Kernel-level caching for optimizing I/O by exploiting inter-application data sharing

M. Vilayannur, M. Kandemir, A. Sivasubramaniam
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引用次数: 10

Abstract

With applications becoming larger and the increasing load on high performance systems, it is important to tackle the I/O bottleneck problem from several angles. It is not only essential to optimize the I/O accesses of any one application, but also to be able to identify and exploit opportunities resulting front the sharing of datasets across applications. Clusters are rapidly becoming the platform of choice for demanding applications due to their cost-effectiveness and widespread deployment. Consequently, this paper attempts to optimize data sharing across applications concurrently executing on the cluster. Specifically, we propose and implement a kernel-level caching module at each node of a Linux cluster that can be used to service several processes of different applications. Using detailed evaluations on an actual Linux cluster this paper demonstrates the benefits of this module in optimizing intra and inter-application I/O requests.
通过利用应用程序间数据共享来优化I/O的内核级缓存
随着应用程序变得越来越大,高性能系统上的负载越来越大,从几个角度解决I/O瓶颈问题非常重要。优化任何一个应用程序的I/O访问不仅至关重要,而且还必须能够识别和利用导致跨应用程序共享数据集的机会。由于具有成本效益和广泛的部署,集群正迅速成为要求苛刻的应用程序的首选平台。因此,本文试图优化在集群上并发执行的应用程序之间的数据共享。具体来说,我们在Linux集群的每个节点上提出并实现了一个内核级缓存模块,该模块可用于为不同应用程序的多个进程提供服务。通过对实际Linux集群的详细评估,本文演示了该模块在优化应用程序内部和应用程序间I/O请求方面的好处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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