Fast and memory-efficient regular expression matching for deep packet inspection
Proceedings of the 2006 ACM/IEEE symposium on Architecture for networking and communications systems
An improved algorithm to accelerate regular expression evaluation
Proceedings of the 3rd ACM/IEEE Symposium on Architecture for networking and communications systems
iNFAnt: NFA pattern matching on GPGPU devices
ACM SIGCOMM Computer Communication Review
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Regular expression matching is a central task in several networking (and search) applications and has been accelerated on a variety of parallel architectures. All solutions are based on finite automata (either in deterministic or non-deterministic form), and mostly focus on effective memory representations for such automata. Recently, a handful of work has proposed efficient regular expression matching designs for GPUs; however, most of them aim at achieving good performance on small datasets. Nowadays, practical solutions must support the increased size and complexity of real world datasets. In this work, we explore the deployment and optimization of different GPU designs of regular expression matching engines, focusing on large datasets containing a large number of complex patterns.