Automatic Differentiation of Algorithms (Hardcover)

George Corliss

ISBN 10: 0387953051 / ISBN 13: 9780387953052

Verlag: Springer-Verlag New York Inc., New York, NY, 2002

Beschreibung

Hardcover. 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. A 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Bestandsnummer des Verkäufers 9780387953052

Bibliografische Details

• Titel: Automatic Differentiation of Algorithms (Hardcover)
• Verlag: Springer-Verlag New York Inc., New York, NY
• Erscheinungsjahr: 2002
• Sprache: Englisch
• ISBN-10: 0387953051
• ISBN-13: 9780387953052
• Einband: Hardcover
• Zustand: new

Über diesen Titel

Inhaltsangabe

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. The key objective is to survey the field and present the recent developments. In doing so the topics covered shed light on a variety of perspectives. They reflect the mathematical aspects, such as the differentiation of iterative processes, and the analysis of nonsmooth code. They cover the scientific programming aspects, such as the use of adjoints in optimization and the propagation of rounding errors. They also cover "implementation" problems.