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A novel system architecture for web scale applications using lightweight CPUs and virtualized I/O

机译:使用轻量级CPU和虚拟I / O的Web规模应用程序的新颖系统架构

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Large web-scale applications typically use a distributed platform, like clusters of commodity servers, to achieve scalable and low-cost processing. The Map-Reduce framework and its open-source implementation, Hadoop, is commonly used to program these applications. Since these applications scale well with an increased number of servers, the cluster size is an important parameter. Cluster size however is constrained by power consumption. In this paper we present a system that uses low-power CPUs to increase the cluster size in a fixed power budget. Using low-power CPUs leads to the situation where the majority of a server's power is now consumed by the I/O sub-system. To overcome this, we develop a virtualized I/O sub-system where multiple servers share I/O resources. An ASIC based high-bandwidth interconnect fabric, and FPGA based I/O cards implement this virtualized I/O. The resulting system is the first production quality implementation of cluster-in-a-box that uses low-power CPUs. The unique design demonstrates a way to build systems using low-power CPUs, allowing a much larger number of servers in a cluster in the same power envelope. To overcome software inefficiency and increase the utilization of virtualized disk bandwidth, optimizations necessary for the operating system are also discussed. We built hardware based on these ideas and experiments on this system show a 3X average improvement in performance-per-Watt-hour compared to a commodity cluster with the same power budget.
机译:大型Web规模的应用程序通常使用分布式平台(例如商品服务器集群)来实现可伸缩且低成本的处理。 Map-Reduce框架及其开源实现Hadoop通常用于对这些应用程序进行编程。由于这些应用程序可以随着服务器数量的增加而很好地扩展,因此群集大小是一个重要的参数。但是,群集大小受功耗限制。在本文中,我们介绍了一个使用低功率CPU来在固定功率预算中增加群集大小的系统。使用低功率的CPU会导致这样一种情况,即服务器的大部分功率现在都由I / O子系统消耗。为了克服这个问题,我们开发了一个虚拟化的I / O子系统,其中多个服务器共享I / O资源。基于ASIC的高带宽互连结构和基于FPGA的I / O卡实现了该虚拟化I / O。最终的系统是使用低功耗CPU的一体机集群的第一个生产质量实现。独特的设计演示了一种使用低功耗CPU构建系统的方法,该方法允许在同一功耗范围内的群集中使用大量服务器。为了克服软件效率低下和提高虚拟磁盘带宽利用率的问题,还讨论了操作系统所需的优化。我们基于这些想法构建了硬件,并在该系统上进行了实验,与具有相同功率预算的商品集群相比,每瓦时性能平均提高了3倍。

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