Evaluation of parallel sparse matrix partitioning software for parallel multilevel ilu preconditioning on shared-memory multiprocessors

José I. Aliaga, Matthias Bollhöfer, Alberto F. Martín, Enrique S. Quintana-Ortí

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In this paper we analyze the performance of two parallel sparse matrix partitioning software packages, ParMETIS and PT-SCOTCH. We focus our analysis on the parallel performance of the nested dissection partitioning stage as well as its impact on the performance of the numerical stages of the solution of sparse linear systems via multilevel ILU preconditioned iterative methods. Experimental results on a shared-memory platform with 16 processors show that ParMETIS seems to be the best choice for our approach.

Original languageEnglish
Title of host publicationParallel Computing
Subtitle of host publicationFrom Multicores and GPU's to Petascale
PublisherIOS Press
Number of pages8
ISBN (Print)9781607505297
Publication statusPublished - 1 Jan 2010
Externally publishedYes

Publication series

NameAdvances in Parallel Computing
ISSN (Print)0927-5452


  • factorization-based preconditioning
  • large sparse linear systems
  • nested dissection
  • parallel partitioning software
  • shared-memory multiprocessors

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