Cargando…

Reinforcing User Data Analysis with Ganga in the LHC Era: Scalability, Monitoring and User-support

Ganga is a grid job submission and management system widely used in the ATLAS and LHCb experiments and several other communities in the context of the EGEE project. The particle physics communities have entered the LHC operation era which brings new challenges for user data analysis: a strong growth...

Descripción completa

Detalles Bibliográficos
Autores principales: Brochu, F, Dzhunov, I, Ebke, J, Egede, U, Elmsheuser, J, Jha, M K, Kokoszkiewicz, L, Lee, H C, Maier, A, Moscicki, J, Munchen, T, Reece, W, Samset, B, Slater, M, Tuckett, D, Van der Ster, D, Williams, M
Lenguaje:eng
Publicado: 2010
Materias:
Acceso en línea:http://cds.cern.ch/record/1298835
_version_ 1780921001822912512
author Brochu, F
Dzhunov, I
Ebke, J
Egede, U
Elmsheuser, J
Jha, M K
Kokoszkiewicz, L
Lee, H C
Maier, A
Moscicki, J
Munchen, T
Reece, W
Samset, B
Slater, M
Tuckett, D
Van der Ster, D
Williams, M
author_facet Brochu, F
Dzhunov, I
Ebke, J
Egede, U
Elmsheuser, J
Jha, M K
Kokoszkiewicz, L
Lee, H C
Maier, A
Moscicki, J
Munchen, T
Reece, W
Samset, B
Slater, M
Tuckett, D
Van der Ster, D
Williams, M
author_sort Brochu, F
collection CERN
description Ganga is a grid job submission and management system widely used in the ATLAS and LHCb experiments and several other communities in the context of the EGEE project. The particle physics communities have entered the LHC operation era which brings new challenges for user data analysis: a strong growth in the number of users and jobs is already noticable. Current work in the Ganga project is focusing on dealing with these challenges. In recent Ganga releases the support for the pilot job based grid systems Panda and Dirac of the ATLAS and LHCb experiment respectively have been strengthened. A more scalable job repository architecture, which allows efficient storage of many thousands of jobs in XML or several database formats, was recently introduced. A better integration with monitoring systems, including the Dashboard and job execution monitor systems is underway. These will provide comprehensive and easy job monitoring. A simple to use error reporting tool integrated at the Ganga command-line will help to improve user support and debugging user problems. Ganga is a mature, stable and widely-used tool with long-term support from the HEP community. We report on how it is being constantly improved following the user needs for faster and easier distributed data analysis on the grid.
id cern-1298835
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2010
record_format invenio
spelling cern-12988352019-09-30T06:29:59Zhttp://cds.cern.ch/record/1298835engBrochu, FDzhunov, IEbke, JEgede, UElmsheuser, JJha, M KKokoszkiewicz, LLee, H CMaier, AMoscicki, JMunchen, TReece, WSamset, BSlater, MTuckett, DVan der Ster, DWilliams, MReinforcing User Data Analysis with Ganga in the LHC Era: Scalability, Monitoring and User-supportDetectors and Experimental TechniquesGanga is a grid job submission and management system widely used in the ATLAS and LHCb experiments and several other communities in the context of the EGEE project. The particle physics communities have entered the LHC operation era which brings new challenges for user data analysis: a strong growth in the number of users and jobs is already noticable. Current work in the Ganga project is focusing on dealing with these challenges. In recent Ganga releases the support for the pilot job based grid systems Panda and Dirac of the ATLAS and LHCb experiment respectively have been strengthened. A more scalable job repository architecture, which allows efficient storage of many thousands of jobs in XML or several database formats, was recently introduced. A better integration with monitoring systems, including the Dashboard and job execution monitor systems is underway. These will provide comprehensive and easy job monitoring. A simple to use error reporting tool integrated at the Ganga command-line will help to improve user support and debugging user problems. Ganga is a mature, stable and widely-used tool with long-term support from the HEP community. We report on how it is being constantly improved following the user needs for faster and easier distributed data analysis on the grid.ATL-SOFT-SLIDE-2010-363oai:cds.cern.ch:12988352010-10-11
spellingShingle Detectors and Experimental Techniques
Brochu, F
Dzhunov, I
Ebke, J
Egede, U
Elmsheuser, J
Jha, M K
Kokoszkiewicz, L
Lee, H C
Maier, A
Moscicki, J
Munchen, T
Reece, W
Samset, B
Slater, M
Tuckett, D
Van der Ster, D
Williams, M
Reinforcing User Data Analysis with Ganga in the LHC Era: Scalability, Monitoring and User-support
title Reinforcing User Data Analysis with Ganga in the LHC Era: Scalability, Monitoring and User-support
title_full Reinforcing User Data Analysis with Ganga in the LHC Era: Scalability, Monitoring and User-support
title_fullStr Reinforcing User Data Analysis with Ganga in the LHC Era: Scalability, Monitoring and User-support
title_full_unstemmed Reinforcing User Data Analysis with Ganga in the LHC Era: Scalability, Monitoring and User-support
title_short Reinforcing User Data Analysis with Ganga in the LHC Era: Scalability, Monitoring and User-support
title_sort reinforcing user data analysis with ganga in the lhc era: scalability, monitoring and user-support
topic Detectors and Experimental Techniques
url http://cds.cern.ch/record/1298835
work_keys_str_mv AT brochuf reinforcinguserdataanalysiswithgangainthelhcerascalabilitymonitoringandusersupport
AT dzhunovi reinforcinguserdataanalysiswithgangainthelhcerascalabilitymonitoringandusersupport
AT ebkej reinforcinguserdataanalysiswithgangainthelhcerascalabilitymonitoringandusersupport
AT egedeu reinforcinguserdataanalysiswithgangainthelhcerascalabilitymonitoringandusersupport
AT elmsheuserj reinforcinguserdataanalysiswithgangainthelhcerascalabilitymonitoringandusersupport
AT jhamk reinforcinguserdataanalysiswithgangainthelhcerascalabilitymonitoringandusersupport
AT kokoszkiewiczl reinforcinguserdataanalysiswithgangainthelhcerascalabilitymonitoringandusersupport
AT leehc reinforcinguserdataanalysiswithgangainthelhcerascalabilitymonitoringandusersupport
AT maiera reinforcinguserdataanalysiswithgangainthelhcerascalabilitymonitoringandusersupport
AT moscickij reinforcinguserdataanalysiswithgangainthelhcerascalabilitymonitoringandusersupport
AT munchent reinforcinguserdataanalysiswithgangainthelhcerascalabilitymonitoringandusersupport
AT reecew reinforcinguserdataanalysiswithgangainthelhcerascalabilitymonitoringandusersupport
AT samsetb reinforcinguserdataanalysiswithgangainthelhcerascalabilitymonitoringandusersupport
AT slaterm reinforcinguserdataanalysiswithgangainthelhcerascalabilitymonitoringandusersupport
AT tuckettd reinforcinguserdataanalysiswithgangainthelhcerascalabilitymonitoringandusersupport
AT vandersterd reinforcinguserdataanalysiswithgangainthelhcerascalabilitymonitoringandusersupport
AT williamsm reinforcinguserdataanalysiswithgangainthelhcerascalabilitymonitoringandusersupport