It all works multi-threaded.

It restarts the threads every generation.  Maybe not the worst thing
every, but it seems like it would be better to stay in the thread and
notify the main thread that they're done with that iteration.

1 files changed, 105 insertions, 25 deletions

diff --git a/src/explicitsimulation.cpp b/src/explicitsimulation.cpp
index 281e7e5..6a9356b 100644
--- a/src/explicitsimulation.cpp
+++ b/src/explicitsimulation.cpp
@@ -1,17 +1,21 @@
 #include "genetic/explicitsimulation.h"
 #include "genetic/operator.h"
 #include "genetic/fitnessfunction.h"
+#include "genetic/phenotype.h"
 
 #include <bu/random.h>
 #include <bu/sio.h>
+#include <bu/mutexlocker.h>
+
+#include <stdlib.h>
 
 using namespace Bu;
 
 Genetic::ExplicitSimulation::ExplicitSimulation( Genetic::Operator *pOper,
-                Genetic::FitnessFunction *pFunc, int iPopSize, float fKeep,
-                float fRandom, bool bKeepBest ) :
+                Genetic::FitnessFunction *pFunc, int iThreads, int iPopSize,
+                float fKeep, float fRandom, bool bKeepBest ) :
         pOper( pOper ),
-        pFunc( pFunc ),
+        //pFunc( pFunc ),
         iPopSize( iPopSize ),
         fKeep( fKeep ),
         fRandom( fRandom ),
@@ -22,13 +26,30 @@ Genetic::ExplicitSimulation::ExplicitSimulation( Genetic::Operator *pOper,
                 xPop.addPhenotype( pOper->random() );
         }
 
+        if( iThreads < 1 )
+                iThreads = 1;
+
+        int iId = 0;
+        lProcessor.append( new Processor( *this, pFunc, qWork, iId++ ) );
+        while( lProcessor.getSize() < iThreads )
+                lProcessor.append(
+                        new Processor( *this, pFunc->clone(), qWork, iId++ )
+                        );
+
         updateFitness();
 }
 
 Genetic::ExplicitSimulation::~ExplicitSimulation()
 {
         delete pOper;
-        delete pFunc;
+
+        for( ProcessorList::iterator i = lProcessor.begin(); i; i++ )
+                (*i)->setRunning( false );
+        for( ProcessorList::iterator i = lProcessor.begin(); i; i++ )
+        {
+                (*i)->join();
+                delete *i;
+        }
 }
 
 void Genetic::ExplicitSimulation::timestep()
@@ -52,12 +73,15 @@ void Genetic::ExplicitSimulation::timestep()
         for( int j = 0; j < iKeep; j++ )
         {
                 Genetic::PhenotypeId id = selectWeighted();
+                mFitness.lock();
                 lNew.append( xPop.takePhenotype( id ) );
                 hTempFitness.insert( id, hFitness.get( id ) );
                 hFitness.erase( id );
                 dTotalFitness -= hTempFitness.get( id );
+                mFitness.unlock();
         }
 
+        mFitness.lock();
         if( bKeepBest && hFitness.has( uMaxFitness ) )
         {
                 lNew.append( xPop.takePhenotype( uMaxFitness ) );
@@ -65,6 +89,7 @@ void Genetic::ExplicitSimulation::timestep()
                 hFitness.erase( uMaxFitness );
                 dTotalFitness -= hTempFitness.get( uMaxFitness );
         }
+        mFitness.unlock();
 
         // Fill in the remainder with random phenotypes
         while( lNew.getSize() < iPopSize )
@@ -73,7 +98,9 @@ void Genetic::ExplicitSimulation::timestep()
         }
 
         // Refill the population
+        mFitness.lock();
         hFitness = hTempFitness;
+        mFitness.unlock();
         xPop.clear();
         xPop.timestep();
         for( PhenotypeList::iterator i = lNew.begin(); i; i++ )
@@ -86,6 +113,8 @@ void Genetic::ExplicitSimulation::timestep()
 
