def create_app_less():
app_graph = ApplicationGraph("Test")
mac_graph = MachineGraph("Test", app_graph)
n_keys_map = DictBasedMachinePartitionNKeysMap()
# An output vertex to aim things at (to make keys required)
out_mac_vertex = SimpleMacVertex()
mac_graph.add_vertex(out_mac_vertex)
# Create 5 application vertices (3 bits)
for app_index in range(5):
# For each, create up to (5 x 4) + 1 = 21 machine vertices (5 bits)
for mac_index in range((app_index * 4) + 1):
mac_vertex = SimpleMacVertex()
mac_graph.add_vertex(mac_vertex)
# For each machine vertex create up to
# (20 x 2) + 1 = 81(!) partitions (6 bits)
for mac_edge_index in range((mac_index * 2) + 1):
mac_edge = MachineEdge(mac_vertex, out_mac_vertex)
part_name = "Part{}".format(mac_edge_index)
mac_graph.add_edge(mac_edge, part_name)
# Give the partition up to (40 x 4) + 1 = 161 keys (8 bits)
p = mac_graph.get_outgoing_edge_partition_starting_at_vertex(
mac_vertex, part_name)
n_keys_map.set_n_keys_for_partition(
p, (mac_edge_index * 4) + 1)
return app_graph, mac_graph, n_keys_map
def create_graphs_only_fixed():
app_graph = ApplicationGraph("Test")
# An output vertex to aim things at (to make keys required)
out_app_vertex = SimpleAppVertex()
app_graph.add_vertex(out_app_vertex)
# Create 5 application vertices (3 bits)
app_vertex = SimpleAppVertex()
app_graph.add_vertex(app_vertex)
mac_graph = MachineGraph("Test", app_graph)
n_keys_map = DictBasedMachinePartitionNKeysMap()
# An output vertex to aim things at (to make keys required)
out_mac_vertex = SimpleMacVertex(app_vertex=out_app_vertex)
mac_graph.add_vertex(out_mac_vertex)
mac_vertex = SimpleMacVertex(app_vertex=app_vertex)
mac_graph.add_vertex(mac_vertex)
for mac_edge_index in range(2):
mac_edge = MachineEdge(mac_vertex, out_mac_vertex)
part_name = "Part{}".format(mac_edge_index)
mac_graph.add_edge(mac_edge, part_name)
p = mac_graph.get_outgoing_edge_partition_starting_at_vertex(
mac_vertex, part_name)
if (mac_edge_index == 0):
p.add_constraint(FixedKeyAndMaskConstraint(
[BaseKeyAndMask(0x4c00000, 0xFFFFFFFE)]))
if (mac_edge_index == 1):
p.add_constraint(FixedKeyAndMaskConstraint(
[BaseKeyAndMask(0x4c00000, 0xFFFFFFFF)]))
n_keys_map.set_n_keys_for_partition(
p, (mac_edge_index * 4) + 1)
return app_graph, mac_graph, n_keys_map
def create_big(with_fixed):
# This test shows how easy it is to trip up the allocator with a retina
app_graph = ApplicationGraph("Test")
# Create a single "big" vertex
big_app_vertex = SimpleTestVertex(1, label="Retina")
app_graph.add_vertex(big_app_vertex)
# Create a single output vertex (which won't send)
out_app_vertex = SimpleTestVertex(1, label="Destination")
app_graph.add_vertex(out_app_vertex)
# Create a load of middle vertex
mid_app_vertex = SimpleTestVertex(1, "Population")
app_graph.add_vertex(mid_app_vertex)
mac_graph = MachineGraph("Test", app_graph)
n_keys_map = DictBasedMachinePartitionNKeysMap()
# Create a single big machine vertex
big_mac_vertex = big_app_vertex.create_machine_vertex(None,
None,
label="RETINA")
mac_graph.add_vertex(big_mac_vertex)
# Create a single output vertex (which won't send)
out_mac_vertex = out_app_vertex.create_machine_vertex(None, None)
mac_graph.add_vertex(out_mac_vertex)
# Create a load of middle vertices and connect them up
for _ in range(2000): # 2000 needs 11 bits
mid_mac_vertex = mid_app_vertex.create_machine_vertex(None, None)
mac_graph.add_vertex(mid_mac_vertex)
edge = MachineEdge(big_mac_vertex, mid_mac_vertex)
mac_graph.add_edge(edge, "Test")
edge_2 = MachineEdge(mid_mac_vertex, out_mac_vertex)
mac_graph.add_edge(edge_2, "Test")
mid_part = mac_graph.get_outgoing_edge_partition_starting_at_vertex(
mid_mac_vertex, "Test")
n_keys_map.set_n_keys_for_partition(mid_part, 100)
big_mac_part = mac_graph.get_outgoing_edge_partition_starting_at_vertex(
big_mac_vertex, "Test")
if with_fixed:
big_mac_part.add_constraint(
FixedKeyAndMaskConstraint([BaseKeyAndMask(0x0, 0x180000)]))
# Make the "retina" need 21 bits, so total is now 21 + 11 = 32 bits,
# but the application vertices need some bits too
n_keys_map.set_n_keys_for_partition(big_mac_part, 1024 * 768 * 2)
return app_graph, mac_graph, n_keys_map
def test_write_synaptic_matrix_and_master_population_table(self):
MockSimulator.setup()
default_config_paths = os.path.join(
