A fast string searching algorithm
Communications of the ACM
Efficient string matching: an aid to bibliographic search
Communications of the ACM
A String Matching Algorithm Fast on the Average
Proceedings of the 6th Colloquium, on Automata, Languages and Programming
Deep Packet Filter with Dedicated Logic and Read Only Memories
FCCM '04 Proceedings of the 12th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
Scalable Pattern Matching for High Speed Networks
FCCM '04 Proceedings of the 12th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
Snort - Lightweight Intrusion Detection for Networks
LISA '99 Proceedings of the 13th USENIX conference on System administration
Offloading IDS Computation to the GPU
ACSAC '06 Proceedings of the 22nd Annual Computer Security Applications Conference
Compiling PCRE to FPGA for accelerating SNORT IDS
Proceedings of the 3rd ACM/IEEE Symposium on Architecture for networking and communications systems
Exact multi-pattern string matching on the cell/b.e. processor
Proceedings of the 5th conference on Computing frontiers
A GPU-Based Multiple-Pattern Matching Algorithm for Network Intrusion Detection Systems
AINAW '08 Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops
Gnort: High Performance Network Intrusion Detection Using Graphics Processors
RAID '08 Proceedings of the 11th international symposium on Recent Advances in Intrusion Detection
Input-independent, scalable and fast string matching on the Cray XMT
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
GrAVity: a massively parallel antivirus engine
RAID'10 Proceedings of the 13th international conference on Recent advances in intrusion detection
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String matching is a computationally intensive procedure which poses significant challenges on current software and hardware implementations. In this paper we present an efficient implementation of the Aho-Corasick string matching algorithm on Graphic Processing Units (GPUs), showing how we progressively redesigned the algorithm and the data structures to fit on the architecture. We then evaluate the implementation on single and multiple Tesla C2050 (T20 "Fermi" based) boards, comparing them to the previous Tesla C1060 (T10 based) solutions and equivalent multi-core implementations on x86 CPUs. We discuss the various tradeoffs of the different architectures.