Description
Any physicist who will analyse data from the LHC experiments will have to deal with
data and computing resources which are distributed across multiple locations and with
different access methods. GANGA helps the end user by tying in specifically to the
solutions for a given experiment ranging from specification of data to retrieval and
post-processing of produced output. For LHCb and ATLAS the main goal is to assist in
running jobs based on the Gaudi/Athena C++ framework. GANGA is written in Python and
presents the user with a single GUI rather than a set of different applications. It
interacts with external resources like experiments bookkeeping databases, job
configuration, and Grid submission systems through plug-able modules. The user is
upon start-up presented with a list of templates for common analysis tasks and GANGA
persists information about ongoing tasks between invocations. GANGA can also be used
through a command line interface that has a tight connection to the GUI to ease the
transition from one to the other. Examples will be presented that demonstrates the
integration into the distributed analysis systems of the LHCb and ATLAS experiments
as used during their 2004 data challenges.
Primary authors
A. Maier
(CERN)
A. Soroko
(Oxford University)
C.L. Tan
(Birmingham University)
D. Adams
(BNL)
G.N. Patrick
(RAL)
J. Martyniak
(Imperial College London)
J. Moscicki
(CERN)
K. Harrison
(Cambridge University)
P. Charpentier
(CERN)
P. Mato
(CERN)
R. Jones
(Lancaster University)
U. Egede
(IMPERIAL COLLEGE LONDON)
