A Survey of Dynamic Power Saving Strategies in Real Systems

Authors(1) :-Sai Kiran Talamudupula

Energy efficiency and energy-proportional computing have become major constraints in the design of modern exascale platforms. Dynamic Voltage and Frequency Scaling (DVFS) is one of the most commonly used and effective techniques to dynamically reduce power consumption based on workload characteristics. The focus of this paper is to survey several energy saving strategies designed for improving power efficiency of CPU and DRAM systems. This paper also presents a characterization of the strategies based on their salient features, to help the research community in gaining insights into the similarities and differences between the them. The aim of the paper is to equip researchers with knowledge of the state of the art energy saving strategies and serve as a quick reference to engineers while they are devising novel energy saving strategies.

Authors and Affiliations

Sai Kiran Talamudupula
Senior Bios Engineer, Intel, Chandler, Arizona, USA

DynamicVoltage and Frequency Scaling (DVFS), Power Efficiency, Energy Saving, Survey, Review.

  1. www.cpmd.org.
  2. A. Sodani. Knights Landing (KNL): 2nd generation Intel Xeon phi Processor. In HotChips 2015.
  3. D.H. Bailey et. Al. The NAS Parallel Benchmarks Summary and Preliminary Results. In Proceedings of the 1991 ACM/IEEE conference on Supercomputing, pages 158-165, 1991.
  4. S. Bhalachandra, A. Porterfield, S. L. Olivier, and J. F. Prins. An Adaptive Core-specific Runtime for Energy Efficiency. In 2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pages 947-956, May 2017.
  5. H. David, E. Gorbatov, U.R. Hanebutte, R. Khannal, and C. Le RAPL: Memory Power Estimation and Capping. In Proceedings of the 16th ACM/IEEE international symposium on Low power electronics and design, ISLPED’10, pages 189-194, New York, NY, USA, 2010. ACM.
  6. Ellie L. Fought, Vaibhav Sundriyal, Masha Sosonkina, and Theresa L. Windus. Saving time and energy with oversubscription and semi-direct Moller-Plesset second order perturbation methods. Journal of Computational Chemistry, 38(11):830-841, 2017.
  7. V.W. Freeh and D.K. Lowenthal. Using Multiple Energy Gears in MPI Programs on a Power-scalable Cluster. In Proceedings of the tenth ACM SIGPLAN symposium on Principles and practice of parallel programming, pages 164-173, 2005.
  8. R. Ge, X. Feng, W. Feng, and K.W. Cameron. CPU MISER: A Performance Directed, Run-time System for Power-aware Clusters. In Parallel Processing, 2007. ICPP 2007. International Conference on, page 18, Sep. 2007.
  9. R. Ge, X. Feng, Y. He, and P. Zou. The Case for Cross-component Power Coordination on Power Bounded Systems. In 2016 45th International Conference on Parallel Processing (ICPP), pages 516-525, Aug 2016.
  10. R. Ge, X. Feng, S. Song, H.C. Chang, D. Li, and K.W. Cameron. PowerPack: Energy Profiling and Analysis of High-performance systems and Applications. Parallel and Distributed Systems, IEEE Transactions on, 21:658-671, 2010.
  11. C.H. Hsu and W. Feng.   A Power-aware Run-time System for High-Performance Computing. In Supercomputing, 2005. Proceedings of the ACM/IEEE SC 2005 Conference, page 1, Nov. 2005.
  12. S. Huang and W. Feng. Energy-efficient Cluster Computing via Accurate Workload Characterization. In Cluster Computing and the Grid, 2009. CCGRID’09. 9th IEEE/ACM International Symposium on, pages 68- 75, May 2009.
  13. C. Iancu, S. Hofmeyr, F. Blagojevi, and Y. Zheng. Oversubscription on Multicore Processors. In 2010 IEEE International Symposium on Parallel Distributed Processing (IPDPS), pages 1-11, April 2010.
  14. N. Ioannou, M. Kauschke, M. Gries, and M. Cin- tra. Phase-based Application-driven Hierarchical Power Management on the Single-chip Cloud Computer. In Parallel Architectures and Compilation Techniques (PACT), 2011 International Conference on, pages 131-142, Oct. 2011.
