| Simulation and visualization typically involve complex computations and large amount of data, hence consume huge computation power and memory bandwidth. Fortunately, most of these applications exhibit high parallelism, hence are suitable for acceleration on modern graphics hardware, that has evolved into a powerful and highly programmable graphics processing unit (GPU), composed of multi-pipelined stream processors and high memory bandwidth. In addition, while the simulation results reside directly within the graphics memory, they are easily visualized and steered without incurring expensive transfer overhead.; The first part of the thesis is concentrated on GPU accelerated simulation, that utilizes graphics hardware for non-graphics purposes. We present a GPU program development environment (GDE) for general purpose GPU application development. As a case study, we implement a GPU-based Lattice Boltzmann Model, a physically based method for fluid simulation supporting complex boundary conditions. With GPU-specific optimizations, the simulation runs an order of magnitude faster than the CPU version with the same accuracy. We also develop several applications involving amorphous phenomena based on the accelerated simulation.; To visualize the simulation results, which are usually represented as volumetric datasets, texture-based volume rendering is employed. Traditional texture-based volume rendering unnecessarily processes all the voxels. It is unnecessary, since a large amount of voxels are invisible, either due to the transfer function or occlusion by other voxels. The second part of the thesis is focused on accelerating the volume visualization on GPUs by skipping the invisible voxels, without any loss of image quality. |
