Operational Experience and R&D results using the Google Cloud for High Energy Physics in the ATLAS experiment
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arXiv
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| Autori principali: | , , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866929407421054976 |
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| author | Megino, Fernando Barreiro De, Kaushik Elmsheuser, Johannes Klimentov, Alexei Lassnig, Mario Euell, Miles Hartmann, Nikolai Maeno, Tadashi Outschoorn, Verena Martinez Sandesara, Jay Ajitbhai Sell, Dustin |
| author_facet | Megino, Fernando Barreiro De, Kaushik Elmsheuser, Johannes Klimentov, Alexei Lassnig, Mario Euell, Miles Hartmann, Nikolai Maeno, Tadashi Outschoorn, Verena Martinez Sandesara, Jay Ajitbhai Sell, Dustin |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_15873 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Operational Experience and R&D results using the Google Cloud for High Energy Physics in the ATLAS experiment Megino, Fernando Barreiro De, Kaushik Elmsheuser, Johannes Klimentov, Alexei Lassnig, Mario Euell, Miles Hartmann, Nikolai Maeno, Tadashi Outschoorn, Verena Martinez Sandesara, Jay Ajitbhai Sell, Dustin High Energy Physics - Experiment 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. |
| title | Operational Experience and R&D results using the Google Cloud for High Energy Physics in the ATLAS experiment |
| topic | High Energy Physics - Experiment |
| url | https://arxiv.org/abs/2403.15873 |