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: 3 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 10 years ago)
• Default Branch: master
• Last Pushed: 2025-01-20T20:03:26.000Z (6 months ago)
• Last Synced: 2025-03-30T05:07:46.183Z (4 months ago)
• Topics: high-performance, julia, mkl, sparse
• Language: Julia
• Homepage:
• Size: 166 KB
• Stars: 53
• Watchers: 14
• Forks: 10
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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README

        
# MKLSparse.jl

[![codecov](https://codecov.io/gh/JuliaSparse/MKLSparse.jl/graph/badge.svg?token=j3KoKBEIt1)](https://codecov.io/gh/JuliaSparse/MKLSparse.jl)

*MKLSparse.jl* is a Julia package to seamlessly use the [sparse BLAS routines from Intel's Math Kernel Library (MKL)](https://www.intel.com/content/www/us/en/docs/onemkl/developer-reference-c)

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