Communications in Numerical Methods in Engineering - Articles published in this section are of a more general engineering nature and do not necessarily have biomedical applications
Factorized parallel preconditioner for the saddle point problem
Article first published online: 22 DEC 2009
Copyright © 2009 John Wiley & Sons, Ltd.
International Journal for Numerical Methods in Biomedical Engineering
Volume 27, Issue 9, pages 1398–1410, September 2011
How to Cite
Lazarov, B. S. and Sigmund, O. (2011), Factorized parallel preconditioner for the saddle point problem. Int. J. Numer. Meth. Biomed. Engng., 27: 1398–1410. doi: 10.1002/cnm.1366
- Issue published online: 8 JAN 2010
- Article first published online: 22 DEC 2009
- Manuscript Accepted: 15 NOV 2009
- Manuscript Revised: 2 SEP 2009
- Manuscript Received: 10 FEB 2009
- saddle point systems;
- sparse approximate inverse
The aim of this paper is to apply the factorized sparse approximate inverse (FSAI) preconditioner to the iterative solution of linear systems with indefinite symmetric matrices. Until now the FSAI technique has been applied mainly to positive definite systems and with a limited success for the indefinite case. Here, it is demonstrated that the sparsity pattern for the preconditioner can be chosen in such a way that it guarantees the existence of the factorization. The proposed scheme shows excellent parallel scalability, performance and robustness. It is applicable with short recurrence iterative methods such as MinRes and SymmLQ. The properties are demonstrated on linear systems arising from mixed finite element discretizations in linear elasticity. Copyright © 2009 John Wiley & Sons, Ltd.