
An Introduction to Domain Decomposition Methods
Algorithms, Theory, and Parallel Implementation
Society for Industrial & Applied Mathematics,U.S. (Publisher)
Published on 30. December 2015
Book
Paperback/Softback
248 pages
978-1-61197-405-8 (ISBN)
Description
The purpose of this book is to offer an overview of the most popular domain decomposition methods for partial differential equations (PDEs). These methods are widely used for numerical simulations in solid mechanics, electromagnetism, flow in porous media, etc., on parallel machines from tens to hundreds of thousands of cores. The appealing feature of domain decomposition methods is that, contrary to direct methods, they are naturally parallel. The authors focus on parallel linear solvers.
The authors present:
All popular algorithms both at the PDE level and at the discrete level in terms of matrices.
Systematic scripts for sequential implementation in a free open-source finite element package as well as some parallel scripts.
A new coarse space construction (two-level method) that adapts to highly heterogeneous problems.
The authors present:
All popular algorithms both at the PDE level and at the discrete level in terms of matrices.
Systematic scripts for sequential implementation in a free open-source finite element package as well as some parallel scripts.
A new coarse space construction (two-level method) that adapts to highly heterogeneous problems.
More details
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 256 mm
Width: 177 mm
Thickness: 17 mm
Weight
455 gr
ISBN-13
978-1-61197-405-8 (9781611974058)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
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.
Content
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.
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.