Publication: Data structure and algorithms for fast automatic differentiation
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Data structure and algorithms for fast automatic differentiation

- Article in a journal -
 

Area
General Purpose Software Packages

Author(s)
M. Hall I. Tsukanov

Published in
International Journal for Numerical Methods in Engineering

Year
2003

Abstract
In this paper we discuss the data structure and algorithms for the direct application of generalized Leibnitz rules to the numerical computation of partial derivatives in forward mode. The proposed data structure provides constant time access to the partial derivatives, which accelerates the automatic differentiation computations. The interaction among elements of the data structure is explained by several numerical examples. The paper contains analysis of the developed data structure and algorithms.

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BibTeX
@ARTICLE{
         Tsukanov2003Dsa,
       AUTHOR = "I. Tsukanov, M. Hall",
       TITLE = "Data structure and algorithms for fast automatic differentiation",
       JOURNAL = "International Journal for Numerical Methods in Engineering",
       YEAR = "2003",
       volume = "56",
       number = "13",
       pages = "1949-1972",
       month = "April",
       abstract = "In this paper we discuss the data structure and algorithms for the direct
         application of generalized Leibnitz rules to the numerical computation of partial derivatives in
         forward mode. The proposed data structure provides constant time access to the partial derivatives,
         which accelerates the automatic differentiation computations. The interaction among elements of the
         data structure is explained by several numerical examples. The paper contains analysis of the
         developed data structure and algorithms.",
       keywords = "multivariable arbitrary-order automatic differentiation, Taylor coefficients,
         Leibnitz chain rules, data structure",
       ad_area = "General Purpose Software Packages",
       ad_tools = "FFADLib",
       ad_theotech = "Implementation Strategies"
}


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