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Why Fortran is easy to learn
19 projects | news.ycombinator.com | 7 Jan 2022

> But in the end, it's FORTRAN all the way down. Even in Julia.
That's not true. None of the Julia differential equation solver stack is calling into Fortran anymore. We have our own BLAS tools that outperform OpenBLAS and MKL in the instances we use it for (mostly LU-factorization) and those are all written in pure Julia. See https://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 course is all validated on https://github.com/SciML/SciMLBenchmarks.jl

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JuliaSIMD/TriangularSolve.jl is an open source project licensed under MIT License which is an OSI approved license.

The primary programming language of TriangularSolve.jl is Julia.