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Numerical Solution of Partial Differential Equations on Parallel Computers 2006 Edition
Contributor(s): Bruaset, Are Magnus (Editor), Tveito, Aslak (Editor)
ISBN: 3540290761     ISBN-13: 9783540290766
Publisher: Springer
OUR PRICE:   $161.49  
Product Type: Paperback - Other Formats
Published: December 2005
Qty:
Annotation: 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.
Additional Information
BISAC Categories:
- Mathematics | Number Systems
- Mathematics | Differential Equations - General
- Mathematics | Applied
Dewey: 518.64
Series: Lecture Notes in Computational Science and Engineering
Physical Information: 0.74" H x 6.3" W x 9.26" (1.58 lbs) 482 pages
 
Descriptions, Reviews, Etc.
Publisher Description:
Since the dawn of computing, the quest for a better understanding of Nature has been a driving force for technological development. Groundbreaking achievements by great scientists have paved the way from the abacus to the supercomputing power of today. When trying to replicate Nature in the computer's silicon test tube, there is need for precise and computable process descriptions. The scienti?c ?elds of Ma- ematics and Physics provide a powerful vehicle for such descriptions in terms of Partial Differential Equations (PDEs). Formulated as such equations, physical laws can become subject to computational and analytical studies. In the computational setting, the equations can be discreti ed for ef?cient solution on a computer, leading to valuable tools for simulation of natural and man-made processes. Numerical so- tion of PDE-based mathematical models has been an important research topic over centuries, and will remain so for centuries to come. In the context of computer-based simulations, the quality of the computed results is directly connected to the model's complexity and the number of data points used for the computations. Therefore, computational scientists tend to ?ll even the largest and most powerful computers they can get access to, either by increasing the si e of the data sets, or by introducing new model terms that make the simulations more realistic, or a combination of both. Today, many important simulation problems can not be solved by one single computer, but calls for parallel computing.