def generate_data_spec(
self, subvertex, placement, sub_graph, graph, routing_info,
hostname, graph_subgraph_mapper, report_folder, ip_tags,
reverse_ip_tags, write_text_specs, application_run_time_folder):
# Create new DataSpec for this processor:
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
self._update_virtual_key(routing_info, sub_graph)
self._fill_send_buffer()
# Reserve regions
self._reserve_regions(spec)
# Write the system region
self._write_basic_setup_info(spec, self._REGIONS.SYSTEM.value)
# Write the additional recording information
self.write_recording_data(
spec, ip_tags, [self._record_buffer_size],
self._buffer_size_before_receive)
# Write the configuration information
self._write_configuration(spec, routing_info, sub_graph, ip_tags)
# End spec
spec.end_specification()
data_writer.close()
return [data_writer.filename]
def generate_data_spec(self, subvertex, placement, sub_graph, graph,
routing_info, hostname, graph_sub_graph_mapper,
report_folder, ip_tags, reverse_ip_tags,
write_text_specs, application_run_time_folder):
"""
Model-specific construction of the data blocks necessary to build a
single Application Monitor on one core.
"""
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
spec.comment("\n*** Spec for AppMonitor Instance ***\n\n")
# Construct the data images needed for the Neuron:
self.reserve_memory_regions(spec)
self.write_setup_info(spec)
self.write_configuration_region(spec, ip_tags)
# End-of-Spec:
spec.end_specification()
data_writer.close()
def generate_data_spec(
self, subvertex, placement, sub_graph, graph, routing_info,
hostname, graph_subgraph_mapper, report_folder, ip_tags,
reverse_ip_tags, write_text_specs, application_run_time_folder):
# Create new DataSpec for this processor:
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
self._update_virtual_key(routing_info, sub_graph)
self._fill_send_buffer()
# Reserve regions
self._reserve_regions(spec)
# Write the system region
self._write_basic_setup_info(spec, self._REGIONS.SYSTEM.value)
# Write the additional recording information
self.write_recording_data(
spec, ip_tags, [self._record_buffer_size],
self._buffer_size_before_receive)
# Write the configuration information
self._write_configuration(spec, routing_info, sub_graph, ip_tags)
# End spec
spec.end_specification()
data_writer.close()
return data_writer.filename
def generate_data_spec(
self, subvertex, placement, sub_graph, graph, routing_info,
hostname, graph_mapper, report_folder, ip_tags, reverse_ip_tags,
write_text_specs, application_run_time_folder):
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
# Reserve memory:
spec.comment("\nReserving memory space for data regions:\n\n")
# ###################################################################
# Reserve SDRAM space for memory areas:
delay_params_header_words = 3
vertex_slice = graph_mapper.get_subvertex_slice(subvertex)
n_atoms = vertex_slice.hi_atom - vertex_slice.lo_atom + 1
block_len_words = int(math.ceil(n_atoms / 32.0))
num_delay_blocks, delay_blocks = self.get_delay_blocks(
subvertex, sub_graph, graph_mapper)
delay_params_sz = 4 * (delay_params_header_words +
(num_delay_blocks * block_len_words))
spec.reserve_memory_region(
region=self._DELAY_EXTENSION_REGIONS.SYSTEM.value,
size=constants.DATA_SPECABLE_BASIC_SETUP_INFO_N_WORDS * 4,
label='setup')
spec.reserve_memory_region(
region=self._DELAY_EXTENSION_REGIONS.DELAY_PARAMS.value,
size=delay_params_sz, label='delay_params')
self.write_setup_info(spec)
spec.comment("\n*** Spec for Delay Extension Instance ***\n\n")
key = None
if len(sub_graph.outgoing_subedges_from_subvertex(subvertex)) > 0:
keys_and_masks = routing_info.get_keys_and_masks_from_subedge(
sub_graph.outgoing_subedges_from_subvertex(subvertex)[0])
# NOTE: using the first key assigned as the key. Should in future
# get the list of keys and use one per neuron, to allow arbitrary
# key and mask assignments
key = keys_and_masks[0].key
self.write_delay_parameters(spec, placement.x, placement.y,
placement.p, subvertex, num_delay_blocks,
delay_blocks, vertex_slice, key)
# End-of-Spec:
spec.end_specification()
data_writer.close()
return [data_writer.filename]
def generate_data_spec(
self, subvertex, placement, partitioned_graph, graph, routing_info,
hostname, graph_mapper, report_folder, ip_tags, reverse_ip_tags,
write_text_specs, application_run_time_folder):
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
vertex_slice = graph_mapper.get_subvertex_slice(subvertex)
spike_buffer_size = self._spike_recorder.get_sdram_usage_in_bytes(
vertex_slice.n_atoms, self._max_spikes_per_ts(vertex_slice),
self._no_machine_time_steps)
spike_history_sz = recording_utils.get_buffer_sizes(
self._spike_buffer_max_size, spike_buffer_size,
self._enable_buffered_recording)
spike_buffering_needed = recording_utils.needs_buffering(
self._spike_buffer_max_size, spike_buffer_size,
self._enable_buffered_recording)
buffer_size_before_receive = self._buffer_size_before_receive
if not spike_buffering_needed:
buffer_size_before_receive = spike_history_sz + 256
spec.comment("\n*** Spec for SpikeSourcePoisson Instance ***\n\n")
# Basic setup plus 8 bytes for recording flags and recording size
setup_sz = ((front_end_common_constants.
DATA_SPECABLE_BASIC_SETUP_INFO_N_WORDS * 4) +
subvertex.get_recording_data_size(1))
poisson_params_sz = self.get_params_bytes(vertex_slice)
# Reserve SDRAM space for memory areas:
self.reserve_memory_regions(
spec, setup_sz, poisson_params_sz, spike_history_sz, subvertex)
self._write_setup_info(
spec, spike_history_sz, ip_tags, buffer_size_before_receive,
subvertex)
# Every subedge should have the same key
key = None
partitions = partitioned_graph.\
outgoing_edges_partitions_from_vertex(subvertex)
for partition in partitions.values():
keys_and_masks = \
routing_info.get_keys_and_masks_from_partition(partition)
key = keys_and_masks[0].key
self._write_poisson_parameters(spec, key, vertex_slice)
# End-of-Spec:
spec.end_specification()
data_writer.close()
return data_writer.filename
def generate_data_spec(self, subvertex, placement, subgraph, graph,
routing_info, hostname, graph_mapper, report_folder,
ip_tags, reverse_ip_tags, write_text_specs,
application_run_time_folder):
"""
Model-specific construction of the data blocks necessary to build a
single SpikeSourcePoisson on one core.
