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CERN Document Server Намерени са 2,023 записа  1 - 10следващкрай  отиване на запис: Търсенето отне 0.50 секунди. 
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Distributed Machine Learning with PanDA and iDDS in LHC ATLAS / ATLAS Collaboration
Machine learning has become one of the important tools for High Energy Physics analysis. As the size of the dataset increases at the Large Hadron Collider (LHC), and at the same time the search spaces become bigger and bigger in order to exploit the physics potentials, more and more computing resources are required for processing these machine learning tasks. [...]
ATL-SOFT-SLIDE-2023-128.- Geneva : CERN, 2023 - 12 p. Fulltext: PDF; External link: Original Communication (restricted to ATLAS)
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A Function-as-a-Task Workflow Management Approach with PanDA and iDDS / ATLAS Collaboration
The growing complexity of high energy physics analysis often involves running various distinct applications. [...]
ATL-SOFT-PROC-2024-001. - 2024. - 7 p.
Original Communication (restricted to ATLAS) - Full text
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A Function-as-a-Task Workflow Management Approach with PanDA and iDDS / ATLAS Collaboration
The growing complexity of high energy physics analysis often involves running a large number of different tools. This demands a multi-step data processing approach, with each step requiring different resources and carrying dependencies on preceding steps. [...]
ATL-SOFT-SLIDE-2024-037.- Geneva : CERN, 2024 - 21 p. Fulltext: PDF; External link: Original Communication (restricted to ATLAS)
In : 22nd International Workshop on Advanced Computing and Analysis Techniques in Physics Research, Stony Brook, Us, 11 - 15 Mar 2024
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Distributed Machine Learning Workflow with PanDA and iDDS in LHC ATLAS / ATLAS Collaboration
Machine Learning (ML) has become one of the important tools for High Energy Physics analysis. [...]
ATL-SOFT-PROC-2023-010. - 2024 - 6.
Original Communication (restricted to ATLAS) - Full text
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An intelligent Data Delivery Service for and beyond the ATLAS Experiment / Guan, Wen (University of Wisconsin Madison (US)) ; Maeno, Tadashi (Brookhaven National Laboratory (US)) ; Bockelman, Brian Paul (University of Wisconsin Madison (US)) ; Wenaus, Torre (Brookhaven National Laboratory (US)) ; Lin, Fa-Hui (University of Texas at Arlington (US)) ; Padolski, Siarhei (Brookhaven National Laboratory (US)) ; Zhang, Rui (University of Wisconsin Madison (US)) ; Alekseev, Aleksandr (Universidad Andres Bello (CL)) ; Barreiro Megino, Fernando Harald (University of Texas at Arlington (US)) /ATLAS Collaboration
The intelligent Data Delivery Service (iDDS) has been developed to cope with the huge increase of computing and storage resource usage in the coming LHC data taking. iDDS has been designed to intelligently orchestrate workflow and data management systems, decoupling data pre-processing, delivery, and main processing in various workflows. [...]
ATL-SOFT-SLIDE-2021-120.- Geneva : CERN, 2021 - 11 p. Fulltext: PDF; External link: Original Communication (restricted to ATLAS)
In : 25th International Conference on Computing in High-Energy and Nuclear Physics (CHEP), Online, Online, 17 - 21 May 2021
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intelligent Data Delivery Service (iDDS) / Bockelman, Brian Paul (University of Wisconsin Madison (US)) ; Barreiro Megino, Fernando Harald (University of Texas at Arlington (US)) ; Guan, Wen (University of Wisconsin Madison (US)) ; Lin, Fa-Hui (University of Texas at Arlington (US)) ; Maeno, Tadashi (Brookhaven National Laboratory (US)) ; Weber, Christian (Brookhaven National Laboratory (US)) ; Wenaus, Torre (Brookhaven National Laboratory (US)) ; Zhang, Rui (University of Wisconsin Madison (US)) /ATLAS Collaboration
The intelligent Data Delivery Service (iDDS) has been developed to cope with the huge increase of computing and storage resource usage in the coming LHC data taking. It has been designed to intelligently orchestrate workflow and data management systems, decoupling data pre-processing, delivery, and primary processing in large scale workflows. [...]
