def _read_in_master_pop_table(self, p, controller, master_pop_table_region,
MASTER_POPULATION_TABLE_SIZE):
'''
reads in the master pop table from a given processor on the machine
'''
# Get the App Data base address for the core
# (location where this cores memory starts in
# sdram and region table)
app_data_base_address_offset = getAppDataBaseAddressOffset(p)
app_data_base_address = \
self._read_and_convert(app_data_base_address_offset,
scamp.TYPE_WORD, 4, "<I", controller)
# Get the memory address of the master pop table region
master_pop_region = master_pop_table_region
master_region_base_address_address = \
getRegionBaseAddressOffset(app_data_base_address,
master_pop_region)
master_region_base_address_offset = \
self._read_and_convert(master_region_base_address_address,
scamp.TYPE_WORD, 4, "<I", controller)
master_region_base_address =\
master_region_base_address_offset + app_data_base_address
#read in the master pop table and store in ram for future use
logger.debug("Reading {} ({}) bytes starting at {} + "
"4".format(MASTER_POPULATION_TABLE_SIZE,
hex(MASTER_POPULATION_TABLE_SIZE),
hex(master_region_base_address)))
return master_region_base_address, app_data_base_address
def _read_in_master_pop_table(self, p, controller, master_pop_table_region,
MASTER_POPULATION_TABLE_SIZE):
'''
reads in the master pop table from a given processor on the machine
'''
# Get the App Data base address for the core
# (location where this cores memory starts in
# sdram and region table)
app_data_base_address_offset = getAppDataBaseAddressOffset(p)
app_data_base_address = \
self._read_and_convert(app_data_base_address_offset,
scamp.TYPE_WORD, 4, "<I", controller)
# Get the memory address of the master pop table region
master_pop_region = master_pop_table_region
master_region_base_address_address = \
getRegionBaseAddressOffset(app_data_base_address,
master_pop_region)
master_region_base_address_offset = \
self._read_and_convert(master_region_base_address_address,
scamp.TYPE_WORD, 4, "<I", controller)
master_region_base_address =\
master_region_base_address_offset + app_data_base_address
#read in the master pop table and store in ram for future use
logger.debug("Reading {} ({}) bytes starting at {} + "
"4".format(MASTER_POPULATION_TABLE_SIZE,
hex(MASTER_POPULATION_TABLE_SIZE),
hex(master_region_base_address)))
return master_region_base_address, app_data_base_address
def retrieve_region_data(txrx, x, y, p, region_id, region_size):
"""Get the data from the given processor and region.
:param txrx: transceiver to use when communicating with the board
:param region_id: id of the region to retrieve
:param region_size: size of the region (in words)
:returns: a string containing data from the region
"""
# Get the application pointer table to get the address for the region
txrx.select(x, y)
app_data_base_offset = memory_utils.getAppDataBaseAddressOffset(p)
_app_data_table = txrx.memory_calls.read_mem(app_data_base_offset,
scamp.TYPE_WORD, 4)
app_data_table = struct.unpack('<I', _app_data_table)[0]
# Get the position of the desired region
region_base_offset = memory_utils.getRegionBaseAddressOffset(
app_data_table, region_id)
_region_base = txrx.memory_calls.read_mem(region_base_offset,
scamp.TYPE_WORD, 4)
region_address = struct.unpack('<I', _region_base)[0] + app_data_table
# Read the region
data = txrx.memory_calls.read_mem(region_address, scamp.TYPE_WORD,
region_size * 4)
return data
def _getSpikes(self, controller, compatible_output,
spikeRecordingRegion, subVertexOutSpikeBytesFunction,
runtime):
"""
Return a 2-column numpy array containing cell ids and spike times for
recorded cells. This is read directly from the memory for the board.
