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Effects of Topology-Aware Allocation Policies on Scheduling Performance

机译：拓扑感知分配策略对调度性能的影响

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This paper studies the influence that job placement may have on scheduling performance, in the context of massively parallel computing systems. A simulation-based performance study is carried out, using workloads extracted from real systems logs. The starting point is a parallel system built around a k-ary n-tree network and using well-known scheduling algorithms (FCFS and backfilling). We incorporate an allocation policy that tries to assign to each job a contiguous network partition, in order to improve communication performance. This policy results in severe scheduling inefficiency due to increased system fragmentation. A relaxed version of it, which we call quasi-contiguous allocation, reduces this adverse effect. Experiments show that, in those cases where the exploitation of communication locality results in an effective reduction of application execution time, the achieved gains more than compensate the scheduling inefficiency, therefore resulting in better overall performance.
机译：在大规模并行计算系统的背景下，本文研究了工作安排可能对调度性能的影响。使用从真实系统日志中提取的工作负载，进行了基于仿真的性能研究。起点是围绕k元n-树网络并使用众所周知的调度算法（FCFS和回填）构建的并行系统。我们采用了一种分配策略，该策略试图为每个作业分配一个连续的网络分区，以提高通信性能。由于增加了系统碎片，此策略导致严重的调度效率低下。它的宽松版本（我们称为准连续分配）可以减少这种不利影响。实验表明，在那些利用通信局部性导致有效减少应用程序执行时间的情况下，所获得的收益超过了对调度效率低下的补偿，因此可以带来更好的整体性能。

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