def test_popview_on_neuron(self):
pynn.setup(marocco=self.marocco)
pop = pynn.Population(4, pynn.IF_cond_exp, {})
neuron_block = C.NeuronBlockOnWafer(C.NeuronBlockOnHICANN(3))
neuron_block_1 = C.NeuronBlockOnWafer(C.NeuronBlockOnHICANN(2))
logical_neuron = (LogicalNeuron.on(neuron_block)
.add(C.NeuronOnNeuronBlock(X(3), Y(0)), 2)
.add(C.NeuronOnNeuronBlock(X(3), Y(1)), 2)
.done())
logical_neuron_1 = (LogicalNeuron.on(neuron_block_1)
.add(C.NeuronOnNeuronBlock(X(4), Y(0)), 2)
.add(C.NeuronOnNeuronBlock(X(4), Y(1)), 2)
.done())
popview = pynn.PopulationView(pop,[0])
popview_1 = pynn.PopulationView(pop,[2])
popview_auto_placement= pynn.PopulationView(pop,[1,3])
self.marocco.manual_placement.on_neuron(popview, logical_neuron)
self.marocco.manual_placement.on_neuron(popview_1, logical_neuron_1)
pynn.run(0)
pynn.end()
results = self.load_results()
placement_item, = results.placement.find(popview[0])
self.assertEqual(logical_neuron, placement_item.logical_neuron())
placement_item, = results.placement.find(popview_1[0])
self.assertEqual(logical_neuron_1, placement_item.logical_neuron())
for nrn in popview_auto_placement:
placement_item, = results.placement.find(nrn)
self.assertIsNotNone(placement_item.logical_neuron())
def test_on_neurons(self, pop_size):
pynn.setup(marocco=self.marocco)
pop = pynn.Population(pop_size, pynn.IF_cond_exp, {})
neuron_block = C.NeuronBlockOnWafer(C.NeuronBlockOnHICANN(3))
logical_neurons = [
(LogicalNeuron.on(neuron_block)
.add(C.NeuronOnNeuronBlock(X(3), Y(0)), 2)
.add(C.NeuronOnNeuronBlock(X(3), Y(1)), 2)
.done()),
(LogicalNeuron.on(neuron_block)
.add(C.NeuronOnNeuronBlock(X(11), Y(0)), 2)
.add(C.NeuronOnNeuronBlock(X(11), Y(1)), 2)
.done()),
]
self.marocco.manual_placement.on_neuron(pop, logical_neurons)
if pop_size != len(logical_neurons):
with self.assertRaises(RuntimeError):
pynn.run(0)
pynn.end()
return
pynn.run(0)
pynn.end()
results = self.load_results()
for nrn, logical_neuron in zip(pop, logical_neurons):
placement_item, = results.placement.find(nrn)
self.assertEqual(logical_neuron, placement_item.logical_neuron())
def test_on_neuron_block(self, size):
pynn.setup(marocco=self.marocco)
neuron_size = 4
self.marocco.neuron_placement.default_neuron_size(neuron_size)
neuron_block = C.NeuronBlockOnWafer(C.NeuronBlockOnHICANN(3))
pop = pynn.Population(size, pynn.IF_cond_exp, {})
self.marocco.manual_placement.on_neuron_block(pop, neuron_block)
if neuron_size * size > C.NeuronOnNeuronBlock.enum_type.size:
with self.assertRaises(RuntimeError):
pynn.run(0)
pynn.end()
return
pynn.run(0)
pynn.end()
results = self.load_results()
for nrn in pop:
placement_item, = results.placement.find(nrn)
logical_neuron = placement_item.logical_neuron()
self.assertEqual(neuron_size, logical_neuron.size())
for denmem in logical_neuron:
self.assertEqual(neuron_block, denmem.toNeuronBlockOnWafer())
def test_access_queue(self):
"""use queue handling"""
class myPlacer(placer):
def loop(self):
print("reversing populations")
# b = self.m_queue.access; # use this or the following
print((dir(self.m_queue.value()[0])))
b = self.m_queue.value()
print((dir(b)))
marocco = self.marocco
user_strat = myPlacer()
marocco.neuron_placement.default_placement_strategy(user_strat)
pynn.setup(marocco=marocco)
self.network()
result = self.load_results()
hicann = C.HICANNOnWafer(Enum(42))
nb = C.NeuronBlockOnHICANN(Enum(4))
for pop in self.pops:
for nrn in pop:
placement_item, = result.placement.find(nrn)
logical_neuron = placement_item.logical_neuron()
for denmem in logical_neuron:
# all pops shall be on different NBs
self.assertFalse(nb == denmem.toNeuronBlockOnHICANN()
and hicann == denmem.toHICANNOnWafer())
nb = denmem.toNeuronBlockOnHICANN()
hicann = denmem.toHICANNOnWafer()
def test_hw_merging_spl1_should_merge_some(self):
"""
some DNCs shall be merged, but not all, because of syndriver
requirements on each NB. 2 neurons will be placed (same HICANN).
