Ke-Sen Huang has assembled a web page with links to all papers presented at these two important conferences, High Performance Graphics (a synthesis of the Graphics Hardware and Interactive Ray Tracing conferences) and SIGGRAPH. Both conferences had quite a number of GPGPU-related publications.  Highlights from HPG include a paper on computing minimum spanning trees on the GPU, one on optimizing stream compaction on GPUs, and a study from NVIDIA on understanding the efficiency of GPUs and of wide-SIMD architectures in general on inherently imbalanced workloads like ray tracing (among others).

Click here for SIGGRAPH papers, and here for HPG papers. Ke-Sen’s pages are also a good resource for other conferences in the field.

This paper by Robert et al. at the University of Bern, Switzerland describes the object intersection buffer (OIB), a GPU-based visibility preprocessing algorithm for accelerating ray tracing. Based on this approach, a hybrid ray tracer is proposed to exploit parallel ray tracing using the GPU and CPU. (Hybrid Ray Tracing – Ray Tracing Using GPU-Accelerated Image-Space Methods. Philippe C.D. Robert, Severin Schoepke, and Hanspeter Bieri. Proceedings of GRAPP 2007.)

To focus and facilitate research on real-time ray tracing, a new forum is being created for this rapidly developing field: the 2006 IEEE Symposium on Interactive Ray Tracing, sponsored by the IEEE Computer Society and the IEEE Visualization and Graphics Technical Committee (pending). The Call For Participation is now online and contributions on Ray Tracing on GPUs are invited.

Using the GPU to accelerate ray tracing may seem like a natural choice due to the highly parallel nature of the problem. However, determining the most versatile GPU data structure for scene storage and traversal is a challenge. In this paper, we introduce a new method for quick intersection of triangular meshes on the GPU. The method uses a threaded bounding volume hierarchy built from a geometry image, which can be efficiently traversed and constructed entirely on the GPU. This acceleration scheme is highly competitive with other GPU ray tracing methods, while allowing for both dynamic geometry and an efficient level of detail scheme at no extra cost. (Fast GPU Ray Tracing of Dynamic Meshes using Geometry Images Nathan A. Carr, Jared Hoberock, Keenan Crane, and John C. Hart. To appear in Proceedings of Graphics Interface 2006)

Eric Haines has released the latest issue of his long-running “Ray Tracing News”. It’s chock full of news and interesting discussion about ray tracing implementation and optimization, kd-trees, and more. It also includes links to various ray-tracing work being done on GPUs. (Ray Tracing News volume 18, no. 1)

The quaternion Julia fractal is a complex and beautiful object, yet its parameter space is difficult to explore due to the high cost of visualization. Fortunately, rendering the Julia set by ray tracing or “sphere tracing” its surface is an algorithm well suited to the GPU: it has high arithmetic intensity and uses virtually no bandwidth. A GPU implementation (with source) of this algorithm that allows real-time interaction with the Julia set has been made available by Keenan Crane.

This paper presents a fast approximation method to obtain the point hit by a reflection or refraction ray. The calculation is based on the distance values stored in environment map texels. This approximation is used to localize environment mapped reflections and refractions; that is, to make them depend on where they occur. On the other hand, placing the eye into the light source, the method is also good to generate real-time caustics. Computing a map for each refractor surface, we can even evaluate multiple refractions without tracing rays. The method is fast and accurate if the scene consists of larger planar faces, when the results are similar to that of ray-tracing. On the other hand, the method suits very well to the GPU architecture, and can render ray-tracing and global illumination effects at a few hundred frames per second. The primary application area of the proposed method is the introduction of these effects in games. (Approximate Ray-Tracing on the GPU with Distance Impostors. Laszlo Szirmay-Kalos, Barnabas Aszodi, Istvan Lazanyi, and Matyas Premecz. Department of Control Engineering and Information Technology, Technical University of Budapest.)

Recently, ray tracing on consumer level graphics hardware has been introduced. So far, most published studies on this topic use the uniform grid spatial subdivision structure for reducing the number of ray/triangle intersection tests. For many types of scenes, a hierarchical acceleration structure is more appropriate. This thesis by Lars Ole Simonsen and Niels Thrane of University of Aarhus compares GPU based traversal of kd-trees and uniform grids with a novel bounding volume hierarchy traversal scheme. The three implementations are compared in terms of performance and usefulness on the GPU. The thesis concludes that on the GPU, the bounding volume hierarchy traversal technique is up to 9 times faster than its implementations of uniform grid and kd-tree. Additionally, this technique proves the simplest to implement and the most memory efficient. (Lars Ole’s Website or Direct link to thesis PDF.)

We received news simultaneously from the developers of two new GPU ray tracers. Both projects are graduate-level thesis projects. One, called GPU-RT, is developed by Martin Christen and supports .3DS format meshes, multiple materials, and implements acceleration data structures. GPU-RT runs on NVIDIA GeForce 6 Series GPUs under D3D/HLSL and OpenGL/GLSL, and is available on SourceForge.net. The other project, “Ray Tracing on Programmable Graphics Hardware”, is by Filip Karlsson and Carl Johan Ljungstedt of Chalmers University of Technology. The thesis describes, among other things, how proximity clouds can be used to accelerate ray tracing on the GPU. (1. GPU-RT, Diploma Thesis by Martin Christen. 2. “Ray Tracing on Programmable Graphics Hardware”, Masters Thesis by Filip Karlsson and Carl Johan Ljungstedt.)

This dissertation by Tim Purcell of Stanford University discusses several topics relevant to GPGPU including a stream processor abstraction for GPUs, and GPU-based ray tracing and photon mapping algorithms. Much of this work has been reported on GPGPU before, but the description of the ray tracing work in particular is expanded and updated from previous papers with details about the Radeon 9700 ray tracer demonstrated at Siggraph 2002. Included on the web page are links to the dissertation defense talk slides and movies of the various demos. (Ray Tracing on a Stream Processor, Timothy J. Purcell, Ph.D. Dissertation, March 2004.)