def componoud_update(w, c1, c2, p, best, pop):
#doMap = random.random()
#if doMap < 0.1:
mapping_update(w, c1, c2, p.mapping, best.mapping, pop)
#else:
ordering_update(w, c1, c2, p.ordering, best.ordering, pop)
toolbox = Toolbox()
toolbox.register("population", heft_gen)
toolbox.register("fitness", fitness, _wf, rm, estimator)
toolbox.register("update", componoud_update)
return toolbox
pass
if __name__ == "__main__":
exp = RdpsoBaseExperiment(wf_name="Epigenomics_24",
W=0.2,
C1=0.5,
C2=0.5,
GEN=300,
N=20)
result = repeat(exp, 60)
print(result)
# result = exp()
sts = interval_statistics(result)
print("Statistics: {0}".format(interval_stat_string(sts)))
print("Average: {0}".format(numpy.mean(result)))
pass
n = 4
execCount = 1
data_intensive = 100
exp_om = OmpsoBaseExperiment(
wf_name=wf_cur,
#exp_rd = RdpsoBaseExperiment(wf_name=wf_cur,
W=w,
C1=c1,
C2=c2,
GEN=gen,
N=n,
data_intensive=data_intensive)
#result = repeat(exp_om, execCount)
result = repeat(exp_om, execCount)
#file = open("C:\Melnik\Experiments\Work\PSO_compare\populations\OM cyber.txt", 'w')
#file.write("#w = " + str(w) + " c1 = " + str(c1) + " c2 = " + str(c2) + "\n")
#file.write("#gen result" + "\n")
res_list = [0 for _ in range(gen)]
for i in range(execCount):
cur_list = result[i][1]
print(str(cur_list))
for j in range(gen):
res_list[j] = res_list[j] + cur_list[j]
res_list = [x / execCount for x in res_list]
print("res_list = " + str(res_list))
#for i in range(gen):
heft_schedule = run_heft(_wf, rm, estimator)
heft_makespan = Utility.makespan(heft_schedule)
overall_transfer = Utility.overall_transfer_time(heft_schedule, _wf,
estimator)
overall_execution = Utility.overall_execution_time(heft_schedule)
print(
"Heft makespan: {0}, Overall transfer time: {1}, Overall execution time: {2}"
.format(heft_makespan, overall_transfer, overall_execution))
if not only_heft:
exec_count = 100
gen = PARAMS["ga_params"]["generations"]
res_list = [0 for _ in range(gen)]
result = repeat(do_exp_heft_schedule, exec_count)
mean = numpy.mean([makespan for (makespan, list) in result])
for i in range(exec_count):
cur_list = result[i][1]
print(str(cur_list))
for j in range(gen):
res_list[j] = res_list[j] + cur_list[j]
for j in range(gen):
res_list[j] = res_list[j] / exec_count
print(str(res_list))
#file = open("C:\Melnik\Experiments\Work\PSO_compare\populations\GA with HEFT cyber.txt", 'w')
#file.write("#gen result" + "\n")
#for i in range(gen):
# file.write(str(i) + " " + str(res_list[i]) + "\n")
#for (profit, trans) in profit_list:
# file.write(str(profit) + " " + str(trans) + "\n") `
w = 0.1
c1 = 0.6
c2 = 0.2
gen = 300
n = 20
fileRes = open("F:\eScience\Work\experiments\OMPSOvsRDPSO\Sipht_30 c1_06 c2_02 gen_300 n_20 FILTER only RD TEST.txt", 'w')
fileInfo = open("F:\eScience\Work\experiments\OMPSOvsRDPSO\Sipht_30 c1_06 c2_02 gen_300 n_20 FILTER info only RD TEST.txt", 'w')
exp_om = OmpsoBaseExperiment(wf_name=wf_list[0],
W=w, C1=c1, C2=c2,
GEN=gen, N=n)
result2 = repeat(exp_om, 100)
sts2 = interval_statistics(result2)
#for w in [x / 10 for x in range(15)]:
for _ in [1]:
print(w)
wf_cur = wf_list[0]
print(wf_cur)
exp_rd = RdpsoBaseExperiment(wf_name=wf_cur,
W=0.1, C1=0.6, C2=0.2,
GEN=gen, N=n)
result1 = repeat(exp_rd, 100)
sts1 = interval_statistics(result1)
