def run(a_shape=(7, 15),
b_shape=(7, 15),
a_dtype=ng.int32,
b_dtype=ng.int32,
c_dtype=ng.int32,
par=1,
axi_datawidth=32,
silent=False,
filename=None,
simtype='iverilog',
outputfile=None):
# pytorch model
model = MatrixMul()
# Pytorch to ONNX
onnx_filename = 'onnx_matrix_mul.onnx'
dummy_a = torch.randn(*a_shape)
dummy_b = torch.randn(*b_shape)
dummy_inputs = (dummy_a, dummy_b)
input_names = ['a', 'b']
output_names = ['c']
model.eval()
torch.onnx.export(model,
dummy_inputs,
onnx_filename,
input_names=input_names,
output_names=output_names)
# --------------------
# (1) Represent a DNN model as a dataflow by NNgen operators
# --------------------
# ONNX to NNgen
value_dtypes = {'a': a_dtype, 'b': b_dtype, 'c': c_dtype}
(outputs, placeholders, variables, constants,
operators) = ng.from_onnx(onnx_filename,
value_dtypes=value_dtypes,
default_placeholder_dtype=ng.int32,
default_variable_dtype=ng.int32,
default_constant_dtype=ng.int32,
default_operator_dtype=ng.int32,
default_scale_dtype=ng.int32,
default_bias_dtype=ng.int32,
disable_fusion=False)
# --------------------
# (2) Assign quantized weights to the NNgen operators
# --------------------
input_scale_factors = {'a': 10.0, 'b': 15.0}
ng.quantize(outputs, input_scale_factors)
# --------------------
# (3) Assign hardware attributes
# --------------------
for op in operators.values():
if isinstance(op, ng.scaled_multiply):
op.attribute(par=par)
# --------------------
# (4) Verify the DNN model behavior by executing the NNgen dataflow as a software
# --------------------
a = placeholders['a']
b = placeholders['b']
c = outputs['c']
# verification data
input_a = np.arange(a.length, dtype=np.int64).reshape(a.shape) % [17]
input_b = (np.arange(b.length, dtype=np.int64).reshape(b.shape) +
[100]) % [13]
# execution on pytorch
model_a = input_a.astype(np.float32)
if a.perm is not None:
model_a = np.transpose(model_a, a.reversed_perm)
model_b = input_b.astype(np.float32)
if b.perm is not None:
model_b = np.transpose(model_b, b.reversed_perm)
model.eval()
model_c = model(torch.from_numpy(model_a),
torch.from_numpy(model_b)).detach().numpy()
if a.perm is not None:
model_c = np.transpose(model_c, a.perm)
scaled_model_c = model_c * c.scale_factor
# software-based verification
va = input_a * input_scale_factors['a']
va = np.clip(va, -1.0 * (2**(a.dtype.width - 1) - 1),
1.0 * (2**(a.dtype.width - 1) - 1))
va = np.round(va).astype(np.int64)
vb = input_b * input_scale_factors['b']
vb = np.clip(vb, -1.0 * (2**(b.dtype.width - 1) - 1),
1.0 * (2**(b.dtype.width - 1) - 1))
vb = np.round(vb).astype(np.int64)
eval_outs = ng.eval([c], a=va, b=vb)
vc = eval_outs[0]
mean_square_error = np.sum((vc - scaled_model_c)**2) / vc.size
corrcoef = np.corrcoef(model_c.reshape([-1]), vc.reshape([-1]))
# breakpoint()
# --------------------
# (5) Convert the NNgen dataflow to a hardware description (Verilog HDL and IP-XACT)
# --------------------
targ = ng.to_veriloggen([c],
'onnx_matrix_mul',
silent=silent,
config={'maxi_datawidth': axi_datawidth})
# --------------------
# (6) Simulate the generated hardware by Veriloggen and Verilog simulator
# --------------------
if simtype is None:
sys.exit()
# to memory image
param_data = ng.export_ndarray([c])
param_bytes = len(param_data)
variable_addr = int(
math.ceil(
max(a.addr + a.memory_size, b.addr + b.memory_size) / 4096)) * 4096
check_addr = int(math.ceil((variable_addr + param_bytes) / 4096)) * 4096
tmp_addr = int(math.ceil((check_addr + c.memory_size) / 4096)) * 4096
memimg_datawidth = 32
mem = np.zeros([1024 * 1024 * 8 // (memimg_datawidth // 8)],
dtype=np.int64)
mem = mem + [100]
# placeholder
axi.set_memory(mem, va, memimg_datawidth, a_dtype.width, a.addr,
max(int(math.ceil(axi_datawidth / a_dtype.width)), par))
axi.set_memory(mem, vb, memimg_datawidth, b_dtype.width, b.addr,
max(int(math.ceil(axi_datawidth / b_dtype.width)), par))
# parameters (variable and constant)
axi.set_memory(mem, param_data, memimg_datawidth, 8, variable_addr)
# verification data
axi.set_memory(mem, vc, memimg_datawidth, c_dtype.width, check_addr,
max(int(math.ceil(axi_datawidth / c_dtype.width)), par))
# test controller
m = Module('test')
params = m.copy_params(targ)
ports = m.copy_sim_ports(targ)
clk = ports['CLK']
resetn = ports['RESETN']
rst = m.Wire('RST')
rst.assign(Not(resetn))
# AXI memory model
if outputfile is None:
outputfile = os.path.splitext(os.path.basename(__file__))[0] + '.out'
memimg_name = 'memimg_' + outputfile
memory = axi.AxiMemoryModel(m,
'memory',
clk,
rst,
datawidth=axi_datawidth,
memimg=mem,
memimg_name=memimg_name,
memimg_datawidth=memimg_datawidth)
memory.connect(ports, 'maxi')
