Preparing for In Situ Processing on Upcoming Leading-edge Supercomputers

James Kress; Randy Michael Churchill; Scott Klasky; Mark Kim; Hank Childs; David Pugmire

doi:10.14529/jsfi160404

Authors

James Kress University of Oregon, Eugene Oak Ridge National Laboratory, Oak Ridge
Randy Michael Churchill Princeton Plasma Physics Laboratory, Princeton
Scott Klasky Oak Ridge National Laboratory, Oak Ridge
Mark Kim Oak Ridge National Laboratory, Oak Ridge
Hank Childs University of Oregon, Eugene Lawrence Berkeley National Laboratory, Berkeley
David Pugmire Oak Ridge National Laboratory, Oak Ridge

DOI:

https://doi.org/10.14529/jsfi160404

Abstract

High performance computing applications are producing increasingly large amounts of data and placing enormous stress on current capabilities for traditional post-hoc visualization techniques. Because of the growing compute and I/O imbalance, data reductions, including in situ visualization, are required. These reduced data are used for analysis and visualization in a variety of different ways. Many of he visualization and analysis requirements are known a priori, but when they are not, scientists are dependent on the reduced data to accurately represent the simulation in post hoc analysis. The contributions of this paper is a description of the directions we are pursuing to assist a large scale fusion simulation code succeed on the next generation of supercomputers. These directions include the role of in situ processing for performing data reductions, as well as the tradeoffs between data size and data integrity within the context of complex operations in a typical scientific workflow.

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