Perf: bring SIMD take back and generalize by Copy

[connortsui20]

Brings back the portable_simd take implementation back, and instead of constraining by NativePType, this bounds by T: Copy and will cast to u8 - u64 depending on the size of the type.

This also adds a check for out-of-bounds indices that adds a single simd and bitwise instruction to the hot loop so we correctly panic at the end if there was an out of bounds.

It might be the case that separating out the &= and the simd_lt is so that the gather isn't depending on the &=, but if register pressure is high then we do not want to evict any data from the SIMD registers. I should probably benchmark that...

[codecov]

Codecov Report

❌ Patch coverage is 54.32099% with 37 lines in your changes missing coverage. Please review.
✅ Project coverage is 82.68%. Comparing base (9a76489) to head (078ca7c).

Files with missing lines	Patch %	Lines
vortex-compute/src/take/slice/asm_stubs.rs	0.00%	18 Missing ⚠️
vortex-compute/src/take/slice/portable.rs	44.82%	16 Missing ⚠️
vortex-compute/src/take/slice/mod.rs	0.00%	2 Missing ⚠️
vortex-compute/src/take/slice/avx2.rs	96.87%	1 Missing ⚠️

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[codspeed-hq]

CodSpeed Performance Report

Merging #5722 will improve performances by 22.72%

_{Comparing ct/simd-portable-take (078ca7c) with develop (9a76489)}

Summary

⚡ 20 improvements
✅ 1236 untouched
⏩ 621 skipped¹

Benchmarks breakdown

	Benchmark	BASE	HEAD	Change
⚡	pvector_take_zipfian[16, 1000]	10.4 µs	9.3 µs	+11.81%
⚡	pvector_take_zipfian[256, 100000]	674.8 µs	550 µs	+22.7%
⚡	pvector_take_zipfian[2048, 10000]	74.6 µs	62.2 µs	+19.88%
⚡	pvector_take_zipfian[2048, 100000]	678.3 µs	553.5 µs	+22.56%
⚡	pvector_take_zipfian[8192, 10000]	85.8 µs	73.4 µs	+16.82%
⚡	pvector_take_zipfian[256, 10000]	71.3 µs	59 µs	+20.92%
⚡	pvector_take_zipfian[256, 1000]	10.8 µs	9.7 µs	+11.33%
⚡	pvector_take_uniform[16, 100000]	674.4 µs	549.6 µs	+22.71%
⚡	pvector_take_uniform[16, 10000]	70.5 µs	58.2 µs	+21.21%
⚡	pvector_take_zipfian[8192, 100000]	700.7 µs	575.8 µs	+21.68%
⚡	pvector_take_uniform[2048, 100000]	678.1 µs	553.3 µs	+22.56%
⚡	pvector_take_uniform[256, 100000]	674.9 µs	550 µs	+22.69%
⚡	pvector_take_uniform[2048, 10000]	74.9 µs	62.6 µs	+19.67%
⚡	pvector_take_zipfian[16, 100000]	674.4 µs	549.5 µs	+22.72%
⚡	pvector_take_uniform[16, 1000]	11.1 µs	10.1 µs	+10.21%
⚡	pvector_take_uniform[256, 10000]	71.3 µs	59 µs	+20.93%
⚡	pvector_take_uniform[256, 1000]	11.6 µs	10.5 µs	+10.46%
⚡	pvector_take_zipfian[16, 10000]	70.9 µs	58.5 µs	+21.08%
⚡	pvector_take_uniform[8192, 10000]	87.9 µs	75.6 µs	+16.27%
⚡	pvector_take_uniform[8192, 100000]	717.4 µs	592.9 µs	+21.01%

Footnotes

1. 621 benchmarks were skipped, so the baseline results were used instead. If they were deleted from the codebase, click here and archive them to remove them from the performance reports. ↩

[connortsui20]

it might be the case that the portable simd is actually faster than the avx2 impl? I think we need to do some more directed benchmarks...