Multimedia power management on a platter: from audio to video & games
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Rank based dynamic voltage and frequency scaling fortiled graphics processors
CODES/ISSS '10 Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
ARIVU: power-aware middleware for multiplayer mobile games
Proceedings of the 9th Annual Workshop on Network and Systems Support for Games
Adaptive display power management for mobile games
MobiSys '11 Proceedings of the 9th international conference on Mobile systems, applications, and services
Energy efficient multi-player smartphone gaming using 3D spatial subdivisioning and pvs techniques
Proceedings of the 3rd ACM international workshop on Interactive multimedia on mobile & portable devices
Program-based dynamic precision selection framework with a dual-mode unified shader for mobile GPUs
Computers and Electrical Engineering
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We propose a novel dynamic voltage scaling (DVS) scheme that is specifically directed towards 3D graphics- intensive interactive game applications running on battery- operated portable devices. The key to this DVS scheme lies in parsing each game frame to estimate its rendering workload and then using such an estimate to scale the volt- age/frequency of the underlying processor. The main nov- elty of this scheme stems from the fact that game frames offer a rich variety of "structural" information (e.g. num- ber of brush and alias models, texture information and light maps) which can be exploited to estimate their processing workload. Although DVS has been extensively applied to video decoding applications, compressed video frames do not offer any information (beyond the frame types I, B or P) that can be used in a similar manner to estimate their processing workload. As a result, DVS algorithms designed for video decoding mostly rely on control-theoretic feedback mechanisms, where the workload of a frame is predicted from the workloads of the previously-rendered frames. We show that compared to such history-based predictors, our proposed scheme performs significantly better for game ap- plications. Our experimental results, based on the Quake II game engine running on Windows XP, show that for the same energy consumption our scheme results in more than 50% improvement in quality (measured in terms of num- ber of frames meeting their deadlines) compared to history- based prediction schemes.