Solar radio astronomical big data classification

Long Xu, Ying Weng, Zhuo Chen

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review


The Solar Broadband Radio Spectrometer (SBRS) monitors the solar radio busts all day long and produces solar radio astronomical big data foranalysis every day, which usually have been accumulated in mass images for scientific study over decades. In the observed mass data, burst events are rare and always along with interference, so it seems impossible to identify whether the mass data contain bursts or not and figure out which type of burst it is by manual operation timely. Therefore, we take advantage of high performance computing and machine learning techniques to classify the huge volume astronomical imaging data automatically. The professional line of multiple NVIDIA GPUs has been exploited to deliver 78x faster parallel processing power for high performance computing of the astronomical big data, and neural networks have been utilized to learn the representations of the solar radio spectra. Experimental results have demonstrated that the employed network can effectively classify a solar radio image into the labeled categories. Moreover, the processing time is dramatically reduced by exploring GPU parallel computing environment.

Original languageEnglish
Title of host publicationHigh Performance Computing and Applications - 3rd International Conference, HPCA 2015, Revised Selected Papers
EditorsCraig C. Douglas, Jiang Xie, Wu Zhang, Zhangxin Chen, Yan Chen, Yan Chen
PublisherSpringer Verlag
Number of pages8
ISBN (Print)9783319325569
Publication statusPublished - 2016
Externally publishedYes
Event3rd International Conference on High Performance Computing and Applications, HPCA 2015 - Shanghai, China
Duration: 26 Jul 201530 Jul 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference3rd International Conference on High Performance Computing and Applications, HPCA 2015


  • Big data
  • Classification
  • Deep learning
  • Solar radio

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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