服务器集群中线程的高能效虚拟化

Hiroki Kataoka, Dilawaer Duolikun, T. Enokido, M. Takizawa
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引用次数: 29

摘要

减少集群中服务器的功耗是实现生态社会的关键。在以往的研究中,我们提出了具有多线程CPU的服务器的多级功耗(MLPC)模型,并讨论了全局能量感知(GEA)算法来为集群中的每个进程选择服务器。这样,不仅可以降低集群内所有服务器的总能耗,而且可以降低集群内服务器消耗的基本电能占总能耗的比例。然而,GEA算法是不可扩展的,因为要检查每个服务器以为集群中的每个进程找到服务器。在本文中,我们提出了一种可扩展的能量感知(SEA)算法来为进程选择服务器。在这里,首先在集群中随机选择一些服务器,然后通过GEA算法在所选服务器中选择一个服务器。我们对SEA算法进行了评估,结果表明,与其他算法相比,SEA算法不仅减少了服务器的总电能消耗,而且减少了进程的平均执行时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Energy-Efficient Virtualisation of Threads in a Server Cluster
It is critical to reduce the electric power consumed by servers in a cluster in order to realize eco society. In our previous studies, the multi-level power consumption (MLPC) model of a server with a multi-thread CPU, the power consumption of the server is proposed and the globally energy-aware (GEA) algorithm is discussed to select a server for each process in a cluster. Here, not only the total electric energy consumption of all the servers but also the ratio of the basic electric energy consumed by the servers to the total electric energy consumption can be reduced in a cluster. However, the GEA algorithm is not scalable since every server is checked to find a server for each process in a cluster. In this paper, we newly propose a scalable energy-aware (SEA) algorithm to select a server for a process. Here, some number of servers are first randomly selected in a cluster and one server is then selected in the selected servers by the GEA algorithm. We evaluate the SEA algorithm and show not only the total electric energy consumption of the servers but also the average execution time of processes are reduced in the SEA algorithm compared with other algorithms.
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