Automatic Differentiation of Algorithms: From Simulation to Optimization [9780387953052]

Overview

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.

The book, Automatic Differentiation of Algorithms: From Simulation to Optimization [Bulk, Wholesale, Quantity] ISBN#9780387953052 in Hardcover by may be ordered in bulk quantities. Minimum starts at 25 copies. Availability based on publisher status and quantity being ordered.