This paper presents a study of the improvement in efficiency of the Rabin-Karp pattern-matching algorithm based Deep Packet Inspection. NVIDIA GPU is programmed with the NVIDIA's general purpose parallel computing architecture, CUDA, that leverages the parallel compute engine in NVIDIA GPUs to solve many complex computational problems in a more efficient way than on a CPU. The proposed CUDA based implementation on a multicore GPU outperforms the Intel quadcore processor and runs upto 14 times faster by executing the algorithm in parallel to search for the pattern from the text. The speedup may not sound exorbitant but nonetheless is significant, keeping in view that the experiments have been conducted on real data and not synthetic data and, optimal performance even with the huge increase in traffic was the main expectation, not just an improvement in speed with few test cases.