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Scientific Programming
Volume 9, Issue 1, Pages 1-10

Comparing Global Strategies for Coding Adjoints

Christèle Faure1 and Isabelle Charpentier2

1INRIA Sophia Antipolis, 2004 route des Lucioles, BP~93, F-06902 Sophia-Antipolis Cedex, France
2Projet IDOPT (CNRS, UJF, INRIA, INPG), 51 rue des mathématiques, BP 53, F-38041 Grenoble Cedex 9, France

Received 20 September 2001; Accepted 20 September 2001

Copyright © 2001 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


From a computational point of view, sensitivity analysis, calibration of a model, or variational data assimilation may be tackled after the differentiation of the numerical code representing the model into an adjoint code. This paper presents and compares methodologies to generate discrete adjoint codes. These methods can be implemented when hand writing adjoint codes, or within Automatic Differentiation (AD) tools. AD has been successfully applied to industrial codes that were large and general enough to fully validate this new technology. We compare these methodologies in terms of execution time and memory requirement on a one dimensional thermal-hydraulic module for two-phase flow modeling. With regard to this experiment, some development axes for AD tools are extracted as well as methods for AD tool users to get efficient adjoint codes semi-automatically. The next objective is to generate automatically adjoint codes as efficient as hand written ones.