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Communication Dans Un Congrès Année : 2017

On learning the energy model of an MPSoC for convex optimization

Résumé

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.
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Dates et versions

hal-01622480 , version 1 (24-10-2017)

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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⟩
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