 Genetic::PhenotypeId Genetic::ExplicitSimulation::selectWeighted()
 {
+        Bu::MutexLocker ml( mFitness );
+
         double dSel = Bu::Random::randNorm()*dTotalFitness;
         double dRun = 0.0;
 
@@ -98,42 +127,93 @@ Genetic::PhenotypeId Genetic::ExplicitSimulation::selectWeighted()
 
         sio << "Genetic::ExplicitSimulation::selectWeighted() - failed, picked max"
                 << sio.nl;
+        sio << "  " << dMinFitness << " - " << dMaxFitness << " -- " << dTotalFitness << " > " << dRun << " > " << dSel << sio.nl;
+        abort();
 
         return uMaxFitness;
 }
 
 void Genetic::ExplicitSimulation::updateFitness()
 {
+        mFitness.lock();
         dMinFitness = -1.0;
         dTotalFitness = 0.0;
+        mFitness.unlock();
+
         for( Population::iterator i = xPop.begin(); i; i++ )
         {
-                double dFitness;
                 if( hFitness.has( i.getKey() ) )
                 {
-                        dFitness = hFitness.get( i.getKey() );
+                        setFitness( i.getKey(), hFitness.get( i.getKey() ) );
                 }
                 else
                 {
-                        dFitness = (*pFunc)( *i );
-                        if( dFitness < 0.0 )
-                                dFitness = 0.0;
-                        hFitness.insert( i.getKey(), dFitness );
-                }
-                dTotalFitness += dFitness;
-                if( dMinFitness < 0.0 )
-                {
-                        dMinFitness = dMaxFitness = dFitness;
-                        uMaxFitness = i.getKey();
-                }
-                else if( dMinFitness > dFitness )
-                {
-                        dMinFitness = dFitness;
-                }
-                else if( dMaxFitness < dFitness )
-                {
-                        dMaxFitness = dFitness;
-                        uMaxFitness = i.getKey();
+                        qWork.enqueue( *i );
                 }
         }
+        
+        for( ProcessorList::iterator i = lProcessor.begin(); i; i++ )
+                (*i)->start();
+
+        for( ProcessorList::iterator i = lProcessor.begin(); i; i++ )
+                (*i)->join();
+}
+
+void Genetic::ExplicitSimulation::setFitness( Genetic::PhenotypeId id,
+                double dFitness )
+{
+        Bu::MutexLocker ml( mFitness );
+        if( dFitness < 0.0 )
+                dFitness = 0.0;
+
+//      sio << id << ": " << dFitness << sio.nl;
+        hFitness.insert( id, dFitness );
+
+        dTotalFitness += dFitness;
+        if( dMinFitness < 0.0 )
+        {
+                dMinFitness = dMaxFitness = dFitness;
+                uMaxFitness = id;
+        }
+        else if( dMinFitness > dFitness )
+        {
+                dMinFitness = dFitness;
+        }
+        else if( dMaxFitness < dFitness )
+        {
+                dMaxFitness = dFitness;
+                uMaxFitness = id;
+        }
+}
+
+Genetic::ExplicitSimulation::Processor::Processor(
+                Genetic::ExplicitSimulation &rSim,
+                Genetic::FitnessFunction *pFunc,
+                Genetic::ExplicitSimulation::WorkQueue &rqWork,
+                int iId ) :
+        rSim( rSim ),
+        pFunc( pFunc ),
+        rqWork( rqWork ),
+        iId( iId )
+{
+}
+
+Genetic::ExplicitSimulation::Processor::~Processor()
+{
+        delete pFunc;
+}
+
+void Genetic::ExplicitSimulation::Processor::run()
+{
+        bRunning = true;
+        while( bRunning && !rqWork.isEmpty() )
+        {
+                Genetic::Phenotype *pPhen = rqWork.dequeue( 0, 250000 );
+                if( pPhen == NULL )
+                        continue;
+
+                double dFitness = (*pFunc)( pPhen );
+                rSim.setFitness( pPhen->getId(), dFitness );
+        }
 }
+