Abstract:  Packet classification, which is the basic processing model of network devices, commonly uses packet filtering system to classify each message. Traditional packet classification is difficult to adapt to todays increasingly high network traffic. Its classification processing speed is lower than the speed of packet to reach the network interface, so that it cannot achieve real-time analysis. Therefore, we proposes a method that uses GPU to classify the large scale packet set parallelly. The thread-level parallel processing capability of GPU is made use to accelerate packet classification throughput. Its performance and optimization methods are analyzed in detail. The experimental results show that compared with processing by pure CPU system, GPU-accelerated Linear Search and RFC algorithm achieve a 4.4x~132.5x speedup.

Key words: GPU, CUDA, packet classification, parallel computing, optimization