DKPN: A Composite Dataflow/Kahn Process Networks Execution Model

Abstract : To address the high level of dynamism and variability in modern streaming applications (e.g. video decoding) as well as the difficulties in programming heterogeneous MPSoCs, we propose a novel execution model based upon both dataflow and Kahn process networks. This paper presents the semantics and properties of this hierarchical and parametric model, called DKPN. Parameters are classified and it is shown that hints can be derived to improve the execution. A scheduler framework and policies to back the model are also exposed. Experiments illustrate the benefits of our approach.
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Communication dans un congrès
24th Euromicro International Conference on Parallel, Distributed and Network-based processing, Feb 2016, Heraklion Crete, Greece. 2016
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https://hal.inria.fr/hal-01234333
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Dernière modification le : lundi 24 septembre 2018 - 11:34:03
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  • HAL Id : hal-01234333, version 1

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Paul-Antoine Arras, Didier Fuin, Emmanuel Jeannot, Samuel Thibault. DKPN: A Composite Dataflow/Kahn Process Networks Execution Model. 24th Euromicro International Conference on Parallel, Distributed and Network-based processing, Feb 2016, Heraklion Crete, Greece. 2016. 〈hal-01234333〉

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