def do_exp_HEFT(wf_name, trans):
_wf = wf("" + wf_name)
estimator.transfer_time = trans
#estim = SimpleTimeCostEstimator(comp_time_cost=0, transf_time_cost=0, transferMx=None,
# ideal_flops=20, transfer_time=trans)
heft_schedule = run_heft(_wf, rm, estimator)
#return heft_schedule
Utility.validate_static_schedule(_wf, heft_schedule)
makespan = Utility.makespan(heft_schedule)
return makespan
def __call__(self):
_wf = wf(self.wf_name)
rm = ExperimentResourceManager(rg.r([10, 15, 25, 30]))
estimator = ModelTimeEstimator(bandwidth=10)
empty_fixed_schedule_part = Schedule({node: [] for node in rm.get_nodes()})
heft_schedule = run_heft(_wf, rm, estimator)
fixed_schedule = empty_fixed_schedule_part
ga_functions = GAFunctions2(_wf, rm, estimator)
generate = partial(ga_generate, ga_functions=ga_functions,
fixed_schedule_part=fixed_schedule,
current_time=0.0, init_sched_percent=0.05,
initial_schedule=heft_schedule)
stats = tools.Statistics(lambda ind: ind.fitness.values[0])
stats.register("avg", numpy.mean)
stats.register("std", numpy.std)
stats.register("min", numpy.min)
stats.register("max", numpy.max)
logbook = tools.Logbook()
logbook.header = ["gen", "evals"] + stats.fields
toolbox = Toolbox()
toolbox.register("generate", generate)
toolbox.register("evaluate", fit_converter(ga_functions.build_fitness(empty_fixed_schedule_part, 0.0)))
toolbox.register("clone", deepcopy)
toolbox.register("mate", ga_functions.crossover)
toolbox.register("sweep_mutation", ga_functions.sweep_mutation)
toolbox.register("mutate", ga_functions.mutation)
# toolbox.register("select_parents", )
# toolbox.register("select", tools.selTournament, tournsize=4)
toolbox.register("select", tools.selRoulette)
pop, logbook, best = run_ga(toolbox=toolbox,
logbook=logbook,
stats=stats,
**self.GA_PARAMS)
resulted_schedule = ga_functions.build_schedule(best, empty_fixed_schedule_part, 0.0)
ga_makespan = Utility.makespan(resulted_schedule)
return (ga_makespan, resulted_schedule, logbook)
def heft_schedule(self):
if not self._heft_schedule:
self._heft_schedule = run_heft(self._wf, self._rm, self._estimator)
return self._heft_schedule
from scheduling.src.core.CommonComponents.ExperimentalManagers import ExperimentResourceManager
from scheduling.src.core.environment.Utility import Utility, wf
from scheduling.src.algs.common.MapOrdSchedule import build_schedule, MAPPING_SPECIE, ORDERING_SPECIE
from scheduling.src.experiments.aggregate_utilities import interval_statistics, interval_stat_string
from scheduling.src.experiments.cga.mobjective.utility import SimpleTimeCostEstimator
from scheduling.src.core.environment.ResourceGenerator import ResourceGenerator as rg
from scheduling.src.experiments.cga.utilities.common import repeat
_wf = wf("CyberShake_30")
rm = ExperimentResourceManager(rg.r([10, 15, 25, 30]))
estimator = SimpleTimeCostEstimator(comp_time_cost=0, transf_time_cost=0, transferMx=None,
ideal_flops=20, transfer_time=100)
sorted_tasks = HeftHelper.heft_rank(_wf, rm, estimator)
heft_schedule = run_heft(_wf, rm, estimator)
heft_mapping = schedule_to_position(heft_schedule)
heft_mapping.velocity = MappingParticle.Velocity({})
heft_gen = lambda n: [deepcopy(heft_mapping) if random.random() > 1.0 else generate(_wf, rm, estimator, 1)[0] for _ in range(n)]
W, C1, C2 = 0.1, 0.6, 0.2
GEN, N = 10, 4
toolbox = Toolbox()
toolbox.register("population", heft_gen)
toolbox.register("fitness", fitness, _wf, rm, estimator, sorted_tasks)
def do_exp(wf_name):
_wf = wf(wf_name)
heft_schedule = run_heft(_wf, rm, estimator)
makespan = Utility.makespan(heft_schedule)
return makespan