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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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Submitted on : Tuesday, January 12, 2016 - 9:42:08 AM
Last modification on : Monday, December 20, 2021 - 4:50:15 PM
Long-term archiving on: : Thursday, November 10, 2016 - 11:36:03 PM


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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. ⟨10.1109/PDP.2016.34⟩. ⟨hal-01234333⟩



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