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Ultrascale Visualization of Climate Data
Found in: Computer
By Dean N. Williams,Timo Bremer,Charles Doutriaux,John Patchett,Sean Williams,Galen Shipman,Ross Miller,David R. Pugmire,Brian Smith,Chad Steed,E. Wes Bethel,Hank Childs,Harinarayan Krishnan,Prabhat Prabhat,Michael Wehner,Claudio T. Silva,Emanuele Santos,David Koop,Tommy Ellqvist,Jorge Poco,Berk Geveci,Aashish Chaudhary,Andy Bauer,Alexander Pletzer,Dave Kindig,Gerald L. Potter,Thomas P. Maxwell
Issue Date:September 2013
pp. 68-76
Collaboration across research, government, academic, and private sectors is integrating more than 70 scientific computing libraries and applications through a tailorable provenance framework, empowering scientists to exchange and examine data in novel ways...
SLIC: Scheduled Linear Image Compositing for Parallel Volume Rendering
Found in: Parallel and Large-Data Visualization and Graphics, IEEE Symposium on
By Aleksander Stompel, Kwan-Liu Ma, Eric B. Lum, James Ahrens, John Patchett
Issue Date:October 2003
pp. 6
Parallel volume rendering offers a feasible solution to the large data visualization problem by distributing both the data and rendering calculations among multiple computers connected by a network. In sort-last parallel volume rendering, each processor ge...
A model for optimizing file access patterns using spatio-temporal parallelism
Found in: Proceedings of the 8th International Workshop on Ultrascale Visualization (UltraVis '13)
By Aashish Chaudhary, Berk Geveci, Galen M. Shipman, Ross Miller, Andrew Bauer, Boonthanome Nouanesengsy, Dean N. Williams, James Ahrens, John Patchett
Issue Date:November 2013
pp. 1-8
For many years now, I/O read time has been recognized as the primary bottleneck for parallel visualization and analysis of large-scale data. In this paper, we introduce a model that can estimate the read time for a file stored in a parallel filesystem when...
Interactive remote large-scale data visualization via prioritized multi-resolution streaming
Found in: Proceedings of the 2009 Workshop on Ultrascale Visualization (UltraVis '09)
By David E. DeMarle, James P. Ahrens, John Patchett, Jonathan Woodring, Mathew Maltrud
Issue Date:November 2009
pp. 1-10
The simulations that run on petascale and future exascale supercomputers pose a difficult challenge for scientists to visualize and analyze their results remotely. They are limited in their ability to interactively visualize their data mainly due to limite...