Hardware accelerated montecarlo financial simulation over low cost FPGA cluster

The use of computational systems to help making the right investment decisions in financial markets is an open research field where multiple efforts have being carried out during the last few years. The ability of improving the assessment process and being faster than the rest of the players is one of the keys for the success on this competitive scenario. This paper explores different options to accelerate the computation of the option pricing problem (supercomputer, FPGA cluster or GPU) using the Montecarlo method to solve the Black-Scholes formula, and presents a quantitative study of their performance and scalability.