Sparse approximate inverse and multilevel block ILU preconditioning techniques for general sparse matrices

Jun Zhang

Research output: Contribution to journalArticlepeer-review

21 Scopus citations

Abstract

We investigate the use of sparse approximate inverse techniques in a multilevel block ILU preconditioner to design a robust and efficient parallelizable preconditioner for solving general sparse matrices. The resulting preconditioner retains robustness of the multilevel block ILU preconditioner (BILUM) and offers a convenient means to control the fill-in elements when large size blocks (subdomains) are used to form block independent set. Moreover, the new implementation of BILUM with a sparse approximate inverse strategy affords maximum parallelism for operations within each level as well as for the coarsest level solution. Thus it has two advantages over the standard BILUM preconditioner: the ability to control sparsity and increased parallelism. Numerical experiments are used to show the effectiveness and efficiency of the proposed variant of BILUM.

Original languageEnglish
Pages (from-to)67-86
Number of pages20
JournalApplied Numerical Mathematics
Volume35
Issue number1
DOIs
StatePublished - Sep 2000

Bibliographical note

Funding Information:
I This research was supported in part by the University of Kentucky Center for Computational Sciences. E-mail address: jzhang@cs.uky.edu (J. Zhang). 1URL: http://www.cs.uky.edu/∼jzhang.

ASJC Scopus subject areas

  • Numerical Analysis
  • Computational Mathematics
  • Applied Mathematics

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