Optimization of sparse matrix-vector multiplication by auto selecting storage schemes on GPU

Authors:
Yuji Kubota;Daisuke Takahashi
Affiliations:
Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba, Ibaraki, Japan;Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba, Ibaraki, Japan
Venue:
ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part II
Year:
2011

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Abstract

Sparse matrix vector multiplication is one of the most often used functions in scientific and engineering computing. Though, various storage schemes for sparse matrices have been proposed, the optimal storage scheme is dependent upon the matrix being stored. In this paper, we will propose an autoselecting algorithm for sparse matrix vector multiplication on GPUs that automatically selects the optimal storage scheme. We evaluated our algorithm using a solver for systems of linear equations. As a result, we found that our algorithm was effective for many sparse matrices.