"""
logger.info("Getting spikes for %s" % (self.label))
spikes = numpy.zeros((0, 2))
# Find all the sub-vertices that this population exists on
for subvertex in self.subvertices:
(x, y, p) = subvertex.placement.processor.get_coordinates()
logger.debug("Reading spikes from chip %d, %d, core %d, lo_atom %d"
% (x, y, p, subvertex.lo_atom))
controller.txrx.select(x, y)
# Get the App Data for the core
appDataBaseAddressOffset = getAppDataBaseAddressOffset(p)
appDataBaseAddressBuf = controller.txrx.memory_calls.read_mem(
appDataBaseAddressOffset, scamp.TYPE_WORD, 4)
appDataBaseAddress = struct.unpack("<I", appDataBaseAddressBuf)[0]
# Get the position of the spike buffer
spikeRegionBaseAddressOffset = getRegionBaseAddressOffset(
appDataBaseAddress, spikeRecordingRegion)
spikeRegionBaseAddressBuf = controller.txrx.memory_calls.read_mem(
spikeRegionBaseAddressOffset, scamp.TYPE_WORD, 4)
spikeRegionBaseAddress = struct.unpack("<I",
spikeRegionBaseAddressBuf)[0]
spikeRegionBaseAddress += appDataBaseAddress
# Read the spike data size
numberOfBytesWrittenBuf = controller.txrx.memory_calls.read_mem(
spikeRegionBaseAddress, scamp.TYPE_WORD, 4)
numberOfBytesWritten = struct.unpack_from("<I",
numberOfBytesWrittenBuf)[0]
#check that the number of spikes written is smaller or the same as the size of the memory
#region we allocated for spikes
outSpikeBytes = subVertexOutSpikeBytesFunction(subvertex)
machine_time_step = conf.config.getint("Machine", "machineTimeStep")
no_machine_time_steps = int((runtime * 1000.0) / machine_time_step)
size_of_region = self.get_recording_region_size(outSpikeBytes, no_machine_time_steps)
if numberOfBytesWritten > size_of_region:
raise exceptions.MemReadException("the amount of memory written was "
"larger than was allocated for it")
# Read the spikes
logger.debug("Reading %d (%s) bytes starting at %s + 4" %
(numberOfBytesWritten, hex(numberOfBytesWritten),
hex(spikeRegionBaseAddress)))
spikeData = controller.txrx.memory_calls.read_mem(
spikeRegionBaseAddress + 4, scamp.TYPE_WORD,
numberOfBytesWritten)
# Extract number of spike bytes from subvertex
outSpikeBytes = subVertexOutSpikeBytesFunction(subvertex)
numberOfTimeStepsWritten = numberOfBytesWritten / (outSpikeBytes)
logger.debug("Processing %d timesteps" % numberOfTimeStepsWritten)
# Loop through ticks
for tick in range(0, numberOfTimeStepsWritten):
# Convert tick to ms
time = tick * (controller.dao.machineTimeStep / 1000.0)
# Get offset into file data that the bit vector representing
# the state at this tick begins at
vectorOffset = (tick * outSpikeBytes)
# Loop through the words that make up this vector
for neuronWordIndex in range(0, outSpikeBytes, 4):
# Unpack the word containing the spikingness of 32 neurons
spikeVectorWord = struct.unpack_from("<I", spikeData,
vectorOffset + neuronWordIndex)
if spikeVectorWord != 0:
# Loop through each bit in this word
for neuronBitIndex in range(0, 32):
# If the bit is set
neuronBitMask = (1 << neuronBitIndex)
if (spikeVectorWord[0] & neuronBitMask) != 0:
# Calculate neuron ID
neuronID = ((neuronWordIndex * 8) + neuronBitIndex
+ subvertex.lo_atom)
# Add spike time and neuron ID to returned lists
spikes = numpy.append(spikes, [[time, neuronID]], 0)
if len(spikes) > 0:
logger.debug("Arranging spikes as per output spec")
if compatible_output == True:
# Change the order to be neuronID : time (don't know why - this
# is how it was done in the old code, so I am doing it here too)
spikes[:,[0,1]] = spikes[:,[1,0]]
# Sort by neuron ID and not by time
spikeIndex = numpy.lexsort((spikes[:,1],spikes[:,0]))
spikes = spikes[spikeIndex]
return spikes;
# If compatible output, return sorted by spike time
spikeIndex = numpy.lexsort((spikes[:,1], spikes[:,0]))
spikes = spikes[spikeIndex]
return spikes
print("No spikes recorded")
return spikes
def _getSpikes(self, controller, compatible_output, spikeRecordingRegion,
subVertexOutSpikeBytesFunction, runtime):
"""
Return a 2-column numpy array containing cell ids and spike times for
recorded cells. This is read directly from the memory for the board.
