Comparing datasets of volume servers to illuminate their energy use in data centers

  • Heidi FuchsEmail author
  • Arman Shehabi
  • Mohan Ganeshalingam
  • Louis-Benoit Desroches
  • Brian Lim
  • Kurt Roth
  • Allen Tsao
Original Article


As data centers proliferate, their energy intensity deserves close attention. Always-on operations and growing usage for cloud and other backend processes make servers the fundamental driver of data center energy use. Yet servers’ power draw under real-world conditions is poorly understood. This paper explores characteristics of volume servers that affect energy use, quantifying differences in power draw between higher-performing Standard Performance Evaluation Corporation (SPEC) and ENERGY STAR servers and that of a typical server. First, we establish general characteristics of the US installed base, before reporting hardware configurations from a major online retail website. We then compare idle power across three datasets (one unique to this paper) and explain their differences via the hardware characteristics to which power draw is most sensitive. We find idle server power demand to be significantly higher than benchmarks from ENERGY STAR and the industry-released SPEC database, and SPEC server configurations—and likely their power scaling—to be atypical of volume servers. Next, we examine power draw trends among high-performing servers across their load range to consider whether these trends are representative of volume servers, before inputting average idle power load values into a recent national server energy use model. Lastly, results from two surveys of IT professionals illustrate the incidence of more efficient equipment and operational practices in server rooms/closets. Future work should include server power field measurements in data centers of different sizes, accounting for variations in configurations and setting changes post-purchase, as well as investigating the linkage between time and server energy efficiency.


Volume servers Energy use Server hardware Data centers Operational practices 



This work was supported by the Office of Energy Efficiency and Renewable Energy, Building Technologies Program, of the US Department of Energy under Lawrence Berkeley National Laboratory Contract No. DE-AC02-05CH11231.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


  1. Bard, A., Huang, R., & Friedmann, R. (2014). From our closet to yours: fashioning energy efficiency programs for small data centers. ACEEE Summer Study on Energy Efficiency in Buildings. Accessed October 2, 2017.
  2. Barroso, L. A., Clidaras, J., & Holzle, U. (2013). The datacenter as a computer: an introduction to the design of warehouse-scale machines. In M. D. Hill (Ed.), Synthesis lectures on computer architecture (2nd ed.). San Rafael: Morgan & Claypool Publishers Accessed September 21, 2017.
  3. Brown, R., Masanet, E., Nordman, B., Tschudi, W., Shehabi, A., Stanley, J., Koomey, J., Sartor, D., Chan, P., Loper, J., Capana, S., Hedman, B., Duff, R., Haines, E., Sass, D., & Fanara, A. (2007). Report to congress on server and data center energy efficiency: public law 109–431. Berkeley: Lawrence Berkeley National Laboratory LBNL-363E. Accessed September 15, 2017.
  4. ENERGY STAR. (2013). ENERGY STAR Program Requirements: Product Specification for Computer Servers—Eligibility Criteria, Version 2.1. U.S. Environmental Protection Agency and U.S. Department of Energy. Accessed September 5, 2017.
  5. ENERGY STAR. (2016). ENERGY STAR Unit Shipment and Market Penetration Report–Calendar Year 2015 Summary. U.S. Environmental Protection Agency and U.S. Department of Energy. Accessed September 28, 2017.
  6. ENERGY STAR. (2017). ENERGY STAR unit shipment and market penetration report – calendar year 2016 summary. Accessed September 28, 2017.
  7. IDC (International Data Corporation). (2014). Worldwide quarterly server tracker. Installed Base, 2006-2018. Framingham: IDC December.Google Scholar
  8. Koomey, J. (2008). Worldwide electricity used in data centers. Environmental Research Letters, 3, 034008.CrossRefGoogle Scholar
  9. Koomey, J. (2012). The economics of green DRAM in servers. Berkeley: Analytics Press Accessed August 30, 2017.
  10. Koomey, J. & Taylor, J. (2017). Zombie/comatose servers redux. Accessed October 2, 2017.
  11. Mansoor, A., Fortenbery, B. Vairamohan, B., Geist, T., May-Ostendorp, P., Calwell C., Rasmussen, R., McIlvoy, D., & Boehlke, J. (2014). Generalized test protocol for calculating the energy efficiency of internal Ac-Dc and Dc-Dc power supplies – revision 6.7. Accessed November 9, 2018.
  12. Masanet, E., Brown, R., Shehabi, A., Koomey, J., & Nordman, B. (2011). Estimating the energy use and efficiency potential of U.S. data centers. Proceedings of the IEEE, 99(8), 1440–1453.CrossRefGoogle Scholar
  13. Masanet, E., Shehabi, A., & Koomey, J. (2013). Characteristics of low-carbon data centres. Nature Climate Change, 3(7), 627–630.CrossRefGoogle Scholar
  14. Natural Resources Defense Council. (2014). Data center efficiency assessment – scaling up energy efficiency across the data center industry. Issue Paper 14-08-A. Accessed September 29, 2017.
  15. Shehabi, A., Smith, S. J., Horner, N., Azevedo, I., Brown, R., Koomey, J., Masanet, E., Sartor, D., Herrlin, M., & Lintner, W. (2016). U.S. data center energy usage report. Lawrence Berkeley National Laboratory Report #1005775. Accessed September 20, 2017.
  16. Van Heddeghem, W., Lambert, S., Lannoo, B., Colle, D., Pickavet, M., & Demeester, P. (2014). Trends in worldwide ICT electricity consumption from 2007 to 2012. Computer Communications, 50, 64–76.CrossRefGoogle Scholar

Copyright information

© This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2019

Authors and Affiliations

  1. 1.Lawrence Berkeley National LaboratoryEnergy Technologies AreaBerkeleyUSA
  2. 2.Department of Computer ScienceNational University of SingaporeSingaporeSingapore
  3. 3.Fraunhofer Center for Sustainable Energy SystemsBostonUSA
  4. 4.Navigant Consulting, Inc.SeattleUSA

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