Speaker
Description
The calibration of Belle II data involves two key processes: prompt
calibration and reprocessing. Prompt calibration represents the initial
step in continuously deriving calibration constants in a timely manner for
the data collected over the previous couple of weeks. Currently, this process
is managed by b2cal, a Python-based plugin built on Apache
Airflow to handle calibration jobs. However, b2cal is a complex
system with many interconnected components, introducing usability and maintenance challenges.
To address these limitations, a new prototype system called
b2luca (b2LUigi CAlibration) is under
development. Built on b2luigi, a helper package for Spotify's Luigi for scheduling large workflows on a batch system, b2luca centralizes
all prompt calibration processes at the Belle II calibration center
hosted at the Scientific Data and Computing Center of the Brookhaven
National Laboratory (BNL). Here, all calibration tasks are executed
either in parallel or sequentially, depending on their dependencies, and the results
are stored in a centralized database. The system ensures robust
validation.
Instead of relying on a custom web interface, b2luca leverages GitLab
for managing workflows, collecting expert feedback, and tracking
calibration tasks. This integration not only simplifies the workflow but
also fosters collaboration through GitLab's version control and
issue-tracking features.
By running all calibration tasks directly on one site and incorporating
an efficient workflow scheduler, b2luca aims to provide a scalable,
user-friendly, and reliable solution for managing calibration pipelines
in the Belle II experiment.
| Experiment context, if any | Belle II |
|---|