:param subvertex:
:param placement:
:param subgraph:
:param graph:
:param routing_info:
:param hostname:
:param graph_mapper:
:param report_folder:
:param ip_tags:
:param reverse_ip_tags:
:param write_text_specs:
:param application_run_time_folder:
:return:
"""
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
vertex_slice = graph_mapper.get_subvertex_slice(subvertex)
spike_hist_buff_sz = self._spike_recorder.get_sdram_usage_in_bytes(
vertex_slice.n_atoms, self._no_machine_time_steps)
spec.comment("\n*** Spec for SpikeSourcePoisson Instance ***\n\n")
# Basic setup plus 8 bytes for recording flags and recording size
setup_sz = ((constants.DATA_SPECABLE_BASIC_SETUP_INFO_N_WORDS * 4) + 8)
poisson_params_sz = self.get_params_bytes(vertex_slice)
# Reserve SDRAM space for memory areas:
self.reserve_memory_regions(
spec, setup_sz, poisson_params_sz, spike_hist_buff_sz)
self.write_setup_info(spec, spike_hist_buff_sz)
# Every subedge should have the same key
key = None
subedges = subgraph.outgoing_subedges_from_subvertex(subvertex)
if len(subedges) > 0:
keys_and_masks = routing_info.get_keys_and_masks_from_subedge(
subedges[0])
key = keys_and_masks[0].key
self.write_poisson_parameters(spec, key, vertex_slice.n_atoms)
# End-of-Spec:
spec.end_specification()
data_writer.close()
def test_call(self):
executor = HostExecuteDataSpecification()
transceiver = _MockTransceiver(user_0_addresses={0: 1000})
machine = VirtualMachine(2, 2)
tempdir = tempfile.mkdtemp()
dsg_targets = DataSpecificationTargets(machine, tempdir)
with dsg_targets.create_data_spec(0, 0, 0) as spec_writer:
spec = DataSpecificationGenerator(spec_writer)
spec.reserve_memory_region(0, 100)
spec.reserve_memory_region(1, 100, empty=True)
spec.reserve_memory_region(2, 100)
spec.switch_write_focus(0)
spec.write_value(0)
spec.write_value(1)
spec.write_value(2)
spec.switch_write_focus(2)
spec.write_value(3)
spec.end_specification()
infos = executor.__call__(
transceiver, machine, 30, dsg_targets, tempdir)
# Test regions - although 3 are created, only 2 should be uploaded
# (0 and 2), and only the data written should be uploaded
# The space between regions should be as allocated regardless of
# how much data is written
header_and_table_size = (MAX_MEM_REGIONS + 2) * 4
regions = transceiver.regions_written
self.assertEqual(len(regions), 4)
# Base address for header and table
self.assertEqual(regions[0][0], 0)
# Base address for region 0 (after header and table)
self.assertEqual(regions[1][0], header_and_table_size)
# Base address for region 2
self.assertEqual(regions[2][0], header_and_table_size + 200)
# User 0 write address
self.assertEqual(regions[3][0], 1000)
# Size of header and table
self.assertEqual(len(regions[0][1]), header_and_table_size)
# Size of region 0
self.assertEqual(len(regions[1][1]), 12)
# Size of region 2
self.assertEqual(len(regions[2][1]), 4)
# Size of user 0
self.assertEqual(len(regions[3][1]), 4)
info = infos[(0, 0, 0)]
self.assertEqual(info["memory_used"], 372)
self.assertEqual(info["memory_written"], 88)
def generate_data_spec(
self, subvertex, placement, partitioned_graph, graph, routing_info,
hostname, graph_mapper, report_folder, ip_tags, reverse_ip_tags,
write_text_specs, application_run_time_folder):
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
vertex_slice = graph_mapper.get_subvertex_slice(subvertex)
spike_buffer_size = self._spike_recorder.get_sdram_usage_in_bytes(
vertex_slice.n_atoms, self._no_machine_time_steps)
spike_history_sz = recording_utils.get_buffer_sizes(
self._spike_buffer_max_size, spike_buffer_size,
self._enable_buffered_recording)
spike_buffering_needed = recording_utils.needs_buffering(
self._spike_buffer_max_size, spike_buffer_size,
self._enable_buffered_recording)
buffer_size_before_receive = self._buffer_size_before_receive
if not spike_buffering_needed:
buffer_size_before_receive = spike_history_sz + 256
spec.comment("\n*** Spec for SpikeSourcePoisson Instance ***\n\n")
# Basic setup plus 8 bytes for recording flags and recording size
setup_sz = ((front_end_common_constants.
DATA_SPECABLE_BASIC_SETUP_INFO_N_WORDS * 4) +
subvertex.get_recording_data_size(1))
poisson_params_sz = self.get_params_bytes(vertex_slice)
# Reserve SDRAM space for memory areas:
self.reserve_memory_regions(
spec, setup_sz, poisson_params_sz, spike_history_sz, subvertex)
self._write_setup_info(
spec, spike_history_sz, ip_tags, buffer_size_before_receive,
subvertex)
# Every subedge should have the same key
key = None
partitions = partitioned_graph.\
outgoing_edges_partitions_from_vertex(subvertex)
for partition in partitions.values():
keys_and_masks = \
routing_info.get_keys_and_masks_from_partition(partition)
key = keys_and_masks[0].key
self._write_poisson_parameters(spec, key, vertex_slice)
# End-of-Spec:
spec.end_specification()
data_writer.close()
return data_writer.filename
def generate_data_spec(self, subvertex, placement, partitioned_graph,
graph, routing_info, hostname,
graph_subgraph_mapper, report_folder, ip_tags,
reverse_ip_tags, write_text_specs,
application_run_time_folder):
"""
Model-specific construction of the data blocks necessary to build a
single external retina device.
"""
# Create new DataSpec for this processor:
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
# reserve regions
self.reserve_memory_regions(spec)
# Write the setup region
spec.comment("\n*** Spec for robot motor control ***\n\n")
self._write_basic_setup_info(spec, self.SYSTEM_REGION)
# locate correct subedge for key
edge_key = None
if len(graph.outgoing_edges_from_vertex(self)) != 1:
raise exceptions.SpynnakerException(
"This motor should only have one outgoing edge to the robot")
partitions = partitioned_graph.\
outgoing_edges_partitions_from_vertex(subvertex)
for partition in partitions.values():
edge_keys_and_masks = \
routing_info.get_keys_and_masks_from_partition(partition)
edge_key = edge_keys_and_masks[0].key
# write params to memory
spec.switch_write_focus(region=self.PARAMS_REGION)
spec.write_value(data=edge_key)
spec.write_value(data=self._speed)
spec.write_value(data=self._sample_time)
spec.write_value(data=self._update_time)
spec.write_value(data=self._delay_time)
spec.write_value(data=self._delta_threshold)
if self._continue_if_not_different:
spec.write_value(data=1)
else:
spec.write_value(data=0)
# End-of-Spec:
spec.end_specification()
data_writer.close()
return data_writer.filename
def generate_data_spec(self, subvertex, placement, subgraph, graph,
routing_info, hostname, graph_mapper, report_folder,
ip_tags, reverse_ip_tags, write_text_specs,
application_run_time_folder):
"""
Model-specific construction of the data blocks necessary to build a
single SpikeSourcePoisson on one core.
