Dissertation/ Thesis

A Computational study of sparse or structured matrix operations

Bibliographic Details
Title: A Computational study of sparse or structured matrix operations
Authors: Aimaiti, Nuerrennisahan (Nurgul), University of Lethbridge. Faculty of Arts and Science
Contributors: Hossain, Shahadat
Publisher Information: Universtiy of Lethbridge, Department of Mathematics and Computer Science
Department of Mathematics and Computer Science
Arts and Science
Publication Year: 2018
Collection: University of Lethbridge Institutional Repository
Subject Terms: Sparse matrices -- Data processing, Java (Computer program language), Algebras, linear, High performance computing, Mathematical optimization -- Data processing, Numerical calculations -- Data processing, sparse data structure, CRS, Compressed Row Storage, JSA, Java Sparse Array, diagonal, BLAS, Basic Linear Algebra Subroutines
Description: Matrix 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.
Document Type: thesis
File Description: application/pdf
Language: English
Relation: Thesis (University of Lethbridge. Faculty of Arts and Science); https://hdl.handle.net/10133/5268
Availability: https://hdl.handle.net/10133/5268
Accession Number: edsbas.FAD7E847
Database: BASE
Description
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