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ATLAS & Google — "Data Ocean" R&D Project
ATLAS is facing several challenges with respect to their computing requirements for LHC Run-3 (2020-2023) and HL-LHC runs (2025-2034). The challenges are not specific for ATLAS or/and LHC, but common for HENP computing community. Most importantly, storage continues to be the driving cost factor and...
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Lenguaje: | eng |
Publicado: |
2017
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Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2299146 |
Sumario: | ATLAS is facing several challenges with respect to their computing requirements for LHC Run-3 (2020-2023) and HL-LHC runs (2025-2034). The challenges are not specific for ATLAS or/and LHC, but common for HENP computing community. Most importantly, storage continues to be the driving cost factor and at the current growth rate cannot absorb the increased physics output of the experiment. Novel computing models with a more dynamic use of storage and computing resources need to be considered. This project aims to start an R&D project for evaluating and adopting novel IT technologies for HENP computing. ATLAS and Google plan to launch an R&D project to integrate Google cloud resources (Storage and Compute) to the ATLAS distributed computing environment. After a series of teleconferences, a face-to-face brainstorming meeting in Denver, CO at the Supercomputing 2017 conference resulted in this proposal for a first prototype of the "Data Ocean" project. The idea is threefold: (a) to allow ATLAS to explore the use of different computing models to prepare for High-Luminosity LHC, (b) to allow ATLAS user analysis to benefit from the Google infrastructure, and (c) to give Google real science use cases to improve their cloud platform. |
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