An Introduction to Domain Decomposition Methods


Algorithms, Theory, and Parallel Implementation

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By Victorita Dolean, Pierre Jolivet, Frederic Nataf
Imprint:
SIAM - SOCIETY FOR INDUSTRIAL AND APPLIED
Release Date:
Format:
PAPERBACK
Dimensions:
229 x 152 mm
Weight:
460 g
Pages:
248

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Description

Victorita Dolean is a Reader in the Department of Mathematics and Statistics, University of Strathclyde. She has been a research assistant in CMAP (Center of Applied Mathematics) at the Ecole Polytechnique in Paris, assistant professor at the University of Evry and the University of Nice, and visiting professor at the University of Geneva. Her research has been oriented toward practical and modern applications of scientific computing by developing interactions between academic and industrial partners and taking part in the life of the scientific community as a member of the Board of Directors of SMAI (Society of Industrial and Applied Mathematics in France). Pierre Jolivet is a scientist at CNRS in the Toulouse Institute of Computer Science Research, France, working mainly in the field of parallel computing. Before that, he was an ETH Zuerich Postdoctoral Fellow of the Scalable Parallel Computing Lab, Zuerich, Switzerland. He received his PhD from the University of Grenoble, France, in 2014 for his work on domain decomposition methods and their applications on massively parallel architectures. Frederic Nataf is a senior scientist at CNRS in Laboratory J. L. Lions at Universite de Paris VI (Pierre et Marie Curie), France. He is also part of an INRIA team. His field of expertise is in high performance scientific computing (domain decomposition methods/approximate factorizations), absorbing/PML boundary conditions, and inverse problems. He has coauthored nearly 100 papers and given several invited plenary talks on these subjects. He developed the theory of optimized Schwarz methods and, very recently, the GENEO coarse space. This last method enables the solving of very large highly heterogeneous problems on large scale computers.

Preface Chapter 1: Schwarz methods Chapter 2: Optimized Schwarz methods Chapter 3: Krylov methods Chapter 4: Coarse spaces Chapter 5: Theory of two-level additive Schwarz methods Chapter 6: Neumann-Neumann and FETI algorithms Chapter 7: Robust coarse spaces via generalized eigenproblems: The GenEO method Chapter 8: Parallel implementation of Schwarz methods Index.

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