A max-plus approach to incomplete Cholesky factorization preconditioners

Full text not archived in this repository.

Please see our End User Agreement.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Hook, J., Scott, J. ORCID: https://orcid.org/0000-0003-2130-1091, Tisseur, F. and Hogg, J. (2018) A max-plus approach to incomplete Cholesky factorization preconditioners. SIAM Journal on Scientific Computing, 40 (4). A1987-A2004. ISSN 1064-8275 doi: 10.1137/16M1107735

Abstract/Summary

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.

Altmetric Badge

Dimensions Badge

Item Type Article
URI https://reading-pure-test.eprints-hosting.org/id/eprint/76701
Identification Number/DOI 10.1137/16M1107735
Refereed Yes
Divisions Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics
Central Services
Download/View statistics View download statistics for this item

University Staff: Request a correction | Centaur Editors: Update this record