This also involves the planning and execution of a more complex workflow;
namely, the original HEFT workflow from Topcuoglu 2000.
"""
import simpy
from topsim.user.schedule.dynamic_plan import DynamicAlgorithmFromPlan
from topsim.user.telescope import Telescope
from topsim.core.simulation import Simulation
EVENT_FILE = 'simulations/real_time/real_time.trace'
CONFIG = 'simulations/real_time/real_time.json'
env = simpy.Environment()
planning_algorithm = 'heft'
scheduling_algorithm = DynamicAlgorithmFromPlan
instrument = Telescope
simulation = Simulation(
env=env,
config=CONFIG,
instrument=instrument,
algorithm_map={'pheft': 'pheft', 'heft': 'heft', 'fifo': DynamicAlgorithmFromPlan},
event_file=EVENT_FILE,
)
simulation.start(11)
simulation.resume(300)
class TestBasicIngest(unittest.TestCase):
def setUp(self) -> None:
self.env = simpy.Environment()
self.simulation = Simulation(
self.env,
BASIC_CONFIG,
Telescope,
planning_algorithm='heft',
planning_model=SHADOWPlanning('heft'),
scheduling=DynamicAlgorithmFromPlan,
delay=None,
timestamp=SIM_TIMESTAMP
)
# def tearDown(self):
# output = 'test/basic-workflow-data/output/{0}'
# os.remove(f'{output}-sim.pkl')
# os.remove(f'{output}-tasks.pkl')
def testClusterIngest(self):
"""
The basic ingest represents the edge cases for timing and scheduling
within the simulation, as demonstrated in this test.
There are a couple of edge cases that occur here, especially when we
consider that we have only 2 resources; one of these will be taken by
ingest, meaning that we cannot start an observation until 1 timestep
AFTER an ingest has finished, because the telescope will check before
that task is successfully removed from the cluster.
This is why we run for 6 seconds and only process 2 observations.
After we've observed 2 observations, we reach capacity on the
cold-buffer so we are unable to observe any more.
Returns
-------
"""
self.assertEqual(0, self.env.now)
self.simulation.start(runtime=7)
self.assertEqual(
2, self.simulation.cluster._ingest['completed']
)
self.assertEqual(
RunStatus.FINISHED,
self.simulation.instrument.observations[1].status
)
def testBufferIngest(self):
self.assertEqual(0, self.simulation.env.now)
self.simulation.start(runtime=1)
self.assertEqual(
5, self.simulation.buffer.hot[0].current_capacity
)
self.simulation.resume(until=2)
self.assertEqual(
10, self.simulation.buffer.hot[0].current_capacity
)
self.assertEqual(
5, self.simulation.buffer.cold[0].current_capacity
)
self.assertEqual(
1,
len(self.simulation.buffer.cold[0].observations["stored"])
)
self.simulation.resume(until=4)
self.assertEqual(10, self.simulation.buffer.hot[0].current_capacity)
self.assertEqual(0, self.simulation.buffer.cold[0].current_capacity)
self.assertEqual(
2,
len(self.simulation.buffer.cold[0].observations["stored"])
)
def testSchedulerRunTime(self):
self.assertEqual(0, self.simulation.env.now)
self.simulation.start(runtime=2)
self.assertEqual(
1, len(self.simulation.buffer.cold[0].observations['stored'])
)
self.simulation.resume(until=8)
self.simulation.resume(until=11)
self.simulation.resume(until=12)
# self.assertEqual(0, len(self.simulation.cluster.tasks['running']))
# We've finished processing one of the workflows so one observation
# is finished.
self.assertEqual(
2, len(self.simulation.buffer.cold[0].observations['stored'])
)