Tutorial

PyTorchSimFrontend/extension_config.py

@@ -103,7 +103,7 @@ def __getattr__(name):
     if name == "CONFIG_TORCHSIM_DUMP_PATH":
         return os.environ.get('TORCHSIM_DUMP_PATH', default = CONFIG_TORCHSIM_DIR)
     if name == "CONFIG_TORCHSIM_LOG_PATH":
-        return os.environ.get('TORCHSIM_DUMP_LOG_PATH', default = os.path.join(CONFIG_TORCHSIM_DIR, "togsim_results"))
+        return os.environ.get('TORCHSIM_LOG_PATH', default = os.path.join(CONFIG_TORCHSIM_DIR, "togsim_results"))
 
     if name == "CONFIG_TOGSIM_EAGER_MODE":
         return int(os.environ.get("TOGSIM_EAGER_MODE", default=False))

Scheduler/scheduler.py

@@ -144,6 +144,7 @@ class PyTorchSimRunner:
     PARTITION_BUSY = 0
     PARTITION_IDLE = 1
     SELECT_NOTHING = 2
+    NPU_MODULE = None
     def __init__(self, tog_simulator : TOGSimulator, num_partion=1) -> None:
         self.module = self.setup_device()
         self.num_partion = num_partion
@@ -161,8 +162,10 @@ def __init__(self, tog_simulator : TOGSimulator, num_partion=1) -> None:
         # Dry run for compile and create generator
         os.environ["TOGSIM_EAGER_MODE"] = "1"
 
-    @staticmethod
-    def setup_device():
+    @classmethod
+    def setup_device(cls):
+        if cls.NPU_MODULE is not None:
+            return cls.NPU_MODULE
         source_file_path = os.path.dirname(os.path.abspath(__file__))
         source_file = os.path.join(
             source_file_path, f"{extension_config.CONFIG_TORCHSIM_DIR}/PyTorchSimFrontend/extension_device.cpp"
@@ -201,6 +204,7 @@ def setup_device():
         get_wrapper_codegen_for_device("npu")
             == ExtensionWrapperCodegen
         )
+        cls.NPU_MODULE = module
         return module
 
     def submit(self, batched_req, partition_idx) -> List[RequestReturn]:

TOGSim/include/DMA.h

@@ -62,7 +62,7 @@ class DMA {
         const std::vector<int>& tag_key = tag_entry.first;
         uint32_t value = tag_entry.second;
         if (value == 1) {
-          spdlog::warn("[Tag Table][{}] Unused tag found: (key={}, val={})",
+          spdlog::debug("[Tag Table][{}] Unused tag found: (key={}, val={})",
             subgraph_id, fmt::format("[{}]", fmt::join(tag_key, ", ")), value);
         }
       }
@@ -134,4 +134,4 @@ class DMA {
   std::queue<mem_fetch*> _pending_accesses;
   bool _generated_once = false;
 };
-#endif
+#endif

tutorial/session1/DNNServing.ipynb

@@ -38,7 +38,7 @@
     "from Scheduler.scheduler import Scheduler, SchedulerDNNModel, Request\n",
     "from PyTorchSimFrontend import extension_config\n",
     "\n",
-    "scheduler = Scheduler(num_request_queue=1, engine_select=Scheduler.FIFO_ENGINE, togsim_config=extension_config.TOGSIM_CONFIG)\n",
+    "scheduler = Scheduler(num_request_queue=1, engine_select=Scheduler.FIFO_ENGINE, togsim_config=extension_config.CONFIG_TOGSIM_CONFIG)\n",
     "device = scheduler.execution_engine.module.custom_device()\n",
     "\n",
     "model = resnet18().eval()\n",
@@ -83,7 +83,7 @@
     "target_model1 = resnet18().eval()\n",
     "\n",
     "# Init scheduler\n",
-    "scheduler = Scheduler(num_request_queue=1, max_batch=32, engine_select=Scheduler.FIFO_ENGINE, togsim_config=extension_config.TOGSIM_CONFIG)\n",
+    "scheduler = Scheduler(num_request_queue=1, max_batch=32, engine_select=Scheduler.FIFO_ENGINE, togsim_config=extension_config.CONFIG_TOGSIM_CONFIG)\n",
     "# Register compiled model\n",
     "opt_model1 = torch.compile(target_model1.to(device=scheduler.execution_engine.module.custom_device(), memory_format=torch.channels_last), dynamic=False)\n",
     "SchedulerDNNModel.register_model(\"resnet18\", opt_model1)\n",

tutorial/session1/LogAnalysis.ipynb

@@ -19,7 +19,7 @@
     "base_dir = os.environ.get('TORCHSIM_DIR', default='/workspace/PyTorchSim')\n",
     "sys.path.append(base_dir)\n",
     "os.environ['TOGSIM_CONFIG']=f\"{base_dir}/tutorial/session1/togsim_configs/togsim_config_timing_only.yml\"\n",
-    "os.environ['TORCHSIM_DUMP_LOG_PATH']=os.path.join(os.getcwd(), \"togsim_results\")"
+    "os.environ['TORCHSIM_LOG_PATH']=os.path.join(os.getcwd(), \"togsim_results\")"
    ]
   },
   {

tutorial/session2/Hands_on.ipynb

@@ -32,6 +32,7 @@
     "import torch._dynamo\n",
     "import torch.utils.cpp_extension\n",
     "base_dir = os.environ.get('TORCHSIM_DIR', default='/workspace/PyTorchSim')\n",
+    "os.environ['TORCHSIM_DUMP_PATH']=os.path.join(os.getcwd(), \"togsim_results\")\n",
     "sys.path.append(base_dir)\n",
     "\n",
     "from Scheduler.scheduler import PyTorchSimRunner\n",