evotsc.java

Java遗传算法库

        GeneticOperator spxo = new SinglePointXOver();
        GeneticOperator bmin0 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize, fixedAlignments, qDefSize );
        GeneticOperator bmin1 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize + bitsPerAdd, fixedAlignments, qDefSize );
        GeneticOperator bmin2 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize + 2 * bitsPerAdd, fixedAlignments, qDefSize );
        GeneticOperator bmin3 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize + 3 * bitsPerAdd, fixedAlignments, qDefSize );
        GeneticOperator bc = new BlockCopy ( blockSize, blockSize, 0, fixedAlignments, qDefSize );
        GeneticOperator[] geneticOps ={ m,      spxo,   bmin0,  bmin1,  bmin2,  bmin3,  bc      };
        double[] opsProbs =          {  0.3,    0.2,    0.1,    0.1  ,  0.1  ,  0.1  ,  0.1     };
        Selector selector = new RankSelector(  );
        Evolver evolver = new StandardEvolver( POP_SIZE, genotypeLength, geneticOps, opsProbs, selector, NUM_OF_ELITES, seeds );        
        PopulationLogReader.fullOrderGenotypes = true;

        int nrEvals = 5;        boolean overdetecting = true;
        CircuitPainterObject painter = new CircuitPainterObject( new CircuitPainter(), new LUTAbsoluteMapping( experiment.getNumOfInputs(), experiment.getNumOfOutputs() + nrELines, bitsPerVar, LUT_INPUTS, new ConstantDelayModel( 0 ) ) ); 
        BISTPIMSeqOnlineFull inIm = new BISTPIMSeqOnlineFull( evolver, deployment, circuit, experiment, INPUT_SAMPLE_SEP, faultModel, eSize, DQTol, painter, startAt, time2Reset );
        int[] numProps = { 2 };
        InteractionModel noisyIM = new NoisyPIM( inIm, deployment, experiment, numProps, nrEvals, NoisyPIM.AVERAGE );
        double maxSize = nrAddCLBs * 2;
        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 effort = (int) ( avgTPLen * INPUT_SAMPLE_SEP * nrEvals * ( usedEls * 1.5 ) * ( usedEls * 1.5 * 2 ) / 1000000 );
        taskQEffort.add( new Integer( effort ) );
            ControlLib.writeGNUPlotScript( dirName, logDir, logFileName, 3, false );
            ControlLib.writeWebGraphDaemon( dirName, logDir, logFileName, 3, false, new File(".").getCanonicalPath() + File.separator );            
    }
    
    
    protected  void addKISSL2BenchmarkLockedFull( String kissFileName, String sisOutputFileName, String resetStateName, String[][] inputs4ResetState, int[] permanentEdges, String dirName, String descr, int bestIndID, int avgTPLen ) throws IOException
    {
        int time2Reset = -1;
        for( int pl = 0; pl < inputs4ResetState.length; pl++ )
        {
            time2Reset = Math.max( time2Reset, inputs4ResetState[ pl ].length );
        }
        final int INPUT_SAMPLE_SEP = 40;    final int LUT_INPUTS = 2;
        boolean generateClock = false;      int cyclesPerSample = 1;
        int nrELines = 1;        boolean fpga = true;        boolean voter = true;
         FitnessFunction corrFF = new CorrelationFitnessFunction();
         FitnessFunction tSetupFF = new SampleWindowFitnessFunction( corrFF, 20 );
        KISSFSMExperiment inExp = new KISSFSMExperiment( new File( kissFileName ), resetStateName, inputs4ResetState, permanentEdges, generateClock, tSetupFF );
        AddClockCSRIExperiment experiment = new AddClockCSRIExperiment( inExp, cyclesPerSample );
        SisOutputReader sor = new SisOutputReader( new File( sisOutputFileName ), nrELines, LUT_INPUTS, fpga, voter );
        FullOrderGenotype seed = new FullOrderGenotype ( sor.getGenotype() );
        int bitsPerVar = sor.getBitsPerVar();        int usedEls = sor.getTotalEls();
        int bitsPerAdd = bitsPerVar + 1;
        final int POP_SIZE = 15;    final int GENOTYPE_MUT = 1; final int NUM_OF_ELITES = 1;
        int DUMP_POP_EVERY = 1000;
        ElementDelayModel delayModel = new CoinDelayModel( );
        CircuitMapping circuitMapping = new FaultyOptimizedMapping( new FPGALUTAbsoluteMapping( experiment.getNumOfInputs(), experiment.getNumOfOutputs() + nrELines, bitsPerVar, LUT_INPUTS, delayModel ) );
        int DQTol = 5;        int eSize = 14;     int startAt = 25;
        SimulatorFaultyCircuit circuit = new SimulatorFaultyCircuit( circuitMapping );
        boolean alwaysResetBeforeRun = true;
        SimulatorDeployment deployment = new SimulatorDeployment( circuit, alwaysResetBeforeRun );
        SingleFaultModel faultModel = new SingleUsedFaultModel( circuit ); // Should take in whole circuit every time??
        int nrAddCLBs = ( 1 << bitsPerVar ) - experiment.getNumOfInputs();
        int lutSize = 1 << LUT_INPUTS;
        int blockSize = lutSize + ( LUT_INPUTS + 1 ) * bitsPerAdd;
        int qDefSize = ( experiment.getNumOfOutputs() + nrELines ) * bitsPerAdd;
        int genotypeLength = qDefSize + nrAddCLBs * blockSize;
        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 = usedEls;        int howManyBunches = 1;
        //GeneticOperator m = new SAGAMutator( 1, genotypeLength / 50, 0, fixedAlignments * blockSize, -1 );
        ExactGenotypeMutator m = new ExactGenotypeMutator( GENOTYPE_MUT );
        m.setRange( qDefSize + 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 + bitsPerAdd, fixedAlignments, qDefSize );
        //GeneticOperator bmin2 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize + 2 * bitsPerAdd, fixedAlignments, qDefSize );
        //GeneticOperator bmin3 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize + 3 * bitsPerAdd, fixedAlignments, qDefSize );
        GeneticOperator bc = new BlockCopy ( blockSize, blockSize, 0, fixedAlignments, qDefSize );
        //GeneticOperator[] geneticOps ={ m,      spxo,   bmin0,  bmin1,  bmin2,  bmin3,  bc      };
        GeneticOperator[] geneticOps ={ m,      spxo,   bmin0,  bmin1,  bc      };
        double[] opsProbs =          {  0.2,    0.2,    0.2,    0.2  ,  0.2     };
        //double[] opsProbs =          {  0.2,    0.2,    0.1,    0.1  ,  0.1  ,  0.1  ,  0.2     };
        Selector selector = new RankSelector(  );
        Evolver evolver = new StandardEvolver( POP_SIZE, genotypeLength, geneticOps, opsProbs, selector, NUM_OF_ELITES, seeds );        
        PopulationLogReader.fullOrderGenotypes = true;

