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ATLAS Slides
Report number	ATL-SOFT-SLIDE-2010-363
Title	Reinforcing User Data Analysis with Ganga in the LHC Era: Scalability, Monitoring and User-support
Author(s)	Brochu, F (University of Cambridge) ; Dzhunov, I (CERN) ; Ebke, J (Ludwig-Maximilians-Universitat Munchen) ; Egede, U (Imperial College London) ; Elmsheuser, J (Ludwig-Maximilians-Universitat Munchen) ; Jha, M K (INFN Bologna) ; Kokoszkiewicz, L (CERN) ; Lee, H C (NIKHEF) ; Maier, A (CERN) ; Moscicki, J (CERN) ; Munchen, T (University of Wuppertal) ; Reece, W (Imperial College London) ; Samset, B (University of Oslo) ; Slater, M (University of Birmingham) ; Tuckett, D (CERN) ; Van der Ster, D (CERN) ; Williams, M (Imperial College London)
Corporate author(s)	The ATLAS collaboration
Submitted to	Conference on Computing in High Energy and Nuclear Physics 2010, Taipei, Taiwan, 18 - 22 Oct 2010
Submitted by	[email protected] on 11 Oct 2010
Subject category	Detectors and Experimental Techniques
Accelerator/Facility, Experiment	CERN LHC ; ATLAS
Abstract	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.