GPU option pricing

Abstract

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.