Multi-device collaborative management through knowledge sharing

Abstract

Rapidly evolving embedded applications continuously demand more functionality and better performance under tight energy and thermal budgets, and maintaining high energy efficiency has become a significant design challenge for mobile devices. Although learning-based runtime power management can adapt to dynamic conditions, it is a challenging issue to quickly find an efficient management policy under ever-increasing hardware and software complexity. In this work, we propose a multi-device collaborative power management approach to address this issue. The collaborative power management periodically shares knowledge among multiple devices to accelerate the learning process and improve the quality of learned policies. We integrate the proposed method with dynamic voltage and frequency scaling (DVFS) on the multicore processors in mobile devices. Experimental results on realistic applications show that the collaborative power management can achieve on average 8x speedup and 10% energy saving compared with state-of-the-art learning-based approaches.