Adjoining strategies for multi-layered programs

Optimization Methods and Software

Volumn 17, Issue 1, 2002, Pages 129-164

  Faure, Christèle ^a  

^a PolySpace Technologies   (France)

Author keywords

Adjoint code; Automatic differentiation; Complexity; Computational differentiation; Forward mode; Reverse mode

Indexed keywords

COMPUTATIONAL COMPLEXITY; COMPUTATIONAL METHODS; DIFFERENTIATION (CALCULUS);

ADJOINT CODE; AUTOMATIC DIFFERENTIATION; COMPUTATIONAL DIFFERENTIATION; FORWARD MODE; REVERSE MODE;

MATHEMATICAL PROGRAMMING;

EID: 0036462813     PISSN: 10556788     EISSN: None     Source Type: Journal    
DOI: 10.1080/10556780290027800     Document Type: Article

References (20)

1. W. Baur and V. Strassen (1983). The complexity of partial derivatives. Theoretical Comp. Sci., 22, 317-330.
2. M. Berz. C.H. Bischof, G.F. Corliss and A. Griewank (Eds.) (1996). Computational differentiation: Applications, techniques, and tools, SIAM, Philadelphia.
3. C.H. Bischof and M.R. Haghighat (1996). Hierachical approaches to automatic differentiation. In: M. Berz, C. Bishcof, G. Corliss and A. Griewank (Eds.), Computational Differentiation: Applications, Techniques, and Tools. pp. 83-94. SIAM.
4. I. Charpentier (April 1998). Génération de codes adjoints: Traitement de la trajectoire du modèle direct., Rapport de recherche 3405, INRIA.
5. I. Charpentier and M. Ghemires (September 1997). Génération automatique de codes adjoints: Stratégies d'utilisation pour le logiciel Oddyssée. Application au code météorologigue Meso-NH, Rapport de recherceh 3251, INRIA.
6. C. Faure (Ed.) (November 1998). Automatic Differentiation for Adjoint Code Generation, Proceedings of imacs'aco, Automatic Differentiation session, Domaine de Voluceau - Rocquencourt - BP 105 - 78153 Le Chesnay Cedex (France), Rapport de recherche 3555, http://www.inria.fr/RRRT/RR-3555.html.
7. C. Faure (October 1998). Le Gradient de THYC3D par Odyssée, Rapport de recherche 3519, INRIA.
8. C. Faure and Y. Papegay (September 1998). Odyssée User's Guide. Version 1.7, Rapport technique 0224, INRIA.
9. R. Giering (1997). Tangent linear and Adjoint Model Compiler, Users manual, Unpublished available from http://pudlle.mit.edu/~ralf/tamc.
10. J.C. Gilbert, G. Le Vey and J. Masse (November 1991). La Différentiation Automatique de fonctions repésentées par des programmes, Rapport de recherche 1557, INRIA.
11. A. Griewank (1992). Achieving logarithmic growth of temporal and spatial complexity in reverse automatic differentiation. Optimization Methods and Software, 1, 35-54.
12. A. Griewank (2000). Evaluating Derivatives. Principles and Techniques of Algorithmic Differentiation, SIAM.
13. A. Griewank and G.F. Corliss (Eds.) (1991). Automatic differentiation of algorithms: Theory, implementation, and applications, SIAM, Philadelphia.
14. A. Griewank and A. Walther (1997). Treeverse: An implementation of the check-pointing for the reverse or adjoint mode of differentiation, Tech. Report, TU Dresden.
15. J. Grimm, L. Pottier and N. Rostaing-Schmidt (1996). Optimal time and minimum space-time product for reversing a certain class of programs. In: M. Berz. C. Bischof, G. Corliss and A. Griewank (Eds.), Computational Differentiation: Applications, Techniques, and Tools. pp. 95-106. SIAM.
16. J. Morgenstern (1985). How to compute fast a function and all its derivatives, a variation on the theorem of Baur-Strassen. Sigact News, 16, 60-62.
17. G.M. Ostrovskii, Yu. M. Volin and W. W. Borisov (1971). Uber die berechnung von ableitungen, Wiss. Z. Tech. Hochschule fur Chimie, 13, 382-384.
18. B. Speelpening (1980). Compiling fast partial derivatives of functions given by algorithms, Ph.D. thesis, University of Illinois, Urbana-Champaign.
19. M. Tadjouddine, C. Faure and F. Eyssette (September 1998). Sparse Jacobian Computation in Automatic Differentiation by Static Program Analysis, Static Analysis. In G. Levi (ED.). Lecture Notes in Computer Science, Vol. 1503, pp. 311-326. Springer-Verlag.
20. Yu.M. Volin and G.M. Ostrovskii (1985). Automatic computation of derivatives with the use of the multilevel differentiating technique - 1. algorithmic basis. Computers & Mathematics with Applications, 11(11), 1099-1114.