This Ph.D. dissertation by Aaron Lefohn at the University of California, Davis describes the Glift GPU data structure abstraction and its application to both GPU-based data-parallel and interactive rendering algorithms. The applications include octree 3D painting, adaptive shadow maps, resolution matched shadow maps, heat-diffusion depth-of-field, and a GPU-based direct solver for tridiagonal linear systems. While much of this work has been posted previously, this dissertation contains a more in-depth discussion of the Glift data structure library and introduces several GPGPU and rendering algorithms that are not yet published. This dissertation demonstrates that a data structure abstraction for GPUs can simplify the description of new and existing data structures, stimulate development of complex GPU algorithms, and perform equivalently to hand-coded implementations. The dissertation also presents a case that future interactive rendering solutions will be an inseparable mix of general-purpose, data-parallel algorithms and traditional graphics programming. (Aaron Lefohn, "Glift: Generic Data Structures for Graphics Hardware," Ph.D. dissertation, Computer Science Department, University of California Davis, September 2006.)

This Pixar Animation Studios Technical Report by Kass, Lefohn, and Owens describes a GPU-based data-parallel direct tridiagonal linear solver. To the authors' knowledge, this is the first reported direct, linear-time tridiagonal GPU solver. The solver is used to implement a new heat-diffusion-based depth-of-field preview algorithm; and the paper describes solving thousands of tridiagonal systems, each with hundreds of elements, on the GPU at interactive rendering rates. The alternating direction implicit solution gives rise to separable spatially varying recursive (infinite-impulse response, IIR) filters that can compute large-kernel convolutions in constant time per pixel while respecting the boundaries between in-focus and out-of-focus objects. Recursive filters have traditionally been viewed as problematic for GPUs, but using the well-established method of cyclic reduction of tridiagonal systems, we are able to parallelize the computation and implement an efficient solution in terms of GPGPU primitives. (Michael Kass, Aaron Lefohn, and John Owens. Interactive Depth of Field Using Simulated Diffusion on the GPU, Technical Report #06-01, Pixar Animation Studios, January 2006).

An article by David Strom in Information Week includes "Advanced Graphics Processing" in it's article "5 Disruptive Technologies To Watch in 2007", and specifically mentions GPGPU and NVIDIA CUDA. "In some cases, the new graphics cards being developed by NVIDIA and ATI (now a part of AMD) will have a bigger impact on computational processing than the latest chips from Intel and AMD.", writes Strom.