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Y. Escaig, "Large Scale Linear Analysis using Distributed Computing", in B.H.V. Topping, (Editor), "Advances in Computational Mechanics for Parallel and Distributed Processing", Civil-Comp Press, Edinburgh, UK, pp 137-141, 1997. doi:10.4203/ccp.45.5.1

Abstract

This article presents different issues of the implementation of a domain decomposition method on distributed memory systems. The proposed domain decomposition method uses direct solvers for the local problems and for the interface problem. This method, which is sequentially as efficient as other direct solvers (like sparse solvers) shows an inherent parallelism during the resolution of the local problems. Besides, the interface problem, of which the matrix is stored in a skyline format, can also be solved in parallel. The parallel performances of the method, implemented on a Cray T3D, are analyzed in detail. The method appears to be efficient if the processors are fully used and to be scalable if the size of the problem increases with the number of processors.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 45 ADVANCES IN COMPUTATIONAL MECHANICS FOR PARALLEL AND DISTRIBUTED PROCESSING Edited by: B.H.V. Topping Paper V.1 Large Scale Linear Analysis using Distributed Computing Y. Escaig INSA de Rouen, St.Etienne du Rouvray, France doi:10.4203/ccp.45.5.1 purchase the full-text of this paper Full Bibliographic Reference for this paper Y. Escaig, "Large Scale Linear Analysis using Distributed Computing", in B.H.V. Topping, (Editor), "Advances in Computational Mechanics for Parallel and Distributed Processing", Civil-Comp Press, Edinburgh, UK, pp 137-141, 1997. doi:10.4203/ccp.45.5.1 Abstract This article presents different issues of the implementation of a domain decomposition method on distributed memory systems. The proposed domain decomposition method uses direct solvers for the local problems and for the interface problem. This method, which is sequentially as efficient as other direct solvers (like sparse solvers) shows an inherent parallelism during the resolution of the local problems. Besides, the interface problem, of which the matrix is stored in a skyline format, can also be solved in parallel. The parallel performances of the method, implemented on a Cray T3D, are analyzed in detail. The method appears to be efficient if the processors are fully used and to be scalable if the size of the problem increases with the number of processors. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £66 +P&P)
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