A fully connected network is built.
This results in 8*2 = 16 synapses being routed to each neuron.
With neuron size 4 and chain length 3 -> 12 synapses can be realised
on each neuron. As a result at maximum 12 synapses shall be on the
same L1Route. The merger tries to merge them and will fail, then spit
it and merge 8 to each merger [3,5].
The result is a better L1 utilisation compared to one-to-one mapping,
2 instead of 8 routes, while staying within hardware constrains,
compared to merge all (16 synapses requiring 4 drivers, 1 driver will
be lost).
"""
pynn.setup(marocco=self.marocco)
neuron_size = 4
self.marocco.neuron_placement.default_neuron_size(neuron_size)
self.marocco.merger_routing.strategy(
self.marocco.merger_routing.minimize_as_possible)
# restrict to 3 driver, so that this test is hardware agnostic
self.marocco.synapse_routing.driver_chain_length(3)
hicann = C.HICANNOnWafer(Enum(123))
pops = []
# All but the first neuron block are occupied.
for nb in range(C.NeuronBlockOnHICANN.end):
pop = pynn.Population(2, pynn.IF_cond_exp, {})
self.marocco.manual_placement.on_neuron_block(
pop, C.NeuronBlockOnWafer(C.NeuronBlockOnHICANN(nb), hicann))
pops.append(pop)
for p in pops:
for other_p in pops:
pynn.Projection(p, other_p, pynn.AllToAllConnector(weights=1.))
pynn.run(0)
pynn.end()
merged_dncs = [3, 3, 3, 3, 5, 5, 5, 5]
results = self.load_results()
for pop in pops:
nrn = pop[0]
placement_item, = results.placement.find(nrn)
logical_neuron = placement_item.logical_neuron()
self.assertEqual(neuron_size, logical_neuron.size())
for denmem in logical_neuron:
self.assertEqual(hicann, denmem.toHICANNOnWafer())
address = placement_item.address()
# some DNCs shall be merged.
dnc = C.DNCMergerOnHICANN(merged_dncs[pop.euter_id()])
self.assertEqual(hicann, address.toHICANNOnWafer())
self.assertEqual(dnc, address.toDNCMergerOnHICANN())
self.assertEqual(C.DNCMergerOnWafer(dnc, hicann),
address.toDNCMergerOnWafer())
def test_min_spl1_should_allow_external_input_on_same_chip(self):
"""
Even when the rightmost neuron block / DNC merger is not reserved for external input, it
should be possible to place external input on the same chip.
"""
pynn.setup(marocco=self.marocco)
neuron_size = 4
self.marocco.neuron_placement.default_neuron_size(neuron_size)
self.marocco.merger_routing.strategy(
self.marocco.merger_routing.minimize_number_of_sending_repeaters)
# Do not reserve rightmost neuron block / DNC merger for external input.
self.marocco.neuron_placement.restrict_rightmost_neuron_blocks(False)
hicann = C.HICANNOnWafer(Enum(123))
pops = []
# All but the first neuron block are occupied.
for nb in range(1, C.NeuronBlockOnHICANN.end):
pop = pynn.Population(1, pynn.IF_cond_exp, {})
self.marocco.manual_placement.on_neuron_block(
pop, C.NeuronBlockOnWafer(C.NeuronBlockOnHICANN(nb), hicann))
pops.append(pop)
in_pop = pynn.Population(1, pynn.SpikeSourceArray, {})
self.marocco.manual_placement.on_hicann(in_pop, hicann)
pynn.run(0)
pynn.end()
results = self.load_results()
for pop in pops:
nrn = pop[0]
placement_item, = results.placement.find(nrn)
logical_neuron = placement_item.logical_neuron()
self.assertEqual(neuron_size, logical_neuron.size())
for denmem in logical_neuron:
self.assertEqual(hicann, denmem.toHICANNOnWafer())
address = placement_item.address()
# All used neuron blocks should be connected to a single DNC merger.
dnc = C.DNCMergerOnHICANN(3)
self.assertEqual(hicann, address.toHICANNOnWafer())
self.assertEqual(dnc, address.toDNCMergerOnHICANN())
self.assertEqual(C.DNCMergerOnWafer(dnc, hicann),
address.toDNCMergerOnWafer())
nrn = in_pop[0]
placement_item, = results.placement.find(nrn)
logical_neuron = placement_item.logical_neuron()
self.assertTrue(logical_neuron.is_external())
address = placement_item.address()
# External input must not be on DNC 3 merger, since all other
# mergers do not have direct access to a background generator.
dnc = C.DNCMergerOnHICANN(3)
self.assertEqual(hicann, address.toHICANNOnWafer())
self.assertNotEqual(dnc, address.toDNCMergerOnHICANN())
self.assertNotEqual(C.DNCMergerOnWafer(dnc, hicann),
address.toDNCMergerOnWafer())
def test_min_spl1_is_nongreedy_when_pops_are_placed_to_nbs(self, nbs):
"""
See above. Instead of a single population placed to the HICANN, populations are placed to
specific neuron blocks.
