Frontiers of Data and Computing ›› 2022, Vol. 4 ›› Issue (1): 97-112.

doi: 10.11871/jfdc.issn.2096-742X.2022.01.008

• Special Issue: Union of National Scientific Data Center • Previous Articles     Next Articles

Distributed Data Processing Platform of National High Energy Physics Data Center

SHI Jingyan(),HUANG Qiulan(),Wang Lu(),LI Haibo(),DU Ran(),JIANG Xiaowei(),HU Qingbao(),ZHENG Wei(),Yan Xiaofei(),ZHANG Xuantong()   

  1. Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
  • Received:2021-10-08 Online:2022-02-20 Published:2022-03-04
  • Contact: SHI Jingyan E-mail:jingyan.shi@ihep.ac.cn;huangql@ihep.ac.cn;lu.wang@ihep.ac.cn;lihaibo@ihep.ac.cn;duran@ihep.ac.cn;jiangxw@ihep.ac.cn;huqb@ihep.ac.cn;zhengw@ihep.ac.cn;yanxf@ihep.ac.cn;zhangxuantong@ihep.ac.cn

Abstract:

[Objective] This paper introduces the distributed data processing platform of the National High Energy Physics Data Center (NHEPDC). It also provides a reference for data processing in the HEP and related science experiments. [Methods] This paper introduces the composition, key technologies, and intelligent operation of the distributed data processing platform of NHEPDC. By analyzing the characteristics and actual requirements of high energy physics data processing, the paper introduces the strategy of "one platform and multiple centers" for construction of the distributed data processing platform in the data center and elaborates the realization of cross-regional resource sharing, high performance data access, and user interaction data processing. [Results] The paper enumerates two examples of support for high-energy physics experiments on the distributed data processing platform of NHEPDC to facilitate the acquisition of scientific research results. [Conclusions] The distributed data processing platform of NHEPDC has become an important infrastructure and composition of high energy physics, the main place to integrate new research methods. It meets the computing needs of particle physics, theoretical physics, space astronomy, ray science, accelerator design, and other scientific research fields.

Key words: distributed data processing platform, cross-regional resource sharing, high performance computing, high throughput computing