Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Marco Mambelli"'
Publikováno v:
HPDC
High Energy Physics (HEP) experiments entail an abundance of computing resources, i.e. sites, to run simulations and analyses by processing data. This requirement is fulfilled by local batch farms, grid sites, private/commercial clouds, and supercomp
Autor:
Namratha Urs, Marco Mambelli
Publikováno v:
GlideinWMS's use of cvmfsexec.
Autor:
Marco Mambelli, Dennis Box
Publikováno v:
GlideinWMS and IAM.
Publikováno v:
EPJ Web of Conferences, Vol 251, p 02012 (2021)
GlideinWMS is a pilot framework to provide uniform and reliable HTCondor clusters using heterogeneous resources. The Glideins are pilot jobs that are sent to the selected nodes, test them, set them up as desired by the user jobs, and ultimately start
Autor:
Julia Andreeva, Lorena Lobato Pardavila, Panos Paparrigopoulos, Alexey Anisenkov, Marian Zvada, Krista Majewski, Edita Kizinevič, Marco Mascheroni, James Letts, Bruno Coimbra, Alessandro Di Girolamo, Saqib Haleem, Marco Mambelli, Antonio María Pérez-Calero Yzquierdo, Dennis Box, J M Dost
Publikováno v:
EPJ Web of Conferences, Vol 245, p 03023 (2020)
24th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2019), University Adelaide, Adelaide, Australia, November 04-08, 2019, EDP Sciences, 2020, art. no. 03023, p. [1-8]
24th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2019), University Adelaide, Adelaide, Australia, November 04-08, 2019, EDP Sciences, 2020, art. no. 03023, p. [1-8]
GlideinWMS is a workload management and provisioning system that allows sharing computing resources distributed over independent sites. Based on the requests made by GlideinWMS frontends, a dynamically sized pool of resources is created by GlideinWMS
Publikováno v:
Cluster Computing; Jan2004, Vol. 7 Issue 1, p7-19, 13p
Autor:
Marco Mambelli
Publikováno v:
HEPCloud: provisioning heterogeneous resources using GlideinWMS and HTCondor.
Autor:
Marco Mambelli
Publikováno v:
HEPCloud, an elastic virtual cluster from heterogeneous computing resources.