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CERN Document Server	20 のレコードが見つかりました。 1 - 10 レコードへジャンプ：	検索にかかった時間： 0.72 秒

Modernizing ATLAS PanDA for a sustainable multi-experiment future / ATLAS Collaboration
In early 2024, ATLAS undertook an architectural review to evaluate the functionalities of its current components within the workflow and workload management ecosystem. Pivotal to the review was the assessment of the Production and Distributed Analysis (PanDA) system, which plays a vital role in the overall infrastructure. [...]
ATL-SOFT-SLIDE-2024-537.- Geneva : CERN, 2024 - 10 p. Fulltext: PDF; External link: Original Communication (restricted to ATLAS)
In : 27th International Conference on Computing in High Energy & Nuclear Physics, Kraków, Pl, 19 - 25 Oct 2024

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Software and computing for Run 3 of the ATLAS experiment at the LHC / ATLAS Collaboration
The ATLAS experiment has developed extensive software and distributed computing systems for Run 3 of the LHC. [...]
arXiv:2404.06335 ; CERN-EP-2024-100. - 2024 - 175.
Fulltext - Previous draft version - Fulltext

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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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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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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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Utilizing Distributed Heterogeneous Computing with PanDA in ATLAS / ATLAS Collaboration
In recent years, advanced and complex analysis workflows have gained increasing importance in the ATLAS experiment at CERN, one of the large scientific experiments at the Large Hadron Collider (LHC). Support for such workflows has allowed users to exploit remote computing resources and service providers distributed worldwide, overcoming limitations on local resources and services. [...]
ATL-SOFT-SLIDE-2023-156.- Geneva : CERN, 2023 - 14 p. Fulltext: PDF; External link: Original Communication (restricted to ATLAS)
In : 26th International Conference on Computing in High Energy & Nuclear Physics, Norfolk, Virginia, Us, 8 - 12 May 2023

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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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10.

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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似た著者名：
31	Lin, F
1	Lin, F C
1	Lin, F F
1	Lin, F H
10	Lin, F K
26	Lin, F L
1	Lin, F S
1	Lin, F U
19	Lin, F Y
8	Lin, F-K.
9	Lin, F-L.
3	Lin, F.
1	Lin, F.-H.
1	Lin, F.L.
12	Lin, Fahui
1	Lin, Fang
1	Lin, Fang-Pang
1	Lin, Fang-hua
5	Lin, Fanghua
3	Lin, Fanglei
1	Lin, Feiyu
2	Lin, Felix Xiaozhu
6	Lin, Feng
2	Lin, Feng-Cheng
33	Lin, Feng-Li
2	Lin, Fong-Kay
1	Lin, Fou-Lai
1	Lin, Francesco
2	Lin, Fu
8	Lin, Fu-Yuan
10	Lin, Fucai
1	Lin, Fuchun

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