ABSTRACT

The Monte Carlo method is widely used in many areas of scientific research. From computational physics to fluid dynamics, this method has seen exponential growth with the advent of computationally powerful computers. Indeed, the Monte Carlo method is of great interest for solving systems with unknown analytical solutions. In the real world, more often than not, straightforward analytical solutions are not readily available. Hence, empirical modeling and numerical simulations are much sought to better understand the physical problems involved. While in the past such modeling and numerical simulations were not very accurate, ongoing research and advances in computational power have led to more and more sophisticated and high quality models to better approximate the physical problems. Despite that the computational power has grown exponentially over the years, this power is not able to keep up with the ever increasing demands of the improved model developed by researchers. Hence, the advent of grid systems provides the industry with a powerful tool to tap the resources offered by parallel computer networks. Such networks have theoretically a limitless amount of computational power. So far, there is a great tendency for the industry to adopt grid solutions.