:param subvertex:
:param placement:
:param subgraph:
:param graph:
:param routing_info:
:param hostname:
:param graph_mapper:
:param report_folder:
:param ip_tags:
:param reverse_ip_tags:
:param write_text_specs:
:param application_run_time_folder:
:return:
"""
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
vertex_slice = graph_mapper.get_subvertex_slice(subvertex)
spike_hist_buff_sz = self.get_spike_buffer_size(vertex_slice)
spec.comment("\n*** Spec for SpikeSourcePoisson Instance ***\n\n")
# Basic setup plus 8 bytes for recording flags and recording size
setup_sz = ((constants.DATA_SPECABLE_BASIC_SETUP_INFO_N_WORDS * 4) + 8)
poisson_params_sz = self.get_params_bytes(vertex_slice)
# Reserve SDRAM space for memory areas:
self.reserve_memory_regions(spec, setup_sz, poisson_params_sz,
spike_hist_buff_sz)
self.write_setup_info(spec, spike_hist_buff_sz)
# Every subedge should have the same key
keys_and_masks = routing_info.get_keys_and_masks_from_subedge(
subgraph.outgoing_subedges_from_subvertex(subvertex)[0])
key = keys_and_masks[0].key
self.write_poisson_parameters(spec, key, vertex_slice.n_atoms)
# End-of-Spec:
spec.end_specification()
data_writer.close()
def test_call(self):
executor = HostExecuteDataSpecification()
transceiver = _MockTransceiver(user_0_addresses={0: 1000})
machine = VirtualMachine(2, 2)
# Write a data spec to execute
temp_spec = mktemp()
spec_writer = FileDataWriter(temp_spec)
spec = DataSpecificationGenerator(spec_writer)
spec.reserve_memory_region(0, 100)
spec.reserve_memory_region(1, 100, empty=True)
spec.reserve_memory_region(2, 100)
spec.switch_write_focus(0)
spec.write_value(0)
spec.write_value(1)
spec.write_value(2)
spec.switch_write_focus(2)
spec.write_value(3)
spec.end_specification()
# Execute the spec
dsg_targets = {(0, 0, 0): temp_spec}
executor.__call__(transceiver, machine, 30, dsg_targets)
# Test regions - although 3 are created, only 2 should be uploaded
# (0 and 2), and only the data written should be uploaded
# The space between regions should be as allocated regardless of
# how much data is written
header_and_table_size = (constants.MAX_MEM_REGIONS + 2) * 4
regions = transceiver.regions_written
self.assertEqual(len(regions), 4)
# Base address for header and table
self.assertEqual(regions[0][0], 0)
# Base address for region 0 (after header and table)
self.assertEqual(regions[1][0], header_and_table_size)
# Base address for region 2
self.assertEqual(regions[2][0], header_and_table_size + 200)
# User 0 write address
self.assertEqual(regions[3][0], 1000)
# Size of header and table
self.assertEqual(len(regions[0][1]), header_and_table_size)
# Size of region 0
self.assertEqual(len(regions[1][1]), 12)
# Size of region 2
self.assertEqual(len(regions[2][1]), 4)
# Size of user 0
self.assertEqual(len(regions[3][1]), 4)
def generate_data_spec(self, subvertex, placement, subgraph, graph,
routing_info, hostname, graph_mapper, report_folder,
ip_tags, reverse_ip_tags, write_text_specs,
application_run_time_folder):
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
vertex_slice = graph_mapper.get_subvertex_slice(subvertex)
spike_hist_buff_sz = self._spike_recorder.get_sdram_usage_in_bytes(
vertex_slice.n_atoms, self._no_machine_time_steps)
buffer_size_before_receive = self._buffer_size_before_receive
if config.getboolean("Buffers", "enable_buffered_recording"):
if spike_hist_buff_sz < self._spike_buffer_max_size:
buffer_size_before_receive = spike_hist_buff_sz + 256
else:
spike_hist_buff_sz = self._spike_buffer_max_size
else:
buffer_size_before_receive = spike_hist_buff_sz + 256
spec.comment("\n*** Spec for SpikeSourcePoisson Instance ***\n\n")
# Basic setup plus 8 bytes for recording flags and recording size
setup_sz = ((constants.DATA_SPECABLE_BASIC_SETUP_INFO_N_WORDS * 4) +
self.get_recording_data_size(1))
poisson_params_sz = self.get_params_bytes(vertex_slice)
# Reserve SDRAM space for memory areas:
self.reserve_memory_regions(
spec, setup_sz, poisson_params_sz, spike_hist_buff_sz)
self._write_setup_info(
spec, spike_hist_buff_sz, ip_tags, buffer_size_before_receive)
# Every subedge should have the same key
key = None
subedges = subgraph.outgoing_subedges_from_subvertex(subvertex)
if len(subedges) > 0:
keys_and_masks = routing_info.get_keys_and_masks_from_subedge(
subedges[0])
key = keys_and_masks[0].key
self._write_poisson_parameters(spec, key, vertex_slice.n_atoms)
# End-of-Spec:
spec.end_specification()
data_writer.close()
return [data_writer.filename]
def generate_data_spec(self, subvertex, placement, subgraph, graph,
routing_info, hostname, graph_subgraph_mapper,
report_folder, ip_tags, reverse_ip_tags,
write_text_specs, application_run_time_folder):
"""
Model-specific construction of the data blocks necessary to build a
single external retina device.
"""
# Create new DataSpec for this processor:
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
# reserve regions
self.reserve_memory_regions(spec)
# Write the setup region
spec.comment("\n*** Spec for robot motor control ***\n\n")
self._write_basic_setup_info(spec, self.SYSTEM_REGION)
# locate correct subedge for key
edge_key = None
if len(graph.outgoing_edges_from_vertex(self)) != 1:
raise exceptions.SpynnakerException(
"This motor should only have one outgoing edge to the robot")
for subedge in subgraph.outgoing_subedges_from_subvertex(subvertex):
edge_keys_and_masks = \
routing_info.get_keys_and_masks_from_subedge(subedge)
edge_key = edge_keys_and_masks[0].key
# write params to memory
spec.switch_write_focus(region=self.PARAMS_REGION)
spec.write_value(data=edge_key)
spec.write_value(data=self._speed)
spec.write_value(data=self._sample_time)
spec.write_value(data=self._update_time)
spec.write_value(data=self._delay_time)
spec.write_value(data=self._delta_threshold)
if self._continue_if_not_different:
spec.write_value(data=1)
else:
spec.write_value(data=0)
# End-of-Spec:
spec.end_specification()
data_writer.close()
return [data_writer.filename]
def generate_data_spec(
self, subvertex, placement, subgraph, graph, routing_info,
hostname, graph_mapper, report_folder, ip_tags, reverse_ip_tags,
write_text_specs, application_run_time_folder):
"""
Model-specific construction of the data blocks necessary to build a
single SpikeSource Array on one core.
:param subvertex:
:param placement:
:param subgraph:
:param graph:
:param routing_info:
:param hostname:
:param graph_mapper:
:param report_folder:
:param ip_tags:
:param reverse_ip_tags:
:param write_text_specs:
:param application_run_time_folder:
:return:
"""
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
spec.comment("\n*** Spec for SpikeSourceArray Instance ***\n\n")
# ###################################################################
# Reserve SDRAM space for memory areas:
spec.comment("\nReserving memory space for spike data region:\n\n")
vertex_slice = graph_mapper.get_subvertex_slice(subvertex)
spike_buffer = self._get_spike_send_buffer(vertex_slice)
recording_size = (spike_buffer.total_region_size + 4 +
_RECORD_OVERALLOCATION)
self._reserve_memory_regions(spec, spike_buffer.buffer_size,
recording_size)
self._write_setup_info(
spec, spike_buffer.buffer_size, ip_tags, recording_size)
# End-of-Spec:
spec.end_specification()
data_writer.close()
# tell the subvertex its region size
subvertex.region_size = recording_size
def generate_data_spec(self, subvertex, placement, subgraph, graph,
routing_info, hostname, graph_mapper, report_folder,
ip_tags, reverse_ip_tags, write_text_specs,
application_run_time_folder):
"""
Model-specific construction of the data blocks necessary to build a
single SpikeSource Array on one core.
