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Thermal-Aware Task Scheduling for Energy Minimization in Heterogeneous Real-Time MPSoC Systems
139
Citations
32
References
2015
Year
EngineeringEnergy EfficiencyComputer ArchitectureEmbedded SystemsEnergy MinimizationReal-time Embedded SystemsSystems EngineeringParallel ComputingPower-aware SoftwarePower-aware ComputingComputer EngineeringScheduling (Computing)Computer ScienceReal-time AlgorithmThermal-aware Task SchedulingScheduling AnalysisSlack Distribution HeuristicEnergy ManagementEdge ComputingReal-time Multiprocessor SystemContinuous ScalingReal-time SystemsPower-efficient ComputingThermal Engineering
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.
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