Automatic Differentiation: Applications, Theory, and Implementations
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Automatic Differentiation: Applications, Theory, and Implementations: (50 Lecture Notes in Computational Science and Engineering)

Automatic Differentiation: Applications, Theory, and Implementations: (50 Lecture Notes in Computational Science and Engineering)


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About the Book

The Fourth International Conference on Automatic Di?erentiation was held July20-23inChicago,Illinois.Theconferenceincludedaonedayshortcourse, 42 presentations, and a workshop for tool developers. This gathering of au- matic di?erentiation researchers extended a sequence that began in Breck- ridge, Colorado, in 1991 and continued in Santa Fe, New Mexico, in 1996 and Nice, France, in 2000. We invited conference participants and the general - tomatic di?erentiation community to submit papers to this special collection. The28acceptedpapersre?ectthestateoftheartinautomaticdi?erentiation. The number of automatic di?erentiation tools based on compiler techn- ogy continues to expand. The papers in this volume discuss the implem- tation and application of several compiler-based tools for Fortran, including the venerable ADIFOR, an extended NAGWare compiler, TAF, and TAPE- NADE. While great progress has been made toward robust, compiler-based tools for C/C++, most notably in the form of the ADIC and TAC++ tools, for now operator-overloading tools such as ADOL-C remain the undisputed champions for reverse-mode automatic di?erentiation of C++. Tools for - tomatic di?erentiation of high level languages, including COSY and ADiMat, continue to grow in importance as the productivity gains o? ered by high-level programming are recognized.

Table of Contents:
Perspectives on Automatic Differentiation: Past, Present, and Future?.- Backwards Differentiation in AD and Neural Nets: Past Links and New Opportunities.- Solutions of ODEs with Removable Singularities.- Automatic Propagation of Uncertainties.- High-Order Representation of Poincarée Maps.- Computation of Matrix Permanent with Automatic Differentiation.- Computing Sparse Jacobian Matrices Optimally.- Application of AD-based Quasi-Newton Methods to Stiff ODEs.- Reduction of Storage Requirement by Checkpointing for Time-Dependent Optimal Control Problems in ODEs.- Improving the Performance of the Vertex Elimination Algorithm for Derivative Calculation.- Flattening Basic Blocks.- The Adjoint Data-Flow Analyses: Formalization, Properties, and Applications.- Semiautomatic Differentiation for Efficient Gradient Computations.- Computing Adjoints with the NAGWare Fortran 95 Compiler.- Transforming Equation-Based Models in Process Engineering.- Extension of TAPENADE toward Fortran 95.- A Macro Language for Derivative Definition in ADiMat.- Simulation and Optimization of the Tevatron Accelerator.- Periodic Orbits of Hybrid Systems and Parameter Estimation via AD.- Implementation of Automatic Differentiation Tools for Multicriteria IMRT Optimization.- Application of Targeted Automatic Differentiation to Large-Scale Dynamic Optimization.- Automatic Differentiation: A Tool for Variational Data Assimilation and Adjoint Sensitivity Analysis for Flood Modeling.- Development of an Adjoint for a Complex Atmospheric Model, the ARPS, using TAF.- Tangent Linear and Adjoint Versions of NASA/GMAO’s Fortran 90 Global Weather Forecast Model.- Efficient Sensitivities for the Spin-Up Phase.- Streamlined Circuit Device Model Development with fREEDAR® ãnd ADOL-C.- Adjoint Differentiation of aStructural Dynamics Solver.- A Bibliography of Automatic Differentiation.


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Product Details
  • ISBN-13: 9783540284031
  • Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
  • Publisher Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Height: 235 mm
  • No of Pages: 370
  • Returnable: Y
  • Width: 155 mm
  • ISBN-10: 3540284036
  • Publisher Date: 14 Dec 2005
  • Binding: Paperback
  • Language: English
  • Returnable: Y
  • Series Title: 50 Lecture Notes in Computational Science and Engineering


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