Traffic Pattern-Based Adaptive Routing for Intra-Group Communication in Dragonfly Networks

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 to improve UGAL by incorporating a traffic patternbased adaptation mechanism for intra-group communication in Dragonfly. 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, our scheme is more effective in making adaptive routing decisions and achieves lower latency under low load and higher throughput under high load than the existing UGAL in many situations.