# AXI-Slave controller
_saxi = vthread.AXIMLite(m, '_saxi', clk, rst, noio=True)
_saxi.connect(ports, 'saxi')
# timer
time_counter = m.Reg('time_counter', 32, initval=0)
seq = Seq(m, 'seq', clk, rst)
seq(time_counter.inc())
num_rep = functools.reduce(lambda x, y: x * y, c.shape[:-1], 1)
def ctrl():
for i in range(100):
pass
ng.sim.set_global_addrs(_saxi, tmp_addr)
start_time = time_counter.value
ng.sim.start(_saxi)
print('# start')
ng.sim.wait(_saxi)
end_time = time_counter.value
print('# end')
print('# execution cycles: %d' % (end_time - start_time))
# verify
ok = True
for i in range(num_rep):
for j in range(c.shape[-1]):
orig = memory.read_word(i * c.aligned_shape[-1] + j, c.addr,
c_dtype.width)
check = memory.read_word(i * c.aligned_shape[-1] + j,
check_addr, c_dtype.width)
if vthread.verilog.NotEql(orig, check):
print('NG', i, j, orig, check)
ok = False
# else:
# print('OK', i, j, orig, check)
if ok:
print('# verify: PASSED')
else:
print('# verify: FAILED')
vthread.finish()
th = vthread.Thread(m, 'th_ctrl', clk, rst, ctrl)
fsm = th.start()
uut = m.Instance(targ,
'uut',
params=m.connect_params(targ),
ports=m.connect_ports(targ))
# simulation.setup_waveform(m, uut)
simulation.setup_clock(m, clk, hperiod=5)
init = simulation.setup_reset(m,
resetn,
m.make_reset(),
period=100,
polarity='low')
init.add(
Delay(1000000),
Systask('finish'),
)
# output source code
if filename is not None:
m.to_verilog(filename)
# run simulation
sim = simulation.Simulator(m, sim=simtype)
rslt = sim.run(outputfile=outputfile)
lines = rslt.splitlines()
if simtype == 'verilator' and lines[-1].startswith('-'):
rslt = '\n'.join(lines[:-1])
return rslt
def run(a_shape=(15, 15),
b_shape=(15, 15),
a_dtype=ng.int32,
b_dtype=ng.int32,
c_dtype=ng.int32,
par=1,
axi_datawidth=32,
silent=False,
filename=None,
simtype='iverilog',
outputfile=None):
# create target hardware
a = ng.placeholder(a_dtype, shape=a_shape, name='a')
b = ng.placeholder(b_dtype, shape=b_shape, name='b')
t = ng.add(a, b, dtype=c_dtype, par=par)
c = ng.relu(t, dtype=c_dtype, par=par)
targ = ng.to_veriloggen([c],
'matrix_add_relu',
silent=silent,
config={'maxi_datawidth': axi_datawidth})
# verification data
va = np.arange(a.length, dtype=np.int64).reshape(a.shape) % [5] - [10]
vb = (np.arange(b.length, dtype=np.int64).reshape(b.shape) +
[100]) % [6] - [10]
eval_outs = ng.eval([c], a=va, b=vb)
vc = eval_outs[0]
# to memory image
size_max = int(
math.ceil(
max(a.memory_size, b.memory_size, c.memory_size) / 4096)) * 4096
check_addr = max(a.addr, b.addr, c.addr) + size_max
size_check = size_max
tmp_addr = check_addr + size_check
memimg_datawidth = 32
mem = np.zeros([1024 * 1024 * 8 // (memimg_datawidth // 8)],
dtype=np.int64)
mem = mem + [100]
axi.set_memory(mem, va, memimg_datawidth, a_dtype.width, a.addr,
max(int(math.ceil(axi_datawidth / a_dtype.width)), par))
axi.set_memory(mem, vb, memimg_datawidth, b_dtype.width, b.addr,
max(int(math.ceil(axi_datawidth / b_dtype.width)), par))
axi.set_memory(mem, vc, memimg_datawidth, c_dtype.width, check_addr,
max(int(math.ceil(axi_datawidth / c_dtype.width)), par))
# test controller
m = Module('test')
params = m.copy_params(targ)
ports = m.copy_sim_ports(targ)
clk = ports['CLK']
resetn = ports['RESETN']
rst = m.Wire('RST')
rst.assign(Not(resetn))
# AXI memory model
if outputfile is None:
outputfile = os.path.splitext(os.path.basename(__file__))[0] + '.out'
memimg_name = 'memimg_' + outputfile
memory = axi.AxiMemoryModel(m,
'memory',
clk,
rst,
datawidth=axi_datawidth,
memimg=mem,
memimg_name=memimg_name,
memimg_datawidth=memimg_datawidth)
memory.connect(ports, 'maxi')
# AXI-Slave controller
_saxi = vthread.AXIMLite(m, '_saxi', clk, rst, noio=True)
_saxi.connect(ports, 'saxi')
# timer
time_counter = m.Reg('time_counter', 32, initval=0)
seq = Seq(m, 'seq', clk, rst)
seq(time_counter.inc())
num_rep = functools.reduce(lambda x, y: x * y, c.shape[:-1], 1)
def ctrl():
for i in range(100):
pass
ng.sim.set_global_addrs(_saxi, tmp_addr)
start_time = time_counter.value
ng.sim.start(_saxi)
print('# start')
ng.sim.wait(_saxi)
end_time = time_counter.value
print('# end')
print('# execution cycles: %d' % (end_time - start_time))
# verify
ok = True
for i in range(num_rep):
for j in range(c.shape[-1]):
orig = memory.read_word(i * c.aligned_shape[-1] + j, c.addr,
c_dtype.width)
check = memory.read_word(i * c.aligned_shape[-1] + j,
check_addr, c_dtype.width)
if vthread.verilog.NotEql(orig, check):
print('NG', i, j, orig, check)
ok = False
# else:
# print('OK', i, j, orig, check)
if ok:
print('# verify: PASSED')
else:
print('# verify: FAILED')
vthread.finish()
