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dc.contributor.supervisor Hossain, Shahadat
dc.contributor.supervisor Gaur, Daya Haque, Sardar Anisul University of Lethbridge. Faculty of Arts and Science 2009-10-13T15:44:33Z 2009-10-13T15:44:33Z 2008
dc.description xi, 76 leaves : ill. ; 29 cm. en
dc.description.abstract 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. en
dc.language.iso en_US en
dc.publisher Lethbridge, Alta. : University of Lethbridge, Deptartment of Mathematics and Computer Science, 2008 en
dc.relation.ispartofseries Thesis (University of Lethbridge. Faculty of Arts and Science) en
dc.subject Sparse matrices -- Data processing en
dc.subject Dissertations, Academic en
dc.title A computational study of sparse matrix storage schemes en
dc.type Thesis en
dc.publisher.faculty Arts and Science en
dc.publisher.department Mathematics and Computer Science en Masters

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