随机任务布置不能随机化流量(足够)

Ana Jokanovic, B. Prisacari, G. Rodríguez, C. Minkenberg
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引用次数: 7

摘要

蜻蜓是Exascale项目中最有前途的拓扑之一,因为它具有可扩展性和成本。蜻蜓在均匀流量下可以实现非常高的吞吐量,但在其他规则流量模式下会出现病态行为,其中一些在高性能计算应用中非常常见。最近的一项研究表明,任务放置的随机化可以使病态的、规则的(多维模板)交通模式表现得与均匀交通相似。在这项工作中,我们提供了一个理论模型,能够预测均匀流量下通用蜻蜓网络的预期性能,并表征性能最优的蜻蜓。然后,我们通过对多个此类模式在连续和随机任务布置下的性能进行基准测试,分析该模型是否可以扩展到其他模式。我们得出的结论是,尽管与连续任务放置相比,随机化确实导致病态通信模式的性能显著提高,但这种性能与均匀流量的性能相比并不相同,而是一半。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Randomizing task placement does not randomize traffic (enough)
Dragonflies are one of the most promising topologies for the Exascale effort for their scalability and cost. Dragonflies achieve very high throughput under uniform traffic, but have a pathological behavior under other regular traffic patterns, some of them very common in HPC applications. A recent study showed that randomization of task placement can make pathological, regular (multi-dimensional stencil) traffic patterns behave similar to uniform traffic. In this work we provide a theoretical model that is able to predict the expected performance of a generic dragonfly network under uniform traffic and characterize performance-optimal dragonflies. We then analyze whether this model can be extended to other patterns by means of benchmarking the performance of multiple such patterns under both contiguous and randomized task placement. We conclude that, although in comparison with contiguous task placement, randomization does lead to a significant improvement in performance for pathological communication patterns, this performance is not on par with that of uniform traffic, but rather half of it.
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