ATL-SOFT-SLIDE-2022-249.- Geneva : CERN, 2022 - 15 p. Fulltext: PDF; External link: Original Communication (restricted to ATLAS)
In : 41st International Conference on High Energy Physics (ICHEP 2022), Bologna, Italy, 6 - 13 Jul 2022, pp.ATL-SOFT-SLIDE-2022-249
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intelligent Data Delivery Service (iDDS) / Guan, Wen (University of Wisconsin Madison (US)) ; Maeno, Tadashi (Brookhaven National Laboratory (US)) ; Padolski, Siarhei (Brookhaven National Laboratory (US)) ; Bockelman, Brian Paul (University of Wisconsin Madison (US)) ; Wenaus, Torre (Brookhaven National Laboratory (US)) ; Barreiro Megino, Fernando Harald (University of Texas at Arlington (US)) ; Lin, Fa-Hui (University of Texas at Arlington (US)) ; Zhang, Rui (University of Wisconsin Madison (US)) /ATLAS Collaboration
The intelligent Data Delivery Service (iDDS) has been developed to cope with the huge increase of computing and storage resource usage in the coming LHC data taking. It has been designed to intelligently orchestrate workflow and data management systems, decoupling data pre-processing, delivery, and main processing in various workflows. [...]
ATL-SOFT-SLIDE-2022-001.- Geneva : CERN, 2022 - 1 p. Fulltext: PDF; External link: Original Communication (restricted to ATLAS)
In : 30th International Symposium on Lepton Photon Interactions at High Energies, Manchester, Gb, 10 - 14 Jan 2022
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An intelligent Data Delivery Service for and beyond the ATLAS experiment / Guan, Wen (Brookhaven National Laboratory (US)) ; Maeno, Tadashi (Brookhaven National Laboratory (US)) ; Bockelman, Brian Paul (University of Wisconsin Madison (US)) ; Wenaus, Torre (Brookhaven National Laboratory (US)) ; Zhang, Rui (University of Wisconsin Madison (US)) ; Weber, Christian (Brookhaven National Laboratory (US)) ; Barreiro Megino, Fernando Harald (University of Texas at Arlington (US)) ; Lin, Fa-Hui (University of Texas at Arlington (US)) ; Alekseev, Aleksandr (Universidad Andres Bello (CL))
The intelligent Data Delivery Service (iDDS) has been developed to cope with the huge increase of computing and storage resource usage in the coming LHC data taking. [...]
ATL-SOFT-PROC-2022-004. - 2022. - 5 p.
Original Communication (restricted to ATLAS) - Full text
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Accelerating science: the usage of commercial clouds in ATLAS distributed computing / ATLAS Collaboration
The ATLAS experiment at CERN is one of the largest scientific machines built to date and will have ever growing computing needs as the Large Hadron Collider collects an increasingly larger volume of data over the next 20 years. ATLAS is conducting R&D; projects on Amazon and Google clouds as complementary resources for distributed computing, focusing on some of the key features of commercial clouds: lightweight operation, elasticity and availability of multiple chip architectures. [...]
ATL-SOFT-SLIDE-2023-151.- Geneva : CERN, 2023 - 13 p. Fulltext: PDF; External link: Original Communication (restricted to ATLAS)
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Accelerating science: the usage of commercial clouds in ATLAS Distributed Computing / ATLAS Collaboration
The ATLAS experiment at CERN is one of the largest scientific ma- chines built to date and will have ever growing computing needs as the Large Hadron Collider collects an increasingly larger volume of data over the next 20 years. [...]
ATL-SOFT-PROC-2023-020. - 2024 - 11.
Original Communication (restricted to ATLAS) - Full text
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