Graceful performance adaption through hardware-software interaction for autonomous battery management of multicore smartphones

Abstract

Despite advances in multicore smartphone technologies, battery consumption still remains one of customer’s least satisfying features. This is because existing energy saving techniques do not consider the electrochemical characteristics of batteries, which causes battery consumption to vary unpredictably, both within and across applications. Additionally, these techniques provide application specific fixed performance degradation in order to reduce energy consumption. Having a performance penalty, even when a battery is fully charged, adds to customer dissatisfaction. We propose a control-based approach for runtime power management of multicore smartphones, which scales the frequency of processing cores in response to the battery consumption, taking into account the electrochemical characteristics of a battery. The objective is to enable graceful performance modulation, which adapts with application and battery availability in a predictable manner, improving quality-of-userexperience. Our control approach is practically demonstrated on embedded Linux running on Cortex A15-based smartphone development platform from nvidia. A thorough validation with mobile and Java workloads demonstrate 2.9x improvement in
battery availability compared to state-of-the-art approaches.

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ORCID for Geoff Merrett: orcid.org/0000-0003-4980-3894

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