American Journal of Information Science and Technology

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Construction and Management of Astronomical Big Data Analysis and Multi-dimensional Information Visualization Platform

Received: Mar. 10, 2020    Accepted: Apr. 09, 2020    Published: Apr. 29, 2020
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Abstract

The development of modern astronomy is rapidly and astronomical data increases exponentially. The HPC architecture based on GPU provides an efficient way of astronomic big data computing. Based on secure Ipv6 network environment, PMO has constructed the Big Data Analysis and Multi-dimensional Information Visualization Platform, which can reach the peak computing speed of 352Tflops and the totally storage capacity of 288TB. The platform is composed of 25 computing nodes, one management node and 5 storage nodes. The use of user-friendly, centralized cluster management software, the deployment of proprietary environmental control settings and multi-dimensional visualization of safety management systems form a multi-level, tridimensional and efficient management structure. A high-speed, high-capacity, highly reliable, secure and efficient high-performance computing cluster is finally constructed. The platform has a fully redundant, self-healing, highly scalable distributed storage system, a high-performance InfiniBand parallel computing and storage network, a complete job scheduling system, a cuda parallel computing architecture, and a variety of physical software tools for astronomical applications. It offers a great help to astronomical research topics such as astronomical image processing, moving target extraction, space target orbit calculation, numerical cosmology, cosmology simulation, galaxy fluid simulation. Thus it provides an important information support for the research work of 3 major breakthroughs and 5 key cultivation directions in the "One Three Five" plan of Purple Mountain Observatory.

DOI 10.11648/j.ajist.20200402.12
Published in American Journal of Information Science and Technology ( Volume 4, Issue 2, June 2020 )
Page(s) 30-40
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

HPC, GPU, Cluster, Parallel Storage, Portal Batch System

References
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  • APA Style

    Yang Zherui, Gao Na, Liu Liang. (2020). Construction and Management of Astronomical Big Data Analysis and Multi-dimensional Information Visualization Platform. American Journal of Information Science and Technology, 4(2), 30-40. https://doi.org/10.11648/j.ajist.20200402.12

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    ACS Style

    Yang Zherui; Gao Na; Liu Liang. Construction and Management of Astronomical Big Data Analysis and Multi-dimensional Information Visualization Platform. Am. J. Inf. Sci. Technol. 2020, 4(2), 30-40. doi: 10.11648/j.ajist.20200402.12

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    AMA Style

    Yang Zherui, Gao Na, Liu Liang. Construction and Management of Astronomical Big Data Analysis and Multi-dimensional Information Visualization Platform. Am J Inf Sci Technol. 2020;4(2):30-40. doi: 10.11648/j.ajist.20200402.12

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  • @article{10.11648/j.ajist.20200402.12,
      author = {Yang Zherui and Gao Na and Liu Liang},
      title = {Construction and Management of Astronomical Big Data Analysis and Multi-dimensional Information Visualization Platform},
      journal = {American Journal of Information Science and Technology},
      volume = {4},
      number = {2},
      pages = {30-40},
      doi = {10.11648/j.ajist.20200402.12},
      url = {https://doi.org/10.11648/j.ajist.20200402.12},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ajist.20200402.12},
      abstract = {The development of modern astronomy is rapidly and astronomical data increases exponentially. The HPC architecture based on GPU provides an efficient way of astronomic big data computing. Based on secure Ipv6 network environment, PMO has constructed the Big Data Analysis and Multi-dimensional Information Visualization Platform, which can reach the peak computing speed of 352Tflops and the totally storage capacity of 288TB. The platform is composed of 25 computing nodes, one management node and 5 storage nodes. The use of user-friendly, centralized cluster management software, the deployment of proprietary environmental control settings and multi-dimensional visualization of safety management systems form a multi-level, tridimensional and efficient management structure. A high-speed, high-capacity, highly reliable, secure and efficient high-performance computing cluster is finally constructed. The platform has a fully redundant, self-healing, highly scalable distributed storage system, a high-performance InfiniBand parallel computing and storage network, a complete job scheduling system, a cuda parallel computing architecture, and a variety of physical software tools for astronomical applications. It offers a great help to astronomical research topics such as astronomical image processing, moving target extraction, space target orbit calculation, numerical cosmology, cosmology simulation, galaxy fluid simulation. Thus it provides an important information support for the research work of 3 major breakthroughs and 5 key cultivation directions in the "One Three Five" plan of Purple Mountain Observatory.},
     year = {2020}
    }
    

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  • TY  - JOUR
    T1  - Construction and Management of Astronomical Big Data Analysis and Multi-dimensional Information Visualization Platform
    AU  - Yang Zherui
    AU  - Gao Na
    AU  - Liu Liang
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    T2  - American Journal of Information Science and Technology
    JF  - American Journal of Information Science and Technology
    JO  - American Journal of Information Science and Technology
    SP  - 30
    EP  - 40
    PB  - Science Publishing Group
    SN  - 2640-0588
    UR  - https://doi.org/10.11648/j.ajist.20200402.12
    AB  - The development of modern astronomy is rapidly and astronomical data increases exponentially. The HPC architecture based on GPU provides an efficient way of astronomic big data computing. Based on secure Ipv6 network environment, PMO has constructed the Big Data Analysis and Multi-dimensional Information Visualization Platform, which can reach the peak computing speed of 352Tflops and the totally storage capacity of 288TB. The platform is composed of 25 computing nodes, one management node and 5 storage nodes. The use of user-friendly, centralized cluster management software, the deployment of proprietary environmental control settings and multi-dimensional visualization of safety management systems form a multi-level, tridimensional and efficient management structure. A high-speed, high-capacity, highly reliable, secure and efficient high-performance computing cluster is finally constructed. The platform has a fully redundant, self-healing, highly scalable distributed storage system, a high-performance InfiniBand parallel computing and storage network, a complete job scheduling system, a cuda parallel computing architecture, and a variety of physical software tools for astronomical applications. It offers a great help to astronomical research topics such as astronomical image processing, moving target extraction, space target orbit calculation, numerical cosmology, cosmology simulation, galaxy fluid simulation. Thus it provides an important information support for the research work of 3 major breakthroughs and 5 key cultivation directions in the "One Three Five" plan of Purple Mountain Observatory.
    VL  - 4
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Author Information
  • Information Technology Center, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing, China

  • Information Technology Center, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing, China

  • Information Technology Center, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing, China

  • Section