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News & Announcements
  • 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.
  • Professor Kwan-Liu Ma spoke on "Space for Visualization" at the Neyman seminar of UC Berkeley on April 8th.
  • John Owens received the UC Davis Department of Electrical and Computer Engineering's Graduate Student Association Award for Graduate Teaching and Mentorship, April 2009.
  • Professor Maneesh Agrawala spoke at UC Davis on Visual Design Principles on November 13
 
Visualization Billboard
Turbulent Combustion Simulation  
   
 
Research Highlights
Volumetric datasets with multiple variables on each voxel over multiple timesteps are often complex, especially when considering the exponentially large attribute space formed by the variables, and spatial and temporal dimensions. It is intuitive, practical, and thus often desirable, to interactively select a subset of the data from within that high-dimensional value space for efficient visualization. This approach is straightforward to implement if the dataset is small enough to be stored entirely in-core. However, to handle datasets sized at hundreds of gigabytes and beyond, this simplistic approach becomes infeasible. More sophisticated solutions are needed. In this work, we developed a system that supports efficient visualization of an arbitrary subset, selected by range-queries, of a large multivariate time-varying dataset. By employing specialized data structure and schemes of data distribution, our system can leverage a large number of networked computers as parallel data servers and guarantees a near optimal load-balance. We demonstrate our system of scalable data servers using a large dataset from a supernova simulation... Read more

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