Automatic Differentiation of Algorithms (eBook, PDF)

From Simulation to Optimization
Redaktion: Corliss, George; Naumann, Uwe; Hascoet, Laurent; Griewank, Andreas; Faure, Christele

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Springer US
• Seitenzahl: 432
• Erscheinungstermin: 21. November 2013
• Englisch
• ISBN-13: 9781461300755
• Artikelnr.: 44179931

Inhaltsangabe

Part titles: Invited Contributions.- Parameter Identification and Least Squares.- Applications in Ode's and Optimal Control.- Applications in PDE's.- 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.