A Hybrid Parallel Signature Matching Model for Network Security Applications Using SIMD GPU.

High performance signature matching against a large dictionary is of great importance in network security applications. The many-core SIMD GPU is a competitive choice for signature matching. In this paper, a hybrid parallel signature matching model (HPSMM) using SIMD GPU is proposed, which uses pattern set partition and input text partition together. Then the problem of load balancing for multiprocessors in the GPU is discussed carefully, and a balanced pattern set partition method (BPSPM) employed in HPSMM is introduced. Experiments demonstrate that using pattern set partition and input text partition together can help achieve a better performance, and the proposed BPSPM-Length works well in load balancing. [ABSTRACT FROM AUTHOR]