Quality-aware Video Decoding on Thermally-constrained MPSoC Platforms

被引:0
|
作者
Gangadharan, Deepak [1 ]
Teich, Juergen [1 ]
Chakraborty, Samarjit [2 ]
机构
[1] Univ Erlangen Nurnberg, Dept Comp Sci, Erlangen, Germany
[2] Tech Univ Munich, Inst Real Time Comp Syst, Munich, Germany
关键词
ENERGY OPTIMIZATION;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Current mobile devices extensively run video players that are power hungry. Further, higher power densities as a result of technology scaling results in higher on-chip temperatures. Unlike general purpose computer systems, mobile devices that run on batteries cannot afford to have expensive cooling mechanisms. Therefore, in order to satisfy thermal constraints while running power hungry applications, dynamic thermal management (DTM) techniques have been employed. For multimedia applications, the techniques primarily relied on dynamic voltage and frequency scaling (DVFS) and dynamic power management (DPM) while taking care that maximum video quality is achieved. However, no prior work has exploited frame drops to lower the inserted idle times under predetermined quality constraints. In this work, we propose a DPM framework that utilizes frame drops to dynamically insert low idle times in order to satisfy a peak temperature constraint under a given quality constraint. This also reduces the end-to-end latency. The latencies are further reduced by maintaining lightweight workload histories. For the videos used in our experiments, it was observed that a small reduction in quality of 2 dB (reduction from 32 dB to 30 dB) due to frame drops in motion videos results in a maximum latency reduction of 1.7 sec.
引用
收藏
页码:256 / 263
页数:8
相关论文
共 49 条
  • [1] Quality-Aware Media Scheduling on MPSoC Platforms
    Gangadharan, Deepak
    Chakraborty, Samarjit
    Zimmermann, Roger
    DESIGN, AUTOMATION & TEST IN EUROPE, 2013, : 976 - 981
  • [2] Quality-aware video
    Hiremath, Basavaraj
    Li, Qiang
    Wang, Zhou
    2007 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-7, 2007, : 1597 - 1600
  • [3] Quality-Aware Decoding for Neural Machine Translation
    Fernandes, Patrick
    Farinhas, Antonio
    Rei, Ricardo
    de Souza, Jose G. C.
    Ogayo, Perez
    Neubig, Graham
    Martins, Andre F. T.
    NAACL 2022: THE 2022 CONFERENCE OF THE NORTH AMERICAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS: HUMAN LANGUAGE TECHNOLOGIES, 2022, : 1396 - 1412
  • [4] Perceptual Tools for Quality-Aware Video Networks
    Bovik, A. C.
    IMAGE QUALITY AND SYSTEM PERFORMANCE XI, 2014, 9016
  • [5] STRATEGIES FOR QUALITY-AWARE VIDEO CONTENT ANALYTICS
    Reibman, Amy R.
    2018 IEEE SOUTHWEST SYMPOSIUM ON IMAGE ANALYSIS AND INTERPRETATION (SSIAI), 2018, : 77 - 80
  • [6] Quality-aware pattern diffusion for video object segmentation
    Zhou, Chuanwei
    Xu, Chunyan
    Li, Jun
    Cui, Zhen
    Yang, Jian
    NEUROCOMPUTING, 2023, 528 : 148 - 159
  • [7] Quality-Aware Merge Candidate Construction For Video Coding
    Zhao, Lei
    Zhang, Kai
    Zhang, Li
    2022 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS 22), 2022, : 2388 - 2392
  • [8] Quality-Aware Estimation of Facial Landmarks in Video Sequences
    Haque, Mohammad A.
    Nasrollahi, Kamal
    Moeslund, Thomas B.
    2015 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV), 2015, : 678 - 685
  • [9] Learning Quality-aware Dynamic Memory for Video Object Segmentation
    Liu, Yong
    Yu, Ran
    Yin, Fei
    Zhao, Xinyuan
    Zhao, Wei
    Xia, Weihao
    Yang, Yujiu
    COMPUTER VISION, ECCV 2022, PT XXIX, 2022, 13689 : 468 - 486
  • [10] Quality-Aware DASH Video Caching Schemes At Mobile Edge
    Ye, Zakaria
    De Pellegrini, Francesco
    El-Azouzi, Rachid
    Maggi, Lorenzo
    Jimenez, Tania
    2017 PROCEEDINGS OF THE 29TH INTERNATIONAL TELETRAFFIC CONGRESS (ITC 29), VOL 1, 2017, : 205 - 213