GentleCool: Cooling aware proactive workload scheduling in multi-machine systems

R. Ayoub, Shervin Sharifi, T. Simunic
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引用次数: 29

Abstract

In state of the art systems, workload scheduling and server fan speed operate independently leading to cooling inefficiencies. We propose GentleCool, a proactive multi-tier approach for significantly lowering the fan cooling costs without compromising the performance. Our technique manages the fan speed through intelligently allocating the workload across different machines. The experimental results show our approach delivers average cooling energy savings of 72% and improves the mean time between failures (MTBF) of the fans by 2.3X compared to the state of the art.
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genlecool:多机系统中具有冷却意识的主动工作负载调度
在最先进的系统中,工作负载调度和服务器风扇速度独立运行导致冷却效率低下。我们提出了GentleCool,这是一种主动的多层方法,可以在不影响性能的情况下显着降低风扇冷却成本。我们的技术通过智能地在不同的机器上分配工作负载来管理风扇速度。实验结果表明,我们的方法平均节省了72%的冷却能源,并将风扇的平均无故障时间(MTBF)提高了2.3倍。
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