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Worst-case temperature analysis for different resource models

Worst-case temperature analysis for different resource models

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Published

The rapid increase in heat dissipation in real-time systems imposes various thermal issues. For instance, real-time constraints cannot be guaranteed if a certain threshold temperature is exceeded, as it would immediately reduce the system reliability and performance. Dynamic thermal management techniques are promising methods to prevent a system from overheating. However, when designing real-time systems that make use of such thermal management techniques, the designer has to be aware of their effect on both real-time constraints and worst-case peak temperature. In particular, the worst-case peak temperature of a real-time system with non-deterministic workload is the maximum possible temperature under all feasible scenarios of task arrivals. This study proposes an analytic framework to calculate the worst-case peak temperature of a system with general resource availabilities, which means that computing power might not be fully available for certain time intervals. The event and resource models are based on real-time and network calculus, and therefore, our analysis method is able to handle a broad range of uncertainties in terms of task arrivals and available computing power. Finally, we propose an indicator for the quality of the resource model with respect to worst-case peak temperature and schedulability.

Inspec keywords: reliability; thermal management (packaging)

Other keywords: thermal issues; heat dissipation; worst-case peak temperature analysis; worst-case peak schedulability; real-time systems; resource models; task arrivals; general resource availabilities; nondeterministic workload; system reliability; real-time constraints; network calculus; dynamic thermal management techniques

Subjects: Reliability; Product packaging

References

    1. 1)
    2. 2)
      • P. Garcia del Valle , D. Atienza . Emulation-based transient thermal modeling of 2D/3D systems-on-chip with active cooling. Microelectron. J. , 10 , 1 - 9
    3. 3)
    4. 4)
      • Bartolini, A., Cacciari, M., Tilli, A., Benini, L., Gries, M.: `A virtual platform environment for exploring power, thermal and reliability management control strategies in high-performance multicores', Proc. Great Lakes Symp. on VLSI (GLSVLSI), 2010, Providence, Rhode Island, USA, p. 311–316.
    5. 5)
      • Shin, I., Lee, I.: `Periodic resource model for compositional real-time guarantees', Proc. Real-Time Systems Symp., (RTSS), 2003, Cancun, Mexico, p. 2–13.
    6. 6)
      • J.-Y. Le Boudec , P. Thiran . Network calculus: a theory of deterministic queuing systems for the internet.
    7. 7)
      • Liu, Y., Dick, R.P., Shang, L., Yang, H.: `Accurate temperature-dependent integrated circuit leakage power estimation is easy', Proc. Design, Automation and Test in Europe (DATE), 2007, Nice, France, p. 1526–1531.
    8. 8)
    9. 9)
      • Bansal, N., Pruhs, K.: `Speed scaling to manage temperature', Proc. Symp on Theoretical Aspects of Computer Science (STACS), 2005, p. 460–471, (LNCS, 3404).
    10. 10)
      • Schor, L., Bacivarov, I., Yang, H., Thiele, L.: `Worst-case temperature guarantees for real-time applications on multi-core systems', Proc. IEEE Real-Time and Embedded Technology and Applications Symp., (RTAS), IEEE, 2012, Beijing, China, p. 87–96.
    11. 11)
      • Wandeler, E., Maxiaguine, A., Thiele, L.: `Performance analysis of greedy shapers in real-time systems', Proc. Design, Automation and Test in Europe (DATE), 2006, Munich, Germany, p. 444–449.
    12. 12)
    13. 13)
      • Kumar, P., Thiele, L.: `Cool shapers: shaping real-time tasks for improved thermal guarantees', Proc. Design Automation Conf., (DAC), 2011, San Diego, CA, USA, p. 468–473.
    14. 14)
    15. 15)
      • Thiele, L., Schor, L., Yang, H., Bacivarov, I.: `Thermal-aware system analysis and software synthesis for embedded multi-processors', Proc. Design Automation Conf., (DAC), 2011, San Diego, CA, USA, p. 268–273.
    16. 16)
      • Coskun, A.K., Rosing, T.S., Whisnant, K.: `Temperature aware task scheduling in MPSoCs', Proc. Design, Automation and Test in Europe (DATE), 2007, Nice, France, p. 1659–1664.
    17. 17)
    18. 18)
      • Chantem, T., Hu, X.S., Dick, R.P.: `Online work maximization under a peak temperature constraint', Proc. Int. Symp. on Low Power Electronics and Design (ISLPED), 2009, San Fancisco, CA, USA, p. 105–110.
    19. 19)
    20. 20)
      • Serreli, N., Lipari, G., Bini, E.: `The demand bound function interface of distributed sporadic pipelines of tasks scheduled by EDF', Proc. Euromicro Conf. on Real-Time Systems (ECRTS), 2010, Brussels, Belgium, p. 187–196.
    21. 21)
      • Thiele, L., Chakraborty, S., Naedele, M.: `Real-time calculus for scheduling hard real-time systems', Proc. IEEE Int. Symp on Circuits and Systems (ISCAS), 2000, Geneva, Switzerland, p. 101–104.
    22. 22)
      • Rai, D., Yang, H., Bacivarov, I., Chen, J.-J., Thiele, L.: `Worst-case temperature analysis for real-time systems', Proc. Design, Automation and Test in Europe (DATE), 2011, Grenoble, France, p. 1–6.
    23. 23)
    24. 24)
      • Murali, S., Mutapcic, A., Atienza, D., Gupta, R., Boyd, S., De Micheli, G.: `Temperature-aware processor frequency assignment for MPSoCs using convex optimization', Proc. Int. Conf. on Hardware/Software Codesign and System Synthesis (CODES+ISSS), 2007, Salzburg, Austria, p. 111–116.
    25. 25)
      • Donald, J., Martonosi, M.: `Techniques for multicore thermal management: classification and new exploration', Proc. Int. Symp on Computer Architecture (ISCA), 2006, Boston, Massachusetts, USA, p. 78–88.
    26. 26)
      • A. Krum , F. Kreith . (2000) Thermal management, The CRC handbook of thermal engineering.
    27. 27)
      • Schor, L., Yang, H., Bacivarov, I., Thiele, L.: `Worst-case temperature analysis for different resource availabilities: a case study', Proc. Int. Workshop on Power and Timing Modeling, Optimization, and Simulation (PATMOS), 2011, p. 288–297, (LNCS, 6951).
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