2006Journal of Changchun University of Science and TechnologyRequires access

Sparse Storage Technique for Sparse Matrix

Sun Qin

Open publisher page 1 citations

Abstract

In the computational field of science and engineering, many problems finally go to solve sparse linear equations and the sparse matrix has a few nonzero elements. For saving storage of computer and quickening elements' operation, it is very necessary to study storage technique for sparse matrix. Based on basal storage technique for matrix, this paper introduces some common storage methods for sparse matrix. After analyzing advantages and disadvantages of the methods, we show applied conditions for them. It is anticipant to provide some availability ways about effective solution for sparse linear equations.

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What this paper is about

In the computational field of science and engineering, many problems finally go to solve sparse linear equations and the sparse matrix has a few nonzero elements. For saving storage of computer and quickening elements' operation, it is very necessary to study storage technique for sparse matrix. Based on basal storage technique for matrix, this paper introduces some common storage methods for sparse matrix. After analyzing advantages and disadvantages of the methods, we show applied conditions for them. It is anticipant to provide some availability ways about effective solution for sparse linear equations.

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Available abstract

In the computational field of science and engineering, many problems finally go to solve sparse linear equations and the sparse matrix has a few nonzero elements. For saving storage of computer and quickening elements' operation, it is very necessary to study storage technique for sparse matrix. Based on basal storage technique for matrix, this paper introduces some common storage methods for sparse matrix. After analyzing advantages and disadvantages of the methods, we show applied conditions for them. It is anticipant to provide some availability ways about effective solution for sparse linear equations.

Key concepts: Matrix-free methods, Sparse matrix, Sparse approximation, Matrix (chemical analysis), Computer science, Computer data storage, Quickening, Field (mathematics)

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