th = vthread.Thread(m, 'th_ctrl', clk, rst, ctrl)
fsm = th.start()
uut = m.Instance(targ,
'uut',
params=m.connect_params(targ),
ports=m.connect_ports(targ))
# simulation.setup_waveform(m, uut)
simulation.setup_clock(m, clk, hperiod=5)
init = simulation.setup_reset(m,
resetn,
m.make_reset(),
period=100,
polarity='low')
init.add(
Delay(1000000),
Systask('finish'),
)
# output source code
if filename is not None:
m.to_verilog(filename)
# run simulation
sim = simulation.Simulator(m, sim=simtype)
rslt = sim.run(outputfile=outputfile)
lines = rslt.splitlines()
if simtype == 'verilator' and lines[-1].startswith('-'):
rslt = '\n'.join(lines[:-1])
return rslt
def run(act_shape=(1, 4, 4, 3),
weight0_shape=(9, 3, 3, 3),
weight1_shape=(9, 36),
act_dtype=ng.int32,
weight_dtype=ng.int32,
stride0=1,
padding0=0,
with_batchnorm0=False,
with_batchnorm1=False,
act_func0='ReLU',
act_func1='relu',
disable_fusion=False,
par_ich=1,
par_och=1,
par_col=1,
par_row=1,
concur_och=None,
stationary='filter',
chunk_size=64,
axi_datawidth=32,
silent=False,
filename=None,
simtype='iverilog',
outputfile=None):
# pytorch model
layers = []
layers.append(
nn.Conv2d(weight0_shape[3],
weight0_shape[0],
weight0_shape[1],
stride=stride0,
padding=padding0))
if with_batchnorm0:
layers.append(nn.BatchNorm2d(weight0_shape[0]))
if act_func0 is not None:
layers.append(getattr(nn, act_func0)())
class Transpose(nn.Module):
def __init__(self, perm):
super(Transpose, self).__init__()
self.perm = perm
def forward(self, input):
return input.permute(*self.perm)
layers.append(Transpose([0, 1, 3, 2]))
class Flatten(nn.Module):
def forward(self, input):
# return input.view(input.size(0), -1)
return torch.reshape(input, (input.size(0), -1))
layers.append(Flatten())
layers.append(nn.Linear(weight1_shape[1], weight1_shape[0]))
if with_batchnorm1:
layers.append(nn.BatchNorm2d(weight1_shape[0]))
if act_func1 is not None:
layers.append(getattr(nn, act_func1)())
model = nn.Sequential(*layers)
# Pytorch to ONNX
onnx_filename = 'onnx_matrix_conv2d_transpose_linear.onnx'
dummy_input = torch.randn(*act_shape).transpose(1, 3)
input_names = ['act']
output_names = ['out']
model.eval()
torch.onnx.export(model,
dummy_input,
onnx_filename,
input_names=input_names,
output_names=output_names)
# --------------------
# (1) Represent a DNN model as a dataflow by NNgen operators
# --------------------
# ONNX to NNgen
value_dtypes = {
'act': act_dtype,
'0.weight': weight_dtype,
'3.weight': weight_dtype,
'out': act_dtype
}
(outputs, placeholders, variables, constants,
operators) = ng.from_onnx(onnx_filename,
value_dtypes=value_dtypes,
default_placeholder_dtype=act_dtype,
default_variable_dtype=weight_dtype,
default_constant_dtype=weight_dtype,
default_operator_dtype=act_dtype,
default_scale_dtype=ng.int32,
default_bias_dtype=ng.int32,
disable_fusion=disable_fusion)
# --------------------
# (2) Assign quantized weights to the NNgen operators
# --------------------
if act_dtype.width > 8:
act_scale_factor = 128
else:
act_scale_factor = int(round(2**(act_dtype.width - 1) * 0.5))
input_scale_factors = {'act': act_scale_factor}
ng.quantize(outputs, input_scale_factors)
# --------------------
# (3) Assign hardware attributes
# --------------------
for op in operators.values():
if isinstance(op, ng.conv2d):
op.attribute(par_ich=par_ich,
par_och=par_och,
par_row=par_row,
par_col=par_col,
concur_och=concur_och)
# --------------------
# (4) Verify the DNN model behavior by executing the NNgen dataflow as a software
# --------------------
act = placeholders['act']
out = outputs['out']
# verification data
# random data
std = 0.2
mean = 0.5
img = np.random.normal(size=act.length).astype(np.float32).reshape(
act.shape)
img = img * std + mean
# execution on pytorch
model_input = img
if act.perm is not None:
model_input = np.transpose(model_input, act.reversed_perm)
model.eval()
model_out = model(torch.from_numpy(model_input)).detach().numpy()
if act.perm is not None and len(model_out.shape) == len(act.shape):
model_out = np.transpose(model_out, act.perm)
scaled_model_out = model_out * out.scale_factor
# software-based verification
vact = img * act_scale_factor
vact = np.clip(vact, -1.0 * (2**(act.dtype.width - 1) - 1),
1.0 * (2**(act.dtype.width - 1) - 1))
vact = np.round(vact).astype(np.int64)
eval_outs = ng.eval([out], act=vact)
vout = eval_outs[0]
mean_square_error = np.sum((vout - scaled_model_out)**2) / vout.size
corrcoef = np.corrcoef(model_out.reshape([-1]), vout.reshape([-1]))
# breakpoint()
# --------------------
# (5) Convert the NNgen dataflow to a hardware description (Verilog HDL and IP-XACT)
# --------------------
targ = ng.to_veriloggen([out],
