"Gutenkunst, Ryan N - (rgutenk)" <rgut...@arizona.edu> writes:
> Hello, > > I need to access the tridiagonal solving routines gtsv2StridedBatch > and gtsvInterleavedBatch from the cuSPARSE library in a Python/C > program. Is there a way to access/link to the cuSPARSE library using > PyCUDA? > > For background, I’m hoping to port a Python (with inner loops in C) > application to leverage GPU computing. The most intensive part of the > computation is solving tridiagonal systems, so I was excited to see > that the standard cuSPARSE library includes routines for this. But I’m > struggling to see how to access cuSPARSE using any of the existing > Python to CUDA interfaces. For PyCUDA, I couldn’t find a similar > example in the documentation. Pyculib has bindings for an older > version of cuSPARSE, but it’s not maintained and I couldn’t get it > installed easily: > https://pyculib.readthedocs.io/en/latest/cusparse.html. CuPy seems to > support only a very small fraction of cuSPARSE: > https://docs-cupy.chainer.org/en/stable/reference/sparse.html . There's scikit.cuda, which offers access to cuSOLVER, which bills itself as "the CUDA sparse matix library." https://scikit-cuda.readthedocs.io/en/latest/ There's also discussion going on about adapting PyCUDA to Nvidia's "primary context" notion for easier interoperability with the runtime API. Hope that helps, Andreas
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