An Energy-Aware Scheduler for Dynamically Reconfigurable Multi-Core Systems
| Autor: | Robin Bonamy, Sébastien Bilavarn, Fabrice Muller |
|---|---|
| Přispěvatelé: | Laboratoire d'Electronique, Antennes et Télécommunications (LEAT), Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), European Project: CA505,BENEFIC, Université Nice Sophia Antipolis (1965 - 2019) (UNS) |
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
Multi-core processor
Computer science power aware computing 020208 electrical & electronic engineering Software execution Control reconfiguration 02 engineering and technology 020202 computer hardware & architecture Scheduling (computing) multiprocessing systems Computer architecture 0202 electrical engineering electronic engineering information engineering Hardware acceleration [INFO.INFO-ES]Computer Science [cs]/Embedded Systems scheduling Decoding methods |
| Zdroj: | 6th International Workshop on Reconfigurable Communication-centric Systems-on-Chip, ReCoSoC 2015 6th International Workshop on Reconfigurable Communication-centric Systems-on-Chip, ReCoSoC 2015, Jun 2015, Bremen, Germany ReCoSoC 6th International Workshop on Reconfigurable Communication-centric Systems-on-Chip, ReCoSoC 2015, Jun 2015, Bremen, Germany. pp.1-6, ⟨10.1109/ReCoSoC.2015.7238084⟩ |
| DOI: | 10.1109/ReCoSoC.2015.7238084⟩ |
| Popis: | International audience; This paper describes an energy-aware scheduling approach intended for use in heterogeneous multiprocessors supporting hardware acceleration with Dynamic and Partial Re-configuration. Scheduler decisions rely on pragmatic power and energy models to map the load across cores and reconfigurable regions with regards to the actual power costs. Results on a multithreaded H.264/AVC profile decoder with three possible hardware functions on a Xilinx Zynq based platform report energy gains up to 44.1% over full software execution and 49.6% over static hardware / software execution, while ensuring real-time decoding requirement. |
| Databáze: | OpenAIRE |
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