def run(self, mbs, x, y):
# setup system
sim.setup(model_binary_module=(
speed_tracker_with_protocol_search_c_code_version))
# build verts
reader = SDRAMReaderAndTransmitterWithProtocol(mbs)
reader.add_constraint(ChipAndCoreConstraint(x=x, y=y))
receiver = PacketGathererWithProtocol()
# add verts to graph
sim.add_machine_vertex_instance(reader)
sim.add_machine_vertex_instance(receiver)
# build and add edge to graph
sim.add_machine_edge_instance(MachineEdge(reader, receiver),
"TRANSMIT")
machine = sim.machine()
if machine.is_chip_at(x, y):
return self._do_run(reader, receiver, mbs)
else:
sim.stop()
return None, False, False, "", 0
from pacman.model.graphs.machine import MachineEdge
from pkt_injector_vertex import Pkt_Injector_Vertex
from pkt_extractor_vertex import Pkt_Extractor_Vertex
NUM_INJECTORS = 9
gfe.setup(machine_time_step=1000000,
n_chips_required=1,
model_binary_folder=os.path.dirname(__file__))
# instantiate injector vertices
injectors = []
for i in range(NUM_INJECTORS):
iv = Pkt_Injector_Vertex(i)
gfe.add_machine_vertex_instance(iv)
injectors.append(iv)
# instantiate extractor vertices
ev = Pkt_Extractor_Vertex()
gfe.add_machine_vertex_instance(ev)
# create links from injectors to extractor
for iv in injectors:
gfe.add_machine_edge_instance(MachineEdge(iv, ev), iv.inj_lnk)
gfe.run(10000)
gfe.stop()
def add_machine_edge_instance(source, dest, partition):
global partition_manager
partition_manager.add_outgoing_partition(source, partition)
front_end.add_machine_edge_instance(__generate_machine_edge(
source, dest, partition), partition)
positions = [(x, (y + 1) % MAX_Y_SIZE_OF_FABRIC, "N"),
((x + 1) % MAX_X_SIZE_OF_FABRIC,
(y + 1) % MAX_Y_SIZE_OF_FABRIC, "NE"),
((x + 1) % MAX_X_SIZE_OF_FABRIC, y, "E"),
((x + 1) % MAX_X_SIZE_OF_FABRIC,
(y - 1) % MAX_Y_SIZE_OF_FABRIC, "SE"),
(x, (y - 1) % MAX_Y_SIZE_OF_FABRIC, "S"),
((x - 1) % MAX_X_SIZE_OF_FABRIC,
(y - 1) % MAX_Y_SIZE_OF_FABRIC, "SW"),
((x - 1) % MAX_X_SIZE_OF_FABRIC, y, "W"),
((x - 1) % MAX_X_SIZE_OF_FABRIC,
(y + 1) % MAX_Y_SIZE_OF_FABRIC, "NW")]
for (dest_x, dest_y, compass) in positions:
front_end.add_machine_edge_instance(
MachineEdge(vertices[x][y],
vertices[dest_x][dest_y],
label=compass), ConwayBasicCell.PARTITION_ID)
# run the simulation
front_end.run(runtime)
# get recorded data
recorded_data = dict()
# get the data per vertex
for x in range(0, MAX_X_SIZE_OF_FABRIC):
for y in range(0, MAX_Y_SIZE_OF_FABRIC):
recorded_data[(x, y)] = vertices[x][y].get_data(
front_end.buffer_manager(),
front_end.placements().get_placement_of_vertex(vertices[x][y]))
(y + 1) % MAX_Y_SIZE_OF_FABRIC, "SE"),
((x + 1) % MAX_X_SIZE_OF_FABRIC, y, "S"),
((x + 1) % MAX_X_SIZE_OF_FABRIC,
(y - 1) % MAX_Y_SIZE_OF_FABRIC, "SW"),
(x, (y - 1) % MAX_Y_SIZE_OF_FABRIC, "W"),
((x - 1) % MAX_X_SIZE_OF_FABRIC,
(y - 1) % MAX_Y_SIZE_OF_FABRIC, "NW"),
((x - 1) % MAX_X_SIZE_OF_FABRIC, y, "N"),
((x - 1) % MAX_X_SIZE_OF_FABRIC,
(y + 1) % MAX_Y_SIZE_OF_FABRIC, "NE")]
# build edges for each direction for this vertex
for (dest_x, dest_y, compass) in positions:
front_end.add_machine_edge_instance(
LatticeEdge(
vertices[x][y], vertices[dest_x][dest_y], compass,
"edge between {} and {}".format(vertices[x][y],
vertices[dest_x][dest_y])),
LatticeBasicCell.PARTITION_ID)
vertices[x][y].set_direction_vertex(
direction=compass, vertex=vertices[dest_x][dest_y])
# run the simulation
front_end.run(runtime)
# get recorded data
recorded_data = dict()
# if not front_end.use_virtual_machine():
buffer_manager = front_end.buffer_manager()
# get the data per vertex
def generate_machine_graph (self):
