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Performance Modeling of Subnet Management on Fat Tree InfiniBand Networks using OpenSM

机译:使用opensm对脂肪树Infiniband网络的子网管理性能建模

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InfiniBand is becoming increasingly popular in the area of cluster computing due to its open standard and high performance. Fat Tree is a primary interconnection topology for building large scale InfiniBand clusters. Instead of using a shared bus approach, InfiniBand employs an arbitrary switched point-to-point topology. In order to manage the subnet, InfiniBand specifies a basic management infrastructure responsible for discovery, configuration and maintaining the active state of the network. In the literature, simulation studies have been done on irregular topologies to characterize the subnet management mechanism. However, there is no study to model subnet management mechanism on regular topologies using actual implementations. In this paper, we take up the challenge of modeling subnet management mechanism for Fat Tree InfiniBand networks using a popular subnet manager OpenSM. We present the timings for various subnet management phases namely topology discovery, path computation and path distribution for large scale fat tree InfiniBand subnets and present basic performance evaluation on small scale InfiniBand cluster. We verify our model with the basic set of results obtained, and present the results for the model by varying different parameters on Fat Trees.
机译:由于其开放标准和高性能,Infiniband在集群计算领域变得越来越受欢迎。脂肪树是建立大型Infiniband集群的主要互连拓扑。 Infiniband而不是使用共享总线方法,而是使用任意切换点对点拓扑。为了管理子网,InfiniBand指定负责发现,配置和维护网络的活动状态的基本管理基础架构。在文献中,已经在不规则拓扑上进行了模拟研究,以表征子网管理机制。但是,使用实际实现,没有研究常规拓扑上的子网管理机制。在本文中,我们使用流行的子网管理器opensm占用脂肪树Infiniband网络的模型管理机制的挑战。我们介绍了各种子网管理阶段的时间,即大规模胖树Infiniband子网的拓扑发现,路径计算和路径分布,并对小型InfiniBand集群进行基本性能评估。我们使用获得的基本结果验证我们的模型,并通过在脂肪树上改变不同的参数来展示模型的结果。

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