Parallel visualization on leadership computing resources

T. Peterka, R. B. Ross, H. W. Shen, Kwan-Liu Ma, W. Kendall, H. Yu

Research output: Contribution to journalConference articlepeer-review

5 Scopus citations


Changes are needed in the way that visualization is performed, if we expect the analysis of scientific data to be effective at the petascale and beyond. By using similar techniques as those used to parallelize simulations, such as parallel I/O, load balancing, and effective use of interprocess communication, the supercomputers that compute these datasets can also serve as analysis and visualization engines for them. Our team is assessing the feasibility of performing parallel scientific visualization on some of the most powerful computational resources of the U.S. Department of Energy's National Laboratories in order to pave the way for analyzing the next generation of computational results. This paper highlights some of the conclusions of that research.

Original languageEnglish (US)
Article number012088
JournalJournal of Physics: Conference Series
Issue number1
StatePublished - Jan 1 2009

ASJC Scopus subject areas

  • Physics and Astronomy(all)


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