SIMD-Matcher: A SIMD-based Arbitrary Matching Framework

Author:

Wang Ping1ORCID,Wen Fei1,Gratz Paul V.1,Sprintson Alex1

Affiliation:

1. Department of Electrical and Computer Engineering  Texas A&M University, TX, USA

Abstract

Packet classification methods rely upon matching packet content/header against pre-defined rules, which are generated by network applications and their configurations. With the rapid development of network technology and the fast-growing network applications, users seek more enhanced, secure, and diverse network services. Hence it becomes critical to improve the performance of arbitrary matching operations. This article presents SIMD-Matcher, an efficient Single Instruction Multiple Data (SIMD) and cache-friendly arbitrary matching framework. To further improve the arbitrary matching performance, SIMD-Matcher adopts a trie node with a fixed high fanout and a varying span for each node depending on the data distribution. The trie node layout leverages cache and modern processor features such as SIMD instructions. To support arbitrary matching, we first interpret arbitrary rules into three fields: value, mask, and priority. Second, to support insertion of randomly positioned wildcards to arbitrary rules, we propose the SIMD-Matcher extraction algorithm to process the wildcard bits. Third, we add an array of wildcard entries to the leaf entries, which store the wildcard rules and guarantee the correctness of matching results. Experiments show that SIMD-Matcher outperforms GenMatcher under large-scale ruleset and key set, in terms of search time, insert time, and memory cost. Specifically with 5M rules, our method achieves a 2.7X speedup on search time, and the insertion time takes \( ~\sim \!\! 7.3 \) seconds, gaining a 1.38X speedup; meanwhile, the memory cost reduction is up to 6.17X.

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Information Systems,Software

Reference33 articles.

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2. Common non-wildcard portion-based partitioning approach to SDN many-field packet classification

3. Nikolas Askitis and Ranjan Sinha. 2007. HAT-trie: A cache-conscious trie-based data structure for strings. In Proceedings of the 30th Australasian Conference on Computer Science - Volume 62 (ACSC’07). Australian Computer Society, Inc., AUS, 97–105.

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