The parallelization and vectorization of Monte Carlo algorithms for modelling charge transport in semiconductor devices are considered. The standard ensemble Monte Carlo simulation of a three parabolic band model for GaAs is first presented as partial verification of the simulation. The model includes scattering due to acoustic, polar-optical and intervalley phonons. This ensemble simulation is extended to a full device simulation by the addition of real-space positions, and solution for the electrostatic potential from the charge density distribution using Poisson's equation. Poisson's equation was solved using the cloud-in-cell scheme for charge assignment, finite differences for spatial discretization, and simultaneous over-relaxation for solution. The particle movement (acceleration and scattering) and the solution of Poisson's are both separately parallelized. The parallelization techniques used in both parts are based on the use of semaphores for the protection of shared resources and processor synchronization. The speed increase results for parallelization with and without vectorization on the Ardent Titan II are presented. The results show saturation due to memory access limitations at a speed increase of approximately 3.3 times the serial case when four processors are used. Vectorization alone provides a speed increase of approximately 1.6 times when compared with the nonvectorized serial case. It is concluded that the speed increase achieved with the Titan II is limited by memory access considerations and that this limitation is likely to plague shared memory machines for the forseeable future. For the program presented here, vectorization is concluded to provide a better speed increase per day of development time than parallelization. However, when vectorization is used in conjunction with parallelization, the speed increase due to vectorization is negligible. / Graduation date: 1993