From 9db4f2a3eb85946b484fc45cd8cfca70ef5880ff Mon Sep 17 00:00:00 2001 From: Wimmerer Date: Mon, 11 Apr 2022 09:46:57 -0400 Subject: [PATCH 1/2] add callouts --- docs/src/index.md | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/docs/src/index.md b/docs/src/index.md index b463a855..d22368a6 100644 --- a/docs/src/index.md +++ b/docs/src/index.md @@ -233,3 +233,14 @@ permute!{Tv, Ti, Tp <: Integer, Tq <: Integer}(::SparseMatrixCSC{Tv,Ti}, ::Spars ```@meta DocTestSetup = nothing ``` +# Noteworthy external packages + +Several other Julia packages provide sparse matrix implementations that should be mentioned: + +1. [SuiteSparseGraphBLAS.jl](https://github.com/JuliaSparse/SuiteSparseGraphBLAS.jl) is a wrapper over the fast and flexible SuiteSparse:GraphBLAS C library. On CPU this is typically the fastest option, often significantly outperforming MKLSparse. + +2. [CUDA.jl](https://github.com/JuliaGPU/CUDA.jl) exposes the [CUSPARSE](https://docs.nvidia.com/cuda/cusparse/index.html) library for GPU sparse matrix operations. + +3. [SparseMatricesCSR.jl](https://github.com/gridap/SparseMatricesCSR.jl) provides a Julia native implementation of the Compressed Sparse Rows (CSR) format. + +4. [MKLSparse.jl](https://github.com/JuliaSparse/MKLSparse.jl) accelerates SparseArrays sparse-dense matrix operations using Intel's MKL library. \ No newline at end of file From c07c0062dfc3caca76376bce2eb9cb1718ca4be5 Mon Sep 17 00:00:00 2001 From: Wimmerer Date: Mon, 11 Apr 2022 09:47:33 -0400 Subject: [PATCH 2/2] be more objective --- docs/src/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/src/index.md b/docs/src/index.md index d22368a6..c0320c05 100644 --- a/docs/src/index.md +++ b/docs/src/index.md @@ -237,7 +237,7 @@ DocTestSetup = nothing Several other Julia packages provide sparse matrix implementations that should be mentioned: -1. [SuiteSparseGraphBLAS.jl](https://github.com/JuliaSparse/SuiteSparseGraphBLAS.jl) is a wrapper over the fast and flexible SuiteSparse:GraphBLAS C library. On CPU this is typically the fastest option, often significantly outperforming MKLSparse. +1. [SuiteSparseGraphBLAS.jl](https://github.com/JuliaSparse/SuiteSparseGraphBLAS.jl) is a wrapper over the fast, multithreaded SuiteSparse:GraphBLAS C library. On CPU this is typically the fastest option, often significantly outperforming MKLSparse. 2. [CUDA.jl](https://github.com/JuliaGPU/CUDA.jl) exposes the [CUSPARSE](https://docs.nvidia.com/cuda/cusparse/index.html) library for GPU sparse matrix operations.