@article{31940,
  author = {Heidi Fuchs and Arman Shehabi and Mohan Ganeshalingam and Louis-Benoit Desroches and Brian Lim and Kurt Roth and Allen Tsao},
  title = {Comparing datasets of volume servers to illuminate their energy use in data centers},
  abstract = {<p>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.</p>},
  year = {2019},
  journal = {Energy Efficiency},
  volume = {13},
  pages = {379-392},
  month = {07/2019},
  issn = {1570-646X},
  doi = {10.1007/s12053-019-09809-8},
  language = {eng},
}