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Performance comparison of thermal aware job scheduling based on multi priorities on computational grid

机译:计算网格上基于多优先级的热感知作业调度的性能比较

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Electricity consumption for cooling purpose is known to be the most expensive operational cost factor in data centers. Inefficient cooling leads to high temperature and this in turn leads to hardware failure. This paper proposes a Thermal Aware Modified Least Slack Time Round Robin Based (MLST-RR) scheduling algorithm that can avoid high thermal stress circumstances such as large hotspots, thermal violations as well as reduce electricity consumption for cooling in data center labs. The experimental results show that, the thermal aware MLST-RR is able to significantly decrease the electricity consumption while maintaining competitive performance. Specifically, the thermal aware scheduling algorithm saves electricity consumption as much as 15000KW compared to the benchmark job scheduling algorithms such as Round Robin (RR) and First Come First Serve (FCFS); this is an electrical saving of 8.4%.
机译:众所周知,用于冷却目的的电力消耗是数据中心中最昂贵的运营成本因素。散热不充分会导致高温,进而导致硬件故障。本文提出了一种基于热感知的改进的最小松弛时间基于循环调度(MLST-RR)的调度算法,该算法可避免出现大的热点,热违规等高热应力情况,并减少数据中心实验室的冷却用电。实验结果表明,具有热敏性的MLST-RR能够显着降低耗电量,同时保持竞争优势。具体来说,与基准作业调度算法(如Round Robin(RR)和先来先服务(FCFS))相比,热感知调度算法可节省多达15000KW的电力消耗;节省了8.4%的电力。

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