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Analysis of power-saving techniques over a large multi-use cluster with variable workload

机译:工作负载可变的大型多用途集群上的节能技术分析

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Reduction of power consumption for any computer system is now an important issue, although this should be carried out in a manner that is not detrimental to the users of that computer system. We present a number of policies that can be applied to multi-use clusters where computers are shared between interactive users and high-throughput computing. We evaluate policies by trace-driven simulations to determine the effects on power consumed by the high-throughput workload and impact on high-throughput users. We further evaluate these policies for higher workloads by synthetically generating workloads based around the profiled workload observed through our system. We demonstrate that these policies could save -55% of the currently used energy for our high-throughput jobs over our current cluster policies without affecting the high-throughput users' experience.
机译:现在,减少任何计算机系统的功耗都是一个重要的问题,尽管应该以不损害该计算机系统用户的方式进行。我们提出了许多策略,可以将这些策略应用于多用途集群,在这些集群中,计算机在交互式用户和高吞吐量计算之间共享。我们通过跟踪驱动的仿真来评估策略,以确定对高吞吐量工作负载所消耗的功率的影响以及对高吞吐量用户的影响。通过基于通过系统观察到的概要分析工作负载综合生成工作负载,我们进一步评估了这些策略以应对更高的工作负载。我们证明,与我们当前的群集策略相比,这些策略可以为我们的高吞吐量工作节省目前-55%的能耗,而不会影响高吞吐量用户的体验。

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