Adapting Particle Filter Algorithms to the GPU Architecture

The particle filter is a Bayesian estimation technique based on Monte Carlo simulations. The non-parametric nature of particle filters makes them ideal for non-linear non-Gaussian systems. This greater filtering accuracy, however, comes at the price of increased computational complexity which limits their practical use for real-time applications...

Accelerating Computational Electromagnetic Diffraction Model on Programmable Graphics Processors

This thesis is done in the framework of wafer metrology to accelerate an electromagnetic diffraction model (EDM), which is used to measure the profile on a wafer, on programmable graphics processors (GPU). The main focus of this thesis is to investigate the suitability of EDM to GPU architectures. This study contributes with statistical data and...