A Comparison of the Preconditioners for the Large Symmetric Generalized Eigenvalue Problems by CG-type Methods
- Authors
- 마상백
- Issue Date
- May-2014
- Publisher
- POLSKIE TOWARZYSTWO LESNE
- Citation
- SYLWAN, v.158, no.5, pp.63 - 68
- Indexed
- OTHER
- Journal Title
- SYLWAN
- Volume
- 158
- Number
- 5
- Start Page
- 63
- End Page
- 68
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/22869
- ISSN
- 0039-7660
- Abstract
- Preconditioned Krylov subspace methods have proved to be efficient for computing the
smallest eigenvalue of large symmetric generalized eigenvalue problem. As in the case of
linear systems the success of these methods in many cases is due to the existence of good preconditioning
techniques. In this paper we consider various preconditioners, such as ILU(0),
ILU(k), ILUT(l, ), SSOR(Symmetric Successive OverRelaxation), and AGMG(AGgregate
MultiGrid). We tested on the large sparse symmetric matrices arising from discretizations
of PDE(Partial Differential Equation)s on structured grids. Our results show that ILUT
gives the best performance for almost all of the problems tested.
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