User view

1
Ganga simplifying use of the Grid F.Brochu1,
U.Egede2, J.Elmsheuser3, B.Gaidioz4, K.Harrison1,
B.Koblitz4, H.C.Lee5,D.Liko4, A.Maier4,
J.T.Moscicki4, A.Muraru4, V.Romanovsky6,A.Soroko7,
C.L.Tan8 1University of Cambridge, 2Imperial
College London, 3Ludwig-Maximilians-Universität
München,4CERN, 5ASGC Taipei, 6IHEP Protvino,
7University of Oxford, 8University of Birmingham
http//cern.ch/ganga/
HEP Computing
Uniform User Interface
Worldwide Resources
GANGA
Scope Ganga is an easy-to-use frontend for job
definition and management, implemented in Python.
It is being developed to meet the needs of the
ATLAS and LHCb experiments for a Grid user
interface, but offers possibilities for extension
and customisation that make it interesting for a
wide range of user communities. ATLAS and LHCb
will investigate various aspects of particle
production and decay in high-energy proton-proton
interactions at the Large Hadron Collider (LHC),
due to start operation at the European Laboratory
for Particle Physics (CERN), Geneva, towards the
end of 2007. Both experiments will require
processing of data volumes of the order of
petabytes per year, and will rely on computing
resources distributed across multiple locations.
The experiments data-processing applications,
from event modelling to physics analysis, are
based on the Gaudi/Athena C framework. Ganga
(Gaudi/Athena and Grid Alliance), deals with
configuring these applications, allows simple
switching between testing on a local batch system
and large-scale processing on the Grid, and helps
keep track of results.
User view Ganga classes and functions can be
used interactively at a Python prompt, can be
referenced in scripts, or can be used indirectly
via a Graphical User Interface (GUI). The GUI
consists of a main panel, which displays job
information, and three dockable windows - windows
that can be hidden, integrated in the main panel,
or floated separately. The dockable windows
provide for job building, for execution of
arbitrary Ganga/Python commands, and for the
logging of system messages.
Scriptor
Job details
Job representation A job in Ganga is constructed
from a set of building blocks. All jobs must
specify the software to be run (application) and
the processing system (backend) to be used. Many
jobs will specify an input dataset to be read
and/or an output dataset to be produced.
Optionally, a job may also define functions
(splitters and mergers) for dividing a job into
subjobs that can be processed in parallel, and
for combining the resultant outputs. Ganga
provides a framework for handling different types
of application, backend, dataset, splitter and
merger, implemented as plug-in classes. Each of
these has its own schema, which places in
evidence the configurable properties.
Logical Folders
Job Monitoring
Job builder
Log window
Ganga tutorials for ATLAS and LHCb have been held
at locations including Bologna, Cambridge, CERN,
Edinburgh, Lyon, Milan, Mumbai and Munich, and
online guides to getting started with Ganga are
also available. Tutorials and guides have been
key factors in stimulating Ganga take-up, with
more than 300 Ganga users recorded.
Ganga Tutorials at National e-Science Centre,
Edinburgh
Tutorial for LHCb, January 2007
Tutorial for ATLAS, February 2007

• Other projects using Ganga
• In addition to its use in ATLAS and LHCb, Ganga
  is finding application in a growing number of
  other projects, both as a standalone tool and as
  submission engine and monitoring system for the
  DIANE job-distribution framework. The Ganga user
  groups include
• other high-energy physics experiments Compass,
  Harp
• teams developing detector simulations Garfield,
  Geant4
• biomedical projects med-austron, projects
  researching Avian flue
• projects involving image processing Cambridge
  Ontology, Xmipp
• chemistry project WIEN2k
• telecomunications industry International
  Telecommunication Union (ITU)

5 May 2006
The ITU Regional Radio Conference, held in Geneva
in May-June 2006, required real-time optimisation
of evolving plans for sharing frequencies between
120 countries. The aim was to maximise the
number of satisfied requests, and minimise
interference. Ganga/DIANE was used to run the
optimisation jobs on the Grid.
Job statistics from Ganga
Use of the Grid to search for drugs against avian
flu was widely reported. About one eighth of the
Grid jobs were submitted using Ganga/DIANE
Cambridge Ontology is developing solutions for
image retrieval based on image content.
Regression tests for Geant4 major releases
require a few years of CPU, concentrated in a
short time. These tests are run on the Grid using
Ganga/DIANE.
Plug-in classes specialised for the required
image-processing tasks have been implemented, and
are used with Ganga to submit jobs to the Grid.