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International Journal of Reconfigurable Computing
Volume 2013, Article ID 681894, 33 pages
Research Article

Hardware Accelerators Targeting a Novel Group Based Packet Classification Algorithm

School of Engineering and Computer Science, University of Guelph, Guelph, ON, Canada N1G 2W1

Received 10 December 2012; Revised 26 February 2013; Accepted 26 February 2013

Academic Editor: Michael Hübner

Copyright © 2013 O. Ahmed et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Packet classification is a ubiquitous and key building block for many critical network devices. However, it remains as one of the main bottlenecks faced when designing fast network devices. In this paper, we propose a novel Group Based Search packet classification Algorithm (GBSA) that is scalable, fast, and efficient. GBSA consumes an average of 0.4 megabytes of memory for a 10 k rule set. The worst-case classification time per packet is 2 microseconds, and the preprocessing speed is 3 M rules/second based on an Xeon processor operating at 3.4 GHz. When compared with other state-of-the-art classification techniques, the results showed that GBSA outperforms the competition with respect to speed, memory usage, and processing time. Moreover, GBSA is amenable to implementation in hardware. Three different hardware implementations are also presented in this paper including an Application Specific Instruction Set Processor (ASIP) implementation and two pure Register-Transfer Level (RTL) implementations based on Impulse-C and Handel-C flows, respectively. Speedups achieved with these hardware accelerators ranged from 9x to 18x compared with a pure software implementation running on an Xeon processor.