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Measuring Server Energy Proportionality

Published:31 January 2015Publication History

ABSTRACT

In performance engineering, metrics are often used to track the progress over time. Concerning the potential bias of using a single metric, performance engineers tend to use multiple metrics for reasoning. However, this approach has its own challenges. In this work we study one of the challenges in the context of analyzing trends in server energy proportionality. We examine a wide range of metrics for measuring energy proportionality, trying to determine which metrics are essential and which are redundant. We do this by comparing the trend curves of the metrics for the published results of the SPECpower_ssj2008 benchmark. While the context is specific, the proposed analysis method is quite general. We hope that this method would help us do performance engineering more effectively.

References

  1. L. Barroso and U. Hölzle. The case for energy-proportional computing. IEEE Computer, 40(12):33--37, Dec. 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. C. Belady. In the data center, power and cooling costs more than the IT equipment it supports. Electronics Cooling Magazine, Feb. 2007.Google ScholarGoogle Scholar
  3. L. Gray, A. Kumar, and H. Li. Workload characterization of the SPECpower ssj2008 benchmark. In SPEC International Performance Evaluation Workshop, June 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. The Green500 list: Environmentally responsible supercomputing. http://www.green500.org.Google ScholarGoogle Scholar
  5. C. Hsu, J. Kuehn, and S. Poole. Towards efficient supercomputing: Searching for the right efficiency metric. In International Conference on Performance Engineering, Apr. 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. C. Hsu and S. Poole. Revisiting server energy proportionality. In International Workshop on Power-Aware Systems and Architectures, Oct. 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. F. Ryckbosch, S. Polfliet, and L. Eeckhout. Trends in server energy proportionality. IEEE Computer, 44(9):69--72, Sept. 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. T. Scogland, C. Stefen, T. Wilde, F. Parent, S. Coghlan, N. Bates, W. Feng, and E. Strohmaier. A power-measurement methodology for large-scale, high-performance computing. In International Conference on Performance Engineering, Mar. 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. M. Stojmenović, A. Nayak, and J. Zunic. Measuring linearity of planar point sets. Pattern Recognition, 41(8):2503--2511, Aug. 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. B. Subramaniam and W. Feng. GBench: Benchmarking methodology for evaluating the energy efficiency of supercomputers. In International Supercomputing Conference, June 2012.Google ScholarGoogle Scholar
  11. B. Subramaniam and W. Feng. Towards energy-proportional computing for enterprise-class server workloads. In International Conference on Performance Engineering, Apr. 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. B. Subramaniam and W. Feng. Enabling efficient power provisioning for enterprise applications. In International Symposium on Cluster, Cloud and Grid Computing, May 2014.Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. G. Varsamopoulos, Z. Abbasi, and S. Gupta. Trends and effects of energy proportionality on server provisioning in data centers. In International Conference on High Performance Computing, Dec. 2010.Google ScholarGoogle ScholarCross RefCross Ref
  14. D. Wong and M. Annavaram. Scaling the energy proportionality wall with KnightShift. IEEE Micro, 33(3):28--37, May/June 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. D. Wong and M. Annavaram. Implications of high energy proportional servers on cluster-wide energy proportionality. In International Symposium on High-Performance Computer Architecture, Feb. 2014.Google ScholarGoogle ScholarCross RefCross Ref

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              cover image ACM Conferences
              ICPE '15: Proceedings of the 6th ACM/SPEC International Conference on Performance Engineering
              January 2015
              366 pages
              ISBN:9781450332484
              DOI:10.1145/2668930

              Copyright © 2015 ACM

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              Association for Computing Machinery

              New York, NY, United States

              Publication History

              • Published: 31 January 2015

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              ICPE '15 Paper Acceptance Rate23of74submissions,31%Overall Acceptance Rate252of851submissions,30%

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