Improving energy efficiency for mobile platforms by exploiting low-power sleep states

CF '12 - Proceedings of the ACM Computing Frontiers Conference

Volumn , Issue , 2012, Pages 133-142

  Min, Alexander W ^a   Wang, Ren ^a   Tsai, James ^a   Ergin, Mesut A ^a   Tai, Tsung Yuan Charlie ^a  

^a INTEL CORPORATION   (United States)

Author keywords

energy efficiency; idle duration prediction; low power sleep states; mobile platform; reward based sleep state selection

Indexed keywords

BATTERY LIFE; DURATION PREDICTIONS; ENERGY EFFICIENT; EVALUATION RESULTS; INTELLIGENT POWER; LEVERAGING SYSTEMS; LOW-POWER SLEEP STATE; MOBILE PLATFORM; NONDETERMINISTIC SYSTEMS; OPTIMAL THRESHOLD; POWER SAVINGS; REDUCING ENERGY CONSUMPTION; REWARD-BASED SLEEP-STATE SELECTION; SELECTION ERROR; SLEEP STATE;

DECISION SUPPORT SYSTEMS; ENERGY EFFICIENCY; ENERGY UTILIZATION; FORECASTING; MOBILE PHONES; OPTIMIZATION; SMARTPHONES; VIDEO STREAMING;

SLEEP RESEARCH;

EID: 84862669038     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2212908.2212928     Document Type: Conference Paper

References (46)

