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An Evaluation of the Benefits of Fine-Grained Value-Based Scheduling on General Purpose Clusters

机译:通用集群上基于细粒度值的计划的收益评估

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General purpose compute clusters fulfill a prominent role in a wide range of organizations to deliver the necessary computational power for their processes. In order to manage the shared use of such clusters, scheduling policies are installed to determine if and when the jobs submitted to the cluster are executed. Value-based scheduling policies differ from other policies in that they allow users to communicate the value of their computation to the scheduling mechanism. The design of market mechanisms whereby users are able to bid for resources in a fine-grained manner has proven to be an attractive means to implement such policies. In the clearing phase of the mechanism, supply and demand for resources are matched in pursuit of a value-maximizing job schedule and resource prices are dynamically adjusted to the level of excess demand in the system. Despite their success in simulations and research literature, such fine-grained value-based scheduling policies have been rarely used in practice as they are often considered too fragile, too onerous for end-users to work with, and difficult to implement. A coarse-grained form of value-based scheduling that mitigates aformentioned disadvantages involves the installation of a priority queueing system with fixed costs per queue. At present, it is however unclear to which extent a fine-grained form of value-based scheduling through auctions can outperform such a priority queueing system. Using workload traces of a general purpose cluster, we indicate under which conditions this is the case and quantify the resulting efficiency gains.
机译:通用计算集群在众多组织中扮演着重要角色,为他们的流程提供必要的计算能力。为了管理此类集群的共享使用,安装了调度策略以确定是否以及何时执行提交给集群的作业。基于值的调度策略与其他策略的不同之处在于,它们允许用户将其计算值传达给调度机制。设计市场机制,使用户能够以细粒度的方式竞标资源,这已被证明是实施此类政策的一种有吸引力的手段。在该机制的清理阶段,为了实现价值最大化的工作计划,对资源的供需进行匹配,并且将资源价格动态调整到系统中过量需求的水平。尽管基于粒度的基于值的细粒度调度策略在模拟和研究文献中取得了成功,但由于它们通常被认为过于脆弱,对于最终用户而言过于繁琐且难以实施,因此在实践中很少使用。一种基于价值的调度的粗粒度形式,可以缓解上述缺点,其中包括安装优先级排队系统,每个队列固定成本。但是,目前尚不清楚通过拍卖进行的基于价值的计划的细粒度形式在何种程度上可以胜过这种优先级排队系统。通过使用通用集群的工作负载跟踪,我们可以指出在哪种条件下会发生这种情况,并量化由此带来的效率提升。

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