Automatic Differentiation of Algorithms

版本说明：1

作     者：George Corliss Christèle Faure Andreas Griewank Laurent Hascoët Uwe Naumann 

I S B N：(纸本) 9780387953052;9781461265436 

出 版 社：Springer New York  NY 

出 版 年：1000年

页      数：XXVII, 432页

主 题 词：Computer Science, general 

摘      要：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.