簡易檢索 / 詳目顯示

研究生: 莊博凱
Po-Kai Chuang
論文名稱: 動態行動裝置遊戲節能調整
An adaptive on-line CPU-GPU power management framework of games on mobile devices
指導教授: 陳雅淑
Ya-Shu Chen
口試委員: 謝仁偉
Jen-Wei Hsieh
吳晉賢
Chin-Hsien Wu
修丕承
Pi-Cheng Hsiu
學位類別: 碩士
Master
系所名稱: 電資學院 - 電機工程系
Department of Electrical Engineering
論文出版年: 2016
畢業學年度: 104
語文別: 英文
論文頁數: 25
中文關鍵詞: 行動裝置節能GPU使用者經驗
外文關鍵詞: Mobile Device, Energy Saving, User Experience, GPU
相關次數: 點閱:353下載:1
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 現代人使用智慧型手機時,有30%以上的時間是花費在玩手機遊戲。據統計,手機遊戲消耗了大部分的手機電量。為解決此議題,現有的電源管理多是針對中央處理器(CPU)進行頻率調整來省電。然而,現在的智慧型手機多利用GPU來輔助CPU進行遊戲的複雜運算。本篇論文提出一個能夠在盡可能不傷害使用者的遊戲體驗下動態調整CPU與GPU頻率用以省電的演算法。本方法於遊戲過程中分析遊戲所需要的服務品質與計算資源用量,進行即時頻率調整。為了能貼近使用者進行遊戲的環境,本篇論文將演算法實做於Google Nexus 7 平板電腦上,並測試不同種類遊戲的省電效果,而根據實驗結果,我們所提出的方法可以節省20%的系統耗電量。


    Energy efficiency is a critical issue for battery-driven mobile
    devices. With the increasing needs of graphic mobile games
    on such devices, an on-line power governor for both CPUs
    and GPUs is highly motivated. This study proposes an
    adaptive on-line CPU-GPU governor of games on mobile
    devices to reduce the energy. In contrast to existing governors,
    an adaptive frequency scaling framework is presented
    to switch the performance-driven or energy-driven to minimize
    the energy without user attention. Also, to adjust the
    dynamic of quality during game stages, an on-line learning
    is applied to our framework to predict the required quality
    and to sense the relations between quality and CPU/GPU
    frequencies. The idea is implemented on Google Nexus 7
    and evaluated with real-world gaming apps. The results
    show that we can save up to 20% system energy (included
    the network, screen, and systemidle power) for a high frame
    rate game and maintaining a stable user experience.