'onnx_matrix_conv2d_transpose_linear',
silent=silent,
config={
'maxi_datawidth': axi_datawidth,
'chunk_size': chunk_size
})
# --------------------
# (6) Simulate the generated hardware by Veriloggen and Verilog simulator
# --------------------
if simtype is None:
sys.exit()
# to memory image
param_data = ng.export_ndarray([out], chunk_size)
param_bytes = len(param_data)
variable_addr = int(math.ceil(
(act.addr + act.memory_size) / chunk_size)) * chunk_size
check_addr = int(math.ceil(
(variable_addr + param_bytes) / chunk_size)) * chunk_size
tmp_addr = int(math.ceil(
(check_addr + out.memory_size) / chunk_size)) * chunk_size
memimg_datawidth = 32
mem = np.zeros([1024 * 1024 * 8 // (memimg_datawidth // 8)],
dtype=np.int64)
mem = mem + [100]
# placeholder
axi.set_memory(
mem, vact, memimg_datawidth, act_dtype.width, act.addr,
max(int(math.ceil(axi_datawidth / act_dtype.width)), par_ich))
# parameters (variable and constant)
axi.set_memory(mem, param_data, memimg_datawidth, 8, variable_addr)
# verification data
axi.set_memory(
mem, vout, memimg_datawidth, act_dtype.width, check_addr,
max(int(math.ceil(axi_datawidth / act_dtype.width)), par_och))
# test controller
m = Module('test')
params = m.copy_params(targ)
ports = m.copy_sim_ports(targ)
clk = ports['CLK']
resetn = ports['RESETN']
rst = m.Wire('RST')
rst.assign(Not(resetn))
# AXI memory model
if outputfile is None:
outputfile = os.path.splitext(os.path.basename(__file__))[0] + '.out'
memimg_name = 'memimg_' + outputfile
memory = axi.AxiMemoryModel(m,
'memory',
clk,
rst,
datawidth=axi_datawidth,
memimg=mem,
memimg_name=memimg_name,
memimg_datawidth=memimg_datawidth)
memory.connect(ports, 'maxi')
# AXI-Slave controller
_saxi = vthread.AXIMLite(m, '_saxi', clk, rst, noio=True)
_saxi.connect(ports, 'saxi')
# timer
time_counter = m.Reg('time_counter', 32, initval=0)
seq = Seq(m, 'seq', clk, rst)
seq(time_counter.inc())
def ctrl():
for i in range(100):
pass
ng.sim.set_global_addrs(_saxi, tmp_addr)
start_time = time_counter.value
ng.sim.start(_saxi)
print('# start')
ng.sim.wait(_saxi)
end_time = time_counter.value
print('# end')
print('# execution cycles: %d' % (end_time - start_time))
# verify
ok = True
for i in range(out.shape[0]):
for j in range(out.shape[1]):
orig = memory.read_word(i * out.aligned_shape[1] + j, out.addr,
act_dtype.width)
check = memory.read_word(i * out.aligned_shape[1] + j,
check_addr, act_dtype.width)
if vthread.verilog.NotEql(orig, check):
print('NG (', i, j, ') orig: ', orig, 'check: ', check)
ok = False
# else:
# print('OK (', i, j, ') orig: ', orig, 'check: ', check)
if ok:
print('# verify: PASSED')
else:
print('# verify: FAILED')
vthread.finish()
th = vthread.Thread(m, 'th_ctrl', clk, rst, ctrl)
fsm = th.start()
uut = m.Instance(targ,
'uut',
params=m.connect_params(targ),
ports=m.connect_ports(targ))
# simulation.setup_waveform(m, uut)
simulation.setup_clock(m, clk, hperiod=5)
init = simulation.setup_reset(m,
resetn,
m.make_reset(),
period=100,
polarity='low')
init.add(
Delay(10000000),
Systask('finish'),
)
# output source code
if filename is not None:
m.to_verilog(filename)
# run simulation
sim = simulation.Simulator(m, sim=simtype)
rslt = sim.run(outputfile=outputfile)
lines = rslt.splitlines()
if simtype == 'verilator' and lines[-1].startswith('-'):
rslt = '\n'.join(lines[:-1])
return rslt
def run(act_shape=(1, 7, 7, 15), weight_shape=(7, 3, 3, 15),
bias_shape=None, scale_shape=None,
act_dtype=ng.int32, weight_dtype=ng.int32,
bias_dtype=ng.int32, scale_dtype=ng.int32,
out_dtype=ng.int32,
conv2d_stride=(1, 1, 1, 1),
rshift_mul=None, rshift_sum=None, rshift_out=None,
act_func=None,
par_ich=1, par_och=1, par_col=1, par_row=1,
concur_och=None, stationary='filter',
input_ram_size=None, filter_ram_size=None,
bias_ram_size=None, scale_ram_size=None,
out_ram_size=None,
ksize=(1, 2, 2, 1), pool_stride=(1, 2, 2, 1), par=1,
axi_datawidth=32, silent=False,
filename=None, simtype='iverilog', outputfile=None):
# create target hardware
act = ng.placeholder(act_dtype, shape=act_shape, name='act')
weight = ng.variable(weight_dtype, shape=weight_shape, name='weight')
if bias_shape is not None:
bias = ng.variable(bias_dtype, bias_shape, name='bias')
else:
bias = None
if scale_shape is not None:
scale = ng.variable(scale_dtype, scale_shape, name='scale')
else:
scale = None
tmp = ng.conv2d(act, weight, conv2d_stride,
bias, scale,
rshift_mul, rshift_sum, rshift_out,
act_func, 'SAME',
out_dtype, ng.int32, ng.int32,
'conv2d',
par_ich, par_och, par_col, par_row,
concur_och, stationary,
input_ram_size, filter_ram_size,
bias_ram_size, scale_ram_size,
