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.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:ALU.w.uleth.ca/dspace#10133/777 |
| Date | January 2008 |
| Creators | Haque, Sardar Anisul, University of Lethbridge. Faculty of Arts and Science |
| Contributors | Hossain, Shahadat, Gaur, Daya |
| Publisher | Lethbridge, Alta. : University of Lethbridge, Deptartment of Mathematics and Computer Science, 2008, Arts and Science, Mathematics and Computer Science |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
| Relation | Thesis (University of Lethbridge. Faculty of Arts and Science) |
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