    1 Introduction 2 Related Work 3 System Model 4 Algorithms 5 Experiment 6 Conclusion

    [1] Linux cpufreq cpufreq governors. In https://android.googlesource.com/kernel/common/+
    /a7827a2a60218b25f222b54f77ed38f57aebe08b/Documentation/cpu-freq/governors.txt,
    2012.
    [2] Game apps are no. 1 for amazon, apple and google. In
    http://www.emarketer.com/Article/Game-Apps-No-1-Amazon-Apple-Google/1010739,
    2014.
    [3] F. Alam, P. R. Panda, N. Tripathi, N. Sharma, and S. Narayan. Energy optimization in
    android applications through wakelock placement. In Design, Automation and Test in
    Europe Conference and Exhibition (DATE), pages 1–4. IEEE, 2014.
    [4] M. Bansal, D. Pushpan, H. Medha, S. Jain, and S. Jain. Cpu frequency scaling by utilization.
    Technocal Report, IIITB-TR-2012-003, 2012.
    [5] S. Bischoff, A. Hansson, and B. M. Al-Hashimi. Applying of quality of experience to
    system optimisation. In Power and Timing Modeling, Optimization and Simulation (PATMOS),
    23rd International Workshop on, pages 91–98. IEEE, 2013.
    [6] D. Cederman and P. Tsigas. Dynamic load balancing using work-stealing. GPU Computing
    Gems Jade Edition, pages 485–499, 2011.
    [7] H.-C. Chang, A. R. Agrawal, and K. W. Cameron. Energy-aware computing for android
    platforms. In Energy Aware Computing (ICEAC), International Conference on, pages
    1–4. IEEE, 2011.
    [8] Q. Chen, L. Zheng, M. Guo, and Z. Huang. Eewa: Energy-efficient workload-aware task
    scheduling in multi-core architectures. In Parallel & Distributed Processing Symposium
    Workshops (IPDPSW), IEEE International, pages 642–651. IEEE, 2014.
    [9] W.-M. Chen, S.-W. Cheng, P.-C. Hsiu, and T.-W. Kuo. A user-centric cpu-gpu governing
    framework for 3d games on mobile devices. In Proceedings of the IEEE/ACM International
    Conference on Computer-Aided Design, pages 224–231. IEEE Press, 2015.
    [10] X. Chen, Y. Chen, Z. Ma, and F. C. Fernandes. How is energy consumed in smartphone
    display applications? In Proceedings of the 14thWorkshop onMobile Computing Systems
    and Applications. ACM, 2013.
    [11] L. Cheng, S.Mohapatra,M. El Zarki, N. Dutt, and N. Venkatasubramanian. Quality-based
    backlight optimization for video playback on handheld devices. Advances in Multimedia,
    (1):4–4, 2007.
    [12] S.-L. Chu, S.-R. Chen, and S.-F. Weng. Design a low-power scheduling mechanism
    for a multicore android system. In Parallel Architectures, Algorithms and Programming
    (PAAP), Fifth International Symposium on, pages 25–30. IEEE, 2012.
    [13] S. K. Datta, C. Bonnet, and N. Nikaein. Android power management: Current and future
    trends. In Enabling Technologies for Smartphone and Internet of Things (ETSIoT), First
    IEEE Workshop on, pages 48–53. IEEE, 2012.
    [14] K. De Moor, I. Ketyko, W. Joseph, T. Deryckere, L. De Marez, L. Martens, and G. Verleye.
    Proposed framework for evaluating quality of experience in a mobile, testbedoriented
    living lab setting. Mobile Networks and Applications, 15(3):378–391, 2010.
    [15] B. Dietrich and S. Chakraborty. Managing power for closed-source android os games
    by lightweight graphics instrumentation. In Network and Systems Support for Games
    (NetGames), 11th Annual Workshop on, pages 1–3. IEEE, 2012.
    [16] B. Dietrich and S. Chakraborty. Forget the battery, let’s play games! In Embedded
    Systems for Real-time Multimedia (ESTIMedia), IEEE 12th Symposium on, pages 1–8.
    IEEE, 2014.
    [17] B. Dietrich, S. Nunna, D. Goswami, S. Chakraborty, and M. Gries. Lms-based lowcomplexity
    game workload prediction for dvfs. In Computer Design (ICCD), IEEE International
    Conference on, pages 417–424. IEEE, 2010.
    [18] A. Elewi, M. Shalan, M. Awadalla, and E. M. Saad. Energy-efficient task allocation
    techniques for asymmetric multiprocessor embedded systems. ACM Transactions on Embedded
    Computing Systems (TECS), 13(2s):71, 2014.
    [19] J. Froehlich, M. Y. Chen, S. Consolvo, B. Harrison, and J. A. Landay. Myexperience: a
    system for in situ tracing and capturing of user feedback on mobile phones. In Proceedings
    of the 5th international conference on Mobile systems, applications and services,
    pages 57–70. ACM, 2007.
    [20] Y. Gu and S. Chakraborty. Control theory-based dvs for interactive 3d games. In Design
    Automation Conference, 45th ACM/IEEE, pages 740–745. IEEE, 2008.
    [21] H. Han, J. Yu, H. Zhu, Y. Chen, J. Yang, G. Xue, Y. Zhu, and M. Li. E 3: energyefficient
    engine for frame rate adaptation on smartphones. In Proceedings of the 11th
    ACM Conference on Embedded Networked Sensor Systems. ACM, 2013.
    [22] A. Iranli, W. Lee, and M. Pedram. Hvs-aware dynamic backlight scaling in tft-lcds. Very
    Large Scale Integration (VLSI) Systems, IEEE Transactions on, 14(10):1103–1116, 2006.
    [23] D. Kim, N. Jung, and H. Cha. Content-centric display energy management for mobile
    devices. In Proceedings of the 51st Annual Design Automation Conference, pages 1–6.
    ACM, 2014.
    [24] J.-B. Lee,M. Kim, and E.-Y. Chung. Schedule-aware dvfs algorithm on android platforms
    for energy minimization. The 29th International Technical Conference on Circuit/Systems
    Computers and Communications (ITC-CSCC), 2014.
    [25] Y.-T. Lee, K.-T. Chen, H.-I. Su, and C.-L. Lei. Are all games equally cloud-gamingfriendly?
    an electromyographic approach. In Network and Systems Support for Games
    (NetGames), 11th Annual Workshop on, pages 1–6. IEEE, 2012.