None, None, None,
out_ram_size)
out = ng.avg_pool(tmp, ksize=ksize,
strides=pool_stride,
sum_dtype=ng.int32, dtype=out_dtype, par=par)
targ = ng.to_veriloggen([out], 'matrix_conv2d_avg_pool', silent=silent,
config={'maxi_datawidth': axi_datawidth})
# verification data
vact = np.arange(act.length, dtype=np.int64).reshape(act.shape) % [16]
vweight = np.arange(weight.length,
dtype=np.int64).reshape(weight.shape) % [32] - [16]
if bias is not None:
vbias = np.arange(bias.length,
dtype=np.int64).reshape(bias.shape) % [4]
else:
vbias = None
if scale is not None:
vscale = np.arange(scale.length,
dtype=np.int64).reshape(scale.shape) % [6]
else:
vscale = None
eval_outs = ng.eval([out], act=vact, weight=vweight, bias=vbias, scale=vscale)
vout = eval_outs[0]
# to memory image
size_max = int(math.ceil(max(act.memory_size, weight.memory_size,
bias.memory_size if bias is not None else 0,
scale.memory_size if scale is not None else 0,
out.memory_size) / 4096)) * 4096
check_addr = max(act.addr, weight.addr,
bias.addr if bias is not None else -1,
scale.addr if scale is not None else -1,
out.addr) + size_max
size_check = size_max
tmp_addr = check_addr + size_check
memimg_datawidth = 32
mem = np.zeros([1024 * 1024 * 8 // (memimg_datawidth // 8)], dtype=np.int64)
mem = mem + [100]
axi.set_memory(mem, vact, memimg_datawidth,
act_dtype.width, act.addr,
max(int(math.ceil(axi_datawidth / act_dtype.width)), par_ich))
axi.set_memory(mem, vweight, memimg_datawidth,
weight_dtype.width, weight.addr,
max(int(math.ceil(axi_datawidth / weight_dtype.width)), par_ich))
if bias is not None:
axi.set_memory(mem, vbias, memimg_datawidth,
bias_dtype.width, bias.addr,
max(int(math.ceil(axi_datawidth / bias_dtype.width)), par_och))
if scale is not None:
axi.set_memory(mem, vscale, memimg_datawidth,
scale_dtype.width, scale.addr,
max(int(math.ceil(axi_datawidth / scale_dtype.width)), par_och))
axi.set_memory(mem, vout, memimg_datawidth,
out_dtype.width, check_addr,
max(int(math.ceil(axi_datawidth / out_dtype.width)), par))
# test controller
m = Module('test')
params = m.copy_params(targ)
ports = m.copy_sim_ports(targ)
clk = ports['CLK']
resetn = ports['RESETN']
rst = m.Wire('RST')
rst.assign(Not(resetn))
# AXI memory model
if outputfile is None:
outputfile = os.path.splitext(os.path.basename(__file__))[0] + '.out'
memimg_name = 'memimg_' + outputfile
memory = axi.AxiMemoryModel(m, 'memory', clk, rst,
datawidth=axi_datawidth,
memimg=mem, memimg_name=memimg_name,
memimg_datawidth=memimg_datawidth)
memory.connect(ports, 'maxi')
# AXI-Slave controller
_saxi = vthread.AXIMLite(m, '_saxi', clk, rst, noio=True)
_saxi.connect(ports, 'saxi')
# timer
time_counter = m.Reg('time_counter', 32, initval=0)
seq = Seq(m, 'seq', clk, rst)
seq(
time_counter.inc()
)
def ctrl():
for i in range(100):
pass
ng.sim.set_global_addrs(_saxi, tmp_addr)
start_time = time_counter.value
ng.sim.start(_saxi)
print('# start')
ng.sim.wait(_saxi)
end_time = time_counter.value
print('# end')
print('# execution cycles: %d' % (end_time - start_time))
# verify
ok = True
for bat in range(out.shape[0]):
for y in range(out.shape[1]):
for x in range(out.shape[2]):
for ch in range(out.shape[3]):
orig = memory.read_word(bat * out.aligned_shape[1] * out.aligned_shape[2] * out.aligned_shape[3]
+ y * out.aligned_shape[2] * out.aligned_shape[3]
+ x * out.aligned_shape[3] + ch,
out.addr, out_dtype.width)
check = memory.read_word(bat * out.aligned_shape[1] * out.aligned_shape[2] * out.aligned_shape[3]
+ y * out.aligned_shape[2] * out.aligned_shape[3]
+ x * out.aligned_shape[3] + ch,
check_addr, out_dtype.width)
if vthread.verilog.NotEql(orig, check):
print('NG (', bat, y, x, ch,
') orig: ', orig, ' check: ', check)
ok = False
# else:
# print('OK (', bat, y, x, ch,
# ') orig: ', orig, ' check: ', check)
if ok:
print('# verify: PASSED')
else:
print('# verify: FAILED')
vthread.finish()
th = vthread.Thread(m, 'th_ctrl', clk, rst, ctrl)
fsm = th.start()
uut = m.Instance(targ, 'uut',
params=m.connect_params(targ),
ports=m.connect_ports(targ))
# simulation.setup_waveform(m, uut)
simulation.setup_clock(m, clk, hperiod=5)
init = simulation.setup_reset(m, resetn, m.make_reset(), period=100, polarity='low')
init.add(
Delay(10000000),
Systask('finish'),
)
# output source code
if filename is not None:
m.to_verilog(filename)
# run simulation
sim = simulation.Simulator(m, sim=simtype)
rslt = sim.run(outputfile=outputfile)
lines = rslt.splitlines()
if simtype == 'verilator' and lines[-1].startswith('-'):
rslt = '\n'.join(lines[:-1])
return rslt
def run(act_shape=(1, 7, 7, 3),
act_dtype=ng.int32,
ksize=2, stride=2, padding=0,
par=1,
