Articoli correlati a Automatic Differentiation of Algorithms: From Simulation...
Sinossi
Automatic Differentiation (AD) is a maturing computational technology and has become a mainstream tool used by practicing scientists and computer engineers. The rapid advance of hardware computing power and AD tools has enabled practitioners to quickly generate derivative-enhanced versions of their code for a broad range of applications in applied research and development.
Automatic Differentiation of Algorithms provides a comprehensive and authoritative survey of all recent developments, new techniques, and tools for AD use. The book covers all aspects of the subject: mathematics, scientific programming (i.e., use of adjoints in optimization) and implementation (i.e., memory management problems). A strong theme of the book is the relationships between AD tools and other software tools, such as compilers and parallelizers. A rich variety of significant applications are presented as well, including optimum-shape design problems, for which AD offers more efficient tools and techniques.
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Contenuti
Part titles: *Invited Contributions * Parameter Identification and Least Squares * Applications in Ode's and Optimal Control * Applications in PDE's * Applications in Science and Engineering * Maintaining and Enhancing Parallelism * Exploiting Structure and Sparsity * Space-Time Tradeoffs in the Reverse Mode * Use of Second and Higher Derivatives * Error Estimates and Inclusions
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Automatic Differentiation of Algorithms: From Simulation to Optimization
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Automatic Differentiation of Algorithms: From Simulation to Optimization
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Springer-Verlag New York Inc., 2002
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Hardback. Condizione: Very Good. A survey book focusing on the key relationships and synergies between automatic differentiation (AD) tools and other software tools, such as compilers and parallelizers, as well as their applications. The key objective is to survey the field and present the recent developments. In doing so the topics covered shed light on a variety of perspectives. They reflect the mathematical aspects, such as the differentiation of iterative processes, and the analysis of nonsmooth code. They cover the scientific programming aspects, such as the use of adjoints in optimization and the propagation of rounding errors. They also cover implementation problems. Codice articolo CIN0387953051VG
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Automatic Differentiation of Algorithms: From Simulation to Optimization
Editore:
Springer-Verlag New York Inc., 2002
ISBN 10: 0387953051
ISBN 13: 9780387953052
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Da: World of Books Inc, Montgomery, IL, U.S.A.
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Hardback. Condizione: Very Good. A survey book focusing on the key relationships and synergies between automatic differentiation (AD) tools and other software tools, such as compilers and parallelizers, as well as their applications. The key objective is to survey the field and present the recent developments. In doing so the topics covered shed light on a variety of perspectives. They reflect the mathematical aspects, such as the differentiation of iterative processes, and the analysis of nonsmooth code. They cover the scientific programming aspects, such as the use of adjoints in optimization and the propagation of rounding errors. They also cover implementation problems. Codice articolo CIN0387953051VG
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Automatic Differentiation Of Algorithms
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Automatic Differentiation of Algorithms : From Simulation to Optimazation
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