On learning the energy model of an MPSoC for convex optimization

E. Nogues 1 D. Menard 1 A. Mercat 1 M. Pelcat 2
1 IETR - Institut d'Electronique et de Télécommunications de Rennes
2 IP - Institut Pascal - Clermont Auvergne
Abstract : The energy efficiency of a Multiprocessor SoC (MPSoC) is enhanced by complex hardware features such as Dynamic Voltage and Frequency Scaling (DVFS) and Dynamic Power Management (DPM). This paper proposes a methodology to learn an energy model from real power measurements. From this energy model, a convex optimization framework can determine the optimal energy efficient operating point in terms of frequency and number of active cores in an MPSoC. Experimental data are reported using a Samsung Exynos 5410 MPSoC. They show that a precise yet relatively simple model can be derived. © 2017 ACM.
Keywords : Convex optimization Energy consumption Multi-core platform
Type de document :
Communication dans un congrès
14th ACM International Conference on Computing Frontiers, CF 2017, May 2017, Ischia, Italy. 〈10.1145/3075564.3078893〉
Liste complète des métadonnées
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01622480
Contributeur : Laurent Jonchère <>
Soumis le : mardi 24 octobre 2017 - 14:12:26
Dernière modification le : vendredi 20 avril 2018 - 01:30:22

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IETR | UNIV-NANTES | SUP_IETR | SIGMA-CLERMONT | CENTRALESUPELEC | UR1-UFR-ISTIC | IETR-VAADER | PRES_CLERMONT | INSTITUT_PASCAL | UNIV-RENNES

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E. Nogues, D. Menard, A. Mercat, M. Pelcat. On learning the energy model of an MPSoC for convex optimization. 14th ACM International Conference on Computing Frontiers, CF 2017, May 2017, Ischia, Italy. 〈10.1145/3075564.3078893〉. 〈hal-01622480〉

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