"""
pynn.setup(marocco=self.marocco)
neuron_size = 4
self.marocco.neuron_placement.default_neuron_size(neuron_size)
self.marocco.merger_routing.strategy(
self.marocco.merger_routing.minimize_number_of_sending_repeaters)
self.marocco.neuron_placement.restrict_rightmost_neuron_blocks(True)
hicann = C.HICANNOnWafer(Enum(123))
pops = []
for nb in nbs:
pop = pynn.Population(1, pynn.IF_cond_exp, {})
self.marocco.manual_placement.on_neuron_block(
pop, C.NeuronBlockOnWafer(C.NeuronBlockOnHICANN(nb), hicann))
pops.append(pop)
in_pop = pynn.Population(1, pynn.SpikeSourceArray, {})
self.marocco.manual_placement.on_hicann(in_pop, hicann)
pynn.run(0)
pynn.end()
results = self.load_results()
for pop in pops:
nrn = pop[0]
placement_item, = results.placement.find(nrn)
logical_neuron = placement_item.logical_neuron()
self.assertEqual(neuron_size, logical_neuron.size())
for denmem in logical_neuron:
self.assertEqual(hicann, denmem.toHICANNOnWafer())
address = placement_item.address()
# All used neuron blocks should still be connected to a single DNC merger.
dnc = C.DNCMergerOnHICANN(3)
self.assertEqual(hicann, address.toHICANNOnWafer())
self.assertEqual(dnc, address.toDNCMergerOnHICANN())
self.assertEqual(C.DNCMergerOnWafer(dnc, hicann),
address.toDNCMergerOnWafer())
nrn = in_pop[0]
placement_item, = results.placement.find(nrn)
logical_neuron = placement_item.logical_neuron()
self.assertTrue(logical_neuron.is_external())
address = placement_item.address()
# External input should be on the rightmost DNC merger since that is tried first.
dnc = C.DNCMergerOnHICANN(7)
self.assertEqual(hicann, address.toHICANNOnWafer())
self.assertEqual(dnc, address.toDNCMergerOnHICANN())
self.assertEqual(C.DNCMergerOnWafer(dnc, hicann),
address.toDNCMergerOnWafer())
def test_loop_modularity_nb(self):
"""tests to override the loop hook with NB handling"""
class myPlacer(placer):
def initialise(self):
b = sorted(
self.m_neuron_blocks.access,
key=lambda nb: int(nb.toHICANNOnWafer().toEnum().value()))
self.m_neuron_blocks.access = b
def loop(self):
print("removing the last NB")
b = self.m_neuron_blocks.access # use this or the following
b = self.m_neuron_blocks.value()
b = sorted(
b,
key=lambda nb: int(nb.toHICANNOnWafer().toEnum().value()))
c = []
for i in range(len(b) - 1):
c.append(b[i])
# use access to set full vector
self.m_neuron_blocks.access = c
# or use the value() to access single elements
for i in range(len(self.m_neuron_blocks.value())):
del (self.m_neuron_blocks.value()[0])
for nb in c:
self.m_neuron_blocks.value().append(nb)
marocco = self.marocco
user_strat = myPlacer()
marocco.neuron_placement.default_placement_strategy(user_strat)
pynn.setup(marocco=marocco)
self.network()
result = self.load_results()
hicann = C.HICANNOnWafer(Enum(42))
nb = C.NeuronBlockOnHICANN(Enum(4))
for pop in self.pops:
for nrn in pop:
placement_item, = result.placement.find(nrn)
logical_neuron = placement_item.logical_neuron()
for denmem in logical_neuron:
# all pops must be on different NBs
self.assertFalse(nb == denmem.toNeuronBlockOnHICANN()
and hicann == denmem.toHICANNOnWafer())
nb = denmem.toNeuronBlockOnHICANN()
hicann = denmem.toHICANNOnWafer()
def test_on_neuron_wrong_shape(self):
pynn.setup(marocco=self.marocco)
pop = pynn.Population(1, pynn.IF_cond_exp, {})
neuron_block = C.NeuronBlockOnWafer(C.NeuronBlockOnHICANN(3))
logical_neuron = (LogicalNeuron.on(neuron_block)
.add(C.NeuronOnNeuronBlock(X(2), Y(0)), 4)
.add(C.NeuronOnNeuronBlock(X(3), Y(1)), 2)
.done())
self.marocco.manual_placement.on_neuron(pop, logical_neuron)
with self.assertRaises(RuntimeError):
pynn.run(0)
pynn.end()
def test_on_neuron(self):
