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Giering, Ralf - FastOpt
http:/ / www.FastOpt.com GAMM, Dresden, March 2004
TAF and TAC++: Source-to-source transformation in
Adjoint and Hessian of a Satellite Code written in C
Generating the tangent linear and adjoint models of the DAO finite volume GCM's dynamical core by means of TAF
Automatic Sparsity Detection Implemented as a Source-to-Source Transformation
FastOpt CCDAS Using CCDAS for Integration
Generating tangent linear and adjoint versions of NASA/GMAO's Fortran-90
Efficient Computation of Hedge-Sensitivities via Automatic
Design Optimization International Conference, April 5 -April 7 2005, Las Palmas, Spain,
Topological Design Based on Highly Efficient Adjoints Generated by Automatic Differentiation
SScience &cience & TTechnologyechnology AAppliedpplied RRemoteemote SSensingensing
Automatic Differentiation of Navier-Stokes Solvers
FastOpt CCDAS Integration and
Automatically generated tangent and adjoint
Numbers for TLM and ADM give CPU time for (model + gradient) rel. to model Due to bug of SGI-Fortran compiler,
covariance of uncertainty measurements + model
Efficient Sensitivities for the Spin-up Phase
FastOpt CAMELS An example of an
FastOpt CAMELS A prototype of a data
The automatic differentiation tool TAF
Towards a tool for forward and reverse mode source to source transformation in C++
FastOpt CAMELS A prototype of a carbon
Supporting the improvement of the carbon observing system by
Fortran codes recently differentiated by means of
FastOpt CCDAS Assimilation
