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A class of asynchronous parallel multisplitting relaxation methods for large sparse linear complementarity problems
Bai Zhongzhi1; Huang Yuguang2
2003
Source PublicationJournal of Computational Mathematics
ISSN0254-9409
Volume21Issue:6Pages:773
AbstractAsynchronous parallel multisplitting relaxation methods for solving large sparse linear complementarity problems are presented, and their convergence is proved when the system matrices are H-matrices having positive diagonal elements. Moreover, block and multi-parameter variants of the new methods, together with their convergence properties, are investigated in detail. Numerical results show that these new methods can achieve high parallel efficiency for solving the large sparse linear complementarity problems on multiprocessor systems.
Language英语
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/18656
Collection中国科学院数学与系统科学研究院
Affiliation1.中国科学院数学与系统科学研究院
2.Programming Research Group, Oxford University Computing Laboratory, Wolfson Building, Parks Road, Oxford OX1 3QD
Recommended Citation
GB/T 7714
Bai Zhongzhi,Huang Yuguang. A class of asynchronous parallel multisplitting relaxation methods for large sparse linear complementarity problems[J]. Journal of Computational Mathematics,2003,21(6):773.
APA Bai Zhongzhi,&Huang Yuguang.(2003).A class of asynchronous parallel multisplitting relaxation methods for large sparse linear complementarity problems.Journal of Computational Mathematics,21(6),773.
MLA Bai Zhongzhi,et al."A class of asynchronous parallel multisplitting relaxation methods for large sparse linear complementarity problems".Journal of Computational Mathematics 21.6(2003):773.
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