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Design of network topology aware scheduling services for large InfiniBand clusters

机译:大型InfiniBand集群的网络拓扑感知调度服务设计

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The goal of any scheduler is to satisfy user's demands for computation and achieve a good performance in overall system utilization by efficiently assigning jobs to resources. However, the current state-of-the-art scheduling techniques do not intelligently balance node allocation based on the total bandwidth available between switches - that leads to over subscription. Additionally, poor placement of processes can lead to network congestion and poor performance. In this paper, we explore the design of a network-topology-aware plugin for the SLURM job scheduler for modern InfiniBand-based clusters. We present designs to enhance the performance of applications with varying communication characteristics. Through our techniques, we are able to considerably reduce the amount of network contention observed during the Alltoall / FFT operations. The results of our experimental evaluation indicate that our proposed technique is able to deliver up to a 9% improvement in the communication time of P3DFFT at 512 processes. We also see that our techniques are able to increase the performance of microbenchmarks that rely on point-to-point operations up to 40% for all message sizes. Our techniques were also able to improve the throughput of a 512-core cluster by up to 8%.
机译:任何调度程序的目标都是通过有效地将作业分配给资源来满足用户的计算需求,并在整体系统利用率方面达到良好的性能。但是,当前最新的调度技术不能基于交换机之间可用的总带宽来智能地平衡节点分配,这会导致超额预订。此外,不良的流程放置可能导致网络拥塞和性能下降。在本文中,我们探索了用于基于InfiniBand的现代集群的SLURM作业调度程序的网络拓扑感知插件的设计。我们提出了各种设计,以增强具有各种通信特性的应用程序的性能。通过我们的技术,我们能够大大减少Alltoall / FFT操作期间观察到的网络争用量。我们的实验评估结果表明,我们提出的技术能够在512个进程中将P3DFFT的通信时间提高9%。我们还看到,我们的技术能够将依赖点对点操作的微基准的性能提高到所有消息大小的40%。我们的技术还能够将512核群集的吞吐量提高多达8%。

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