def generateDataSpec(self, processor, subvertex, dao):
# Create new DataSpec for this processor:
spec = data_spec_gen.DataSpec(processor=processor, dao=dao)
spec.initialise(self.core_app_identifier, dao) # User specified identifier
spec.comment("\n*** Spec for robot motor control ***\n\n")
# Load the expected executable to the list of load targets for this core
# and the load addresses:
x, y, p = processor.get_coordinates()
populationIdentity = packet_conversions.get_key_from_coords(x, y, p+1) #our own key
file_path = os.path.join(dao.get_common_binaries_directory(),
'myorobot_motor_control.aplx')
executable_target = lib_map.ExecutableTarget(file_path, x, y, p)
memory_write_targets = list()
simulationTimeInTicks = INFINITE_SIMULATION
if dao.run_time is not None:
simulationTimeInTicks = int((dao.run_time * 1000.0)
/ dao.machineTimeStep)
user1Addr = 0xe5007000 + 128 * p + 116 # User1 location reserved for core p
memory_write_targets.append(lib_map.MemWriteTarget(x, y, p, user1Addr,
simulationTimeInTicks))
#reserve regions
self.reserve_memory_regions(spec)
#write system info
spec.switchWriteFocus(region = self.SYSTEM_REGION)
spec.write(data = 0xBEEF0000)
spec.write(data = 0)
spec.write(data = 0)
spec.write(data = 0)
edge_key = None
#locate correct subedge for key
for subedge in subvertex.out_subedges:
if subedge.edge == self.out_going_edge:
edge_key = subedge.key
#write params to memory
spec.switchWriteFocus(region=self.PARAMS)
spec.write(data=edge_key|self.myoID)
# spec.write(data=populationIdentity)
spec.write(data=spec.doubleToS1615(self.output_scale),sizeof='s1615')
spec.write(data=self.sample_time)
spec.write(data=spec.doubleToS1615(self.decay_factor), sizeof='s1615')
spec.write(data=spec.doubleToS1615(self.kernel_amplitude), sizeof='s1615')
spec.write(data=self.threshold)
spec.write(data=self.n_neurons)
# End-of-Spec:
spec.endSpec()
spec.closeSpecFile()
load_targets = list()
# Return list of executables, load files:
return executable_target, load_targets, memory_write_targets
def writeDelayParameters(self, spec, processor, subvertex, num_delay_blocks,
delay_block):
"""
Generate Delay Parameter data (region 2):
"""
# Write spec with commands to construct required delay region:
spec.comment("\nWriting Delay Parameters for %d Neurons:\n"
% subvertex.n_atoms)
# Set the focus to the memory region 2 (delay parameters):
spec.switchWriteFocus( region = REGIONS.DELAY_PARAMS )
# Write header info to the memory region:
# Write Key info for this core:
chipX, chipY, chipP = processor.get_coordinates()
populationIdentity = packet_conversions.get_key_from_coords(
chipX, chipY, chipP)
spec.write(data = populationIdentity)
# Write the number of neurons in the block:
spec.write(data = subvertex.n_atoms)
# Write the number of blocks of delays:
spec.write(data = num_delay_blocks)
# Write the actual delay blocks
for i in range(0, num_delay_blocks):
spec.write_array(data = delay_block[i])
def writeBlockIndexRegion(self, spec, subvertex, numNeurons, tableEntries):
"""
Spike block index table. Gives address of each block of spikes.
numNeurons is the total number of spike sources to be modelled.