os.path.dirname(abstract_spinnaker_common.__file__),
AbstractSpiNNakerCommon.CONFIG_FILE_NAME)
config = conf_loader.load_config(
AbstractSpiNNakerCommon.CONFIG_FILE_NAME, default_config_paths)
config.set("Simulation", "one_to_one_connection_dtcm_max_bytes", 40)
machine_time_step = 1000.0
pre_app_vertex = SimpleApplicationVertex(10)
pre_vertex = SimpleMachineVertex(resources=None)
pre_vertex_slice = Slice(0, 9)
post_app_vertex = SimpleApplicationVertex(10)
post_vertex = SimpleMachineVertex(resources=None)
post_vertex_slice = Slice(0, 9)
post_slice_index = 0
one_to_one_connector_1 = OneToOneConnector(None)
one_to_one_connector_1.set_projection_information(
pre_app_vertex, post_app_vertex, None, machine_time_step)
one_to_one_connector_1.set_weights_and_delays(1.5, 1.0)
one_to_one_connector_2 = OneToOneConnector(None)
one_to_one_connector_2.set_projection_information(
pre_app_vertex, post_app_vertex, None, machine_time_step)
one_to_one_connector_2.set_weights_and_delays(2.5, 2.0)
all_to_all_connector = AllToAllConnector(None)
all_to_all_connector.set_projection_information(
pre_app_vertex, post_app_vertex, None, machine_time_step)
all_to_all_connector.set_weights_and_delays(4.5, 4.0)
direct_synapse_information_1 = SynapseInformation(
one_to_one_connector_1, SynapseDynamicsStatic(), 0)
direct_synapse_information_2 = SynapseInformation(
one_to_one_connector_2, SynapseDynamicsStatic(), 1)
all_to_all_synapse_information = SynapseInformation(
all_to_all_connector, SynapseDynamicsStatic(), 0)
app_edge = ProjectionApplicationEdge(
pre_app_vertex, post_app_vertex, direct_synapse_information_1)
app_edge.add_synapse_information(direct_synapse_information_2)
app_edge.add_synapse_information(all_to_all_synapse_information)
machine_edge = ProjectionMachineEdge(
app_edge.synapse_information, pre_vertex, post_vertex)
partition_name = "TestPartition"
graph = MachineGraph("Test")
graph.add_vertex(pre_vertex)
graph.add_vertex(post_vertex)
graph.add_edge(machine_edge, partition_name)
graph_mapper = GraphMapper()
graph_mapper.add_vertex_mapping(
pre_vertex, pre_vertex_slice, pre_app_vertex)
graph_mapper.add_vertex_mapping(
post_vertex, post_vertex_slice, post_app_vertex)
graph_mapper.add_edge_mapping(machine_edge, app_edge)
weight_scales = [4096.0, 4096.0]
key = 0
routing_info = RoutingInfo()
routing_info.add_partition_info(PartitionRoutingInfo(
[BaseKeyAndMask(key, 0xFFFFFFF0)],
graph.get_outgoing_edge_partition_starting_at_vertex(
pre_vertex, partition_name)))
temp_spec = tempfile.mktemp()
spec_writer = FileDataWriter(temp_spec)
spec = DataSpecificationGenerator(spec_writer, None)
master_pop_sz = 1000
master_pop_region = 0
all_syn_block_sz = 2000
synapse_region = 1
spec.reserve_memory_region(master_pop_region, master_pop_sz)
spec.reserve_memory_region(synapse_region, all_syn_block_sz)
synapse_type = MockSynapseType()
synaptic_manager = SynapticManager(
synapse_type=synapse_type, ring_buffer_sigma=5.0,
spikes_per_second=100.0, config=config)
synaptic_manager._write_synaptic_matrix_and_master_population_table(
spec, [post_vertex_slice], post_slice_index, post_vertex,
post_vertex_slice, all_syn_block_sz, weight_scales,
master_pop_region, synapse_region, routing_info, graph_mapper,
graph, machine_time_step)
spec.end_specification()
spec_writer.close()
spec_reader = FileDataReader(temp_spec)
executor = DataSpecificationExecutor(
spec_reader, master_pop_sz + all_syn_block_sz)
executor.execute()
master_pop_table = executor.get_region(0)
synaptic_matrix = executor.get_region(1)
all_data = bytearray()
all_data.extend(master_pop_table.region_data[
:master_pop_table.max_write_pointer])
all_data.extend(synaptic_matrix.region_data[
:synaptic_matrix.max_write_pointer])
master_pop_table_address = 0
synaptic_matrix_address = master_pop_table.max_write_pointer
direct_synapses_address = struct.unpack_from(
"<I", synaptic_matrix.region_data)[0]
direct_synapses_address += synaptic_matrix_address + 8
indirect_synapses_address = synaptic_matrix_address + 4
placement = Placement(None, 0, 0, 1)
transceiver = MockTransceiverRawData(all_data)
# Get the master population table details
items = synaptic_manager._poptable_type\
.extract_synaptic_matrix_data_location(
key, master_pop_table_address, transceiver,
placement.x, placement.y)
