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Add performance test for mock backend [WIP]
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‎test/system/test_speed_mock.py‎

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try:
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import unittest2 as unittest
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except ImportError:
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import unittest
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# import pyNN.nest as sim
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import pyNN.mock as sim
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from pyNN.utility import Timer
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class PopulationTest(unittest.TestCase):
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@staticmethod
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def do_scaling_per_population_test(N):
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timer = Timer()
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timer.start()
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sim.setup()
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timer.mark("setup")
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p = sim.Population(N, sim.IF_curr_exp())
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timer.mark("Population: " + str(N))
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sim.end()
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timer.mark("end")
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elapsed_time = timer.elapsed_time()
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relative_elapsed_time = elapsed_time / N
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print(
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"Creating a {}-sized population took {}s ({}s per neuron)".format(
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N, elapsed_time, relative_elapsed_time
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)
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)
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def test_scaling_per_population(self, sim=sim):
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for powerN in range(13):
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N = 2 ** powerN
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with self.subTest(N=N):
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self.do_scaling_per_population_test(N)
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@staticmethod
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def do_scaling_test(N):
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timer = Timer()
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timer.start()
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sim.setup()
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timer.mark("setup")
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for _ in range(N):
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p = sim.Population(1, sim.IF_curr_exp())
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timer.mark("Population: " + str(N))
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sim.end()
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timer.mark("end")
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elapsed_time = timer.elapsed_time()
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relative_elapsed_time = elapsed_time / N
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print(
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"Creating {} populations took {}s ({}s per population)".format(
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N, elapsed_time, relative_elapsed_time
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)
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)
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def test_scaling(self, sim=sim):
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for powerN in range(13):
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N = 2 ** powerN
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with self.subTest(N=N):
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self.do_scaling_test(N)
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@staticmethod
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def _add_dummy_parameters(celltype, M):
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for i in range(M):
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pname = "tmp{}".format(i)
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celltype.default_parameters[pname] = 0.0
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celltype.units[pname] = "mV"
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celltype.translations[pname] = {
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"translated_name": pname.upper(),
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"forward_transform": pname,
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"reverse_transform": pname.upper(),
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}
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@staticmethod
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def _remove_dummy_parameters(celltype, M):
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for i in range(M):
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pname = "tmp{}".format(i)
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del celltype.default_parameters[pname]
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del celltype.units[pname]
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del celltype.translations[pname]
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@staticmethod
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def do_scaling_cellparams_test(N, M):
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# copy.deepcopy doesn't help here => we add and restore manually
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celltype = sim.IF_cond_exp
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assert len(celltype.get_parameter_names()) < 100
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PopulationTest._add_dummy_parameters(celltype, M)
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sim.setup()
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t0 = Timer()
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t0.start()
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pop = sim.Population(N, celltype()) # this is the culprit
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elapsed_time = t0.elapsed_time()
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relative_elapsed_time = elapsed_time / M
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print(
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"Creating a population with {} parameters took {} ({} per parameter)".format(
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len(celltype.get_parameter_names()), elapsed_time, relative_elapsed_time
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)
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)
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sim.end()
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PopulationTest._remove_dummy_parameters(celltype, M)
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def test_scaling_cellparams(self, sim=sim):
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for powerN in range(16):
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N = 2 ** powerN
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with self.subTest(N=N):
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self.do_scaling_cellparams_test(1, N)
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@staticmethod
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def do_scaling_cellparams_popview_test(N, M):
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# copy.deepcopy doesn't help here => we add and restore manually
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celltype = sim.IF_cond_exp
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assert len(celltype.get_parameter_names()) < 100
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PopulationTest._add_dummy_parameters(celltype, M)
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sim.setup()
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pop = sim.Population(N, celltype())
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pview = sim.PopulationView(pop, [0])
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post_cell = sim.simulator.ID(pview.first_id)
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post_cell.parent = pop # this is the culprit
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t0 = Timer()
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t0.start()
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post_index = pview.id_to_index(post_cell)
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elapsed_time = t0.elapsed_time()
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relative_elapsed_time = elapsed_time / M
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print(
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"Calling id_to_index on a view into a population with {} parameters took {} ({} per parameter)".format(
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len(celltype.get_parameter_names()), elapsed_time, relative_elapsed_time
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)
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)
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sim.end()
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PopulationTest._remove_dummy_parameters(celltype, M)
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def test_scaling_cellparams_popview(self, sim=sim):
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for powerN in range(8):
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N = 2 ** powerN
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with self.subTest(N=N):
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self.do_scaling_cellparams_popview_test(1, N)
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class ProjectionTest(unittest.TestCase):
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@staticmethod
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def do_scaling_per_projection_test(N):
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sim.setup()
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pre = sim.Population(N, sim.IF_cond_exp())
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post = sim.Population(N, sim.IF_cond_exp())
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timer = Timer()
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timer.start()
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proj = sim.Projection(
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pre, post, sim.OneToOneConnector(), synapse_type=sim.StaticSynapse(weight=1.0)
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)
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timer.mark("Projection: " + str(N))
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elapsed_time = timer.elapsed_time()
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relative_elapsed_time = elapsed_time / N
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sim.end()
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print(
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"Creating {}-sized projection took {}s ({}s per synapse)".format(
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N, elapsed_time, relative_elapsed_time
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)
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)
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def test_scaling_per_projection(self, sim=sim):
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for powerN in range(13):
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N = 2 ** powerN
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with self.subTest(N=N):
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self.do_scaling_per_projection_test(N)
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@staticmethod
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def do_scaling_test(N):
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sim.setup()
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pre = sim.Population(N, sim.IF_cond_exp())
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post = sim.Population(N, sim.IF_cond_exp())
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timer = Timer()
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timer.start()
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for i in range(N):
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# FIXME: add check for class-vs-instance in connector, it fails if the connector is a class
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proj = sim.Projection(
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pre[i : i + 1],
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post[i : i + 1],
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sim.OneToOneConnector(),
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synapse_type=sim.StaticSynapse(weight=1.0),
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)
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timer.mark("Projection: " + str(N))
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elapsed_time = timer.elapsed_time()
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relative_elapsed_time = elapsed_time / N
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sim.end()
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print(
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"Creating {} projections took {}s ({}s per projection)".format(
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N, elapsed_time, relative_elapsed_time
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)
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)
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def test_scaling(self, sim=sim):
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for powerN in range(13):
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N = 2 ** powerN
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with self.subTest(N=N):
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self.do_scaling_test(N)
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# import profile
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if __name__ == "__main__":
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unittest.main()
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# profile.run('print(PopulationTest.do_scaling_cellparams_popview_test(1, 100))')

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