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SciWIND: Effectively Exploiting Node-Local Storage for Data-Intensive High-Energy Physics Workflows

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Τίτλος: SciWIND: Effectively Exploiting Node-Local Storage for Data-Intensive High-Energy Physics Workflows
Συγγραφείς: Zhou, Jin, Thomas, Colin, Sly-Delgado, Barry, Moore, Connor, Tovar, Benjamin, Lannon, Kevin, Thain, Douglas
Πηγή: 2026 IEEE International Parallel and Distributed Processing Symposium (IPDPS) IPDPS Parallel and Distributed Processing Symposium (IPDPS), 2026 IEEE International. :498-512 May, 2026
Relation: 2026 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
Βάση Δεδομένων: IEEE Xplore Digital Library
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PubType: Conference
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  Data: 2026 IEEE International Parallel and Distributed Processing Symposium (IPDPS) IPDPS Parallel and Distributed Processing Symposium (IPDPS), 2026 IEEE International. :498-512 May, 2026
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1109/IPDPS65963.2026.00050
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        PageCount: 15
        StartPage: 498
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      – TitleFull: SciWIND: Effectively Exploiting Node-Local Storage for Data-Intensive High-Energy Physics Workflows
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            NameFull: Zhou, Jin
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            NameFull: Thomas, Colin
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            NameFull: Sly-Delgado, Barry
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            NameFull: Moore, Connor
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            NameFull: Tovar, Benjamin
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            NameFull: Lannon, Kevin
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            NameFull: Thain, Douglas
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              Type: published
              Y: 2026
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            – TitleFull: 2026 IEEE International Parallel and Distributed Processing Symposium (IPDPS), Parallel and Distributed Processing Symposium (IPDPS), 2026 IEEE International, IPDPS
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