November 2007
Software Enabling Technologies for Petascale Science
E. Wes Bethel, Lawrence Berkeley National Laboratory
Chris Johnson, University of Utah
Cecilia Aragon, Lawrence Berkeley National Laboratory
Prabhat, Lawrence Berkeley National Laboratory
Oliver Rübel, Lawrence Berkeley National Laboratory
Gunther Weber, Lawrence Berkeley National Laboratory
Valerio Pascucci, Lawrence Livermore National Laboratory
Hank Childs, Lawrence Livermore National Laboratory
Peer-Timo Bremer, Lawrence Livermore National Laboratory
Brad Whitlock, Lawrence Livermore National Laboratory
Sean Ahern, Oak Ridge National Laboratory
Jeremey Meredith, Oak Ridge National Laboratory
George Ostrouchov, Oak Ridge National Laboratory
Ken Joy, University of California, Davis
Bernd Hamann, University of California, Davis
Christoph Garth, University of California, Davis
Martin Cole, University of Utah
Charles Hansen, University of Utah
Steven Parker, University of Utah
Allen Sanderson, University of Utah
Claudio Silva, University of Utah
Xavier Tricoche, University of Utah


Recently, VACET has focused attention on implementing a set of essential debugging features in VisIt so that one of our stakeholders, the DOE SciDAC Applied Partial Differential Equations Center (APDEC), can fully migrate from their project-written and maintained visual data analysis software (ChomboVis) to VisIt. This migration will result in two benefits crucial to APDEC. The first is a cost savings, as APDEC will no longer need to expend in-project resources on maintaining visualization software. The second is new AMR visualization capabilities that include the ability to run on parallel machines as well as support for remote and distributed visualization.

We added a new capability in VisIt – AMR spreadsheet plots – that support direct viewing of numerical values on a particular slice of a patch (see Figure 7). This function is essential for debugging and used by AMR code development teams on a daily basis. The new spreadsheet capability is integrated with VisIt’s “pick cell” feature, allowing users to “link” them to other plots. Additional new features include the ability to customize the VisIt interface, thereby improving usability so that new users can quickly navigate and employ features familiar to them in their older, retiring software.

While not as visible as the features above, other recent accomplishments include software architecture and engineering work to produce all-important performance improvements. Optimizations in AMR grid processing have produced a ten-fold savings in memory, and support more efficient rendering. Additional performance and memory optimizations improve efficiency for the important use case of rendering patch boundaries. Our new, specialized algorithm is an order of magnitude faster and more memory efficient than the previous implementation.

All of these software enhancements that produce important performance improvements and visualization capabilities crucial to AMR-based computational science projects have been made available to the public through production-quality, parallel-capable, open source visualization software.

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Reference this article
Bethel, E. W., Johnson, C., Aragon, C., Prabhat, Rübel, O., Weber, G., Pascucci, V., Childs, H., Bremer, P.-T., Whitlock, B., Ahern, S., Meredith, J., Ostrouchov, G., Joy, K., Hamann, B., Garth, C., Cole, M., Hansen, C., Parker, S., Sanderson, A., Silva, C., Tricoche, X. "DOE's SciDAC Visualization and Analytics Center for Enabling Technologies - Strategy for Petascale Visual Data Analysis Success," CTWatch Quarterly, Volume 3, Number 4, November 2007. http://www.ctwatch.org/quarterly/articles/2007/11/does-scidac-visualization-and-analytics-center-for-enabling-technologies-strategy-for-petascale-visual-data-analysis-success/

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