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We present a flexible version of GPBi-CG algorithm which allows for the use of a different preconditioner at each step of the algorithm. In particular, a result of the flexibility of the variable preconditioner is to use any iterative method. For example, the standard GPBi-CG algorithm itself can be used as a preconditioner, as can other Krylov subspace methods or splitting methods. Numerical experiments are conducted for flexible GPBi-CG for a few matrices including some nonsymmetric matrices. These experiments illustrate the convergence and robustness of the flexible iterative method.


Krylov Subspace Method; Flexible Preconditioning; Inner-Outer Iteration; GPBi-CG

Cite this paper

J. Wang and T. Gu -Flexible GPBi-CG Method for Nonsymmetric Linear Systems,- Applied Mathematics, Vol. 3 No. 4, 2012, pp. 331-335. doi: 10.4236-am.2012.34050.

Autor: Jia-Min Wang, Tong-Xiang Gu

Fuente: http://www.scirp.org/


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