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Optimality and improvement of dynamic voltage scaling algorithms for multimedia applications
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Source Annual ACM IEEE Design Automation Conference archive
Proceedings of the 45th annual Design Automation Conference table of contents
Anaheim, California
SESSION: Application mapping and power efficiency table of contents
Pages 179-184  
Year of Publication: 2008
ISBN ~ ISSN:0738-100X , 978-1-60558-115-6
Authors
Zhen Cao  UCLA Los Angeles, CA
Brian Foo  UCLA Los Angeles, CA
Lei He  UCLA Los Angeles, CA
Mihaela van der Schaar  UCLA Los Angeles, CA
Sponsors
SIGDA: ACM Special Interest Group on Design Automation
: IEEE/CASS/CANDE/CEDA
: The EDA Consortium
Publisher
ACM  New York, NY, USA
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ABSTRACT

The time-varying workload for multimedia applications poses a great challenge for the efficient performance of dynamic voltage scaling (DVS) algorithms. While many DVS algorithms have been proposed for real-time applications, there does not yet exist a systematic method for evaluating the optimality of such DVS algorithms. In this paper, we propose an offline linear programming (LP) method to determine the minimum energy consumption for processing multimedia tasks under stringent delay deadlines. Based on this lower bound, we evaluate the efficiency of various existing DVS algorithms. Furthermore, we modify the LP formulation to construct an online robust sequential linear programming DVS algorithm for real-time multimedia processing. Simulation results from decoding over a wide range of video sequences shows that on average, our online algorithm consumes less than 1% more energy than the optimal lower bound while dropping only 0.1% of all scheduled decoding jobs, while the existing best algorithm consumes roughly 3% more energy at the same miss rate.


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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Z. Cao, B. Foo, L. He, and M. van der Schaar. Optimality and Improvement of Dynamic Voltage Scaling Algorithms for Multimedia Applications. Technical Report UCLA, 08--267, 2008.

Collaborative Colleagues:
Zhen Cao: colleagues
Brian Foo: colleagues
Lei He: colleagues
Mihaela van der Schaar: colleagues