- TriangularSolve.jl VS Pkg.jl
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- TriangularSolve.jl VS BLIS.jl
- TriangularSolve.jl VS rr
- TriangularSolve.jl VS MPI.jl
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- TriangularSolve.jl VS CUDA.jl
- TriangularSolve.jl VS quickjs
- TriangularSolve.jl VS Octavian.jl
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NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better TriangularSolve.jl alternative or higher similarity.
TriangularSolve.jl reviews and mentions
Posts with mentions or reviews of TriangularSolve.jl.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-01-07.
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Why Fortran is easy to learn
> 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
Stats
Basic TriangularSolve.jl repo stats
1
12
6.6
15 days ago
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.
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