Speaker
Description
The Jiangmen Underground Neutrino Observatory (JUNO) commenced physics data taking in August 2025, marking the transition from commissioning to full-scale operation of its Distributed Computing Infrastructure (DCI) system for real physics data. This contribution presents the Monte Carlo production and physics production experience accumulated during the first year of data taking.
We provide an overview of the production workflow, detailing the integration of the DCI system with the JUNO offline processing pipelines. We report production features and status, and describe the system’s operational mechanism. Moreover, we will mention the adjustment of the computing model to meet the need of physics analysis in this period. We will highlight the challenges and bottlenecks we met during reconstruction, including unforeseen network constraints, and higher-than-expected I/O demands, and the targeted mitigations are made accordingly.
These improvements have significantly boosted system reliability and throughput. The lessons learned offer critical guidance for sustaining long-term JUNO computing operations and optimizing service deployment strategies.