SCOJO的自适应时间/空间共享

A. Sodan, Xuemin Huang
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引用次数: 14

摘要

众所周知,通过组调度分时执行并行作业比空间共享产生更好的平均响应时间。我们采用自适应CPU/节点资源分配来考虑不同的系统负载并减少碎片。作为主要的创新,我们的SCOJO方法提供了一个清晰的模型,如何适应,并考虑到现实的工作混合,可塑,可塑和刚性的工作。我们的自适应SCOJO显著降低了响应时间和平均慢速,同时使用比标准组调度更低的多路编程级别,从而降低了内存压力。尽管实际的工作组合限制了资源分配的灵活性,但这些好处仍然适用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive time/space sharing with SCOJO
Time-shared execution of parallel jobs via gang scheduling is known to yield better average response times than space sharing. We incorporate adaptive CPU/node-resource allocation to consider varying system load and to reduce fragmentation. As main innovations, our SCOJO approach provides a clear model how to adapt, and considers realistic job mixes with moldable, malleable and rigid jobs. Our adaptive SCOJO significantly decreases response times and average slowdowns, while using a lower multiprogramming level than standard gang scheduling uses best and, therefore, decreasing the memory pressure. These benefits apply though the realistic job mixes limit the flexibility in resource allocation.
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