Predict and act: dynamic thermal management for multi-core processors

  • Authors:
  • Raid Zuhair Ayoub;Tajana Simunic Rosing

  • Affiliations:
  • University of California, San Diego, La Jolla, CA, USA;University of California, San Diego, La Jolla, CA, USA

  • Venue:
  • Proceedings of the 14th ACM/IEEE international symposium on Low power electronics and design
  • Year:
  • 2009

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Abstract

In this paper, we propose a proactive dynamic thermal management scheme for chip multiprocessors that run multi-threaded workloads. We introduce a new predictor that utilizes the band-limited property of the temperature frequency spectrum. A big advantage of our predictor is that it does not require the costly training phase like ARMA [7]. Our thermal management scheme incorporates temperature prediction information and runtime workload characterization to perform efficient thermally aware scheduling. Our results show that applying our algorithm considerably improves the average system temperature, hottest core temperature, product MTTF and performance by 6 °C, 8 °C, 41% and 72% respectively.