Research Projects: Terascale Visualization
We are developing visualization algorithms for real time exploration of massive, time varying point cloud datasets produced by atomistic simulations. Challenges include developing level of detail algorithms for unstructured point data and representing sub-pixel features such as occlusion and intersections. The massive size of these datasets (gigabytes per timestep) make simply loading and rendering an image a challenging task. Our algorithms target efficient exploration of tera-scale datasets which contain millions to billions of objects as well as thousands of timesteps. This project is in collaboration with Mark Duchaineau of Lawrence Livermore National Laboratories.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by the author's copyright. This work may not be reposted without the explicit permission of the copyright holder.