Ganga: a User-Grid Interface for ATLAS and LHCb

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Ganga a User-Grid Interface for ATLAS and LHCb
K. Harrison, P. Mato, A. Soroko and C. Tull

• Motivation and background
• Objectives and design
• Low-level tools
• High-level tools and GUI
• Future plans and conclusions

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Motivation and background

• ATLAS and LHCb develop applications within a
  common framework Gaudi/Athena
• Both collaborations aim to exploit potential of
  Grid for large-scale, data-intensive distributed
  computing

• Simplify management of analysis and production
  jobs for end-user physicists by developing tools
  for accessing Grid services with built-in
  knowledge of how Gaudi/Athena works Gaudi/Athena
  and Grid Alliance (GANGA)
• Generic tools interfacing to the Grid can be used
  at other experiments.

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Motivation and background

• First ideas for GANGA were presented in summer
  2001 (P.Mato and C.Tull)
• An Atlas/LHCb design team was set up, including
  US representatives

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Objectives and design

• The user interacts with a single application
  integrating all stages of job life-time.
• Modular design. Each module can be accessed via
  Python interface or is entirely written in
  Python.
• Although Atlas and LHCb use the same framework
  and the same software management tool, there are
  significant differences in what is expected from
  the software, and Ganga must have the flexibility
  to cope.
• Ganga provides a set of tools to manipulate jobs
  and data. Tools are accessible from CLI (other
  scripts) or from GUI.
• Ganga allows access both to the local resources
  (LSF batch system) and to the GRID.
• Should follow, and contribute to, developments in
  LCG.

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Required Functionality

• Job preparation and configuration
• Resource booking
• Job submission
• User can choose between Grid and local resource
  management system
• Job monitoring and control
• GUI for the resource browsing
• VO active services
• CEs
• SEs
• Query existing files in the Grid
• GUI for data management tools
• e.g., Dataset registration to the Grid (used by
  Production Manager)
• Copy file from a Computing Element to a Storage
  Element
• Replication of files

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Athena/Gaudi Architecture
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Ganga Python Bus Design
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Class Diagram of Ganga Core Module
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Ganga Job and Application Handlers
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Core Module Implementation

• Most of base classes are developed. Serialization
  of objects (user jobs) is implemented with the
  Python pickle module.
• GaudiApplicationHandler can access Configuration
  DB for some Gaudi applications (Brunel). It is
  implemented with the xmlrpclib module. Ganga can
  create user-customized Job Options files using
  this DB.
• DaVinci and AtlFast application handlers are in
  the last stage of development.
• LSFJobHandler is implemented. It allows to submit
  and to get simple monitoring information for a
  job at LSF batch system.
• Much of GRID-related functionality is already
  implemented in GridJobHandler using EDG testbed
  1.4 software. Ganga can submit, monitor, and get
  output from GRID jobs.
• JobsRegistry class provides jobs monitoring via
  multithreaded environment based on Python
  threading module

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EDG Grid Interface
Job Handler class
Job class
JobsRegistry class
Data management service
Job submission
Job monitoring
Security service
dg-job-list-match dg-job-submit dg-job-cancel
grid-proxy-init MyProxy
dg-job-status dg-job-get-logging-info GRM/PROVE
edg-replica-manager dg-job-get-output globus-url-c
opy GDMP
EDG UI
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Ganga low-level tools

• In Ganga, components used to define a job are
  mapped to Python classes.
• The low-level software needs to provide
  representations of the most basic components, and
  must allow flexibility in manipulating them.
• Users will have access to low-level data and
  methods at the command line, but in most cases
  shouldnt need them
• Low-level software works, but is preliminary.
• Some details of component representations and
  their interfaces are still being discussed by
  development team, but most of them have already
  been defined.

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Low-level tools Atlas example (AtlFast)
atlasSetup GangaCommand(source
/afs/cern.ch/user/h/harrison/public/atlasSetup.sh
) atlfast GangaCMTApplication(TestRelease,
TestRelease-00-00-15,athena.exe,
run/AtlasfastOptions.txt) atlfastO
utput GangaOutputFile(atlfast.ntup) workStep1
GangaWorkStep(atlasSetup,atlfast,atlfastOutput
) workFlow GangaWorkFlow(workStep1) lsfJob
GangaLSFJob(atlfastTest,workFlow) lsfJob.build()
lsfJob.run()
At this level, there is less built-in
intelligence than in ASK, but a lot of flexibility
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Low-level tools LHCb example (DaVinci)
lhcbSetup GangaCommand(source
/afs/cern.ch/lhcb/scripts/lhcbenv.sh) daVinciSet
up GangaCommand(source
/afs/cern.ch/lhcb/scripts/ProjectEnv.sh DaVinci
v7r2) daVinci GangaCMTApplication(Phys/DaVinc
i, v7r2,DaVinci.exe,
options/DaVinci.opts) daVinciOutput
GangaOutputFile(dvhistos.hbook) workStep1
GangaWorkStep(lhcbSetup,daVinciSetup,daVinci,
daVinciOutput) workFlow
GangaWorkFlow(workStep1) lsfJob
GangaLSFJob(daVinciTest,workFlow) lsfJob.build()
lsfJob.run()
Command sequences for Atlas and LHCb are very
similar
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Ganga high-level tools

• In Ganga, common tasks are realized via methods
  of job and application handler classes
  (JobHandler, ApplicationHandler and their
  subclasses).
• The low-level software needs to provide building
  blocks for these methods.
• High-level tools are available both at the
  command line and through a GUI.
• More advanced functionality will appear with the
  progress of low-level tools development.

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Ganga GUI Implementation

• GUI is created using wxPython extension module.
• All job configuration data are represented as a
  hierarchical structure accessible via tree
  control. Most important job parameters are
  brought to the top of the tree.
• All job parameters defined by the user can be
  edited via GUI dialogs.
• All implemented tools are available via GUI, but
  some of them require more elaborated interface,
  e.g., Job Options browser/editor.
• Python interpreter is embedded into the GUI and
  allows user to configure interface from the
  command line.

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GUI Snapshots
Embedded Python interpreter
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GUI Snapshots
Create a new job
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GUI Snapshots
Access Job (application) options downloaded from
DB
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GUI Snapshots
Define batch system
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GUI Snapshots
Define necessary resources
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GUI Snapshots
Submit the job (after configuration)
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GUI Snapshots
Job has been submitted successfully
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GUI Snapshots
Job monitoring has been started automatically
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GUI Snapshots
Standard output for the Hello World LSF job
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Future Plans and Conclusions

• One of the immediate plans is to complete
  implementation of Grid data management tools
  (interface to GDMP and replica-manager).
• Advanced Job Options Editor should be developed
  and integrated with Ganga.
• We plan to add new job handlers, e.g., for PBS
  and for local PC.
• While we assume that basic LHCb software is
  available at worker nodes, we cant require the
  same for the user code. Therefore the possibility
  to build user software remotely with Ganga should
  be investigated.
• Web-based variant of GUI (or thin remote client)
  should be considered. Some questions remain
  related to the security issues, but we can try
  Globus PyCoG to overcome these problems.
• We plan to investigate possibilities for
  exploiting Grid Monitoring Architecture in Ganga.
• Code for the Ganga package can be obtained from
  Gaudi CVS repository.
• More information about GANGA development can be
  found in the web site http//ganga.web.cern.ch/gan
  ga/