JOURNAL ARTICLE

An Implementation of Gaussian Elimination with Partial Pivoting for Sparse Systems

Alan D. GeorgeEsmond Ng

Year: 1985 Journal:   SIAM Journal on Scientific and Statistical Computing Vol: 6 (2)Pages: 390-409   Publisher: Society for Industrial and Applied Mathematics

Abstract

In this paper, we consider the problem of solving a sparse nonsingular system of linear equations. We show that the structures of the triangular matrices obtained in the $LU$-decomposition of a sparse nonsingular matrix A using Gaussian elimination with partial pivoting are contained in those of the Cholesky factors of $A^T A$, provided that the diagonal elements of A are nonzero. Based on this result, a method for solving sparse linear systems is then described. The main advantage of this method is that the numerical computation can be carried out using a static data structure. Numerical experiments comparing this method with other implementations of Gaussian elimination for solving sparse linear systems are presented and the results indicate that the method proposed in this paper is quite competitive with other approaches.

Keywords:
Gaussian elimination Cholesky decomposition Sparse matrix Linear system Invertible matrix Applied mathematics Mathematics LU decomposition Sparse approximation Gaussian Matrix (chemical analysis) Algorithm System of linear equations Computation Diagonal Mathematical optimization Matrix decomposition Mathematical analysis Pure mathematics Eigenvalues and eigenvectors

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77
Cited By
4.78
FWCI (Field Weighted Citation Impact)
19
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0.95
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Citation History

Topics

Matrix Theory and Algorithms
Physical Sciences →  Computer Science →  Computational Theory and Mathematics
Computational Geometry and Mesh Generation
Physical Sciences →  Computer Science →  Computer Graphics and Computer-Aided Design
Advanced Graph Theory Research
Physical Sciences →  Computer Science →  Computational Theory and Mathematics

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