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Accelerate eigs with GPU

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Sven Auschra
Sven Auschra on 29 Jul 2020
Commented: Bruno Luong on 30 Jul 2020
Dear all,
I have implemented a numerical solver (of the Fokker-Planck equation) in MATLAB.
At some point, the algorithm needs to calculate
eigs(L, 1, 0)
of a very large sparse matrix L.
I would like to perform this calculation on a GPU to lower the computational costs. So, I created the array
Lgpu = gpuArray(L);
on the GPU and tried to calculate
eigs(Lgpu, 1, 0)
again.
Unfortunately, I receive the error message: "First argument must be a double matrix or a function."
I am wondering what the cause of this error might be and appreciate any help from you.
Thank you very much.
best,
Sven

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Answers (2)

Walter Roberson
Walter Roberson on 29 Jul 2020
There is no GPU support for sparse arrays.

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Edric Ellis
Edric Ellis on 30 Jul 2020
This is no longer correct, support for sparse gpuArray was added in R2015a.

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Christine Tobler
Christine Tobler on 30 Jul 2020
Edited: Edric Ellis on 30 Jul 2020
The eigs function is not supported on the GPU. There is support for sparse matrices on the GPU, since R2015a: Release notes parallel computing toolbox.
You could pass a function handle to EIGS that would use computation on the GPU, but would need to accept and pass back out vectors on the CPU. I'm not sure how efficient that would be, but it could be worth a try.

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Christine Tobler
Christine Tobler on 30 Jul 2020
Bruno, it looks like we were posting at the same time there. Using Lgpu\gpuArray(x) will definitely work, but since backslash is called many times here, to be efficient Lgpu should be factorized and this factorization used in the function handle. Otherwise I'd expect that the CPU version will still be faster.
Unfortunately, LU doesn't support sparse gpuArrays at this point, which means we have to call backslash which will compute this factorization underneath on every call.
Overall, it's worth trying out these ideas, but I kind of expect that while they will move some computation to the GPU, they won't actually make your EIGS call faster than the CPU version, because gpuArray doesn't yet support all tools to get the best possible performance out of EIGS.
Sven Auschra
Sven Auschra on 30 Jul 2020
Thank you so much for your support.
Unfortunately, calculations on the GPU (Kepler K20) are by a factor of 17 slower than on the CPU. So, I guess I will stick to calculating EIGS on the latter one.
Anyway, thank you so much. I really appreciate it.
Bruno Luong
Bruno Luong on 30 Jul 2020
Yeah I would also expect any speedup using GPU. Mostly EIGS on sparse is mainly an iterative process in double layers. Nothing really leans for GPU computation.

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