?? evotsc.java~
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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 = 2; int eSize = 3; int startAt = 10;
CircuitPainterObject painter = new CircuitPainterObject( new CircuitPainter(), new LUTAbsoluteMapping( experiment.getNumOfInputs(), experiment.getNumOfOutputs() + E_LINES, bitsPerVar, LUT_INPUTS, new ConstantDelayModel( 0 ) ) );
double[] thresholds = { 0.1, 0.1, 0.1 }; int avgRound = 1; int faultDepth = 4;
boolean assumptionA = false; int getEMode = BISTLib.E_MODE_OSCILLATING;
TestingTesterBISTPIMComb inIm = new TestingTesterBISTPIMComb( evolver, deployment, experiment, circuit, thresholds, eSize, E_LINES, avgRound, faultDepth, startAt, getEMode, INPUT_SAMPLE_SEP, assumptionA, painter );
int[] numProps = { 2 }; // Warning, if raise nrEvals will give incorrect value for p0d
InteractionModel noisyIM = new NoisyPIM( inIm, deployment, experiment, numProps, nrEvals );
double maxSize = nrAddUnits;
InteractionModel interactionModel = new CircuitParsimonyPIM( noisyIM, circuit, maxSize, faultDepth );
//int windowSize = 10; InteractionModel interactionModel = new HistoryWindowIM( windowSize, parsIM );
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 avgCirSize = ( int ) ( 1.5 * usedEls );
int tpLen = 1 << experiment.getNumOfInputs(); int effort = tpLen * nrEvals * avgCirSize * INPUT_SAMPLE_SEP * sumBinCo( avgCirSize, faultDepth ) / 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 int sumBinCo( int n, int maxR )
{
int rv = 0;
for( int r = 1; r < maxR; r++ )
{
rv += ESLib.binomialCoefficient( n, r );
}
return rv;
}
protected void addTTAdd1( String dirName ) throws IOException
{
final int INPUT_SAMPLE_SEP = 30;
BooleanFunction functionC = new Add1bitCFun(); BooleanFunction functionQ = new Add1bitQFun();
FitnessFunction corrFF = new CorrelationFitnessFunction();
FitnessFunction tSetupFF = new SampleWindowFitnessFunction( corrFF, 15 );
ArbitraryFunctionExperiment expC = new ArbitraryFunctionExperiment ( functionC, tSetupFF );
ArbitraryFunctionExperiment expQ = new ArbitraryFunctionExperiment ( functionQ, tSetupFF );
ConfigurableRandomInputExperiment[] exps = { expQ, expC }; ConfigurableRandomInputMultiOutputExperiment experiment = new ConfigurableRandomInputMultiOutputExperiment( exps );
final int LUT_INPUTS = 2; final int E_LINES = 1; int bitsPerVar = 4;
final int POP_SIZE = 31; final int NUM_OF_ELITES = 1;
final int GENOTYPE_MUT = 1; int DUMP_POP_EVERY = 20000;
ElementDelayModel delayModel = new CoinDelayModel( );
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 );
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 ];
Genotype seed = new FullOrderGenotype( genotypeLength );
//FullOrderGenotype seed = new FullOrderGenotype( "011011011011011010010011011001000001011111111110011010000010101001011110011101100101000010010000100110101100001000001101000111101111011011111110001011010000" );
//FullOrderGenotype seed = new FullOrderGenotype( "RRQNQ1faOcALlfVu][8D7uRuBG", genotypeLength, 6 );
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; int qDefSize = 0; int fixedAlignments = 0;
ExactGenotypeMutator m = new ExactGenotypeMutator( GENOTYPE_MUT );
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 + 2 * bitsPerVar, fixedAlignments, qDefSize );
GeneticOperator bmin3 = new BunchMutator( bitsPerVar, howManyBunches, blockSize, lutSize + 3 * bitsPerVar, 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 = 1; int eSize = 3; int startAt = 3;
CircuitPainterObject painter = new CircuitPainterObject( new CircuitPainter(), new LUTAbsoluteMapping( experiment.getNumOfInputs(), experiment.getNumOfOutputs() + E_LINES, bitsPerVar, LUT_INPUTS, new ConstantDelayModel( 0 ) ) );
