S6199 - Raytracing Scientific Data in NVIDIA OptiX™ with GVDB Sparse Volumes
Graphics Research Engineer, NVIDIA
Rama Hoetzlein's current research with NVIDIA explores data structures for large-scale simulation and volume rendering. Rama completed a dual-degree in computer science and fine arts from Cornell in 2001, with research in robotics and imaging. In 2010, his dissertation at the University of California, Santa Barbara, focused on tools for creative interaction in procedural modeling for media artists. In 2010, Rama was co-director and lead scientist of the Transliteracies project in the Digital Humanities, and professor of media studies at the Medialogy program in Copenhagen with a focus on visual effects and animation.
Senior Software Engineer, NVIDIA
Thomas Fogal is an NVIDIA engineer specializing in HPC visualization. As a doctoral student, he worked on parallel volume rendering techniques as well as novel approaches to in situ visualization. At the Scientific Computing & Imaging Institute, ORNL, and LLNL, he worked on parallel rendering for large scientific data. Thomas holds a B.S. and M.S. from the University of New Hampshire, and will soon have a doctorate from the University of Duisburg-Essen in Germany.
We present a novel technique for visualization of scientific data with compute operators and multi-scatter ray tracing entirely on GPU. Our source data consists of a high-resolution simulation using point-based wavelets, a representation not supported by existing tools. To visualize this data, and consider dynamic time-based rendering, our approach is inspired by OpenVDB from motion pictures, which uses a hierarchy of grids similar to AMR. We develop GVDB, a ground-up implementation with tree traversal, compute, and ray tracing via OptiX all on the GPU. GVDB enables multi-scatter rendering at 200 million rays/sec, and full-volume compute operations in a few milliseconds on datasets up to 4,200^3 entirely in GPU memory.
Tags: In-Situ and Scientific Visualization; Rendering & Ray Tracing; Computational Fluid Dynamics