GPU packet classification using OpenCL: a consideration of viable classification methods

Authors:
Alastair Nottingham;Barry Irwin
Affiliations:
Rhodes University, Grahamstown, South Africa;Rhodes University, Grahamstown, South Africa
Venue:
Proceedings of the 2009 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists
Year:
2009

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Abstract

Packet analysis is an important aspect of network security, which typically relies on a flexible packet filtering system to extrapolate important packet information from each processed packet. Packet analysis is a computationally intensive, highly parallelisable task, and as such, classification of large packet sets, such as those collected by a network telescope, can require significant processing time. We wish to improve upon this, through parallel classification on a GPU. In this paper, we first consider the OpenCL architecture and its applicability to packet analysis. We then introduce a number of packet demultiplexing and routing algorithms, and finally present a discussion on how some of these techniques may be leveraged within a GPGPU context to improve packet classification speeds.