  15. C. Isci and M. Martonosi. Runtime Power Monitoring in High-end Processors: Methodology and empirical data. In Proceedings of the 36th annual IEEE/ACM International Symposium on Microarchitecture, MICRO 36, pages 93-, Washington, DC, USA, 2003. IEEE Computer Society.
  16. K. Kandalla, E.P. Mancini, S. Sur, and D.K. Panda. Designing Power-aware Collective Communication Algorithms for InfiniBand Clusters. In Parallel Processing (ICPP), 2010 39th International Conference on, pages 218-227, 2010.
  17. Kristopher Keipert, Gaurav Mitra, Vaibhav Sunriyal, Sarom S. Leang, Masha Sosonkina, Alistair P. Rendell, and Mark S. Gordon. Energy-Efficient Computational Chemistry: Comparison of x86 and ARM Systems. Journal of Chemical Theory and Computation, 11(11):5055-5061, 2015. PMID: 26574303.
  18. Gary Lawson, Vaibhav Sundriyal, Masha Sosonkina, and Yuzhong Shen. Runtime Power Limiting of Parallel applications on Intel Xeon Phi Processors. In Proceedings of the 4th International Workshop on Energy Efficient Supercomputing, E2SC ’16, pages 39- 45, Piscataway, NJ, USA, 2016. IEEE Press.
  19. M.Y. Lim, V.W. Freeh, and D.K. Lowenthal. Adaptive, Transparent Frequency and Voltage scaling of Communication Phases in MPI Programs. In Proceedings of the 2006 ACM/IEEE conference on Supercomputing, 2006.
  20. K. Ma, X. Li, W. Chen, C. Zhang, and X. Wang. GreenGPU: A Holistic Approach to Energy Efficiency in GPU-CPU Heterogeneous Architectures. In 2012 41st International Conference on Parallel Processing, pages 48-57, Sept 2012.
  21. B. Rountree, D.K. Lowenthal, B.R. de Supinski, M. Schulz, V.W. Freeh, and T. Bletsch. Adagio: Making DVS Practical for Complex HPC Applications. In Proceedings of the 23rd international conference on Supercomputing, ICS’09, pages 460-469, New York, NY, USA, 2009. ACM.
  22. M. W. Schmidt, K.K. Baldridge, J.A. Boatz, S.T. Elbert, M.S. Gordon, J.H. Jensen, S. Koseki, N. Matsunaga, K.A. Nguyen, S. Su, T.L. Windus, M. Dupuis, and Jr. J.A. Montgomery. General atomic and Molecular Electronic Structure System. J. Comput. Chem., 14:1347-1363, Nov. 1993.
  23. Jayanth Srinivasan. An Overview of Static Power Dissipation. Technical report.
  24. V. Sundriyal and M. Sosonkina. Per-call Energy Saving Strategies in All-to-all Communications. In Proceedings of the 18th European MPI Users’ Group conference on Recent advances in the message passing interface, EuroMPI’11, pages 188-197, Berlin, Heidelberg, 2011. Springer-Verlag.
  25. V. Sundriyal and M. Sosonkina. Initial Investigation of a Scheme to use Instantaneous CPU Power Consumption for Energy Savings format. In Proceedings of the 1st International Workshop on Energy Efficient Supercomputing, E2SC ’13, pages 1:1-1:6, New York, NY, USA, 2013. ACM.
  26. V. Sundriyal and M. Sosonkina. Joint Frequency Scaling of Processor and DRAM. The Journal of Supercomputing, 72(4):1549-1569, 2016.
  27. V. Sundriyal, M. Sosonkina, and A. Gaenko. Runtime Procedure for Energy Savings in Applications with Point-to-point Communications. In Computer Architecture and High-Performance Computing (SBAC-PAD), 2012 IEEE 24th International Symposium on, pages 155-162, 2012.
  28. V. Sundriyal, M. Sosonkina, and Z. Zhang. Achieving Energy Efficiency During Collective Communications. Concurrency and Computation: Practice and Experience, 25(15):2140-2156, 2013.
  29. V. Sundriyal, M. Sosonkina, and Z. Zhang. Automatic Runtime Frequency Scaling System for Energy Savings in Parallel Applications. The Journal of Supercomputing, 68(2):777-797, 2014.
  30. Vaibhav Sundriyal, Ellie Fought, Masha Sosonkina, and Theresa L. Windus. Power Profiling and Evaluating the Effect of Frequency Scaling on NWChem. In Proceedings of the 24th High Performance Computing Symposium, HPC ’16, pages 19:1-19:8, San Diego, CA, USA, 2016. Society for Computer Simulation International.
  31. Vaibhav Sundriyal, Ellie Fought, Masha Sosonkina, and Theresa L. Windus. Evaluating effects of application based and automatic energy saving strategies on NWChem. In Proceedings of the 25th High Performance Computing Symposium, HPC ’17, pages 16:1-16:12, San Diego, CA, USA, 2017. Society for Computer Simulation International.
