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

Yang Zherui; Gao Na; Liu Liang

doi:doi:10.11648/j.ajist.20200402.12

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

Yang Zherui, Gao Na, Liu Liang

Published in American Journal of Information Science and Technology (Volume 4, Issue 2)

Received: 10 March 2020 Accepted: 9 April 2020 Published: 29 April 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.

Published in	American Journal of Information Science and Technology (Volume 4, Issue 2)
DOI	10.11648/j.ajist.20200402.12
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), 2020. Published by Science Publishing Group

Keywords

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

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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://article.sciencepublishinggroup.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
Y1  - 2020/04/29
PY  - 2020
N1  - https://doi.org/10.11648/j.ajist.20200402.12
DO  - 10.11648/j.ajist.20200402.12
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
IS  - 2
ER  -

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Author Information

Yang Zherui

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

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

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

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Plain Text BibTeX RIS

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

Copy | Download

@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://article.sciencepublishinggroup.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}
}

Copy | Download

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
Y1  - 2020/04/29
PY  - 2020
N1  - https://doi.org/10.11648/j.ajist.20200402.12
DO  - 10.11648/j.ajist.20200402.12
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
IS  - 2
ER  -

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