On learning the energy model of an MPSoC for convex optimization

E. Nogues 1 Daniel Ménard 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 : mardi 11 décembre 2018 - 15:22:47

Identifiants

Collections

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

Citation

E. Nogues, Daniel Ménard, 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〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

142