chunk_size=64,
axi_datawidth=32, silent=False,
filename=None, simtype='iverilog', outputfile=None):
# pytorch model
layers = []
layers.append(nn.AvgPool2d(ksize, stride=stride, padding=padding))
model = nn.Sequential(*layers)
# Pytorch to ONNX
onnx_filename = 'onnx_matrix_avg_pool.onnx'
dummy_input = torch.randn(*act_shape).transpose(1, 3)
input_names = ['act']
output_names = ['out']
torch.onnx.export(model, dummy_input, onnx_filename,
input_names=input_names, output_names=output_names)
# --------------------
# (1) Represent a DNN model as a dataflow by NNgen operators
# --------------------
# ONNX to NNgen
value_dtypes = {'act': act_dtype,
'out': act_dtype}
(outputs, placeholders, variables,
constants, operators) = ng.from_onnx(onnx_filename,
value_dtypes=value_dtypes,
default_placeholder_dtype=act_dtype,
default_variable_dtype=ng.int32,
default_constant_dtype=ng.int32,
default_operator_dtype=act_dtype,
default_scale_dtype=ng.int32,
default_bias_dtype=ng.int32,
disable_fusion=False)
# --------------------
# (2) Assign quantized weights to the NNgen operators
# --------------------
input_scale_factors = {'act': 1.0}
ng.quantize(outputs, input_scale_factors)
# --------------------
# (3) Assign hardware attributes
# --------------------
for op in operators.values():
if isinstance(op, ng.avg_pool):
op.attribute(par=par)
# --------------------
# (4) Verify the DNN model behavior by executing the NNgen dataflow as a software
# --------------------
act = placeholders['act']
out = outputs['out']
# verification data
if act_dtype.width > 4:
vact = np.arange(act.length, dtype=np.int64).reshape(act.shape) % [11] + [1]
else:
vact = np.arange(act.length, dtype=np.int64).reshape(act.shape) % [5] + [1]
eval_outs = ng.eval([out], act=vact)
vout = eval_outs[0]
# software-based verification
model_input = vact.astype(np.float32)
if act.perm is not None:
model_input = np.transpose(model_input, act.reversed_perm)
model.eval()
model_out = model(torch.from_numpy(model_input)).detach().numpy()
if act.perm is not None:
model_out = np.transpose(model_out, act.perm)
scaled_model_out = model_out * out.scale_factor
mean_square_error = np.sum((vout - scaled_model_out) ** 2) / vout.size
corrcoef = np.corrcoef(model_out.reshape([-1]), vout.reshape([-1]))
# breakpoint()
# --------------------
# (5) Convert the NNgen dataflow to a hardware description (Verilog HDL and IP-XACT)
# --------------------
targ = ng.to_veriloggen([out], 'onnx_matrix_avg_pool', silent=silent,
config={'maxi_datawidth': axi_datawidth,
'chunk_size': chunk_size})
# --------------------
# (6) Simulate the generated hardware by Veriloggen and Verilog simulator
# --------------------
if simtype is None:
sys.exit()
# to memory image
param_data = ng.export_ndarray([out])
param_bytes = len(param_data)
variable_addr = int(math.ceil((act.addr + act.memory_size) / chunk_size)) * chunk_size
check_addr = int(math.ceil((variable_addr + param_bytes) / chunk_size)) * chunk_size
tmp_addr = int(math.ceil((check_addr + out.memory_size) / chunk_size)) * chunk_size
memimg_datawidth = 32
mem = np.zeros([1024 * 1024 * 8 // (memimg_datawidth // 8)], dtype=np.int64)
mem = mem + [100]
# placeholder
axi.set_memory(mem, vact, memimg_datawidth,
act_dtype.width, act.addr,
max(int(math.ceil(axi_datawidth / act_dtype.width)), par))
# parameters (variable and constant)
axi.set_memory(mem, param_data, memimg_datawidth,
8, variable_addr)
# verification data
axi.set_memory(mem, vout, memimg_datawidth,
act_dtype.width, check_addr,
max(int(math.ceil(axi_datawidth / act_dtype.width)), par))
# test controller
m = Module('test')
params = m.copy_params(targ)
ports = m.copy_sim_ports(targ)
clk = ports['CLK']
resetn = ports['RESETN']
rst = m.Wire('RST')
rst.assign(Not(resetn))
# AXI memory model
if outputfile is None:
outputfile = os.path.splitext(os.path.basename(__file__))[0] + '.out'
memimg_name = 'memimg_' + outputfile
memory = axi.AxiMemoryModel(m, 'memory', clk, rst,
datawidth=axi_datawidth,
memimg=mem, memimg_name=memimg_name,
memimg_datawidth=memimg_datawidth)
memory.connect(ports, 'maxi')
# AXI-Slave controller
_saxi = vthread.AXIMLite(m, '_saxi', clk, rst, noio=True)
_saxi.connect(ports, 'saxi')
# timer
time_counter = m.Reg('time_counter', 32, initval=0)
seq = Seq(m, 'seq', clk, rst)
seq(
time_counter.inc()
)
def ctrl():
for i in range(100):
pass
ng.sim.set_global_addrs(_saxi, tmp_addr)
start_time = time_counter.value
ng.sim.start(_saxi)
print('# start')
ng.sim.wait(_saxi)
end_time = time_counter.value
print('# end')
print('# execution cycles: %d' % (end_time - start_time))
# verify
ok = True
for bat in range(out.shape[0]):
