FINDING EIGENVALUES AND EIGENVECTORS OF UNSYMMETRIC MATRICES USING A DISTRIBUTED-MEMORY MULTIPROCESSOR

被引：9

作者：

GEIST, GA ^{[1
]}

DAVIS, GJ ^{[1
]}

机构：

[1] GEORGIA STATE UNIV,ATLANTA,GA 30303

来源：

PARALLEL COMPUTING | 1990年 / 13卷 / 02期

关键词：

hypercube multiprocessor; INTEL iPSC/2; Linear algebra; timing results; unsymmetric eigenvalue/eigenvector problem;

D O I：

10.1016/0167-8191(90)90147-2

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Distrubuted-memory parallel algorithms for finding the eigenvalues and eigenvectors of a dense unsymmetric matrix are given. While several parallel algorithms have been developed for symmetric matrices, little work has been done on the unsymmetric case. Our parallel implementation proceeds in three major steps: reduction of the original matrix to Hessenberg form, application of the implicit double-shift QR algoritm to compute the eigenvalues, and back transformations to compute the eigenvectors. Several modifications to our parallel QR algorithm, including ring communication, pipelining and delayed updating are discussed and compared. Results and timings are given. © 1990.

引用

页码：199 / 209

页数：11

共 12 条

[1]

BOLEY D, 1988, SIAM ANN M MINNEAPOL

[2]

CUPPEN JJM, 1981, NUMER MATH, V36, P177, DOI 10.1007/BF01396757

[3] A FULLY PARALLEL ALGORITHM FOR THE SYMMETRICAL EIGENVALUE PROBLEM [J].