In situ generated probability distribution functions for interactive post hoc visualization and analysis

Yucong Chris Ye, Tyson Neuroth, Franz Sauer, Kwan-Liu Ma, Giulio Borghesi, Aditya Konduri, Hemanth Kolla, Jacqueline Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

The growing power and capacity of supercomputers enable scientific simulations at extreme scale, leading to not only more accurate modeling and greater predictive ability but also massive quantities of data to analyze. New approaches to data analysis and visualization are this needed to support interactive exploration through selective data access for gaining insights into terabytes and petabytes of data. In this paper, we present an in situ data processing method for both generating probability distribution functions (PDFs) from field data and reorganizing particle data using a single spatial organization scheme. This coupling between PDFs and particles allows for the interactive post hoc exploration of both data types simultaneously. Scientists can explore trends in large-scale data through the PDFs and subsequently extract desired particle subsets for further analysis. We evaluate the usability of our in situ method using a petascale combustion simulation and demonstrate the increases in task efficiency and accuracy that the resulting workflow provides to scientists.

Original languageEnglish (US)
Title of host publicationIEEE Symposium on Large Data Analysis and Visualization 2016, LDAV 2016 - Proceedings
EditorsKenneth Moreland, Markus Hadwiger, Ross Maciejewski
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages65-74
Number of pages10
ISBN (Electronic)9781509056590
DOIs
StatePublished - Mar 8 2017
Event6th IEEE Symposium on Large-Scale Data Analysis and Visualization, LDAV 2016 - Baltimore, United States
Duration: Oct 23 2016 → …

Other

Other6th IEEE Symposium on Large-Scale Data Analysis and Visualization, LDAV 2016
CountryUnited States
CityBaltimore
Period10/23/16 → …

Keywords

  • G.3 [Mathematics of Computing]: Probability and Statistics-Distribution Functions
  • H.3.2 [Information Systems]: Information Storage and Retrieval-Information Storage
  • I.6.6 [Computing Methodologies]: Simulation and Modeling-Simulation Output Analysis
  • J.2 [Computer Applications]: Physical Sciences and Engineering-Physics

ASJC Scopus subject areas

  • Computer Science Applications
  • Modeling and Simulation

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    Ye, Y. C., Neuroth, T., Sauer, F., Ma, K-L., Borghesi, G., Konduri, A., Kolla, H., & Chen, J. (2017). In situ generated probability distribution functions for interactive post hoc visualization and analysis. In K. Moreland, M. Hadwiger, & R. Maciejewski (Eds.), IEEE Symposium on Large Data Analysis and Visualization 2016, LDAV 2016 - Proceedings (pp. 65-74). [7874311] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/LDAV.2016.7874311