Fast forwarding table lookup exploiting GPU memory architecture

Youngjun Lee, M. Jeong, Sanghwan Lee, E. Im
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引用次数: 5

Abstract

As the traffic of the Internet increases and diversifies, the needs for a fast flexible router have made researchers to work on software routers. The existing software router systems may utilize the cluster structure of multiple machines or GPU systems. Especially, Packet Shader, which uses GPU to exploit GPU's extensive parallelism, shows higher performance compared to other existing software routers. However, Packet Shader does not utilize the memory architecture in the GPU system. Basically, GPU has different types of memories such as constant, texture, and global. Since different types of memories show different memory access performance, we propose a unique index architecture for the forwarding table by exploiting the memory architecture of the GPU system. Through a preliminary evaluation, we show that the forwarding table lookup using GPU can outperform the CPU only system.
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利用GPU内存架构的快速转发表查找
随着互联网流量的增加和多样化,对快速灵活的路由器的需求促使研究人员致力于软件路由器的研究。现有的软件路由器系统可采用多机集群结构或GPU系统。特别是数据包着色器,利用GPU的广泛并行性,与现有的软件路由器相比,显示出更高的性能。然而,包着色器不利用GPU系统中的内存架构。基本上,GPU有不同类型的内存,如常量、纹理和全局。由于不同类型的存储器表现出不同的存储器访问性能,我们利用GPU系统的存储器架构,提出了一种独特的转发表索引架构。通过初步的评估,我们表明使用GPU的转发表查找比仅使用CPU的系统性能更好。
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