Blocked-based sparse matrix-vector multiplication on distributed memory parallel computers

The present paper discusses the implementations of sparse matrix-vector products, which are crucial for high performance solutions of large-scale linear equations, on a PC-Cluster. Three storage formats for sparse matrices compressed row storage, block compressed row storage and sparse block compressed row storage are evaluated. Although using BCRS format reduces the execution time but the improvement may be limited because of the extra work from filled-in zeros. We show that the use of SBCRS not only improves the performance significantly but reduces matrix storage also.