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Title: Optimizing Scientist Time through In Situ Visualization and Analysis

Abstract

In situ processing produces reduced size persistent representations of a simulations state while the simulation is running. The need for in situ visualization and data analysis is often described in terms of supercomputer size and performance in relation to available storage size.

Authors:
ORCiD logo [1]; ORCiD logo [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
Contributing Org.:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); Univ. of Kaiserslautern (Germany); Kitware Inc., Clifton Park, NY (United States)
OSTI Identifier:
1463483
Report Number(s):
LA-UR-17-28785
Journal ID: ISSN 0272-1716
Grant/Contract Number:  
AC52-06NA25396
Resource Type:
Accepted Manuscript
Journal Name:
IEEE Computer Graphics and Applications
Additional Journal Information:
Journal Volume: 38; Journal Issue: 1; Journal ID: ISSN 0272-1716
Publisher:
IEEE
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; visualization; in situ; data analysis; lossless compression; feature extraction; scientific computing; data visualization; computational modeling; atmospheric modeling; solar system; supercomputers; data models

Citation Formats

Patchett, John, and Ahrens, James. Optimizing Scientist Time through In Situ Visualization and Analysis. United States: N. p., 2018. Web. doi:10.1109/MCG.2018.011461533.
Patchett, John, & Ahrens, James. Optimizing Scientist Time through In Situ Visualization and Analysis. United States. doi:10.1109/MCG.2018.011461533.
Patchett, John, and Ahrens, James. Thu . "Optimizing Scientist Time through In Situ Visualization and Analysis". United States. doi:10.1109/MCG.2018.011461533. https://www.osti.gov/servlets/purl/1463483.
@article{osti_1463483,
title = {Optimizing Scientist Time through In Situ Visualization and Analysis},
author = {Patchett, John and Ahrens, James},
abstractNote = {In situ processing produces reduced size persistent representations of a simulations state while the simulation is running. The need for in situ visualization and data analysis is often described in terms of supercomputer size and performance in relation to available storage size.},
doi = {10.1109/MCG.2018.011461533},
journal = {IEEE Computer Graphics and Applications},
number = 1,
volume = 38,
place = {United States},
year = {2018},
month = {3}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Figures / Tables:

Figure 1 Figure 1: An image from the Deep Water Impact Ensemble Data Set showing volume fraction of water with a highly customized color map to show structure as the water moves vertically into upper levels of the atmosphere. Water is a potent greenhouse

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Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.