:param subvertex:
:param placement:
:param subgraph:
:param graph:
:param routing_info:
:param hostname:
:param graph_mapper:
:param report_folder:
:param ip_tags:
:param reverse_ip_tags:
:param write_text_specs:
:param application_run_time_folder:
:return:
"""
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
spec.comment("\n*** Spec for SpikeSourceArray Instance ***\n\n")
# ###################################################################
# Reserve SDRAM space for memory areas:
spec.comment("\nReserving memory space for spike data region:\n\n")
spike_buffer = self._get_spike_send_buffer(
graph_mapper.get_subvertex_slice(subvertex))
self._reserve_memory_regions(spec, spike_buffer.buffer_size)
self._write_setup_info(spec, spike_buffer.buffer_size, ip_tags)
# End-of-Spec:
spec.end_specification()
data_writer.close()
def generate_data_spec(self, placement, sub_graph, routing_info, hostname,
report_folder, ip_tags, reverse_ip_tags,
write_text_specs, application_run_time_folder):
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
spec.comment("\n*** Spec for LivePacketGather Instance ***\n\n")
# Construct the data images needed for the Neuron:
self._reserve_memory_regions(spec)
self._write_setup_info(spec)
self._write_configuration_region(spec, ip_tags)
# End-of-Spec:
spec.end_specification()
data_writer.close()
return data_writer.filename
def generate_data_spec(self, subvertex, placement, sub_graph, graph,
routing_info, hostname, graph_sub_graph_mapper,
report_folder, ip_tags, reverse_ip_tags,
write_text_specs, application_run_time_folder):
"""
"""
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
spec.comment("\n*** Spec for LivePacketGather Instance ***\n\n")
# Construct the data images needed for the Neuron:
self.reserve_memory_regions(spec)
self.write_setup_info(spec)
self.write_configuration_region(spec, ip_tags)
# End-of-Spec:
spec.end_specification()
data_writer.close()
return [data_writer.filename]
def generate_data_spec(self, subvertex, placement, partitioned_graph,
graph, routing_info, hostname, graph_mapper,
report_folder, ip_tags, reverse_ip_tags,
write_text_specs, application_run_time_folder):
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
# Reserve memory:
spec.comment("\nReserving memory space for data regions:\n\n")
# ###################################################################
# Reserve SDRAM space for memory areas:
vertex_slice = graph_mapper.get_subvertex_slice(subvertex)
n_words_per_stage = int(math.ceil(vertex_slice.n_atoms / 32.0))
delay_params_sz = 4 * (_DELAY_PARAM_HEADER_WORDS +
(self._n_delay_stages * n_words_per_stage))
spec.reserve_memory_region(
region=(DelayExtensionPartitionedVertex._DELAY_EXTENSION_REGIONS.
SYSTEM.value),
size=common_constants.DATA_SPECABLE_BASIC_SETUP_INFO_N_WORDS * 4,
label='setup')
spec.reserve_memory_region(
region=(DelayExtensionPartitionedVertex._DELAY_EXTENSION_REGIONS.
DELAY_PARAMS.value),
size=delay_params_sz,
label='delay_params')
subvertex.reserve_provenance_data_region(spec)
self.write_setup_info(spec)
spec.comment("\n*** Spec for Delay Extension Instance ***\n\n")
key = None
partitions = partitioned_graph.\
outgoing_edges_partitions_from_vertex(subvertex)
for partition in partitions.values():
keys_and_masks = \
routing_info.get_keys_and_masks_from_partition(partition)
# NOTE: using the first key assigned as the key. Should in future
# get the list of keys and use one per neuron, to allow arbitrary
# key and mask assignments
key = keys_and_masks[0].key
incoming_key = None
incoming_mask = None
incoming_edges = partitioned_graph.incoming_subedges_from_subvertex(
subvertex)
for incoming_edge in incoming_edges:
incoming_slice = graph_mapper.get_subvertex_slice(
incoming_edge.pre_subvertex)
if (incoming_slice.lo_atom == vertex_slice.lo_atom
and incoming_slice.hi_atom == vertex_slice.hi_atom):
partition = partitioned_graph.get_partition_of_subedge(
incoming_edge)
keys_and_masks = \
routing_info.get_keys_and_masks_from_partition(partition)
incoming_key = keys_and_masks[0].key
incoming_mask = keys_and_masks[0].mask
self.write_delay_parameters(spec, vertex_slice, key, incoming_key,
incoming_mask)
# End-of-Spec:
spec.end_specification()
data_writer.close()
return data_writer.filename
def test_call(self):
executor = HostExecuteDataSpecification()
transceiver = _MockTransceiver(user_0_addresses={0: 1000})
machine = virtual_machine(2, 2)
tempdir = tempfile.mkdtemp()
dsg_targets = DataSpecificationTargets(machine, tempdir)
with dsg_targets.create_data_spec(0, 0, 0) as spec_writer:
spec = DataSpecificationGenerator(spec_writer)
spec.reserve_memory_region(0, 100)
spec.reserve_memory_region(1, 100, empty=True)
spec.reserve_memory_region(2, 100)
spec.switch_write_focus(0)
spec.write_value(0)
spec.write_value(1)
spec.write_value(2)
spec.switch_write_focus(2)
spec.write_value(3)
spec.end_specification()
region_sizes = dict()
region_sizes[0, 0,
0] = (APP_PTR_TABLE_BYTE_SIZE + sum(spec.region_sizes))
# Execute the spec
targets = ExecutableTargets()
targets.add_processor("text.aplx", 0, 0, 0,
ExecutableType.USES_SIMULATION_INTERFACE)
infos = executor.execute_application_data_specs(
transceiver,
machine,
30,
dsg_targets,
False,
targets,
report_folder=tempdir,
region_sizes=region_sizes)
# Test regions - although 3 are created, only 2 should be uploaded
# (0 and 2), and only the data written should be uploaded
# The space between regions should be as allocated regardless of
# how much data is written
header_and_table_size = (MAX_MEM_REGIONS + 2) * BYTES_PER_WORD
regions = transceiver.regions_written
self.assertEqual(len(regions), 4)
# Base address for header and table
self.assertEqual(regions[1][0], 0)
# Base address for region 0 (after header and table)
self.assertEqual(regions[2][0], header_and_table_size)
# Base address for region 2
self.assertEqual(regions[3][0], header_and_table_size + 200)
# User 0 write address
self.assertEqual(regions[0][0], 1000)
# Size of header and table
self.assertEqual(len(regions[1][1]), header_and_table_size)
# Size of region 0
self.assertEqual(len(regions[2][1]), 12)
# Size of region 2
self.assertEqual(len(regions[3][1]), 4)
# Size of user 0
self.assertEqual(len(regions[0][1]), 4)
info = infos[(0, 0, 0)]
self.assertEqual(info.memory_used, 372)
self.assertEqual(info.memory_written, 88)
def generate_data_spec(
self, subvertex, placement, partitioned_graph, graph, routing_info,
hostname, graph_mapper, report_folder, ip_tags, reverse_ip_tags,
write_text_specs, application_run_time_folder):
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
# Reserve memory:
spec.comment("\nReserving memory space for data regions:\n\n")
# ###################################################################
# Reserve SDRAM space for memory areas:
vertex_slice = graph_mapper.get_subvertex_slice(subvertex)
n_words_per_stage = int(math.ceil(vertex_slice.n_atoms / 32.0))
delay_params_sz = 4 * (_DELAY_PARAM_HEADER_WORDS +
(self._n_delay_stages * n_words_per_stage))
spec.reserve_memory_region(
region=(
DelayExtensionPartitionedVertex.
