Capturing inter-application interference on clusters
Capturing inter-application interference on clusters
复制标题
捕获集群上的应用间干扰
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
V. Voevodin
中科院分区：
文献类型：
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作者：
A. Shah;F. Wolf;S. Zhumatiy;V. Voevodin
集群系统通常同时运行多个应用程序（通常来自不同的用户），各个应用程序竞争访问共享资源（如文件系统或网络）。因此，低应用程序性能并不总是低效的程序设计的结果，而可能是由外部干扰引起的。然而，了解两者的区别对于做出适当的反应至关重要。不幸的是，传统的性能分析技术总是孤立地考虑应用程序，无法将其性能与系统执行时的整体性能条件进行比较。在本文中，我们提出了一种新的方法来关联并行运行的应用程序的性能行为。为了实现这一点，我们将应用程序运行时划分为细粒度的时间片，这些时间片的边界在整个系统中同步。将与共享资源相关的性能数据映射到这些时间片上，我们就能够建立它们跨作业使用的同时性，这可以指示应用程序间的干扰。我们的实验表明，这种干扰效应可能会显著降低应用程序的性能，而开发人员通常不会为此负责。
Cluster systems usually run several applications-often from different users-concurrently, with individual applications competing for access to shared resources such as the file system or the network. Low application performance is therefore not always the result of inefficient program design, but may instead be caused by interference from outside. However, knowing the difference is essential for an appropriate response. Unfortunately, traditional performance-analysis techniques consider an application always in isolation, without the ability to compare its performance to the overall performance conditions on the system when it was executed. In this paper, we present a novel approach of how to correlate the performance behavior of applications running side by side. To accomplish this, we divide the application runtime into fine-grained time slices whose boundaries are synchronized across the entire system. Mapping performance data related to shared resources onto these time slices, we are able to establish the simultaneity of their usage across jobs, which can be indicative of inter-application interference. Our experiments show that such interference effects, for which the developer is usually not to blame, can degrade application performance significantly.