|5 months ago||about 18 hours ago|
|Apache License 2.0||GNU General Public License v3.0 or later|
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Small Neural networks in Julia 5x faster than PyTorch
8 projects | news.ycombinator.com | 14 Apr 2022
The article asks "Which Micro-optimizations matter for BLAS3?", implying small dimensions, but doesn't actually tell me. The problem is well-studied, depending on what you consider "small". The most important thing is to avoid the packing step below an appropriate threshold. Implementations include libxsmm, blasfeo, and the "sup" version in blis (with papers on libxsmm and blasfeo). Eigen might also be relevant.
Eigen: A C++ template library for linear algebra
6 projects | news.ycombinator.com | 4 Apr 2022
Matrix Multiplication Inches Closer To Mythic Goal
2 projects | news.ycombinator.com | 18 Dec 2021
However, on recent CPUs 4x4 is small for the innermost block size of the non-trivial hierarchy you need. You can see examples under https://github.com/flame/blis/tree/master/config with an a priori procedure for determining them in https://www.cs.utexas.edu/users/flame/pubs/TOMS-BLIS-Analyti... (but compare with what's actually used for SKX, in particular). OpenBLAS will normally be similar, though it may come out somewhat faster, but it's easier to see in BLIS.
What are some alternatives?
tiny-cuda-nn - Lightning fast C++/CUDA neural network framework
blasfeo - Basic linear algebra subroutines for embedded optimization
abseil-cpp - Abseil Common Libraries (C++)
rofi-pass - rofi frontend for pass
sundials - Official development repository for SUNDIALS - a SUite of Nonlinear and DIfferential/ALgebraic equation Solvers. Pull requests are welcome for bug fixes and minor changes.
diffrax - Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
juliaup - Julia installer and version multiplexer
neanderthal - Fast Clojure Matrix Library
DirectXMath - DirectXMath is an all inline SIMD C++ linear algebra library for use in games and graphics apps
laser - The HPC toolbox: fused matrix multiplication, convolution, data-parallel strided tensor primitives, OpenMP facilities, SIMD, JIT Assembler, CPU detection, state-of-the-art vectorized BLAS for floats and integers