GPU Volume Voxelization : Exploration of the performance characteristics of different GPU-based implementations

Sammanfattning: In recent years, voxel-based modelling has seen a reintroduction to computer game development through massive graphics hardware improvements. Never- theless, polygons continue to be the default building block of 3D objects, intro- ducing a need for the transformation of polygon meshes into voxel-based models; this process is known as voxelization. Efficient voxelization algorithms take ad- vantage of the flexibility and control offered by modern, programmable GPU pipelines. However, the variability in possible approaches poses the question of how different GPU-based implementations affect voxelization performance.This thesis explores the impact of GPU-based improvements by comparing four different implementations of a solid voxelization algorithm. The implemen- tations include a naive transition from the CPU to the GPU, a non-branching execution path approach, data pre-processing, and a combination of the two previous approaches. Benchmarking experiments run on four, standard polygo- nal models and three graphics cards (NVIDIA and AMD) provide runtime and memory usage data for each implementation. A comparative analysis is per- formed on the basis of this data to determine the performance impact of the GPU-based adjustments to the voxelization algorithm implementation.Results indicate that the non-branching execution path approach yields clear improvements over the naive implementation, while data pre-processing has in- consistent performance and a large initial performance cost; the combination of the two improvements unsurprisingly leads to combined results. Therefore, the conclusive recommendation is using the non-branching execution path technique for GPU-based improvements.