def one_layer(image_size,
filter_size,
in_chn,
out_chn,
block_size,
ifmap,
weights,
bias,
num_nonzero,
pruner_name="NaivePruner"):
os_tb = OSArchTB(image_size, filter_size, in_chn, out_chn, block_size,
ifmap, weights, bias, pruner_name, num_nonzero)
run_tb(os_tb, verbose=False)
return os_tb.stimulus.ofmap
def main(architecture_name, layer_name, mapping_name, bias_data_name,
weights_data_name, ifmap_data_name, stats_name):
from nnsim.simulator import run_tb
# =======================================================================
print('\t SETTING UP WS DESIGN TESTBENCH...')
print('##############################################')
print(' architecture:', architecture_name, \
'\n layer:', layer_name, \
'\n mapping: ', mapping_name,\
'\n bias_data:', bias_data_name,\
'\n ifmap_data:', ifmap_data_name,\
'\n weights_data:', weights_data_name,\
'\n stats_name:', stats_name)
print('##############################################')
#==============================================================
# Instantiate & Configure Testbench
#==============================================================
setup = {'architecture_name': architecture_name, \
'layer_name': layer_name,\
'bias_data_name': bias_data_name,\
'ifmap_data_name': ifmap_data_name,\
'weights_data_name': weights_data_name,\
'mapping_name': mapping_name}
tb = ws_PE_sparse_tb(setup)
tb.configure()
# ==============================================================
# run simulation
#==============================================================
# directory for saving the stats (access counts, traces, etc.)
import os
os.makedirs(stats_name, exist_ok=True)
# start simulation
run_tb(tb, \
verbose = False, \
dump_stats = True, \
stats_dir = stats_name, \
nticks = None)
out_chn=6,
name='conv1',
activations=(ReLU('name=relu1'),Pool(dh=2,dw=2,name='pool'))
),
Conv(image_size=(4, 4),
filter_size=(3, 3),
in_chn=6,
out_chn=2,
name='conv2',
activations=(ReLU('name=relu2'),)
),
FC(input_size=32,
output_size=11,
name='fc1',
activations=(ReLU('name=relu3'),)
),
FC(input_size=11,
output_size=3,
name='fc2',
activations=(ReLU('name=relu4'),)
),
]
tb = MetaArchTB(arr_x=8,
arr_y=4,
chn_per_word=4,
layers=layers,
batch_size=2
)
run_tb(tb, verbose=False, dump_stats=True)
for tup in noc_multicast_list:
sub_module, key = tup[0], tup[1]
noc_multicasts += sub_module.raw_stats[key]
self.raw_stats['total_noc_multicasts'] = noc_multicasts
### scale memory access stats by energy factors to determine the energy stats
self.raw_stats['dram_energy'] = self.raw_stats[
'dram_mem_acc'] * DRAM_ENERGY_FACTOR
self.raw_stats[
'glb_energy'] = self.raw_stats['glb_mem_acc'] * GLB_ENERGY_FACTOR
self.raw_stats[
'rf_energy'] = self.raw_stats['rf_mem_acc'] * RF_ENERGY_FACTOR
self.raw_stats['data_energy'] = self.raw_stats['dram_energy'] + \
self.raw_stats['glb_energy'] + self.raw_stats['rf_energy']
self.raw_stats['comp_energy'] = self.raw_stats[
'pe_comp_energy'] + self.raw_stats['tr_alu_comp_energy']
### total energy = data energy + comp energy
self.raw_stats['total_energy'] = self.raw_stats[
'data_energy'] + self.raw_stats['comp_energy']
if __name__ == "__main__":
from nnsim.simulator import run_tb
ws_tb = WSArchTB()
run_tb(ws_tb, verbose=False)
def test_fifo_unchecked():
with pytest.raises(FIFOError):
fifo_tb = FIFOTB(False)
sim.run_tb(fifo_tb, 20, True)
def test_fifo_checked():
fifo_tb = FIFOTB(True)
sim.run_tb(fifo_tb, 20, True)
# send in one extra iteration to flush out last outputs
print("Stimulus:")
print("[")
for i in range(len(self.test_data)-1):
print(self.test_data[i])
print("]")
def tick(self):
if (self.in_chn.vacancy() and not self.iteration == self.iterations+1):
imin = self.curr_set*self.input_size
imax = imin+self.input_size
data = [self.test_data[self.iteration][i] for i in range(imin, imax)]
self.in_chn.push(data)
self.curr_set += 1
if (self.curr_set == self.in_sets):
self.curr_set = 0
self.iteration += 1
if (self.out_chn.valid()):
data = self.out_chn.pop()
print(data)
#print("out_counter: ", self.out_counter)
self.out_counter += 1
if (self.out_counter == self.iterations):
raise Finish("Check manually")
if __name__ == "__main__":
from nnsim.simulator import run_tb
converter_tb = ConverterTB()
run_tb(converter_tb, verbose=False)
def test_channel():
channel_tb = ChannelTB()
sim.run_tb(channel_tb, 100, True)
def test_reg_rd_wr():
reg_tb = RegTB()
sim.run_tb(reg_tb, 10, True)