In this paper, we explore the possible approaches to harness extra computing power from commodity hardware to speedup pricing calculation of individual options. Specifically, we leverage two parallel computing platforms: Open Computing Language (OpenCL) and Compute United Device Architecture (CUDA). We propose several parallel implementations of the two most popular numerical methods of option pricing: Lattice model and Monte Carlo method. In the end, we show that the parallel implementations achieve significant performance improvement over serial implementations.