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Thermal-Aware Task Scheduling for Energy Minimization in Heterogeneous Real-Time MPSoC Systems

机译:异构实时MPSoC系统中用于热量最小化的热感知任务调度

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With the continuous scaling of CMOS devices, the increase in power density and system integration level have not only resulted in huge energy consumption but also led to elevated chip temperature. Thus, energy efficient task scheduling with thermal consideration has become a pressing research issue in computing systems, especially for real-time embedded systems with limited cooling techniques. In this paper, we design a two-stage energy-efficient temperature-aware task scheduling scheme for heterogeneous real-time multiprocessor system-on-chip (MPSoC) systems. In the first stage, we analyze the energy optimality of assigning real-time tasks to multiple processors of an MPSoC system, and design a task assignment heuristic that minimizes the system dynamic energy consumption under the constraint of task deadlines. In the second stage, the optimality of minimizing the peak temperature of a processor is investigated, and a slack distribution heuristic is proposed to improve the temperature profile of each processor under the thermal constraint, thus the temperature-dependent system leakage energy consumption is reduced. Through the extensive efforts made in two stages, the system overall energy consumption is minimized. Experimental results have demonstrated the effectiveness of our scheme.
机译:随着CMOS器件规模的不断扩大,功率密度和系统集成度的提高不仅导致巨大的能耗,而且导致芯片温度升高。因此,考虑热量因素的节能任务调度已成为计算系统中的紧迫研究问题,特别是对于冷却技术有限的实时嵌入式系统。在本文中,我们为异构实时多处理器片上系统(MPSoC)系统设计了两阶段的节能温度感知任务调度方案。在第一阶段,我们分析了将实时任务分配给MPSoC系统的多个处理器的能量最优性,并设计了任务分配试探法,该任务试探法可在任务截止期限的约束下将系统动态能耗降至最低。在第二阶段,研究了最小化处理器峰值温度的最优性,并提出了一种松弛分布启发式方法来改善在热约束下每个处理器的温度分布,从而降低了与温度有关的系统泄漏能耗。通过分两个阶段的广泛努力,系统的总能耗得以最小化。实验结果证明了该方案的有效性。

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