This paper by Mustafa et al. examines the use of graphics hardware as a general purpose geometry engine to compute simplification of large geographic maps in real-time. (Hardware Assisted View Dependent Map Simplification. N. Mustafa, E. Koutsofios, S. Krishnan and S. Venkatasubramanian. 17th Annual ACM Symposium on Computational Geometry, June 2001)

This paper by Guha et al., to appear in the 2003 ACM SIGGRAPH Symposium on Interactive 3D graphics, shows how the shadow mapping operation in the new NVIDIA GeForce4 cards can be viewed as a two-sided depth test in order to do CSG rendering efficiently. The result is an algorithm that can perform a topological sweep over an arrangement of objects in three dimensions. It also shows the first lower bounds on the number of rendering passes required for a hardware-assisted computation. (Application of the Two-Sided Depth Test to CSG Rendering. S. Guha, K. Munagala, S. Krishnan and S. Venkatasubramanian. To appear in the 2003 ACM SIGGRAPH Symposium on Interactive 3D graphics.)

This paper by Krishnan et al. demonstrates a large class of non-parametric statistical analysis problems that can be solved using the graphics hardware. It shows how to do duality transforms and operations in primal and dual geometric planes in a robust way using the graphics pipeline. (Hardware-Assisted Computation of Depth Contours. S. Krishnan, N. Mustafa and S. Venkatasubramanian. 13th ACM-SIAM Symposium on Discrete Algorithms).

This paper by Li et al. of SUNY Stony Brook describes the acceleration of the computation of Lattice-Boltzmann methods on graphics hardware, by grouping particle packets into 2D textures and mapping the Boltzmann equations completely to the rasterization and frame buffer operations. The LBM is then used to simulate smoke.(Implementing Lattice Boltzmann Computation on Graphics Hardware. Wei Li, Xiaoming Wei, and Arie Kaufman. To appear in The Visual Computer.)

Peter Schröder taught a course in the fall of 2002 at the California Institute of Technology called Hacking The GPU. The subject matter of the course revolved around general purpose computation. Assignments included stable fluid simulation and mesh smoothing. The course notes page has some useful links.

The GAMMA research group at UNC Chapel Hill (led by Profs. Dinesh Manocha and Ming Lin) uses GPUs for Voronoi computations, collision detection, penetration computation and collision response, motion planning, and more.

This paper describes the use of standard C++ to define a high-level shading language directly in the API. The language is nearly indistinguishable from a special-purpose shading language, yet it simplifies implementation, and permits more direct interaction with the specification of textures, parameters, and attributes. (Shader Metaprogramming. Michael D. McCool, Zheng Qin, and Tiberiu S. Popa. SIGGRAPH/Eurographics Graphics Hardware Workshop, September 2-3, 2002, Saarbruecken, Germany, pp. 57-68.)

This SIGGRAPH 2002 course, organized by Dinesh Manocha of UNC Chapel Hill, covered approaches to using graphics hardware for various geometric problems, including voronoi computation, proximity
queries, motion planning, and more.

A paper from the Journal of Graphics Tools by Ruigang Yang and Greg Welch of UNC Chapel Hill. (Fast Image Segmentation and Smoothing Using Commodity Graphics Hardware. Ruigang Yang and Greg Welch. To appear in the journal of graphics tools, special issue on “Hardware-Accelerated Rendering Techniques”, 2003.)

This Pacific Graphics 2002 paper by Ruigang Yang et al. of UNC Chapel Hill describes a GPU acclerated method for online 3D scene acquisition and view-synthesis from multiple camera streams. (Real-Time Consensus-Based Scene Reconstruction using Commodity Graphics Hardware. Ruigang Yang, Greg Welch, Gary Bishop. In Proceedings of Pacific Graphics 2002.)