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Nonlinear Theory of Elastic Plates

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Exterior Algebras

Elementary Tribute to Grassmann's Ideas

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From Pinch Methodology to Pinch-Exergy Integration of Flexible Systems

Thermodynamics Energy, Environment, Economy Set

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Data Treatment in Environmental Sciences

Multivaried Approach

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Gas Hydrates 1

Fundamentals, Characterization and Modeling

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Smart Decisions in Complex Systems

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Chi-squared Goodness-of-fit Tests for Censored Data

Stochastic Models in Survival Analysis and Reliability Set Volume 3

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Baidu SEO

Challenges and Intricacies of Marketing in China

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Supply Chain Management and Business Performance

The VASC Model

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Asymmetric Alliances and Information Systems

Issues and Prospects

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Parallel Scientific Computing

Frédéric Magoulès, Ecole Centrale Paris, France François-Xavier Roux, Université Pierre et Marie, France Guillaume Houzeaux, Barcelona Supercomputing Center, Spain

ISBN: 9781848215818

Publication Date: December 2015   Hardback   372 pp.

130.00 USD

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Scientific computing has become an indispensable tool in numerous fields, such as physics, biology, chemistry, finance and engineering. For example, it enables us, thanks to efficient algorithms adapted to current computers and supercomputers, to simulate complex phenomena, without the help of models or experimentations. Some examples are the structural behaviors of civil engineering structures, the sound level in a theater, a fluid flowing around an aircraft or a Formula 1 car, and the hydrodynamics of a racing yacht.
This book presents the scientific computing techniques applied to parallel computing for the numerical simulation of large-scale problems; these problems mainly result from systems modeled by partial differential equations. Computing concepts are tackled via examples. Implementation and programming techniques resulting from the finite element, finite volume and finite difference methods are presented for direct solvers, iterative solvers and domain decomposition methods, along with an introduction to MPI and OpenMP.


1. Computer Architectures.
2. Parallelization and Programming Models.
3. Parallel Algorithm.
4. Basics of Numerical Matrix.
5. Sparse Matrices.
6. Solving Linear Systems.
7. LU Methods for Solving Linear Systems.
8. Parallelization of LU Methods for Dense Matrices.
9. LU Methods for Sparse Matrices.
10.Basics of Krylov Subspaces.
11. Methods with Complete Orthogonalization for Symmetric Positive.
12. Exact Orthogonalization Methods for Arbitrary Matrices.
13. Biorthogonalization Methods for Non-symmetric.
14. Parallelization of Krylov Methods.
15. Parallel Preconditioning Methods.

About the Authors

Frédéric Magoulès is Professor at Ecole Centrale Paris in France and Honorary Professor at the University of Pecs in Hungary. His research focuses on parallel computing and numerical linear algebra.
François-Xavier Roux is Professor at Université Pierre et Marie Curie and an Engineer at ONERA, in France. His research focuses on parallel computing and numerical analysis.
Guillaume Houzeaux is Team Leader at the Barcelona Supercomputing Center in Spain. His research focuses on high performance computational mechanics.


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