海报:利用基于利用率的协同调度提高NUMA系统效率

Younghyun Cho, Camilo A. Celis Guzman, Bernhard Egger
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引用次数: 0

摘要

本文提出了一种在非统一内存访问(NUMA)多套接字多核平台上共定位并行应用程序的协同调度技术。该技术为运行并行应用程序分配核心资源,从而使内存控制器和CPU核心的利用率都得到最大化。利用基于排队系统的在线性能预测模型预测利用率。在运行时,会定期重新评估内核分配,并将内核重新分配给正在执行的应用程序。实验结果表明,与默认的Linux调度器和传统的基于可伸缩性的调度器相比,所提出的协同调度技术能够在更短的总执行时间内执行共存的并行应用程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
POSTER: Improving NUMA System Efficiency with a Utilization-Based Co-scheduling
This work proposes a co-scheduling technique for co-located parallel applications on Non-Uniform Memory Access (NUMA) multi-socket multi-core platforms. The technique allocates core resources for running parallel applications such that both the utilization of the memory controllers and the CPU cores are maximized. Utilization is predicted using an online performance prediction model based on queuing systems. At runtime, the core allocation is periodically re-evaluated and cores are re-assigned to executing applications. Experimental results show that the proposed co-scheduling technique is able to execute co-located parallel applications in significantly less total execution time than the default Linux scheduler and a conventional scalability-based scheduler.
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