Excerpted from GPU Gems 2, “The GeForce 6 Series GPU Architecture” (Chapter 30) describes the architecture of the GeForce 6 Series family of GPUs, including details on the overall system architecture, vertex processor, fragment processor, and various other features. (Emmett Kilgariff and Randima Fernando. “The GeForce 6 Series GPU Architecture”, in GPU Gems 2, Addison-Wesley 2005.)

Efficient and visually compelling reproduction of effects due to multiple scattering in participating media remains one of the most difficult tasks in computer graphics. Although several fast techniques were recently developed, most of them work only for special types of media (for example, uniform or sufficiently dense) or require extensive precomputation. In this paper we present a lighting model for the general case of inhomogeneous medium and demonstrate its implementation on programmable graphics hardware. It is capable of producing high quality imagery at interactive frame rates with only mild assumptions about medium scattering properties and a moderate amount of simple precomputation. (A Lighting Model for General Participating Media. Kyle Hegeman, Michael Ashikhmin and Simon Premoze. Accepted for publication. Proceedings of ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, April 2005.)

This paper by Rao et al. at UNC Charlotte describes an algorithm to track human limbs at interactive rates without using markers. 3d point cloud data is derived from a modified visual hull algorithm. This data is fed into a particle filtering algorithm that runs on the GPU. The tracking system runs at interactive rates. (Interactive marker-less tracking of human limbs. Rao S., Hodges L.F to be submitted to Transactions on Visualization and Computer Graphics.)

This paper by Jansen et al. describes how to utilize current commodity graphics hardware to perform Fourier volume rendering directly on the GPU. The paper presents a novel implementation of the Fast Fourier Transform: This Split-Stream-FFT maps the recursive structure of the FFT to the GPU in an efficient way. Additionally, high-quality resampling within the frequency domain is discussed. The implementation enables visualization of large volumetric data sets at interactive frame rates on a mid-range computer system. (Fourier Volume Rendering on the GPU Using a Split-Stream FFT)

A second GPU Gems 2 sample chapter, Streaming Architectures and Technology Trends (Chapter 29), by John Owens is now available. The first sample chapter Per-Pixel Displacement with Distance Functions (Chapter 8), was released last week.

To correlate the intensities in two images an energy functional is successively minimized in a variational setting. The gradient flow formulation makes use of a robust multi-scale regularization, an efficient multi-grid solver and an adaptive time-step control. On the GPU the multi-scale maps to a packed multi-grid pyramid with several scales per grid level. The algorithm uses three nested loops: the regularized multi-scale descent, the iterative solution of the gradient flow PDE, and on the third level the multi-grid smoother and the adaptive time-step iteration. (Image Registration by a Regularized Gradient Flow – A Streaming Implementation in DX9 Graphics Hardware. Robert Strzodka, Marc Droske and Martin Rumpf Computing, 73(4), 373-389, Springer, 2004.)

Natural neighbour interpolation is a popular nonparametric method for interpolating among sample data points and is based on computing Voronoi diagrams. In this paper by Fan, Efrat, Koltun, Krishnan and Venkatasubramanian, we show how natural neighbour interpolation can be performed very efficiently on the GPU. The main advantage of this approach is that multiple interpolation queries can be issued simultaneously; the algorithm creates a scalar field for the interpolated result. (Hardware Assisted Natural Neighbour Interpolation. Quanfu Fan, Alon Efrat, Vladlen Koltun, Shankar Krishnan, and Suresh Venkatasubramanian. Proc. 7th Workshop on Algorithms Engineering and Experimentation.)

This paper by Strzodka and Garbe presents a tool for real-time visualization of motion features in 2D image sequences. The motion is estimated through an eigenvector analysis of the spatio-temporal structure tensor at every pixel location. Post-processing in the form of coloring, blending, threshholding, fading and smoothing helps to select the desired motion features for display. The paper demonstrates several examples of test sequences containing people moving at different velocities. These people are visually marked in the real-time display of the image sequence. The tool is also applied to angiography sequences to emphasize the blood flow and its distribution. The implementation uses DX9 graphics hardware and centers around a vectorized version of the Jacobi method for matrix diagonalization. (Real-Time Motion Estimation and Visualization on Graphics Cards. Robert Strzodka and Christoph Garbe in Proceedings of Visualization 2004, pages 545-552, 2004)

This Pacific Graphics 2004 paper by Youquan Liu et al. presents a way to process complex boundary conditions when simulating fluid flow using the Navier-Stokes Equations on the GPU. After voxelizing the 3D geometry scene, this technique computes a “modification factor texture” and an offset texture in “flat 3D” form to delineate boundary conditions needed to handle the internal obstacles, and in this way it takes advantage of the parallelism of GPU to accelerate the whole computation. (“Real-Time 3D Fluid Simulation on GPU with Complex Obstacles”, Youquan Liu, Xuehui Liu and Enhua Wu, In Proceedings of Pacific Graphics 2004, pages 247-256,October 2004.)

This IEEE Visualization 2004 paper by McCormick et al. describes the Scout System and Language that allow the GPU to be programmed for scientific visualization. Scout uses a data parallel language that allows the user to program visual mappings from data values to the final rendered result. These techniques can be used to replace standard user interface components, such as the transfer function editor commonly used in volume rendering. (“Scout: A Hardware-Accelerated System for Quantitatively Driven Visualization and Analysis”, Patrick S. McCormick, Jeff Inman, James P. Ahrens, Chuck Hansen and Greg Roth, In Proceedings IEEE Visualization 2004, pages 171-178, October 2004.)