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Energy-efficient video decoding schemes for embedded handheld devices

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Abstract

Dynamic voltage and frequency scaling (DVFS) is an effective technique for reducing power consumption. Because of the increasing popularity of multimedia applications for portable consumer electronic devices, the importance of reducing their power consumption has become crucial. This paper proposes a table-based DVFS mechanism for frame decoding that can effectively reduce the power consumption of a processor by exploiting the frame-decoding complexity features. This proposed table-based DVFS predictor requires no prior knowledge on video decoders, and can be flexibly applied on different video codecs. This study implemented the table-based DVFS predictor on the PXA270 embedded platform and all benchmarks were encoded into various video coding formats, including H.264, VP8 and WMV formats. In addition, the proposed DVFS predictor was also ported on a modern platform NVIDIA JETSON TK1, and has demonstrated that the proposed algorithm can provide significant energy saving performance on high definition (HD) videos. The experimental results demonstrate that the energy consumption of decoding videos can be reduced from 6 to 21 %, whereas the frame drop rate is less than 3 %.

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References

  1. ARM.com Cortex-A15 Performance Monitor Unit. http://infocenter.arm.com/help/index. Accessed October 2014

  2. Asaduzzaman A, Gunasekara GH (2013) Power and performance analysis of multimedia applications running on low-power devices by cache modeling. Multimedia Tools Appl 1–24, on-line published. doi: 10.1007/s11042-012-1350-3

  3. Bankoski J, Wilkins P, Xu Y (2011) Technical overview of VP8, an open source video codec for the web. In: Proc. IEEE International Conference on Multimedia and Expo 1–6

  4. Barnes RD, Nystrom EM, Merten MC, Hwu WW (2002) Vacuum packing: extracting hardware-detected program phases for post-link optimization. In: Proc. International Symposium on Microarchitecture, pp. 233–244

  5. Chen Y-L, Chang M-F, Liang W-Y (2014) FT-DVFS open source. Release on GitHub. https://github.com/winner121/FT-DVFS. Accessed November 2014

  6. Choi J, Cha H (2006) Memory-aware dynamic voltage scaling for multimedia applications. IEE Proc Comput Digit Tech 153(2):130–136

    Article  Google Scholar 

  7. Choi J, Cha H (2010) System-level power management for system-on-a-chip -based mobile devices. IET Comput Digit Tech 4(5):400–409

    Article  Google Scholar 

  8. Choi K, Dantu K, Cheng W-C, Pedram M (2002) Frame-based dynamic voltage and frequency scaling for a MPEG decoder. In: Proc. IEEE/ACM International Conference on Computer-aided Design, NY, USA, pp. 732–737

  9. Choi K, Soma R, Pedram M (2005) Fine-grained dynamic voltage and frequency scaling for precise energy and performance tradeoff based on the ratio of off-chip access to on-chip computation times. IEEE Trans Computer Aided Des Integr Circ Syst 24(1):18–28

    Article  Google Scholar 

  10. Contreras G, Martonosi M (2005) Power prediction for Intel XScale® processors using performance monitoring unit events. In: Proc. International Symposium on Low Power Electronics and Design 221–226

  11. Dhodapkar A, Smith JE (2002) Managing multi-configuration hardware via dynamic working set analysis. In: Proc. International Symposium on Computer Architecture

  12. Gao H, Qiao F, Yang H (2012) Design and implementation of motion compensator in memory reduced HDTV decoder with embedded compression engine. Multimedia Tools Appl 56:597–614

    Article  Google Scholar 

  13. Isci C, Contreras G, Martonosi M (2006) Live, runtime phase monitoring and prediction on real systems with application to dynamic power management. In: Proc. IEEE/ACM International Symposium on Microarchitecture 359–370

  14. Jeong S, Ahn H (2011) Optimal power reduction based on DVFS algorithm for video decoders. In: Proc ACM Symposium on Research in Applied Computation, NY, USA, pp. 107–109

  15. Jha NK (2005) Low-power system scheduling, synthesis and displays. IET Comput Digit Tech 152(3):344–352

    Article  Google Scholar 

  16. Lee B, Nurvitadhi E, Dixit R, Yu C, Kim M (2005) Dynamic voltage scaling techniques for power efficient video decoding. J Syst Archit 51(10–11):633–652

