Publication: Algorithm 755: ADOL-C: A Package for the Automatic Differentiation of Algorithms Written in C/ C++
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Algorithm 755: ADOL-C: A Package for the Automatic Differentiation of Algorithms Written in C/ C++

- Article in a journal -
 

Author(s)
Andreas Griewank , David Juedes , Jean Utke

Published in
ACM Transactions on Mathematical Software

Year
1996

Abstract
The C++ package ADOL-C described here facilitates the evaluation of first and higher derivatives of vector functions that are defined by computer programs written in C or C++. The resulting derivative evaluation routines may be called from C/C++, Fortran, or any other language that can be linked with C. The numerical values of derivative vectors are obtained free of truncation errors at a small multiple of the run-time and randomly accessed memory of the given function evaluation program. Derivative matrices are obtained by columns or rows. For solution curves defined by ordinary differential equations, special routines are provided that evaluate the Taylor coefficient vectors and their Jacobians with respect to the current state vector. The derivative calculations involve a possibly substantial (but always predictable) amount of data that are accessed strictly sequentially and are therefore automatically paged out to external files.

AD Tools
ADOL-C

AD Theory and Techniques
Hessian, Reverse Mode, Taylor Arithmetic, Forward Mode

BibTeX
@ARTICLE{
         Griewank1996AAC,
       author = "Andreas Griewank and David Juedes and Jean Utke",
       title = "{Algorithm 755}: {ADOL-C}: A Package for the Automatic Differentiation of Algorithms
         Written in {C\slash C++}",
       journal = "{ACM} Transactions on Mathematical Software",
       volume = "22",
       number = "2",
       pages = "131--167",
       year = "1996",
       CODEN = "ACMSCU",
       ISSN = "0098-3500",
       bibsource = "http://www.acm.org/pubs/contents/journals/toms/",
       URL = "http://doi.acm.org/10.1145/229473.229474",
       abstract = "The C++ package ADOL-C described here facilitates the evaluation of first and
         higher derivatives of vector functions that are defined by computer programs written in C or C++.
         The resulting derivative evaluation routines may be called from C/C++, Fortran, or any other
         language that can be linked with C. The numerical values of derivative vectors are obtained free of
         truncation errors at a small multiple of the run-time and randomly accessed memory of the given
         function evaluation program. Derivative matrices are obtained by columns or rows. For solution
         curves defined by ordinary differential equations, special routines are provided that evaluate the
         Taylor coefficient vectors and their Jacobians with respect to the current state vector. The
         derivative calculations involve a possibly substantial (but always predictable) amount of data that
         are accessed strictly sequentially and are therefore automatically paged out to external files.",
       keywords = "algorithms; performance",
       subject = "{\bf G.1.4}: Mathematics of Computing, NUMERICAL ANALYSIS, Quadrature and
         Numerical Differentiation. {\bf I.1.2}: Computing Methodologies, ALGEBRAIC MANIPULATION,
         Algorithms, Analysis of algorithms. {\bf I.1.2}: Computing Methodologies, ALGEBRAIC
         MANIPULATION, Algorithms.",
       comment = "Also appeared as Preprint MCS--P180--1190, Mathematics and Computer Science
         Division, Argonne National Laboratory, Argonne, Ill., November 1990.",
       url = "ftp://info.mcs.anl.gov/pub/tech_reports/reports/TM162.ps",
       ad_tools = "ADOL-C",
       ad_theotech = "Hessian, Reverse Mode, Taylor Arithmetic, Forward Mode"
}


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