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It's not parallel, a framework, or a GPU feature. It's single-instruction-multiple-data (SIMD) which is used to speed up single threaded execution on a CPU when
by AshleysBrain 12y ago
It's not parallel, a framework, or a GPU feature. It's single-instruction-multiple-data (SIMD) which is used to speed up single threaded execution on a CPU when working with lists of numbers.
- cma 12y ago>Single instruction, multiple data (SIMD), is a class of parallel computers in Flynn's taxonomy
- LnxPrgr3 12y agoMy understanding is architectures are different enough that the fastest SIMD strategy is sometimes CPU-dependent. The author of FFTS, for example, chose a different strategy on ARM than x86_64: http://anthonix.com/ffts/preprints/tsp2013.pdf http://anthonix.com/ffts/preprints/tsp2013.pdf He found himself writing the NEON code in assembly entirely by hand because vector intrinsics didn't even expose CPU features he wanted to use—even in C, where vector intrinsics are CPU-specific. Having access to SIMD is definitely better than not having it, but it really should be paired with good optimized implementations of things like BLAS and FFT libraries.