A survey of sparse matrix-vector multiplication performance on large matrices
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}
}
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).
August 4, 2016 by hgpu
