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Domain Decomposition Methods in Science and Engineering XX [electronic resource] /edited by Randolph Bank, Michael Holst, Olof Widlund, Jinchao Xu.

by Bank, Randolph [editor.]; Holst, Michael [editor.]; Widlund, Olof [editor.]; Xu, Jinchao [editor.]; SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Computational Science and Engineering: 91Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : 2013.Description: XIX, 686 p. 156 illus. online resource.ISBN: 9783642352751.Subject(s): Mathematics | Computer aided design | Differential equations, partial | Computer science -- Mathematics | Computer science | Mathematics | Computational Mathematics and Numerical Analysis | Computational Science and Engineering | Partial Differential Equations | Computer-Aided Engineering (CAD, CAE) and DesignDDC classification: 518 | 518 Online resources: Click here to access online
Contents:
Preface -- Part I: Plenary Presentations -- Part II: Minisymposia -- Part III: Contributed Presentations.
In: Springer eBooksSummary: These are the proceedings of the 20th international conference on domain decomposition methods in science and engineering. Domain decomposition methods are iterative methods for solving the often very large linearor nonlinear systems of algebraic equations that arise when various problems in continuum mechanics are discretized using finite elements. They are designed for massively parallel computers and take the memory hierarchy of such systems in mind. This is essential for approaching peak floating point performance. There is an increasingly well developed theory whichis having a direct impact on the development and improvements of these algorithms.
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Preface -- Part I: Plenary Presentations -- Part II: Minisymposia -- Part III: Contributed Presentations.

These are the proceedings of the 20th international conference on domain decomposition methods in science and engineering. Domain decomposition methods are iterative methods for solving the often very large linearor nonlinear systems of algebraic equations that arise when various problems in continuum mechanics are discretized using finite elements. They are designed for massively parallel computers and take the memory hierarchy of such systems in mind. This is essential for approaching peak floating point performance. There is an increasingly well developed theory whichis having a direct impact on the development and improvements of these algorithms.

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