A Computational study of sparse or structured matrix operations

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dc.contributor.authorAimaiti, Nuerrennisahan (Nurgul)
dc.contributor.authorUniversity of Lethbridge. Faculty of Arts and Science
dc.contributor.supervisorHossain, Shahadat
dc.date.accessioned2019-01-18T19:00:24Z
dc.date.available2019-01-18T19:00:24Z
dc.date.issued2018
dc.degree.levelMastersen_US
dc.description.abstractMatrix computation is an important area in high-performance scientific computing. Major computer manufacturers and vendors typically provide architecture- aware implementation libraries such as Basic Linear Algebra Subroutines (BLAS). In this thesis, we perform an experimental study of a subset of matrix operations, where the matrices are dense, sparse, or structured in Java. We implement a subset of BLAS operations in Java and compare their performance with standard data structures Compressed Row Storage (CRS) and Java Sparse Array (JSA) for dense and sparse structured matrices. The diagonal storage format is shown to be a viable alternative for dense and structured matrices.en_US
dc.embargoNoen_US
dc.identifier.urihttps://hdl.handle.net/10133/5268
dc.language.isoen_USen_US
dc.proquestyesNoen_US
dc.publisherLethbridge, Alta. : Universtiy of Lethbridge, Department of Mathematics and Computer Scienceen_US
dc.publisher.departmentDepartment of Mathematics and Computer Scienceen_US
dc.publisher.facultyArts and Scienceen_US
dc.relation.ispartofseriesThesis (University of Lethbridge. Faculty of Arts and Science)en_US
dc.subjectSparse matrices -- Data processingen_US
dc.subjectJava (Computer program language)en_US
dc.subjectAlgebras, linearen_US
dc.subjectHigh performance computingen_US
dc.subjectMathematical optimization -- Data processingen_US
dc.subjectNumerical calculations -- Data processingen_US
dc.subjectsparse data structureen_US
dc.subjectCRSen_US
dc.subjectCompressed Row Storageen_US
dc.subjectJSAen_US
dc.subjectJava Sparse Arrayen_US
dc.subjectdiagonalen_US
dc.subjectBLASen_US
dc.subjectBasic Linear Algebra Subroutinesen_US
dc.titleA Computational study of sparse or structured matrix operationsen_US
dc.typeThesisen_US
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