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 \page ExampleThreadsafeScorers Example ThreadsafeScorers
 
  This example demonstrates a very simple application where an energy
  deposit and # of steps is accounted in thread-local (i.e. one instance per
  thread) hits maps with underlying types of plain-old data (POD) and global
  (i.e. one instance) hits maps with underlying types of atomics.
  The example uses a coarse mesh, extensive physics, and step limiters
  to ensure that there is a higher degree of conflict between threads
  when updating the scorers to test the robustness of the atomics
  classes and maximize the compounding of thread-local round-off error.
 
  At the end of the simulation, the scorers are printed to
  "mfd_DATA_TYPE_SCORER_TYPE.out", where DATA_TYPE is either
  "tl" (thread-local) or "tg" (thread-global) and SCORER_TYPE is "EnergyDeposit"
  or "NumberOfSteps". These values are then compared to a thread-global
  sum of these scorers that were updated via mutex locking. If round-off
  errors in thread-local EnergyDeposit are present, they can be viewed
  in "mfd_diff.out" at the end of the simulation
 
 ## ATOMICS and the ATOMIC SCORERS
 
    atomics can ONLY handle plain-old data (POD) types, e.g. int, double, etc.
    The implementation of atomics in compiler-dependent. At the very worst,
    the performance of an atomic is the same mutex locking.
    Atomics, in general, are not copy-constructable. This has to do with
    thread safety (e.g. making a copy while another thread tries to update)
    This is why atomics cannot be used in STL containers. The implementation
    in atomic.hh has limited copy-construction and still cannot be used in
    STL containers. Use these copy-constructors with extreme caution. See
    opening comments of G4atomic.hh for more details.
 
    The newly provided classes in this example (G4atomic, G4TAtomicHitsMap, and
    G4TAtomicHitsCollection) are intended for applications where memory is a
    greater concern than performance. While atomics generally perform better than
    mutex locking, the synchronization is not without a cost. However, since
    the memory consumed by thread-local hits maps scales roughly linearly
    with the number of threads, simulations with a large number of scoring
    volumes can decrease simulation time by increasing the number of threads
    beyond what was previously allowed due to the increase in memory consumption.
    These classes are intended to be included in the Geant4 source code.
 
    The G4TAtomicHitsMap and G4TAtomicHitsCollection work exactly the same way
    as the standard G4THitsMap and G4THitsCollection, respectively, with the
    exception(s) that you should only implement one instance and provide a
    pointer/reference of that instance to the threads instead of having the
    threads create them. Additionally, there is no need to include them
    in the G4Run::Merge().
 
 ## GEOMETRY DEFINITION
 
    The geometry is constructed in the TSDetectorConstruction class.
    The setup consists of a box filling the world. The volume is divided into
    subregions, where the outermost boxes are a different material. The materials
    by default are water and boron as these have large scattering cross-sections
    for neutrons (the default particle).
 
 ## PHYSICS LIST
 
    The particle's type and the physic processes which will be available
    in this example are set are built from a variety of physics constructors.
    The chosen physics lists are extensive, primarily
    The constructors are:
 
       - G4EmStandardPhysics_option4
       - G4DecayPhysics
       - G4RadioactiveDecayPhysics
       - G4HadronPhysicsQGSP_BERT_HP
       - G4HadronElasticPhysicsHP
       - G4StepLimiterPhysics
       - G4IonElasticPhysics
       - G4IonBinaryCascadePhysics
 
 ## ACTION INITALIZATION
 
    TSActionInitialization, instantiates and registers to Geant4 kernel
     all user action classes.
 
    While in sequential mode the action classes are instatiated just once,
    via invoking the method:
       TSActionInitialization::Build()
    in multi-threading mode the same method is invoked for each thread worker
    and so all user action classes are defined thread-local.
 
    A run action class is instantiated both thread-local
    and global that's why its instance is created also in the method
       TSActionInitialization::BuildForMaster()
    which is invoked only in multi-threading mode.
 
 ## PRIMARY GENERATOR
 
    The primary generator is defined in the TSPrimaryGeneratorAction class.
    The default kinematics is a 1 MeV neutron, randomly distributed in front
    of the target across 100% of the transverse (X,Y) target size.
    This default setting can be changed via the Geant4 built-in commands
    of the G4ParticleGun class.
 
 ## DETECTOR RESPONSE
 
    This example demonstrates a scoring implemented
    in the user action classes and TSRun object.
 
    The energy deposited is collected per event in the PrimitiveScorer
    G4PSEnergyDeposit (as part of a MultiFunctionalDetector)
    and the thread-local version are merged at the end of the run.
 
    The number of steps is collected per event in the PrimativeScorer
    G4PSNoOfSteps and the thread-local version are merged at the end of the run.
 
    When the MFD is recording an event i.e. TSRun::RecordEvent(const G4Event*),
    the global atomic hits map adds the same hits collections
 
    In multi-threading mode the energy accumulated in TSRun MFD object per
    workers is merged to the master in TSRun::Merge().
 
    Scoring is accumulated with thread-local doubles, thread-global atomics,
    mutex-locking, G4StatAnalysis, and G4ConvergenceTester
 
    TSRun contains five hits collections types:
        1) a thread-local hits map,
        2) a global atomic hits map
        3) a global "mutex" hits map
        4) a global G4StatAnalysis hits deque
        5) a global G4ConvergenceTester hits deque
 
    The thread-local hits map is the same as you will find in many other
        examples.
 
    The atomics hits map is the purpose of this example. Code-wise, the
        implementation looks extremely similar to the thread-local version with
        3 primary exceptions:
        (1) construction - there should only be one instance so it should be a
            static member variable or a pointer/reference to a single instance
        (2) It does not need to, nor should be, summed in G4Run::Merge()
        (3) destruction -- it should only be cleared by the master thread since
            there is only one instance.
 
    The "mutex" hits map is also included as reference for checking the results
        accumulated by the thread-local hits maps and atomic hits maps. The
        differences w.r.t. this hits maps are computed in
        TSRunAction::EndOfRunAction
 
    The "G4StatAnalysis" and "G4ConvergenceTester" hits deques are
        memory-efficient version of the standard G4THitsMap. While maps are
        ideal for scoring at the G4Event-level, where sparsity w.r.t. indices
        is common; at the G4Run-level, these data structures require much
        less memory overhead. Due to a lack of
        G4ConvergenceTester::operator+=(G4ConvergenceTester), the static version
        of G4ConvergenceTester is the only valid way to use G4ConvergenceTester
        in a scoring container. This is not the case for G4StatAnalysis, which
        can be used in lieu of G4double.
 
 ## HOW TO RUN
 
   - Execute ts_scorers in the 'interactive mode' with visualization:
 
         % ./ts_scorers
 
     and type in the commands from run.mac line by line:
 
         Idle> /control/verbose 2
         Idle> /tracking/verbose 1
         Idle> /run/beamOn 10
         Idle> ...
         Idle> exit
 
     or
 
         Idle> /control/execute run.mac
         ....
         Idle> exit
 
   - Execute ts_scorers in the 'batch' mode from macro files
     (without visualization)
 
         % ./ts_scorers run.mac
         % ./ts_scorers run.mac > run.out
 

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