Performance-aware thermal management via task scheduling

  • Authors:
  • Xiuyi Zhou;Jun Yang;Marek Chrobak;Youtao Zhang

  • Affiliations:
  • University of Pittsburgh, Pittsburgh, PA;University of Pittsburgh, Pittsburgh, PA;University of California, Riverside, CA;University of Pittsburgh, Pittsburgh, PA

  • Venue:
  • ACM Transactions on Architecture and Code Optimization (TACO)
  • Year:
  • 2010

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Abstract

High on-chip temperature impairs the processor's reliability and reduces its lifetime. Hardware-level dynamic thermal management (DTM) techniques can effectively constrain the chip temperature, but degrades the performance. We propose an OS-level technique that performs thermal-aware job scheduling to reduce DTMs. The algorithm is based on the observation that hot and cool jobs executed in a different order can make a difference in resulting temperature. Real-system implementation in Linux shows that our scheduler can remove 10.5% to 73.6% of the hardware DTMs in a medium thermal environment. The CPU throughput is improved by up to 7.6% (4.1%, on average) in a severe thermal environment.