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The State of Energy and Performance Benchmarking for Enterprise Servers

  • Andrew Fanara
  • Evan Haines
  • Arthur Howard
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5895)

Abstract

To address the server industry’s marketing focus on performance, benchmarking organizations have played a pivotal role in developing techniques to determine the maximum achievable performance level of a system. Generally missing has been an assessment of energy use to achieve that performance. The connection between performance and energy consumption is becoming necessary information for designers and operators as they grapple with power constraints in the data center. While industry and policy makers continue to strategize about a universal metric to holistically measure IT equipment efficiency, existing server benchmarks for various workloads could provide an interim proxy to assess the relative energy efficiency of general servers. This paper discusses ideal characteristics a future energy-performance benchmark might contain, suggests ways in which current benchmarks might be adapted to provide a transitional step to this end, and notes the need for multiple workloads to provide a holistic proxy for a universal metric.

Keywords

Energy Efficiency High Performance Computing Energy Measurement Enterprise Server Performance Benchmark 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    ENERGY STAR Program. ENERGY STAR Program Requirements for Computer Servers (2009)Google Scholar
  2. 2.
    Forrest, W., Kaplan, J., Kindler, N.: Data Centers: How to cut carbon emissions and costs. McKinsey on Business Technology 14, 6 (2008)Google Scholar
  3. 3.
    Garber, K.: The Internet’s Hidden Energy Hogs: Data Servers. US News and World Report (2009)Google Scholar
  4. 4.
    The Green500 List, http://www.green500.org
  5. 5.
    Hass, J., Monroe, M., Pflueger, J., Pouchet, J., Snelling, P., Rawson, A., Rawson, F.: Proxy Proposals for Measuring Data Center Productivity. The Green Grid: Beaverton, OR (2009)Google Scholar
  6. 6.
    Koomey, J., Belady, C., Wong, C., Snevely, R., Nordman, B., Hunter, E., Lange, K., Tipley, R., Darnell, G., Accapadi, M., Rumsey, P., Kelley, B., Tschudi, W., Moss, D., Greco, R., Brill, K.: Server Energy Measurement Protocol. Analytics Press, Oakland (2006)Google Scholar
  7. 7.
    Koomey, J., Brill, K., Turner, W.P., Stanley, J.R.: A Simple Model for Determining True Total Cost of Ownership for Data Centers. The Uptime Institute, Santa Fe (2007)Google Scholar
  8. 8.
    Neal Nelson & Associates, http://www.nna.com
  9. 9.
    Standard Performance Evaluation Corporation, http://www.spec.org
  10. 10.
    Stanley, J.R., Brill, K., Koomey, J.: Four Metrics Define Data Center “Greenness” Enabling Users to Quantify “Energy Efficiency for Profit” Initiatives. The Uptime Institute, Santa Fe (2007)Google Scholar
  11. 11.
    Transaction Processing Performance Council, http://www.tpc.org/information/about/abouttpc.asp
  12. 12.
    United States Environmental Protection Agency: Report to Congress on Server and Data Center Energy Efficiency, Public Law 109-431 (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Andrew Fanara
    • 1
  • Evan Haines
    • 2
  • Arthur Howard
    • 2
  1. 1.US EPANW Washington
  2. 2.ICF InternationalFairfax

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