https://github.com/JuliaSparse/MKLSparse.jl

Make available to Julia the sparse functionality in MKL
https://github.com/JuliaSparse/MKLSparse.jl

high-performance julia mkl sparse

Last synced: about 2 months ago
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Make available to Julia the sparse functionality in MKL

• Host: GitHub
• URL: https://github.com/JuliaSparse/MKLSparse.jl
• Owner: JuliaSparse
• License: other
• Created: 2015-06-28T14:14:41.000Z (about 9 years ago)
• Default Branch: master
• Last Pushed: 2024-07-07T23:04:11.000Z (2 months ago)
• Last Synced: 2024-07-08T23:19:43.587Z (2 months ago)
• Topics: high-performance, julia, mkl, sparse
• Language: Julia
• Homepage:
• Size: 120 KB
• Stars: 47
• Watchers: 15
• Forks: 10
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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• awesome-sciml - JuliaSparse/MKLSparse.jl: Make available to Julia the sparse functionality in MKL

README

        
# MKLSparse.jl

`MKLSparse.jl` is a Julia package to seamlessly use the sparse functionality in MKL to speed up operations on sparse arrays in Julia.

In order to use `MKLSparse.jl` you do not need to install Intel's MKL library nor build Julia with MKL. `MKLSparse.jl` will automatically download and use the MKL library for you when installed.

### Matrix multiplications

Loading `MKLSparse.jl` will make sparse-dense matrix operations be computed using MKL.

### Solving linear systems

Solving linear systems with triangular sparse matrices is supported.

These matrices should be wrapped in their corresponding type, for example `LowerTriangular` for lower triangular matrices.

For solving general sparse linear systems using MKL we refer to [Pardiso.jl](https://github.com/JuliaSparse/Pardiso.jl).

## Misc

* The integer type that should be used in order for MKL to be called is the same as used by the Julia BLAS library, see `Base.USE_BLAS64`.

### Possible TODO's

* Wrap BLAS1 (`SparseVector`)

* Wrap DSS

* Wrap Incomplete LU preconditioners