Automatic Differentiation of Algorithms: From Simulation to Optimization

Corliss, George [Editor]; Faure, Christele [Editor]; Griewank, Andreas [Editor]; Hascoet, Laurent [Editor]; Naumann, Uwe [Editor];

ISBN 10: 0387953051 / ISBN 13: 9780387953052

Published by Springer, 2002

About this Item

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Seller Inventory # Q-0387953051

Bibliographic Details

• Title: Automatic Differentiation of Algorithms: From Simulation to Optimization
• Publisher: Springer
• Publication Date: 2002
• Language: English
• ISBN 10: 0387953051
• ISBN 13: 9780387953052
• Binding: hardcover
• Condition: New
• Weight: 36 ounces

About this title

Synopsis

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.