_DELAY_EXTENSION_REGIONS.SYSTEM.value),
size=common_constants.DATA_SPECABLE_BASIC_SETUP_INFO_N_WORDS * 4,
label='setup')
spec.reserve_memory_region(
region=(
DelayExtensionPartitionedVertex.
_DELAY_EXTENSION_REGIONS.DELAY_PARAMS.value),
size=delay_params_sz, label='delay_params')
subvertex.reserve_provenance_data_region(spec)
self.write_setup_info(spec)
spec.comment("\n*** Spec for Delay Extension Instance ***\n\n")
key = None
partitions = partitioned_graph.\
outgoing_edges_partitions_from_vertex(subvertex)
for partition in partitions.values():
keys_and_masks = \
routing_info.get_keys_and_masks_from_partition(partition)
# NOTE: using the first key assigned as the key. Should in future
# get the list of keys and use one per neuron, to allow arbitrary
# key and mask assignments
key = keys_and_masks[0].key
incoming_key = None
incoming_mask = None
incoming_edges = partitioned_graph.incoming_subedges_from_subvertex(
subvertex)
for incoming_edge in incoming_edges:
incoming_slice = graph_mapper.get_subvertex_slice(
incoming_edge.pre_subvertex)
if (incoming_slice.lo_atom == vertex_slice.lo_atom and
incoming_slice.hi_atom == vertex_slice.hi_atom):
partition = partitioned_graph.get_partition_of_subedge(
incoming_edge)
keys_and_masks = \
routing_info.get_keys_and_masks_from_partition(partition)
incoming_key = keys_and_masks[0].key
incoming_mask = keys_and_masks[0].mask
self.write_delay_parameters(
spec, vertex_slice, key, incoming_key, incoming_mask)
# End-of-Spec:
spec.end_specification()
data_writer.close()
return data_writer.filename
def generate_data_spec(self, subvertex, placement, subgraph, graph,
routing_info, hostname, graph_mapper, report_folder,
ip_tags, reverse_ip_tags, write_text_specs,
application_run_time_folder):
"""
Model-specific construction of the data blocks necessary to
build a group of IF_curr_exp neurons resident on a single core.
:param subvertex:
:param placement:
:param subgraph:
:param graph:
:param routing_info:
:param hostname:
:param graph_mapper:
:param report_folder:
:param ip_tags:
:param reverse_ip_tags:
:param write_text_specs:
:param application_run_time_folder:
:return:
"""
# Create new DataSpec for this processor:
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
spec.comment("\n*** Spec for block of {} neurons ***\n".format(
self.model_name))
vertex_slice = graph_mapper.get_subvertex_slice(subvertex)
# Calculate the size of the tables to be reserved in SDRAM:
vertex_in_edges = graph.incoming_edges_to_vertex(self)
neuron_params_sz = self.get_neuron_params_size(vertex_slice)
synapse_params_sz = self.get_synapse_parameter_size(vertex_slice)
master_pop_table_sz = self.get_population_table_size(
vertex_slice, vertex_in_edges)
subvert_in_edges = subgraph.incoming_subedges_from_subvertex(subvertex)
all_syn_block_sz = self.get_exact_synaptic_block_memory_size(
graph_mapper, subvert_in_edges)
spike_hist_buff_sz = self.get_spike_buffer_size(vertex_slice)
potential_hist_buff_sz = self.get_v_buffer_size(vertex_slice)
gsyn_hist_buff_sz = self.get_g_syn_buffer_size(vertex_slice)
synapse_dynamics_region_sz = self.get_synapse_dynamics_parameter_size(
vertex_in_edges)
# Declare random number generators and distributions:
# TODO add random distrubtion stuff
# self.write_random_distribution_declarations(spec)
ring_buffer_shifts = self.get_ring_buffer_to_input_left_shifts(
subvertex, subgraph, graph_mapper, self._spikes_per_second,
self._machine_time_step, self._ring_buffer_sigma)
weight_scales = [self.get_weight_scale(r) for r in ring_buffer_shifts]
if logger.isEnabledFor(logging.DEBUG):
for t, r, w in zip(self.get_synapse_targets(), ring_buffer_shifts,
weight_scales):
logger.debug(
"Synapse type:%s - Ring buffer shift:%d, Max weight:%f" %
(t, r, w))
# update projections for future use
in_partitioned_edges = \
subgraph.incoming_subedges_from_subvertex(subvertex)
for partitioned_edge in in_partitioned_edges:
partitioned_edge.weight_scales_setter(weight_scales)
# Construct the data images needed for the Neuron:
self._reserve_population_based_memory_regions(
spec, neuron_params_sz, synapse_params_sz, master_pop_table_sz,
all_syn_block_sz, spike_hist_buff_sz, potential_hist_buff_sz,
gsyn_hist_buff_sz, synapse_dynamics_region_sz)
# Remove extension to get application name
self._write_setup_info(spec, spike_hist_buff_sz,
potential_hist_buff_sz, gsyn_hist_buff_sz)
# Every outgoing edge from this vertex should have the same key
key = None
if len(subgraph.outgoing_subedges_from_subvertex(subvertex)) > 0:
keys_and_masks = routing_info.get_keys_and_masks_from_subedge(
subgraph.outgoing_subedges_from_subvertex(subvertex)[0])
# NOTE: using the first key assigned as the key. Should in future
# get the list of keys and use one per neuron, to allow arbitrary
# key and mask assignments
key = keys_and_masks[0].key
self._write_neuron_parameters(spec, key, subvertex, vertex_slice)
self.write_synapse_parameters(spec, subvertex, vertex_slice)
spec.write_array(ring_buffer_shifts)
self.write_synaptic_matrix_and_master_population_table(
spec, subvertex, all_syn_block_sz, weight_scales,
constants.POPULATION_BASED_REGIONS.POPULATION_TABLE.value,
constants.POPULATION_BASED_REGIONS.SYNAPTIC_MATRIX.value,
routing_info, graph_mapper, subgraph)
self.write_synapse_dynamics_parameters(
spec, self._machine_time_step,
constants.POPULATION_BASED_REGIONS.SYNAPSE_DYNAMICS.value,
weight_scales)
in_subedges = subgraph.incoming_subedges_from_subvertex(subvertex)
for subedge in in_subedges:
subedge.free_sublist()
# End the writing of this specification:
spec.end_specification()
data_writer.close()
def generate_data_spec(
self, subvertex, placement, subgraph, graph, routing_info,
hostname, graph_mapper, report_folder, ip_tags, reverse_ip_tags,
write_text_specs, application_run_time_folder):
"""
Model-specific construction of the data blocks necessary to
build a group of IF_curr_exp neurons resident on a single core.
