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Title: Preparing for in situ processing on upcoming leading-edge supercomputers

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. Finally, 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.
Authors:
 [1] ;  [2] ;  [3] ;  [3] ;  [4] ;  [3]
  1. Univ. of Oregon, Eugene, OR (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  2. Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States)
  3. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  4. Univ. of Oregon, Eugene, OR (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Publication Date:
Grant/Contract Number:
AC05-00OR22725
Type:
Accepted Manuscript
Journal Name:
Supercomputing Frontiers and Innovations
Additional Journal Information:
Journal Volume: 3; Journal Issue: 4; Related Information: Oct - Dec 2016 issue; Journal ID: ISSN 2409-6008
Publisher:
South Ural State University
Research Org:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
Contributing Orgs:
Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States); Univ. of Oregon, Eugene, OR (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; scientific visualization; in situ methods; data staging methods; data reductions; high performance computing
OSTI Identifier:
1338570