""" generates a machine graph for the application graph
"""
print ("generating machine graph")
# path to binary files
binaries_path = os.path.join(os.path.dirname(__file__), "..", "binaries")
# estimate number of SpiNNaker boards required
# number of subgroups
for grp in self.groups:
self.subgroups += grp.subgroups
# number of required cores
w_cores = self.subgroups * self.subgroups
s_cores = self.subgroups * (((self.subgroups - 2) //
(MLPConstants.MAX_S_CORE_LINKS - 1)) + 1)
i_cores = self.subgroups
t_cores = self.subgroups
cores = w_cores + s_cores + i_cores + t_cores
s = '' if cores == 1 else 's'
print (f"need {cores} SpiNNaker core{s}")
# number of required chips
chips = ((cores - 1) // MLPConstants.DEF_SPINN_CORES_PER_CHIP) + 1
s = '' if chips == 1 else 's'
print (f"estimating {chips} SpiNNaker chip{s}")
# number of required boards
boards = ((chips - 1) // MLPConstants.DEF_SPINN_CHIPS_PER_BOARD) + 1
s = '' if boards == 1 else 's'
print (f"requesting {boards} SpiNNaker board{s}")
# request a SpiNNaker machine and setup the machine graph
try:
gfe.setup (model_binary_folder = binaries_path,
n_boards_required = boards
)
except Exception as err:
print ("\n--------------------------------------------------")
print (f"error: {err}")
print ("--------------------------------------------------\n")
return False
# create weight, sum, input and threshold
# machine vertices associated with every subgroup
for grp in self.groups:
for sgrp in range (grp.subgroups):
# create one weight core for every
# (from_group/from_subgroup, group/subgroup) pair
#TODO: all-zero cores can be optimised out
wvs = []
for from_grp in self.groups:
for from_sgrp in range (from_grp.subgroups):
wv = WeightVertex (self, grp, sgrp,
from_grp, from_sgrp)
gfe.add_machine_vertex_instance (wv)
wvs.append (wv)
grp.w_vertices.append (wvs)
# create a sum core tree per subgroup
#NOTE: sum vertices are added during tree building
svt = SumVertexTree (self, grp, sgrp)
grp.s_vertex.append (svt)
# create one input core per subgroup
iv = InputVertex (self, grp, sgrp)
grp.i_vertex.append (iv)
gfe.add_machine_vertex_instance (iv)
# create one threshold core per subgroup
tv = ThresholdVertex (self, grp, sgrp)
grp.t_vertex.append (tv)
gfe.add_machine_vertex_instance (tv)
# groups and subgroups with special functions
first_grp = self.groups[0]
first_subgroup_svt = first_grp.s_vertex[0]
last_out_grp = self.output_chain[-1]
last_out_subgroup_t_vertex = (
last_out_grp.t_vertex[last_out_grp.subgroups - 1]
)
# create associated forward, backprop, link delta summation,
# criterion, stop and sync machine edges for every subgroup
for grp in self.groups:
for sgrp in range (grp.subgroups):
svt = grp.s_vertex[sgrp]
iv = grp.i_vertex[sgrp]
tv = grp.t_vertex[sgrp]
for wv in grp.w_vertices[sgrp]:
from_grp = wv.from_group
from_sgrp = wv.from_subgroup
from_svt = from_grp.s_vertex[from_sgrp]
from_tv = from_grp.t_vertex[from_sgrp]
# sum tree leaf to connect to depends on group/subgroup
svt_leaf = svt.leaf (from_grp, from_sgrp)
from_svt_leaf = from_svt.leaf (grp, sgrp)
# forward w to s link
gfe.add_machine_edge_instance (
MachineEdge (wv, svt_leaf),
wv.fwd_link
)
# forward t to w (multicast) link
gfe.add_machine_edge_instance (
MachineEdge (from_tv, wv),
from_tv.fwd_link
)
# backprop w to s link
gfe.add_machine_edge_instance (
MachineEdge (wv, from_svt_leaf),
wv.bkp_link
)
# backprop i to w (multicast) link
gfe.add_machine_edge_instance (
MachineEdge (iv, wv),
iv.bkp_link
)
# link delta summation w to s link
gfe.add_machine_edge_instance (
MachineEdge (wv, svt_leaf),
wv.lds_link
