Improving Batch Scheduling on Blue Gene/Q by Relaxing Network Allocation Constraints
Z Zhou and X Yang and ZL Lan and P Rich and W Tang and V Morozov and N Desai, IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 27, 3269-3282 (2016).
As systems scale toward exascale, many resources will become increasingly constrained. While some of these resources have historically been explicitly allocated, many-such as network bandwidth, I/O bandwidth, or power-have not. As systems continue to evolve, we expect many such resources to become explicitly managed. This change will pose critical challenges to resource management and job scheduling. In this paper, we explore the potential of relaxing network allocation constraints for Blue Gene systems. Our objective is to improve the batch scheduling performance, where the partition-based interconnect architecture provides a unique opportunity to explicitly allocate network resources to jobs. This paper makes three major contributions. The first is substantial benchmarking of parallel applications, focusing on assessing application sensitivity to communication bandwidth at large scale. The second is three new scheduling schemes using relaxed network allocation and targeted at balancing individual job performance with overall system performance. The third is a comparative study of our scheduling schemes versus the existing scheduler on Mira, a 48-rack Blue Gene/Q system at Argonne National Laboratory. Specifically, we use job traces collected from this production system.
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