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首页> 外文期刊>Parallel and Distributed Systems, IEEE Transactions on >Synchronization-Aware Scheduling for Virtual Clusters in Cloud
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Synchronization-Aware Scheduling for Virtual Clusters in Cloud

机译:云中虚拟集群的同步感知调度

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摘要

Due to high flexibility and cost-effectiveness, cloud computing is increasingly being explored as an alternative to local clusters by academic and commercial users. Recent research already confirmed the feasibility of running tightly-coupled parallel applications with virtual clusters. However, such types of applications suffer from significant performance degradation, especially as the overcommitment is common in cloud. That is, the number of executable Virtual CPUs (VCPUs) is often larger than that of available Physical CPUs (PCPUs) in the system. The performance degradation is mainly due to the fact that the current virtual machine monitors (VMMs) are unaware of the synchronization requirements of the VMs which are running parallel applications. In this paper, There are two key contributions. (1) We propose an autonomous synchronization-aware VM scheduling (SVS) algorithm, which can effectively mitigate the performance degradation of tightly-coupled parallel applications running atop them in overcommitted situation. (2) We integrate the SVS algorithm into Xen VMM scheduler, and rigorously implement a prototype. We evaluate our design on a real cluster environment with NPB benchmark and real-world trace. Experiments show that our solution attains better performance for tightly-coupled parallel applications than the state-of-the-art approaches like Xen’s Credit scheduler, balance scheduling, and hybrid scheduling.
机译:由于高度的灵活性和成本效益,学术和商业用户越来越多地探索云计算作为本地集群的替代方案。最近的研究已经证实了使用虚拟集群运行紧密耦合的并行应用程序的可行性。但是,此类应用程序的性能会显着下降,尤其是在云中普遍存在过量使用情况。即,可执行虚拟CPU(VCPU)的数量通常大于系统中可用物理CPU(PCPU)的数量。性能下降的主要原因是当前的虚拟机监视器(VMM)不了解运行并行应用程序的VM的同步要求。在本文中,有两个主要贡献。 (1)我们提出了一种自主的同步感知VM调度(SVS)算法,该算法可以有效地缓解在过载情况下运行在其上的紧密耦合并行应用程序的性能下降。 (2)我们将SVS算法集成到Xen VMM调度程序中,并严格实现了原型。我们在具有NPB基准和实际跟踪的真实集群环境中评估我们的设计。实验表明,与紧密结合的并行应用程序相比,我们的解决方案具有比Xen的Credit计划程序,余额计划和混合计划等最新方法更好的性能。

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