A fully parallel block independent set algorithm for distributed sparse matrices

Chi Shen, Jun Zhang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


We present a fully parallel algorithm for constructing block independent set for general sparse matrices in a distributed environment. The block independent set is used in the construction of parallel multilevel preconditioners in solving large sparse matrices on distributed memory parallel computers. We compare a few implementations of the parallel multilevel ILU preconditioners with different block independent set construction strategies. Numerical experiments indicate that the parallel block independent set algorithm is effective in reducing both the parallel multilevel preconditioner construction time and the size of the last level reduced system.

Original languageEnglish
Pages (from-to)1685-1699
Number of pages15
JournalParallel Computing
Issue number11-12 SPEC.ISS.
StatePublished - Nov 2003


  • Block independent set
  • Distributed sparse matrices
  • Parallel multilevel preconditioning

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Networks and Communications
  • Computer Graphics and Computer-Aided Design
  • Artificial Intelligence


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