Subdirectories of Automatic Differentiation:
Websites on Automatic Differentiation: ADiMat Using the source transformation approach to apply automatic differentiation (AD) concepts to Matlab codes, ADiMat is developed at the RWTH Aachen University, Germany. Binaries can be obtained upon request from the author. ADMAT The Numerical solution of large scale nonlinear problems in Matlab involves computing the derivative information in the form of gradients, Jacobian and Hessian matrices. ADMAT/ADMIT is developed by the University of Waterloo, Canada. Downloads are available after personal registration. ADOL-C A package for Automatic Differentiation of algorithms written in C/C++, developed by the TU Dresden, Germany. Source code, manual and examples are freely available for download. Autodiff.org Overview, resources and examples on of Automatic Differentiation, as well as and index of conferences and publications. Automatic Differentiation: Theory, Methods, and Applications An overview of projects and applications at the Supercomputing Center of the Chinese Academy of Sciences. The Computational Differentiation Project Technologies for generating efficient derivative code for models implemented as computer programs, developed by the Argonne National Laboratory, USA. While the tool ADIC (ANSI C) is available for download as source code, ADIFOR (Fortran) is only available through personal registration. COSY Infinity A system for the use of automatic differentiation and Taylor Models in Fortran and C++, developed by the Michigan State University, USA. While site contains links to manual and description, the tool is only available through registration. CppAD A Package for Differentiation of C++ Algorithms developed by the COmputational INfrastructure for Operations Research (COIN-OR) project. Windows and Linux Binaries are available for download as well as documentation and source code. FastOpt Company provides tools for Automatic Differentiation and their application in Geoscience, Economics, Engineering and Mathematics. Home of the commercial tools TAF (Fortran) and TAC++ (C++). INTLAB INTerval LABoratory is the Matlab toolbox for self-validating algorithms, developed by the Hamburg University of Technology, Germany. Along with examples and related publications, the source code can be downloaded freely for private and academic use. Commercial applications require a license. Matlab Automatic Differentiation (MAD) Automatic Differentiation addon for the TOMLAB optimization package for Matlab, developed by Cranfield University, UK. Site contains links to related publications and User Guide, however the package is commercially distributed by TOMLAB. OpenAD A flexible, modular, open source tool that can generate adjoint codes of numerical simulation programs written in C and Fortan. Along with examples, case studies, documentation and related publications, Test Binaries can be downloaded from freely from CVS tree. REVOLVE For adjoint calculations, derivative computations using the reverse mode of automatic differentiation, one may need to reverse the execution of a computer program. Site contains links to source code for C and Fortran, as well as description and publication references. The Tangent linear and Adjoint Model Compiler (TAMC) A source-to-source translator that generates Fortran routines for computation of the first-order derivatives out of Fortran routines. Site contains documentation and references to publications. Usage is restricted to non-commercial and educational applications remotely via email. Wikipedia: Automatic Differentiation In mathematics and computer algebra, automatic differentiation is a method to numerically evaluate the derivative of a function specified by a computer program.
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