DocumentCode :
7467
Title :
Performance of Preconditioned Linear Solvers Based on Minimum Residual for Complex Symmetric Linear Systems
Author :
Tsuburaya, Tomonori ; Okamoto, Yuji ; Fujiwara, Koji ; Sato, Seiki
Author_Institution :
Dept. of Electr. & Electron. Syst. Eng., Utsunomiya Univ., Utsunomiya, Japan
Volume :
50
Issue :
2
fYear :
2014
fDate :
Feb. 2014
Firstpage :
557
Lastpage :
560
Abstract :
Fast computation of linear systems is essential for reducing the elapsed time when using finite element analysis. The incomplete Cholesky conjugate orthogonal conjugate gradient method is widely used as a linear solver for complex symmetric systems derived from the edge-based FEM in the frequency domain. On the other hand, the performance of the preconditioned minimized residual method based on the three-term recurrence (MRTR) formula of the conjugate gradient-type method has been demonstrated on various symmetric sparse linear systems obtained from edge-based FEM formulated in the magnetostatic and time domain. This paper shows for the first time the performance of the preconditioned conjugate orthogonal MRTR method applied to complex symmetric linear systems.
Keywords :
conjugate gradient methods; finite element analysis; magnetostatics; complex symmetric linear systems; edge-based FEM; finite element analysis; frequency domain; incomplete Cholesky conjugate orthogonal conjugate gradient method; magnetostatics; preconditioned conjugate orthogonal MRTR method; preconditioned linear solvers; preconditioned minimized residual method; symmetric sparse linear systems; three-term recurrence formula; time domain; Analytical models; Convergence; Finite element analysis; Integrated circuit modeling; Linear systems; Mathematical model; COMRTR method; Complex symmetric linear systems; frequency-domain finite element analysis; split preconditioner;
fLanguage :
English
Journal_Title :
Magnetics, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9464
Type :
jour
DOI :
10.1109/TMAG.2013.2281410
Filename :
6749029
Link To Document :
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