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Displaying 1-13 out of 13 total
Streaming-Enabled Parallel Data Flow Framework in the Visualization ToolKit
Found in: Computing in Science and Engineering
By Huy T. Vo,João L.D. Comba,Berk Geveci,Cláudio T. Silva
Issue Date:September 2011
pp. 72-83
A parallel dataflow framework implemented into VTK addresses the need for the streaming parallel computation in visualization pipelines.
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...
Research Challenges for Visualization Software
Found in: Computer
By Hank Childs,Berk Geveci,Will Schroeder,Jeremy Meredith,Kenneth Moreland,Christopher Sewell,Torsten Kuhlen,E. Wes Bethel
Issue Date:May 2013
pp. 34-42
As the visualization research community reorients its software to address up-coming challenges, it must successfully deal with diverse processor architectures, distributed systems, various data sources, massive parallelism, multiple input and output device...
The SDAV Software Frameworks for Visualization and Analysis on Next-Generation Multi-Core and Many-Core Architectures
Found in: 2012 SC Companion: High Performance Computing, Networking, Storage and Analysis (SCC)
By Christopher Sewell,Jeremy Meredith,Kenneth Moreland,Tom Peterka,Dave DeMarle,Li-ta Lo,James Ahrens,Robert Maynard,Berk Geveci
Issue Date:November 2012
pp. 206-214
This paper surveys the four software frameworks being developed as part of the visualization pillar of the SDAV (Scalable Data Management, Analysis, and Visualization) Institute, one of the SciDAC (Scientific Discovery through Advanced Computing) Institute...
Corrections to
Found in: IEEE Transactions on Visualization and Computer Graphics
By John Biddiscombe, Berk Geveci, Ken Martin, Kenneth Moreland, David Thompson
Issue Date:January 2008
pp. 241
No summary available.
Intelligence Analysis Using Titan
Found in: Symposium On Visual Analytics Science And Technology
By Patricia Crossno, Brian Wylie, Andrew Wilson, John Greenfield, Eric Stanton, Timothy Shead, Lisa Ice, Kenneth Moreland, Jeffrey Baumes, Berk Geveci
Issue Date:November 2007
pp. 241-242
The open source Titan Informatics Toolkit Project, which extends the Visualization Toolkit (VTK) to include information visualization capabilities, is being developed by Sandia National Laboratories in collaboration with Kitware. The VAST Contest provided ...
Compatible Triangulations of Spatial Decompositions
Found in: Visualization Conference, IEEE
By William J. Schroeder, Berk Geveci, Mathieu Malaterre
Issue Date:October 2004
pp. 211-218
We describe a general algorithm to produce compatible 3D triangulations from spatial decompositions. Such triangulations match edges and faces across spatial cell boundaries, solving several problems in graphics and visualization including the crack proble...
Large-Scale Data Visualization Using Parallel Data Streaming
Found in: IEEE Computer Graphics and Applications
By James Ahrens, Kristi Brislawn, Ken Martin, Berk Geveci, C. Charles Law, Michael Papka
Issue Date:July 2001
pp. 34-41
Effective large-scale data visualization remains an important challenge with analysis codes already producing terabyte results on clusters with thousands of processors. Frequently the analysis codes produce distributed data and consume a significant portio...
Verifying Scientific Simulations via Comparative and Quantitative Visualization
Found in: IEEE Computer Graphics and Applications
By James Ahrens,Katrin Heitmann,Mark Petersen,Jonathan Woodring,Sean Williams,Patricia Fasel,Christine Ahrens, Chung-Hsing Hsu,Berk Geveci
Issue Date:November 2010
pp. 16-28
This article presents a visualization-assisted process that verifies scientific-simulation codes. Code verification is necessary because scientists require accurate predictions to interpret data confidently. This verification process integrates iterative h...
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...
On-demand unstructured mesh translation for reducing memory pressure during in situ analysis
Found in: Proceedings of the 8th International Workshop on Ultrascale Visualization (UltraVis '13)
By Berk Geveci, Jonathan Woodring, Tom Peterka, James Ahrens, Timothy J. Tautges, Venkatram Vishwanath
Issue Date:November 2013
pp. 1-8
When coupling two different mesh-based codes, for example with in situ analytics, the typical strategy is to explicitly copy data (deep copy) from one implementation to another, doing translation in the process. This is necessary because codes usually do n...
A classification of scientific visualization algorithms for massive threading
Found in: Proceedings of the 8th International Workshop on Ultrascale Visualization (UltraVis '13)
By Kenneth Moreland, Kwan-Liu Ma, Berk Geveci, Robert Maynard
Issue Date:November 2013
pp. 1-10
As the number of cores in processors increase and accelerator architectures are becoming more common, an ever greater number of threads is required to achieve full processor utilization. Our current parallel scientific visualization codes rely on partition...
Electronic poster: co-visualization of full data and in situ data extracts from unstructured grid cfd at 160k cores
Found in: Proceedings of the 2011 companion on High Performance Computing Networking, Storage and Analysis Companion (SC '11 Companion)
By Andrew Bauer, Benjamin Matthews, Jing Fu, Kenneth Jansen, Mark Hereld, Min Zhou, Onkar Sahni, Venkatram Vishwanath, Berk Geveci, Christopher Carothers, Kalyan Kumaran, Mark Shephard, Michael Papka, Michel Rasquin, Ning Liu, Patrick Marion, Raymond Loy
Issue Date:November 2011
pp. 103-104
Scalability and time-to-solution studies have historically been focused on the size of the problem and run time. We consider a more strict definition of "solution" whereby a live data analysis (co-visualization of either the full data or in situ data extra...