    Article  Google Scholar 

  17. Liang W-Y, Chang M-F, Chen Y-L, Lai C-F (2013) Energy efficient video decoding for the Android operating system. In: Proc. IEEE International Conference on Consumer Electronics 344–345

  18. Liang W-Y, Chen S-C, Chang Y-L, Fang J-P (2008) Memory-aware dynamic voltage and frequency prediction for portable devices. In: Proc. IEEE Int. Conf. Embedded and Real-Time Computing Systems and Applications 229–236

  19. Ma Z, Hu H, Wang Y (2011) On complexity modeling of H.264/AVC video decoding and its application for energy efficient decoding. IEEE Trans Multimedia 13(6):1240–1255

    Article  MathSciNet  Google Scholar 

  20. Mesarina M, Turner Y (2002) Reduced energy decoding of MPEG streams. ACM/SPIE Multimedia Computing and Networking, pp. 202–213

  21. Mochocki B, Rajan D, Sharon Hu X, Poellabauer C, Otten K, Chantem T (2007) Network-aware dynamic voltage and frequency scaling. In: Proc. IEEE Real-Time and Embedded Technology and Applications Symposium

  22. NVIDIA (2014) Jetson TK1 Development Kit. http://www.nvidia.com/object/jetson-tk1-embedded-dev-kit.html. Accessed October 2014

  23. Palladi V, Starikovskiy A (2006) The ondemand governor: past, present and future. Proc Linux Symp 2:223–238

    Google Scholar 

  24. Park SO, Lee JK, Park JH, Kim SJ (2012) Adaptive power management system for mobile multimedia device. IET Commun 6(11):1407–1415

    Article  MathSciNet  Google Scholar 

  25. Poellabauer C, Singleton L, Schwan K (2005) Feedback-based dynamic voltage and frequency scaling for memory-bound real-time applications. In: Proc. IEEE Real Time on Embedded Technology and Applications Symposium 234–243

  26. Pouwelse J, Langendoen K, Sips H (2001) Dynamic voltage scaling on a low-power microprocessor. In: Proc. International Conference on Mobile Computing and Networking, NY, USA, 251–259

  27. Sakurai T, Newton AR (1990) Alpha-power law MOSFET model and its applications to CMOS inverter delay and other formulas. IEEE J Solid State Circuits 25:584–594

    Article  Google Scholar 

  28. Sherwood T, Sair S, Calder B (2003) Phase tracking and prediction. In: Proc. International Symposium on Computer Architecture 336–347

  29. Snowdon DC, Linden GVD, Petters S, Heiser G (2007) Accurate run-time prediction of performance degradation under frequency scaling. In: Proc. Workshop on Operating System Platforms for Embedded Real-Time Applications 58–64

  30. Snowdon DC, Petters SM, Heiser G (2007) Accurate on-line prediction of processor and memory energy usage under voltage scaling. In: Proc. ACM & IEEE Int. Conf. Embedded Software 84–93

  31. Weissel A, Bellosa F (2006) Self-learning hard disk power management for mobile devices. In: Proc. International Workshop on Software Support for Portable Storage 33–40

  32. Xia F, Tian Y-C, Sun Y, Dong J (2008) Control-theoretic dynamic voltage scaling for embedded controllers. IET Comput Digit Tech 377–385

  33. Xiph.org Video Test Media. http://media.xiph.org/video/derf/. Accessed March 2014

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Acknowledgments

This study was supported by the Ministry of Science and Technolgy of the Republic of China (Contract No. MOST-103-2221-E-027-061). The authors express their gratitude to Prof. Chin-Feng Lai at National Chung Cheng University for his valuable suggestions on this study.

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  1. Department of Computer Science and Information Engineering, National Taipei University of Technology, Taipei, 106, Taiwan

    Yen-Lin Chen, Ming-Feng Chang & Wen-Yew Liang

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  1. Yen-Lin Chen
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  2. Ming-Feng Chang
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Correspondence to Yen-Lin Chen.

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Chen, YL., Chang, MF. & Liang, WY. Energy-efficient video decoding schemes for embedded handheld devices. Multimed Tools Appl 75, 3281–3300 (2016). https://doi.org/10.1007/s11042-014-2435-y

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