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Title: Remote visual analysis of large turbulence databases at multiple scales

Journal Article · · Journal of Parallel and Distributed Computing
 [1];  [2];  [3];  [3];  [2];  [2];  [4]
  1. Univ. of California, Davis, CA (United States). Dept. of Computer Science; Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  3. Johns Hopkins Univ., Baltimore, MD (United States)
  4. Univ. of California, Davis, CA (United States). Dept. of Computer Science

The remote analysis and visualization of raw large turbulence datasets is challenging. Current accurate direct numerical simulations (DNS) of turbulent flows generate datasets with billions of points per time-step and several thousand time-steps per simulation. Until recently, the analysis and visualization of such datasets was restricted to scientists with access to large supercomputers. The public Johns Hopkins Turbulence database simplifies access to multi-terabyte turbulence datasets and facilitates the computation of statistics and extraction of features through the use of commodity hardware. In this paper, we present a framework designed around wavelet-based compression for high-speed visualization of large datasets and methods supporting multi-resolution analysis of turbulence. By integrating common technologies, this framework enables remote access to tools available on supercomputers and over 230 terabytes of DNS data over the Web. Finally, the database toolset is expanded by providing access to exploratory data analysis tools, such as wavelet decomposition capabilities and coherent feature extraction.

Research Organization:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
AC52-06NA25396
OSTI ID:
1457276
Alternate ID(s):
OSTI ID: 1582730
Report Number(s):
LA-UR-17-20757
Journal Information:
Journal of Parallel and Distributed Computing, Vol. 120; ISSN 0743-7315
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 6 works
Citation information provided by
Web of Science

Figures / Tables (12)