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I built Julia, which incorporates SuiteSparse, from scratch. When building the SuiteSparse dependency I ensured the instructions were followed for setting the relevant parts of the SuiteSparse_config.mk file.

However, having completed the build the execution time for c = A\b with 220k unknowns (very regular structure for A) isn't changed.

How can I test whether CHOLMOD is actively using the GPU or not?

Michael Ohlrogge
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    I do not know the details about GPU acceleration with SuiteSparse, but wouldn't you need to explicitly push the matrix to the GPU? Base Julia doesn't ship with GPU facilities. You can find them under the [JuliaParallel](https://github.com/JuliaParallel) umbrella. – Kevin L. Keys May 28 '16 at 01:51
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    Have you looked into the CUSPARSE package for sparse matrices on GPUs? – Michael Ohlrogge Jun 07 '16 at 18:09
  • @KevinLKeys , it's an option in compiling CHOLMOD that gets handled in the background. – conjectures Jun 08 '16 at 15:41
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    @aireties CUSPARSE and CHOLMOD don't implement the same set of functions. Also, CHOLMOD is already integrated with the rest of Julia, and so enabling its GPU capabilities would make it trivial to use with "\". – conjectures Jun 08 '16 at 15:42
  • @conjectures maybe file an issue at Julia base? they would understand build issues best – Kevin L. Keys Jun 09 '16 at 21:49

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I did notice that something similar was asked here. It was for a C/CUDA environment, but perhaps it applies.

From that answer:

Only the long integer version of CHOLMOD can leverage GPU acceleration. The long integer version is distinguished by api calls like cholmod_l_start instead of cholmod_start.

It may be the case that Julia does not use the "long integer" version of CHOLMOD calls. I see no evidence for it in cholmod.jl.

As I said earlier, perhaps one of the Julia Language developers will pipe up if you file the issue in the repo. Otherwise, you may need to build Julia after changing cholmod.jl first.

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