Description: Automatic Differentiation of Algorithms by George Corliss, Christele Faure, Andreas Griewank, Laurent Hascoet, Uwe Naumann 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. They cover the scientific programming aspects, such as the use of adjoints in optimization and the propagation of rounding errors. FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher Description 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. Table of Contents Part titles: Invited Contributions.- Parameter Identification and Least Squares.- Applications in Odes and Optimal Control.- Applications in PDEs.- 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. Promotional Springer Book Archives Long Description 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 toolshas 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.Topics and features:* helpful introductory AD survey chapter for brief overview of the field*extensive applications chapters, i.e., for circuit simulation, optimization and optimal-control shape design, structural mechanics, and multibody dynamical systems modeling*comprehensive bibliography for all current literature and results for the field*performance issues *optimal control sensitivity analysis*AD use with object oriented software tool kitsThe book is an ideal and accessible survey of recent developments and applications of AD tools and techniques for a broad scientific computing and computer engineering readership. Practitioners, professionals, and advanced graduates working in AD development will find the book auseful reference and essential resource for their work. Description for Sales People A state-of-the-art survey book focusing upon the key applications and relationships and synergies between automatic differentiation (AD) tools and other software tools, such as compilers and parallelizers. Essential reading for practitioners and professionals in scientific computing, as well as for computer engineers. Details ISBN1461265436 Year 2014 ISBN-10 1461265436 ISBN-13 9781461265436 Format Paperback Publication Date 2014-01-27 Pages 432 Short Title AUTOMATIC DIFFERENTIATION OF A Language English Media Book DEWEY 004 Imprint Springer-Verlag New York Inc. Subtitle From Simulation to Optimization Place of Publication New York, NY Country of Publication United States Edited by Uwe Naumann Illustrations 84 Illustrations, black and white; XXVII, 432 p. 84 illus. AU Release Date 2014-01-27 NZ Release Date 2014-01-27 US Release Date 2014-01-27 UK Release Date 2014-01-27 Author Uwe Naumann Publisher Springer-Verlag New York Inc. Edition Description Softcover reprint of the original 1st ed. 2002 Alternative 9780387953052 Audience Professional & Vocational We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:96352608;
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ISBN-13: 9781461265436
Book Title: Automatic Differentiation of Algorithms
Number of Pages: 432 Pages
Language: English
Publication Name: Automatic Differentiation of Algorithms: from Simulation to Optimization
Publisher: Springer-Verlag New York Inc.
Publication Year: 2014
Subject: Computer Science
Item Height: 235 mm
Item Weight: 706 g
Type: Textbook
Author: Uwe Naumann, Laurent Hascoet, Christele Faure, George Corliss, Andreas Griewank
Item Width: 155 mm
Format: Paperback
