Numerical Solution of Partial Differential Equations on Parallel Computers

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160,49 

Lecture Notes in Computational Science and Engineering 51

ISBN: 3540290761
ISBN 13: 9783540290766
Herausgeber: Are Magnus Bruaset/Aslak Tveito
Verlag: Springer Verlag GmbH
Umfang: xii, 482 S., 171 s/w Illustr., 30 farbige Illustr., 482 p. 201 illus., 30 illus. in color.
Erscheinungsdatum: 16.12.2005
Auflage: 1/2006
Format: 1.7 x 23.5 x 15.4
Gewicht: 720 g
Produktform: Kartoniert
Einband: Kartoniert

Includes supplementary material: sn.pub/extras

Artikelnummer: 1486285 Kategorie:

Beschreibung

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 computers 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 models 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.

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