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Title

Efficient scheduling policies for dynamic data flow programs executed on multi-core

Authors
Michalska, Malgorzata
Boutellier, Jani
Bezati, Endri
Mattavelli, Marco
Published in 11th International Meeting on Logistics Research. Lausanne (Suisse) - 7-9 septembre - . 2016
Abstract An important challenge of dataflow program implementations on multi-core platforms is the partitioning and scheduling providing the best possible throughput when satisfying multiple objective functions. Not only it has been proven that these problems are NP-complete, but also the quality of any heuristic approach can be affected by other factors (e.g., buffer dimensioning, influence of an established partitioning configuration and scheduling strategy on each other, uncertainties of a compiler affecting the profiling information). This paper proposes an evaluation of alternative partitioning and scheduling configurations based on the application profiling results. It investigates the impact of the scheduling on the overall execution time, and verifies which policies could further drive the metaheuristic-based search of a close-to-optimal partitioning configuration.
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MICHALSKA, Malgorzata et al. Efficient scheduling policies for dynamic data flow programs executed on multi-core. In: 11th International Meeting on Logistics Research. Lausanne (Suisse). [s.l.] : [s.n.], 2016. https://archive-ouverte.unige.ch/unige:91453

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