JuliaLinearAlgebra/Octavian.jl
View on GitHub ↗ ★ 256 Julia
Multi-threaded BLAS-like library that provides pure Julia matrix multiplication
14 mentions on Hacker News by 8 people: 1 story, 13 comments · first 2021-02-05 · latest 2023-02-22
20082026
-
…absolutely do. Here's a matmul and LU respectively that are SOTA (especially for small matrices) https://github.com/JuliaLinearAlgebra/Octavian.jl and https://github.com/JuliaLinearAlgebra/RecursiveFactorization...
comment by adgjlsfhk1 · 2023-02-22 · in ML would have advanced faster if another front-end language had been adopted? -
…github.com/YingboMa/RecursiveFactorization.jl , https://github.com/JuliaSIMD/TriangularSolve.jl , and https://github.com/JuliaLinearAlgebra/Octavian.jl . And this is one part of the DiffEq performance story. The performance of this of…
comment by ChrisRackauckas · 2022-01-08 · in Fortran is easy to learn -
> Even in Julia. Unless you're using [Octavian.jl]( https://github.com/JuliaLinearAlgebra/Octavian.jl ) or such for your linear algebra in place of BLAS. But yes, it is always interesting how many people do not know how much of modern…
comment by cbkeller · 2022-01-08 · in Fortran is easy to learn -
…also do it at the LLVM level: https://github.com/JuliaComputingOSS/llvm-cbe One cool use case is in https://github.com/JuliaLinearAlgebra/Octavian.jl which relies on loopvectorization.jl to do transforms on Julia AST beyond what LLVM does.…
comment by amkkma · 2021-11-17 · in Show HN: Prometeo – a Python-to-C transpiler for high-performance computing -
…is able to outperform MKL for sizes up to to 1000 or so (and is about 20% slower for bigger sizes). https://github.com/JuliaLinearAlgebra/Octavian.jl .
comment by adgjlsfhk1 · 2021-09-29 · in The GIL and its effects on Python multithreading -
Or much faster (at small sizes): https://github.com/JuliaLinearAlgebra/Octavian.jl
comment by celrod · 2021-06-20 · in Julia: Faster than Fortran, cleaner than Numpy -
…true, hard-real time, yes julia is not a good choice but it's perfectly fine for soft realtime. [1] https://github.com/JuliaLinearAlgebra/Octavian.jl/issues/24#...
comment by eigenspace · 2021-06-06 · in From Julia to Rust -
…... has benchmarks with Julia out-performing highly optimized Fortran DiffEq solvers, and https://github.com/JuliaLinearAlgebra/Octavian.jl shows that pure Julia BLAS implementations can compete with MKL and openBLAS, which are among the…
comment by lmm · 2021-05-28 · in Julia 1.6 addresses latency issues -
…has benchmarks with Julia out-performing highly optimized Fortran DiffEq solvers, and https://github.com/JuliaLinearAlgebra/Octavian.jl shows that pure Julia BLAS implementations can compete with MKL and openBLAS, which are among the most…
comment by adgjlsfhk1 · 2021-05-28 · in Julia 1.6 addresses latency issues -
…computers, form our workhorse. https://raw.githubusercontent.com/JuliaLinearAlgebra/Octavia... https://github.com/JuliaLinearAlgebra/Octavian.jl https://github.com/YingboMa/RecursiveFactorization.jl
comment by ChrisRackauckas · 2021-05-23 · in An early look at Postgres 14: Performance and monitoring Improvements -
…best right now are Octavian and PaddedMatrices.jl. On Ryzen these BLAS's are doing extremely well: https://github.com/JuliaLinearAlgebra/Octavian.jl/issues/24#... but also on Intel: https://chriselrod.github.io/PaddedMatrices.jl/dev/arches/…
comment by ChrisRackauckas · 2021-03-12 · in Julia receives DARPA award to accelerate electronics simulation -
…possible to write, including BLAS libraries that are competitive with OpenBLAS, BLIS, and MKL ( https://github.com/JuliaLinearAlgebra/Octavian.jl/issues/24 )
comment by eigenspace · 2021-02-05 · in Metals with Scala 3