A max-plus approach to incomplete Cholesky factorization preconditioners

James Hook, Jennifer Scott, Francoise Tisseur, Jonathan Hogg

Research output: Contribution to journalArticle

Abstract

We present a new method for constructing incomplete Cholesky factorization preconditioners for use in solving large sparse symmetric positive-definite linear systems. This method uses max-plus algebra to predict the positions of the largest entries in the Cholesky factor and then uses these positions as the sparsity pattern for the preconditioner. Our method builds on the max-plus incomplete LU factorization preconditioner recently proposed in J. Hook and F. Tisseur, Incomplete LU preconditioner based on max-plus approximation of {LU} factorization, MIMS Eprint 2016.47, Manchester, 2016 but applied to symmetric positive-definite matrices, which comprise an important special case for the method and its application. An attractive feature of our approach is that the sparsity pattern of each column of the preconditioner can be computed in parallel. Numerical comparisons are made with other incomplete Cholesky factorization preconditioners using problems from a range of practical applications. We demonstrate that the new preconditioner can outperform traditional level-based preconditioners and offer a parallel alternative to a serial
limited-memory based approach.
Original languageEnglish
Pages (from-to)A1987-A2004
Number of pages18
JournalSIAM Journal on Scientific Computing
Volume40
Issue number4
Early online date3 Jul 2018
DOIs
Publication statusPublished - 2 Aug 2018

    Fingerprint

Keywords

  • Hungarian scaling
  • Incomplete factorizations
  • Max-plus algebra
  • Preconditioners
  • Sparse symmetric linear systems
  • Sparsity pattern

ASJC Scopus subject areas

  • Computational Mathematics
  • Applied Mathematics

Cite this