evotsc.java

Java遗传算法库

        GeneticOperator bmin0 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize, fixedAlignments, qDefSize );
        GeneticOperator bmin1 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize + bitsPerVar, fixedAlignments, qDefSize );
        GeneticOperator bmin2 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize + bitsPerVar * 2, fixedAlignments, qDefSize );
        GeneticOperator bmin3 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize + bitsPerVar * 3, fixedAlignments, qDefSize );
        GeneticOperator bc = new BlockCopy ( blockSize, blockSize, 0, fixedAlignments, qDefSize );
        GeneticOperator[] geneticOps = { m, spxo, bmin0, bmin1, bmin2, bmin3, bc };
        double[] opsProbs = { 0.2, 0.3, 0.1, 0.1, 0.1, 0.1, 0.1 };
        if( LUTInputs == 2 )
        {
            geneticOps[ 4 ] = bmin0;
            geneticOps[ 5 ] = bmin1;
        }
        Selector selector = new RankSelector(  );
        Evolver evolver = new StandardEvolver( POP_SIZE, genotypeLength, geneticOps, opsProbs, selector, NUM_OF_ELITES, seeds );
        
        PopulationLogReader.fullOrderGenotypes = true;  int[] numProps = { 2 }; double maxSize = nrAddUnits;
        CircuitPainterObject painter = new CircuitPainterObject( new CircuitPainter(), new LUTAbsoluteMapping( experiment.getNumOfInputs(), experiment.getNumOfOutputs() + E_LINES, bitsPerVar, LUTInputs, new ConstantDelayModel( 0 ) ) ); 
        TSCCombinationalIM inIm = new TSCCombinationalIM( evolver, deployment, circuit, experiment, faultModel, E_SIZE, E_START_AT, INPUT_SAMPLE_SEP, painter);
        InteractionModel noisyIM = new NoisyPIM( inIm, deployment, experiment, numProps, NO_EVALS );
        InteractionModel interactionModel = new CircuitParsimonyPIM( noisyIM, circuit, maxSize );
        Monica monica = new Monica( interactionModel, DUMP_POP_EVERY, java.lang.Integer.MAX_VALUE );
        painter.setEvoTask( monica );   monica.setName( dirName );
        taskQ.add( monica );    taskQNames.add( dirName );  taskQDescr.add( descr );    taskQBestIndID.add( new Integer( bestIndID ) );
        int avgSize = ( int )( usedEls * 1.45 );
        int effort = NO_EVALS * INPUT_SAMPLE_SEP * avgSize * avgSize * ( 1 << experiment.getNumOfInputs() );
        taskQEffort.add( new Integer( effort ) );        
        ControlLib.writeGNUPlotScript( dirName, logDir, logFileName, 3, false );
        ControlLib.writeWebGraphDaemon( dirName, logDir, logFileName, 3, false, new File(".").getCanonicalPath() + File.separator, getIntConfig( IX_GRAPH_REFRESH_MIN ) );
    }    

    protected void oldAddCombBLIFBenchmark( String blifFileName, String sisOutputFileName, String dirName, String descr, int bestIndID, int LUTInputs, boolean spaceForVoter, boolean locking ) throws IOException
    {
        final int INPUT_SAMPLE_SEP = 30;    final int SAMPLE_WINDOW_START = 20;
        final int DUMP_POP_EVERY = getIntConfig( IX_DUMP_POP_EVERY );     final int E_LINES = 2;
        final int NO_EVALS = 1;
        final int E_SIZE = INPUT_SAMPLE_SEP - SAMPLE_WINDOW_START;
        final int E_START_AT = SAMPLE_WINDOW_START;
        
        FitnessFunction corrFF = new CorrelationFitnessFunction();
        FitnessFunction tSetupFF = new SampleWindowFitnessFunction( corrFF, SAMPLE_WINDOW_START );
        TestPatternGenerator tpg = new CompleteShuffledTPG();
        CombinationalBLIFExperiment experiment = new CombinationalBLIFExperiment( blifFileName, tSetupFF, tpg );
        
        final boolean FPGA = false;
        SisOutputReader sor = new SisOutputReader( new File( sisOutputFileName ), E_LINES, LUTInputs, FPGA, spaceForVoter );
        FullOrderGenotype seed = new FullOrderGenotype ( sor.getVassilevGenotype() );
        int bitsPerVar = sor.getBitsPerVar();        int usedEls = sor.getTotalEls();
        int nrAddUnits = ( 1 << bitsPerVar ) - experiment.getNumOfInputs();

        int lutSize = 1 << LUTInputs;
        int blockSize = lutSize + LUTInputs * bitsPerVar;
        int qDefSize = ( experiment.getNumOfOutputs() + E_LINES ) * bitsPerVar;
        int genotypeLength = qDefSize + nrAddUnits * blockSize;
        