for y in range(out.shape[1]):
for x in range(out.shape[2]):
for ch in range(out.shape[3]):
orig = memory.read_word(
bat * out.aligned_shape[1] * out.aligned_shape[2] * out.aligned_shape[3] +
y * out.aligned_shape[2] * out.aligned_shape[3] +
x * out.aligned_shape[3] + ch,
out.addr, act_dtype.width)
check = memory.read_word(
bat * out.aligned_shape[1] * out.aligned_shape[2] * out.aligned_shape[3] +
y * out.aligned_shape[2] * out.aligned_shape[3] +
x * out.aligned_shape[3] + ch,
check_addr, act_dtype.width)
if vthread.verilog.NotEql(orig, check):
print('NG (', bat, y, x, ch,
') orig: ', orig, ' check: ', check)
ok = False
# else:
# print('OK (', bat, y, x, ch,
# ') orig: ', orig, ' check: ', check)
if ok:
print('# verify: PASSED')
else:
print('# verify: FAILED')
vthread.finish()
th = vthread.Thread(m, 'th_ctrl', clk, rst, ctrl)
fsm = th.start()
uut = m.Instance(targ, 'uut',
params=m.connect_params(targ),
ports=m.connect_ports(targ))
# simulation.setup_waveform(m, uut)
simulation.setup_clock(m, clk, hperiod=5)
init = simulation.setup_reset(m, resetn, m.make_reset(), period=100, polarity='low')
init.add(
Delay(10000000),
Systask('finish'),
)
# output source code
if filename is not None:
m.to_verilog(filename)
# run simulation
sim = simulation.Simulator(m, sim=simtype)
rslt = sim.run(outputfile=outputfile)
lines = rslt.splitlines()
if simtype == 'verilator' and lines[-1].startswith('-'):
rslt = '\n'.join(lines[:-1])
return rslt
def run(act_shape=(1, 7, 7, 15),
weight1_shape=(7, 3, 3, 15), bias1_shape=None, scale1_shape=None,
weight2_shape=(9, 3, 3, 7), bias2_shape=None, scale2_shape=None,
act_dtype=ng.int32,
weight1_dtype=ng.int32, bias1_dtype=ng.int32, scale1_dtype=ng.int32,
weight2_dtype=ng.int32, bias2_dtype=ng.int32, scale2_dtype=ng.int32,
tmp_dtype=ng.int32,
out_dtype=ng.int32,
stride1=(1, 1, 1, 1), stride2=(1, 1, 1, 1),
rshift_mul1=None, rshift_sum1=None, rshift_out1=None,
rshift_mul2=None, rshift_sum2=None, rshift_out2=None,
act_func1=None, act_func2=None,
par_ich1=1, par_och1=1, par_col1=1, par_row1=1,
concur_och1=None, stationary1='filter',
par_ich2=1, par_och2=1, par_col2=1, par_row2=1,
concur_och2=None, stationary2='filter',
input_ram_size1=None, filter_ram_size1=None,
bias_ram_size1=None, scale_ram_size1=None,
out_ram_size1=None,
input_ram_size2=None, filter_ram_size2=None,
bias_ram_size2=None, scale_ram_size2=None,
out_ram_size2=None,
chunk_size=64,
axi_datawidth=32, silent=False,
filename=None, simtype='iverilog', outputfile=None):
# create target hardware
act = ng.placeholder(act_dtype, shape=act_shape, name='act')
weight1 = ng.variable(weight1_dtype, shape=weight1_shape,
name='weight1')
if bias1_shape is not None:
bias1 = ng.variable(bias1_dtype, bias1_shape, name='bias1')
else:
bias1 = None
if scale1_shape is not None:
scale1 = ng.variable(scale1_dtype, scale1_shape, name='scale1')
else:
scale1 = None
weight2 = ng.variable(weight2_dtype, shape=weight2_shape,
name='weight2')
if bias2_shape is not None:
bias2 = ng.variable(bias2_dtype, bias2_shape, name='bias2')
else:
bias2 = None
if scale2_shape is not None:
scale2 = ng.variable(scale2_dtype, scale2_shape, name='scale2')
else:
scale2 = None
tmp = ng.conv2d(act, weight1, stride1,
bias1, scale1,
rshift_mul1, rshift_sum1, rshift_out1,
act_func1, 'SAME',
tmp_dtype, ng.int32, ng.int32,
'conv2d_1',
par_ich1, par_och1, par_col1, par_row1,
concur_och1, stationary1,
input_ram_size1, filter_ram_size1,
bias_ram_size1, scale_ram_size1,
None, None, None,
out_ram_size1)
out = ng.conv2d(tmp, weight2, stride2,
bias2, scale2,
rshift_mul2, rshift_sum2, rshift_out2,
act_func2, 'SAME',
out_dtype, ng.int32, ng.int32,
'conv2d_2',
par_ich2, par_och2, par_col2, par_row2,
concur_och2, stationary2,
input_ram_size2, filter_ram_size2,
bias_ram_size2, scale_ram_size2,
None, None, None,
out_ram_size2)
targ = ng.to_veriloggen([out], 'matrix_conv2d_conv2d_variable', silent=silent,
config={'maxi_datawidth': axi_datawidth,
'offchipram_chunk_bytes': chunk_size})
# verification data
vact = np.arange(act.length, dtype=np.int64).reshape(act.shape) % [16]
vweight1 = np.arange(weight1.length,
dtype=np.int64).reshape(weight1_shape) % [32] - [16]
if bias1 is not None:
vbias1 = np.arange(bias1.length,
dtype=np.int64).reshape(bias1.shape) % [16]
else:
vbias1 = None
if scale1 is not None:
vscale1 = np.arange(scale1.length,
dtype=np.int64).reshape(scale1.shape) % [8]
else:
vscale1 = None
vweight2 = np.arange(weight2.length,
dtype=np.int64).reshape(weight2_shape) % [32] - [16]
if bias2 is not None:
vbias2 = np.arange(bias2.length,
dtype=np.int64).reshape(bias2.shape) % [16]
else:
vbias2 = None
if scale2 is not None:
