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LOMARC - Lookahead Matchmaking for Multi-resource Coscheduling

机译:LOMARC-用于多资源协同调度的前瞻对接会

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Job scheduling typically focuses on the CPU with little work existing to include I/O or memory. Time-shared execution provides the chance to hide I/O and long-communication latencies though potentially creating a memory conflict. We consider two different cases: standard local CPU scheduling and coscheduling on hyperthreaded CPUs. The latter supports coscheduling without any context switches and provides additional options for CPU-internal resource sharing. We present an approach that includes all possible resources into the schedule optimization and improves utilization by coscheduling two jobs if feasible. Our LOMARC approach partially reorders the queue by lookahead to increase the potential to find good matches. In simulations based on the workload model of [12], we have obtained improvements of about 50% in both response times and relative bounded response times on hyperthreaded CPUs (i.e. cut times by half) and of about 25% on standard CPUs for our LOMARC scheduling approach.
机译:作业调度通常集中在CPU上,很少有工作要包含I / O或内存。分时执行可提供隐藏I / O和长时间通信延迟的机会,尽管这可能会造成内存冲突。我们考虑两种不同的情况:标准本地CPU调度和超线程CPU上的协同调度。后者支持无需任何上下文切换的协同调度,并为CPU内部资源共享提供了其他选项。我们提出了一种方法,该方法将所有可能的资源包括在计划优化中,并在可行的情况下通过共同计划两个作业来提高利用率。我们的LOMARC方法通过提前进行部分重新排序,以增加找到良好匹配的可能性。在基于工作负载模型[12]的仿真中,对于LOMARC,我们在超线程CPU上的响应时间和相对有限响应时间都得到了大约50%的改进(即减少了一半的时间),在标准CPU上,我们获得了大约25%的改进。调度方法。

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