Sep 2 – 9, 2007
Victoria, Canada
Europe/Zurich timezone
Please book accomodation as soon as possible.

Distributed Analysis using GANGA on the EGEE/LCG infrastructure

Sep 3, 2007, 3:20 PM
20m
Saanich (Victoria, Canada)

Saanich

Victoria, Canada

oral presentation Distributed data analysis and information management Distributed data analysis and information management

Speaker

Dr Johannes Elmsheuser (Ludwig-Maximilians-Universität München)

Description

The distributed data analysis using Grid resources is one of the fundamental applications in high energy physics to be addressed and realized before the start of LHC data taking. The needs to manage the resources are very high. In every experiment up to a thousand physicist will be submitting analysis jobs into the Grid. Appropriate user interfaces and helper applications have to be made available to assure that all users can use the Grid without too much expertise in Grid technology. These tools enlarge the number of grid users from a few production administrators to potentially all participating physicists. The GANGA job management system (http://cern.ch/ganga), developed as a common project between the ATLAS and LHCb experiments provides and integrates these kind of tools. GANGA provides a simple and consistent way of preparing, organizing and executing analysis tasks within the experiment analysis framework, implemented through a plug-in system. It allows trivial switching between running test jobs on a local batch system and running large-scale analyzes on the Grid, hiding Grid technicalities. We will be reporting on the plug-ins and our experiences of distributed data analysis using GANGA within the ATLAS experiment and the EGEE/LCG infrastructure. The integration with the ATLAS data management system DQ2 into GANGA is a key functionality. In combination with the job splitting mechanism large amounts of jobs can be sent to the locations of data following the ATLAS computing model. GANGA supports tasks of user analysis with reconstructed data and small scale production of Monte Carlo data.
Submitted on behalf of Collaboration (ex, BaBar, ATLAS) ATLAS Offline Computing

Primary author

Dr Johannes Elmsheuser (Ludwig-Maximilians-Universität München)

Co-authors

Mr Adrian Muraru (CERN) Dr Alexander Soroko (University of Oxford) Dr Benjamin Gaidioz (CERN) Mr Chun Lik Tan (University of Birmingham) Dr Dietrich Liko (CERN) Mr Frederic Brochu (University of Cambridge) Mr Hurng-Chung Lee (ASGC, Taipei and CERN) Mr Jakub Moscicki (CERN) Mr Karl Harrison (High Energy Physics Group, Cavendish Laboratory) Dr Ulrik Egede (Imperial College London) Mr Vladimir Romanovsky (State Res. Center of Russian Feder. Inst. f. High Energy Phys. (IFVE))

Presentation materials