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DiBA: Distributed Power Budget Allocation for Large-Scale Computing Clusters

机译:DiBA:大型计算集群的分布式电源预算分配

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Power management has become a central issue inlarge-scale computing clusters where a considerable amount ofenergy is consumed and a large operational cost is incurredannually. Traditional power management techniques have a centralizeddesign that creates challenges for scalability of computingclusters. In this work, we develop a framework for distributedpower budget allocation that maximizes the utility of computingnodes subject to a total power budget constraint. To eliminate the role of central coordinator in the primaldualtechnique, we propose a distributed power budget allocationalgorithm (DiBA) which maximizes the combined performanceof a cluster subject to a power budget constraint in a distributedfashion. Specifically, DiBA is a consensus-based algorithm inwhich each server determines its optimal power consumptionlocally by communicating its state with neighbors (connectednodes) in a cluster. We characterize a synchronous primal-dualtechnique to obtain a benchmark for comparison with thedistributed algorithm that we propose. We demonstrate numericallythat DiBA is a scalable algorithm that outperforms theconventional primal-dual method on large scale clusters in termsof convergence time. Further, DiBA eliminates the communicationbottleneck in the primal-dual method. We thoroughly evaluatethe characteristics of DiBA through simulations of large-scaleclusters. Furthermore, we provide results from a proof-of-conceptimplementation on a real experimental cluster.
机译:在大型计算集群中,电源管理已成为一个中心问题,在该集群中,大量的能源被消耗,并且每年产生大量的运营成本。传统的电源管理技术具有集中式设计,这给计算集群的可伸缩性带来了挑战。在这项工作中,我们开发了用于分布式电源预算分配的框架,该框架在受到总电源预算约束的情况下最大程度地提高了计算节点的效用。为了消除中央协调器在原始技术中的作用,我们提出了一种分布式电源预算分配算法(DiBA),该算法可以使在分布式电源中受电源预算约束的群集的综合性能最大化。具体来说,DiBA是一种基于共识的算法,其中,每个服务器都通过与群集中的邻居(连接的节点)进行通信来在本地确定其最佳功耗。我们表征了同步原始对偶技术,以获取基准,以便与我们提出的分布式算法进行比较。我们通过数值证明,DiBA是一种可扩展算法,在收敛时间方面,它在大规模集群上优于传统的原始对偶方法。此外,DiBA消除了原始对偶方法中的沟通瓶颈。通过对大型集群的仿真,我们彻底评估了DiBA的特性。此外,我们提供了在真实实验集群上的概念验证实现的结果。

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