)
# link delta result (first group) s to w (multicast) link
gfe.add_machine_edge_instance (
MachineEdge (first_subgroup_svt.root, wv),
first_subgroup_svt.root.lds_link
)
# stop (last output group/subgroup) t to w (multicast) link
gfe.add_machine_edge_instance (
MachineEdge (last_out_subgroup_t_vertex, wv),
last_out_subgroup_t_vertex.stp_link
)
# forward sync generation w to s links
gfe.add_machine_edge_instance (
MachineEdge (wv, svt_leaf),
wv.fsg_link
)
# forward s to i link
gfe.add_machine_edge_instance (
MachineEdge (svt.root, iv),
svt.root.fwd_link
)
# forward i to t link
gfe.add_machine_edge_instance (
MachineEdge (iv, tv),
iv.fwd_link
)
# backprop t to i link
gfe.add_machine_edge_instance (
MachineEdge (tv, iv),
tv.bkp_link
)
# backprop s to t link
gfe.add_machine_edge_instance (
MachineEdge (svt.root, tv),
svt.root.bkp_link
)
# link delta summation s to s link
if sgrp != 0:
# first subgroup collects from all other subgroups
gfe.add_machine_edge_instance (
MachineEdge (
svt.root,
grp.s_vertex[0].root
),
svt.root.lds_link
)
elif grp != first_grp:
# first group collects from all other groups
gfe.add_machine_edge_instance (
MachineEdge (
svt.root,
first_subgroup_svt.root
),
svt.root.lds_link
)
# t to t criterion link
# intra-group criterion link to last subgroup t
if sgrp < (grp.subgroups - 1):
gfe.add_machine_edge_instance (
MachineEdge (tv, grp.t_vertex[grp.subgroups - 1]),
tv.stp_link
)
elif grp != last_out_grp:
# inter-group criterion link to last output subgroup
gfe.add_machine_edge_instance (
MachineEdge (tv, last_out_subgroup_t_vertex),
tv.stp_link
)
# stop (last output group/subgroup) t to s (multicast) link
for s in svt.vertices:
gfe.add_machine_edge_instance (
MachineEdge (last_out_subgroup_t_vertex, s),
last_out_subgroup_t_vertex.stp_link
)
# stop (last output group/subgroup) t to i (multicast) link
gfe.add_machine_edge_instance (
MachineEdge (last_out_subgroup_t_vertex, iv),
last_out_subgroup_t_vertex.stp_link
)
# stop (last output group/subgroup) t to t (multicast) link
if tv != last_out_subgroup_t_vertex:
gfe.add_machine_edge_instance (
MachineEdge (last_out_subgroup_t_vertex, tv),
last_out_subgroup_t_vertex.stp_link
)
# forward sync generation s to s links
#NOTE: s cores that are tree internal nodes not involved
if sgrp != 0:
# first subgroup collects from all other subgroups
gfe.add_machine_edge_instance (
MachineEdge (
svt.root,
grp.s_vertex[0].root
),
svt.root.fsg_link
)
elif grp != first_grp:
# first group collects from all other groups
gfe.add_machine_edge_instance (
MachineEdge (
svt.root,
first_subgroup_svt.root
),
svt.root.fsg_link
)
# forward sync generation first s to last t link
gfe.add_machine_edge_instance (
MachineEdge (first_subgroup_svt.root, last_out_subgroup_t_vertex),
first_subgroup_svt.root.fsg_link
)
self._graph_rdy = True
return True
mbs = 1.0 # setup system sim.setup(model_binary_module=test_retransmission_phase_on_multi_cores) # build verts reader = SDRAMReaderAndTransmitterWithProtocol(mbs) reader.add_constraint(ChipAndCoreConstraint(x=1, y=1)) receiver = PacketGathererWithProtocol() # add verts to graph sim.add_machine_vertex_instance(reader) sim.add_machine_vertex_instance(receiver) # build and add edge to graph sim.add_machine_edge_instance(MachineEdge(reader, receiver), "TRANSMIT") # run forever (to allow better speed testing) sim.run() # get placements for extraction placements = sim.placements() # try getting data via mc transmission start = None end = None data = None sim.transceiver().set_watch_dog(False) try:
def run_mcmc(model,
data,
n_samples,