double[] thresholds = { 0.1, 0.1, 0.1 }; int avgRound = 1; int faultDepth = 4;
boolean simpleMode = true; int getEMode = BISTLib.E_MODE_OSCILLATING;
TestingTesterBISTPIMComb inIm = new TestingTesterBISTPIMComb( evolver, deployment, experiment, circuit, thresholds, eSize, E_LINES, avgRound, faultDepth, startAt, getEMode, INPUT_SAMPLE_SEP, simpleMode, painter );
int[] numProps = { 2 }; // Warning, if raise nrEvals will give incorrect value for p0d
InteractionModel noisyIM = new NoisyPIM( inIm, deployment, experiment, numProps, nrEvals );
double maxSize = ( 1 << bitsPerVar ) - experiment.getNumOfInputs();
InteractionModel parsIM = new CircuitParsimonyPIM( noisyIM, circuit, maxSize );
int windowSize = 10;
InteractionModel interactionModel = new HistoryWindowIM( windowSize, parsIM );
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( "Full adder (5 gates) under multiple faults (Ass. A)" );
taskQBestIndID.add( new Integer( 1574 ) );
int avgTPLen = 8; int usedEls = 7;
int effort = 3;
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 addDK27() throws IOException
{
String[][] inputs4ResetState = { { "0","1","0","0" } }; // for dk27
int[] permanentEdges = { 9,11,12,14,16,17,18 }; // for dk27
String resetStateName = "START"; // for dk27
String kissFileName = "dk27";
int bestID = 1985; // 23 * 2 + 1 = 47. 1 - 47/(64-1) = 0.25397
int avgTPLen = 35; // avtTP
addKISSL2BenchmarkLockedFull
(
"/home/mmg20/eh/benchmarks/dk27.kiss2",
"/home/mmg20/eh/benchmarks/dk27.sout",
resetStateName, inputs4ResetState, permanentEdges, "DK27L2",
"Locked Sequential Benchmark: DK27 (20 gates, 3 latches). <strong>Largest Sequential Circuit Evolution ever undertaken!</strong>",
bestID, avgTPLen
);
}
protected void addMC() throws IOException
{
int[] permEdges = { 8,10,12,15 }; // for mc
String[][] resetIns = { {"001","001","001" },{"011", "011", "011" } }; // for mc
int bestID = 1338; // L2 => 8 ?? This may be BEECOUNT
String resetStateName = "HG"; // for mc
int avgTPLen = 155; // avtTP
addKISSL4BenchmarkUnlockedFull
(
"/home/mmg20/eh/benchmarks/mc.kiss2",
"/home/mmg20/eh/benchmarks/mcL4.sout",
resetStateName, resetIns, permEdges, "MCF32",
"Sequential Benchmark: MC (8 four-input LUTs, 2 D-latches)",
bestID, avgTPLen
);
}
protected void addBeecount() throws IOException
{
String[][] resetIns = { {"001"},{"011"},{"101"},{"111"} }; // for beecount
int[] permEdges = { 10,14,17,19,21 }; // for beecount
int bestID = 1869;
int avgTPLen = 220; // avtTP
addKISSL4BenchmarkUnlockedFull
(
"/home/mmg20/eh/benchmarks/beecountSimp.kiss2",
"/home/mmg20/eh/benchmarks/beecountL4.sout",
"S2", resetIns, permEdges, "BeecountL4",
"Locked Sequential Benchmark BEECOUNT (9 four-input LUTs, 2 latches)",
bestID, avgTPLen
);
}
protected void addKISSL4BenchmarkUnlockedFull( 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 = 4;
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 = 21; final int GENOTYPE_MUT = 1; final int NUM_OF_ELITES = 1;
int DUMP_POP_EVERY = 2000;
ElementDelayModel delayModel = new CoinDelayModel( );
CircuitMapping circuitMapping = new FaultyOptimizedMapping( new FPGALUTAbsoluteMapping( experiment.getNumOfInputs(), experiment.getNumOfOutputs() + nrELines, bitsPerVar, LUT_INPUTS, delayModel ) );
int DQTol = 3; int eSize = 19; int startAt = 20;
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 = 0; int howManyBunches = 1;
//GeneticOperator m = new SAGAMutator( 1, genotypeLength / 50, 0, fixedAlignments * blockSize, -1 );
ExactGenotypeMutator m = new ExactGenotypeMutator( GENOTYPE_MUT );
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