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Formal Methods in Computing
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muskel:SCPE:07 (Article)
Author(s) Marco Aldinucci, Marco Danelutto and Patrizio Dazzi
Title« MUSKEL: an expandable skeleton environment »
JournalScalable Computing: Practice and Experience
Volume8
Number4
Page(s)325-341
Year2007
URLhttp://www.scpe.org/index.php/scpe/article/view/429
Abstract
Programming models based on algorithmic skeletons promise to raise the level of abstraction perceived by programmers when implementing parallel applications, while guaranteeing good performance figures. At the same time, however, they restrict the freedom of programmers to implement arbitrary parallelism exploitation patterns. In fact, efficiency is achieved by restricting the parallelism exploitation patterns provided to the programmer to the useful ones for which efficient implementations, as well as useful and efficient compositions, are known. In this work we introduce muskel, a full Java library targeting workstation clusters, networks and grids and providing the programmers with a skeleton based parallel programming environment. muskel is implemented exploiting (macro) data flow technology, rather than the more usual skeleton technology relying on the use of implementation templates. Using data flow, muskel easily and efficiently implements both classical, predefined skeletons, and user-defined parallelism exploitation patterns. This provides a means to overcome some of the problems that Cole identified in his skeleton ``manifesto'' as the issues impairing skeleton success in the parallel programming arena. We discuss fully how user-defined skeletons are supported by exploiting a data flow implementation, experimental results and we also discuss extensions supporting the further characterization of skeletons with non-functional properties, such as security, through the use of Aspect Oriented Programming and annotations.

BibTeX code

@article{muskel:SCPE:07,
  volume = {8},
  number = {4},
  month = dec,
  author = {Marco Aldinucci and Marco Danelutto and Patrizio Dazzi},
  url = {http://www.scpe.org/index.php/scpe/article/view/429},
  abstract = {Programming models based on algorithmic skeletons promise to raise
              the level of abstraction perceived by programmers when
              implementing parallel applications, while guaranteeing good
              performance figures. At the same time, however, they restrict the
              freedom of programmers to implement arbitrary parallelism
              exploitation patterns. In fact, efficiency is achieved by
              restricting the parallelism exploitation patterns provided to the
              programmer to the useful ones for which efficient implementations,
              as well as useful and efficient compositions, are known. In this
              work we introduce muskel, a full Java library targeting
              workstation clusters, networks and grids and providing the
              programmers with a skeleton based parallel programming
              environment. muskel is implemented exploiting (macro) data flow
              technology, rather than the more usual skeleton technology relying
              on the use of implementation templates. Using data flow, muskel
              easily and efficiently implements both classical, predefined
              skeletons, and user-defined parallelism exploitation patterns.
              This provides a means to overcome some of the problems that Cole
              identified in his skeleton ``manifesto'' as the issues impairing
              skeleton success in the parallel programming arena. We discuss
              fully how user-defined skeletons are supported by exploiting a
              data flow implementation, experimental results and we also discuss
              extensions supporting the further characterization of skeletons
              with non-functional properties, such as security, through the use
              of Aspect Oriented Programming and annotations.},
  title = {MUSKEL: an expandable skeleton environment},
  journal = {Scalable Computing: Practice and Experience},
  pages = {325-341},
  year = {2007},
}


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