Other GEANT4 capabilities

Event biasing Parameterisation (fast simulation)

Persistency Parallelisation and integration in a distributed

computing environment

Fast simulationFast simulation

The parameterisationparameterisation process produces a direct detector response, from the knowledge of particle and volume properties– hits, digis, reconstructed-like objects (tracks, clusters etc.)

Great flexibility– activate fast /full simulation by detectorby detector example: full simulation for inner detectors, fast simulation for calorimeters– activate fast /full simulation by geometry regionby geometry region example: fast simulation in central areas and full simulation near cracks– activate fast /full simulation by particle typeby particle type example: in e.m. calorimeter, e/ parameterisation + full simulation of

hadrons– parallel geometriesparallel geometries in fast/full simulation example: inner and outer tracking detectors distinct in full simulation, but

handled together in fast simulation

Geant4 allows to perform fullfull and fast fast simulation in the same environment

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

Leading particle biasingSimulating 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

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

I = 1.0 I = 2.0

W=1.0W=0.5W=0.5

P = 0.5

PersistencyPersistencyGeant4 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

Object Database

Constructor

Destructor

Time

File

G4Application

PersistentObject

G4Application

TransientObject

G4Persistency

G4Kernel

Store( )Retrieve( ) Inherits from HepPersObj

in HepODBMS

G4 kernel objects have corresponding “P” objects in G4PersistencyG4Run G4PRunG4Event G4PEventG4Hit G4PHit : :

G4 kernel objects have corresponding “P” objects in G4PersistencyG4Run G4PRunG4Event G4PEventG4Hit G4PHit : :

“Parallel World” approach

Data members of transient and persistent objects are copied by Store( ) and Retrieve( )

Access to distributed computingAccess to distributed computingBy 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

IRCC LAN

SWITCH

Node01

Node02

Node03

Node04

IMRT

Geant4 Simulation and Anaphe Analysis on a dedicated Beowulf

ClusterS. Chauvie et al., IRCC Torino, Siena

2002

An example of parallelisation of a Geant4 based medical application

DIANE DIstributed ANalysis Environment

prototype for an intermediate layer between applications and the GRID

Hide complex details of underlying technology

Developed by J. Moscicki, CERN

http://cern.ch/DIANE

R&D in progress forR&D in progress forLarge Scale Large Scale

Master-WorkerMaster-Worker ComputingComputing

DIANEDIANE

Parallelisation Access to the GRID

Transparent access to a distributed computing environment

Parallel mode: local cluster Parallel mode: distributed resources

DIANE framework and generic GRID middleware

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

Poland

Greece

Portugal Traceback from a run of the Geant4 brachytherapy advanced example on CrossGrid testbed