sparse in cuda matlab shows bad performance

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俊凯 王
俊凯 王 on 5 Nov 2021
Answered: Joss Knight on 6 Nov 2021
This question is simple
I understand that MATLAB solves sparse linear equations by multi wavefront method on CPU
like sparse_a Is a sparse b is a full vector then x can be computed by x=sparse_a\b
is there any method to let matlab compute sparse in gpu?
gpu_sparse_a=gpuArray(sparse_a ) b_gpu=gpuArray(b)
and then x=gpu_sparse_a\b_gpu
result shows that gpu compute sparse slower than cpu....why?is sparse in cpu transfer into gpu actually become a full matrix?
  5 Comments
俊凯 王
俊凯 王 on 5 Nov 2021
and i wonder if the sparse solver on the CPU uses a multi-core CPU

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Accepted Answer

Joss Knight
Joss Knight on 6 Nov 2021
It is often slower. The problem is that sparse factorizations create dense matrices...basically, it's hard to parallelize.
We generally advise to use the sparse iterative solvers, generally with preconditioners, instead. These are typically faster on GPU and CPU. Look for gmres, cgs, pcg and so on.

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