TCAM-Hash:用于网络应用的组合路由查找

2023 5th International Conference on Electronic Engineering and Informatics (EEI) Pub Date : 2023-06-30 DOI:10.1109/EEI59236.2023.10212979

Keran Zhang, Wenjun Huang, Nailiang Kuang, Sheng Zhong, Yong Liang, Hangzai Luo

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引用次数: 0

摘要

延迟和资源消耗是网络应用程序中路由查找(RL)的重要因素。本文提出了一种综合了基于TCAM和基于哈希的强化学习的优点的组合强化学习策略(TCAM- hash)。哈希模块解决了90%以上的网络规则的RL问题。TCAM模块解决了其他规则的RL。在FPGA实验中，哈希模块支持宽输入规则(144位)的RL，实现了非常低的延迟(12.8 ns)，并且花费非常有限的FPGA资源(2.5 BRAM和664 LUT)。

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TCAM-Hash: A Combined Routing Lookup for Network Applications

The latency and resource consumption are significant factors for routing lookup (RL) in network applications. This paper proposes a combined RL strategy (TCAM-Hash), which utilizes the advantages of both TCAM- based and hash-based RL. The hash module solves the RL for over 90% of network rules. The TCAM module solves the RL for the rest rules. In the FPGA experiment, the hash module supports the RL for wide input rules (144-bit), achieves very low latency (12.8 ns), and costs very limited FPGA resources (2.5 BRAM and 664 LUT).

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2023 5th International Conference on Electronic Engineering and Informatics (EEI)

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