    [26] D. Li and W. G. Halfond. An investigation into energy-saving programming practices for
    android smartphone app development. In Proceedings of the 3rd International Workshop
    on Green and Sustainable Software, pages 46–53. ACM, 2014.
    [27] C.-H. Lin, P.-C. Hsiu, and C.-K. Hsieh. Dynamic backlight scaling optimization: A
    cloud-based energy-saving service for mobile streaming applications. Computers, IEEE
    Transactions on, 63(2):335–348, 2014.
    [28] X. Liu, F. Ding, J. Li, H. Liu, Z. Yang, J. Chen, and F. Xia. Phonejoule: An energy
    management system for android-based smartphones. In Green Computing and Communications
    (GreenCom), IEEE and Internet of Things (iThings/CPSCom), IEEE International
    Conference on and IEEE Cyber, Physical and Social Computing, pages 1996–2001. IEEE,
    2013.
    [29] T.-Y. Ma, C.-Y. Lin, S.-W. Hsu, C.-W. Hu, and T.-W. Hou. Automatic brightness control
    of the handheld device display with low illumination. In Computer Science and Automation
    Engineering (CSAE), IEEE International Conference on, volume 2, pages 382–385.
    IEEE, 2012.
    [30] J. D. McCarthy, M. A. Sasse, and D. Miras. Sharp or smooth?: comparing the effects of
    quantization vs. frame rate for streamed video. In Proceedings of the SIGCHI conference
    on Human factors in computing systems, pages 535–542. ACM, 2004.
    [31] A. McLaughlin, I. Paul, J. L. Greathouse, S. Manne, and S. Yalamanchili. A power
    characterization and management of gpu graph traversal. In Workshop on Architectures
    and Systems for Big Data (ASBD), 2014.
    [32] T. Mittal, L. Singhal, and D. Sethia. Optimized cpu frequency scaling on android devices
    based on foreground running application. Computer Networks & Communications
    (NetCom), page 827, 2013.
    [33] M. Motlhabi. Advanced android power management and implementation of wakelocks.
    University of the Western Cape. Paper available online: http://www. cs. uwc. ac. za/˜
    mmotlhabi/apm2. pdf (nd), 2008.
    [34] R.Muralidhar, H. Seshadri, V. Bhimarao, V. Rudramuni, I.Mansoor, S. Thomas, B. Veera,
    Y. Singh, and S. Ramachandra. Experiences with power management enabling on the intel
    medfield phone. In Linux Symposium, 2012.
    [35] K. Nagata, S. Yamaguchi, and H. Ogawa. A power saving method with consideration of
    performance in android terminals. In Ubiquitous Intelligence & Computing and 9th International
    Conference on Autonomic & Trusted Computing (UIC/ATC), 9th International
    Conference on, pages 578–585. IEEE, 2012.
    [36] V. Pallipadi and A. Starikovskiy. The ondemand governor. In Proceedings of the Linux
    Symposium, volume 2, pages 215–230. sn, 2006.
    [37] A. Pathania, A. E. Irimiea, A. Prakash, and T. Mitra. Power-performance modelling of
    mobile gaming workloads on heterogeneous mpsocs. Design Automation Conference
    (DAC), 2015.
    [38] A. Pathania, Q. Jiao, A. Prakash, and T. Mitra. Integrated cpu-gpu power management
    for 3d mobile games. In Design Automation Conference (DAC), 51st ACM/EDAC/IEEE,
    pages 1–6. IEEE, 2014.
    [39] T. D. Sanger. Optimal unsupervised learning in a single-layer linear feedforward neural
    network. Neural networks, 2(6):459–473, 1989.
    [40] E. Setton, J. Noh, and B. Girod. Rate-distortion optimized video peer-to-peer multicast
    streaming. In Proceedings of the ACM workshop on Advances in peer-to-peer multimedia
    streaming, pages 39–48. ACM, 2005.
    [41] A. Shye, Y. Pan, J. Scholbrock, S. Miller, G. Memik, P. Dinda, R. P. Dick, et al. Power to
    the people: Leveraging human physiological traits to control microprocessor frequency.
    In Microarchitecture, MICRO-41. 41st IEEE/ACM International Symposium on, pages
    188–199. IEEE, 2008.
    [42] P.-H. Tseng, P.-C. Hsiu, C.-C. Pan, and T.-W. Kuo. User-centric energy-efficient scheduling
    on multi-core mobile devices. In Proceedings of the 51st Annual Design Automation
    Conference, pages 1–6. ACM, 2014.
    [43] P. K. Yadav and N. Ramasubramanian. Power consumption of android device using different
    video codecs: An analysis. In Advance Computing Conference (IACC), IEEE International,
    pages 1019–1023. IEEE, 2014.
    [44] L. Yang, R. Dick, G. Memik, and P. Dinda. Happe: Human and application-driven frequency
    scaling for processor power efficiency. Mobile Computing, IEEE Transactions on,
    12(8):1546–1557, 2013.
    [45] D. You and K.-S. Chung. Dynamic voltage and frequency scaling framework for lowpower
    embedded gpus. Electronics letters, 48(21):1333–1334, 2012.
    [46] M. Zakarya, N. Dilawar, M. A. Khattak, and M. Hayat. Energy efficient workload balancing
    algorithm for real-time tasks over multi-core. World Applied Sciences Journal,
    22(10):1431–1439, 2013.
    [47] L. Zhou and L. Yu. Frequency-utilization based power-aware schedule policy for realtime
    multi-core system. In Green Computing and Communications (GreenCom), IEEE
    and Internet of Things (iThings/CPSCom), IEEE International Conference on and IEEE
    Cyber, Physical and Social Computing, pages 200–207. IEEE, 2013.
    [48] Z. Zhuang, K.-H. Kim, and J. P. Singh. Improving energy efficiency of location sensing
    on smartphones. In Proceedings of the 8th international conference on Mobile systems,
    applications, and services, pages 315–330. ACM, 2010.

    無法下載圖示 全文公開日期 2021/02/02 (校內網路)
    全文公開日期 本全文未授權公開 (校外網路)
    全文公開日期 本全文未授權公開 (國家圖書館:臺灣博碩士論文系統)
    QR CODE