Speaker
Dr
Andrew Maier
(CERN)
Description
Ganga (http://cern.ch/ganga) is a job-management tool that offers a simple, efficient and consistent user experience in a variety of heterogeneous environments: from local clusters to global Grid systems. Experiment specific plugins allow Ganga to be customised for each experiment. This paper will describe these LHCb plugins of Ganga. For LHCb users, Ganga is the job submission tool of choice to the Grid as the LHCb specific plugins allow support for end-to-end analysis helping the user to perform his complete analysis with the help of Ganga. This starts with the support for data selection, where a user can select datasets from the LHCb Bookkeeping system. Followed by the setup for large analysis jobs with tailored plugins for the LHCb core software where jobs can be managed by the splitting of these analysis jobs with the subsequent merging of the result files. Furthermore, Ganga offers support for Toy Monte-Carlos to help the user tune their analysis. In addition, to describing the Ganga architecture, typical usage patters within LHCb and experience with the updated LHCb DIRAC 3 WMS will be shown.
| Presentation type (oral | poster) | oral |
|---|
Author
Dr
Andrew Maier
(CERN)
Co-authors
Adrian Muraru
(University of Bucarest)
Alexander Soroko
(University of Oxford)
Benjamin Gaidioz
(CERN)
Bjørn Samset
(University of Oslo)
Chun Lik Tan
(University of Birmingham)
Daniel van der Ster
(CERN)
Dietrich Liko
(Institut für Hochenergiephysik Wien)
Frederic Brochu
(University of Cambridge)
Greg Cowan
(University of Edinburgh)
Hurng-Chun Lee
(NIKHEF)
Jakub Moscicki
(CERN)
Johannes Elmsheuser
(Ludwig-Maximilians-Universität München)
Karl Harrison
(University of Birmingham)
Katarina Pajchel
(University of Oslo)
Mark Slater
(University of Birmingham)
Mike Williams
(Imperial College)
Ulrik Egede
(Imperial College)
Vladimir Romanovsky
(IHEP)
Will Reece
(Imperial College)