burn_in=2000,
thinning=5,
degrees_of_freedom=3.0,
seed=None,
n_chips=None,
n_boards=None):
""" Executes an MCMC model, returning the received samples
:param model: The MCMCModel to be used
:param data: The data to sample
:param n_samples: The number of samples to generate
:param burn_in:\
no of MCMC transitions to reach apparent equilibrium before\
generating inference samples
:param thinning:\
sampling rate i.e. 5 = 1 sample for 5 generated steps
:param degrees_of_freedom:\
The number of degrees of freedom to jump around with
:param seed: The random seed to use
:param n_chips: The number of chips to run the model on
:param root_finder: Use the root finder by adding root finder vertices
:param cholesky: Use the Cholesky algorithm by adding Cholesky vertices
:return: The samples read
:rtype: A numpy array with fields for each model state variable
"""
# Set up the simulation
g.setup(n_boards_required=n_boards,
n_chips_required=n_chips,
model_binary_module=model_binaries)
# Get the number of cores available for use
n_cores = 0
machine = g.machine()
# Create a coordinator for each board
coordinators = dict()
boards = dict()
for chip in machine.ethernet_connected_chips:
# Create a coordinator
coordinator = MCMCCoordinatorVertex(model, data, n_samples, burn_in,
thinning, degrees_of_freedom, seed)
g.add_machine_vertex_instance(coordinator)
# Put the coordinator on the Ethernet chip
coordinator.add_constraint(ChipAndCoreConstraint(chip.x, chip.y))
coordinators[chip.x, chip.y] = coordinator
boards[chip.x, chip.y] = chip.ip_address
# Go through all the chips and add the workhorses
n_chips_on_machine = machine.n_chips
n_workers = 0
if (model.root_finder):
n_root_finders = 0
if (model.cholesky):
n_cholesky = 0
for chip in machine.chips:
# Count the cores in the processor
# (-1 if this chip also has a coordinator)
n_cores = len([p for p in chip.processors if not p.is_monitor])
if (chip.x, chip.y) in coordinators:
n_cores -= 3 # coordinator and extra_monitor_support (2)
if (model.root_finder):
if (model.cholesky):
n_cores = n_cores // 3
else:
n_cores = n_cores // 2
else:
n_cores -= 1 # just extra_monitor_support
if (model.root_finder):
if (model.cholesky):
n_cores = n_cores // 3
else:
n_cores = n_cores // 2
# Find the coordinator for the board (or 0, 0 if it is missing)
eth_x = chip.nearest_ethernet_x
eth_y = chip.nearest_ethernet_y
coordinator = coordinators.get((eth_x, eth_y))
if coordinator is None:
print("Warning - couldn't find {}, {} for chip {}, {}".format(
eth_x, eth_y, chip.x, chip.y))
coordinator = coordinators[0, 0]
print("Using coordinator ", coordinator)
# hard-code remove some cores (chip power monitor etc.) just
# to see what happens
# n_cores -= non_worker_cores_per_chip
# print 'n_cores: ', n_cores
# Add a vertex for each core
for _ in range(n_cores):
# Create the vertex and add it to the graph
vertex = MCMCVertex(coordinator, model)
n_workers += 1
g.add_machine_vertex_instance(vertex)
# Put the vertex on the same board as the coordinator
vertex.add_constraint(ChipAndCoreConstraint(chip.x, chip.y))
# Add an edge from the coordinator to the vertex, to send the data
g.add_machine_edge_instance(MachineEdge(coordinator, vertex),
coordinator.data_partition_name)
# Add an edge from the vertex to the coordinator,
# to send acknowledgement
g.add_machine_edge_instance(MachineEdge(vertex, coordinator),
coordinator.acknowledge_partition_name)
if (model.root_finder):
# Create a root finder vertex
rf_vertex = MCMCRootFinderVertex(vertex, model)
n_root_finders += 1
g.add_machine_vertex_instance(rf_vertex)
