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Expressiveness and Data-Flow Compilation of OpenMP Streaming Programs

Antoniu Pop 1 Albert Cohen 1 
1 Parkas - Parallélisme de Kahn Synchrone
DI-ENS - Département d'informatique - ENS Paris, Inria Paris-Rocquencourt, CNRS - Centre National de la Recherche Scientifique : UMR 8548
Abstract : We present a data-flow extension of OpenMP to express highly dynamic control and data flow over nested, dependent tasks. The language supports dynamic creation, modular composition, variable and unbounded sets of producers/consumers, separate compilation, and first-class streams. These features, enabled by our original compilation flow, allow translating high-level parallel programming patterns, like dependences arising from StarSs' array regions, or universal low-level primitives like futures. In particular, these dynamic features can be embedded efficiently and naturally into an unmanaged imperative language, avoiding the complexity and overhead of a concurrent garbage collector. We demonstrate the performance advantages of a data-flow execution model compared to more restricted task and barrier models. We also demonstrate the efficiency of our compilation and runtime algorithms for the support of complex dependence patterns arising from StarSs benchmarks.
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Submitted on : Monday, July 2, 2012 - 3:23:55 PM
Last modification on : Thursday, March 17, 2022 - 10:08:43 AM
Long-term archiving on: : Wednesday, October 3, 2012 - 3:15:15 AM


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  • HAL Id : hal-00710409, version 2



Antoniu Pop, Albert Cohen. Expressiveness and Data-Flow Compilation of OpenMP Streaming Programs. [Research Report] RR-8001, INRIA. 2012, pp.28. ⟨hal-00710409v2⟩



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