Hybrid reordering strategies for ILU preconditioning of indefinite sparse matrices

Eun Joo Lee, Jun Zhang

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Incomplete LU factorization preconditioning techniques often have difficulty on indefinite sparse matrices. We present hybrid reordering strategies to deal with such matrices, which include new diagonal reorderings that are in conjunction with a symmetric nondecreasing degree algorithm. We first use the diagonal reorderings to efficiently search for entries of single element rows and columns and/or the maximum absolute value to be placed on the diagonal for computing a nonsymmetric permutation. To augment the effectiveness of the diagonal reorderings, a nondecreasing degree algorithm is applied to reduce the amount of fill-in during the ILU factorization. With the reordered matrices, we achieve a noticeable improvement in enhancing the stability of incomplete LU factorizations. Consequently, we reduce the convergence cost of the preconditioned Krylov subspace methods on solving the reordered indefinite matrices.

Original languageEnglish
Pages (from-to)307-316
Number of pages10
JournalJournal of Applied Mathematics and Computing
Volume22
Issue number1-2
DOIs
StatePublished - Sep 2006

Keywords

  • Indefinite matrix
  • Preconditioning
  • Reordering

ASJC Scopus subject areas

  • Computational Mathematics
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'Hybrid reordering strategies for ILU preconditioning of indefinite sparse matrices'. Together they form a unique fingerprint.

Cite this