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Construction and application of LHAASO data processing platform

Radiation Detection Technology and Methods (2022)Cite this article

Abstract

Purpose

The LHAASO project collects trillions of cosmic ray events every year, generating about 10 PB of raw data annually, which brings big challenges for data processing platform.

Method

The LHAASO data processing platform is built to handle such a large amount of data, which is composed of some subsystems such as data transfer, data storage, high throughput computing and metadata management.

Results and conclusions

The platform was under construction since 2018 and has been working well since 2021. In this paper, the details of the design, implementation and performance of the data processing platform are presented.

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Acknowledgements

This work is supported by National Nature Science Foundation of China (Grant Nos. 12075268, 12175255, 12175258, 12105300), the Chinese Academy of Science, Institute of High Energy Physics.

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Authors and Affiliations

  1. Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, 100049, China

    Yaodong Cheng, Haibo Li, Yujiang Bi, Jingyan Shi, Shan Zeng, Hongmei Zhang, Ge Ou, Mengyao Qi, Qiuling Yao & Yaosong Cheng

  2. TIANFU Cosmic Ray Research Center, Chengdu, 610213, China

    Yaodong Cheng & Yujiang Bi

  3. University of Chinese Academy of Sciences, Beijing, 100049, China

    Yaodong Cheng

Authors
  1. Yaodong Cheng
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  2. Haibo Li
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  3. Yujiang Bi
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  4. Jingyan Shi
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  5. Shan Zeng
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  6. Hongmei Zhang
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  7. Ge Ou
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  8. Mengyao Qi
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  9. Qiuling Yao
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  10. Yaosong Cheng
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Corresponding author

Correspondence to Haibo Li.

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On behalf of all authors, the corresponding author states that there is no conflict of interest.

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Cite this article

Cheng, Y., Li, H., Bi, Y. et al. Construction and application of LHAASO data processing platform. Radiat Detect Technol Methods (2022). https://doi.org/10.1007/s41605-022-00328-2

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  • DOI: https://doi.org/10.1007/s41605-022-00328-2

Keywords

  • LHAASO
  • Data processing platform
  • Data storage and management
  • High-performance computing
  • Metadata management