Interactive Exploration and Analysis of Large-Scale Simulations Using Topology-Based Data Segmentation
Abstract
Large-scale simulations are increasingly being used to study complex scientific and engineering phenomena. As a result, advanced visualization and data analysis are also becoming an integral part of the scientific process. Often, a key step in extracting insight from these large simulations involves the definition, extraction, and evaluation of features in the space and time coordinates of the solution. However, in many applications, these features involve a range of parameters and decisions that will affect the quality and direction of the analysis. Examples include particular level sets of a specific scalar field, or local inequalities between derived quantities. A critical step in the analysis is to understand how these arbitrary parameters/decisions impact the statistical properties of the features, since such a characterization will help to evaluate the conclusions of the analysis as a whole. We present a new topological framework that in a single-pass extracts and encodes entire families of possible features definitions as well as their statistical properties. For each time step we construct a hierarchical merge tree a highly compact, yet flexible feature representation. While this data structure is more than two orders of magnitude smaller than the raw simulation data it allows us to extract a setmore »
- Authors:
-
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- French National Center for Scientific Research, Paris (France); Telecom ParisTech (France)
- Univ. of Utah, Salt Lake City, UT (United States)
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
- OSTI Identifier:
- 1511329
- Grant/Contract Number:
- AC02-05CH11231
- Resource Type:
- Accepted Manuscript
- Journal Name:
- IEEE Transactions on Visualization and Computer Graphics
- Additional Journal Information:
- Journal Volume: 17; Journal Issue: 9; Journal ID: ISSN 1077-2626
- Publisher:
- IEEE
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING
Citation Formats
Bremer, P-T, Weber, G., Tierny, J., Pascucci, V., Day, M., and Bell, J. Interactive Exploration and Analysis of Large-Scale Simulations Using Topology-Based Data Segmentation. United States: N. p., 2010.
Web. doi:10.1109/TVCG.2010.253.
Bremer, P-T, Weber, G., Tierny, J., Pascucci, V., Day, M., & Bell, J. Interactive Exploration and Analysis of Large-Scale Simulations Using Topology-Based Data Segmentation. United States. https://doi.org/10.1109/TVCG.2010.253
Bremer, P-T, Weber, G., Tierny, J., Pascucci, V., Day, M., and Bell, J. Fri .
"Interactive Exploration and Analysis of Large-Scale Simulations Using Topology-Based Data Segmentation". United States. https://doi.org/10.1109/TVCG.2010.253. https://www.osti.gov/servlets/purl/1511329.
@article{osti_1511329,
title = {Interactive Exploration and Analysis of Large-Scale Simulations Using Topology-Based Data Segmentation},
author = {Bremer, P-T and Weber, G. and Tierny, J. and Pascucci, V. and Day, M. and Bell, J.},
abstractNote = {Large-scale simulations are increasingly being used to study complex scientific and engineering phenomena. As a result, advanced visualization and data analysis are also becoming an integral part of the scientific process. Often, a key step in extracting insight from these large simulations involves the definition, extraction, and evaluation of features in the space and time coordinates of the solution. However, in many applications, these features involve a range of parameters and decisions that will affect the quality and direction of the analysis. Examples include particular level sets of a specific scalar field, or local inequalities between derived quantities. A critical step in the analysis is to understand how these arbitrary parameters/decisions impact the statistical properties of the features, since such a characterization will help to evaluate the conclusions of the analysis as a whole. We present a new topological framework that in a single-pass extracts and encodes entire families of possible features definitions as well as their statistical properties. For each time step we construct a hierarchical merge tree a highly compact, yet flexible feature representation. While this data structure is more than two orders of magnitude smaller than the raw simulation data it allows us to extract a set of features for any given parameter selection in a postprocessing step. Furthermore, we augment the trees with additional attributes making it possible to gather a large number of useful global, local, as well as conditional statistic that would otherwise be extremely difficult to compile. We also use this representation to create tracking graphs that describe the temporal evolution of the features over time. Our system provides a linked-view interface to explore the time-evolution of the graph interactively alongside the segmentation, thus making it possible to perform extensive data analysis in a very efficient manner. We demonstrate our framework by extracting and analyzing burning cells from a large-scale turbulent combustion simulation. In particular, we show how the statistical analysis enabled by our techniques provides new insight into the combustion process.},
doi = {10.1109/TVCG.2010.253},
journal = {IEEE Transactions on Visualization and Computer Graphics},
number = 9,
volume = 17,
place = {United States},
year = {Fri Dec 17 00:00:00 EST 2010},
month = {Fri Dec 17 00:00:00 EST 2010}
}
Free Publicly Available Full Text
Publisher's Version of Record
Other availability
Search WorldCat to find libraries that may hold this journal
Cited by: 70 works
Citation information provided by
Web of Science
Web of Science
Figures / Tables:
Fig. 1: The projection of the two-dimensional impact parameter distribution of muon pairs onto one of the two axes is compared to the fit result. The various $P$ + $HF$ components listed in the first column of Table 1 are shown separately
All figures and tables
(36 total)
Save to My Library
You must Sign In or Create an Account in order to save documents to your library.
Works referencing / citing this record:
Graphs in Scientific Visualization: A Survey: Graphs in Scientific Visualization: A Survey
journal, February 2016
- Wang, Chaoli; Tao, Jun
- Computer Graphics Forum, Vol. 36, Issue 1
In Situ Methods, Infrastructures, and Applications on High Performance Computing Platforms
journal, June 2016
- Bauer, A. C.; Abbasi, H.; Ahrens, J.
- Computer Graphics Forum, Vol. 35, Issue 3
A Survey of Topology-based Methods in Visualization
journal, June 2016
- Heine, C.; Leitte, H.; Hlawitschka, M.
- Computer Graphics Forum, Vol. 35, Issue 3
Data Reduction Techniques for Simulation, Visualization and Data Analysis: Survey on Scientific Data Reduction Techniques
journal, March 2018
- Li, S.; Marsaglia, N.; Garth, C.
- Computer Graphics Forum, Vol. 37, Issue 6
Figures / Tables found in this record:
Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.