JOURNAL ARTICLE

A Max-Plus Approach to Incomplete Cholesky Factorization Preconditioners

James HookJ. A. ScottFrançoise TisseurJonathan Hogg

Year: 2018 Journal:   SIAM Journal on Scientific Computing Vol: 40 (4)Pages: A1987-A2004   Publisher: Society for Industrial and Applied Mathematics

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\nincomplete LU factorization preconditioner\nrecently 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. A 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.

Keywords:
Cholesky decomposition Incomplete Cholesky factorization Preconditioner Incomplete LU factorization Minimum degree algorithm Factorization Mathematics Positive-definite matrix Sparse matrix Matrix (chemical analysis) Applied mathematics Matrix decomposition Algorithm Algebra over a field Iterative method Pure mathematics Eigenvalues and eigenvectors Computational chemistry

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Citation History

Topics

Matrix Theory and Algorithms
Physical Sciences →  Computer Science →  Computational Theory and Mathematics
Electromagnetic Scattering and Analysis
Physical Sciences →  Physics and Astronomy →  Atomic and Molecular Physics, and Optics
Advanced Optimization Algorithms Research
Physical Sciences →  Mathematics →  Numerical Analysis

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