Coherence-based Analysis of GPU-assisted Ray Tracing Acceleration Structures

• Main Authors: Shih-hsuan Hsu, 徐士璿
• Other Authors: Yung-Yu Chuang
• Format: Others
• Language: en_US
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/10166987878080873991

碩士 === 國立臺灣大學 === 資訊工程學研究所 === 94 === With the rapidly increasing processing power and the growing of the levels of the programmability of graphics processing units (GPUs), GPUs have become popular platforms for doing lots of computation-intensive jobs. However, while transferring programs from CPUs to GPUs, many issues have to be taken into consideration to make the programs execute efficiently on GPU''s SIMD architecture. In this thesis, we put our focus on three acceleration structures for the GPU ray tracing algorithm: uniform grid, KD-tree, and bounding volume hierarchies. The concepts about how to do the general purpose computations on GPUs (GPGPU) and the techniques used in the GPGPU programming are introduced first. Then we give the details about the construction of these acceleration structures and how to do the traversal with GPU implementations. Afterward, we discuss the performance differences among them from the coherence''s point of view. Experiments about the control coherence and the data coherence, such as texture fetching patterns, ray order while doing traversing, the looping limit of a shader, and the hardware-assisted z-culling, are performed to reveal the distinct characteristics of different structures. By observing the results of these coherencebased experiments, we get better understandings about the underlying GPU architecture and have more insights about how to maximize the capabilities of GPUs to increase the performance of the ray tracing algorithm.