Parallel preconditioned conjugate gradient optimization of the Rayleigh quotient for the solution of sparse eigenproblems

被引：10

作者：

Bergamaschi, Luca ^{[1
]}

Martinez, Angeles ^{[1
]}

Pini, Giorgio ^{[1
]}

机构：

[1] Univ Padua, Dept Math Methods & Models Sci Applicat, I-35100 Padua, Italy

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2006年 / 175卷 / 02期

关键词：

D O I：

10.1016/j.amc.2005.09.015

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

A parallel algorithm based on the multidimensional minimization of the Rayleigh quotient is proposed to evaluate the leftmost eigenpairs of the generalized symmetric positive definite eigenproblem. The minimization is performed via a conjugate gradient-like procedure accelerated by a factorized approximate inverse preconditioner (FSAI) and by a number of block preconditioners. The resulting code obtains a high level of parallel efficiency and proves to be comparable with the PARPACK package on a set of large matrices arising from various discretizations of PDEs of elliptic/parabolic type. (c) 2005 Elsevier Inc. All rights reserved.

引用

页码：1694 / 1715

页数：22

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