  32. Vaibhav Sundriyal and Masha Sosonkina. Runtime power-aware energy-saving scheme for parallel applications. 2015.
  33. Vaibhav Sundriyal, Masha Sosonkina, Alexander Gaenko, and Zhao Zhang. Energy saving strategies for parallel applications with point-to-point communication phases. Journal of Parallel and Distributed Computing, 73(8):1157 - 1169, 2013.
  34. M. Valiev, E.J. Bylaska, N. Govind, K. Kowalski, T.P. Straatsma, H.J.J. Van Dam, D. Wang, J. Nieplocha, E. Apra, T.L. Windus, and W.A. de Jong. NWChem: A comprehensive and scalable open-source solution for large scale molecular simulations. Computer Physics Communications, 181(9):1477 - 1489, 2010.
  35. A. Vishnu, S. Song, A. Marquez, K. Barker, D. Kerbyson, K. Cameron, and P. Balaji. Designing Energy Efficient Communication Runtime Systems for Data Centric Programming Models. In Proceedings of the 2010 IEEE/ACM Int’l Conference on Green Computing and Communications & Int’l Conference on Cyber, Physical and Social Computing, GREENCOM- CPSCOM ’10, pages 229-236, Washington, DC, USA, 2010. IEEE Computer Society.
  36. Xinxin Mei, Qiang Wang, and Xiaowen Chu. A Survey and Measurement Study of GPU DVFS on Energy Conservation. Digital Communications and Networks, 3(2):89 -100,2017.
  37. Khaled M. Attia, Mostafa A. El-Hosseini, and Hesham A. Ali. Dynamic power management techniques in multi-core architectures: A survey study. Ain Shams Engineering Journal, 8(3):445-456, 2017.
  38. S. Zhuravlev, J. C. Saez, S. Blagodurov, A. Fedorova, and M. Prieto. Survey of energy cognizant cheduling techniques. IEEE Transactions on Parallel and Distributed Systems, 24(7):1447-1464. July 2013.
  39. C. Lefurgy, K. Rajamani, F. Rawson, W. Felter, M. Kistler, and T.W. Keller. Energy management for commercial servers. Computer, 36(12):39- 48, December 2003.
  40. S. Borkar. The exascale challenge, 2011. Keynote speech, the 12th International Conference on Parallel Architectures and Compilation Techniques.
  41. R. Gonzalez, B. M. Gordon, and M. A. Horowitz. Supply and Threshold Voltage Scaling for Low Power CMOS. IEEE Journal of Solid-State Circuits, 32(8):1210-1216, Aug 1997.
  42. G. Semeraro, G. Magklis, R. Balasubramonian, D. H. Albonesi, S. Dwarkadas, and M. L. Scott. Energy-Efficient Processor Design Using Multiple Clock Domains with Dynamic Voltage and Frequency Scaling. In Proceedings Eighth International Symposium on High Performance Computer Architecture, pages 29-40, Feb 2002.
  43. Linux Kernel Governors. https://www.kernel.org/doc/Documentation/cpu-freq/governors.txt. Online].
  44. V Pallipadi and A Starikovskiy. The Ondemand Governor: Past, Present and Future. 2:223-238, 01 2006.
  45. R. Efraim, R. Ginosar, C. Weiser, and A. Mendelson. Energy Aware Race to Halt: A Down to Earth Approach for Platform Energy Management. IEEE Computer Architecture Letters, 13(1):25-28, Jan 2014.
  46. J. P. Halimi, B. Pradelle, A. Guermouche, N. Triquenaux, A. Laurent, J. C. Beyler, and W. Jalby. Reactive DVFS Control for Multicore Processors. In 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, pages 102-109, Aug 2013.
  47. Vaibhav Sundriyal, Masha Sosonkina, Fang Liu, and Michael W. Schmidt. Dynamic Frequency Scaling and Energy Saving in Quantum Chemistry Applications. In IEEE International Symposium on Parallel and Distributed Processing Workshops and PhD Forum, pages 837-845, 2011.

Publication Details

Published in : Volume 3 | Issue 8 | November-December 2017
Date of Publication : 2017-12-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 28-35
Manuscript Number : IJSRSET173829
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Sai Kiran Talamudupula, " A Survey of Dynamic Power Saving Strategies in Real Systems, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 3, Issue 8, pp.28-35, November-December-2017.
Journal URL : http://ijsrset.com/IJSRSET173829

Article Preview