tableEntries is a list of the entries, each of which consists of:
struct {
uint32 timeStamp # In simulation ticks
uint32 addressOfBlockWord # Relative to start of spikeDataRegion
} entry
"""
spec.switchWriteFocus(region = BLOCK_INDEX_REGION)
# Word 0 is the key (x, y, p) for this core:
chipX, chipY, chipP = subvertex.placement.processor.get_coordinates()
populationIdentity = \
packet_conversions.get_key_from_coords(chipX, chipY, chipP)
spec.write(data = populationIdentity)
# Word 1 is the total number of 'neurons' (i.e. spike sources) in
# the population:
spec.write(data = numNeurons)
# Word 2 is the total number of entries in this table of indices:
numEntries = len(tableEntries)
spec.write(data = numEntries)
# Write individual entries:
for entry in tableEntries:
timeStamp = entry[0] # Time in ticks when this block is used
address = entry[1] # Address into spikeBlock region
spec.write(data = timeStamp)
spec.write(data = address)
return
def generate_routing_info(self, subedge):
processor_id = subedge.presubvertex.placement.processor.idx % 16
if self.position == self.RIGHT_RETINA:
if self.polarity == ExternalRetinaDevice.UP_POLARITY:
part_1 = packet_conversions.get_key_from_coords(0, 6, processor_id)
key = part_1 | (1 << 14)
return key, 0xffff7800
else:
key = packet_conversions.get_key_from_coords(0, 6, processor_id)
return key, 0xffff7800
else:
if self.polarity == ExternalRetinaDevice.UP_POLARITY:
key = packet_conversions.get_key_from_coords(0, 7, processor_id) | (1 << 14)
return key, 0xffff7800
else:
key = packet_conversions.get_key_from_coords(0, 7, processor_id)
return key, 0xffff7800
def generate_routing_info(self, subedge):
processor_id = subedge.presubvertex.placement.processor.idx % 16
if self.position == self.RIGHT_RETINA:
if self.polarity == ExternalRetinaDevice.UP_POLARITY:
part_1 = packet_conversions.get_key_from_coords(
0, 6, processor_id)
key = part_1 | (1 << 14)
return key, 0xffff7800
else:
key = packet_conversions.get_key_from_coords(
0, 6, processor_id)
return key, 0xffff7800
else:
if self.polarity == ExternalRetinaDevice.UP_POLARITY:
key = packet_conversions.get_key_from_coords(
0, 7, processor_id) | (1 << 14)
return key, 0xffff7800
else:
key = packet_conversions.get_key_from_coords(
0, 7, processor_id)
return key, 0xffff7800
def generate_routing_info( self, subedge ):
"""
For the given subedge generate the key and mask for routing.
:param subedge: The subedge for which to generate the key and mask.
:returns: A tuple containing the key and mask.
"""
x, y, p = subedge.presubvertex.placement.processor.get_coordinates()
key = packet_conversions.get_key_from_coords(x, y, p)
#bodge to deal with external perrifables
return key, self._app_mask
def generate_routing_info(self, subedge):
"""
For the given subedge generate the key and mask for routing.
:param subedge: The subedge for which to generate the key and mask.
:returns: A tuple containing the key and mask.
"""
x, y, p = subedge.presubvertex.placement.processor.get_coordinates()
key = packet_conversions.get_key_from_coords(x, y, p)
#bodge to deal with external perrifables
return key, self._app_mask
def writeNeuronParameters(self, spec, machineTimeStep,
processor, subvertex,
ring_buffer_to_input_left_shift):
spec.comment("\nWriting Neuron Parameters for %d "
"Neurons:\n"%subvertex.n_atoms)
# Set the focus to the memory region 2 (neuron parameters):
spec.switchWriteFocus( region = REGIONS.NEURON_PARAMS )
# Write header info to the memory region:
# Write Key info for this core:
chipX, chipY, chipP = processor.get_coordinates()
populationIdentity = \
packet_conversions.get_key_from_coords(chipX, chipY, chipP)
spec.write(data = populationIdentity)
# Write the number of neurons in the block:
spec.write(data = subvertex.n_atoms)
# Write the number of parameters per neuron (struct size in words):
params = self.get_parameters(machineTimeStep)
spec.write(data = len( params ))
# Write machine time step: (Integer, expressed in microseconds)
spec.write(data = machineTimeStep)
# Write ring_buffer_to_input_left_shift
spec.write(data = ring_buffer_to_input_left_shift)
# TODO: Took this out for now as I need random parameters
# Create loop over number of neurons:
#spec.loop(countReg = 15, startVal = 0, endVal = subvertex.n_atoms)
for atom in range(0, subvertex.n_atoms):
# Process the parameters
for param in params:
value = param.get_value()
if (hasattr(value, "__len__")):
if len(value) > 1:
value = value[atom]
else:
value = value[0]
datatype = param.get_datatype()
scale = param.get_scale()
value = value * scale
if datatype == 's1615':
value = spec.doubleToS1615(value)
elif datatype == 'uint32':
value = ctypes.c_uint32(value).value
spec.write(data = value, sizeof=datatype)
def generate_routing_info(self, subedge):
x, y, p = subedge.postsubvertex.placement.processor.get_coordinates()
key = packet_conversions.get_key_from_coords(x, y, p)
return key, 0xfffff800
def writePoissonParameters(self, spec, machineTimeStep, processor,
numNeurons):
"""
Generate Neuron Parameter data for Poisson spike sources (region 2):
"""
spec.comment("\nWriting Neuron Parameters for %d poisson sources:\n"
% numNeurons)
# Set the focus to the memory region 2 (neuron parameters):
spec.switchWriteFocus(region = POISSON_PARAMS_REGION)
# Write header info to the memory region:
# Write Key info for this core:
chipX, chipY, chipP = processor.get_coordinates()
populationIdentity = \
packet_conversions.get_key_from_coords(chipX, chipY, chipP)
spec.write(data = populationIdentity)
