使用gpu每秒索引数百万个数据包

F. Fusco, M. Vlachos, X. Dimitropoulos, L. Deri
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引用次数: 43

摘要

网络流量记录器是为安全应用程序(如回顾性法医调查)记录大量网络流量的设备。当部署在高速网络上时,流量记录器必须每秒处理和存储数百万个数据包。为了能够对如此大的流量档案进行交互式探索,需要数据包索引机制。在商用硬件上以线速率(10 Gbps及以上)索引数据包,对高吞吐量索引创建提出了无与伦比的要求。这样的索引吞吐量目前在现代索引技术和当前的处理器体系结构中是无法维持的。在这项工作中,我们建议将索引智能地卸载到商品通用处理单元(gpu)上。我们介绍了在gpu上实时构建压缩位图索引的算法,并表明我们可以实现每秒高达1.85亿条记录的索引吞吐量,与最先进的技术相比,这是一个数量级的改进。这表明以多个10gbps的速率索引网络流量是完全可以实现的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Indexing million of packets per second using GPUs
Network traffic recorders are devices that record massive volumes of network traffic for security applications, like retrospective forensic investigations. When deployed over very high-speed networks, traffic recorders must process and store millions of packets per second. To enable interactive explorations of such large traffic archives, packet indexing mechanisms are required. Indexing packets at wire rates (10 Gbps and above) on commodity hardware imposes unparalleled requirements for high throughput index creation. Such indexing throughputs are presently untenable with modern indexing technologies and current processor architectures. In this work, we propose to intelligently offload indexing to commodity General Processing Units (GPUs). We introduce algorithms for building compressed bitmap indexes in real time on GPUs and show that we can achieve indexing throughputs of up to 185 millions records per second, which is an improvement by one order of magnitude compared to the state-of-the-art. This shows that indexing network traffic at multi-10-Gbps rates is well within reach.
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