A computational study of sparse matrix storage schemes

Thumbnail Image
Haque, Sardar Anisul
University of Lethbridge. Faculty of Arts and Science
Journal Title
Journal ISSN
Volume Title
Lethbridge, Alta. : University of Lethbridge, Deptartment of Mathematics and Computer Science, 2008
The efficiency of linear algebra operations for sparse matrices on modern high performance computing system is often constrained by the available memory bandwidth. We are interested in sparse matrices whose sparsity pattern is unknown. In this thesis, we study the efficiency of major storage schemes of sparse matrices during multiplication with dense vector. A proper reordering of columns or rows usually results in reduced memory traffic due to the improved data reuse. This thesis also proposes an efficient column ordering algorithm based on binary reflected gray code. Computational experiments show that this ordering results in increased performance in computing the product of a sparse matrix with a dense vector.
xi, 76 leaves : ill. ; 29 cm.
Sparse matrices -- Data processing , Dissertations, Academic