Adifor 2.0: automatic differentiation of Fortran 77 programs

Adifor 2.0: automatic differentiation of Fortran 77 programs

Numerical codes that calculate not only a result, but also the derivatives of the variables with respect to each other, facilitate sensitivity analysis, inverse problem solving, and optimization. The paper considers how Adifor 2.0, which won the 1995 Wilkinson Prize for Numerical Software, can autom...

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Veröffentlicht in:IEEE computational science & engineering 1996-01, Vol.3 (3), p.18-32
Hauptverfasser: Bischof, C., Khademi, P., Mauer, A., Carle, A.
Format: Artikel
Sprache:eng
Schlagworte:
Application software
Computational modeling
Design optimization
Differential equations
Inverse problems
MIMO
Nonlinear equations
Partial differential equations
Pervasive computing
Sensitivity analysis
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Zusammenfassung:Numerical codes that calculate not only a result, but also the derivatives of the variables with respect to each other, facilitate sensitivity analysis, inverse problem solving, and optimization. The paper considers how Adifor 2.0, which won the 1995 Wilkinson Prize for Numerical Software, can automatically differentiate complicated Fortran code much faster than a programmer can do it by hand. The Adifor system has three main components: the AdiFor preprocessor, the ADIntrinsics exception-handling system, and the SparsLinC library.
ISSN:1070-9924
1558-190X
DOI:10.1109/99.537089