skip to main content

DOE PAGESDOE PAGES

Title: Towards real-time detection and tracking of spatio-temporal features: Blob-filaments in fusion plasma

A novel algorithm and implementation of real-time identification and tracking of blob-filaments in fusion reactor data is presented. Similar spatio-temporal features are important in many other applications, for example, ignition kernels in combustion and tumor cells in a medical image. This work presents an approach for extracting these features by dividing the overall task into three steps: local identification of feature cells, grouping feature cells into extended feature, and tracking movement of feature through overlapping in space. Through our extensive work in parallelization, we demonstrate that this approach can effectively make use of a large number of compute nodes to detect and track blob-filaments in real time in fusion plasma. Here, on a set of 30GB fusion simulation data, we observed linear speedup on 1024 processes and completed blob detection in less than three milliseconds using Edison, a Cray XC30 system at NERSC.
Authors:
 [1] ;  [2] ;  [2] ;  [3] ;  [4] ;  [1] ;  [3] ;  [4]
  1. College of William and Mary, Williamsburg, VA (United States)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  3. Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States)
  4. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Grant/Contract Number:
AC05-00OR22725; AC02-05CH11231
Type:
Accepted Manuscript
Journal Name:
IEEE Transactions on Big Data
Additional Journal Information:
Journal Volume: 2; Journal Issue: 3; Journal ID: ISSN 2332-7790
Publisher:
IEEE
Research Org:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
Country of Publication:
United States
Language:
English
Subject:
70 PLASMA PHYSICS AND FUSION TECHNOLOGY; 97 MATHEMATICS AND COMPUTING; big data analytics; spatio-temporal feature; real-time detection and tracking; blob-filaments; fusion plasma
OSTI Identifier:
1326546
Alternate Identifier(s):
OSTI ID: 1377450