connector = pynn.AllToAllConnector(weights=1)
duration = 1500.0
# initialize without spike times
stimulus_exc = pynn.Population(1, pynn.SpikeSourceArray, {'spike_times': []})
stimulus_neuron = stimulus_exc[0]
projections = [
pynn.Projection(stimulus_exc, pop, connector, target='excitatory'),
]
# ——— run mapping —————————————————————————————————————————————————————————————
marocco.skip_mapping = False
marocco.backend = PyMarocco.None
pynn.reset()
pynn.run(duration)
# ——— change low-level parameters before configuring hardware —————————————————
def set_sthal_params(wafer, gmax, gmax_div):
"""
synaptic strength:
gmax: 0 - 1023, strongest: 1023
gmax_div: 1 - 15, strongest: 1
"""
# for all HICANNs in use
sim.AllToAllConnector(), target='excitatory')
exc_wta_proj.append(proj)
proj = sim.Projection(inh_mid_pop, mid_pops[idx],
sim.AllToAllConnector(), target='inhibitory')
inh_wta_proj.append(proj)
# import sys
# sys.exit(0)
### ====================== PERFORM MAPPING =========================== ###
seed = 0
marocco.l1_routing.shuffle_switches_seed(seed)
marocco.skip_mapping = False
marocco.backend = PyMarocco.None
sim.reset()
sim.run(duration)
### ==================== DO A FIRST HARDWARE RUN ======================= ###
wafer = runtime.wafer()
hicanns_in_use = wafer.getAllocatedHicannCoordinates()
print("\n\n\n\n")
print(hicanns_in_use)
# for p in mid_pops:
# if p.hicann is None:
def main():
parser = argparse.ArgumentParser()
# scale factor of the whole network compared to the original one
parser.add_argument('--scale', default=0.01, type=float)
# size of one neueron in hw neurons
parser.add_argument('--n_size', default=4, type=int)
parser.add_argument('--k_scale', type=float) # scale of connections
# wafer defects that should be considered in the mapping
parser.add_argument('--wafer', '-w', type=int, default=24)
# specific path where the defect parts of the wafer are saved
# if nothing specified, current defects of the given wafer are used
parser.add_argument('--defects_path', type=str)
parser.add_argument('--ignore_blacklisting',
type=str2bool,
nargs='?',
default=False,
const=True)
parser.add_argument('--name', type=str,
default='cortical_column_network') # name
parser.add_argument('--placer', type=str, default='byNeuron')
parser.add_argument('--seed', default=0, type=int)
args = parser.parse_args()
# k_scale is set to "scale" by deflaut
if not args.k_scale:
args.k_scale = args.scale
taskname = "scale{}_k-scale{}_nsize{}_wafer{}_ignoreBlacklsiting{}".format(
args.scale, args.k_scale, args.n_size, args.wafer,
args.ignore_blacklisting)
marocco = PyMarocco()
marocco.neuron_placement.default_neuron_size(args.n_size)
if (args.ignore_blacklisting):
marocco.defects.backend = Defects.Backend.Without
else:
marocco.defects.backend = Defects.Backend.XML
marocco.skip_mapping = False
marocco.backend = PyMarocco.Without
marocco.continue_despite_synapse_loss = True
marocco.default_wafer = C.Wafer(args.wafer) # give wafer args
marocco.calib_backend = PyMarocco.CalibBackend.Default
marocco.calib_path = "/wang/data/calibration/brainscales/default"
if args.defects_path:
marocco.defects.path = args.defects_path
else:
marocco.defects.path = "/wang/data/commissioning/BSS-1/rackplace/" + str(
args.wafer) + "/derived_plus_calib_blacklisting/current"
# c 4189 no specification
#taskname += "_c4189_"
# strategy
marocco.merger_routing.strategy( # is now default
marocco.merger_routing.minimize_as_possible)
#taskname += "_minimAsPoss"
'''
# placement strategy
user_strat = placer()
taskname += "_placer"
'''
if args.placer == "byNeuron":
user_strat = placer_neuron_cluster() # cluster by neurons
taskname += "_byNeuron"
marocco.neuron_placement.default_placement_strategy(user_strat)
if args.placer == "byEnum":
user_strat = placer_enum_IDasc() # cluster by neurons
taskname += "_byEnum"
marocco.neuron_placement.default_placement_strategy(user_strat)
if args.placer == "constrained":
# needed for 5720 with patch set 36(best results) or ps 50
from pymarocco_runtime import ConstrainedNeuronClusterer as placer_neuron_resizer
user_strat = placer_neuron_resizer()
taskname += "_constrained"
marocco.neuron_placement.default_placement_strategy(user_strat)
# give marocco the format of the results file
taskname += str(datetime.now())
marocco.persist = "results_{}_{}.xml.gz".format(args.name, taskname)
start = datetime.now()
r = CorticalNetwork(marocco,
scale=args.scale,
k_scale=args.k_scale,
seed=args.seed)
r.build()
mid = datetime.now()
try:
r.run()
totsynapses = marocco.stats.getSynapses()
totneurons = marocco.stats.getNumNeurons()
lostsynapses = marocco.stats.getSynapseLoss()
lostsynapsesl1 = marocco.stats.getSynapseLossAfterL1Routing()
perPopulation = r.getLoss(marocco)
print("Losses: ", lostsynapses, " of ", totsynapses, " L1Loss:",
lostsynapsesl1, " Relative:", lostsynapses / float(totsynapses))
except RuntimeError as err:
# couldn't place all populations
totsynapses = 1
totneurons = 1
lostsynapses = 1
lostsynapsesl1 = 1
logger.error(err)
end = datetime.now()
print("time:", end - start)
result = {
"model":
args.name,
"task":
taskname,
"scale":
args.scale,
"k_scale":
args.k_scale,
"n_size":
args.n_size,
"wafer":
args.wafer,
"ignore_blacklisting":
args.ignore_blacklisting,
"timestamp":
datetime.now().isoformat(),
"placer":
args.placer,
"perPopulation":
perPopulation,
"results": [{
"type": "performance",
"name": "setup_time",
"value": (end - mid).total_seconds(),
"units": "s",
"measure": "time"
}, {
"type": "performance",
"name": "total_time",
"value": (end - start).total_seconds(),
"units": "s",
"measure": "time"
}, {
"type": "performance",
"name": "synapses",
"value": totsynapses
}, {
"type": "performance",
"name": "neurons",
"value": totneurons
}, {
"type": "performance",
"name": "synapse_loss",
"value": lostsynapses
}, {
"type": "performance",
"name": "synapse_loss_after_l1",
"value": lostsynapsesl1
}]
}
with open("{}_{}_results.json".format(result["model"], result["task"]),
'w') as outfile:
json.dump(result, outfile)