TitleGlift: Generic Data Structures for Graphics Hardware (PhD Thesis)
Author(s) Aaron Lefohn
Year September 2006
SchoolComputer Science, University of California, Davis
Abstract This thesis presents Glift, an abstraction and generic template library for parallel, random-access data structures on graphics hardware. We demonstrate that a data structure abstraction for graphics processing units (GPUs) can simplify the description of new and existing data structures, stimulate development of complex GPU algorithms, and perform equivalently to hand-coded implementations. Glift defines the GPGPU computation model in terms of parallel iteration over data structure elements and demonstrates iteration over complex structures. This thesis also presents a case that future interactive rendering solutions will be an inseparable mix of general-purpose, parallel GPU programming (GPGPU) and traditional graphics programming. We describe the use of Glift in four novel interactive rendering algorithms with complex data structure and iterator requirements: octree 3D paint, adaptive shadow maps, resolution-matched shadow maps and a heat-diffusion depth-of-field algorithm.