k元n立方网络中的吞吐量公平性

C. Izu
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引用次数: 10

摘要

互连网络的性能由两个指标衡量:平均延迟和峰值网络吞吐量。网络吞吐量是单位时间内发送的数据包总数。大多数合成网络负载由以相同给定速率注入的源组成,使用诸如随机、排列或热点等流量模式,这些模式反映了许多并行应用程序中数据包目的地的分布。假设网络是公平的:所有源节点都能够以相同的速率注入。这项工作将表明这样的假设是没有根据的大多数路由器提案。在非均匀负载下,所有路由器设计都表现出显著的网络不公平性。一些路由器在随机流量模式下也不公平。在负载超过饱和时,如果信道利用率不均匀,则注入矩阵会变得不均匀:低利用率区域的数据包接受率高于繁忙区域的数据包接受率。由于合成流量不能反映并行应用程序生成的流量的耦合性质,因此无法衡量这种不公平对应用程序性能的影响。需要开发新的综合负载来更好地评估超过饱和的网络响应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Throughput fairness in k-ary n-cube networks
The performance of an interconnection network is measured by two metrics: average latency and peak network throughput. Network throughput is the total number of packets delivered per unit of time.Most synthetic network loads consist of sources injecting at the same given rate, using traffic patterns such as random, permutations or hot spot, which reflect the distribution of packet destinations in many parallel applications. The network is assumed to be fair: all source nodes are able to inject at the same rate. This work will show such assumption is unfounded for most router proposals. All router designs exhibited significant network unfairness under non-uniform loads. Some routers are also unfair under random traffic patterns. At loads above saturation, if the channel utilization is uneven, the injection matrix will become uneven: packet at low used areas will be accepted at a higher rate that those at the busy areas.As synthetic traffic does not reflect the coupled nature of the traffic generated by parallel applications, the impact of this unfairness on application performance could not be measured. New synthetic loads need to be developed to better evaluate network response beyond saturation.
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