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

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Description

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 ... continued below

Physical Description

64 p.

Creation Information

Rogers, David; Moreland, Kenneth D.; Oldfield, Ron A. & Fabian, Nathan D. March 1, 2013.

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This report is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. More information about this report can be viewed below.

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  • Sandia National Laboratories
    Publisher Info: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
    Place of Publication: Albuquerque, New Mexico

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Description

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.

Physical Description

64 p.

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Identifier

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  • Report No.: SAND2013-1122
  • Grant Number: AC04-94AL85000
  • Office of Scientific & Technical Information Report Number: 1093707
  • Archival Resource Key: ark:/67531/metadc844684

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Office of Scientific & Technical Information Technical Reports

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Creation Date

  • March 1, 2013

Added to The UNT Digital Library

  • May 19, 2016, 9:45 a.m.

Description Last Updated

  • June 17, 2016, 3:07 p.m.

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Citations, Rights, Re-Use

Rogers, David; Moreland, Kenneth D.; Oldfield, Ron A. & Fabian, Nathan D. Data co-processing for extreme scale analysis level II ASC milestone (4745)., report, March 1, 2013; Albuquerque, New Mexico. (digital.library.unt.edu/ark:/67531/metadc844684/: accessed September 25, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.