I am using the below sample code for OneMax problem (maximizing the number of ones of a bitstring) using DEAP package and multiprocessing.
I am unable to speed up the process using multiprocessing. I want to use this for a more complex problem before finding out what is the issue here.
Thank you.
import array
import multiprocessing
from multiprocessing import Pool
import random
import time
import numpy as np
from deap import algorithms
from deap import base
from deap import creator
from deap import tools
creator.create("FitnessMax", base.Fitness, weights=(1.0,))
creator.create("Individual", array.array, typecode='b', fitness=creator.FitnessMax)
toolbox = base.Toolbox()
toolbox.register("attr_bool", random.randint, 0, 1)
toolbox.register("individual", tools.initRepeat, creator.Individual, toolbox.attr_bool, 10000)
toolbox.register("population", tools.initRepeat, list, toolbox.individual)
#OneMax problem is a simple problem consisting in maximizing the number of ones of a bitstring.
def evalOneMax(individual):
return sum(individual),
toolbox.register("evaluate", evalOneMax)
toolbox.register("mate", tools.cxTwoPoint)
toolbox.register("mutate", tools.mutFlipBit, indpb=0.05)
toolbox.register("select", tools.selTournament, tournsize=3)
if __name__ == "__main__":
t1 = time.time()
CPU_count = multiprocessing.cpu_count()-1
p = Pool(CPU_count)
toolbox.register("map", p.map)
pop = toolbox.population(n=1000)
hof = tools.HallOfFame(1)
stats = tools.Statistics(lambda ind: ind.fitness.values)
stats.register("avg", np.mean)
stats.register("std", np.std)
stats.register("min", np.min)
stats.register("max", np.max)
algorithms.eaSimple(pop, toolbox, cxpb=0.5, mutpb=0.2, ngen=50,
stats=stats, halloffame=hof)
p.close()
p.join()
t2 = time.time()
print("Multiprocessing with",CPU_count,"core(s) took",round((t2-t1),2),"s")
