# Apple Accelerate Sparse Solvers

**URL:** <https://discourse.julialang.org/t/apple-accelerate-sparse-solvers/110175>\
**Category:** General Usage\
**Created:** [February 13, 2024, 9:56pm UTC](https://discourse.julialang.org/t/apple-accelerate-sparse-solvers/110175 "2024-02-13T21:56:59Z")\
**Posts on this page:** 1\
**Showing post:** 14

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**Author:** ![gdalle](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/gdalle/32/27854_2.png) [@gdalle](https://discourse.julialang.org/u/gdalle)\
**Post date:** [May 27, 2026, 8:18am UTC](https://discourse.julialang.org/t/apple-accelerate-sparse-solvers/110175/14 "2026-05-27T08:18:43Z")

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This looks awesome, thank you so much! Do you have any idea whether something similar is possible for Metal.jl?

> [@Sparse matrix multiplication for Metal](https://discourse.julialang.org/t/sparse-matrix-multiplication-for-metal/131088):
>
> I need to perform a multiplication between two fairly large sparse matrices C = A \* B and I would like to try using the GPU for that. The problem arises in a context where A represents a fixed 2D convolution kernel, while B represents a list of 2D images (each of which is a column of B). Therefore, if necessary, I can easily change the storage scheme of A without a significant penalty. I can easily do this operation with CUDA, but I could not find any way to perform sparse matrix products with …

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