TY - GEN
T1 - A user-centric CPU-GPU governing framework for 3D games on mobile devices
AU - Chen, Wei-Ming
AU - Cheng, Sheng-Wei
AU - Hsiu, Pi-Cheng
AU - Kuo, Tei-Wei
PY - 2015/11
Y1 - 2015/11
N2 - Graphics-intensive mobile games are becoming increasingly popular, but such applications place high demand on device CPUs and GPUS. The design of current mobile systems results in unnecessary energy waste due to lack of consideration of application phases and user attention (a demand-level gap) and because each processor administers power management autonomously (a processor-level gap). This paper proposes a user-centric CPU-GPU governing framework which aims to reduce energy consumption without significantly impacting the user experience. To bridge the gap at the demand level, we identify the user demand at runtime and accordingly determine appropriate governing policies for the respective processors. On the other hand, to bridge the gap at the processor level, the proposed framework interprets the frequency scaling intents of processors based on the observation of the CPU-GPU interaction and the processor status. We implemented our framework on a Samsung Galaxy S4, and conducted extensive experiments with real-world 3D gaming apps. Experimental results showed that, for an application being highly interactive and frequent phase changing, our proposed framework can reduce energy consumption by 45.1% compared with state-of-the-art policy without significantly impacting the user experience.
AB - Graphics-intensive mobile games are becoming increasingly popular, but such applications place high demand on device CPUs and GPUS. The design of current mobile systems results in unnecessary energy waste due to lack of consideration of application phases and user attention (a demand-level gap) and because each processor administers power management autonomously (a processor-level gap). This paper proposes a user-centric CPU-GPU governing framework which aims to reduce energy consumption without significantly impacting the user experience. To bridge the gap at the demand level, we identify the user demand at runtime and accordingly determine appropriate governing policies for the respective processors. On the other hand, to bridge the gap at the processor level, the proposed framework interprets the frequency scaling intents of processors based on the observation of the CPU-GPU interaction and the processor status. We implemented our framework on a Samsung Galaxy S4, and conducted extensive experiments with real-world 3D gaming apps. Experimental results showed that, for an application being highly interactive and frequent phase changing, our proposed framework can reduce energy consumption by 45.1% compared with state-of-the-art policy without significantly impacting the user experience.
UR - https://www.scopus.com/pages/publications/84964478843
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84964478843&origin=recordpage
U2 - 10.1109/ICCAD.2015.7372574
DO - 10.1109/ICCAD.2015.7372574
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 978-1-4673-8388-2
T3 - IEEE/ACM International Conference on Computer-Aided Design, ICCAD
SP - 224
EP - 231
BT - 2015 IEEE/ACM International Conference on Computer-Aided Design (ICCAD) - Digest of Technical Papers
PB - IEEE
T2 - 34th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2015
Y2 - 2 November 2015 through 6 November 2015
ER -