TY - GEN
T1 - Reinforcing user data analysis with Ganga in the LHC era
T2 - International Conference on Computing in High Energy and Nuclear Physics, CHEP 2010
AU - Elmsheuser, Johannes
AU - Brochu, Frederic
AU - Dzhunov, Ivan
AU - Ebke, Johannes
AU - Egede, Ulrik
AU - Jha, Manoj Kumar
AU - Kokoszkiewicz, Lukasz
AU - Lee, Hurng Chun
AU - Maier, Andrew
AU - Mościcki, Jakub
AU - München, Tim
AU - Reece, Will
AU - Samset, Bjorn
AU - Slater, Mark
AU - Tuckett, David
AU - Vanderster, Daniel
AU - Williams, Michael
PY - 2011/12/23
Y1 - 2011/12/23
N2 - 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 noticeable. 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.
AB - 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 noticeable. 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.
UR - http://www.scopus.com/inward/record.url?scp=84863233977&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/331/7/072011
DO - 10.1088/1742-6596/331/7/072011
M3 - Conference Paper
AN - SCOPUS:84863233977
VL - 331
T3 - Journal of Physics: Conference Series
BT - Journal of Physics: Conference Series
Y2 - 18 October 2010 through 22 October 2010
ER -