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Taking Advantage of Node Power Variation in Homogenous HPC Systems to Save Energy

机译:利用同质HPC系统中的节点功率变化来节省能源

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Saving energy and, therefore, reducing the Total Cost of Ownership (TCO) for High Performance Computing (HPC) data centers has increasingly generated attention in light of rising energy costs and the technical hurdles imposed when powering multi-MW data centers. The broadest impact on data center energy efficiency can be achieved by techniques that do not require application specific tuning. Improving the Power Usage Effectiveness (PUE), for example, benefits everything that happens in a data center. Less broad but still better than individual application tuning would be to improve the energy efficiency of the HPC system itself. One property of homogeneous HPC systems that hasn't been considered so far is the existence of node power variation. This paper discusses existing node power variations in two HPC systems. It introduces three energy-saving techniques: node power aware scheduling, node power aware system partitioning, and node ranking based on power variation, which take advantage of this variation, and quantifies possible savings for each technique. It will show that using node power aware system partitioning and node ranking based on power variation will save energy with very minimal effort over the lifetime of the system. All three techniques are also relevant for distributed and cloud environments.
机译:鉴于不断增长的能源成本以及为多兆瓦数据中心供电时遇到的技术障碍,节约能源并因此降低高性能计算(HPC)数据中心的总体拥有成本(TCO)越来越引起人们的关注。通过不需要特定应用程序调整的技术,可以实现对数据中心能源效率的最广泛影响。例如,提高电源使用效率(PUE)可以使数据中心发生的一切事情都受益。如果不那么广泛,但比单独的应用程序调整更好,将是提高HPC系统本身的能效。到目前为止尚未考虑的同类HPC系统的一个特性是节点功率变化的存在。本文讨论了两个HPC系统中现有节点功率的变化。它介绍了三种节能技术:节点功率感知调度,节点功率感知系统分区和基于功率变化的节点排名,它们利用了这种变化并量化了每种技术的可能节省量。它将显示使用基于节点功率感知的节点功率感知系统分区和节点排名将在系统的整个生命周期内以最小的工作量来节省能源。所有这三种技术都与分布式和云环境有关。

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