        
        ElementDelayModel delayModel = new CoinDelayModel( );
        CircuitMapping inMapping = new LUTAbsoluteMapping( experiment.getNumOfInputs(), experiment.getNumOfOutputs() + E_LINES, bitsPerVar, LUTInputs, delayModel );
        CircuitMapping circuitMapping = new VassilevMapping( inMapping, experiment.getNumOfOutputs() + E_LINES, bitsPerVar );
        int[] inputDefWithinGene = new int[ LUTInputs ];
        for( int il = 0; il < LUTInputs; il++ )
        {
            inputDefWithinGene[ il ] = lutSize + il * bitsPerVar;
        }
        circuitMapping = new FaultyOptimizedMapping( circuitMapping );
        SimulatorFaultyCircuit circuit = new SimulatorFaultyCircuit( circuitMapping );
        SimulatorDeployment deployment = new SimulatorDeployment( circuit );
        
        SingleFaultModel faultModel = new SingleUsedFaultModel( circuit );

        final int POP_SIZE = 32;   final int NUM_OF_ELITES = 2;
        

        Genotype[] seeds = new Genotype[ POP_SIZE ];
        //seeds[ 0 ] = seed;
        for( int pl = 0; pl < POP_SIZE; pl++ )
        {
            seeds[ pl ] = ( FullOrderGenotype ) seed.clone();
            for( int bl = qDefSize + usedEls * blockSize; bl < seeds[ pl ].length(); bl++ )
                if( Math.random() < 0.5 ) seeds[ pl ].set( bl );
        }
        
        int fixedAlignments = locking ? usedEls : 0;
        int minMutationRate = 1;//genotypeLength / 500 + 1;
        int maxMutationRate = genotypeLength / 25 + 1;
        // was 1000, 50
        int SAGAFitnessIndex = 1;        int howManyBunches = 1;
        GeneticOperator m = new SAGAMutator( minMutationRate, maxMutationRate, SAGAFitnessIndex, fixedAlignments * blockSize, -1 );
        //ExactGenotypeMutator m = new ExactGenotypeMutator( ( int ) ( genotypeLength / 500 ) + 1 ); // For real biggies
        //m.setRange( fixedAlignments * blockSize, -1 );
        GeneticOperator spxo = new SinglePointXOver();
        GeneticOperator bmin0 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize, fixedAlignments, qDefSize );
        GeneticOperator bmin1 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize + bitsPerVar, fixedAlignments, qDefSize );
        GeneticOperator bmin2 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize + bitsPerVar * 2, fixedAlignments, qDefSize );
        GeneticOperator bmin3 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize + bitsPerVar * 3, fixedAlignments, qDefSize );
        GeneticOperator bc = new BlockCopy ( blockSize, blockSize, 0, fixedAlignments, qDefSize );
        GeneticOperator[] geneticOps = { m, spxo, bmin0, bmin1, bmin2, bmin3, bc };
        double[] opsProbs = { 0.2, 0.3, 0.1, 0.1, 0.1, 0.1, 0.1 };
        if( LUTInputs == 2 )
        {
            geneticOps[ 4 ] = bmin0;
            geneticOps[ 5 ] = bmin1;
        }
        Selector selector = new RankSelector(  );
        Evolver evolver = new StandardEvolver( POP_SIZE, genotypeLength, geneticOps, opsProbs, selector, NUM_OF_ELITES, seeds );
        
        PopulationLogReader.fullOrderGenotypes = true;  int[] numProps = { 2 }; double maxSize = nrAddUnits;
        CircuitPainterObject painter = new CircuitPainterObject( new CircuitPainter(), new LUTAbsoluteMapping( experiment.getNumOfInputs(), experiment.getNumOfOutputs() + E_LINES, bitsPerVar, LUTInputs, new ConstantDelayModel( 0 ) ) ); 
        TSCCombinationalIM inIm = new TSCCombinationalIM( evolver, deployment, circuit, experiment, faultModel, E_SIZE, E_START_AT, INPUT_SAMPLE_SEP, painter);
        InteractionModel noisyIM = new NoisyPIM( inIm, deployment, experiment, numProps, NO_EVALS );
        InteractionModel interactionModel = new CircuitParsimonyPIM( noisyIM, circuit, maxSize );
        Monica monica = new Monica( interactionModel, DUMP_POP_EVERY, java.lang.Integer.MAX_VALUE );
        painter.setEvoTask( monica );   monica.setName( dirName );
        taskQ.add( monica );    taskQNames.add( dirName );  taskQDescr.add( descr );    taskQBestIndID.add( new Integer( bestIndID ) );
        int avgSize = ( int )( usedEls * 1.45 );
        int effort = NO_EVALS * INPUT_SAMPLE_SEP * avgSize * avgSize * ( 1 << experiment.getNumOfInputs() );
        taskQEffort.add( new Integer( effort ) );        
        ControlLib.writeGNUPlotScript( dirName, logDir, logFileName, 3, false );
        ControlLib.writeWebGraphDaemon( dirName, logDir, logFileName, 3, false, new File(".").getCanonicalPath() + File.separator, getIntConfig( IX_GRAPH_REFRESH_MIN ) );
    }    
    
