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News & Announcements
  • The technical program of the 4th Ultrascale Visualization Workshop at SC09 is now available: http://vis.cs.ucdavis.edu/Ultravis09
  • Professor Ma gave an invited talk at the Pacific Graphics 2009 Conference.
  • Professor Kwan-Liu Ma gave an invited talk at the 10th International Computational Accelerator Physics Conference (ICAP 2009).
  • Ultravis Institute researchers along with combustion simulation scientists at the Sandia National Laboratory has successfully demonstrated in situ visualization at the petascale using up to 6480 processors of the Cray XT5 at NCCS/ORNL.
  • John Owens is Program Chair of "High Performance Graphics", August 2009.
  • Kwan-Liu Ma is Paper Chair of IEEE Visualization 2009 Conference.
  • John Owens is giving the keynote talk, "GPU Computing: Heterogeneous Computing for Future Systems", International Heterogeneity in Computing Workshop, Rome, May 18th.
  • PacificVis 2009 was held April 20-23 in Beijing, China. Members of the Ultravis Institute are playing leading roles in this conference.
 
Visualization Billboard
Turbulent Combustion Simulation  
   
 
Research Highlights
Feature detection and display are the essential goals of the visualization process. Most volume visualization software achieves these goals by mapping properties of sampled intensity values and their derivatives to color and opacity. However, by considering samples in isolation, it is difficult to visualize features that are not surface-based. In this work, we expand the basis of classification to broader neighborhoods centered around each voxel. Our approach allows users to enter predicate-based hypotheses about relational patterns in the local neighborhoods' frequency distributions and render visualizations that show how neighborhoods match the predicates (illustrated above). We have built a simple graphical user interface for forming and testing queries interactively and we describe a volume rendering algorithm tailored for investigating statistical queries. The query framework readily applies to spatial datasets from arbitrary domains and supports queries on time variant and multifield data. Users can directly query for classes of features previously inaccessible in general feature detection tools... Read more

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