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Automatic Differentiation of Algorithms : From Simulation to Optimization, Pa...

Description: Automatic Differentiation of Algorithms : From Simulation to Optimization, Paperback by Corliss, George (EDT); Faure, Christele (EDT); Griewank, Andreas (EDT); Hascoet, Laurent (EDT); Naumann, Uwe (EDT), ISBN 1461265436, ISBN-13 9781461265436, Like New Used, Free shipping in the US 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. Th covers all aspects of the subject: mathematics, scientific programming (., use of adjoints in optimization) and implementation (., memory management problems). A strong theme of th 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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Book Title: Automatic Differentiation of Algorithms : From Simulation to Opti

Number of Pages: Xxvii, 432 Pages

Publication Name: Automatic Differentiation of Algorithms : from Simulation to Optimization

Language: English

Publisher: Springer New York

Subject: General, Calculus

Publication Year: 2014

Type: Textbook

Item Weight: 24.9 Oz

Item Length: 9.3 in

Author: Christele Faure

Subject Area: Mathematics, Computers

Item Width: 6.1 in

Format: Trade Paperback

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