subtract_val0 (), + .subtract_val1 (), + .subtract_val2 (), + .subtract_val3 () + ); + + // Testbench // Force tready to enable remaining AXIS masters to send data diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/ip/aie/Makefile b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/ip/aie/Makefile index e2a7377b4b..b62f758fd0 100644 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/ip/aie/Makefile +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/ip/aie/Makefile @@ -82,7 +82,7 @@ allx86 : clean x86compile x86sim #${AIE_OUTPUT}: ${AIE_SRC}/* ${AIE_GRAPHS}/* ${AIE_KERNELS}/* # $(MAKE) clean -# aiecompiler -target=hw -v --use-phy-shim=${FLAG} --constraints=${CONSTRAINT_FILE} -include=${AIE_SRC} -include=${AIE_GRAPHS} -include=${AIE_KERNELS} ${TEST_BENCH} ${OTHER_OPTS} -Xmapper=${MAP_OPT} --platform=${XPFM} -workdir=${WORK_DIR} ${PL_FREQ} |& tee ${LOG_FILE} +# aiecompiler -target=hw -v --use-phy-shim=${FLAG} --constraints=${CONSTRAINT_FILE} -include=${AIE_SRC} -include=${AIE_GRAPHS} -include=${AIE_KERNELS} ${TEST_BENCH} ${OTHER_OPTS} -Xmapper=${MAP_OPT} --platform=${XPFM} -workdir=${WORK_DIR} ${PL_FREQ} 2>&1 | tee ${LOG_FILE} ${AIE_WS}: mkdir ${AIE_WS} @@ -117,14 +117,14 @@ ${AIE_OUTPUT}: ${AIE_WS} ${AIE_SRC}/* ${AIE_GRAPHS}/* ${AIE_KERNELS}/* ${AIE_XFLAGS} \ --config ${AIE_CFG} \ ${TEST_BENCH} \ - |& tee ${LOG_FILE} + 2>&1 | tee ${LOG_FILE} sim: - aiesimulator --pkg-dir=$(WORK_DIR) -o $(SIM_OUTPUT) --simulation-cycle-timeout $(MAX_CYCLES) |& tee -a $(SIM_LOG_FILE) + aiesimulator --pkg-dir=$(WORK_DIR) -o $(SIM_OUTPUT) --simulation-cycle-timeout $(MAX_CYCLES) 2>&1 | tee -a $(SIM_LOG_FILE) sim_analyzer: - aiesimulator --pkg-dir=$(WORK_DIR) --profile --online -wdb -text -o $(SIM_OUTPUT) --simulation-cycle-timeout $(MAX_CYCLES) |& tee -a $(SIM_LOG_FILE) + aiesimulator --pkg-dir=$(WORK_DIR) --profile --online -wdb -text -o $(SIM_OUTPUT) --simulation-cycle-timeout $(MAX_CYCLES) 2>&1 | tee -a $(SIM_LOG_FILE) analyze: vitis_analyzer -report system.wdb @@ -136,7 +136,7 @@ get_op: grep -v T ${SIM_OUTPUT}/data/output3.txt > ${SIM_OUTPUT}/data/output3_raw.txt x86sim: - x86simulator --pkg-dir=$(WORK_DIR) |& tee -a $(SIM_LOG_FILE) + x86simulator --pkg-dir=$(WORK_DIR) 2>&1 | tee -a $(SIM_LOG_FILE) clean: rm -rf Work Work* $(AIE_WS) diff --git a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/ip/aie/src/kernels/my_stream_32b_dm.cpp b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/ip/aie/src/kernels/my_stream_32b_dm.cpp index 0416ef1aac..8add0a2014 100644 --- a/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/ip/aie/src/kernels/my_stream_32b_dm.cpp +++ b/Vitis_System_Design/Design_Tutorials/02-Versal_Vitis_Subsystem_Flow/vss/ip/aie/src/kernels/my_stream_32b_dm.cpp @@ -31,7 +31,7 @@ void __attribute__ ((noinline)) my_stream_32b_dm::run(input_streamhttps://docs.amd.com/v/u/ja-JP/UG1605-vitis-tutorials

-内容に相違が生じる場合には原文を優先します。英語版の更新に対応していないことがありますので、日本語版は参考用としてご使用の上、最新情報につきましては、必ず最新英語版 (https://github.com/Xilinx/Vitis-Tutorials) をご参照ください。 +内容に相違が生じる場合には原文を優先します。英語版の更新に対応していないことがありますので、日本語版は参考用としてご使用の上、最新情報につきましては、必ず最新英語版 (https://github.com/Xilinx/Vitis-Tutorials) をご参照ください。 +

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