Optimize sgemm on RISC-V platform

• sgemm_riscv

  2 9 6.8 C

  This project records the process of optimizing SGEMM (single-precision floating point General Matrix Multiplication) on the riscv platform.

this sgemm progress is pretty impressive. i assume 'version 1' is one of the lower lines on the first graph? he has a graph lower down that shows it getting under 300 megaflops, closer to 50 megaflops for most problem sizes. getting up to 2 gigaflops is seriously impressive; that's 50% of the maximum theoretical possible throughput, which is really challenging on things that aren't vector supercomputers

probably worth archiving this link: https://github.com/Zhao-Dongyu/sgemm_riscv

i was astounded yesterday to find that gcc 12.2.0 fails at some basic optimizations on risc-v. (all of the following is with -Os)

this trivial subroutine

    int sumarray(int *a, int n)

• julia

  350 44,510 10.0 Julia

  The Julia Programming Language

  

I don't believe there is any official documentation on this, but https://github.com/JuliaLang/julia/pull/49430 for example added prefetching to the marking phase of a GC which saw speedups on x86, but not on M1.

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• neural-engine

  20 1,861 5.1

  Everything we actually know about the Apple Neural Engine (ANE)

yep. they have a neural engine that is separate from the CPU and GPU that does really fast matmuls https://github.com/hollance/neural-engine. it's basically completely undocumented.

• amx

  18 843 4.1 C

  Apple AMX Instruction Set

I am talking about the matrix/vector coprocessor (AMX). You can find some reverse-engineered documentation here: https://github.com/corsix/amx

On M3 a singe matrix block can achieve ~ 1TFLOP on DGEMM, I assume it will be closer to 4TFLOPS for SGEMM. The Max variants have two such blocks. Didn't do precise benchmarking myself, but switching Python/R matrix libraries to use Apple's BLAS result in 5-6x perf improvement on matrix heavy code for me.

• blis

  17 2,091 7.0 C

  BLAS-like Library Instantiation Software Framework

  

There is a recent update to the blis alternative to BLAS that includes a number of RISC-V performance optimizations.

https://github.com/flame/blis/pull/737

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