ACE: Abstracting, characterizing and exploiting peaks and valleys in datacenter power consumption

Di Wang, Chuangang Ren, Sriram Govindan, Anand Sivasubramaniam, Bhuvan Urgaonkar, Aman Kansal, Kushagra Vaid

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

5 Scopus citations

Abstract

Peak power management of datacenters has tremendous cost implications. While numerous mechanisms have been proposed to cap power consumption, real datacenter power consumption data is scarce. To address this gap, we collect power demands at multiple spatial and fine-grained temporal resolutions from the load of geo-distributed datacenters of Microsoft over 6 months. We conduct aggregate analysis of this data, to study its statistical properties. With workload characterization a key ingredient for systems design and evaluation, we note the importance of better abstractions for capturing power demands, in the form of peaks and valleys. We identify and characterize attributes for peaks and valleys, and important correlations across these attributes that can influence the choice and effectiveness of different power capping techniques. With the wide scope of exploitability of such characteristics for power provisioning and optimizations, we illustrate its benefits with two specific case studies.

Original languageEnglish (US)
Title of host publicationSIGMETRICS 2013 - Proceedings of the 2013 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems
Pages333-334
Number of pages2
Edition1 SPEC. ISS.
DOIs
StatePublished - Jul 22 2013
Event2013 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2013 - Pittsburgh, PA, United States
Duration: Jun 17 2013Jun 21 2013

Publication series

NamePerformance Evaluation Review
Number1 SPEC. ISS.
Volume41
ISSN (Print)0163-5999

Other

Other2013 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2013
CountryUnited States
CityPittsburgh, PA
Period6/17/136/21/13

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

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    Wang, D., Ren, C., Govindan, S., Sivasubramaniam, A., Urgaonkar, B., Kansal, A., & Vaid, K. (2013). ACE: Abstracting, characterizing and exploiting peaks and valleys in datacenter power consumption. In SIGMETRICS 2013 - Proceedings of the 2013 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems (1 SPEC. ISS. ed., pp. 333-334). (Performance Evaluation Review; Vol. 41, No. 1 SPEC. ISS.). https://doi.org/10.1145/2494232.2465536