# Write the random seed (4 words), generated randomly!
if self.seed == None:
spec.write(data = numpy.random.randint(0x7FFFFFFF))
spec.write(data = numpy.random.randint(0x7FFFFFFF))
spec.write(data = numpy.random.randint(0x7FFFFFFF))
spec.write(data = numpy.random.randint(0x7FFFFFFF))
else:
spec.write(data = self.seed[0])
spec.write(data = self.seed[1])
spec.write(data = self.seed[2])
spec.write(data = self.seed[3])
# For each neuron, get the rate to work out if it is a slow
# or fast source
slow_sources = list()
fast_sources = list()
for i in range(0, numNeurons):
# Get the parameter values for source i:
rateVal = generateParameter(self.rate, i)
startVal = generateParameter(self.start, i)
endVal = generateParameter(self.duration, i) + startVal
# Decide if it is a fast or slow source and
spikesPerTick = (float(rateVal) * (machineTimeStep / 1000000.0))
if spikesPerTick <= SLOW_RATE_PER_TICK_CUTOFF:
slow_sources.append([i, rateVal, startVal, endVal])
else:
fast_sources.append([i, spikesPerTick, startVal, endVal])
# Write the numbers of each type of source
spec.write(data = len(slow_sources))
spec.write(data = len(fast_sources))
# Now write one struct for each slow source as follows
#
# typedef struct slow_spike_source_t
# {
# uint32_t neuron_id;
# uint32_t start_ticks;
# uint32_t end_ticks;
#
# accum mean_isi_ticks;
# accum time_to_spike_ticks;
# } slow_spike_source_t;
for (neuronId, rateVal, startVal, endVal) in slow_sources:
isiValScaled = int(float(1000000.0 / (rateVal * machineTimeStep))
* 32768.0)
startScaled = int(startVal * 1000.0 / machineTimeStep)
endScaled = int(endVal * 1000.0 / machineTimeStep)
spec.write(data = neuronId, sizeof='uint32')
spec.write(data = startScaled, sizeof='uint32')
spec.write(data = endScaled, sizeof='uint32')
spec.write(data = isiValScaled, sizeof='s1615')
spec.write(data = 0x0, sizeof='uint32')
# Now write
# typedef struct fast_spike_source_t
# {
# uint32_t neuron_id;
# uint32_t start_ticks;
# uint32_t end_ticks;
#
# unsigned long fract exp_minus_lambda;
# } fast_spike_source_t;
for (neuronId, spikesPerTick, startVal, endVal) in fast_sources:
exp_minus_lamda = exp(-1.0 * spikesPerTick)
exp_minus_lamda_scaled = int(exp_minus_lamda * float(0xFFFFFFFF))
startScaled = int(startVal * 1000.0 / machineTimeStep)
endScaled = int(endVal * 1000.0 / machineTimeStep)
spec.write(data = neuronId, sizeof='uint32')
spec.write(data = startScaled, sizeof='uint32')
spec.write(data = endScaled, sizeof='uint32')
spec.write(data = exp_minus_lamda_scaled, sizeof='u032')
return
def writePoissonParameters(self, spec, machineTimeStep, processor,
numNeurons):
"""
Generate Neuron Parameter data for Poisson spike sources (region 2):
"""
spec.comment("\nWriting Neuron Parameters for %d poisson sources:\n" %
numNeurons)
# Set the focus to the memory region 2 (neuron parameters):
spec.switchWriteFocus(region=POISSON_PARAMS_REGION)
# Write header info to the memory region:
# Write Key info for this core:
chipX, chipY, chipP = processor.get_coordinates()
populationIdentity = \
packet_conversions.get_key_from_coords(chipX, chipY, chipP)
spec.write(data=populationIdentity)
