Leveraging public cloud resources for the processing of CMS open data

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.

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Publication Details

Journal
EPJ Web of Conferences
Published
2025-01-01
DOI
https://doi.org/10.1051/epjconf/202533701020
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Leveraging public cloud resources for the processing of CMS open data

Kati Lassila-Perini, Tom Cordruwisch, Subash Jayawardhana Pathiranage
EPJ Web of Conferences
Distributed and Parallel Computing Systems
article

Leveraging public cloud resources for the processing of CMS open data

Kati Lassila-Perini, Tom Cordruwisch, Subash Jayawardhana Pathiranage
article en

Abstract

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.

EPJ Web of ConferencesVol. 337
Helsinki Institute of Physics (FI), Lapland University of Applied Sciences (FI)
CERN
Openalex Percentile: Top 68%
Distributed and Parallel Computing Systems
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