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H. Akiba, "A Coarse Grid Conjugate Gradient Method and its Application to Realistic Problems: Fully Iterative Method with Coarse Grid", in F. Magoulès, (Editor), "Substructuring Techniques and Domain Decomposition Methods", Saxe-Coburg Publications, Stirlingshire, UK, Chapter 6, pp 137-170, 2010. doi:10.4203/csets.24.6

Keywords: parallel processing, large scale analysis, domain decomposition method, iterative substructuring method, Schwarz framework, Neumann precondition, BDD method, CGCG method, coarse grid problem.

Abstract

This chapter describes a newly developed coarse grid conjugate gradient (CGCG) method in a context of the domain decomposition method, or the iterative substructuring method. The iterative substructuring method is viewed from the Schwarz framework and the preconditioned conjugate gradient (CG) method. Starting from an elementary explanation, then the Schwartz framework is explained, followed by a description of the well known BDD method as an example of Schwarz framework, and finally the CGCG method is constructed. The CGCG method is implemented in a code called ADVENTURE Cluster (ADVC). As an analysis example, a drop impact analysis of a mobile phone model with 305 million degrees of freedom using ADVC performed on the IBM Blue Gene/L with 8 racks, 8192 nodes, 8192 processes is shown. The analysis yielded a performance of 1.27 TFLOPS.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Computational Science, Engineering & Technology Series ISSN 1759-3158 CSETS: 24 SUBSTRUCTURING TECHNIQUES AND DOMAIN DECOMPOSITION METHODS Edited by: F. Magoulès Chapter 6 A Coarse Grid Conjugate Gradient Method and its Application to Realistic Problems: Fully Iterative Method with Coarse Grid H. Akiba Allied Engineering Corporation, Tokyo, Japan doi:10.4203/csets.24.6 purchase the full-text of this chapter Full Bibliographic Reference for this chapter H. Akiba, "A Coarse Grid Conjugate Gradient Method and its Application to Realistic Problems: Fully Iterative Method with Coarse Grid", in F. Magoulès, (Editor), "Substructuring Techniques and Domain Decomposition Methods", Saxe-Coburg Publications, Stirlingshire, UK, Chapter 6, pp 137-170, 2010. doi:10.4203/csets.24.6 Keywords: parallel processing, large scale analysis, domain decomposition method, iterative substructuring method, Schwarz framework, Neumann precondition, BDD method, CGCG method, coarse grid problem. Abstract This chapter describes a newly developed coarse grid conjugate gradient (CGCG) method in a context of the domain decomposition method, or the iterative substructuring method. The iterative substructuring method is viewed from the Schwarz framework and the preconditioned conjugate gradient (CG) method. Starting from an elementary explanation, then the Schwartz framework is explained, followed by a description of the well known BDD method as an example of Schwarz framework, and finally the CGCG method is constructed. The CGCG method is implemented in a code called ADVENTURE Cluster (ADVC). As an analysis example, a drop impact analysis of a mobile phone model with 305 million degrees of freedom using ADVC performed on the IBM Blue Gene/L with 8 racks, 8192 nodes, 8192 processes is shown. The analysis yielded a performance of 1.27 TFLOPS. purchase the full-text of this chapter (price £25) go to the previous chapter go to the next chapter return to the table of contents return to the book description purchase this book (price £95 +P&P)
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