A computational study of sparse matrix storage schemes

dc.contributor.authorHaque, Sardar Anisul
dc.contributor.authorUniversity of Lethbridge. Faculty of Arts and Science
dc.contributor.supervisorHossain, Shahadat
dc.contributor.supervisorGaur, Daya
dc.date.accessioned2009-10-13T15:44:33Z
dc.date.available2009-10-13T15:44:33Z
dc.date.issued2008
dc.degree.levelMasters
dc.descriptionxi, 76 leaves : ill. ; 29 cm.en
dc.description.abstractThe 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.identifier.urihttps://hdl.handle.net/10133/777
dc.language.isoen_USen
dc.publisherLethbridge, Alta. : University of Lethbridge, Deptartment of Mathematics and Computer Science, 2008en
dc.publisher.departmentMathematics and Computer Scienceen
dc.publisher.facultyArts and Scienceen
dc.relation.ispartofseriesThesis (University of Lethbridge. Faculty of Arts and Science)en
dc.subjectSparse matrices -- Data processingen
dc.subjectDissertations, Academicen
dc.titleA computational study of sparse matrix storage schemesen
dc.typeThesisen
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