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

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Abstract

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.

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Notes

  1. For example, all federal agencies must procure ENERGY STAR or Federal Energy Management Program (FEMP) designated products when possible, according to the Energy Policy Act of 2005.

  2. To test the power supplies, NCI followed the generalized internal PSU efficient test protocol document used by the 80 PLUS program (Mansoor et al. 2014). This standard specifies how to set a constant load on the 12 V/5 V/3.3 V rails for a given loading condition (i.e., 10%). NCI tested a single sample of each type of 80 PLUS PSU.

  3. No particular date of publication or revision is given on this site, other than a copyright running from 2007 to 2018. We include the access date for each discrete data collection event.

  4. In an effort to assign a “typical” value based on number of sockets and number of processors, we used median values because they are less influenced by extreme values in the distribution, and also represent an actual value from the distribution.

  5. The most recent year of market share data we had available was 2014.

  6. Assuming a 95% confidence level; the Bureau of Labor Statistics reports 348,500 computer and information systems manager jobs nationwide in 2014 at https://www.bls.gov/ooh/management/computer-and-information-systems-managers.htm.

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Acknowledgements

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.

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Correspondence to Heidi Fuchs.

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Fuchs, H., Shehabi, A., Ganeshalingam, M. et al. Comparing datasets of volume servers to illuminate their energy use in data centers. Energy Efficiency 13, 379–392 (2020). https://doi.org/10.1007/s12053-019-09809-8

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  • DOI: https://doi.org/10.1007/s12053-019-09809-8

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