We consider the problem of distilling efficient network topologies for collective communications. We provide an algorithmic framework for constructing direct-connect topologies optimized for the latency vs. bandwidth trade-off associated with the workload. Our approach synthesizes many different topologies and schedules for a given cluster size and degree and then identifies the appropriate topology and schedule for a given workload. Our algorithms start from small, optimal base topologies and associated communication schedules and use techniques that can be iteratively applied to derive much larger topologies and schedules. Additionally, we incorporate well-studied large-scale graph topologies into our algorithmic framework by producing efficient collective schedules for them using a novel polynomial-time algorithm. Our evaluation uses multiple testbeds and large-scale simulations to demonstrate significant performance benefits from our derived topologies and schedules.

翻译：我们研究了为集体通信提炼高效网络拓扑结构的问题。我们提供了一个算法框架，用于构建针对工作负载相关的延迟与带宽权衡进行优化的直连拓扑结构。我们的方法针对给定的集群规模和度数，综合多种不同的拓扑结构和调度方案，然后为给定的工作负载确定合适的拓扑结构和调度方案。我们的算法从最优的小型基础拓扑结构及其相关的通信调度方案开始，并利用可迭代应用的技术来导出更大的拓扑结构和调度方案。此外，我们通过一种新颖的多项式时间算法为它们生成高效的集体调度方案，从而将经过充分研究的大规模图拓扑结构纳入我们的算法框架。我们的评估使用多个测试平台和大规模模拟，证明了我们从导出的拓扑结构和调度方案中获得的显著性能优势。