SwitchAgg：迈向网内计算的又一步
SwitchAgg:A Further Step Towards In-Network Computation
摘要：
许多分布式应用程序采用分区/聚合模式来实现高性能和可伸缩性。聚合过程通常占用整个执行时间的很大一部分，导致大量的网络流量和系统性能的瓶颈。为了减少网络流量，一些研究利用网络设备进行网络聚合。然而，这些方法要么使用特殊的拓扑结构或中间盒，这不能很容易地部署在当前的网络中心。可编程RMT交换机的出现为实现网内计算任务带来了新的机遇。然而，我们认为，RMT交换机的体系结构是不适合在网络聚合，因为它主要是为了实现传统的网络功能。本文首先对网内聚合进行了详细的分析，指出了影响数据精简率的关键因素。然后，我们提出了SwitchAgg，这是一个innetwork聚合系统，与当前的数据中心基础设施兼容。我们还评估了我们从SwitchAgg获得的性能改进。实验结果表明，SwitchAgg能够以线速处理数据聚合任务，并具有较高的数据缩减率，从而减少了网络流量，减轻了服务器CPU的压力。在系统性能测试中，作业完成时间可减少50%
英文摘要：
Many distributed applications adopt a partition/aggregation pattern to achieve high performance and scalability. The aggregation process, which usually takes a large portion of the overall execution time, incurs large amount of network traffic and bottlenecks the system performance. To reduce network traffic,some researches take advantage of network devices to commit innetwork aggregation. However, these approaches use either special topology or middle-boxes, which cannot be easily deployed in current datacenters. The emerging programmable RMT switch brings us new opportunities to implement in-network computation task. However, we argue that the architecture of RMT switch is not suitable for in-network aggregation since it is designed primarily for implementing traditional network functions. In this paper, we first give a detailed analysis of in-network aggregation, and point out the key factor that affects the data reduction ratio. We then propose SwitchAgg, which is an innetwork aggregation system that is compatible with current datacenter infrastructures. We also evaluate the performance improvement we have gained from SwitchAgg. Our results show that, SwitchAgg can process data aggregation tasks at line rate and gives a high data reduction rate, which helps us to cut down network traffic and alleviate pressure on server CPU. In the system performance test, the job-completion-time can be reduced as much as 50%
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
