The Journal of Supercomputing

, Volume 70, Issue 3, pp 1451–1476 | Cite as

Energy measurement, modeling, and prediction for processors with frequency scaling

  • Thomas RauberEmail author
  • Gudula Rünger
  • Michael Schwind
  • Haibin Xu
  • Simon Melzner


The energy consumption is an important aspect of today’s processors and a large variety of research approaches deal with reducing the energy consumption for specific application codes on different platforms under certain constraints. These research approaches are based on energy information acquired by very different means, such as hardware settings with power-meters, software methods with hardware counters available for more recent CPUs, or simulations based on theoretical models. In this article, all of these energy acquisition methods are investigated and compared. As application programs, we consider the SPEC CPU2006 integer and floating-point benchmark collections, which represent a large variety of applications from different areas. The investigations are done for single multicore CPUs with the goal to get more insight into their energy consumption behavior. An experimental evaluation is performed on three recent processor types with dynamic voltage–frequency scaling. The article compares the measured energy and the energy provided by hardware counters with the energy predicted by simulation models. The comparison shows that the simulation models are able to capture the energy consumption quite accurately.


Dynamic voltage–frequency scaling DVFS SPEC CPU2006 benchmarks Energy measurement Energy models 



This work was supported by the federal Cluster of Excellence EXC 1075 “MERGE technologies for Functional Lightweight Structures” and the research grant RU591-10/2, both supported by the German Research Foundation (DFG).


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Thomas Rauber
    • 1
    Email author
  • Gudula Rünger
    • 2
  • Michael Schwind
    • 2
  • Haibin Xu
    • 2
  • Simon Melzner
    • 1
  1. 1.Computer Science DepartmentUniversity BayreuthBayreuthGermany
  2. 2.Computer Science DepartmentChemnitz University of TechnologyChemnitzGermany

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