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A survey of sparse matrix-vector multiplication performance on large matrices

Max Grossman, Christopher Thiele, Mauricio Araya-Polo, Florian Frank, Faruk O. Alpak, Vivek Sarkar
Rice University
arXiv:1608.00636 [cs.PF], (1 Aug 2016)

@article{grossman2016survey,

   title={A survey of sparse matrix-vector multiplication performance on large matrices},

   author={Grossman, Max and Thiele, Christopher and Araya-Polo, Mauricio and Frank, Florian and Alpak, Faruk O. and Sarkar, Vivek},

   year={2016},

   month={aug},

   archivePrefix={"arXiv"},

   primaryClass={cs.PF}

}

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We contribute a third-party survey of sparse matrix-vector (SpMV) product performance on industrial-strength, large matrices using: (1) The SpMV implementations in Intel MKL, the Trilinos project (Tpetra subpackage), the CUSPARSE library, and the CUSP library, each running on modern architectures. (2) NVIDIA GPUs and Intel multi-core CPUs (supported by each software package). (3) The CSR, BSR, COO, HYB, and ELL matrix formats (supported by each software package).
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