Numerical Solution of Partial Differential Equations on Parallel Computers / Edition 1

Numerical Solution of Partial Differential Equations on Parallel Computers / Edition 1

by Are Magnus Bruaset
     
 

This book surveys the major topics that are essential to high-performance simulation on parallel computers or computational clusters. These topics, including programming models, load balancing, mesh generation, efficient numerical solvers, and scientific software, are vital ingredients in the research fields of computer science, numerical analysis, and scientific

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Overview

This book surveys the major topics that are essential to high-performance simulation on parallel computers or computational clusters. These topics, including programming models, load balancing, mesh generation, efficient numerical solvers, and scientific software, are vital ingredients in the research fields of computer science, numerical analysis, and scientific computing. In addition to presenting the technological basis, this volume addresses selected applications that combine different techniques in order to meet demanding computational challenges. Through contributions from a wide range of internationally acknowledged experts, this book gives a to-the-point and self-containing overview of efficient ways to deal with large-scale simulation problems.

Product Details

ISBN-13:
9783540290766
Publisher:
Springer Berlin Heidelberg
Publication date:
02/28/2006
Series:
Lecture Notes in Computational Science and Engineering Series, #51
Edition description:
2006
Pages:
482
Product dimensions:
6.30(w) x 9.26(h) x 0.74(d)

Meet the Author

Table of Contents

Parallel Computing.- Parallel Programming Models Applicable to Cluster Computing and Beyond.- Partitioning and Dynamic Load Balancing for the Numerical Solution of Partial Differential Equations.- Graphics Processor Units: New Prospects for Parallel Computing.- Parallel Algorithms.- Domain Decomposition Techniques.- Parallel Geometric Multigrid.- Parallel Algebraic Multigrid Methods — High Performance Preconditioners.- Parallel Mesh Generation.- Parallel Software Tools.- The Design and Implementation of hypre, a Library of Parallel High Performance Preconditioners.- Parallelizing PDE Solvers Using the Python Programming Language.- Parallel PDE-Based Simulations Using the Common Component Architecture.- Parallel Applications.- Full-Scale Simulation of Cardiac Electrophysiology on Parallel Computers.- Developing a Geodynamics Simulator with PETSc.- Parallel Lattice Boltzmann Methods for CFD Applications.

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