Lecture Notes in Computational Science and Engineering

Applications, Theory, and Implementations

By: H. Martin BÃ¼cker (Editor), George Corliss (Editor), Paul Hovland (Editor)

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Paperback | 14 December 2005

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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.

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Perspectives on Automatic Differentiation: Past, Present, and Future?	p. 1
Backwards Differentiation in AD and Neural Nets: Past Links and New Opportunities	p. 15
Solutions of ODEs with Removable Singularities	p. 35
Automatic Propagation of Uncertainties	p. 47
High-Order Representation of Poincaré Maps	p. 59
Computation of Matrix Permanent with Automatic Differentiation	p. 67
Computing Sparse Jacobian Matrices Optimally	p. 77
Application of AD-based Quasi-Newton Methods to Stiff ODEs	p. 89
Reduction of Storage Requirement by Checkpointing for Time-Dependent Optimal Control Problems in ODEs	p. 99
Improving the Performance of the Vertex Elimination Algorithm for Derivative Calculation	p. 111
Flattening Basic Blocks	p. 121
The Adjoint Data-Flow Analyses: Formalization, Properties, and Applications	p. 135
Semiautomatic Differentiation for Efficient Gradient Computations	p. 147
Computing Adjoints with the NAGWare Fortran 95 Compiler	p. 159
Extension of TAPENADE toward Fortran 95	p. 171
A Macro Language for Derivative Definition in ADiMat	p. 181
Transforming Equation-Based Models in Process Engineering	p. 189
Simulation and Optimization of the Tevatron Accelerator	p. 199
Periodic Orbits of Hybrid Systems and Parameter Estimation via AD	p. 211
Implementation of Automatic Differentiation Tools for Multicriteria IMRT Optimization	p. 225
Application of Targeted Automatic Differentiation to Large-Scale Dynamic Optimization	p. 235
Automatic Differentiation: A Tool for Variational Data Assimilation and Adjoint Sensitivity Analysis for Flood Modeling	p. 249
Development of an Adjoint for a Complex Atmospheric Model, the ARPS, using TAF	p. 263
Tangent Linear and Adjoint Versions of NASA/GMAO's Fortran 90 Global Weather Forecast Model	p. 275
Efficient Sensitivities for the Spin-Up Phase	p. 285
Streamlined Circuit Device Model Development with fREEDA“ãnd ADOL-C	p. 295
Adjoint Differentiation of a Structural Dynamics Solver	p. 309
A Bibliography of Automatic Differentiation	p. 321
References	p. 323
Index	p. 355
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Lecture Notes in Computational Science and Engineering

Applications, Theory, and Implementations

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