Abstract
Employing multicore in mobile computing such as smartphone and IoT (Internet of Things) device is a double-edged sword. It provides ample computing capabilities required in recent intelligent mobile services including voice recognition, image processing, big data analysis, and deep learning. However, it requires a great deal of power consumption, which causes creating a thermal hot spot and putting pressure on the energy resource in a mobile device. In this paper, we propose a novel framework that integrates two well-known low-power techniques, DPM (Dynamic Power Management) and DVFS (Dynamic Voltage and Frequency Scaling) for energy efficiency in multicore mobile systems. The key feature of the proposed framework is adaptability. By monitoring the online resource usage such as CPU utilization and power consumption, the framework can orchestrate diverse DPM and DVFS policies according to workload characteristics. Real implementation based experiments using three mobile devices have shown that it can reduce the power consumption ranging from 22% to 79%, while affecting negligibly the performance of workloads.
Highlights
Intelligent services are actively introduced into mobile computing environments [1, 2]
Smartphones have the heterogeneous multicore architecture, called big.LITTLE, which consists of performance-optimized big cores and energy-optimized little cores with a single ISA (Instruction Set Architecture) [3]
Tawara et al design a framework, called idle reduction, which turns on/off cores or changes the CPU frequency dynamically according to the intensity of workloads [8]. These two works are closely related to our work in that they integrate DPM and DVFS and apply them adaptively based on workload characteristics
Summary
Intelligent services are actively introduced into mobile computing environments [1, 2]. Smartphones provide voice recognition and image processing for better HCI (Human Computer Interface) and big data processing and deep learning for context-aware services with the consideration of user personality To support such intelligent services efficiently, mobile computing devices are equipped with multiple cores. We propose a new low-power framework for multicore mobile devices It supports both DPM and DVFS in an integrated manner. The policy manager provides a rule regarding how to integrate DPM and DVFS techniques based on their overhead and effect on the power consumption. It applies the integrated solution appropriately according to the resource usage characteristics of applications.
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