TY - BOOK ID - 211622 TI - Numerical solution of partial differential equations on parallel computers AU - Bruaset, A. M. AU - Tveito, Aslak PY - 2006 SN - 1280607920 9786610607921 3540316191 3540290761 PB - Berlin ; New York : Springer, DB - UniCat KW - Differential equations, Partial KW - Parallel processing (Electronic computers) KW - Numerical solutions KW - Data processing. KW - 519.63 KW - 681.3 *G18 KW - Partial differential equations KW - 681.3 *G18 Partial differential equations: difference methods; elliptic equations; finite element methods; hyperbolic equations; method of lines; parabolic equations (Numerical analysis) KW - Partial differential equations: difference methods; elliptic equations; finite element methods; hyperbolic equations; method of lines; parabolic equations (Numerical analysis) KW - 519.63 Numerical methods for solution of partial differential equations KW - Numerical methods for solution of partial differential equations KW - High performance computing KW - Multiprocessors KW - Parallel programming (Computer science) KW - Supercomputers KW - Numerical solutions&delete& KW - Data processing KW - Global analysis (Mathematics). KW - Computer science. KW - Computer science KW - Differential equations, partial. KW - Analysis. KW - Computational Science and Engineering. KW - Computational Mathematics and Numerical Analysis. KW - Mathematics of Computing. KW - Theoretical, Mathematical and Computational Physics. KW - Partial Differential Equations. KW - Mathematics. KW - Computer mathematics KW - Discrete mathematics KW - Electronic data processing KW - Informatics KW - Science KW - Analysis, Global (Mathematics) KW - Differential topology KW - Functions of complex variables KW - Geometry, Algebraic KW - Mathematics KW - Mathematical analysis. KW - Analysis (Mathematics). KW - Computer mathematics. KW - Computer science—Mathematics. KW - Mathematical physics. KW - Partial differential equations. KW - 517.1 Mathematical analysis KW - Mathematical analysis KW - Physical mathematics KW - Physics UR - https://www.unicat.be/uniCat?func=search&query=sysid:211622 AB - 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. ER -