SciML/SciMLBenchmarks.jl
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Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R
6 mentions on Hacker News by 2 people: 0 stories, 6 comments · first 2021-12-01 · latest 2024-03-26
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…In the meantime, if you have more requests for the benchmarks, please feel free to open issues at https://github.com/SciML/SciMLBenchmarks.jl so we can track them. All of our benchmarks run on this open platform and anyone can add things…
comment by ChrisRackauckas · 2024-03-26 · in Nonlinearsolve.jl: Fast and Robust Solvers for Nonlinear Equations in Julia -
…If you have a concrete change you think can improve the benchmarks, then please share it at https://github.com/SciML/SciMLBenchmarks.jl . We'll be happy to make and maintain another.
comment by ChrisRackauckas · 2023-05-02 · in Can Fortran survive another 15 years? -
…). Every fully reproducible project has a Manifest that decrease the complete package state ( https://github.com/SciML/SciMLBenchmarks.jl/blob/master/benc... ).
comment by ChrisRackauckas · 2023-01-11 · in Why Fortran is a scientific powerhouse -
…or any of the other C++ solver. (for a bunch of benchmarks vs pretty much everything else, see https://github.com/SciML/SciMLBenchmarks.jl )
comment by adgjlsfhk1 · 2022-04-18 · in Castor: A C++ library to code “à la Matlab” -
…is one part of the DiffEq performance story. The performance of this of course is all validated on https://github.com/SciML/SciMLBenchmarks.jl
comment by ChrisRackauckas · 2022-01-08 · in Fortran is easy to learn -
…for many reasons showcased in the SciMLBenchmarks routinely outperforming C and Fortran solvers ( https://github.com/SciML/SciMLBenchmarks.jl ). So it's excelling pretty well, and things like the automated discovery of black hole dynamics…
comment by ChrisRackauckas · 2021-12-01 · in Julia 1.7 Highlights