pynn.setup(marocco=self.marocco)
pop = pynn.Population(1, pynn.IF_cond_exp, {})
neuron_block = C.NeuronBlockOnWafer(C.NeuronBlockOnHICANN(3))
logical_neuron = (LogicalNeuron.on(neuron_block)
.add(C.NeuronOnNeuronBlock(X(3), Y(0)), 2)
.add(C.NeuronOnNeuronBlock(X(3), Y(1)), 2)
.done())
self.marocco.manual_placement.on_neuron(pop, logical_neuron)
pynn.run(0)
pynn.end()
results = self.load_results()
placement_item, = results.placement.find(pop[0])
self.assertEqual(logical_neuron, placement_item.logical_neuron())
def test_python_interface_nb_enum_increase(self):
"""tests to set switches of the class"""
marocco = self.marocco
user_strat = placer()
user_strat.m_neuron_block_on_hicann_ordering = placer.neuron_block_on_hicann_enum_increasing
marocco.neuron_placement.default_placement_strategy(user_strat)
pynn.setup(marocco=marocco)
self.run_placement()
result = self.load_results()
nb = C.NeuronBlockOnHICANN(Enum(0))
for pop in self.pops:
for nrn in pop:
placement_item, = result.placement.find(nrn)
logical_neuron = placement_item.logical_neuron()
for denmem in logical_neuron:
self.assertEqual(nb.toEnum(),
denmem.toNeuronBlockOnHICANN().toEnum())
def test_python_interface_merger_friendly(self):
"""tests to set switches of the class"""
marocco = self.marocco
user_strat = placer()
user_strat.m_neuron_block_on_hicann_ordering = placer.merger_tree_friendly
marocco.neuron_placement.default_placement_strategy(user_strat)
pynn.setup(marocco=marocco)
self.run_placement()
result = self.load_results()
# the first NB for merger friendly placemnt.
nb = C.NeuronBlockOnHICANN(Enum(3))
for pop in self.pops:
for nrn in pop:
placement_item, = result.placement.find(nrn)
logical_neuron = placement_item.logical_neuron()
for denmem in logical_neuron:
self.assertEqual(nb, denmem.toNeuronBlockOnHICANN())
def test_hook_modularity_nb(self):
"""tests to override some hooks of the Placement Base class"""
class myPlacer(placer):
def initialise(self):
print("initialise in python,\
remove all but NeuronBlock 4 on HICANN 42")
# use one of the two ways to access the value
a = self.m_neuron_blocks.access
b = self.m_neuron_blocks.value()
assert (a == b)
b = sorted(
b,
key=lambda nb: int(nb.toHICANNOnWafer().toEnum().value()))
c = []
for nb in b:
if nb.toHICANNOnWafer().toEnum().value() == 42:
if (nb.toNeuronBlockOnHICANN().toEnum().value() == 4):
c.append(nb)
# smaller values are in the front.
# the c++ code pops from the back.
c = sorted(c,
key=lambda nb: int(nb.toNeuronBlockOnHICANN().
toEnum().value()),
reverse=False)
for nb in c:
print(("will use : {}".format(nb)))
# There are two options to set it again:
# use access to set a full vector
self.m_neuron_blocks.access = c
# or use the value() to access single elements
for i in range(len(self.m_neuron_blocks.value())):
del (self.m_neuron_blocks.value()[0])
for nb in c:
self.m_neuron_blocks.value().append(nb)
def loop(self):
print("loop of the custom placer has been called")
# OPTIONAL do some stuff, shuffle pops, etc.
def finalise(self):
print("finalise of the custom placer has been called")
# OPTIONAL do some stuff, put pops back to original place etc.
marocco = self.marocco
user_strat = myPlacer()
marocco.neuron_placement.default_placement_strategy(user_strat)
pynn.setup(marocco=marocco)
self.network()
result = self.load_results()
hicann = C.HICANNOnWafer(Enum(42))
nb = C.NeuronBlockOnHICANN(Enum(4))
for pop in self.pops:
for nrn in pop:
placement_item, = result.placement.find(nrn)
logical_neuron = placement_item.logical_neuron()
for denmem in logical_neuron:
self.assertEqual(hicann, denmem.toHICANNOnWafer())
self.assertEqual(nb, denmem.toNeuronBlockOnHICANN())