University of Economics, Prague
High performance computing is becoming increasingly important in the field of financial computing, as the complexity of financial models continues to increase. Many of these financial models do not have a practical close form solution in which case numerical methods are the only alternative. Monte-Carlo simulation is one of most commonly used numerical methods, in scientific computing in general, with huge computation benefits in solving problems where close form solutions are impossible to derive. As the Monte-Carlo method relies on the average result of thousands of independent stochastic paths, massive parallelism can be adopted to accelerate the computation.