Analysis demonstrates the performance of Hyperloop in data processing for collider experiments, suggesting improvements for future applications.
This paper presents an analysis of operational experience with the Hyperloop train system, a framework designed for organized grid data processing in the ALICE experiment at CERN’s Large Hadron Collider (LHC) in Run 3. Hyperloop orchestrates distributed computing resources using a web-based interface that structures analyses as sequential workflows called trains. The system integrates automated resource estimation, validation, and submission mechanisms providing also version control and dataset comparison tools. The application of this operational experience to the development of analysis train systems for the MPD experiment at the NICA collider is discussed.
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V. N. Kovalenko (2026) studied this question.
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