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R&D in ATLAS Distributed Computing towards HL-LHC
The computing challenges at HL-LHC require fundamental changes to the distributed computing models that have served experiments well throughout LHC. ATLAS planning for HL-LHC computing started back in 2020 with a Conceptual Design Report outlining various challenges to explore. This was followed in...
Autores principales: | , , |
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Lenguaje: | eng |
Publicado: |
2023
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Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2857628 |
Sumario: | The computing challenges at HL-LHC require fundamental changes to the distributed computing models that have served experiments well throughout LHC. ATLAS planning for HL-LHC computing started back in 2020 with a Conceptual Design Report outlining various challenges to explore. This was followed in 2022 by a roadmap defining concrete milestones and associated effort required. Today, ATLAS is proceeding further with a set of "demonstrators" with focused R&D in specific topics described in the roadmap. The demonstrators cover areas such as optimized tape writing and access, data recreation on-demand and the use of commercial clouds. This paper presents an overview of the demonstrators, detailing the plans, timelines and expected impact of the work. |
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