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S+: Efficient 2D sparse LU factorization on parallel machines

  • University of California at Santa Barbara

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Static symbolic factorization coupled with supernode partitioning and asynchronous computation scheduling can achieve high gigaflop rates for parallel sparse LU factorization with partial pivoting. This paper studies properties of elimination forests and uses them to optimize supernode partitioning/amalgamation and execution scheduling. It also proposes supernodal matrix multiplication to speed up kernel computation by retaining the BLAS-3 level efficiency and avoiding unnecessary arithmetic operations. The experiments show that our new design with proper space optimization, called S+, improves our previous solution substantially and can achieve up to 10 GFLOPS on 128 Cray T3E 450MHz nodes.

Original languageEnglish
Pages (from-to)282-305
Number of pages24
JournalSIAM Journal on Matrix Analysis and Applications
Volume22
Issue number1
DOIs
StatePublished - 2000

Keywords

  • Asynchronous computation scheduling
  • Elimination forests
  • Gaussian elimination with partial pivoting
  • LU factorization
  • Sparse matrices
  • Supernode amalgamation and partitioning

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