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基于CUDA的多模式匹配技术 被引量:2

Multi-pattern Matching Technology Based on CUDA
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摘要 文章以经典的多模式匹配算法—AC算法为例,通过对CUDA特性的分析,提出了基于CUDA的并行模型,设计了适合CUDA并行技术的AC匹配算法。实验结果表明,基于CUDA的AC匹配算法较CPU上获得了22倍的加速比,有效提高了入侵检测系统的性能。 By analyzing the characteristic of CUDA, a parallel module of AC matching algorithm based on CUDA is proposed. Experiment shows that the AC multi-pattern matching algorithm based on GPU gets 22 times speedup ratio than it based on CPU, and it improves the performance of intrusion detection system effectively.
出处 《信息网络安全》 2011年第9期126-128,共3页 Netinfo Security
关键词 CUDA 并行技术 多模式匹配 AC算法 CUDA parallel technology multi-pattern matching AC algorithm
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参考文献7

  • 1Martin Roesh Sonort. Snort-Light Weight Intrusion Detection for Networks[C]. Proceeding of LISA'99:13th Systems Adminstration corference. Washington, 1999. 299-238.
  • 2李伟男,鄂跃鹏,葛敬国,钱华林.多模式匹配算法及硬件实现[J].软件学报,2006,17(12):2403-2415. 被引量:42
  • 3HUANGNEN FU, HUNG HSIEN-WEI, LAI SHENG-HUANG, et. A GPU-based multiple-pattern matching algorithm for network intrusion detection systems[C]. Proceedings of the 22nd International Conference on Advanced Information Networking and Apphcations Workshops. Washington, DC:IEEE Computer Society, 2008.62-67.
  • 4张庆丹,戴正华,冯圣中,孙凝晖.基于GPU的串匹配算法研究[J].计算机应用,2006,26(7):1735-1737. 被引量:15
  • 5唐定车,刘任任,谭建龙.基于统一计算设备架构的并行串匹配算法[J].计算机应用,2009,29(B06):399-401. 被引量:3
  • 6JACOB N, BRODLEY C. Offloading IDS computation to the GPUIC]. 22dn Annual Computer Security Applications Conference: ACSAC. Washington, DC:IEEE Press, 2006. 371-380.
  • 7NVidia Corporation. NVidia CUDA Compute Unified Device Architecture programming guide, V3.2[EB/OL]. http:// developer,download.nvidia.com/compute/cuda/3.0/toolkit/docs/ NVIDIA_CUDA_Programming Guide.pdf, 2010-02-20/2011-06-14.

二级参考文献12

  • 1吴恩华,柳有权.基于图形处理器(GPU)的通用计算[J].计算机辅助设计与图形学学报,2004,16(5):601-612. 被引量:226
  • 2陈国良,林洁,顾乃杰.分布式存储的并行串匹配算法的设计与分析[J].软件学报,2000,11(6):771-778. 被引量:10
  • 3张庆丹,戴正华,冯圣中,孙凝晖.基于GPU的串匹配算法研究[J].计算机应用,2006,26(7):1735-1737. 被引量:15
  • 4JOWENS JD, LUEBKE D, GOVINDARAJU N, et al. A survey of general-purpose computation on graphics hardware [ A]. EUROGRAPHICS 2005[ C].2005.21 -51.
  • 5MARK WR, GLANVILLE RS, AKELEY K, et al. Cg: a system for programming graphics hardware in a C-like language[J]. ACM Transactions on Graphics, 2003, 22(3) : 896 -907.
  • 6LEFOHN A, KNISS J, OWENS J. Implementing efficient parallel data structures on GPUs[ A]. GPU gems 2: programming techniques for high performance graphics and general purpose computation[ C].Addison-Wesley, 2005. 521 -545.
  • 7HARRIS M. Mapping computational concepts to GPUs[ A]. GPUGems2: programming techniques for high performance graphics and general purpose computation[ C]. Addison-Wesley, 2006.493 -508.
  • 8THOMPSON CJ, HAHN S, OSKIN M. Using modem graphics architectures for general-purpose computing: a framework and analysis[A]. Proceedings of the 35th Annual ACM/IEEE International Symposium on Microarchitecture[C].2002. 306 -317.
  • 9BUCK I, FOLEY T, HORN D, et al. Brook for GPUs: stream computing on graphics hardware[ A]. Proceedings of the ACM SIGGRAPH 2004[C].2004.
  • 10BUCK I. GPGPU: General-purpose computation on graphics hardware-GPU computation strategies & tricks[ A]. ACM SIGGRAPH Course Notes[C].2004.

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