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On the performance of discrete adjoint CFD codes using automatic differentiation
Author(s) -
Müller J.D.,
Cusdin P.
Publication year - 2005
Publication title -
international journal for numerical methods in fluids
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.938
H-Index - 112
eISSN - 1097-0363
pISSN - 0271-2091
DOI - 10.1002/fld.885
Subject(s) - automatic differentiation , fortran , computational fluid dynamics , code (set theory) , computer science , software , transformation (genetics) , adjoint equation , tangent , source code , algorithm , computational science , theoretical computer science , mathematics , programming language , computation , geometry , partial differential equation , engineering , set (abstract data type) , mathematical analysis , biochemistry , chemistry , gene , aerospace engineering
Adjoint methods are a computationally inexpensive way of deriving sensitivity information where there are fewer dependent (cost) variables than there are independent (input) variables. Automatic differentiation (AD) software makes it possible to create discrete adjoint codes with minimal human effort, an issue that had previously restricted acceptance of adjoint CFD codes. In terms of computational performance, automatic code is often assumed to be inferior to hand code. The structure of the underlying code is critical to the performance of the transformed code. This paper reviews the implementation of AD on Fortran CFD codes and gives details of how small rearrangements can be used to produce competitive tangent and adjoint code using source transformation AD. Copyright © 2005 John Wiley & Sons, Ltd.