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* [[{{{1}}}:Administration|Administration]]
* [[{{{1}}}:Administration|Administration]]
Direct access to resources for '''{{{1}}}''''s site:
Direct access to resources for '''{{{1}}}''''s site:
* [https://helpdesk.grid5000.fr/oar/{{{urlname|{{{1}}}}}}/monika.cgi reservation state] and [https://helpdesk.grid5000.fr/oar/{{{1}}}/DrawOARGantt.pl reservation history] via OAR
* [https://helpdesk.grid5000.fr/oar/{{{urlname|{{{1}}}}}}/monika.cgi reservation state] and [https://helpdesk.grid5000.fr/oar/{{{urlname|{{{1}}}}}}/DrawOARGantt.pl reservation history] via OAR
* [https://helpdesk.grid5000.fr/ganglia/?c={{{1}}} available resources] via Ganglia
* [https://helpdesk.grid5000.fr/ganglia/?c={{{urlname|{{{1}}}}}} available resources] via Ganglia
* [https://helpdesk.grid5000.fr/nagios/cgi-bin/status.cgi?hostgroup={{{nagios_group}}}&style=overview critical services] via Nagios
* [https://helpdesk.grid5000.fr/nagios/cgi-bin/status.cgi?hostgroup={{{nagios_group}}}&style=overview critical services] via Nagios
* '''{{Template:Open bugs|{{{1}}}|opened bugs}} via BugZilla'''
* '''{{Template:Open bugs|{{{urlname|{{{1}}}}}}|opened bugs}} via BugZilla'''
* [mailto:{{{1}}}-staff_AT_lists_DOT_grid5000_DOT_fr {{{1}}}-staff] via mail
* [mailto:{{{nagios_group|{{{1}}}}}}-staff_AT_lists_DOT_grid5000_DOT_fr {{{nagios_group|{{{1}}}}}}-staff] via mail
Shortcuts to global tools and informations:
Shortcuts to global tools and informations:
* [[Support|support procedures]] to report bugs or ask for enhancements
* [[Support|support procedures]] to report bugs or ask for enhancements
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* [https://helpdesk.grid5000.fr/admin/phpldapadmin/ registered users] via phpLDAPadmin
* [https://helpdesk.grid5000.fr/admin/phpldapadmin/ registered users] via phpLDAPadmin
Latest updated publications
Latest updated publications
{{#publications: 5|{{{1}}}}}
{{#publications: 5|{{{nagios_group|{{{1}}}}}}}}
Latest updated experiments
Latest updated experiments
{{#experiments: 5|{{{1}}}}}
{{#experiments: 5|{{{nagios_group|{{{1}}}}}}}}


{{{misc}}}
{{{misc}}}
{{Site link|Home}}
{{Site link|Home}}

Revision as of 16:22, 23 July 2009

Specific informations of {{{1}}}'s site:

  • [[{{{1}}}:Hardware|Hardware]]
  • [[{{{1}}}:Network|Network]]
  • [[{{{1}}}:Storage|Storage]]
  • [[{{{1}}}:External access|External access]]
  • [[{{{1}}}:People|People]]
  • [[{{{1}}}:Roadmap|Roadmap]]
  • [[{{{1}}}:Logs|Logs]]
  • [[{{{1}}}:Administration|Administration]]

Direct access to resources for {{{1}}}'s site:

Shortcuts to global tools and informations:

Latest updated publications Five random publications that benefited from Grid'5000 (at least 2945 overall):

  • Cédric Prigent, Melvin Chelli, Alexandru Costan, Loïc Cudennec, René Schubotz, et al.. Efficient Resource-Constrained Federated Learning Clustering with Local Data Compression on the Edge-to-Cloud Continuum. HiPC 2024 - 31st IEEE International Conference on High Performance Computing, Data, and Analytics, Dec 2024, Bengaluru (Bangalore), India. pp.1-11, 10.1109/HiPC62374.2024.00033. hal-04779813 view on HAL pdf
  • Mai Huong Do, Millian Poquet, Georges da Costa. FedE-ator : A framework for energy consumption analysis of federated learning in distributed systems. Compas’2025 : Parallélisme / Architecture/ Système, Jul 2025, Bordeaux, France. hal-05181877 view on HAL pdf
  • Alan Lira Nunes, Cristina Boeres, Lúcia Maria de A. Drummond, Laércio Lima Pilla. Optimal Time and Energy-Aware Client Selection Algorithms for Federated Learning on Heterogeneous Resources. 2024 IEEE 36th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), Nov 2024, Hilo, France. pp.148-158, 10.1109/SBAC-PAD63648.2024.00021. hal-04690494v2 view on HAL pdf
  • Théophile Bastian. Towards automatic characterization of microarchitectural behaviour form performance modeling of computing kernels : an analysis of the Cortex A72 and Intel microarchitectures. Hardware Architecture cs.AR. Université Grenoble Alpes 2020-.., 2024. English. NNT : 2024GRALM072. tel-05116111 view on HAL pdf
  • Rahma Hellali, Zaineb Chelly Dagdia, Karine Zeitouni. A Multi-Objective Multi-Agent Interactive Deep Reinforcement Learning Approach for Feature Selection. International conference on neural information processing, Dec 2024, Auckland (Nouvelle Zelande), New Zealand. pp.15. hal-04723314 view on HAL pdf

Latest updated experiments {{#experiments: 5|{{{1}}}}}

{{{misc}}}