Experience with distributed analysis in LHCb
Author: Dr. EGEDE, Ulrik (IMPERIAL COLLEGE LONDON)
Track: Distributed Data Analysis
Physics analysis of large amounts of data by many users requires the usage of Grid resources. It is however important that users can see a single environment for developing and testing algorithms locally and for running on large data samples on the Grid. The Ganga job wizard, developed by LHCb and ATLAS, provides physicists such an integrated environment for job preparation, bookkeeping and archiving, job splitting and merging and allows job submission to a large variety of back-ends. Ganga can be used from a python Command Line Interface, from python scripts or from a GUI. The LHCb baseline back-end for accessing Grid resources is the DIRAC Workload Management System. The DIRAC Workload Management system implements many advanced methods to minimize the response time for the user analysis jobs as well as to maximize the success rate of user tasks. It provides an easy way for clients to securely submit and monitor their jobs and to retreive the results. We present here the experience of using Ganga for submitting analysis jobs to the Grid through the DIRAC WMS, directly to LCG, and to a local batch system. Performances of the various back-ends are compared.
Last modified Wed 7 December 2005 . View page history
Switch to HTTPS . Website Help . Print View . Built with GridSite 1.4.3