public bool InitRandomPopulation(List <string> selectedTraces)
{
ConfigurationGenerator cg = new ConfigurationGenerator();
for (int i = 0; i < populationSize; i++)
{
population.Add(cg.RandomConfig(individualID.ToString()));
}
allConfigurations.AddRange(population);
var results = sim.Run(population, selectedTraces);
for (int i = 0; i < population.Count; i++)
{
population[i] = new GeneticIndividual(population[i], 0.0, 0.0, 0.0);
for (int j = 0; j < selectedTraces.Count; j++)
{
((GeneticIndividual)population[i]).Ipc += 1.0 / results[i + population.Count * j].ipc;
((GeneticIndividual)population[i]).Power += results[i + population.Count * j].power;
((GeneticIndividual)population[i]).Energy += results[i + population.Count * j].energy;
}
if (selectedTraces.Count > 1)
{
((GeneticIndividual)population[i]).Ipc /= selectedTraces.Count;
((GeneticIndividual)population[i]).Power /= selectedTraces.Count;
((GeneticIndividual)population[i]).Energy /= selectedTraces.Count;
}
nsgaPopulation.Add(new GeneticIndividual(population[i], ((GeneticIndividual)population[i]).Ipc, ((GeneticIndividual)population[i]).Power, ((GeneticIndividual)population[i]).Energy));
}
return(true);
}
private List <Configuration> CreateRandomConfigurations(int count)
{
int configurationIndex = 0;
ConfigurationGenerator configurationGenerator = new ConfigurationGenerator();
var result = new List <Configuration>();
for (int i = 0; i < count; i++)
{
result.Add(configurationGenerator.RandomConfig(string.Format("configuration-{0}", configurationIndex++)));
}
return(result);
}
public void InitRandomPopulation(List <string> selectedTraces)
{
this.selectedTraces = selectedTraces;
for (int i = 0; i < populationSize; i++)
{
population.Add(cg.RandomConfig(individualID.ToString()));
}
CalculateObjectives();
var v = Crossover(population[1], population[2]);
var m = Mutate(v[0]);
}