Field-split parallel architecture for high performance multi-match packet classification using FPGAs

  • Authors:
  • Weirong Jiang;Viktor K. Prasanna

  • Affiliations:
  • University of Southern California, Los Angeles, CA, USA;University of Southern California, Los Angeles, CA, USA

  • Venue:
  • Proceedings of the twenty-first annual symposium on Parallelism in algorithms and architectures
  • Year:
  • 2009

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Abstract

Multi-match packet classification is a critical function in network intrusion detection systems (NIDS), where all matching rules for a packet need to be reported. Most of the previous work is based on ternary content addressable memories (TCAMs) which are expensive and are not scalable with respect to clock rate, power consumption, and circuit area. This paper studies the characteristics of real-life Snort NIDS rule sets, and proposes a novel SRAM-based architecture. The proposed architecture is called field-split parallel bit vector (FSBV) where some header fields of a packet are further split into bit-level subfields. Unlike previous multi-match packet classification algorithms which suffer from memory explosion, the memory requirement of FSBV is linear in the number of rules. FPGA technology is exploited to provide high throughput and to support dynamic updates. Implementation results show that our architecture can store on a single Xilinx Virtex-5 FPGA the full set of packet header rules extracted from the latest Snort NIDS and sustains 100 Gbps throughput for minimum size (40 bytes) packets. The design achieves 1.25× improvement in throughput while the power consumption is approximately one fourth that of the state-of-the-art solutions.