In this introductory text, the fundamental algorithms of numerical linear algebra are developed in a parallel context.
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Ronald W. Shonkwiler is a Professor in the School of Mathematics at the Georgia Institute of Technology. He has authored or co-authored over 50 research papers in areas of functional analysis, mathematical biology, image processing algorithms, fractal geometry, neural networks and Monte Carlo optimization methods. His algorithm for monochrome image comparison is part of a US patent for fractal image compression. He has co-authored two other books, An Introduction to the Mathematics of Biology and The Handbook of Stochastic Analysis and Applications.
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Zustand: New. In this introductory text, the fundamental algorithms of numerical linear algebra are developed in a parallel context. Series Editor(s): Ablowitz, Mark J.; Davis, S. H.; Hinch, E. J.; Iserles, A.; Ockendon, J.; Olver, P. J. Series: Cambridge Texts in Applied Mathematics. Num Pages: 300 pages, 10 tables 120 exercises. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 228 x 152 x 18. Weight in Grams: 432. . 2006. Illustrated. paperback. . . . . Books ship from the US and Ireland. Artikel-Nr. V9780521683371
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In this text, students of applied mathematics, science and engineering are introduced to fundamental ways of thinking about the broad context of parallelism. The authors begin by giving the reader a deeper understanding of the issues through a general examination of timing, data dependencies, and communication. These ideas are implemented with respect to shared memory, parallel and vector processing, and distributed memory cluster computing. Threads, OpenMP, and MPI are covered, along with code examples in Fortran, C, and Java. The principles of parallel computation are applied throughout as the authors cover traditional topics in a first course in scientific computing. Building on the fundamentals of floating point representation and numerical error, a thorough treatment of numerical linear algebra and eigenvector/eigenvalue problems is provided. By studying how these algorithms parallelize, the reader is able to explore parallelism inherent in other computations, such as Monte Carlo methods. Artikel-Nr. 9780521683371
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