Issue No. 10 - Oct. (2013 vol. 62)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TC.2012.254
Cheng-Hung Lin , National Taiwan Normal University, Taipei
Chen-Hsiung Liu , National Tsing-Hua University, HsinChu
Lung-Sheng Chien , National Tsing-Hua University, HsinChu
Shih-Chieh Chang , National Tsing-Hua University, HsinChu
Graphics processing units (GPUs) have attracted a lot of attention due to their cost-effective and enormous power for massive data parallel computing. In this paper, we propose a novel parallel algorithm for exact pattern matching on GPUs. A traditional exact pattern matching algorithm matches multiple patterns simultaneously by traversing a special state machine called an Aho-Corasick machine. Considering the particular parallel architecture of GPUs, in this paper, we first propose an efficient state machine on which we perform very efficient parallel algorithms. Also, several techniques are introduced to do optimization on GPUs, including reducing global memory transactions of input buffer, reducing latency of transition table lookup, eliminating output table accesses, avoiding bank-conflict of shared memory, coalescing writes to global memory, and enhancing data transmission via peripheral component interconnect express. We evaluate the performance of the proposed algorithm using attack patterns from Snort V2.8 and input streams from DEFCON. The experimental results show that the proposed algorithm performed on NVIDIA GPUs achieves up to 143.16-Gbps throughput, 14.74 times faster than the Aho-Corasick algorithm implemented on a 3.06-GHz quad-core CPU with the OpenMP. The library of the proposed algorithm is publically accessible through Google Code.
Pattern matching, Instruction sets, Algorithm design and analysis, Graphics processing unit, Vectors, Complexity theory, Acceleration, Aho-Corasick, Graphics processing units, pattern matching, parallel algorithm
S. Chang, L. Chien, C. Liu and C. Lin, "Accelerating Pattern Matching Using a Novel Parallel Algorithm on GPUs," in IEEE Transactions on Computers, vol. 62, no. , pp. 1906-1916, 2013.