缓存QoS:从概念到现实在英特尔®至强®处理器E5-2600 v3产品系列

Andrew J. Herdrich, Edwin Verplanke, Priya Autee, R. Illikkal, C. Gianos, Ronak Singhal, R. Iyer
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引用次数: 135

摘要

近十年来,解决多核服务器平台中的服务质量(QoS)问题已成为一个日益增长的研究课题。已经提出QoS技术来解决服务器中共同运行的应用程序或虚拟机之间的共享资源争用,从而提供更好的隔离、性能确定性并潜在地提高总体吞吐量。最重要的共享资源之一是缓存空间。大多数解决共享缓存争用的建议都是基于模拟和分析的,目前还没有集成这些技术并提供实用解决方案的商业平台。在本文中,我们将介绍第一组在最先进的商用服务器(Intel®Xeon®处理器E5-2600 v3产品系列)中设计和实现的共享缓存QoS技术。我们将描述两项关键技术:(i)缓存监控技术(CMT),用于监控不同应用程序的共享缓存使用情况;(ii)缓存分配技术(CAT),用于在应用程序之间重新分配共享缓存空间,以解决争用问题。这是第一篇描述这些技术从概念到现实,从早期研究到产品实现的论文。我们还将通过使用多编程工作负载、数据中心中的虚拟化平台和通信平台的示例场景展示案例研究,以突出这些技术的价值。最后,我们将描述最初的软件基础设施,并使行业从业者和研究人员能够利用这些技术满足他们的QoS需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cache QoS: From concept to reality in the Intel® Xeon® processor E5-2600 v3 product family
Over the last decade, addressing quality of service (QoS) in multi-core server platforms has been growing research topic. QoS techniques have been proposed to address the shared resource contention between co-running applications or virtual machines in servers and thereby provide better isolation, performance determinism and potentially improve overall throughput. One of the most important shared resources is cache space. Most proposals for addressing shared cache contention are based on simulations and analysis and no commercial platforms were available that integrated such techniques and provided a practical solution. In this paper, we will present the first set of shared cache QoS techniques designed and implemented in state-of-the-art commercial servers (the Intel® Xeon® processor E5-2600 v3 product family). We will describe two key technologies: (i) Cache Monitoring Technology (CMT) to enable monitoring of shared cache usage by different applications and (ii) Cache Allocation Technology (CAT) which enables redistribution of shared cache space between applications to address contention. This is the first paper to describing these techniques as they moved from concept to reality, starting from early research to product implementation. We will also present case studies highlighting the value of these techniques using example scenarios of multi-programmed workloads, virtualized platforms in datacenters and communications platforms. Finally, we will describe initial software infrastructure and enabling for industry practitioners and researchers to take advantage of these technologies for their QoS needs.
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