A low-order block preconditioner for saddle point linear systems
Journal Article
·
· Computational and Applied Mathematics
- Fujian Normal University, School of Mathematics and Computer Science and FJKLMAA (China)
A preconditioner is proposed for the large and sparse linear saddle point problems, which is based on a low-order three-by-three block saddle point form. The eigenvalue distribution and an upper bound of the degree of the minimal polynomial for the preconditioned matrix are discussed. Numerical results show that the optimal convergence behavior can be achieved when the new preconditioner is used to accelerate the convergence rate of Krylov subspace methods such as GMRES.
- OSTI ID:
- 22769324
- Journal Information:
- Computational and Applied Mathematics, Journal Name: Computational and Applied Mathematics Journal Issue: 2 Vol. 37; ISSN 0101-8205
- Country of Publication:
- United States
- Language:
- English
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