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Towards efficient supercomputing: searching for the right efficiency metric

Published:22 April 2012Publication History

ABSTRACT

Efficiency in supercomputing has traditionally focused on execution time. In early 2000's, the concept of total cost of ownership was re-introduced, with the introduction of efficiency measure to include aspects such as energy and space. Yet the supercomputing community has never agreed upon a metric that can cover these aspects completely and also provide a fair basis for comparison. This paper examines the metrics that have been proposed in the past decade, and proposes a vector-valued metric for efficient supercomputing. Using this metric, the paper presents a study of where the supercomputing industry has been and where it stands today with respect to efficient supercomputing.

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. Bekas and A. Curioni. A new energy aware performance metric. In International Conference on Energy-Aware High Performance Computing, Sept. 2010.Google ScholarGoogle ScholarCross RefCross Ref
  3. K. D. Bois, T. Schaeps, S. Polfliet, F. Ryckbosch, and L. Eeckhout. SWEEP: Evaluating computer system energy efficiency using synthetic workloads. In International Conference on High Performance Embedded Architectures and Compilers, Jan. 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. D. Brooks, P. Bose, S. Schuster, H. Jacobson, P. Kudva, A. Buyuktosunoglu, J.-D. Wellman, V. Zyuban, M. Gupta, and P. Cook. Power-aware microarchitecture: Design and modeling challenges for the next generation microprocessors. IEEE Micro, 20(6):26--44, November/December 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. T. Conte and W. Hwu. Advances in benchmarking techniques: New standards and quantitative metrics. Advances in Computers, 41:231--253, 1995.Google ScholarGoogle ScholarCross RefCross Ref
  6. J. Dongarra, P. Luszczek, and A. Petitet. The LINPACK benchmark: Past, present, and future. Concurrency and Computation: Practice and Experience, 15(9):803--820, Aug. 2003.Google ScholarGoogle ScholarCross RefCross Ref
  7. Energy Efficient High Performance Computing Working Group. http://eehpcwg.lbl.gov.Google ScholarGoogle Scholar
  8. A. Fanara, E. Haines, and A. Howard. The state of energy and performance benchmarking for enterprise servers. In TPC Technology Conference on Performance Evaluation and Benchmarking, Aug. 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. R. Ge, X. Feng, and K. Cameron. Improvement of power-performance efficiency for high-end computing. In Workshop on High-Performance, Power-Aware Computing, Apr. 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. R. Gonzalez and M. Horowitz. Energy dissipation in general purpose microprocessors. IEEE Journal of Solid-State Circuits, 31(9):1277--1284, Sept. 1996.Google ScholarGoogle ScholarCross RefCross Ref
  11. The Graph 500 list. http://www.graph500.org.Google ScholarGoogle Scholar
  12. 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
  13. The Green500 list: Environmentally responsible supercomputing. http://www.green500.org.Google ScholarGoogle Scholar
  14. D. Hackenberg, R. Schöne, D. Molka, M. Müller, and A. Knüpfer. Quantifying power consumption variations of HPC systems using SPEC MPI benchmarks. In International Conference on Energy-Aware High Performance Computing, Sept. 2010.Google ScholarGoogle ScholarCross RefCross Ref
  15. HPC Challenge benchmark. http://icl.cs.utk.edu/hpcc/.Google ScholarGoogle Scholar
  16. C. Hsu, W. Feng, and J. Archuleta. Towards efficient supercomputing: A quest for the right metric. In Workshop on High-Performance, Power-Aware Computing, Apr. 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. J. Koomey, S. Berard, M. Sanchez, and H. Wong. Implications of historical trends in the electrical efficiency of computing. IEEE Annals of the History of Computing, 33(3):46--54, July-September 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. K.-D. Lange and M. Tricker. The design and development of the server efficiency rating tool (SERT). In International Conference on Performance Engineering, Mar. 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. T. Makimoto, K. Eguchi, and M. Yoneyama. The cooler the better: New directions in the nomadic age. IEEE Computer, 34(4):38--42, Apr. 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. A. Martin. Towards an energy complexity of computation. Information Processing Letters, 77:181--187, Feb. 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. D. Meisner and T. Wenisch. Does low-power design imply energy efficiency for data centers. In International Symposium on Low Power Electronics and Design, Aug. 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. S. Microsystems. The SWaP (Space, Watts and Performance) metric, 2007.Google ScholarGoogle Scholar