    
    protected  void addTTC17() throws IOException
    {
        String blifFN = "/home/mmg20/eh/benchmarks/C17.blif";
        String sisQFN = "/home/mmg20/eh/benchmarks/C17L4.sout";
        String dirName = "TTC17L4OM4SBPV5";
        String descr = "Benchmark C17 (2 four-input LUTs) under multiple faults (Osc.)";
        int bestHD = 1530;
        addCombBLIFBenchmarkNoLockingTT( blifFN, sisQFN, dirName, descr, bestHD );
    }

    protected  void addTTCM42() throws IOException
    {
        String blifFN = "/home/mmg20/eh/benchmarks/cm42a.blif";
        String sisQFN = "/home/mmg20/eh/benchmarks/cm42a.sout";
        String dirName = "TTCM42AD";
        String descr = "Benchmark CM42A (22 gates) under multiple faults (Ass. A, Dual Rail)";
        int bestHD = 1661;
        addCombBLIFBenchmarkNoLockingTT( blifFN, sisQFN, dirName, descr, bestHD );
    }
    
    
    protected  void addCombBLIFBenchmarkNoLockingTT( String blifFileName, String sisOutputFileName, String dirName, String descr, int bestIndID ) throws IOException
    {
        final double T_SETUP = 0.45;
        final int INPUT_SAMPLE_SEP = 30;
        // D -  Circuit Structure Properties
         final int LUT_INPUTS = 4;
        
        // B - BENCHMARK STUFF
         FitnessFunction corrFF = new CorrelationFitnessFunction();
         FitnessFunction tSetupFF = new SampleWindowFitnessFunction( corrFF, 15 );
         TestPatternGenerator tpg = new CompleteShuffledTPG();
        CombinationalBLIFExperiment experiment = new CombinationalBLIFExperiment( blifFileName, tSetupFF, tpg );
        final int E_LINES = 1;
        final boolean FPGA = false;
        final boolean VOTER = true;
        final int EXTRA_BPV = 1;
        final boolean VARSIZED = false;
        SisOutputReader sor = new SisOutputReader( new File( sisOutputFileName ), E_LINES, LUT_INPUTS, FPGA, VOTER, EXTRA_BPV, VARSIZED );
        FullOrderGenotype seed = new FullOrderGenotype ( sor.getGenotype() );
        int bitsPerVar = sor.getBitsPerVar();   
        int usedEls = sor.getTotalEls();        
        // A - Genetic Algorithms Properties
        // Standard
        final int POP_SIZE = 32;
        final int GENOTYPE_MUT = 1;
        final int NUM_OF_ELITES = 2;
        // M - Log Properties
        int DUMP_POP_EVERY = 1000;
        // D - DEPLOYMENT set up
        ElementDelayModel delayModel = new CoinDelayModel( );
        //ElementDelayModel delayModel = new GaussianDelayModel( 0.3, 0.3 );
        CircuitMapping circuitMapping = new LUTAbsoluteMapping( experiment.getNumOfInputs(), experiment.getNumOfOutputs() + E_LINES, bitsPerVar, LUT_INPUTS, delayModel );
        SimulatorFaultyCircuit circuit = new SimulatorFaultyCircuitAsynchronous( circuitMapping );
        boolean randomResetBeforeEveryEval = true;  SimulatorDeployment deployment = new SimulatorDeployment( circuit, randomResetBeforeEveryEval );
        SingleFaultModel faultModel = new SingleUsedFaultModel( circuit, experiment.getNumOfOutputs() );
        
        // A - Genetic Operators Set up
        int nrAddUnits = ( 1 << bitsPerVar ) - experiment.getNumOfInputs();
        int lutSize = 1 << LUT_INPUTS;
        int blockSize = lutSize + LUT_INPUTS * bitsPerVar;
        int genotypeLength = nrAddUnits * blockSize;

        Genotype[] seeds = new Genotype[ POP_SIZE ];
        seeds[ 0 ] = seed;
        for( int pl = 1; pl < POP_SIZE; pl++ )
        {
            seeds[ pl ] = ( FullOrderGenotype ) seed.clone();
            for( int bl = 0; bl < seeds[ pl ].length(); bl++ )
            {
                if( Math.random() < 0.5 )
                {
                    seeds[ pl ].set( bl );
                }
            }
        }
        int howManyBunches = 1;
        //GeneticOperator m = new SAGAMutator( 1, genotypeLength / 100, 0 );
        ExactGenotypeMutator m = new ExactGenotypeMutator( GENOTYPE_MUT );
        GeneticOperator spxo = new SinglePointXOver();
        GeneticOperator bmin0 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize );
        GeneticOperator bmin1 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize + bitsPerVar );
        GeneticOperator bc = new BlockCopy ( blockSize, blockSize, 0 );