BibTeX
@INPROCEEDINGS{
         Kowarz2008PDC,
       title = "Parallel Derivative Computation Using {ADOL-C}",
       author = "A. Kowarz and A. Walther",
       editor = "W. Nagel and R. Hoffmann and A. Koch",
       year = "2008",
       booktitle = "Proceedings of PASA 2008",
       series = "Lecture Notes in Informatics, Vol. 124",
       pages = "83--92",
       abstract = "Derivative computation using Automatic Differentiation (AD) is often considered to
         operate purely serial. Performing the differentiation task in parallel may require the applied
         AD-tool to extract parallelization information from the user function, transform it, and apply this
         new strategy in the differentiation process. Furthermore, when using the reverse mode of AD, it must
         be ensured that no data races are introduced due to the reversed data access scheme. Considering an
         operator overloading based AD-tool, an additional challenge is to be met: Parallelization statements
         are typically not recognized. In this paper, we present and discuss the parallelization approach
         that we have integrated into ADOL-C, an operator overloading based AD-tool for the differentiation
         of C/C++ programs. The advantages of the approach are clarified by means of the parallel
         differentiation of a function that handles the time evolution of a 1D-quantum plasma.",
       ad_area = "Physics",
       ad_tools = "ADOL-C",
       ad_theotech = "Parallelism",
       url = "http://subs.emis.de/LNI/Proceedings/Proceedings124/article2036.html"
}