{ "id": "2403.15873", "version": "v1", "published": "2024-03-23T15:44:29.000Z", "updated": "2024-03-23T15:44:29.000Z", "title": "Operational Experience and R&D results using the Google Cloud for High Energy Physics in the ATLAS experiment", "authors": [ "Fernando Barreiro Megino", "Kaushik De", "Johannes Elmsheuser", "Alexei Klimentov", "Mario Lassnig", "Miles Euell", "Nikolai Hartmann", "Tadashi Maeno", "Verena Martinez Outschoorn", "Jay Ajitbhai Sandesara", "Dustin Sell" ], "comment": "21 pages, 8 figures", "categories": [ "hep-ex" ], "abstract": "The ATLAS experiment at CERN relies on a worldwide distributed computing Grid infrastructure to support its physics program at the Large Hadron Collider. ATLAS has integrated cloud computing resources to complement its Grid infrastructure and conducted an R&D program on Google Cloud Platform. These initiatives leverage key features of commercial cloud providers: lightweight configuration and operation, elasticity and availability of diverse infrastructure. This paper examines the seamless integration of cloud computing services as a conventional Grid site within the ATLAS workflow management and data management systems, while also offering new setups for interactive, parallel analysis. It underscores pivotal results that enhance the on-site computing model and outlines several R&D projects that have benefited from large-scale, elastic resource provisioning models. Furthermore, this study discusses the impact of cloud-enabled R\\&D projects in three domains: accelerators and AI/ML, ARM CPUs and columnar data analysis techniques.", "revisions": [ { "version": "v1", "updated": "2024-03-23T15:44:29.000Z" } ], "analyses": { "keywords": [ "high energy physics", "google cloud", "atlas experiment", "operational experience", "distributed computing grid infrastructure" ], "note": { "typesetting": "TeX", "pages": 21, "language": "en", "license": "arXiv", "status": "editable" } } }