Savant is a asymptotic ray-tracing CEM tool used to predict the performance of antennas installed on electrically large platforms, including far-field antenna patterns, near-field distributions, and antenna-to-antenna coupling. Savant is based on the shooting and bouncing rays (SBR) formulation. While asymptotic solvers like Savant have significantly smaller computational and memory requirements for electrically large problems than full-wave techniques, the computation costs still increase significantly with frequency and simulation fidelity, and such solvers benefit greatly from parallelization techniques. Graphics processing units (GPUs) are throughput-oriented processing devices that are well suited for the mathematically intensive workloads found in CEM solvers. Current GPUs contain hundreds of processing units, leverage thousands of threads, and can execute over one trillion floating-point operations per second. A hybrid CPU and GPU parallelization approach has been developed for Savant, providing significant speedups compared to CPU-only implementations. Results from the execution of GPU-accelerated Savant on multiple case studies will be presented.
(T. Courtney, J. E. Stone and R. Kipp, “Using GPUs to Accelerate installed antenna performance simulations,” Proc. Allerton Antenna Symposium, Sept. 2011, Monticello, IL. [PDF])
Exposure Render is a Direct Volume Rendering Application that applies progressive Monte Carlo raytracing, coupled with physically based light transport to heterogeneous volumetric data. Exposure Render enables the configuration of any number of arbitrarily shaped area lights, models a real-world camera, including its lens and aperture, and incorporates complex materials, whilst still maintaining interactive display updates. It features both surface and volumetric scattering, and applies noise reduction to remove the unwanted startup noise associated with progressive Monte Carlo rendering. The complete implementation is available in source and binary forms under a permissive free software license.
Implementing flexible software solutions, such as rendering and ray tracing, is still challenging for GPU programs. The amount of available memory on modern GPUs is relatively small. Scenes for feature film rendering and visualization have large geometric complexity and can easily contain millions of polygons and a large number of texture maps and other data attributes. CentiLeo presents an interactive out-of-core ray tracing engine running on the single desktop GPU. The system is built around a virtual memory manager. A novel ray intersection algorithm built around an acceleration structure, cached on the GPU, loads needed data on-demand using page swapping. The ray tracing engine is used to implement a variety of rendering and light transport algorithms. The system is implemented using CUDA and runs on a single NVIDIA GTX 480.
Glare Technologies is proud to announce the release of Indigo Renderer 3.0 and Indigo RT. We use a hybrid GPU acceleration approach, which typically results in a 2-3x speedup when paired with a sufficiently powerful CPU. Realtime scene changes are possible, also in conjunction with network rendering to further accelerate rendering performance. A page outlining the other features and improvements of Indigo 3.0 and Indigo RT can be found at http://www.indigorenderer.com/indigo3 and http://www.indigorenderer.com/indigo_rt.
Press release (submitted to gpgpu.org very late…):
LOS ANGELES,CA – July 26, 2010 – PEER 1 Hosting (TSX:PIX), a global online IT hosting provider, today announced the availability of the industry’s first large-scale, hosted graphics processing unit (GPU) Cloud at the 37th Annual Siggraph International Conference.
The system runs the RealityServer® 3D web application service platform, developed by mental images, a wholly owned subsidiary of NVIDIA. The RealityServer platform is a powerful combination of NVIDIA Tesla GPUs and 3D web services software. It delivers interactive and photorealistic applications over the web using the iray® renderer, which enables animators, product designers, architects and consumers to easily visualize 3D scenes with remarkable realism. Read the rest of this entry »
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).
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)
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