Back to Search
Start Over
Domain decomposition based preconditioner combined local low-rank approximation with global corrections.
- Source :
-
Computers & Mathematics with Applications . May2022, Vol. 114, p41-46. 6p. - Publication Year :
- 2022
-
Abstract
- To solve general sparse linear systems, this paper presents a domain decomposition based parallel preconditioner. Vertex-based partitioning is utilized to reorder the original coefficient matrix, resulting in a s × s block structure. Here, s is the number of subdomains used in the partition. Variables corresponding to the interface nodes are obtained by solving a linear system with coefficient matrix being the Schur complement S of the reordered matrix. Combining local low-rank correction approximation with a global low-rank correction technique to approximate the inverse of S , the method presented in this paper is different with previous Schur complement based preconditioners. The global low-rank correction terms are obtained by using the information comes from the local low-rank correction terms. In addition, variables corresponding to the interior nodes are computed by solving s small linear systems in parallel. Some numerical tests are presented to show the efficiency and robustness of the proposed preconditioner. [ABSTRACT FROM AUTHOR]
- Subjects :
- *SCHUR complement
*LINEAR systems
*KRYLOV subspace
Subjects
Details
- Language :
- English
- ISSN :
- 08981221
- Volume :
- 114
- Database :
- Academic Search Index
- Journal :
- Computers & Mathematics with Applications
- Publication Type :
- Academic Journal
- Accession number :
- 156452815
- Full Text :
- https://doi.org/10.1016/j.camwa.2022.03.006