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MICRO2020顶会

CATCAM: Constant-time Alteration Ternary CAM with Scalable In-Memory Architecture

Dibei Chen, Zhaoshi Li, Tianzhu Xiong, Zhiwei Liu, Jun Yang, Shouyi Yin, Shaojun Wei, Leibo Liu

2020年份
6被引次数
1顶会引用

摘要

TCAM (Ternary Content-Addressable Memory) is the essential component for high-speed packet classification in modern hardware switches. However, due to its relatively slow update process, recent advances in Software-Defined Network (SDN) regard them as the bottleneck to the agile deployment of network services. Rule installation in commodity switches suffers from non-deterministic delays, ranging from a few milliseconds to nearly half a second. The crux of the problem is that TCAM prioritizes rules based on physical addresses. Corresponding entries have to be reallocated according to the priority of an incoming rule, such that the insertion delay grows linearly with the number of existing rules in a TCAM. In this paper, we present Constant-time Alteration Ternary CAM (CATCAM) that can accomplish both lookup queries and update requests for packet classification in a few nanoseconds. The key to fast update is to decouple rule priorities from physical addresses. We propose a matrix-based priority encoding scheme that records the priority relation between rules and can be implemented in 8T SRAM arrays with the emerging Processing In-Memory (PIM) technique. CATCAM also comes with a hierarchical architecture to scale out, its interval-based scheduling scheme guarantees deterministic update performance in all scenarios. CATCAM is developed under full-custom design in the 28 nm process. Evaluation across benchmark workloads shows that CATCAM provides at least three orders of magnitude speedup over state-of-the-art TCAM update algorithms and offers equivalent search capability to conventional TCAM while incurring 0.3% power and 20% area overhead.

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