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Data co-processing for extreme scale analysis level II ASC milestone (4745)

Rogers, David R.; Moreland, Kenneth D.; Oldfield, Ron A.; Fabian, Nathan D.

Exascale supercomputing will embody many revolutionary changes in the hardware and software of high-performance computing. A particularly pressing issue is gaining insight into the science behind the exascale computations. Power and I/O speed con- straints will fundamentally change current visualization and analysis work ows. A traditional post-processing work ow involves storing simulation results to disk and later retrieving them for visualization and data analysis. However, at exascale, scien- tists and analysts will need a range of options for moving data to persistent storage, as the current o ine or post-processing pipelines will not be able to capture the data necessary for data analysis of these extreme scale simulations. This Milestone explores two alternate work ows, characterized as in situ and in transit, and compares them. We nd each to have its own merits and faults, and we provide information to help pick the best option for a particular use.

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TYPE SAND Report YEAR 2013
DOIOSTI

A survey of visualization pipelines

IEEE Transactions on Visualization and Computer Graphics

Moreland, Kenneth D.

The most common abstraction used by visualization libraries and applications today is what is known as the visualization pipeline. The visualization pipeline provides a mechanism to encapsulate algorithms and then couple them together in a variety of ways. The visualization pipeline has been in existence for over 20 years, and over this time many variations and improvements have been proposed. This paper provides a literature review of the most prevalent features of visualization pipelines and some of the most recent research directions. © 1995-2012 IEEE.

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TYPE Presentation YEAR 2013
OSTIOSTIScopusScopus
Results 176–200 of 329
Results 176–200 of 329