Abstract
The distributed data analysis using Grid resources is one of the funda-
mental 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 adminis-
trators to potentially all participating physicists.
The GANGA job management system (http://cern.ch/ganga), devel-
oped as a common project between the ATLAS and LHCb experiments
provides and integrates these kind of tools. GANGA provides a sim-
ple 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 and interaction with the
ATLAS data management system DQ2/DDM into GANGA is a key
functionality. In combination with the job splitting mechanism large
amounts of analysis 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.