        int nrEvals = 3;        boolean overdetecting = true;
        CircuitPainterObject painter = new CircuitPainterObject( new CircuitPainter(), new LUTAbsoluteMapping( experiment.getNumOfInputs(), experiment.getNumOfOutputs() + nrELines, bitsPerVar, LUT_INPUTS, new ConstantDelayModel( 0 ) ) ); 
        BISTPIMSeqOnlineFull inIm = new BISTPIMSeqOnlineFull( evolver, deployment, circuit, experiment, INPUT_SAMPLE_SEP, faultModel, eSize, DQTol, painter, startAt, time2Reset );
        int[] numProps = { 2 };
        InteractionModel noisyIM = new NoisyPIM( inIm, deployment, experiment, numProps, nrEvals, NoisyPIM.AVERAGE );
        double maxSize = nrAddCLBs * 2;
        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 effort = (int) ( avgTPLen * INPUT_SAMPLE_SEP * nrEvals * ( usedEls * 1.5 ) * ( usedEls * 1.5 * 2 ) / 1000000 );
        taskQEffort.add( new Integer( effort ) );
            ControlLib.writeGNUPlotScript( dirName, logDir, logFileName, 3, false );
            ControlLib.writeWebGraphDaemon( dirName, logDir, logFileName, 3, false, new File(".").getCanonicalPath() + File.separator );            
    }
        