:param subvertex:
:param placement:
:param subgraph:
:param graph:
:param routing_info:
:param hostname:
:param graph_mapper:
:param report_folder:
:param ip_tags:
:param reverse_ip_tags:
:param write_text_specs:
:param application_run_time_folder:
:return:
"""
# Create new DataSpec for this processor:
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
spec.comment("\n*** Spec for block of {} neurons ***\n"
.format(self.model_name))
vertex_slice = graph_mapper.get_subvertex_slice(subvertex)
# Calculate the size of the tables to be reserved in SDRAM:
vertex_in_edges = graph.incoming_edges_to_vertex(self)
neuron_params_sz = self.get_neuron_params_size(vertex_slice)
synapse_params_sz = self.get_synapse_parameter_size(vertex_slice)
master_pop_table_sz = self.get_population_table_size(vertex_slice,
vertex_in_edges)
subvert_in_edges = subgraph.incoming_subedges_from_subvertex(subvertex)
all_syn_block_sz = self.get_exact_synaptic_block_memory_size(
graph_mapper, subvert_in_edges)
spike_hist_buff_sz = self.get_spike_buffer_size(vertex_slice)
potential_hist_buff_sz = self.get_v_buffer_size(vertex_slice)
gsyn_hist_buff_sz = self.get_g_syn_buffer_size(vertex_slice)
synapse_dynamics_region_sz = self.get_synapse_dynamics_parameter_size(
vertex_in_edges)
# Declare random number generators and distributions:
# TODO add random distrubtion stuff
# self.write_random_distribution_declarations(spec)
ring_buffer_shifts = self.get_ring_buffer_to_input_left_shifts(
subvertex, subgraph, graph_mapper, self._spikes_per_second,
self._machine_time_step, self._ring_buffer_sigma)
weight_scales = [self.get_weight_scale(r) for r in ring_buffer_shifts]
if logger.isEnabledFor(logging.DEBUG):
for t, r, w in zip(self.get_synapse_targets(), ring_buffer_shifts,
weight_scales):
logger.debug(
"Synapse type:%s - Ring buffer shift:%d, Max weight:%f"
% (t, r, w))
# update projections for future use
in_partitioned_edges = \
subgraph.incoming_subedges_from_subvertex(subvertex)
for partitioned_edge in in_partitioned_edges:
partitioned_edge.weight_scales_setter(weight_scales)
# Construct the data images needed for the Neuron:
self._reserve_population_based_memory_regions(
spec, neuron_params_sz, synapse_params_sz,
master_pop_table_sz, all_syn_block_sz,
spike_hist_buff_sz, potential_hist_buff_sz, gsyn_hist_buff_sz,
synapse_dynamics_region_sz)
self._write_setup_info(spec, spike_hist_buff_sz,
potential_hist_buff_sz, gsyn_hist_buff_sz,
self._executable_constant)
# Every outgoing edge from this vertex should have the same key
key = None
if len(subgraph.outgoing_subedges_from_subvertex(subvertex)) > 0:
keys_and_masks = routing_info.get_keys_and_masks_from_subedge(
subgraph.outgoing_subedges_from_subvertex(subvertex)[0])
# NOTE: using the first key assigned as the key. Should in future
# get the list of keys and use one per neuron, to allow arbitrary
# key and mask assignments
key = keys_and_masks[0].key
self._write_neuron_parameters(spec, key, subvertex, vertex_slice)
self.write_synapse_parameters(spec, subvertex, vertex_slice)
spec.write_array(ring_buffer_shifts)
self.write_synaptic_matrix_and_master_population_table(
spec, subvertex, all_syn_block_sz, weight_scales,
constants.POPULATION_BASED_REGIONS.POPULATION_TABLE.value,
constants.POPULATION_BASED_REGIONS.SYNAPTIC_MATRIX.value,
routing_info, graph_mapper, subgraph)
self.write_synapse_dynamics_parameters(
spec, self._machine_time_step,
constants.POPULATION_BASED_REGIONS.SYNAPSE_DYNAMICS.value,
weight_scales)
in_subedges = subgraph.incoming_subedges_from_subvertex(subvertex)
for subedge in in_subedges:
subedge.free_sublist()
# End the writing of this specification:
spec.end_specification()
data_writer.close()
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 generate_data_spec(
self, subvertex, placement, partitioned_graph, graph, routing_info,
hostname, graph_mapper, report_folder, ip_tags, reverse_ip_tags,
write_text_specs, application_run_time_folder):
"""
:param subvertex:
:param placement:
:param partitioned_graph:
:param graph:
:param routing_info:
:param hostname:
:param graph_mapper:
:param report_folder:
:param ip_tags:
:param reverse_ip_tags:
:param write_text_specs:
:param application_run_time_folder:
:return:
"""
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
# reserve region - add a word for the region size
n_command_bytes = self._get_n_command_bytes()
self._reserve_memory_regions(spec, n_command_bytes + 4, subvertex)
# Write system region
spec.comment("\n*** Spec for multicast source ***\n\n")
self._write_basic_setup_info(
spec, CommandSenderPartitionedVertex.SYSTEM_REGION)
# Go through the times and replace negative times with positive ones
new_times = set()
for time in self._times_with_commands:
if time < 0 and self._no_machine_time_steps is not None:
real_time = self._no_machine_time_steps + (time + 1)
if time in self._commands_with_payloads:
if real_time in self._commands_with_payloads:
self._commands_with_payloads[real_time].extend(
self._commands_with_payloads[time])
else:
self._commands_with_payloads[real_time] = \
self._commands_with_payloads[time]
del self._commands_with_payloads[time]
if time in self._commands_without_payloads:
if real_time in self._commands_without_payloads:
self._commands_without_payloads[real_time].extend(
self._commands_without_payloads[time])
else:
self._commands_without_payloads[real_time] = \
self._commands_without_payloads[time]
del self._commands_without_payloads[time]
new_times.add(real_time)
# if runtime is infinite, then there's no point storing end of
# simulation events, as they will never occur
elif time < 0 and self._no_machine_time_steps is None:
if time in self._commands_with_payloads:
del self._commands_with_payloads[time]
if time in self._commands_without_payloads:
del self._commands_without_payloads[time]
else:
new_times.add(time)
# write commands
spec.switch_write_focus(region=CommandSenderPartitionedVertex.COMMANDS)
spec.write_value(n_command_bytes)
for time in sorted(new_times):
# Gather the different types of commands
with_payload = list()
if time in self._commands_with_payloads:
with_payload = self._commands_with_payloads[time]
without_payload = list()
if time in self._commands_without_payloads:
without_payload = self._commands_without_payloads[time]
spec.write_value(time)
spec.write_value(len(with_payload))
for command in with_payload:
spec.write_value(self._get_key(
command, graph_mapper, routing_info, partitioned_graph))
payload = command.get_payload(routing_info, partitioned_graph,
graph_mapper)
spec.write_value(payload)
spec.write_value(command.repeat << 16 |
command.delay_between_repeats)
spec.write_value(len(without_payload))
for command in without_payload:
spec.write_value(self._get_key(
command, graph_mapper, routing_info, partitioned_graph))
spec.write_value(command.repeat << 16 |
command.delay_between_repeats)
# End-of-Spec:
spec.end_specification()
data_writer.close()
return data_writer.filename
def generate_data_spec(self, subvertex, placement, sub_graph, graph,
routing_info, hostname, graph_mapper,
report_folder, ip_tags, reverse_ip_tags,
write_text_specs, application_run_time_folder):
# Create new DataSpec for this processor:
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
spec.comment("\n*** Spec for block of {} neurons ***\n"
.format(self.model_name))
spec.comment("\nReserving memory space for data regions:\n\n")
# Reserve memory regions:
spec.reserve_memory_region(
region=self._REVERSE_IPTAG_MULTICAST_REGIONS.SYSTEM.value,
size=constants.DATA_SPECABLE_BASIC_SETUP_INFO_N_WORDS * 4 + 8,
label='SYSTEM')
spec.reserve_memory_region(
region=self._REVERSE_IPTAG_MULTICAST_REGIONS.CONFIGURATION.value,
size=self._CONFIGURATION_REGION_SIZE, label='CONFIGURATION')
if self._buffer_space is not None and self._buffer_space > 0:
spec.reserve_memory_region(
region=self._REVERSE_IPTAG_MULTICAST_REGIONS.BUFFER.value,
size=self._buffer_space, label="BUFFER", empty=True)
# set up system region writes
self._write_basic_setup_info(
spec, self._REVERSE_IPTAG_MULTICAST_REGIONS.SYSTEM.value)