  23. D. Molka, D. Hackenberg, R. Schöne, T. Minartz, and W. Nagel. Flexible workload generation for HPC cluster efficiency benchmarking. In International Conference on Energy-Aware High Performance Computing, Sept. 2011.Google ScholarGoogle Scholar
  24. T. Mudge and U. Hölzle. Challenges and opportunities for extremely energy-efficient processors. IEEE Micro, 30(4):20--24, July/August 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. M. Müller, M. van Waveren, R. Lieberman, B. Whitney, H. Saito, K. Kumaran, J. Baron, W. Brantley, C. Parrott, T. Elken, H. Feng, and C. Ponder. SPEC MPI2007:an application benchmark suite for parallel systems using MPI. Concurrency and Computation: Practice and Experience, 22(2):191--205, Feb. 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. V. Pel. Energy efficiency aspects in Cray supercomputers. In International Conference on Energy-Aware High Performance Computing, Sept. 2010.Google ScholarGoogle Scholar
  27. P. Pénzes and A. Martin. Energy-delay efficiency of VLSI computations. In ACM Great Lakes Symposium on VLSI, Apr. 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. M. Poess, R. Nambiar, and K. Vaid. Optimizing benchmark configurations for energy efficiency. In International Conference on Performance Engineering, Mar. 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. M. Poess, R. Nambiar, K. Vaid, J. J. M. Stephens, K. Huppler, and E. Haines. Energy benchmarks: A detailed analysis. In International Conference on Energy-Efficient Computing and Networking, Apr. 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. S. Rivoire, M. Shah, P. Ranganathan, and C. Kozyrakis. JouleSort: A balanced energy-efficiency benchmark. In International Conference on Management of Data, June 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. F. Ryckbosch, S. Polfliet, and L. Eeckhout. Trend in server energy-proportionality. IEEE Computer, 44(9):69--72, Sept. 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. V. Sarkar. ExaScale software study: Software challenges in extreme scale systems. DARPA IPTO Report, Sept. 2009.Google ScholarGoogle Scholar
  33. D. Schall, V. Hoefner, and M. Kern. Towards an enhanced benchmark advocating energy-efficient systems. In TPC Technology Conference on Performance Evaluation & Benchmarking, Aug. 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. T. Scogland, B. Subramaniam, and W. Feng. Emerging trends on the evolving Green500: Year three. In Workshop on High-Performance, Power-Aware Computing, May 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. SPECpower_ssj2008 Results. http://www.spec.org/power_ssj2008/results/.Google ScholarGoogle Scholar
  36. E. Strohmaier. Generalized utility metrics for supercomputers. June 2009.Google ScholarGoogle Scholar
  37. The Green Grid. The Green Grid power efficiency metrics: PUE and DCiE, 2007.Google ScholarGoogle Scholar
  38. The Green Grid. Recommendations for measuring and reporting overall data center efficiency (version 2), May 2011.Google ScholarGoogle Scholar
  39. TOP500 supercomputing sites. http://www.top500.org.Google ScholarGoogle Scholar
  40. G. Varsamopoulos and S. Gupta. Energy proportionality and the future: Metrics and directions. In International Workshop on Green Computing, Sept. 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library

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              cover image ACM Conferences
              ICPE '12: Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering
              April 2012
              362 pages
              ISBN:9781450312028
              DOI:10.1145/2188286

              Copyright © 2012 ACM

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              Publication History

              • Published: 22 April 2012

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