Experimental Study of the Asynchronous Multisplitting Relaxation Methods for the Linear Complementarity Problems
Year: 2002
Author: Zhong-Zhi Bai
Journal of Computational Mathematics, Vol. 20 (2002), Iss. 6 : pp. 561–574
Abstract
We study the numerical behaviours of the relaxed asynchronous multisplitting methods for the linear complementarity problems by solving some typical problems from practical applications on a real multiprocessor system. Numerical results show that the parallel multisplitting relaxation methods always perform much better than the corresponding sequential alternatives, and that the asynchronous multisplitting relaxation methods often outperform their corresponding synchronous counterparts. Moreover, the two-sweep relaxed multisplitting methods have better convergence properties than their corresponding one-sweep relaxed ones in the sense that they have larger convergence domains and faster convergence speeds. Hence, the asynchronous multisplitting unsymmetric relaxation iterations should be the methods of choice for solving the large sparse linear complementarity problems in the parallel computing environments.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/2002-JCM-8941
Journal of Computational Mathematics, Vol. 20 (2002), Iss. 6 : pp. 561–574
Published online: 2002-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 14
Keywords: Linear complementarity problem Matrix multisplitting Asynchronous iterative methods Numerical experiments.