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Other GEANT4 capabilities

Geant4 offers powerful capabilities for fast simulation, event biasing, and data persistency in a distributed computing environment. The parameterization process enables direct detector responses based on particle and volume properties, facilitating hits and reconstructed objects. Users can selectively activate fast or full simulations by detector type, geometry region, and particle type. Event biasing techniques enhance efficiency by selectively tracking significant secondary particles. Moreover, Geant4 supports integration with external utilities for parallel execution across multiple processes, making it a flexible tool for advanced simulations.

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Other GEANT4 capabilities

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  1. Other GEANT4 capabilities Event biasing Parameterisation (fast simulation) Persistency Parallelisation and integration in a distributed computing environment

  2. Fast simulation Geant4 allows to perform full and fast simulation in the same environment • Theparameterisationprocess produces a direct detectorresponse, from the knowledge of particle and volume properties • hits, digis, reconstructed-like objects (tracks, clusters etc.) • Great flexibility • activate fast /full simulation by detector • example:full simulation for inner detectors, fast simulation for calorimeters • activate fast /full simulation by geometry region • example:fast simulation in central areas and full simulation near cracks • activate fast /full simulation by particle type • example:in e.m. calorimeter, e/g parameterisation + full simulation of hadrons • parallel geometries in fast/full simulation • example:inner and outer tracking detectors distinct in full simulation, but handled together in fast simulation

  3. Event biasing • Geant4 provides facilities for event biasing • The effect consists in producing a small number of secondaries, which are artificially recognized as a huge number of particles by their statistical weights • Event biasing can be used, for instance, for the transportation of slow neutrons or in the radioactive decay simulation • Various variance reduction techniques available

  4. Leading particle biasing • Simulating a full shower is an expensive calculation • Instead of generating a full shower, trace only the most energetic secondary • Other secondary particles are immediately killed before being stacked • Convenient way to roughly estimate, e.g. the thickness of a shield • Physical quantities such as energy are not conserved for each event

  5. I = 1.0 I = 2.0 W=0.5 W=0.5 W=1.0 P = 0.5 Geometrical importance biasing • Define importance for each geometrical region • Duplicate a track with half (or relative) weight if it goes toward more important region • Russian-roulette in another direction • Scoring particle flux with weights • at the surface of volumes

  6. Retrieve( ) Inherits from HepPersObj in HepODBMS Store( ) Persistency • Geant4 Persistency makes run, event, hits, digits and geometry information be persistent, to be read back later by user programs • no dependence on any specific persistency model • use industrial standard ODMG C++ binding and HepODBMS as persistency interface • Possibility to run in transient or persistent mode G4 kernel objects have corresponding “P” objects in G4Persistency G4Run G4PRun G4Event G4PEvent G4Hit G4PHit :: “Parallel World” approach Data members of transient and persistent objects are copied by Store( ) and Retrieve( )

  7. IRCC LAN Node01 SW I T C H Node02 Node03 Node04 Access to distributed computing • By design, Geant4 can be executed in more than one process/machine in parallel • Geant4 itself does not provide any mechanism of parallelisation • use external utilities IMRT An example of parallelisation of a Geant4 based medical application Geant4 Simulation and Anaphe Analysis on a dedicated Beowulf Cluster S. Chauvie et al., IRCC Torino,Siena 2002

  8. DIANE prototype for an intermediate layer between applications and the GRID Transparentaccess to a distributed computing environment Parallelisation Access to the GRID DIANE DIstributed ANalysis Environment Hide complex details of underlying technology R&D in progress for Large Scale Master-Worker Computing http://cern.ch/DIANE Developed by J. Moscicki, CERN

  9. Current #Grid setup (computing elements): 5000 events, 2 workers, 10 tasks (500 events each) - aocegrid.uab.es:2119/jobmanager-pbs-workq - bee001.ific.uv.es:2119/jobmanager-pbs-qgrid - cgnode00.di.uoa.gr:2119/jobmanager-pbs-workq - cms.fuw.edu.pl:2119/jobmanager-pbs-workq - grid01.physics.auth.gr:2119/jobmanager-pbs-workq - xg001.inp.demokritos.gr:2119/jobmanager-pbs-workq - xgrid.icm.edu.pl:2119/jobmanager-pbs-workq - zeus24.cyf-kr.edu.pl:2119/jobmanager-pbs-infinite - zeus24.cyf-kr.edu.pl:2119/jobmanager-pbs-long - zeus24.cyf-kr.edu.pl:2119/jobmanager-pbs-medium - zeus24.cyf-kr.edu.pl:2119/jobmanager-pbs-short - ce01.lip.pt:2119/jobmanager-pbs-qgrid Spain Greece Poland Portugal Parallel mode: distributed resources Parallel mode: local cluster DIANE framework and generic GRID middleware Traceback from a run of the Geant4 brachytherapy advanced example on CrossGrid testbed

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