2021-04-09 18:01:29 +02:00
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import multiprocessing, threading
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import time
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import random
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ARROW_NUMBER = 150
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MAX_CYCLES = 20000
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SPACE_SIZE = 10000
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PREEMPTION_GLOBAL_SPACE = [True] * SPACE_SIZE
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ARROW_LIST = [(random.randint(0,SPACE_SIZE - 1),0) for x in range(ARROW_NUMBER)]
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TRANSITIONS_TREE = None
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2021-04-09 18:14:56 +02:00
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MAX_THREAD = 10
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2021-04-09 18:01:29 +02:00
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class CurrentlyComputing(Exception):
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pass
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class SuccessfulOperation(Exception):
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pass
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class FailedOperation(Exception):
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pass
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2021-04-09 18:14:56 +02:00
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## Local Threads
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2021-04-09 18:01:29 +02:00
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class LocalThread(multiprocessing.Process):
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def __init__(self, id, shared_memory, address, orientation, transitions):
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multiprocessing.Process.__init__(self)
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self.id = id
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self.address = address
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self.orientation = orientation
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self.transitions = transitions
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self.namespace = shared_memory.Namespace()
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self.namespace.returncode = CurrentlyComputing()
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def run(self):
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try:
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# Actual code
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print("Thread local n°{} parle depuis {} !".format(self.id, self.address))
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2021-04-09 18:14:56 +02:00
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L = [random.randint(0,3000) for x in range(random.randint(0, 300))]
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for i in xrange(10000000):
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sum(range(100))
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2021-04-09 18:01:29 +02:00
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self.namespace.returncode = SuccessfulOperation()
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except Exception as exception:
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self.namespace.returncode = exception
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2021-04-09 18:14:56 +02:00
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## Master Thread
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2021-04-09 18:01:29 +02:00
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class GreatScheduler(threading.Thread):
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def __init__(self, preemption_space, arrow_list, n_thread, nmax_cycles):
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threading.Thread.__init__(self)
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self.preemption_space = preemption_space
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self.arrow_list = arrow_list
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self.n_thread = n_thread
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self.cur_id = -1
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self.n_cycle = -1
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self.nmax_cycles = nmax_cycles
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self.stopped = False
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def run(self):
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thread_list = []
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shared_memory = multiprocessing.Manager()
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while not self.stopped and self.n_cycle != self.nmax_cycles:
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self.n_cycle += 1
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#print("--- Mesures et écoute ---")
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#print("Espace global de préemption :\t {}".format(self.preemption_space))
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#print("Liste des flèches :\t {}".format(self.arrow_list))
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## Tirer une flêche au hasard
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n = int(random.random()*len(self.arrow_list))
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elected_arrow = self.arrow_list[n]
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## Vérification de l'espace global de préemption autour de la flêche
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if not(len(thread_list) >= self.n_thread) and self.preemption_space[elected_arrow[0]]:
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print("Espace local libre à {}".format(elected_arrow[0]))
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self.preemption_space[elected_arrow[0]] = False
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## Création du thread local
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self.cur_id += 1
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thread_list.append(
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LocalThread(self.cur_id,
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shared_memory,
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elected_arrow[0],
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elected_arrow[1],
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TRANSITIONS_TREE
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)
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)
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## Lancer le thread local
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thread_list[-1].start()
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for thread in thread_list:
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if not thread.is_alive():
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if not thread.namespace.returncode.__class__ is SuccessfulOperation:
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if thread.namespace.returncode.__class__ is FailedOperation:
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print("A optimiser : créer une règle")
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else:
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raise thread.namespace.returncode
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print("Thread local n°{} est terminé".format(thread.id))
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self.preemption_space[thread.address] = True
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thread_list.pop(thread_list.index(thread))
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## Sortie du scheduler
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print("Attente de la fin des thread locaux")
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for thread in thread_list:
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thread.join()
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if not thread.namespace.returncode.__class__ is SuccessfulOperation:
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if thread.namespace.returncode.__class__ is FailedOperation:
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print("A optimiser : créer une règle")
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else:
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raise thread.namespace.returncode
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print("Thread local n°{} est terminé".format(thread.id))
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class ServerCLI:
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def start():
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stopped = False
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while not stopped:
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stopped = input()
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return
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#multiprocessing.set_start_method('fork')
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scheduler = GreatScheduler(PREEMPTION_GLOBAL_SPACE, ARROW_LIST, MAX_THREAD, MAX_CYCLES)
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scheduler.start()
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ServerCLI.start()
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scheduler.stopped = True
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