TPR: Traffic Pattern-Based Adaptive Routing for Dragonfly Networks
TPR: Traffic Pattern-Based Adaptive Routing for Dragonfly Networks
复制标题
TPR：蜻蜓网络基于流量模式的自适应路由
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
M. Lang
中科院分区：
文献类型：
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作者：
Peyman Faizian;Juan Francisco Alfaro;Md. Shafayat Rahman;Md Atiqul Mollah;Xin Yuan;S. Pakin;M. Lang
Cray Cascade Architecture使用Dragonfly作为其互连拓扑，并采用了一种称为ugal的全球自适应路由方案。 Ugal根据链接负载指导流量，但可能会在各种情况下做出不适当的适应性路由决策，从而降低其性能。在这项工作中，我们为蜻蜓提出了基于流量模式的自适应路由（TPR），该路由通过结合基于交通模式的适应机制来改善乌干达。这个想法是要明确使用在性能计数器中收集的链接使用统计信息来推断流量模式，并在做出自适应路由决策时考虑推断的流量模式以及链接负载。我们对各种交通状况的绩效评估结果表明，通过纳入基于交通模式的适应机制，TPR在做出适应性路由决策方面更有效，并且在高负载下低负载和较高的吞吐量在高负载下的潜伏期明显较低。丑陋。
The Cray Cascade architecture uses Dragonfly as its interconnect topology and employs a globally adaptive routing scheme called UGAL. UGAL directs traffic based on link loads but may make inappropriate adaptive routing decisions in various situations, which degrades its performance. In this work, we propose traffic pattern-based adaptive routing (TPR) for Dragonfly that improves UGAL by incorporating a traffic pattern-based adaptation mechanism. The idea is to explicitly use the link usage statistics that are collected in performance counters to infer the traffic pattern, and to take the inferred traffic pattern plus link loads into consideration when making adaptive routing decisions. Our performance evaluation results on a diverse set of traffic conditions indicate that by incorporating the traffic pattern-based adaptation mechanism, TPR is much more effective in making adaptive routing decisions and achieves significant lower latency under low load and higher throughput under high load than its underlying UGAL.