PARALLEL ALGORITHMS FOR THE ITERATIVE SOLUTION OF SPARSE LEAST-SQUARES PROBLEMS

被引：0

作者：

MORANDI, R ^{[1
]}

SGALLARI, F ^{[1
]}

机构：

[1] UNIV BOLOGNA,DIPARTIMENTO MATEMAT,I-40123 BOLOGNA,ITALY

来源：

PARALLEL COMPUTING | 1990年 / 13卷 / 03期

关键词：

Parallel iterative methods; parallel processors; relaxation parameter; sparse least-squares problems;

D O I：

10.1016/0167-8191(90)90129-W

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this paper, we are concerned with a generalized Gauss-Seidel approach to sparse linear least-squares problems. Two algorithms, related to those given by Schechter (1959), for the solution of linear systems are presented and their parallel implementation is discussed. In these procedures, which can be viewed as an alternative ordering of the variables in the SOR methods, the variables are divided into nondisjoint groups. Numerical results, obtained on CRAY X-MP/48, are presented and discussed. © 1990.

引用

页码：271 / 280

页数：10

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