At SIGGRAPH in Boston, Derek Gerstmann of ATI presented a sketch titled, "A Performance-Oriented Data Parallel Virtual Machine for GPGPU Applications." The system exposes GPU functionality at a low-level (including the fragment processors' native instruction set), giving the programmer direct control over program compilation and loading, GPU memory management, and GPU/CPU synchronization. A write-up is available at www.ati.com/developer. If you are interested in obtaining the system for evaluation, please contact researcher@ati.com.

Using unevaluated sums of paired or quadrupled single-precision (f32) values, double-float (df64) and quad-float (qf128) numeric types can be implemented on current GPUs and used efficiently and effectively for extended-precision computation for real and complex arithmetic. These numeric types provide 48 and 96 bits of precision respectively at f32 exponent ranges for computer raphics and general purpose (GPGPU) programming. Double- and quad-floats may be useful not only for extending available precision but also for accurate computation by only partially IEEE compliant single-precision floats. The poster and demos presented at ACM SIGGRAPH 06 discussed the implementation and application of these numbers in the Cg language for real and complex GPU programming. The df64 library includes math routines for exponential, log, and trigonometric functions. The poster can be downloaded from Andrew Thall's website. Technical details will be available shortly, and the code itself will be made available for distribution given sufficient interest.

This SIGGRAPH poster by Oliver Fluck et al. presents an approach to computing histograms in fragment shaders. The proposed method enables iterative and histogram-guided algorithms to run on GPUs and avoids data transfer between the GPU and main memory. The algorithm has been demonstrated using the example of a GPU level set segmentation. (GPU Histogram Computation)

GPU_KLT is an implementation (using OpenGL/Cg) of the popular KLT feature tracker which runs primarily on the graphics processing unit (GPU). The GPU-based implementation emulates Stan Birchfield's KLT implementation of the original algorithm proposed by Kanade, Lucas and Tomasi (1991). GPU_KLT tracks approximately 1000 feature points within 1024x768 resolution video at 30 Hz on an ATI 1900 XT and at 25 Hz on a Nvidia Geforce 7900 GTX. It can be used for real-time computer vision systems involving object detection, structure from motion, robot navigation and video surveillance. Source code is available for research use on our webpage. ( GPU_KLT webpage Sudipta N Sinha, Jan-Michael Frahm, Marc Pollefeys and Yakup Genc, "Feature Tracking and Matching in Video Using Programmable Graphics Hardware", submitted to Machine Vision and Applications, July 2006.)

This paper by Savage, Searle and myself describes a program which uses the built in support for 4-vector/matrix operations on a programmable GPU to perform Lorentz transformations on relativistic 4-momentum vectors in real time. This allows a pixel shader to render relativistic effects such as Geometric Aberration, Doppler shift and the Headlight effect in response to user's interaction. A program, "Real-Time Relativity", has been written to demonstrate these effects. ( Real-Time Relativity C. M. Savage, A. C. Searle, L. McCalman. Physics ArXiv )

The Ph.D. dissertation Rendering Methods for Augmented Reality by Jan Fischer describes several GPU-based methods for artistic and illustrative rendering. A real-time video filter is described, which generates a cartoon-like version of the input video and is executed entirely on the GPU (Section 3.3). Section 4.2 of the thesis discusses a GPU-based algorithm for the real-time illustrative display of hidden structures in polygonal datasets. In Section 4.3, the real-time conversion of augmented reality video streams into an illustrative style on the GPU is described. The thesis discusses the underlying image processing and rendering algorithms as well as implementation-specific aspects of the respective GPU techniques. (Jan Fischer, Rendering Methods for Augmented Reality, Dissertation, University of Tübingen, June 2006)