1. Intel Ultrabook, http://www.intel.com/content/www/us/en/sponsors-of- tomorrow/ultrabook.html.
2. Apple FaceTime, http://www.apple.com/mac/facetime/.
3. Intel Wireless Display (WiDi), http://www.intel.com/content/www/us/en/ architecture-and-technology/intel-wireless-display.html.
4. The idle governor in Linux kernel, http://www.kernel.org.
5. 2011 U.S. Wireless Handset Customer Satisfaction Studies, http://www.jdpower.com/news/pressRelease.aspx?ID=2011146/.
6. Windows 7 Power Management, http://www.supertalent.com/datasheets/ Windows7.pdf.
7. pyTimechart, http://packages.python.org/pytimechart/.
8. Iperf, http://iperf.sourceforge.net.
9. Interrupt Moderation Using Intel GbE Controllers, http://www.intel.com/ content/dam/doc/application-note/gbe-controllers-interrupt-moderation-appl-note. pdf/.
10. H. Amur, R. Nathuji, M. Ghosh, K. Schwan, and H.-H. S. Lee. Idle power: Application-aware management of processor idle states. In ACM MMCS, June 2008.
11. B. Anand, K. Thirugnanam, J. Sebastian, P. G. Kannan, A. L. Ananda, M. C. Chan, and R. K. Balan. Adaptive display power management for mobile games. In ACM MobiSys, June/July 2011.
12. M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. Katz, A. Konwinski, G. Lee, D. Patterson, A. Rabkin, I. Stoica, and M. Zaharia. Above the clouds: A berkeley view of cloud computing. In Technical Report. UCB/EECS-2009-28. EECS Department, University of California, Berkeley, February 2009.
13. S.-Y. Bang, K. Bang, S. Yoon, and E.-Y. Chung. Run-time adaptive workload estimation for dynamic voltage scaling. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 28(9):1334-1347, September 2009.
14. L. A. Barroso and U. Hölzl. The case for energy-proportional computing. IEEE Computer, 40(12):33-37, December 2007.
15. L. Benini, A. Bogliolo, G. A. Paleologo, and G. D. Micheli. Policy optimization for dynamic power management. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 18(6):813-833, June 1999.
16. L. Benini and G. D. Michel. System-level power optimization: Techniques and tools. ACM Transactions on Design Automation of Electronic Systems, 5(2):115-192, April 2000.
17. T. D. Burd, T. A. Pering, A. J. Stratakos, and R. W. Brodersen. A dynamic voltage scaled microprocessor system. IEEE Journal of Solid-State Circuits, 35(11):1571-1580, November 2000.
18. E.-Y. Chung, L. Benini, and G. D. Micheli. Dynamic power management using adaptive learning tree. In ACM ICCAD, November 1999.
19. V. Devadas and H. Aydin. On the interplay of voltage/frequency scaling and device power management for frame-based real-time embedded applications. IEEE Transactions on Computers, 61(1):31-44, January 2011.
20. G. Dhiman, K. K. Pusukuri, and T. Rosing. Analysis of dynamic voltage scaling for system level energy management. In ACM HotPower, December 2008.
21. G. Dhiman and T. S. Rosing. Dynamic power management using machine learning. In ACM ICCAD, November 2006.
22. Q. Diao and J. Song. Prediction of CPU idle-busy activity pattern. In IEEE HPCA, February 2008.
23. K. Flautner, N. S. Kim, S. Martin, D. Blaauw, and T. Mudge. Drowsey caches: Simple techniques for reducing leakage power. In IEEE Computer Architecture, August 2002.
24. J. Flinn and M. Satyanarayanan. Energy-aware adaptation for mobile applications. In ACM SOSP, December 1999.
25. C. Gniady, Y. C. Hu, , and Y.-H. Lu. Program counter based techniques for dynamic power management. In IEE Software, February 2004.
26. R. Golding, P. Bosch, and J. Wilke. Idlness is not sloth. In ACM USENIX, September 1995.
27. M. Hayenga, C. Sudanthi, M. Ghosh, P. Ramrakhyani, and N. Paver. Accurate system-level performance modeling and workload characterization for mobile internet devices. In ACM MEDEA, October 2008.
28. H. Huang, K. G. Shin, C. Lefurgy, and T. Keller. Improving energy efficiency by making DRAM less randomly accessed. In ACM ISLPED, August 2005.
29. S. Irani, S. Shukla, and R. Gupta. Competitive analysis of dynamic power management strategies for systems with multiple power saving states. In ACM DATE, March 2002.
30. A. Kulkarni, R. Wang, C. Maciocco, S. Bakshi, and J. Tsai. IDC: An energy efficient communication scheme for connected mobile platforms. In IEEE ICC, June 2009.
31. K. Li, R. Kumpf, P. Horton, and T. Anderson. A quantitative analysis of disk drive power management in portable computers. In ACM USENIX, December 1994.
32. J. Liu and P. H. Chou. Optimizing mode transition sequences in idle intervals for component-level and system-level energy minimization. In IEEE/ACM ICCAD, January 2005.
33. Y.-H. Lu, E.-Y. Chung, T. Šimunić, L. Benini, and G. D. Micheli. Server workload analysis for power minimization using consolidation. In ACM USENIX, September 2009.
34. Y.-H. Lu and G. De Micheli. Comparing system level power management policies. IEEE Design Test of Computers, 18(2):10-19, March/April 2001.
35. D. Meisner, B. T. Gold, and T. F. Wenisch. Powernap: Eliminating server idle power. In ACM ASPLOS, March 2009.
36. A. Miyoshi, C. Lefurgy, E. V. Hensbergen, R. Rajamony, and R. Rajkumar. Critical power slope: Understanding the rumtime effects of frequency scaling. In ACM ICS, June 2002.
37. NVIDIA, September 2001. The Benefits of Quad Core CPUs in Mobile Devices, http://www.nvidia.com/content/PDF/tegra-white-papers/tegra-whitepaper-0911a. pdf.
38. V. Pallipadi, S. Li, and A. Belay. cpuidle - do nothing, efficiently... In The Linux Symposium, June 2006.
39. K. Patel, E. Macii, and M. Poncino. Frame buffer energy optimization by pixel prediction. In ACM ICCD, October 2005.
40. K. Pentikousis. In search of energy-efficient mobile networking. IEEE Communications Magazine, 48(1):95-103, January 2010.
41. P. Pillai and K. G. Shin. Real-time dynamic voltage scaling for low-power embedded operating systems. In ACM SOSP, October 2001.
42. P. Ranganathan. Recipe for efficiency: Principles of power-aware computing. ACM Communications, 53(4):60-67, April 2010.
43. K. D. Ryu and J. K. Hollingsworth. Exploiting fine-grained idle periods in networks of workstations. IEEE Transactions on Parallel and Distributed Systems, 11(7):683-698, July 2000.
44. T. Simunic, L. Benini, A. Acquaviva, P. Glynn, and G. D. Michieli. Dynamic voltage scaling and power management for portable systems. In ACM DAC, June 2001.
45. A. Verma, G. Dasgupta, T. K. Nayak, P. De, and R. Kothari. Server workload analysis for power minimization using consolidation. In ACM USENIX, September 2009.
46. R. Wang, J. Tsai, C. Maciocco, T.-Y. C. Tai, and J. Wu. Reducing power consumption for mobile platforms via adaptive traffic coalescing. IEEE Journal on Selected Areas in Communications, 29(8):1618-1629, September 2011.