![]() ![]() Douglas University of Kentucky Lexington, Kentucky and Yale University New Haven, Connecticut Gundolf Haase Johannes Kepler University Linz, Austria Ulrich Langer Johannes Kepler University Linz, Austria A Tutorial on Elliptic PDE Solvers and Their Parallelization Society for Industrial and Applied Mathematics PhiladelphiaĬopyright � 2003 by the Society for Industrial and Applied Mathematics 1 0 9 8 7 6 5 4 3 2 1 All rights reserved. Sorensen,and Henk van der Vorst, Solving Linear Systems on Vector and Shared Memory Computers J. Sorensen, LAPACK Users' Guide, Second Edition Jack J. Hockney, The Science of Computer Benchmarking Richard Barrett, Michael Berry, Tony F.Chan, James Demmel, June Donato, Jack Dongarra, Victor Eijkhout, Roldan Pozo, Charles Romine, and Henk van der Vorst, Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods E. Whaley, ScaLAPACK Users' Guide Greg Astfalk, editor, Applications on Advanced Architecture Computers Francoise Chaitin-Chatelin and Valerie Fraysse, Lectures on Finite Precision Computations Roger W. #Instal parallels 13 review softwareYang, ARPACK Users' Guide: Solution of Large-Scale Eigenvalue Problems with Implicitly Restarted Arnoldi Methods Randolph E.Bank, PLTMC: A Software Package for SolvingElliptic Partial Differential Equations, Users' Guide 8.0 L. van der Vorst, Numerical Linear Algebra for High-Performance Computers R. Berry and Murray Browne, Understanding Search Engines: Mathematical Modeling and Text Retrieval Jack J. ![]() Sorensen,LAPACK Users' Guide, Third Edition Michael W. Yalamov, LAPACK95 Users' Guide Stefan Goedecker and Adolfy Hoisie, Performance Optimization of Numerically Intensive Codes Zhaojun Bai, James Demmel, Jack Dongarra, Axel Ruhe, and Henk van der Vorst, Templates for the Solution of Algebraic Eigenvalue Problems:A Practical Guide Lloyd N. Douglas, Gundolf Haase, and Ulrich Langer, A Tutorial on Elliptic PDESolvers and Their Parallelization Louis Komzsik, The Lanczos Method: Evolution and Application Bard Ermentrout, Simulating, Analyzing, and Animating Dynamical Systems: A Guide to XPPAUT for Researchers and Students V. More, Argonne National Laboratory Software, Environments, and Tools Craig C. Demmel, University of California, Berkeley Dennis Gannon, Indiana University Eric Grosse, AT&T Bell Laboratories Ken Kennedy, Rice University Jorge J. Dongarra University of Tennessee and Oak Ridge National Laboratory Editorial Board James W. The focus is on making recent developments available in a practical format to researchers and other users of these methods and tools. #Instal parallels 13 review seriesSOFTWARE � ENVIRONMENTS � TOOLS The series includes handbooks and software guides as well as monographs on practical implementation of computational methods, environments, and tools. One of the highlights of the tutorial is that the course material can run on a laptop, not just on a parallel computer or cluster of PCs, thus allowing readers to experience their first successes in parallel computing in a relatively short amount of time.Īudience This tutorial is intended for advanced undergraduate and graduate students in computational sciences and engineering however, it may also be helpful to professionals who use PDE-based parallel computer simulations in the field.Ĭontents List of figures List of algorithms Abbreviations and notation Preface Chapter 1: Introduction Chapter 2: A simple example Chapter 3: Introduction to parallelism Chapter 4: Galerkin finite element discretization of elliptic partial differential equations Chapter 5: Basic numerical routines in parallel Chapter 6: Classical solvers Chapter 7: Multigrid methods Chapter 8: Problems not addressed in this book Appendix: Internet addresses Bibliography Index.Ī Tutorial on Elliptic PDE Solvers and Their Parallelization Examples throughout the book are intentionally kept simple so that the parallelization strategies are not dominated by technical details.Ī Tutorial on Elliptic PDE Solvers and Their Parallelization is a valuable aid for learning about the possible errors and bottlenecks in parallel computing. In just eight short chapters, the authors provide readers with enough basic knowledge of PDEs, discretization methods, solution techniques, parallel computers, parallel programming, and the run-time behavior of parallel algorithms to allow them to understand, develop, and implement parallel PDE solvers. This compact yet thorough tutorial is the perfect introduction to the basic concepts of solving partial differential equations (PDEs) using parallel numerical methods. ![]()
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