2025/01/01 by Kati Lassila-Perini, Tom Cordruwisch, Subash Jayawardhana Pathiranage · 1 voice
Computer Science · Decision Sciences · #Advanced Data Storage Technologies #Distributed and Parallel Computing Systems #Scientific Computing and Data Management
paper · pdf · doi:10.1051/epjconf/202533701020
openalex publication_date 2025/01/01 · openalex created_date 2025/10/07 · openalex updated_date 2026/07/29
The CMS experiment at the Large Hadron Collider (LHC) regularly releases open data and simulations, enabling a wide range of physics analyses and studies by the global scientific community. The recent introduction of the NanoAOD data format has provided a streamlined and efficient approach to data processing, allowing for fast analysis turnaround. However, the larger MiniAOD format retains richer information that may be crucial for certain types of analyses. This work explores the potential of using public cloud resources for the computationally intensive processing of the MiniAOD format, for which many open data users may not have the necessary computing resources. With a scalable cloud infrastructure, researchers can benefit from increased processing power in their data analysis workflows, with a moderate short-term cost. This study investigates best practices and challenges for efficiently utilizing public cloud platforms to handle the processing of CMS MiniAOD data, with a focus on quantifying the overall time and cost of using these resources. The results indicate that the technical implementation of a typical CMS open data workflow in a public cloud environemnt is smooth, and the processing can be done with a reasonable overall cost and time.