REDUCTION TO CONDENSED FORM FOR THE EIGENVALUE PROBLEM ON DISTRIBUTED MEMORY ARCHITECTURES

被引：32

作者：

DONGARRA, JJ

VANDEGEIJN, RA

机构：

[1] OAK RIDGE NATL LAB,MATH SCI SECT,OAK RIDGE,TN 37831

[2] UNIV TEXAS,DEPT COMP SCI,AUSTIN,TX 78712

来源：

PARALLEL COMPUTING | 1992年 / 18卷 / 09期

基金：

美国国家科学基金会;

关键词：

EIGENVALUE PROBLEM; LINEAR ALGEBRA; LAPACK; DISTRIBUTED MEMORY ARCHITECTURE;

D O I：

10.1016/0167-8191(92)90011-U

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this paper, we describe a parallel implementation for the reduction of general and symmetric matrices to Hessenberg and tridiagonal form, respectively. The methods are based on LAPACK sequential codes and use a panel-wrapped mapping of matrices to nodes. Results from experiments on the Intel Touchstone Delta are given.

引用

页码：973 / 982

页数：10

共 13 条

[1]

ANDERSON E, 1991, 6TH DISTR MEM COMP C, P287

[2] A PARALLEL HOUSEHOLDER TRIDIAGONALIZATION STRATAGEM USING SCATTERED SQUARE DECOMPOSITION [J].