This paper discusses the implementation and performance of a parallel algorithm for pricing discrete Asian options. Using a partial differential equation (PDE) based method, one attempts to solve simultaneously many PDEs on a Cartesian grid in the direction of underlying asset S then followed by an interpolation in the orthogonal direction A - average of the underlying - at each time step. This leads one to consider algorithms to perform such calculations in parallel. The interpolation is non-local, thus it requires a global data access to A. This requires that an efficient parallel implementation must minimize the cost of data movement among processes. We describe in this paper three implementations: one using message passing interface (MPI), one using OpenMP and one using POSIX threads through a high level FORTRAN API. We then discuss the performances of these three implementations on different platforms.