Power Modelling for Heterogeneous Cloud-Edge Data Centers

Kai Chen, Blesson Varghese, Peter Kilpatrick, Dimitrios S. Nikolopoulos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)
140 Downloads (Pure)


Existing power modelling research focuses not on the method used for developing models but rather on the model itself. This paper aims to develop a method for deploying power models on emerging processors that will be used, for example, in cloud-edge data centers. Our research first develops a hardware counter selection method that appropriately selects counters most correlated to power on ARM and Intel processors. Then, we propose a two stage power model that works across multiple architectures. The key results are: (i) the automated hardware performance counter selection method achieves comparable selection to the manual selection methods reported in literature, and (ii) the two stage power model can predict dynamic power more accurately on both ARM and Intel processors when compared to classic power models.
Original languageEnglish
Title of host publication International Conference on Parallel Computing: Proceedings
Number of pages10
Publication statusPublished - 15 Sept 2017
EventInternational Conference on Parallel Computing - Bologna, Italy
Duration: 12 Sept 201715 Sept 2017

Publication series

NameAdvances in Parallel Computing
ISSN (Print)0927-5452


ConferenceInternational Conference on Parallel Computing


  • power modelling
  • cloud-edge computing
  • heterogeneous data centers


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