A Fully Parallel Algorithm for the Symmetric Eigenvalue Problem

In this paper we present a parallel algorithm for the symmetric algebraic eigenvalue problem. The algorithm is based upon a divide and conquer scheme suggested by Cuppen for computing the eigensystem of a symmetric tridiagonal matrix. We extend this idea to obtain a parallel algorithm that retains a...

Full description

Saved in:
Bibliographic Details
Published in:SIAM journal on scientific and statistical computing Vol. 8; no. 2; pp. s139 - s154
Main Authors: Dongarra, J. J., Sorensen, D. C.
Format: Journal Article
Language:English
Published: Philadelphia, PA Society for Industrial and Applied Mathematics 01.03.1987
Subjects:
Algorithms
Computational mathematics
Eigenvalues
Eigenvectors
Exact sciences and technology
Mathematics
Matrix
Numerical analysis
Numerical analysis. Scientific computation
Numerical linear algebra
Sciences and techniques of general use
Parallel algorithm
Mathematical matrix
Eigenvalue problem
Symmetric matrix
ISSN:0196-5204, 1064-8275, 2168-3417, 1095-7197
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper we present a parallel algorithm for the symmetric algebraic eigenvalue problem. The algorithm is based upon a divide and conquer scheme suggested by Cuppen for computing the eigensystem of a symmetric tridiagonal matrix. We extend this idea to obtain a parallel algorithm that retains a number of active parallel processes that is greater than or equal to the initial number throughout the course of the computation. We give a new deflation technique which together with a robust root finding technique will assure computation of an eigensystem to full accuracy in the residuals and in the orthogonality of eigenvectors. A brief analysis of the numerical properties and sensitivity to round off error is presented to indicate where numerical difficulties may occur. The algorithm is able to exploit parallelism at all levels of the computation and is well suited to a variety of architectures. Computational results are presented for several machines. These results are very encouraging with respect to both accuracy and speedup. A surprising result is that the parallel algorithm, even when run in serial mode, can be significantly faster than the previously best sequential algorithm on large problems, and is effective on moderate size problems when run in serial mode.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
content type line 14
ISSN:0196-5204
1064-8275
2168-3417
1095-7197
DOI:10.1137/0908018