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Implementing the Data Center Energy Productivity Metric in a High-Performance Computing Data Center

  • Landon H. Sego
  • Andrés Márquez
  • Andrew Rawson
  • Tahir Cader
  • Kevin Fox
  • William I. GustafsonJr.
  • Christopher J. Mundy
Chapter

Abstract

As data centers proliferate in size and number, improving energy efficiency and productivity has become an economic and environmental imperative. Making these improvements requires metrics that are robust, interpretable, and practical. We examine the properties of a number of proposed metrics of energy efficiency and productivity. In particular, we focus on the Data Center Energy Productivity (DCeP) metric, which is the ratio of useful work produced by the data center to the energy consumed performing that work. We investigated DCeP as the principal outcome of a designed experiment using a highly instrumented, high-performance computing (HPC) data center. We found that DCeP was successful in clearly distinguishing different operational states in the data center, thereby validating its utility as a metric for identifying configurations of hardware and software that would improve energy productivity. We also discuss some of the challenges and benefits associated with implementing the DCeP metric, and we examine the efficacy of the metric in making comparisons within a data center and among data centers.

Keywords

Energy Efficiency Data Center Load Balance Cool Tower Pacific Northwest National Laboratory 
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.

Notes

Acknowledgements

This work was supported in part by the U.S. Department of Energy under DE-Award Numbers 47128, 55430, and SC0005365.

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Landon H. Sego
    • 1
  • Andrés Márquez
    • 1
  • Andrew Rawson
    • 2
  • Tahir Cader
    • 3
  • Kevin Fox
    • 1
  • William I. GustafsonJr.
    • 1
  • Christopher J. Mundy
    • 1
  1. 1.Pacific Northwest National Laboratory (PNNL)RichlandUSA
  2. 2.Advanced Micro Devices, Inc.SunnyvaleUSA
  3. 3.Hewlett-Packard CompanyPalo AltoUSA

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