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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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Seamless integration of commercial Clouds with ATLAS Distributed Computing
/ Elmsheuser, Johannes (Brookhaven National Laboratory (US)) ; Barreiro Megino, Fernando Harald (University of Texas at Arlington (US)) ; Bawa, Harinder Singh (California State University (US)) ; De, Kaushik (University of Texas at Arlington (US)) ; Klimentov, Alexei (Brookhaven National Laboratory (US)) ; Lassnig, Mario (CERN) ; Serfon, Cedric (Brookhaven National Laboratory (US)) ; Wegner, Tobias (Bergische Universitaet Wuppertal (DE))
/ATLAS Collaboration
The CERN ATLAS Experiment successfully uses a worldwide distributed computing Grid infrastructure to support its physics programme at the Large Hadron Collider (LHC). The Grid workflow system PanDA routinely manages up to 700'000 concurrently running production and analysis jobs to process simulation and detector data. [...]
ATL-SOFT-SLIDE-2021-130.-
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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ATLAS data analysis using a parallelized workflow on distributed cloud-based services with GPUs
/ Sandesara, Jay Ajitbhai (Amherst College (US)) ; Coelho Lopes De Sa, Rafael (University of Massachusetts (US)) ; Martinez Outschoorn, Verena Ingrid (University of Massachusetts (US)) ; Barreiro Megino, Fernando Harald (University of Texas at Arlington (US)) ; Elmsheuser, Johannes (Brookhaven National Laboratory (US)) ; Klimentov, Alexei (Brookhaven National Laboratory (US))
/ATLAS Collaboration
We present a new implementation of simulation-based inference using data collected by the ATLAS experiment at the LHC. The method relies on large ensembles of deep neural networks to approximate the exact likelihood. [...]
ATL-SOFT-SLIDE-2023-169.-
Geneva : CERN, 2023
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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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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The ATLAS experiment software on ARM
/ Elmsheuser, Johannes (Brookhaven National Laboratory (US)) ; Barreiro Megino, Fernando Harald (University of Texas at Arlington (US)) ; De Salvo, Alessandro (Sapienza Universita e INFN, Roma I (IT)) ; De Silva, Asoka (TRIUMF (CA)) ; Hauser, Reiner (Michigan State University (US)) ; Konstantinov, Dmitri (Institute for High Energy Physics of NRC Kurchatov Institute (RU)) ; Krasznahorkay, Attila (CERN) ; Lassnig, Mario (CERN) ; Sailer, Andre (CERN) ; Snyder, Scott (Brookhaven National Laboratory (US))
With an increased dataset obtained during the Run-3 of the LHC at CERN and the even larger expected increase of the dataset by more than one order of magnitude for the HL-LHC, the ATLAS experiment is reaching the limits of the current data processing model in terms of traditional CPU resources based on x86\_64 architectures and an extensive program for software upgrades towards the HL-LHC has been set up. [...]
ATL-SOFT-PROC-2023-008.
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2024 - 6.
Original Communication (restricted to ATLAS) - Full text
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