Automatic Differentiation of Algorithms: From Simulation to Optimization. Professional/practitioner

Automatic Differentiation of Algorithms: From Simulation to Optimization. Professional/practitioner 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. Autor: George Corliss, Christele Faure Wydawnictwo: Springer EN Rok wydania: 2014 Okładka: miękka Liczba stron: 432 Wymiary: 23.5 x 15.5 x 1.5 cm Język: angielski ISBN: 9781461265436