A CLASS OF ASYNCHRONOUS PARALLEL NONLINEAR MULTISPLITTING RELAXATION METHODS
作者:
DEREN WANG,
ZHONGZHI BAI,
D. J. EVANS,
期刊:
Parallel Algorithms and Applications
(Taylor Available online 1994)
卷期:
Volume 2,
issue 3
页码: 209-228
ISSN:1063-7192
年代: 1994
DOI:10.1080/10637199408915417
出版商: Taylor & Francis Group
关键词: System of nonlinear equations;nonlinear multisplitting;relaxation;asynchronous iteration;local convergence;G.1.3
数据来源: Taylor
摘要:
In this paper, we establish a class of asynchronous parallel nonlinear multisplitting relaxation methods for solving system of nonlinear equations. With special choices of the relaxed parameters in the new methods, not only can the convergence properties of them be improved, but also many applicable and efficient asynchronous parallel nonlinear multisplitting iteration methods such as the Jacobi, Gauss-Seidel, SOR as well as the asynchronous parallel nonlinear multisplitting AOR-Newton, -Chord and -Steffensen programs, etc., can be obtained. Under proper conditions, we build convergence theories about these asynchronous methods, and estimate their asymptotic convergence rates in detailed manner.
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