Speeding-up the fault-tolerance analysis of interconnection networks

Diego F. Bermúdez Garzón, Crispín Gómez Requena, P. López, M. E. Gómez
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Abstract

Analyzing the fault-tolerance of interconnection networks implies checking the connectivity of each source-destination pair. The size of the exploration space of such operation skyrockets with the network size and with the number of link faults. However, this problem is highly parallelizable since the exploration of each path between a source-destination pair is independent of the other paths. This paper presents an approach to analyze the fault-tolerance degree of multistage interconnection networks using GPUs in order to speed-up it. This approach uses CUDA as parallel programming tool on a GPU in order to take advantage of all available cores. Results show that the execution time of the fault-tolerance exploration can be significantly reduced.
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加快互联网络容错分析
分析互连网络的容错性需要检查每个源-目的对的连通性。随着网络规模和链路故障数量的增加,此类操作的探索空间也随之增大。然而,这个问题是高度并行化的,因为在源-目标对之间的每条路径的探索是独立于其他路径的。本文提出了一种利用图形处理器分析多级互连网络容错程度的方法,以加快多级互连网络的速度。这种方法使用CUDA作为GPU上的并行编程工具,以便利用所有可用的内核。结果表明,该方法可以显著缩短容错探测的执行时间。
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