# Write the random seed (4 words), generated randomly!
if self.seed == None:
spec.write(data=numpy.random.randint(0x7FFFFFFF))
spec.write(data=numpy.random.randint(0x7FFFFFFF))
spec.write(data=numpy.random.randint(0x7FFFFFFF))
spec.write(data=numpy.random.randint(0x7FFFFFFF))
else:
spec.write(data=self.seed[0])
spec.write(data=self.seed[1])
spec.write(data=self.seed[2])
spec.write(data=self.seed[3])
# For each neuron, get the rate to work out if it is a slow
# or fast source
slow_sources = list()
fast_sources = list()
for i in range(0, numNeurons):
# Get the parameter values for source i:
rateVal = generateParameter(self.rate, i)
startVal = generateParameter(self.start, i)
endVal = generateParameter(self.duration, i) + startVal
# Decide if it is a fast or slow source and
spikesPerTick = (float(rateVal) * (machineTimeStep / 1000000.0))
if spikesPerTick <= SLOW_RATE_PER_TICK_CUTOFF:
slow_sources.append([i, rateVal, startVal, endVal])
else:
fast_sources.append([i, spikesPerTick, startVal, endVal])
# Write the numbers of each type of source
spec.write(data=len(slow_sources))
spec.write(data=len(fast_sources))
# Now write one struct for each slow source as follows
#
# typedef struct slow_spike_source_t
# {
# uint32_t neuron_id;
# uint32_t start_ticks;
# uint32_t end_ticks;
#
# accum mean_isi_ticks;
# accum time_to_spike_ticks;
# } slow_spike_source_t;
for (neuronId, rateVal, startVal, endVal) in slow_sources:
isiValScaled = int(
float(1000000.0 / (rateVal * machineTimeStep)) * 32768.0)
startScaled = int(startVal * 1000.0 / machineTimeStep)
endScaled = int(endVal * 1000.0 / machineTimeStep)
spec.write(data=neuronId, sizeof='uint32')
spec.write(data=startScaled, sizeof='uint32')
spec.write(data=endScaled, sizeof='uint32')
spec.write(data=isiValScaled, sizeof='s1615')
spec.write(data=0x0, sizeof='uint32')
# Now write
# typedef struct fast_spike_source_t
# {
# uint32_t neuron_id;
# uint32_t start_ticks;
# uint32_t end_ticks;
#
# unsigned long fract exp_minus_lambda;
# } fast_spike_source_t;
for (neuronId, spikesPerTick, startVal, endVal) in fast_sources:
exp_minus_lamda = exp(-1.0 * spikesPerTick)
exp_minus_lamda_scaled = int(exp_minus_lamda * float(0xFFFFFFFF))
startScaled = int(startVal * 1000.0 / machineTimeStep)
endScaled = int(endVal * 1000.0 / machineTimeStep)
spec.write(data=neuronId, sizeof='uint32')
spec.write(data=startScaled, sizeof='uint32')
spec.write(data=endScaled, sizeof='uint32')
spec.write(data=exp_minus_lamda_scaled, sizeof='u032')
return
def generate_routing_info(self, subedge):
x, y, p = subedge.postsubvertex.placement.processor.get_coordinates()
key = packet_conversions.get_key_from_coords(x, y, p)
return key, 0xfffff800
def generateDataSpec(self, processor, subvertex, dao):
# Create new DataSpec for this processor:
spec = data_spec_gen.DataSpec(processor=processor, dao=dao)
spec.initialise(self.core_app_identifier,
dao) # User specified identifier
spec.comment("\n*** Spec for robot motor control ***\n\n")
# Load the expected executable to the list of load targets for this core
# and the load addresses:
x, y, p = processor.get_coordinates()
populationIdentity = packet_conversions.get_key_from_coords(
x, y, p + 1) #our own key
file_path = os.path.join(dao.get_common_binaries_directory(),
'myorobot_motor_control.aplx')
executable_target = lib_map.ExecutableTarget(file_path, x, y, p)
memory_write_targets = list()
simulationTimeInTicks = INFINITE_SIMULATION
if dao.run_time is not None:
simulationTimeInTicks = int(
(dao.run_time * 1000.0) / dao.machineTimeStep)
user1Addr = 0xe5007000 + 128 * p + 116 # User1 location reserved for core p
memory_write_targets.append(
lib_map.MemWriteTarget(x, y, p, user1Addr, simulationTimeInTicks))
#reserve regions
self.reserve_memory_regions(spec)
#write system info
spec.switchWriteFocus(region=self.SYSTEM_REGION)
spec.write(data=0xBEEF0000)
spec.write(data=0)
spec.write(data=0)
spec.write(data=0)
edge_key = None
#locate correct subedge for key
for subedge in subvertex.out_subedges:
if subedge.edge == self.out_going_edge:
edge_key = subedge.key
#write params to memory
spec.switchWriteFocus(region=self.PARAMS)
spec.write(data=edge_key | self.myoID)
# spec.write(data=populationIdentity)
spec.write(data=spec.doubleToS1615(self.output_scale), sizeof='s1615')
spec.write(data=self.sample_time)
spec.write(data=spec.doubleToS1615(self.decay_factor), sizeof='s1615')
spec.write(data=spec.doubleToS1615(self.kernel_amplitude),
sizeof='s1615')
spec.write(data=self.threshold)
spec.write(data=self.n_neurons)
# End-of-Spec:
spec.endSpec()
spec.closeSpecFile()
load_targets = list()
# Return list of executables, load files:
return executable_target, load_targets, memory_write_targets