"""
logger.info("Getting spikes for %s" % (self.label))
spikes = numpy.zeros((0, 2))
# Find all the sub-vertices that this population exists on
for subvertex in self.subvertices:
(x, y, p) = subvertex.placement.processor.get_coordinates()
logger.debug(
"Reading spikes from chip %d, %d, core %d, lo_atom %d" %
(x, y, p, subvertex.lo_atom))
controller.txrx.select(x, y)
# Get the App Data for the core
appDataBaseAddressOffset = getAppDataBaseAddressOffset(p)
appDataBaseAddressBuf = controller.txrx.memory_calls.read_mem(
appDataBaseAddressOffset, scamp.TYPE_WORD, 4)
appDataBaseAddress = struct.unpack("<I", appDataBaseAddressBuf)[0]
# Get the position of the spike buffer
spikeRegionBaseAddressOffset = getRegionBaseAddressOffset(
appDataBaseAddress, spikeRecordingRegion)
spikeRegionBaseAddressBuf = controller.txrx.memory_calls.read_mem(
spikeRegionBaseAddressOffset, scamp.TYPE_WORD, 4)
spikeRegionBaseAddress = struct.unpack(
"<I", spikeRegionBaseAddressBuf)[0]
spikeRegionBaseAddress += appDataBaseAddress
# Read the spike data size
numberOfBytesWrittenBuf = controller.txrx.memory_calls.read_mem(
spikeRegionBaseAddress, scamp.TYPE_WORD, 4)
numberOfBytesWritten = struct.unpack_from(
"<I", numberOfBytesWrittenBuf)[0]
#check that the number of spikes written is smaller or the same as the size of the memory
#region we allocated for spikes
outSpikeBytes = subVertexOutSpikeBytesFunction(subvertex)
machine_time_step = conf.config.getint("Machine",
"machineTimeStep")
no_machine_time_steps = int((runtime * 1000.0) / machine_time_step)
size_of_region = self.get_recording_region_size(
outSpikeBytes, no_machine_time_steps)
if numberOfBytesWritten > size_of_region:
raise exceptions.MemReadException(
"the amount of memory written was "
"larger than was allocated for it")
# Read the spikes
logger.debug("Reading %d (%s) bytes starting at %s + 4" %
(numberOfBytesWritten, hex(numberOfBytesWritten),
hex(spikeRegionBaseAddress)))
spikeData = controller.txrx.memory_calls.read_mem(
spikeRegionBaseAddress + 4, scamp.TYPE_WORD,
numberOfBytesWritten)
# Extract number of spike bytes from subvertex
outSpikeBytes = subVertexOutSpikeBytesFunction(subvertex)
numberOfTimeStepsWritten = numberOfBytesWritten / (outSpikeBytes)
logger.debug("Processing %d timesteps" % numberOfTimeStepsWritten)
# Loop through ticks
for tick in range(0, numberOfTimeStepsWritten):
# Convert tick to ms
time = tick * (controller.dao.machineTimeStep / 1000.0)
# Get offset into file data that the bit vector representing
# the state at this tick begins at
vectorOffset = (tick * outSpikeBytes)
# Loop through the words that make up this vector
for neuronWordIndex in range(0, outSpikeBytes, 4):
# Unpack the word containing the spikingness of 32 neurons
spikeVectorWord = struct.unpack_from(
"<I", spikeData, vectorOffset + neuronWordIndex)
if spikeVectorWord != 0:
# Loop through each bit in this word
for neuronBitIndex in range(0, 32):
# If the bit is set
neuronBitMask = (1 << neuronBitIndex)
if (spikeVectorWord[0] & neuronBitMask) != 0:
# Calculate neuron ID
neuronID = ((neuronWordIndex * 8) +
neuronBitIndex + subvertex.lo_atom)
# Add spike time and neuron ID to returned lists
spikes = numpy.append(spikes,
[[time, neuronID]], 0)
if len(spikes) > 0:
logger.debug("Arranging spikes as per output spec")
if compatible_output == True:
