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MEMCOP: memory-aware co-operative power management governor for mobile games

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Abstract

Modern mobile heterogeneous platforms have GPUs integrated with multicore processors to enable execution of high-end graphics-intensive games. However, these gaming applications consume significant power due to heavy utilization of CPU–GPU resources, which drains battery resources that are critical for mobile devices. While dynamic voltage and frequency scaling (DVFS) techniques have been exploited previously for dynamic power management, contemporary techniques do not fully exploit the memory access footprint for graphics-intensive gaming applications, missing opportunities for energy efficiency. In this paper, we present MEMCOP, a memory-aware cooperative CPU–GPU DVFS governor that considers both the memory access footprint as well as the CPU/GPU frequency to improve energy efficiency of high-end mobile game workloads. Our experimental results on real games and synthetic game workloads show that our MEMCOP game governor achieves on average 18 and 9% improvement of energy efficiency with minor degradation of performance compared to default governors and state-of-the-art game governors.

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References

  1. Bai Y, Vaidya P (2009) Memory characterization to analyze and predict multimedia performance and power in embedded systems. In: 2009 IEEE international conference on acoustics, speech and signal processing, Taipei, pp 1321–1324. https://doi.org/10.1109/ICASSP.2009.4959835

  2. Cho SJ, Yun SH, Jeon JW (2015) A powersaving DVFS algorithm based on operational intensity for embedded systems. IEICE Electron Express. https://doi.org/10.1587/elex.12.20141128

    Google Scholar 

  3. Dietrich B, Chakraborty S (2014) Forget the battery, let’s play games! In: Embedded systems for real-time multimedia (ESTIMedia), 2014 IEEE 12th symposium on, pp 1–8. https://doi.org/10.1109/ESTIMedia.2014.6962338

  4. Dietrich B, Chakraborty S (2014) Lightweight graphics instrumentation for game state-specific power management in android. Multimed Syst 20(5):563–578. https://doi.org/10.1007/s00530-014-0377-x

    Article  Google Scholar 

  5. Dietrich B, Goswami D, Chakraborty S, Guha A, Gries M (2015) Time series characterization of gaming workload for runtime power management. IEEE Trans Comput 64(1):260–273. https://doi.org/10.1109/TC.2013.198

    Article  MathSciNet  MATH  Google Scholar 

  6. Ercan F, Gazala NA, David H (2012) An integrated approach to system-level CPU and memory energy efficiency on computing systems. In: Energy aware computing, 2012 international conference on, pp 1–6. https://doi.org/10.1109/ICEAC.2012.6471018

  7. Google (2012) Butter project. https://developers.google.com/events/io/2012/sessions

  8. Gu Y, Chakraborty S, Ooi WT (2006) Games are up for DVFS. In: DAC ’06 proceedings of the 43rd annual design automation conference, pp 598–603

  9. Hardkernel (2014) Odroid-xu3. http://www.hardkernel.com/main/products/prdt_info.php

  10. Hsieh CY, Park JG, Dutt N, Lim SS (2015) Memory-aware cooperative CPU–GPU DVFS governor for mobile games. In: Embedded systems for real-time multimedia (ESTIMedia), 2015 13th IEEE symposium on, pp 1–8. https://doi.org/10.1109/ESTIMedia.2015.7351775

  11. Jeong MK, Erez M, Sudanthi C, Paver N (2012) A QoS-aware memory controller for dynamically balancing GPU and CPU bandwidth use in an MPSOC. In: Proceedings of the 49th annual design automation conference. ACM, New York DAC ’12, pp 850–855. https://doi.org/10.1145/2228360.2228513

  12. Kadjo D, Ogras U, Ayoub R, Kishinevsky M, Gratz P (2014) Towards platform level power management in mobile systems. In: System-on-chip conference (SOCC), 2014 27th IEEE international, pp 146–151. https://doi.org/10.1109/SOCC.2014.6948916

  13. Kim D, Jung N, Cha H (2014) Content-centric display energy management for mobile devices. In: Proceedings of the 51st annual design automation conference. ACM, New York, DAC ’14, pp 41:1–41:6. https://doi.org/10.1145/2593069.2593113

  14. Liang WY, Chen YL, Chang MF (2011) A memory-aware energy saving algorithm with performance consideration for battery-enabled embedded systems. In: Consumer electronics (ISCE), 2011 IEEE 15th international symposium on, pp 547–551. https://doi.org/10.1109/ISCE.2011.5973890

  15. McVoy L, Staelin C (1996) Lmbench: portable tools for performance analysis. In: Proceedings of the 1996 annual conference on USENIX annual technical conference, USENIX Association, Berkeley, ATEC ’96, pp 23–23. http://dl.acm.org/citation.cfm?id=1268299.1268322

  16. Park JG, Hsieh CY, Dutt N, Lim SS (2014) Quality-aware mobile graphics workload characterization for energy-efficient DVFS design. In: Embedded systems for real-time multimedia (ESTIMedia), 2014 IEEE 12th symposium on, pp 70–79. https://doi.org/10.1109/ESTIMedia.2014.6962347

  17. Pathania A, Jiao Q, Prakash A, Mitra T (2014) Integrated CPU–GPU power management for 3D mobile games. In: DAC ’14 Proceedings of the 51st annual design automation conference on design automation conference, pp 1–6

  18. Pathania A, Irimiea AE, Prakash A, Mitra T (2015) Power-performance modelling of mobile gaming workloads on heterogeneous MPSOCS. In: Proceedings of the 52nd annual design automation conference. ACM, New York, DAC ’15, pp 201:1–201:6. https://doi.org/10.1145/2744769.2744894

  19. Shuvalov R (2013) GPU performance analyzer. https://play.google.com/store/apps/details?id=com.romanshuvalov.gpupa

  20. You D, Chung K (2014) Quality of service-aware dynamic voltage and frequency scaling for embedded GPUS. Comput Archit Lett. https://doi.org/10.1109/LCA.2014.2319079

    Google Scholar 

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Correspondence to Chen-Ying Hsieh.

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This paper is an expanded version of our ESTIMedia2015 work [10]. The manuscript contains the following additional materials: (1) we describe details of our implementation (Sect. 4.1). (2) We add comparisons with a recent integrated governor (Sect. 4.3). (3) We present evaluations of our model (Sect. 4.4). (4) We discuss additional opportunities for further improvement of energy efficiency (Sect. 5).

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Hsieh, CY., Park, JG., Dutt, N. et al. MEMCOP: memory-aware co-operative power management governor for mobile games. Des Autom Embed Syst 22, 95–116 (2018). https://doi.org/10.1007/s10617-018-9201-8

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