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User Interaction Aware Reinforcement Learning for Power and Thermal Efficiency of CPU-GPU Mobile MPSoCs

Dey, Somdip and Singh, Amit and Wang, Xiaohang and McDonald-Maier, Klaus (2020) User Interaction Aware Reinforcement Learning for Power and Thermal Efficiency of CPU-GPU Mobile MPSoCs. In: Design, Automation, and Test in Europe 2020 (DATE 2020), 2020-04-21 - 2020-05-31, Grenoble, France.

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Abstract

Mobile user’s usage behaviour changes throughout the day and the desirable Quality of Service (QoS) could thus change for each session. In this paper, we propose a QoS aware agent to monitor mobile user’s usage behaviour to find the target frame rate, which satisfies the desired user’s QoS, and applies reinforcement learning based DVFS on a CPU-GPU MPSoC to satisfy the frame rate requirement. Experimental study on a real Exynos hardware platform shows that our proposed agent is able to achieve a maximum of 50% power saving and 29% reduction in peak temperature compared to stock Android’s power saving scheme. It also outperforms the existing state-of-the-art power and thermal management scheme by 41% and 19%, respectively.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: _not provided_
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 22 May 2020 14:56
Last Modified: 22 May 2020 15:15
URI: http://repository.essex.ac.uk/id/eprint/27546

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