Real-time worst-case temperature analysis with temperature-dependent parameters

Abstract

With the evolution of today’s semiconductor technology, chip temperature increases rapidly mainly due to the growth in power density. Therefore, for modern embedded real-time systems it is crucial to estimate maximal temperatures early in the design in order to avoid burnout and to guarantee that the system can meet its real-time constraints. This paper provides answers to a fundamental question: What is the worst-case peak temperature of a real-time embedded system under all feasible scenarios of task arrivals? A novel thermal-aware analytic framework is proposed that combines a general event/resource model based on network and real-time calculus with system thermal equations. This analysis framework has the capability to handle a broad range of uncertainties in terms of task execution times, task invocation periods, jitter in task arrivals, and resource availability. The considered model takes both dynamic and leakage power as well as thermal dependent conductivity into consideration. Thorough simulation experiments validate the theoretical results.

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Notes

  1. 1.

    This is exactly where the work-conserving assumption is effective. That is, without this work-conserving assumption, arbitrarily many workload can be delayed and accumulated regardless of resource availability making γ unbounded.

  2. 2.

    As S(t) implies an operating mode at moment t, it is not a continuous function.

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Acknowledgements

The work described in this paper has been funded by EU FP7 project EURETILE under grant number 247846 and partially supported by the TRANSCEND Strategic Action from Nano-Tera.ch.

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Correspondence to Hoeseok Yang.

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Yang, H., Bacivarov, I., Rai, D. et al. Real-time worst-case temperature analysis with temperature-dependent parameters. Real-Time Syst 49, 730–762 (2013). https://doi.org/10.1007/s11241-013-9188-y

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Keywords

  • Real-time systems
  • Real-time analysis
  • Formal worst-cast temperature analysis
  • Temperature-dependent leakage power
  • Resource availability