面向电信级通用节点

T. Korikawa, Akio Kawabata, A. Masuda
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引用次数: 0

摘要

在本文中,我们阐明了实现数据包处理的主要性能瓶颈,这些数据包处理需要在通用服务器上查找运营商规模的大表(运营商规模的数据包处理)。我们使用基于DPDK-Click的数据包处理模型进行了实验定量分析,结果表明,随着输入流量的增加,CPU缓存缺失的增加是导致运营商规模数据包处理性能下降的主要原因。这表明使用通用硬件的运营商规模数据包处理的主要性能瓶颈是缺乏内存响应性能。作为瓶颈的解决方案,我们提出了一种新的服务器架构,利用混合内存立方体(HMC),一种3d堆叠的DRAM,以增强并发性方面的内存响应性能。我们基于仿真的评估表明,我们提出的服务器架构可以在没有任何专用硬件的情况下实现超过40 Gbps的载波规模数据包处理。我们的工作表明,增强内存响应的并发性与多核CPU上的并行处理一样重要,可以提高使用通用硬件的载波级数据包处理的系统级性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Toward carrier-scale general-purpose node
In this paper, we elucidate the main performance bottleneck in realizing packet processing which require carrier-scale huge tables to lookup (carrier-scale packet processing) on top of general-purpose servers. Our experimental quantitative analysis using DPDK-Click based packet processing model reveals that performance degradation of the carrier-scale packet processing is mainly caused by increased CPU cache misses with increasing number of input traffic flows. This indicates that the main performance bottleneck of carrier-scale packet processing using general-purpose hardware is the lack of memory response performance. As a solution to the bottleneck, we propose novel server architecture that utilizes Hybrid Memory Cube (HMC), a sort of 3D-stacked DRAM, to reinforce memory response performance in terms of concurrency. Our simulation based evaluation shows that our proposed server architecture can realize more than 40 Gbps carrier-scale packet processing without any dedicated hardware. Our work shows that augmented concurrency of memory response is as important as parallel processing at multi-core CPU to improve the system level performance of carrier-scale packet processing using general-purpose hardware.
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