# put it on the same chip as the standard mcmc vertex?
# no - put it on a "nearby" chip, however that works
rf_vertex.add_constraint(ChipAndCoreConstraint(chip.x, chip.y))
# Add an edge from mcmc vertex to root finder vertex,
# to "send" the data - need to work this out
g.add_machine_edge_instance(MachineEdge(vertex, rf_vertex),
vertex.parameter_partition_name)
# Add edge from root finder vertex back to mcmc vertex
# to send acknowledgement / result - need to work this out
g.add_machine_edge_instance(MachineEdge(rf_vertex, vertex),
vertex.result_partition_name)
if (model.cholesky):
# Create a Cholesky vertex
cholesky_vertex = MCMCCholeskyVertex(vertex, model)
n_cholesky += 1
g.add_machine_vertex_instance(cholesky_vertex)
# put it on the same chip as the standard mcmc vertex?
# no - put it on a "nearby" chip, however that works
cholesky_vertex.add_constraint(
ChipAndCoreConstraint(chip.x, chip.y))
# Add an edge from mcmc vertex to Cholesky vertex,
# to "send" the data - need to work this out
g.add_machine_edge_instance(
MachineEdge(vertex, cholesky_vertex),
vertex.cholesky_partition_name)
# Add edge from Cholesky vertex back to mcmc vertex
# to send acknowledgement / result - need to work this out
g.add_machine_edge_instance(
MachineEdge(cholesky_vertex, vertex),
vertex.cholesky_result_partition_name)
start_computing_time = time.time()
logger.info("n_chips_on_machine {}".format(n_chips_on_machine))
logger.info("Running {} worker cores".format(n_workers))
if (model.root_finder):
logger.info("Running {} root finder cores".format(n_root_finders))
if (model.cholesky):
logger.info("Running {} Cholesky cores".format(n_cholesky))
# Run the simulation
g.run_until_complete()
mid_computing_time = time.time()
# Wait for the application to finish
txrx = g.transceiver()
app_id = globals_variables.get_simulator()._app_id
logger.info("Running {} worker cores".format(n_workers))
if (model.root_finder):
logger.info("Running {} root finder cores".format(n_root_finders))
if (model.cholesky):
logger.info("Running {} Cholesky cores".format(n_cholesky))
logger.info("Waiting for application to finish...")
running = txrx.get_core_state_count(app_id, CPUState.RUNNING)