fileInfo.write("OM " + str(w) + " " + str(sts2) + "\n")
logbook=logbook,
stats=stats,
gen_curr=0,
gen_step=GEN,
invalidate_fitness=True,
initial_pop=None,
w=W,
c1=C1,
c2=C2,
n=N,
)
solution = construct_solution(best, sorted_tasks)
schedule = build_schedule(_wf, estimator, rm, solution)
Utility.validate_static_schedule(_wf, schedule)
makespan = Utility.makespan(schedule)
print("Final makespan: {0}".format(makespan))
print("Heft makespan: {0}".format(Utility.makespan(heft_schedule)))
return makespan
if __name__ == "__main__":
result = repeat(do_exp, 4)
sts = interval_statistics(result)
print("Statistics: {0}".format(interval_stat_string(sts)))
print(result)
pass
stats = tools.Statistics(lambda ind: ind.energy.values[0])
stats.register("val", lambda arr: arr[0])
def do_exp():
best, log, current = run_sa(toolbox=toolbox,
logbook=logbook,
stats=stats,
initial_solution=initial_state,
T=T,
N=N)
solution = {
MAPPING_SPECIE: [item for item in best.mapping.items()],
ORDERING_SPECIE: best.ordering
}
schedule = build_schedule(_wf, estimator, rm, solution)
Utility.validate_static_schedule(_wf, schedule)
makespan = Utility.makespan(schedule)
heft_makespan = Utility.makespan(heft_schedule)
print("Final makespan: {0}".format(makespan))
print("Heft makespan: {0}".format(heft_makespan))
return makespan
if __name__ == "__main__":
result = repeat(do_exp, 10)
print(result)
print("Mean: {0}".format(numpy.mean(result)))
pass
jobs_copy = jobslist.copy()
total_job_rate = 0
total_runtime = 0
total_datasize = 0
for it in range(len(jobs_copy)):
job = jobs_copy.pop()
cur_datasize = 0
for file in job.input_files.items():
cur_datasize = cur_datasize + file[1].size
total_job_rate = total_job_rate + (cur_datasize / job.runtime)
total_runtime = total_runtime + job.runtime
total_datasize = total_datasize + cur_datasize
total_job_rate = total_job_rate / len(jobslist)
total_runtime = total_runtime / len(jobslist)
total_datasize = total_datasize / len(jobslist)
return total_job_rate
if __name__ == "__main__":
exp = OmpsoBaseExperiment(wf_name="_30",
W=0.5, C1=1.6, C2=1.2,
GEN=100, N=50, data_intensive=100)
result = repeat(exp, 8)
print(result)
sts = interval_statistics(result)
print("Statistics: {0}".format(interval_stat_string(sts)))
print("Average: {0}".format(numpy.mean(result)))
pass
#curFileOM = open("C:\Melnik\Experiments\Work\PSO_compare\\result\\" + wf_cur + "\\" + "OM w_0.2 c1_0.6 c2_test gen_300 n_20.txt", 'w')
#curFileRD = open("C:\Melnik\Experiments\Work\PSO_compare\\result\\" + wf_cur + "\\" + "RD w_0.2 c1_0.6 c2_test gen_300 n_20.txt", 'w')
#curFileRD2 = open("C:\Melnik\Experiments\Work\PSO_compare\\result\\" + wf_cur + "\\" + "RD2 w_0.2 c1_0.6 c2_test gen_300 n_20.txt", 'w')
#curFile.write("#C1 OM RD RDwithMap Heft" + "\n")
#for wcur in [0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5
#c2 = wcur
#print(c2)
exp_om = OmpsoBaseExperiment(wf_name=wf_cur,
W=w,
C1=c1,
C2=c2,
GEN=gen,
N=n,
data_intensive=100)
result2 = repeat(exp_om, execCount)
sts2 = interval_statistics([makespan for (makespan, pop) in result2])
#print(" om finish")
exp_rd = RdpsoBaseExperiment(wf_name=wf_cur,
W=w,
C1=c1,
C2=c2,
GEN=gen,
N=n,
data_intensive=100)
result1 = repeat(exp_rd, execCount)
sts1 = interval_statistics([makespan for (makespan, pop) in result1])
#print(" rd finish")