GENERALIZED PRECONDITIONED LOCALLY HARMONIC RESIDUAL METHOD FOR NON-HERMITIAN EIGENPROBLEMS

被引：15

作者：

Vecharynski, Eugene ^{[1
]}

Yang, Chao ^{[1
]}

Xue, Fei ^{[2
]}

机构：

[1] Univ Calif Berkeley, Lawrence Berkeley Natl Lab, Computat Res Div, Berkeley, CA 94720 USA

[2] Univ Louisiana Lafayette, Dept Math, Lafayette, LA 70504 USA

来源：

SIAM JOURNAL ON SCIENTIFIC COMPUTING | 2016年 / 38卷 / 01期

基金：

美国国家科学基金会;

关键词：

eigenvalue; eigenvector; non-Hermitian; preconditioned eigensolver; COMPUTING EIGENVALUES; DAVIDSON METHOD; ARNOLDI METHOD; ALGORITHMS; ITERATION;

D O I：

10.1137/15M1027413

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

We introduce the generalized preconditioned locally harmonic residual (GPLHR) method for solving standard and generalized non-Hermitian eigenproblems. The method is particularly useful for computing a subset of eigenvalues, and their eigen-or Schur vectors, closest to a given shift. The proposed method is based on block iterations and can take advantage of a preconditioner if it is available. It does not need to perform exact shift-and-invert transformation. Standard and generalized eigenproblems are handled in a unified framework. Our numerical experiments demonstrate that GPLHR is generally more robust and efficient than existing methods, especially if the available memory is limited.

引用

页码：A500 / A527

页数：28