Implementing a Sparse Matrix Vector Product for the SELL-C/SELL-C-sigma formats on NVIDIA GPUs

@inproceedings{Anzt2014ImplementingAS,
  title={Implementing a Sparse Matrix Vector Product for the SELL-C/SELL-C-sigma formats on NVIDIA GPUs},
  author={Hartwig Anzt and Stanimire Tomov and Jack J. Dongarra},
  year={2014}
}
Numerical methods in sparse linear algebra typically rely on a fast and efficient matrix vector product, as this usually is the backbone of iterative algorithms for solving eigenvalue problems or linear systems. Against the background of a large diversity in the characteristics of high performance computer architectures, it is a challenge to derive a cross-platform efficient storage format along with fast matrix vector kernels. Recently, attention focused on the SELL-C-σ format, a sliced… CONTINUE READING

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