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Anyone knows a good library which implements basic sparse matrix operations such as transpose, SpMV eigenvalues etc. in GPU (cuda/opencl) .

Thanks

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Well, there's Cusp, and for SpMV, there's this technical report by NVIDIA, but I'm skeptical of doing sparse linear algebra on GPUs (see On the limits of GPU acceleration by Vuduc, et al, whose work is reputable). You're probably better off trying to do the sparse linear algebra on CPUs. –  Geoff Oxberry Nov 30 '12 at 6:33
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Hi zimbra, welcome to scicomp! Can you give a few more details about your application domain, expected problem sizes, and whether you would like to take advantages of multiple GPUs on distributed nodes (like a GPU-based cluster or supercomputer)? –  Aron Ahmadia Nov 30 '12 at 22:31
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2 Answers 2

Check ViennaCL. I use that library in many projects to improve performance of sparse operations and I am very pleased with the results. Remember that using GPU makes sense only for relatively large size of the jobs. Otherwise, it is not cost-effective.

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Thanks for suggestion. I was already looking into it. –  zimbra314 Dec 3 '12 at 20:49
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The cuSPARSE library is the official library developed by Nvidia and comes with the CUDA SDK, it implements a lot of sparse matrix operations.

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