Article

Workload prediction and dynamic voltage scaling for MPEG decoding

Authors:

Ying Tan,

Parth Malani,

Qinru Qiu,

Qing WuAuthors Info & Claims

ASP-DAC '06: Proceedings of the 2006 Asia and South Pacific Design Automation Conference

Pages 911 - 916

https://doi.org/10.1145/1118299.1118505

Published: 24 January 2006 Publication History

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Abstract

In this paper we present three efficient DVS techniques for an MPEG decoder. Their energy reduction is comparable to that of the optimal solution. A workload prediction model is also developed based on the block level statistics of each MPEG frame. Compared with previous works, the new model exhibits a remarkable improvement in accuracy of the prediction. The experimental results show that, with the new prediction model, the presented DVS techniques achieve more energy reduction than previous works while delivering the same Quality of Service (QoS).

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Cited By

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Li LGuo SMeng LZhai HHui ZMa BShen S(2020)An Improved Q-Learning for System Power Optimization with Temperature, Performance and Energy Constraint Modeling2020 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)10.1109/TOCS50858.2020.9339699(348-354)Online publication date: 11-Dec-2020
https://doi.org/10.1109/TOCS50858.2020.9339699
Iranfar ASouza WZapater MOlcoz KSouza SAtienza D(2019)A Machine Learning-Based Framework for Throughput Estimation of Time-Varying Applications in Multi-Core Servers2019 IFIP/IEEE 27th International Conference on Very Large Scale Integration (VLSI-SoC)10.1109/VLSI-SoC.2019.8920309(211-216)Online publication date: Oct-2019
https://doi.org/10.1109/VLSI-SoC.2019.8920309
Benmoussa YSenn EDerouineau NTizon NBoukhobza J(2018)Joint DVFS and Parallelism for Energy Efficient and Low Latency Software Video DecodingIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2017.277981229:4(858-872)Online publication date: 1-Apr-2018
https://doi.org/10.1109/TPDS.2017.2779812
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Index Terms

Workload prediction and dynamic voltage scaling for MPEG decoding
1. Hardware
  1. Hardware validation
  2. Very large scale integration design
    1. Application-specific VLSI designs
      1. Application specific processors
2. Information systems
  1. Data management systems
    1. Data structures
      1. Data layout
        Data compression

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Published In

ASP-DAC '06: Proceedings of the 2006 Asia and South Pacific Design Automation Conference

January 2006

998 pages

ISBN:0780394518

General Chair:
Fumiyasu Hirose
Cadence Design Systems, Japan

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IEEE Press

Publication History

Published: 24 January 2006

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Overall Acceptance Rate 466 of 1,454 submissions, 32%

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Li LGuo SMeng LZhai HHui ZMa BShen S(2020)An Improved Q-Learning for System Power Optimization with Temperature, Performance and Energy Constraint Modeling2020 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)10.1109/TOCS50858.2020.9339699(348-354)Online publication date: 11-Dec-2020
https://doi.org/10.1109/TOCS50858.2020.9339699
Iranfar ASouza WZapater MOlcoz KSouza SAtienza D(2019)A Machine Learning-Based Framework for Throughput Estimation of Time-Varying Applications in Multi-Core Servers2019 IFIP/IEEE 27th International Conference on Very Large Scale Integration (VLSI-SoC)10.1109/VLSI-SoC.2019.8920309(211-216)Online publication date: Oct-2019
https://doi.org/10.1109/VLSI-SoC.2019.8920309
Benmoussa YSenn EDerouineau NTizon NBoukhobza J(2018)Joint DVFS and Parallelism for Energy Efficient and Low Latency Software Video DecodingIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2017.277981229:4(858-872)Online publication date: 1-Apr-2018
https://doi.org/10.1109/TPDS.2017.2779812
Wang XLi LWang WDu P(2018)Online learning based on a novel cost function for system power managementIET Computers & Digital Techniques10.1049/iet-cdt.2017.021112:5(227-232)Online publication date: 1-Sep-2018
https://doi.org/10.1049/iet-cdt.2017.0211
Lee BKim Y(2017)ESC-DVS: Dynamic Voltage Scaling Using Entropy-Based Scene Change Detection for AMOLED DisplaysIEEE Journal of the Electron Devices Society10.1109/JEDS.2017.26714265:3(193-208)Online publication date: May-2017
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Nogues EHeulot JHerrou GRobin LPelcat MMenard DRaffin EHamidouche W(2017)Efficient DVFS for low power HEVC software decoderJournal of Real-Time Image Processing10.1007/s11554-016-0624-913:1(39-54)Online publication date: 1-Mar-2017
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Lee BKim Y(2016)Dynamic Voltage Scaling Using Scene Change Detection for Video Playback on Mobile AMOLED DisplaysProceedings of the 2016 International Symposium on Low Power Electronics and Design10.1145/2934583.2934640(302-307)Online publication date: 8-Aug-2016
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Benmoussa YSenn EDerouineau NTizon NBoukhobza J(2016)Green metadata based adaptive DVFS for energy efficient video decoding2016 26th International Workshop on Power and Timing Modeling, Optimization and Simulation (PATMOS)10.1109/PATMOS.2016.7833693(235-242)Online publication date: Sep-2016
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Mendis HAudsley NIndrusiak L(2015)Task allocation for decoding multiple hard real-time video streams on homogeneous NoCs2015 IEEE 13th International Conference on Industrial Informatics (INDIN)10.1109/INDIN.2015.7281742(246-251)Online publication date: Jul-2015
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Mendis HIndrusiak LAudsley NJan MBen Hedia BGoossens JMaiza C(2014)Predictability and Utilisation Trade-off in the Dynamic Management of Multiple Video Stream Decoding on Network-on-Chip based Homogeneous Embedded Multi-coresProceedings of the 22nd International Conference on Real-Time Networks and Systems10.1145/2659787.2659826(161-170)Online publication date: 8-Oct-2014
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A workload prediction model for decoding mpeg video and its application to workload-scalable transcoding

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