# TODO this can be removed once buffered out functionality is in place.
# As then live injection can be recorded
spec.write_value(data=0)
spec.write_value(data=0)
# set up configuration region writes
spec.switch_write_focus(
region=self._REVERSE_IPTAG_MULTICAST_REGIONS.CONFIGURATION.value)
if self._virtual_key is None:
subedge_routing_info = \
routing_info.get_subedge_information_from_subedge(
sub_graph.outgoing_subedges_from_subvertex(subvertex)[0])
key_and_mask = subedge_routing_info.keys_and_masks[0]
self._mask = key_and_mask.mask
self._virtual_key = key_and_mask.key
if self._prefix is None:
if self._prefix_type is None:
self._prefix_type = EIEIOPrefix.UPPER_HALF_WORD
self._prefix = self._generate_prefix(self._virtual_key,
self._prefix_type)
# add prefix boolean value
if self._prefix is None:
spec.write_value(data=0)
else:
spec.write_value(data=1)
# add prefix
if self._prefix is None:
spec.write_value(data=0)
else:
if self._prefix_type is EIEIOPrefix.LOWER_HALF_WORD:
spec.write_value(data=self._prefix)
else:
spec.write_value(data=self._prefix << 16)
# key left shift
spec.write_value(data=self._key_left_shift)
# add key check
if self._check_key:
spec.write_value(data=1)
else:
spec.write_value(data=0)
# add key and mask
spec.write_value(data=self._virtual_key)
spec.write_value(data=self._mask)
# Buffering control
spec.write_value(data=self._buffer_space)
spec.write_value(data=self._space_before_notification)
# Notification
if self._notify_buffer_space:
ip_tag = iter(ip_tags).next()
spec.write_value(data=ip_tag.tag)
else:
spec.write_value(data=0)
# close spec
spec.end_specification()
data_writer.close()
def generate_data_spec(
self, subvertex, placement, subgraph, graph, routing_info,
hostname, graph_mapper, report_folder, ip_tags,
reverse_ip_tags, write_text_specs, application_run_time_folder):
# Create new DataSpec for this processor:
data_writer, report_writer = self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
spec.comment("\n*** Spec for block of {} neurons ***\n".format(
self.model_name))
vertex_slice = graph_mapper.get_subvertex_slice(subvertex)
# Get recording sizes - the order is important here as spikes will
# require less space than voltage and voltage less than gsyn. This
# order ensures that the buffer size before receive is optimum for
# all recording channels
# TODO: Maybe split the buffer size before receive by channel?
spike_history_sz, spike_buffering_needed = \
self._get_recording_and_buffer_sizes(
self._spike_buffer_max_size,
self._spike_recorder.get_sdram_usage_in_bytes(
vertex_slice.n_atoms, self._no_machine_time_steps))
v_history_sz, v_buffering_needed = \
self._get_recording_and_buffer_sizes(
self._v_buffer_max_size,
self._v_recorder.get_sdram_usage_in_bytes(
vertex_slice.n_atoms, self._no_machine_time_steps))
gsyn_history_sz, gsyn_buffering_needed = \
self._get_recording_and_buffer_sizes(
self._gsyn_buffer_max_size,
self._gsyn_recorder.get_sdram_usage_in_bytes(
vertex_slice.n_atoms, self._no_machine_time_steps))
buffer_size_before_receive = self._buffer_size_before_receive
if (not spike_buffering_needed and not v_buffering_needed and
not gsyn_buffering_needed):
buffer_size_before_receive = max((
spike_history_sz, v_history_sz, gsyn_history_sz)) + 256
# Reserve memory regions
self._reserve_memory_regions(
spec, vertex_slice, spike_history_sz, v_history_sz,
gsyn_history_sz)
# Declare random number generators and distributions:
# TODO add random distribution stuff
# self.write_random_distribution_declarations(spec)
# Get the key - use only the first edge
key = None
if len(subgraph.outgoing_subedges_from_subvertex(subvertex)) > 0:
keys_and_masks = routing_info.get_keys_and_masks_from_subedge(
subgraph.outgoing_subedges_from_subvertex(subvertex)[0])
# NOTE: using the first key assigned as the key. Should in future
# get the list of keys and use one per neuron, to allow arbitrary
# key and mask assignments
key = keys_and_masks[0].key
# Write the regions
self._write_setup_info(
spec, spike_history_sz, v_history_sz, gsyn_history_sz, ip_tags,
buffer_size_before_receive, self._time_between_requests)
self._write_neuron_parameters(spec, key, vertex_slice)
# allow the synaptic matrix to write its data specable data
self._synapse_manager.write_data_spec(
spec, self, vertex_slice, subvertex, placement, subgraph, graph,
routing_info, hostname, graph_mapper)
# End the writing of this specification:
spec.end_specification()
data_writer.close()
return [data_writer.filename]
def generate_data_spec(self, subvertex, placement, partitioned_graph,
graph, routing_info, hostname, graph_mapper,
report_folder, ip_tags, reverse_ip_tags,
write_text_specs, application_run_time_folder):
# Create new DataSpec for this processor:
data_writer, report_writer = self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
spec.comment("\n*** Spec for block of {} neurons ***\n".format(
self.model_name))
vertex_slice = graph_mapper.get_subvertex_slice(subvertex)
