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Improved routing algorithms in the dual-port datacenter networks HCN and BCN.

机译:在双端口数据中心网络HCN和BCN中改进了路由算法。

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摘要

We present significantly improved one-to-one routing algorithms in the datacenter networks HCN and View the MathML source in that our routing algorithms result in much shorter paths when compared with existing routing algorithms. We also present a much tighter analysis of HCN and View the MathML sourceby observing that there is a very close relationship between the datacenter networks HCN and the interconnection networks known as WK-recursive networks. We use existing results concerning WK-recursive networks to prove the optimality of our new routing algorithm for HCN and also to significantly aid the implementation of our routing algorithms in both HCN and View the MathML source. Furthermore, we empirically evaluate our new routing algorithms for View the MathML source, against existing ones, across a range of metrics relating to path-length, throughput, and latency for the traffic patterns all-to-one, bisection, butterfly, hot-region, many-all-to-all, and uniform-random, and we also study the completion times of workloads relating to MapReduce, stencil and sweep, and unstructured applications. Not only do our results significantly improve routing in our datacenter networks for all of the different scenarios considered but they also emphasise that existing theoretical research can impact upon modern computational platforms.
机译:我们在数据中心网络HCN和目前的数据中心网络中提出了显着改进的一对一路由算法,因为与现有路由算法相比,我们的路由算法产生的路径短得多。通过观察数据中心网络HCN与称为WK递归网络的互连网络之间存在非常紧密的关系,我们还对HCN和进行了更为严格的分析。我们使用有关WK递归网络的现有结果来证明针对HCN的新路由算法的最优性,并在HCN和View MathML源代码中显着帮助实现我们的路由算法。此外,我们会针对与流量模式的路径长度,吞吐量和延迟相关的一系列指标,针对所有流量模式,一对一,二等分,蝶形,热点,区域,多对所有和均匀随机性,我们还研究了与MapReduce,模板和扫掠以及非结构化应用程序有关的工作负载的完成时间。对于考虑的所有不同情况,我们的结果不仅显着改善了数据中心网络中的路由,而且还强调,现有的理论研究可能会影响现代计算平台。

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