def main():
# single run in current process mode, used for profiling
if True:
#with simdag.Simulation("test/data/pl_4hosts.xml", "test/data/basic_graph.dot") as simulation:
with simdag.Simulation(
"dag/plat_exp1/cluster_5_1-4_100_100_0.xml",
"dag/tasks_exp1/Inspiral_100.xml") as simulation:
#with simdag.Simulation("dag/plat_exp1/cluster_20_1-4_100_100_0.xml", "dag/tasks_exp2/testg0.6.dot") as simulation:
#graph = simulation.get_task_graph()
#scheduler = algorithms.HEFT(simulation)
#scheduler = algorithms.DLS(simulation)
#scheduler = algorithms.HCPT(simulation)
scheduler = algorithms.Lookahead(simulation)
#scheduler = algorithms.OLB(simulation)
#scheduler = algorithms.BatchMin(simulation)
#scheduler = algorithms.PEFT(simulation)
#scheduler = algorithms.SimHEFT(simulation)
scheduler.run()
for t in simulation.tasks.sorted(lambda t: t.start_time):
print(t.name, t.start_time, t.finish_time, t.hosts[0].name)
print(scheduler.scheduler_time, scheduler.total_time)
print(
"EXEC",
sum([(t.finish_time - t.start_time)
for t in simulation.tasks]))
print(
"COMM",
sum([(t.finish_time - t.start_time)
for t in simulation.connections]))
return
# example: how to run multiple simulations in a single script (circumventing SimGrid limitation of 'non-restartable' simulator state)
for scheduler in _SCHEDULERS.keys():
p = multiprocessing.Process(target=run_simulation, args=(scheduler, ))
p.start()
p.join()
def run_plain_simulation(args):
scheduler_name, env, task = args
scheduler_class = _SCHEDULERS[scheduler_name]
with simdag.Simulation(env, task) as simulation:
scheduler = scheduler_class(simulation)
scheduler.run()
return simulation.clock, scheduler_name
def run_simulation(scheduler):
scheduler_class = _SCHEDULERS[scheduler]
with simdag.Simulation("test/data/pl_4hosts_master.xml", "dag/tasks_exp2/testg0.6.dot") as simulation:
print("Scheduler:", scheduler, scheduler_class)
scheduler = scheduler_class(simulation)
scheduler.run()
print("Scheduler time:", scheduler.scheduler_time)
def slave_scheduling(context: Context, connection: Connection):
with ProximalSimulationSlave(connection) as proxy_slave, simdag.Simulation(
context.env_file, context.task_file) as simulation:
with proxy_slave.scheduling_scope():
scheduler = SlaveScheduler(simulation, proxy_slave,
context.feature)
scheduler.run()
if context.slave_callback:
proxy_slave.send(context.slave_callback(simulation))
connection.close()
def run_simulation(args):
scheduler_name, env, task = args
scheduler_class = _SCHEDULERS[scheduler_name]
with simdag.Simulation(env, task) as simulation:
print(f'Start {scheduler_name} simulation')
scheduler = scheduler_class(simulation)
scheduler.run()
print(f"""{scheduler_name}
makespan: {simulation.clock}
scheduling time: {scheduler.scheduler_time}
""")
return simulation.clock, scheduler_name
def run_simulation(system, workload, scheduler):
with simdag.Simulation(system, workload) as simulation:
logging.info("Scheduler: %s" % (scheduler))
# schedule root and end tasks on master host
master_host = simulation.hosts.by_prop('name', 'master')[0]
root_task = simulation.tasks.by_prop('name', 'root')[0]
logging.debug("%s -> %s" % (root_task.name, master_host.name))
root_task.schedule(master_host)
end_task = simulation.tasks.by_prop('name', 'end')[0]
logging.debug("%s -> %s" % (end_task.name, master_host.name))
end_task.schedule(master_host)
sched_class = globals()[scheduler]
sched_class(simulation).run()
return simulation.clock
def main():
# single run in current process mode, used for profiling
if False:
#with simdag.Simulation("test/data/pl_4hosts.xml", "test/data/basic_graph.dot") as simulation:
with simdag.Simulation("test/data/pl_4hosts_master.xml",
"test/data/basic_graph.dot") as simulation:
#with simdag.Simulation("test/data/pl_4hosts.xml", "dag/tasks_exp2/testg0.6.dot") as simulation:
#with simdag.Simulation("dag/plat_exp1/cluster_20_1-4_100_100_0.xml", "dag/tasks_exp2/testg0.6.dot") as simulation:
#graph = simulation.get_task_graph()
#scheduler = heft.HEFTScheduler(simulation)
scheduler = algorithms.BatchSufferage(simulation)
#scheduler = peft.PEFTScheduler(simulation)
scheduler.run()
print(scheduler.scheduler_time, scheduler.total_time)
return
# example: how to run multiple simulations in a single script (circumventing SimGrid limitation of 'non-restartable' simulator state)
for scheduler in _SCHEDULERS.keys():
p = multiprocessing.Process(target=run_simulation, args=(scheduler, ))
p.start()
p.join()
from pysimgrid import simdag
import pysimgrid.simdag.algorithms as algorithms
import logging
import pysimgrid.tools as tools
_LOG_DATE_FORMAT = "%Y-%m-%d %H:%M:%S"
_LOG_FORMAT = "[%(name)s] [%(levelname)5s] [%(asctime)s] %(message)s"
logging.basicConfig(level=logging.DEBUG, format=_LOG_FORMAT, datefmt=_LOG_DATE_FORMAT)
with simdag.Simulation("test/data/pl_4hosts.xml", "test/data/basic_graph.dot") as simulation:
scheduler = algorithms.CLDD(simulation)
scheduler.run()
graph = simulation.get_task_graph()
#print(simulation.clock, scheduler.scheduler_time, scheduler.total_time)
for t in simulation.tasks.sorted(lambda t: t.start_time):
print(t.name, t.start_time, t.finish_time, t.hosts[0].name)
print "TOTAL EXECUTION TIME :", sum([(t.finish_time - t.start_time) for t in simulation.tasks])
print"TOTAL COMMUNICATION TIME :", sum([(t.finish_time - t.start_time) for t in simulation.connections])