You can either have performance (=write manual ASM for each platform), or portability, but not both.
What so-called "portable SIMD" libraries give you is "portable auto-vectorization". "Portable performance" is a global property of the algorithm. Relying on auto-vectorization will result in e.g. sub-optimal register spills in practice. The microbenchmarks will look great, though. ;)
Getting 2x or 4x performance in your inner loops using a reasonable SIMD library is infinitely better than theoretically getting 8x performance with hand-coded nonportable intrinsics, because the latter is never going to happen in most programs, so the actual point of comparison is scalar code, or autovectorized code at best.
Starts to get a bit philosophical on what constitutes "portable" but JIT compilers would emit an opcode based off of whatever the frontend/IR is saying to do surely?
You can either have performance (=write manual ASM for each platform), or portability, but not both.
What so-called "portable SIMD" libraries give you is "portable auto-vectorization". "Portable performance" is a global property of the algorithm. Relying on auto-vectorization will result in e.g. sub-optimal register spills in practice. The microbenchmarks will look great, though. ;)
But yeah to be fair if you are at that point, you probably want to go fully non-portable anyway. Especially with AI.
Has anyone even figured out how to do vector stuff (SVE/RVV) without assembly?
Except in languages with a JIT compiler