Publication: Native Handling of Message-Passing Communication in Data-Flow Analysis
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Native Handling of Message-Passing Communication in Data-Flow Analysis

- incollection -
 

Author(s)
Valérie Pascual , Laurent Hascoët

Published in
Recent Advances in Algorithmic Differentiation

Editor(s)
Shaun Forth, Paul Hovland, Eric Phipps, Jean Utke, Andrea Walther

Year
2012

Publisher
Springer

Abstract
Automatic Differentiation by program transformation uses static data-flow analysis to produce efficient code. This data-flow analysis must be adapted for parallel programs with Message-Passing communication. Starting from a context-sensitive and flow-sensitive data-flow analysis scheme initially devised for sequential codes, we extend this scheme for parallel codes. This extension is independent of the particular analysis and does not require a modification of the code’s internal representation, i.e. the flow graph. This extension relies on an accurate matching of communication points, which can’t be found automatically in general, and thus new user directives prove useful.

Cross-References
Forth2012RAi

AD Theory and Techniques
Parallelism

BibTeX
@INCOLLECTION{
         Pascual2012NHo,
       title = "Native Handling of Message-Passing Communication in Data-Flow Analysis",
       doi = "10.1007/978-3-642-30023-3_8",
       author = "Val{\'e}rie Pascual and Laurent Hasco{\"e}t",
       abstract = "Automatic Differentiation by program transformation uses static data-flow analysis
         to produce efficient code. This data-flow analysis must be adapted for parallel programs with
         Message-Passing communication. Starting from a context-sensitive and flow-sensitive data-flow
         analysis scheme initially devised for sequential codes, we extend this scheme for parallel codes.
         This extension is independent of the particular analysis and does not require a modification of the
         code’s internal representation, i.e. the flow graph. This extension relies on an accurate
         matching of communication points, which can’t be found automatically in general, and thus
         new user directives prove useful.",
       pages = "83--92",
       crossref = "Forth2012RAi",
       booktitle = "Recent Advances in Algorithmic Differentiation",
       series = "Lecture Notes in Computational Science and Engineering",
       publisher = "Springer",
       address = "Berlin",
       volume = "87",
       editor = "Shaun Forth and Paul Hovland and Eric Phipps and Jean Utke and Andrea Walther",
       isbn = "978-3-540-68935-5",
       issn = "1439-7358",
       year = "2012",
       ad_theotech = "Parallelism"
}


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