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

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 auto-selecting 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. © 2011 Springer-Verlag.