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Titlebook: Concurrent Scientific Computing; Eric F. Velde Textbook 1994 Springer Science+Business Media New York 1994 calculus.concurrency.numerical

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书目名称Concurrent Scientific Computing
编辑Eric F. Velde
视频videohttp://file.papertrans.cn/236/235170/235170.mp4
丛书名称Texts in Applied Mathematics
图书封面Titlebook: Concurrent Scientific Computing;  Eric F. Velde Textbook 1994 Springer Science+Business Media New York 1994 calculus.concurrency.numerical
描述Mathematics is playing an ever more important role in the physical and biological sciences, provoking a blurring of boundaries between scientific dis­ ciplines and a resurgence of interest in the modern as well as the classical techniques of applied mathematics. This renewal of interest, both in research and teaching, has led to the establishment of the series: Texts in Applied Mathe­ matics (TAM). The development of new courses is a natural consequence of a high level of excitement on the research frontier as newer techniques, such as numerical and symbolic computer systems, dynamical systems, and chaos, mix with and reinforce the traditional methods of applied mathematics. Thus, the purpose of this textbook series is to meet the current and future needs of these advances and encourage the teaching of new courses. TAM will publish textbooks suitable for use in advanced undergraduate and beginning graduate courses, and will complement the Applied Mathematical Sciences (AMS) series, which will focus on advanced textbooks and research level monographs. Preface A successful concurrent numerical simulation requires physics and math­ ematics to develop and analyze the model, numerical a
出版日期Textbook 1994
关键词calculus; concurrency; numerical methods; programming; scientific computing
版次1
doihttps://doi.org/10.1007/978-1-4612-0849-5
isbn_softcover978-1-4612-6921-2
isbn_ebook978-1-4612-0849-5Series ISSN 0939-2475 Series E-ISSN 2196-9949
issn_series 0939-2475
copyrightSpringer Science+Business Media New York 1994
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LU-Decomposition,ents on the coefficient matrix ranging from positive definiteness to special sparsity structure. Direct solvers, on the other hand, are almost always applicable. Although their operation count and execution time can be large, both are very predictable given the problem size. In Chapters 4 and 5, we
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Tridiagonal Solvers, procedure known as .. The iterative tridiagonal solver is based on concurrent relaxation and is often a good alternative to any direct solver. Tridiagonal systems of linear equations often occur as part of a larger computation. They occur, for example, in some fast Poisson solvers and in alternatin
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Particle Methods,his interesting astrophysical problem, called .-., to introduce particle methods. Algorithmically, these methods are substantially different from grid-oriented computations for two reasons. First, grid operators are short-range operators: they act only on neighboring grid points. Standard particle m
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https://doi.org/10.1007/978-3-322-84844-4portant component of the ., which computes all eigenvalues and eigenvectors of a matrix. The multicomputer program for QR-decomposition is an application of recursive doubling, but several interesting complications arise.
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