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Peak Temperature Minimization via Task Allocation and Splitting for Heterogeneous MPSoC Real-Time Systems

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Abstract

With the continued scaling of the CMOS devices, the exponential increase in power density has strikingly elevated the temperature of on-chip systems. Thus, thermal-aware design has become a pressing research issue in computing system, especially for real-time embedded systems with limited cooling techniques. In this paper, the authors formulate the thermal-aware real-time multiprocessor system-on-chip (MPSoC) task allocation and scheduling problem, present a task-to-processor assignment heuristics that improves the thermal profiles of tasks, and propose a task splitting policy that reduces the on-chip peak temperature. The thermal profiles of tasks are improved via task mapping by minimizing task steady state temperatures, and the task splitting technique is applied to reduce the peak temperature by enabling the alternation of hot task execution and slack time. The proposed algorithms explicitly exploits thermal characteristics of both tasks and processors to minimize the peak temperature without incurring significant overheads. Extensive simulations of benchmarking tasks were performed to validate the effectiveness of the proposed algorithms. Experimental results have shown that the task steady state temperature achieved by the proposed algorithm is 3.57 °C lower on average as compared to the benchmarking schemes, and the peak temperature of the proposed algorithm can be up to 11.5 % lower than that of the benchmarking schemes

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Acknowledgements

This work was supported in part by the Natural Science Foundation of Shanghai City under the grant 12ZR1409200 and by the Scientific Research Foundation for Returned Scholars, Ministry of Education of China, under the grant 44420340.

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Authors and Affiliations

  1. Shanghai Key Laboratory of Multidimensional Information Processing, Shanghai, 200241, China

    Junlong Zhou, Jianming Yan & Tongquan Wei

  2. Computer Science and Technology Department of East China Normal University, Shanghai, 200241, China

    Junlong Zhou, Jianming Yan & Tongquan Wei

  3. Baidu Corporation, Shanghai, 200241, China

    Jing Chen

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  1. Junlong Zhou
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  2. Jianming Yan
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  3. Jing Chen
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  4. Tongquan Wei
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Correspondence to Tongquan Wei.

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Zhou, J., Yan, J., Chen, J. et al. Peak Temperature Minimization via Task Allocation and Splitting for Heterogeneous MPSoC Real-Time Systems. J Sign Process Syst 84, 111–121 (2016). https://doi.org/10.1007/s11265-015-0994-4

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  • DOI: https://doi.org/10.1007/s11265-015-0994-4

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