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Titlebook: Automatic Differentiation of Algorithms; From Simulation to O George Corliss,Christèle Faure,Uwe Naumann Book 2002 Springer Science+Busines

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發(fā)表于 2025-3-21 16:14:09 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Automatic Differentiation of Algorithms
期刊簡稱From Simulation to O
影響因子2023George Corliss,Christèle Faure,Uwe Naumann
視頻videohttp://file.papertrans.cn/167/166413/166413.mp4
圖書封面Titlebook: Automatic Differentiation of Algorithms; From Simulation to O George Corliss,Christèle Faure,Uwe Naumann Book 2002 Springer Science+Busines
影響因子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.
Pindex Book 2002
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Differentiation Methods for Industrial Strength Problemssues such as inhomogeneous source codes written in different languages or table look-ups..Several results concerning the use of tools such as ADIFOR, Odyssée, and ADOL-C are presented. We discuss the benefits and the difficulties of current AD techniques applied to real industrial codes. Finally, we
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Analytical Aspects and Practical Pitfalls in Technical Applications of ADgy function with respect to the strain tensor. These quantities can be derived analytically using complicated analysis but it is fascinating that with minimal preparation and only few mathematical insight exactly the same values can also be computed using AD methods.
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The Earth as an open ecosystem,puter models have to be developed more quickly. The correct description and implementation of the interaction between different components of the entire simulation model as well as the nonlinear behaviour of these components lead in many cases to the need for derivative information. In this chapter,
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Srinivas Bettadpur,Christopher McCulloughd that have proved useful in the installation of nonlinear solvers in the NEOS Server. Our discussion centers on the computation of the gradient and Hessian matrix for partially separable functions and shows that the gradient and Hessian matrix can be computed with guaranteed bounds in time and memo
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