# there are now cores doing extra_monitor etc.
non_worker_cores = n_chips_on_machine + (2 * len(boards))
while running > non_worker_cores:
time.sleep(0.5)
error = txrx.get_core_state_count(app_id, CPUState.RUN_TIME_EXCEPTION)
watchdog = txrx.get_core_state_count(app_id, CPUState.WATCHDOG)
if error > 0 or watchdog > 0:
error_msg = "Some cores have failed ({} RTE, {} WDOG)".format(
error, watchdog)
raise Exception(error_msg)
running = txrx.get_core_state_count(app_id, CPUState.RUNNING)
print('running: ', running)
finish_computing_time = time.time()
# Get the data back
samples = dict()
for coord, coordinator in iteritems(coordinators):
samples[coord[0],
coord[1]] = coordinator.read_samples(g.buffer_manager())
# Close the machine
g.stop()
finish_time = time.time()
# Note: this timing appears to be incorrect now; needs looking at
print("Overhead time is %s seconds" % (start_computing_time - start_time))
print("Computing time is %s seconds" %
(finish_computing_time - start_computing_time))
print("run_until_complete takes %s seconds" %
(mid_computing_time - start_computing_time))
print("Data collecting time is %s seconds" %
(finish_time - finish_computing_time))
print("Overall running time is %s seconds" % (finish_time - start_time))
return samples
def generate_machine_graph (self):
""" generates a machine graph for the application graph
"""
print "generating machine graph"
# setup the machine graph
g.setup ()
# set the number of write blocks before generating vertices
self._num_write_blks = len (self.output_chain)
# create associated weight, sum, input and threshold
# machine vertices for every network group
for grp in self.groups:
# create one weight core per (from_group, group) pair
# NOTE: all-zero cores can be optimised out
for from_grp in self.groups:
wv = WeightVertex (self, grp, from_grp)
grp.w_vertices.append (wv)
g.add_machine_vertex_instance (wv)
self._num_vertices += 1
# create one sum core per group
sv = SumVertex (self, grp)
grp.s_vertex = sv
g.add_machine_vertex_instance (sv)
self._num_vertices += 1
# create one input core per group
iv = InputVertex (self, grp)
grp.i_vertex = iv
g.add_machine_vertex_instance (iv)
self._num_vertices += 1
# create one sum core per group
tv = ThresholdVertex (self, grp)
grp.t_vertex = tv
g.add_machine_vertex_instance (tv)
self._num_vertices += 1
# create associated forward, backprop, synchronisation and
# stop machine edges for every network group
first = self.groups[0]
for grp in self.groups:
for w in grp.w_vertices:
_frmg = w.from_group
# create forward w to s links
g.add_machine_edge_instance (MachineEdge (w, grp.s_vertex),
w.fwd_link)
# create forward t to w (multicast) links
g.add_machine_edge_instance (MachineEdge (_frmg.t_vertex, w),
_frmg.t_vertex.fwd_link)
# create backprop w to s links
g.add_machine_edge_instance (MachineEdge (w, _frmg.s_vertex),
w.bkp_link)
# create backprop i to w (multicast) links
g.add_machine_edge_instance (MachineEdge (grp.i_vertex, w),
grp.i_vertex.bkp_link)
# create forward synchronisation w to t links
g.add_machine_edge_instance (MachineEdge (w, _frmg.t_vertex),
w.fds_link)
# create link delta summation w to s links
g.add_machine_edge_instance (MachineEdge (w, grp.s_vertex),
w.lds_link)
# create link delta summation result s (first) to w links
g.add_machine_edge_instance (MachineEdge (first.s_vertex, w),
first.s_vertex.lds_link)
# create forward s to i link
g.add_machine_edge_instance (MachineEdge (grp.s_vertex,
grp.i_vertex),
grp.s_vertex.fwd_link)
# create backprop s to t link
g.add_machine_edge_instance (MachineEdge (grp.s_vertex,
grp.t_vertex),
grp.s_vertex.bkp_link)
# create forward i to t link
g.add_machine_edge_instance (MachineEdge (grp.i_vertex,
grp.t_vertex),
grp.i_vertex.fwd_link)
# create backprop t to i link
g.add_machine_edge_instance (MachineEdge (grp.t_vertex,
grp.i_vertex),
grp.t_vertex.bkp_link)
# create link delta summation s to s links - all s cores
# (except the first) send to the first s core
if grp != first:
print "Creating lds s-s edge from group {} to group {}".\
format (grp.label, first.label)
g.add_machine_edge_instance (MachineEdge (grp.s_vertex,
first.s_vertex),
grp.s_vertex.lds_link)
# create stop links, if OUTPUT group
if grp in self.output_chain:
# if last OUTPUT group broadcast stop decision
if grp == self.output_chain[-1]:
for stpg in self.groups:
# create stop links to all w cores
for w in stpg.w_vertices:
g.add_machine_edge_instance\
(MachineEdge (grp.t_vertex, w),
grp.t_vertex.stp_link)
# create stop links to all s cores
g.add_machine_edge_instance\
(MachineEdge (grp.t_vertex, stpg.s_vertex),\
grp.t_vertex.stp_link)
# create stop links to all i cores
g.add_machine_edge_instance\
(MachineEdge (grp.t_vertex, stpg.i_vertex),\
grp.t_vertex.stp_link)
