Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Lin, FaHui"'
Autor:
Guan, Wen, Maeno, Tadashi, Bockelman, Brian Paul, Wenaus, Torre, Lin, Fahui, Padolski, Siarhei, Zhang, Rui, Alekseev, Aleksandr
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 sys
Externí odkaz:
http://arxiv.org/abs/2103.00523
Autor:
Guan Wen, Maeno Tadashi, Zhang Rui, Weber Christian, Wenaus Torre, Alekseev Aleksandr, Barreiro Megino Fernando Harald, De Kaushik, Karavakis Edward, Klimentov Alexei, Korchuganova Tatiana, Lin FaHui, Nilsson Paul, Yang Zhaoyu, Zhao Xin
Publikováno v:
EPJ Web of Conferences, Vol 295, p 04019 (2024)
Machine Learning (ML) 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
Externí odkaz:
https://doaj.org/article/608883bf64c14d22838a5f744d88400c
Autor:
Karavakis Edward, Guan Wen, Yang Zhaoyu, Maeno Tadashi, Wenaus Torre, Adelman-McCarthy Jennifer, Barreiro Megino Fernando, De Kaushik, Dubois Richard, Gower Michelle, Jenness Tim, Klimentov Alexei, Korchuganova Tatiana, Kowalik Mikolaj, Lin FaHui, Nilsson Paul, Padolski Sergey, Yang Wei, Ye Shuwei
Publikováno v:
EPJ Web of Conferences, Vol 295, p 04026 (2024)
The Vera C. Rubin Observatory will produce an unprecedented astronomical data set for studies of the deep and dynamic universe. Its Legacy Survey of Space and Time (LSST) will image the entire southern sky every three to four days and produce tens of
Externí odkaz:
https://doaj.org/article/068a5638eed64ab38002535ea3c6926c
Autor:
Maeno Tadashi, Alekseev Aleksandr, Barreiro Megino Fernando Harald, De Kaushik, Guan Wen, Karavakis Edward, Klimentov Alexei, Korchuganova Tatiana, Lin FaHui, Nilsson Paul, Wenaus Torre, Yang Zhaoyu, Zhao Xin
Publikováno v:
EPJ Web of Conferences, Vol 295, p 04053 (2024)
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 LHC. Support for such workflows has allowed users to exploit remote computing resou
Externí odkaz:
https://doaj.org/article/b409fdefb93649849c9a152318be75ba
Autor:
Barreiro Megino Fernando, Borodin Mikhail, De Kaushik, Elmsheuser Johannes, Di Girolamo Alessandro, Hartmann Nikolai, Heinrich Lukas, Klimentov Alexei, Lassnig Mario, Lin FaHui, Maeno Tadashi, Marshall Zachary, Merino Gonzalo, Nilsson Paul, Sandesara Jay, Serfon Cedric, South David, Singh Harinder
Publikováno v:
EPJ Web of Conferences, Vol 295, p 07002 (2024)
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&
Externí odkaz:
https://doaj.org/article/d4d0706a45be45738f4e82b285a2a385
Autor:
Maeno, Tadashi, Alekseev, Aleksandr, Barreiro Megino, Fernando Harald, De, Kaushik, Guan, Wen, Karavakis, Edward, Klimentov, Alexei, Korchuganova, Tatiana, Lin, FaHui, Nilsson, Paul, Wenaus, Torre, Yang, Zhaoyu, Zhao, Xin
Publikováno v:
Computing & Software for Big Science; 1/23/2024, Vol. 8 Issue 1, p1-21, 21p
Autor:
Barreiro Megino Fernando Harald, Albert Jeffrey Ryan, Berghaus Frank, De Kaushik, Lin FaHui, MacDonell Danika, Maeno Tadashi, Da Rocha Ricardo Brito, Seuster Rolf, Taylor Ryan Paul, Yang Ming-Jyuan
Publikováno v:
EPJ Web of Conferences, Vol 245, p 07025 (2020)
In recent years containerization has revolutionized cloud environments, providing a secure, lightweight, standardized way to package and execute software. Solutions such as Kubernetes enable orchestration of containers in a cluster, including for the
Externí odkaz:
https://doaj.org/article/3521943fa10a46a59318a7a52c5c8bc6
Autor:
Barreiro Megino Fernando Harald, Alekseev Aleksandr, Berghaus Frank, Cameron David, De Kaushik, Filipcic Andrej, Glushkov Ivan, Lin FaHui, Maeno Tadashi, Magini Nicolò
Publikováno v:
EPJ Web of Conferences, Vol 245, p 03010 (2020)
ATLAS Computing Management has identified the migration of all computing resources to Harvester, PanDA’s new workload submission engine, as a critical milestone for LHC Run 3 and 4. This contribution will focus on the Grid migration to Harvester. W
Externí odkaz:
https://doaj.org/article/d4d016cb59cc40e0bc7ff3b4ddfd37e4
Autor:
Maeno Tadashi, Barreiro Megino Fernando Harald, Benjamin Doug, Cameron David, Childers John Taylor, De Kaushik, De Salvo Alessandro, Filipcic Andrej, Hover John, Lin FaHui, Oleynik Danila
Publikováno v:
EPJ Web of Conferences, Vol 214, p 03030 (2019)
The Production and Distributed Analysis (PanDA) system has been successfully used in the ATLAS experiment as a data-driven workload management system. The PanDA system has proven to be capable of operating at the Large Hadron Collider data processing
Externí odkaz:
https://doaj.org/article/ef1e65f3d7f84bb3a4fca3359ae2d27d
Autor:
Doglioni, C., Kim, D., Stewart, G.A., Silvestris, L., Jackson, P., Kamleh, W., Barreiro Megino, Fernando Harald, Albert, Jeffrey Ryan, Berghaus, Frank, De, Kaushik, Lin, FaHui, MacDonell, Danika, Maeno, Tadashi, Da Rocha, Ricardo Brito, Seuster, Rolf, Taylor, Ryan Paul, Yang, Ming-Jyuan
Publikováno v:
EPJ Web of Conferences; 11/16/2020, Vol. 245, p1-7, 7p