Zobrazeno 1 - 10
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pro vyhledávání: '"Ejarque, Jorge"'
Autor:
de Parga, S. Ares, Bravo, J. R., Sibuet, N., Hernandez, J. A., Rossi, R., Boschert, Stefan, Quintana-Ortí, Enrique S., Tomás, Andrés E., Tatu, Cristian Cătălin, Vázquez-Novoa, Fernando, Ejarque, Jorge, Badia, Rosa M.
The integration of Reduced Order Models (ROMs) with High-Performance Computing (HPC) is critical for developing digital twins, particularly for real-time monitoring and predictive maintenance of industrial systems. This paper describes a comprehensiv
Externí odkaz:
http://arxiv.org/abs/2409.09080
Autor:
Abdulah, Sameh, Ejarque, Jorge, Marzouk, Omar, Ltaief, Hatem, Sun, Ying, Genton, Marc G., Badia, Rosa M., Keyes, David E.
HPC-based applications often have complex workflows with many software dependencies that hinder their portability on contemporary HPC architectures. In addition, these applications often require extraordinary efforts to deploy and execute at performa
Externí odkaz:
http://arxiv.org/abs/2312.07748
Autor:
Cantini, Riccardo, Marozzo, Fabrizio, Orsino, Alessio, Talia, Domenico, Trunfio, Paolo, Badia, Rosa M., Ejarque, Jorge, Vazquez, Fernando
Publikováno v:
Journal of Big Data, vol. 11, n. 19, 2024
The extensive use of HPC infrastructures and frameworks for running dataintensive applications has led to a growing interest in data partitioning techniques and strategies. In fact, application performance can be heavily affected by how data are part
Externí odkaz:
http://arxiv.org/abs/2211.10819
Autor:
Ejarque, Jorge, Andrio, Pau, Hospital, Adam, Conejero, Javier, Lezzi, Daniele, Gelpi, Josep LL., Badia, Rosa M.
Publikováno v:
2022 IEEE 18th International Conference on e-Science (e-Science)
Developing complex biomolecular workflows is not always straightforward. It requires tedious developments to enable the interoperability between the different biomolecular simulation and analysis tools. Moreover, the need to execute the pipelines on
Externí odkaz:
http://arxiv.org/abs/2208.14130
Autor:
Ejarque, Jorge, Badia, Rosa M., Albertin, Loïc, Aloisio, Giovanni, Baglione, Enrico, Becerra, Yolanda, Boschert, Stefan, Berlin, Julian R., D'Anca, Alessandro, Elia, Donatello, Exertier, François, Fiore, Sandro, Flich, José, Folch, Arnau, Gibbons, Steven J, Koldunov, Nikolay, Lordan, Francesc, Lorito, Stefano, Løvholt, Finn, Macías, Jorge, Marozzo, Fabrizio, Michelini, Alberto, Monterrubio-Velasco, Marisol, Pienkowska, Marta, de la Puente, Josep, Queralt, Anna, Quintana-Ortí, Enrique S., Rodríguez, Juan E., Romano, Fabrizio, Rossi, Riccardo, Rybicki, Jedrzej, Kupczyk, Miroslaw, Selva, Jacopo, Talia, Domenico, Tonini, Roberto, Trunfio, Paolo, Volp, Manuela
Publikováno v:
Future Generation Computer Systems, Volume 134, Pages 414-429, ISSN 0167-739X, Elsevier, 2022
The evolution of High-Performance Computing (HPC) platforms enables the design and execution of progressively larger and more complex workflow applications in these systems. The complexity comes not only from the number of elements that compose the w
Externí odkaz:
http://arxiv.org/abs/2204.09287
Autor:
Abdulah, Sameh, Ejarque, Jorge, Marzouk, Omar, Ltaief, Hatem, Sun, Ying, Genton, Marc G., Badia, Rosa M., Keyes, David E.
Publikováno v:
In Future Generation Computer Systems December 2024 161:248-258
Storage systems have not kept the same technology improvement rate as computing systems. As applications produce more and more data, I/O becomes the limiting factor for increasing application performance. I/O congestion caused by concurrent access to
Externí odkaz:
http://arxiv.org/abs/2111.01504
This paper tries to reduce the effort of learning, deploying, and integrating several frameworks for the development of e-Science applications that combine simulations with High-Performance Data Analytics (HPDA). We propose a way to extend task-based
Externí odkaz:
http://arxiv.org/abs/2007.04939
Autor:
Badia, Rosa M, Ejarque, Jorge, Lordan, Francesc, Lezzi, Daniele, Conejero, Javier, Cid-Fuentes, Javier Álvarez, Becerra, Yolanda, Queralt, Anna
Publikováno v:
Proceedings of 2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS)
Progress in science is deeply bound to the effective use of high-performance computing infrastructures and to the efficient extraction of knowledge from vast amounts of data. Such data comes from different sources that follow a cycle composed of pre-
Externí odkaz:
http://arxiv.org/abs/2006.07066
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