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Aggressive dynamic voltage scaling for energy-aware video playback based on decoding time estimation
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International Conference On Embedded Software archive
Proceedings of the seventh ACM international conference on Embedded software table of contents
Grenoble, France
SESSION: Energy aware design table of contents
Pages: 1-10  
Year of Publication: 2009
ISBN:978-1-60558-627-4
Authors
Ahron Yang  School of Computer and Information Engineering, Inha University, Incheon, South Korea
Minseok Song  School of Computer and Information Engineering, Inha University, Incheon, South Korea
Sponsors
ACM: Association for Computing Machinery
SIGBED: ACM Special Interest Group on Embedded Systems
SIGMICRO: ACM Special Interest Group on Microarchitectural Research and Processing
SIGDA: ACM Special Interest Group on Design Automation
Publisher
ACM  New York, NY, USA
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ABSTRACT

An effective way for reducing CPU power consumption is to reduce its operating frequency. But this slows down program execution, which may violate the real-time requirements of video playback. What is worse, it is difficult to predict future decoding times, and unduly conservative policies may miss viable opportunities to reduce the CPU frequency. The effectiveness of such power-saving techniques is thus dependent on an ability to estimate future demands on the CPU. We present the design, implementation and evaluation of a dynamic voltage scaling (DVS) scheme for portable media players. We measured decoding times on real videos and extracted a precise relationship between frame size and decoding time using logarithmic regression. Based on this model, we propose a frequency selection algorithm which accepts some deadline misses, and selects the frequencies required to achieve a specified deadline miss ratio. We implemented this scheme in MPlayer running on the Linux 2.6. Experimental results show that its system-wide energy consumption is up to 17% less than conventional DVS schemes and up to 24% less than non-DVS schemes.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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S. Chatterjee, A. Hadi, and B. Price. Regression Analysis by Example, The 3rd Edition. Wiley Series Probability and Statistics, New York, 2000.
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M. Fleischmann. Longrun power management - dynamic power management for crusoe processors. Technical report, Transmeta, 2001.
 
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M. Marinoni and G. Buttazzo. Elastic DVS management in processors with discrete voltage/frequency modes. IEEE Transactions on Industrial Informatics, 3(1):51--62, Feb. 2007.
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Collaborative Colleagues:
Ahron Yang: colleagues
Minseok Song: colleagues