# The first entry should be direct, but the rest should be indirect;
# the second is potentially direct, but has been restricted by the
# restriction on the size of the direct matrix
assert len(items) == 3
# TODO: This has been changed because direct matrices are disabled!
assert not items[0][2]
assert not items[1][2]
assert not items[2][2]
data_1, row_len_1 = synaptic_manager._retrieve_synaptic_block(
transceiver=transceiver, placement=placement,
master_pop_table_address=master_pop_table_address,
indirect_synapses_address=indirect_synapses_address,
direct_synapses_address=direct_synapses_address, key=key,
n_rows=pre_vertex_slice.n_atoms, index=0,
using_extra_monitor_cores=False)
connections_1 = synaptic_manager._synapse_io.read_synapses(
direct_synapse_information_1, pre_vertex_slice, post_vertex_slice,
row_len_1, 0, 2, weight_scales, data_1, None,
app_edge.n_delay_stages, machine_time_step)
# The first matrix is a 1-1 matrix, so row length is 1
assert row_len_1 == 1
# Check that all the connections have the right weight and delay
assert len(connections_1) == post_vertex_slice.n_atoms
assert all([conn["weight"] == 1.5 for conn in connections_1])
assert all([conn["delay"] == 1.0 for conn in connections_1])
data_2, row_len_2 = synaptic_manager._retrieve_synaptic_block(
transceiver=transceiver, placement=placement,
master_pop_table_address=master_pop_table_address,
indirect_synapses_address=indirect_synapses_address,
direct_synapses_address=direct_synapses_address, key=key,
n_rows=pre_vertex_slice.n_atoms, index=1,
using_extra_monitor_cores=False)
connections_2 = synaptic_manager._synapse_io.read_synapses(
direct_synapse_information_2, pre_vertex_slice, post_vertex_slice,
row_len_2, 0, 2, weight_scales, data_2, None,
app_edge.n_delay_stages, machine_time_step)
# The second matrix is a 1-1 matrix, so row length is 1
assert row_len_2 == 1
# Check that all the connections have the right weight and delay
assert len(connections_2) == post_vertex_slice.n_atoms
assert all([conn["weight"] == 2.5 for conn in connections_2])
assert all([conn["delay"] == 2.0 for conn in connections_2])
data_3, row_len_3 = synaptic_manager._retrieve_synaptic_block(
transceiver=transceiver, placement=placement,
master_pop_table_address=master_pop_table_address,
indirect_synapses_address=indirect_synapses_address,
direct_synapses_address=direct_synapses_address, key=key,
n_rows=pre_vertex_slice.n_atoms, index=2,
using_extra_monitor_cores=False)
connections_3 = synaptic_manager._synapse_io.read_synapses(
all_to_all_synapse_information, pre_vertex_slice,
post_vertex_slice, row_len_3, 0, 2, weight_scales, data_3, None,
app_edge.n_delay_stages, machine_time_step)
# The third matrix is an all-to-all matrix, so length is n_atoms
assert row_len_3 == post_vertex_slice.n_atoms
# Check that all the connections have the right weight and delay
assert len(connections_3) == \
post_vertex_slice.n_atoms * pre_vertex_slice.n_atoms
assert all([conn["weight"] == 4.5 for conn in connections_3])
assert all([conn["delay"] == 4.0 for conn in connections_3])
def create_graphs1(with_fixed):
app_graph = ApplicationGraph("Test")
# An output vertex to aim things at (to make keys required)
out_app_vertex = SimpleAppVertex()
app_graph.add_vertex(out_app_vertex)
# Create 5 application vertices (3 bits)
app_vertices = list()
for app_index in range(5):
app_vertices.append(SimpleAppVertex())
app_graph.add_vertices(app_vertices)
mac_graph = MachineGraph("Test", app_graph)