# Get recording sizes - the order is important here as spikes will
# require less space than voltage and voltage less than gsyn. This
# order ensures that the buffer size before receive is optimum for
# all recording channels
# TODO: Maybe split the buffer size before receive by channel?
spike_buffer_size = self._spike_recorder.get_sdram_usage_in_bytes(
vertex_slice.n_atoms, self._no_machine_time_steps)
v_buffer_size = self._v_recorder.get_sdram_usage_in_bytes(
vertex_slice.n_atoms, self._no_machine_time_steps)
gsyn_buffer_size = self._gsyn_recorder.get_sdram_usage_in_bytes(
vertex_slice.n_atoms, self._no_machine_time_steps)
spike_history_sz = recording_utils.get_buffer_sizes(
self._spike_buffer_max_size, spike_buffer_size,
self._enable_buffered_recording)
v_history_sz = recording_utils.get_buffer_sizes(
self._v_buffer_max_size, v_buffer_size,
self._enable_buffered_recording)
gsyn_history_sz = recording_utils.get_buffer_sizes(
self._gsyn_buffer_max_size, gsyn_buffer_size,
self._enable_buffered_recording)
spike_buffering_needed = recording_utils.needs_buffering(
self._spike_buffer_max_size, spike_buffer_size,
self._enable_buffered_recording)
v_buffering_needed = recording_utils.needs_buffering(
self._v_buffer_max_size, v_buffer_size,
self._enable_buffered_recording)
gsyn_buffering_needed = recording_utils.needs_buffering(
self._gsyn_buffer_max_size, gsyn_buffer_size,
self._enable_buffered_recording)
buffer_size_before_receive = self._buffer_size_before_receive
if (not spike_buffering_needed and not v_buffering_needed
and not gsyn_buffering_needed):
buffer_size_before_receive = max(
(spike_history_sz, v_history_sz, gsyn_history_sz)) + 256
# Reserve memory regions
self._reserve_memory_regions(spec, vertex_slice, spike_history_sz,
v_history_sz, gsyn_history_sz, subvertex)
# Declare random number generators and distributions:
# TODO add random distribution stuff
# self.write_random_distribution_declarations(spec)
# Get the key - use only the first edge
key = None
for partition in partitioned_graph.\
outgoing_edges_partitions_from_vertex(subvertex).values():
keys_and_masks = \
routing_info.get_keys_and_masks_from_partition(partition)
# NOTE: using the first key assigned as the key. Should in future
# get the list of keys and use one per neuron, to allow arbitrary
# key and mask assignments
key = keys_and_masks[0].key
# Write the regions
self._write_setup_info(spec, spike_history_sz, v_history_sz,
gsyn_history_sz, ip_tags,
buffer_size_before_receive,
self._time_between_requests, subvertex)
self._write_neuron_parameters(spec, key, vertex_slice)
# allow the synaptic matrix to write its data spec-able data
self._synapse_manager.write_data_spec(spec, self, vertex_slice,
subvertex, placement,
partitioned_graph, graph,
routing_info, graph_mapper,
self._input_type)
# End the writing of this specification:
spec.end_specification()
data_writer.close()
return data_writer.filename
def generate_data_spec(self, subvertex, placement, sub_graph, graph,
routing_info, hostname, graph_mapper, report_folder,
ip_tags, reverse_ip_tags, write_text_specs,
application_run_time_folder):
"""
Model-specific construction of the data blocks necessary to build a
single Delay Extension Block on one core.
"""
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
# Reserve memory:
spec.comment("\nReserving memory space for data regions:\n\n")
# ###################################################################
# Reserve SDRAM space for memory areas:
delay_params_header_words = 3
vertex_slice = graph_mapper.get_subvertex_slice(subvertex)
n_atoms = vertex_slice.hi_atom - vertex_slice.lo_atom + 1
block_len_words = int(math.ceil(n_atoms / 32.0))
num_delay_blocks, delay_blocks = self.get_delay_blocks(
subvertex, sub_graph, graph_mapper)
delay_params_sz = 4 * (delay_params_header_words +
(num_delay_blocks * block_len_words))
spec.reserve_memory_region(
region=self._DELAY_EXTENSION_REGIONS.SYSTEM.value,
size=constants.DATA_SPECABLE_BASIC_SETUP_INFO_N_WORDS * 4,
label='setup')
spec.reserve_memory_region(
region=self._DELAY_EXTENSION_REGIONS.DELAY_PARAMS.value,
size=delay_params_sz,
label='delay_params')
self.write_setup_info(spec, 0)
spec.comment("\n*** Spec for Delay Extension Instance ***\n\n")
key = None
if len(sub_graph.outgoing_subedges_from_subvertex(subvertex)) > 0:
keys_and_masks = routing_info.get_keys_and_masks_from_subedge(
sub_graph.outgoing_subedges_from_subvertex(subvertex)[0])
# NOTE: using the first key assigned as the key. Should in future
# get the list of keys and use one per neuron, to allow arbitrary
# key and mask assignments
key = keys_and_masks[0].key
self.write_delay_parameters(spec, placement.x, placement.y,
placement.p, subvertex, num_delay_blocks,
delay_blocks, vertex_slice, key)
# End-of-Spec:
spec.end_specification()
data_writer.close()
def generate_data_spec(
self, subvertex, placement, sub_graph, graph, routing_info,
hostname, graph_mapper, report_folder, ip_tags, reverse_ip_tags,
write_text_specs, application_run_time_folder):
"""
Model-specific construction of the data blocks necessary to build a
single external retina device.
:param subvertex:
:param placement:
:param sub_graph:
:param graph:
:param routing_info:
:param hostname:
:param graph_mapper:
:param report_folder:
:param ip_tags:
:param reverse_ip_tags:
:param write_text_specs:
:param application_run_time_folder:
:return:
"""
data_writer, report_writer = \
self.get_data_spec_file_writers(
placement.x, placement.y, placement.p, hostname, report_folder,
write_text_specs, application_run_time_folder)
spec = DataSpecificationGenerator(data_writer, report_writer)
# reserve region - add a word for the region size
n_command_bytes = self._get_n_command_bytes()
self._reserve_memory_regions(spec, n_command_bytes + 4)
# Write system region
spec.comment("\n*** Spec for multi cast source ***\n\n")
self._write_basic_setup_info(spec, self.SYSTEM_REGION)
# Go through the times and replace negative times with positive ones
new_times = set()
for time in self._times_with_commands:
if time < 0 and self._no_machine_time_steps is not None:
real_time = self._no_machine_time_steps + (time + 1)
if time in self._commands_with_payloads:
if real_time in self._commands_with_payloads:
self._commands_with_payloads[real_time].extend(
self._commands_with_payloads[time])
else:
self._commands_with_payloads[real_time] = \
self._commands_with_payloads[time]
del self._commands_with_payloads[time]
if time in self._commands_without_payloads:
if real_time in self._commands_without_payloads:
self._commands_without_payloads[real_time].extend(
self._commands_without_payloads[time])
else:
self._commands_without_payloads[real_time] = \
self._commands_without_payloads[time]
del self._commands_without_payloads[time]
new_times.add(real_time)
# if runtime is infinite, then theres no point storing end of
# simulation events, as they will never occur
elif time < 0 and self._no_machine_time_steps is None:
if time in self._commands_with_payloads:
del self._commands_with_payloads[time]
if time in self._commands_without_payloads:
del self._commands_without_payloads[time]
else:
new_times.add(time)
# write commands
spec.switch_write_focus(region=self.COMMANDS)
spec.write_value(n_command_bytes)
for time in sorted(new_times):
# Gather the different types of commands
with_payload = list()
if time in self._commands_with_payloads:
with_payload = self._commands_with_payloads[time]
without_payload = list()
if time in self._commands_without_payloads:
without_payload = self._commands_without_payloads[time]
spec.write_value(time)
spec.write_value(len(with_payload))
for command in with_payload:
spec.write_value(self._get_key(command, graph_mapper,
routing_info))
payload = command.get_payload(routing_info, sub_graph,
graph_mapper)
spec.write_value(payload)
spec.write_value(command.repeat << 16 |
command.delay_between_repeats)
spec.write_value(len(without_payload))
for command in without_payload:
spec.write_value(self._get_key(command, graph_mapper,
routing_info))
spec.write_value(command.repeat << 16 |
command.delay_between_repeats)
# End-of-Spec:
spec.end_specification()
data_writer.close()