System-level Power/Performance Analysis and Management on Multicore-based Mobile Systems

Abstract

The usage of modern mobile devices (e.g., smartphones and tablets) is not limited to communication, the traditional usage of mobile phones. Recently, mobile devices have been widely used to perform various user-interactive scenarios, such as web browsing, social networking, multimedia streaming, and gaming. In this context, modern mobile devices have been designed by adopting high-performance processing units (e.g., asymmetric multicore CPU, GPU, and AI accelerator) to meet end-users’ requirements. The integration of the high-performance processing units in a single chip increases the quality-of-service (QoS). However, it also increases power density and therefore causes various power and thermal problems such as reduction of battery life, thermal hot spots, and overheating problems. PCs and server computers are not battery-powered, and their thermal problems can be solved by using a fan or liquid. However, these solutions are not suitable for modern mobile devices. Thus, analysis and management of execution behavior, which causes the degradation of power efficiency and performance, are essential to solving power and thermal problems occurring on modern mobile devices. However, system-level analysis and management of the execution become challenging due to the increasing complexity of mobile devices and the diversity of the user scenarios running on mobile devices. This dissertation presents two research topics that have been conducted to enable effective execution-behavior-analysis and power management of multicore-based modern mobile devices. The first topic is system-level application modeling for analysis of the dynamic execution behavior of multicore-based mobile systems. In this research, a generalized application model, as a task graph representation, is suggested with essential elements that must be included in nodes and edges. Then, an application modeling method is proposed to generate the generalized application model for Android-based mobile systems. To be used for the analysis of the thread-level execution behavior of modern mobile devices, the proposed method provides an adequate task unit to guarantee thread-level granularity. Besides, the proposed method uses kernel events occurring during the execution of the target application, instead of its source code; this enables modeling the entire dynamic-execution-behavior of various user scenarios running on modern mobile devices. Experimental results demonstrated that the proposed policy extracts reliable and realistic Android application models. In terms of CPU utilization, the average mean-absolute-error (MAE) of the proposed method was 2.58 %. Also, it was demonstrated that the proposed method extracts the application models with high consistency for various system configurations. Thus, the proposed method can be used for the analysis of the dynamic execution behavior of modern and future mobile systems. The second topic is user scenario-adaptive power management. In this research, a scenario-adaptive dynamic-voltage/frequency-scaling (DVFS) policy is proposed to balance the trade-off between energy consumption and QoS for various user scenarios. The proposed policy is adaptive to a wide range of user scenarios by using scenario characteristics that are not constrained to specific types of user scenarios. Furthermore, by not requiring the preliminary knowledge of the target scenario, the proposed policy is appropriate to online power management, which is essential for modern mobile devices. The proposed policy predicts the upcoming scenario characteristics (in this research, thread-level parallelism and the requested amount of work) during runtime. Then, it calculates ‘just enough’ processing speed to process the requested work at the given parallelism degree. In the experimental study, the proposed policy achieved a maximum of 25.5 % energy saving on the mobile system that uses the asymmetric multicore processor, and a maximum of 30.7 % energy saving on the mobile system that uses the symmetric multicore processor, without any QoS violation which degrades user experiences.