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October 8, 2025EPJ Web of ConferencesOpen Access

Keep-up Production in JUNO’s Offline Data Processing

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Authors

WYWeiqing YinTLT. LinYZYizhou Zhang

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Overview

This paper reveals the KUP pipeline’s architecture and automation for offline data processing in JUNO, suggesting enhancements for data visualization and management.

Key Points

  • The KUP pipeline streamlines offline data processing, addressing the challenges of data volume and complexity.
  • Key components include job management, real-time monitoring, and data visualization, enhancing operational efficiency.
  • The architecture is designed for scalability, utilizing modern web technologies to support massive data handling.
  • Automation and modularity play crucial roles in the KUP pipeline, allowing for improved workflow and system management.

Cite This Study

Yin et al. (2025) studied this question.

synapsesocial.com/papers/68e62de1a8c0c6d45873fd63https://doi.org/10.1051/epjconf/202533701176
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Keep-up Production in JUNO’s Offline Data Processing2025
  2. 2Offline data processing in the First JUNO Data Challenge2024
  3. 3Monitoring System for JUNO Distributed Computing Infrastructure and Services2026
  4. 4Construction and Commissioning of the JUNO detector2025
  5. 5Detector design and current status of JUNO experiment2024 · 1 citations