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Enhancing the performance of the aggregated bit vector algorithm in network packet classification using GPU
2019
PeerJ Computer Science
Packet classification is a computationally intensive, highly parallelizable task in many advanced network systems like high-speed routers and firewalls that enable different functionalities through discriminating incoming traffic. Recently, graphics processing units (GPUs) have been exploited as efficient accelerators for parallel implementation of software classifiers. The aggregated bit vector is a highly parallelizable packet classification algorithm. In this work, first we present a
doi:10.7717/peerj-cs.185
pmid:33816838
pmcid:PMC7924471
fatcat:6rb3wqxafjghbpktcuzodp3ime