# create stop links to t cores (no link to itself!)
if stpg != grp:
g.add_machine_edge_instance\
(MachineEdge (grp.t_vertex, stpg.t_vertex),\
grp.t_vertex.stp_link)
else:
# create stop link to next OUTPUT group in chain
_inx = self.output_chain.index (grp)
_stpg = self.output_chain[_inx + 1]
g.add_machine_edge_instance (MachineEdge (grp.t_vertex,
_stpg.t_vertex),
grp.t_vertex.stp_link)
def __init__(self, network, group, subgroup):
max_links = MLPConstants.MAX_S_CORE_LINKS
# total number of Sum Vertices needed to build the tree
num_vrt = ((network.subgroups - 2) // (max_links - 1)) + 1
# the root vertex is used as pre-vertex for outgoing links
self._root = SumVertex(network, group, subgroup, 0)
# add the root to the graph
gfe.add_machine_vertex_instance(self.root)
# and to the list of all tree vertices
self._vertices = [self.root]
# create the SumVertex tree
free_links = max_links
to_vrt = 0
for vrt in range(1, num_vrt):
# create a SumVertex
vt = SumVertex(network, group, subgroup, vrt)
# add it to the list of vertices
self._vertices.append(vt)
# add it to the graph
gfe.add_machine_vertex_instance(vt)
# add all SumVertex links towards the tree root
gfe.add_machine_edge_instance(
MachineEdge(vt, self.vertices[to_vrt]), vt.fwd_link)
gfe.add_machine_edge_instance(
MachineEdge(vt, self.vertices[to_vrt]), vt.bkp_link)
gfe.add_machine_edge_instance(
MachineEdge(vt, self.vertices[to_vrt]), vt.lds_link)
gfe.add_machine_edge_instance(
MachineEdge(vt, self.vertices[to_vrt]), vt.fsg_link)
# take away one free link from vertex to_vrt
free_links -= 1
# if out of free links use next available vertex
if free_links == 0:
free_links = max_links
to_vrt += 1
# finally, map every pre-vertex to an available tree vertex
self._leaf_map = {}
for grp in network.groups:
for sgrp in range(grp.subgroups):
# assign available leaf vertex
self._leaf_map[(grp.id, sgrp)] = self.vertices[to_vrt]
# take away one free link from vertex to_vrt
free_links -= 1
# if out of free links use next available vertex
if free_links == 0:
free_links = max_links
to_vrt += 1
output_vertex = ICUBOutputVertex(spinnaker_link_id=spinnaker_link_used,
board_address=None,
label="Output Vertex")
front_end.add_machine_vertex_instance(output_vertex)
# create retina filters and edges from retina to filters
for y_row in range(0, constants.RETINA_Y_SIZE):
partition_identifier = "retina_slice_row_{}".format(y_row)
vertex = RetinaFilter(partition_identifier=partition_identifier,
filter=y_row,
row_id=y_row)
filter_list.append(vertex)
front_end.add_machine_vertex_instance(vertex)
front_end.add_machine_edge_instance(
MachineEdge(pre_vertex=input_vertex,
post_vertex=vertex,
label="Edge between retina and filter"),
partition_identifier)
# create particles
main_particle = True
the_main_particle = None
for x in range(0, n_particles):
vertex = PfFullParticleVertex(x=constants.RETINA_X_SIZE / 2,
y=constants.RETINA_Y_SIZE / 2,
r=constants.INITIAL_R,
batch_size=constants.MAX_BATCH_SIZE,
n_particles=n_particles,
part_id=x,
label="Particle {}".format(x),
main_particle=main_particle)
