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Parallel Job Scheduling in Homogeneous Distributed Systems

机译:异构分布式系统中的并行作业调度

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The performance of parallel programs such as those involving fork-join instructions is significantly affected by the method used to schedule program tasks. This article studies parallel job scheduling in homogeneous distributed systems. A simulation model is used to address performance issues associated with scheduling. Various policies are employed to schedule parallel jobs over a variety of workloads. Fairness is required among competing jobs. The authors examine cases in which the distribution of the number of parallel tasks per job, as well as the distribution of task service demand, varies with time. They also examine the impact of overhead necessary to collect global system information about processor queues on performance. Simulated results indicate that although all scheduling methods have merit, one significantly improves the overall performance and guarantees fairness in terms of individual job execution.
机译:诸如涉及fork-join指令的并行程序的性能受计划程序任务的方法影响很大。本文研究同类分布式系统中的并行作业调度。仿真模型用于解决与调度相关的性能问题。采用了各种策略来调度各种工作负载上的并行作业。竞争性工作之间需要公平。作者研究了每个作业并行任务数量的分布以及任务服务需求的分布随时间变化的情况。他们还检查了收集有关处理器队列的全局系统信息所需的开销对性能的影响。仿真结果表明,尽管所有调度方法都有其优点,但一种方法可以显着提高整体性能,并保证个人作业的公平性。

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