On preconditioner updates for sequences of saddle-point linear systems

On preconditioner updates for sequences of saddle-point linear systems AbstractUpdating preconditioners for the solution of sequences of large and sparse saddle- point linear systems via Krylov methods has received increasing attention in the last few years, because it allows to reduce the cost of preconditioning while keeping the efficiency of the overall solution process. This paper provides a short survey of the two approaches proposed in the literature for this problem: updating the factors of a preconditioner available in a block LDLT form, and updating a preconditioner via a limited-memory technique inspired by quasi-Newton methods. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Communications in Applied and Industrial Mathematics de Gruyter

On preconditioner updates for sequences of saddle-point linear systems

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Publisher
De Gruyter Open
Copyright
© 2018
ISSN
2038-0909
eISSN
2038-0909
D.O.I.
10.1515/caim-2018-0003
Publisher site
See Article on Publisher Site

Abstract

AbstractUpdating preconditioners for the solution of sequences of large and sparse saddle- point linear systems via Krylov methods has received increasing attention in the last few years, because it allows to reduce the cost of preconditioning while keeping the efficiency of the overall solution process. This paper provides a short survey of the two approaches proposed in the literature for this problem: updating the factors of a preconditioner available in a block LDLT form, and updating a preconditioner via a limited-memory technique inspired by quasi-Newton methods.

Journal

Communications in Applied and Industrial Mathematicsde Gruyter

Published: Feb 28, 2018

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