    protected  void addKISSBenchmarkLockedFull( String kissFileName, String sisOutputFileName, String resetStateName, String[][] inputs4ResetState, int[] permanentEdges, String dirName, String descr, int bestIndID, int avgTPLen ) throws IOException
    {
        int time2Reset = -1;
        for( int pl = 0; pl < inputs4ResetState.length; pl++ )
        {
            time2Reset = Math.max( time2Reset, inputs4ResetState[ pl ].length );
        }        
        final int INPUT_SAMPLE_SEP = 40;    final int LUT_INPUTS = 2;
        File kissFile = new File( kissFileName );
         FitnessFunction corrFF = new CorrelationFitnessFunction();
         FitnessFunction tSetupFF = new SampleWindowFitnessFunction( corrFF, 20 );
         boolean generateClock = true; // ** ????????
        KISSFSMExperiment experiment = new KISSFSMExperiment( kissFile, resetStateName, inputs4ResetState, permanentEdges, generateClock, tSetupFF );
        int nrELines = 1;        boolean fpga = false;        boolean voter = true;
        SisOutputReader sor = new SisOutputReader( new File( sisOutputFileName ), nrELines, LUT_INPUTS, fpga, voter );
        FullOrderGenotype seed = new FullOrderGenotype ( sor.getGenotype() );
        int bitsPerVar = sor.getBitsPerVar();        int usedEls = sor.getTotalEls();        
        SingleFaultModel faultModel = new SingleFullFaultModel( usedEls );
        final int POP_SIZE = 15;    final int GENOTYPE_MUT = 1; final int NUM_OF_ELITES = 0;
        int DUMP_POP_EVERY = 25;
        ElementDelayModel delayModel = new CoinDelayModel( );
        CircuitMapping circuitMapping = new LUTAbsoluteMapping( experiment.getNumOfInputs(), experiment.getNumOfOutputs() + nrELines, bitsPerVar, LUT_INPUTS, delayModel );
        int DQTol = 3;
        int eSize = 19;     int ignoreAtStart = 20;
        SimulatorFaultyCircuit circuit = new SimulatorFaultyCircuit( circuitMapping );
        SimulatorDeployment deployment = new SimulatorDeployment( circuit );
        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 = 0; pl < POP_SIZE; pl++ )
        {
            seeds[ pl ] = ( FullOrderGenotype ) seed.clone();
            for( int bl = usedEls * blockSize; bl < seeds[ pl ].length(); bl++ )
            {
                if( Math.random() < 0.5 )
                {
                    seeds[ pl ].set( bl );
                }
            }
        }
        int fixedAlignments = usedEls;
        int howManyBunches = 1;
        //GeneticOperator m = new SAGAMutator( 1, genotypeLength / 50, 0, fixedAlignments * blockSize, -1 );
        ExactGenotypeMutator m = new ExactGenotypeMutator( 2 );
        m.setRange( fixedAlignments * blockSize, -1 );
        GeneticOperator spxo = new SinglePointXOver();
        GeneticOperator bmin0 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize, fixedAlignments );
        GeneticOperator bmin1 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize + bitsPerVar, fixedAlignments );
        GeneticOperator bc = new BlockCopy ( blockSize, blockSize, 0, fixedAlignments );
        GeneticOperator[] geneticOps = { m, spxo, bmin0, bmin1, bc };
        double[] opsProbs = { 0.2, 0.2, 0.2, 0.2, 0.2 };
        Selector selector = new RankSelector(  );
        Evolver evolver = new StandardEvolver( POP_SIZE, genotypeLength, geneticOps, opsProbs, selector, NUM_OF_ELITES, seeds );        
        PopulationLogReader.fullOrderGenotypes = true;

        int nrEvals = 1;        boolean overdetecting = true;
        CircuitPainterObject painter = new CircuitPainterObject( new CircuitPainter(), new LUTAbsoluteMapping( experiment.getNumOfInputs(), experiment.getNumOfOutputs() + nrELines, bitsPerVar, LUT_INPUTS, new ConstantDelayModel( 0 ) ) ); 
        BISTPIMSeqOnlineFull inIm = new BISTPIMSeqOnlineFull( evolver, deployment, circuit, experiment, INPUT_SAMPLE_SEP, faultModel, eSize, DQTol, painter, ignoreAtStart, time2Reset );
        int[] numProps = { 2 };
        InteractionModel noisyIM = new NoisyPIM( inIm, deployment, experiment, numProps, nrEvals, NoisyPIM.MINIMUM );
        double maxSize = nrAddUnits;
        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 effort = (int) ( avgTPLen * INPUT_SAMPLE_SEP * nrEvals * ( usedEls * 1.5 ) * ( usedEls * 1.5 * 2 ) / 1000000 );
        taskQEffort.add( new Integer( effort ) );
            ControlLib.writeGNUPlotScript( dirName, logDir, logFileName, 3, false );
            ControlLib.writeWebGraphDaemon( dirName, logDir, logFileName, 3, false, new File(".").getCanonicalPath() + File.separator );            
    }    
   
    protected  void addC17() throws IOException
    {
        String blifFN = "/home/mmg20/eh/benchmarks/C17.blif";
        String sisQFN = "/home/mmg20/eh/benchmarks/C17.sout";
        String dirName = "C17L";
        String descr = "Adding Built-In Self-Test to Conventionally Designed Benchmark Circuit Without Altering Original Design: C17 using 6 gates";
        int bestHD = 297;
        addCombBLIFBenchmark( blifFN, sisQFN, dirName, descr, bestHD );
    }
    
    protected  void addB1() throws IOException
    {
        String blifFN = "/home/mmg20/eh/benchmarks/b1.blif";
        String sisQFN = "/home/mmg20/eh/benchmarks/b1.sout";
        String dirName = "B1LX";
        String descr = "Locked Benchmark: B1 using 6 gates";
        int bestHD = 2;
        addCombBLIFBenchmark( blifFN, sisQFN, dirName, descr, bestHD );
    }
    

    protected  void addZ4ML() throws IOException
    {
        String blifFN = "/home/mmg20/eh/benchmarks/z4ml.blif";
        String sisQFN = "/home/mmg20/eh/benchmarks/z4ml.sout";
        String dirName = "Z4MLTSC";