For what it's worth, I have been using xsimd at my job for ~1 year, and can only recommend it (optimization of ML clustering code on CPU). Straightforward to use, easy to extend to support additional instructions. The API is clear and the implementation follows modern C++ practices.
On Tue, Feb 9, 2021 at 3:15 AM Yibo Cai <yibo....@arm.com> wrote: > This topic was talked in an earlier thread [1], but not landed yet. > > PR https://github.com/apache/arrow/pull/9424 optimizes ByteStreamSplit > with Arm64 NEON, maybe it's a good chance to evaluate possibility of > simplifying arch dependent SIMD code with an SIMD library. > > I did a quick comparison of four open source SIMD libraries we've > mentioned in earlier talks. > > All libraries support C++11, GCC/Clang/MSVC, x86 (up to AVX512), Arm64 > NEON, with permissive open source licenses. > > Some differences: > > - nsimd: https://github.com/agenium-scale/nsimd > * supports Arm64 SVE, Cuda > * needs installation, not header only > * 133 stars, 11 contributors > > - mipp: https://github.com/aff3ct/MIPP > * header only > * 241 stars, 2 contributors > > - xsimd: https://github.com/xtensor-stack/xsimd > * header only > * 938 stars, 28 contributors > > - libsimdpp: https://github.com/p12tic/libsimdpp > * supports PPC, MIPS > * header only > * 906 stars, 17 contributors > > I have a little experience of libsimdpp. It's straightforward to use. I > suppose other libraries are similar. > I would prefer xsimd. Simply because it has more stars and contributors, > and a more active community. > > [1] > https://mail-archives.apache.org/mod_mbox/arrow-dev/202006.mbox/%3C3667345c-fdd2-5bbd-9bff-023282c377d8%40python.org%3E >