# Change the order to be neuronID : time (don't know why - this
# is how it was done in the old code, so I am doing it here too)
spikes[:, [0, 1]] = spikes[:, [1, 0]]
# Sort by neuron ID and not by time
spikeIndex = numpy.lexsort((spikes[:, 1], spikes[:, 0]))
spikes = spikes[spikeIndex]
return spikes
# If compatible output, return sorted by spike time
spikeIndex = numpy.lexsort((spikes[:, 1], spikes[:, 0]))
spikes = spikes[spikeIndex]
return spikes
print("No spikes recorded")
return spikes
def get_neuron_parameter(self, region, compatible_output, controller):
if not controller.dao.has_ran:
raise exceptions.PacmanException("The simulation has not yet ran,"
"therefore gsyn cannot be "
"retrieved")
value = numpy.zeros((0, 3))
# Find all the sub-vertices that this population exists on
for subvertex in self.subvertices:
(x, y, p) = subvertex.placement.processor.get_coordinates()
controller.txrx.select(x, y)
# Get the App Data for the core
appDataBaseAddressOffset = getAppDataBaseAddressOffset(p)
appDataBaseAddressBuf = controller.txrx.memory_calls.read_mem(
appDataBaseAddressOffset, scamp.TYPE_WORD, 4)
appDataBaseAddress = struct.unpack("<I", appDataBaseAddressBuf)[0]
# Get the position of the value buffer
vRegionBaseAddressOffset = getRegionBaseAddressOffset(
appDataBaseAddress, region)
vRegionBaseAddressBuf = controller.txrx.memory_calls.read_mem(
vRegionBaseAddressOffset, scamp.TYPE_WORD, 4)
vRegionBaseAddress = struct.unpack("<I",
vRegionBaseAddressBuf)[0]
vRegionBaseAddress += appDataBaseAddress
# Read the size
numberOfBytesWrittenBuf = controller.txrx.memory_calls.read_mem(
vRegionBaseAddress, scamp.TYPE_WORD, 4)
numberOfBytesWritten = struct.unpack_from("<I",
numberOfBytesWrittenBuf)[0]
# Read the values
logger.debug("Reading %d (%s) bytes starting at %s"
%(numberOfBytesWritten, hex(numberOfBytesWritten),
hex(vRegionBaseAddress + 4)))
vData = controller.txrx.memory_calls.read_mem(
vRegionBaseAddress + 4, scamp.TYPE_WORD,
numberOfBytesWritten)
bytesPerTimeStep = subvertex.n_atoms * 4
numberOfTimeStepsWritten = numberOfBytesWritten / bytesPerTimeStep
msPerTimestep = controller.dao.machineTimeStep / 1000.0
logger.debug("Processing %d timesteps" % numberOfTimeStepsWritten)
# Standard fixed-point 'accum' type scaling
size = len(vData) / 4
scale = numpy.zeros(size, dtype=numpy.float)
scale.fill(float(0x7FFF))
# Add an array for time and neuron id
time = numpy.array([int(i / subvertex.n_atoms) * msPerTimestep
for i in range(size)], dtype=numpy.float)
neuronId = numpy.array([int(i % subvertex.n_atoms)
+ subvertex.lo_atom for i in range(size)],
dtype=numpy.uint32)
# Get the values
tempValue = numpy.frombuffer(vData, dtype="<i4")
tempValue = numpy.divide(tempValue, scale)
tempArray = numpy.dstack((time, neuronId, tempValue))
tempArray = numpy.reshape(tempArray, newshape=(-1, 3))
value = numpy.append(value, tempArray, axis=0)
logger.debug("Arranging parameter output")
if compatible_output == True:
# Change the order to be neuronID : time (don't know why - this
# is how it was done in the old code, so I am doing it here too)
value[:,[0,1,2]] = value[:,[1,0,2]]
# Sort by neuron ID and not by time
vIndex = numpy.lexsort((value[:,2], value[:,1], value[:,0]))
value = value[vIndex]
return value
# If not compatible output, we will sort by time (as NEST seems to do)
vIndex = numpy.lexsort((value[:,2], value[:,1], value[:,0]))
value = value[vIndex]
return value