n_keys_map = DictBasedMachinePartitionNKeysMap()
# An output vertex to aim things at (to make keys required)
out_mac_vertex = SimpleMacVertex(app_vertex=out_app_vertex)
mac_graph.add_vertex(out_mac_vertex)
# Create 5 application vertices (3 bits)
for app_index, app_vertex in enumerate(app_vertices):
# For each, create up to (5 x 4) + 1 = 21 machine vertices (5 bits)
for mac_index in range((app_index * 4) + 1):
mac_vertex = SimpleMacVertex(app_vertex=app_vertex)
mac_graph.add_vertex(mac_vertex)
# For each machine vertex create up to
# (20 x 2) + 1 = 81(!) partitions (6 bits)
for mac_edge_index in range((mac_index * 2) + 1):
mac_edge = MachineEdge(mac_vertex, out_mac_vertex)
part_name = "Part{}".format(mac_edge_index)
mac_graph.add_edge(mac_edge, part_name)
# Give the partition up to (40 x 4) + 1 = 161 keys (8 bits)
p = mac_graph.get_outgoing_edge_partition_starting_at_vertex(
mac_vertex, part_name)
if with_fixed:
if (app_index == 2 and mac_index == 4 and
part_name == "Part7"):
p.add_constraint(FixedKeyAndMaskConstraint(
[BaseKeyAndMask(0xFE00000, 0xFFFFFFC0)]))
if (app_index == 2 and mac_index == 0 and
part_name == "Part1"):
p.add_constraint(FixedKeyAndMaskConstraint(
[BaseKeyAndMask(0x4c00000, 0xFFFFFFFE)]))
if (app_index == 2 and mac_index == 0 and
part_name == "Part1"):
p.add_constraint(FixedKeyAndMaskConstraint(
[BaseKeyAndMask(0x4c00000, 0xFFFFFFFF)]))
if (app_index == 3 and mac_index == 0 and
part_name == "Part1"):
p.add_constraint(FixedKeyAndMaskConstraint(
[BaseKeyAndMask(0x3300000, 0xFFFFFFFF)]))
if (app_index == 3 and mac_index == 0 and
part_name == "Part1"):
p.add_constraint(FixedKeyAndMaskConstraint(
[BaseKeyAndMask(0x3300001, 0)]))
n_keys_map.set_n_keys_for_partition(
p, (mac_edge_index * 4) + 1)
return app_graph, mac_graph, n_keys_map
def test_convert_to_file_machine_graph_pure_multicast(tmpdir):
# Construct the sample graph
graph = MachineGraph("foo")
v0 = SimpleMachineVertex(ResourceContainer())
graph.add_vertex(v0)
tag = IPtagResource("1.2.3.4", 5, False, tag="footag")
v1 = SimpleMachineVertex(ResourceContainer(iptags=[tag]))
graph.add_vertex(v1)
t1id = md5("%s_tag" % ident(v1))
tag = ReverseIPtagResource(tag="bartag")
v2 = SimpleMachineVertex(ResourceContainer(reverse_iptags=[tag]))
graph.add_vertex(v2)
t2id = md5("%s_tag" % ident(v2))
graph.add_edge(MachineEdge(v1, v0), "part1")
p1 = graph.get_outgoing_edge_partition_starting_at_vertex(v1, "part1")
graph.add_edge(MachineEdge(v0, v2, label="foobar"), "part2")
p2 = graph.get_outgoing_edge_partition_starting_at_vertex(v0, "part2")
# Convert it to JSON
algo = ConvertToFileMachineGraphPureMulticast()
fn = tmpdir.join("foo.json")
filename, _vertex_by_id, _partition_by_id = algo(graph, str(fn))
assert filename == str(fn)
# Rebuild and compare; simplest way of checking given that order is not
# preserved in the underlying string and altering that is hard
obj = json.loads(fn.read())
baseline = {
"vertices_resources": {
ident(v0): {
"cores": 1,
"sdram": 0
},
ident(v1): {
"cores": 1,
"sdram": 0
},
t1id: {
"cores": 0,
"sdram": 0
},
ident(v2): {
"cores": 1,
"sdram": 0
},
t2id: {
"cores": 0,
"sdram": 0
}
},
"edges": {
ident(p1): {
"source": ident(v1),
"sinks": [ident(v0)],
"type": "multicast",
"weight": 1
},
ident(p2): {
"source": ident(v0),
"sinks": [ident(v2)],
"type": "multicast",
"weight": 1
},
t1id: {
"source": ident(v1),
"sinks": [t1id],
"weight": 1.0,
"type": "FAKE_TAG_EDGE"
},
t2id: {
"source": ident(v2),
"sinks": [t2id],
"weight": 1.0,
"type": "FAKE_TAG_EDGE"
}
}
}
assert obj == baseline