vscale2 = np.arange(scale2.length,
dtype=np.int64).reshape(scale2.shape) % [8]
else:
vscale2 = None
vtmp = ng.verify.conv2d(vact, vweight1, stride1,
vbias1, vscale1,
rshift_mul1, rshift_sum1, rshift_out1,
act_func1, 'SAME',
tmp_dtype, ng.int32, ng.int32,
'conv2d_1',
par_ich1, par_och1, par_col1, par_row1,
concur_och1, stationary1,
input_ram_size1, filter_ram_size1,
bias_ram_size1, scale_ram_size1,
None, None, None,
out_ram_size1,
False,
act_dtype, weight1_dtype)
vout = ng.verify.conv2d(vtmp, vweight2, stride2,
vbias2, vscale2,
rshift_mul2, rshift_sum2, rshift_out2,
act_func2, 'SAME',
out_dtype, ng.int32, ng.int32,
'conv2d_2',
par_ich2, par_och2, par_col2, par_row2,
concur_och2, stationary2,
input_ram_size2, filter_ram_size2,
bias_ram_size2, scale_ram_size2,
None, None, None,
out_ram_size2,
False,
tmp_dtype, weight2_dtype)
# to memory image
size_max = int(math.ceil(max(act.memory_size, weight1.memory_size,
bias1.memory_size if bias1 is not None else 0,
scale1.memory_size if scale1 is not None else 0,
weight2.memory_size,
bias2.memory_size if bias2 is not None else 0,
scale2.memory_size if scale2 is not None else 0,
out.memory_size) / chunk_size)) * chunk_size
# assign custom addresses
variable_addr = max(act.addr, out.addr) + size_max
weight1_addr = variable_addr
bias1_addr = weight1_addr + int(math.ceil(weight1.memory_size / chunk_size)) * chunk_size
scale1_addr = (bias1_addr + int(math.ceil(bias1.memory_size / chunk_size)) * chunk_size
if bias1 is not None else weight1_addr)
weight2_addr = (scale1_addr + int(math.ceil(scale1.memory_size / chunk_size)) * chunk_size
if scale1 is not None else bias1_addr)
bias2_addr = weight2_addr + int(math.ceil(weight2.memory_size / chunk_size)) * chunk_size
scale2_addr = (bias2_addr + int(math.ceil(bias2.memory_size / chunk_size)) * chunk_size
if bias2 is not None else weight2_addr)
check_addr = scale2_addr + size_max
size_check = size_max
tmp_addr = check_addr + size_check
memimg_datawidth = 32
mem = np.zeros([1024 * 1024 * 8 // memimg_datawidth], dtype=np.int64)
mem = mem + [100]
axi.set_memory(mem, vact, memimg_datawidth,
act_dtype.width, act.addr,
max(int(math.ceil(axi_datawidth / act_dtype.width)), par_ich1))
axi.set_memory(mem, vweight1, memimg_datawidth,
weight1_dtype.width, weight1_addr,
max(int(math.ceil(axi_datawidth / weight1_dtype.width)), par_ich1))
if bias1_shape is not None:
axi.set_memory(mem, vbias1, memimg_datawidth,
bias1_dtype.width, bias1_addr,
max(int(math.ceil(axi_datawidth / bias1_dtype.width)), par_och1))
if scale1_shape is not None:
axi.set_memory(mem, vscale1, memimg_datawidth,
scale1_dtype.width, scale1_addr,
max(int(math.ceil(axi_datawidth / scale1_dtype.width)), par_och1))
axi.set_memory(mem, vweight2, memimg_datawidth,
weight2_dtype.width, weight2_addr,
max(int(math.ceil(axi_datawidth / weight2_dtype.width)), par_ich2))
if bias2_shape is not None:
axi.set_memory(mem, vbias2, memimg_datawidth,
bias2_dtype.width, bias2_addr,
max(int(math.ceil(axi_datawidth / bias2_dtype.width)), par_och2))
if scale2_shape is not None:
axi.set_memory(mem, vscale2, memimg_datawidth,
scale2_dtype.width, scale2_addr,
max(int(math.ceil(axi_datawidth / scale2_dtype.width)), par_och2))
axi.set_memory(mem, vout, memimg_datawidth,
out_dtype.width, check_addr,
max(int(math.ceil(axi_datawidth / out_dtype.width)), par_och2))
# test controller
m = Module('test')
params = m.copy_params(targ)
ports = m.copy_sim_ports(targ)
clk = ports['CLK']
resetn = ports['RESETN']
rst = m.Wire('RST')
rst.assign(Not(resetn))
# AXI memory model
if outputfile is None:
outputfile = os.path.splitext(os.path.basename(__file__))[0] + '.out'
memimg_name = 'memimg_' + outputfile
memory = axi.AxiMemoryModel(m, 'memory', clk, rst,
datawidth=axi_datawidth,
memimg=mem, memimg_name=memimg_name,
memimg_datawidth=memimg_datawidth)
memory.connect(ports, 'maxi')
# AXI-Slave controller
_saxi = vthread.AXIMLite(m, '_saxi', clk, rst, noio=True)
_saxi.connect(ports, 'saxi')
# timer
time_counter = m.Reg('time_counter', 32, initval=0)
seq = Seq(m, 'seq', clk, rst)
seq(
time_counter.inc()
)
def ctrl():
for i in range(100):
pass
# set custom addresses
ng.sim.set_global_addrs(_saxi, tmp_addr, out.addr, act.addr, variable_addr)
start_time = time_counter.value
ng.sim.start(_saxi)
print('# start')
ng.sim.wait(_saxi)
end_time = time_counter.value
print('# end')
print('# execution cycles: %d' % (end_time - start_time))
# verify
ok = True
for bat in range(out.shape[0]):
for y in range(out.shape[1]):
for x in range(out.shape[2]):
for ch in range(out.shape[3]):
orig = memory.read_word(
bat * out.aligned_shape[1] * out.aligned_shape[2] * out.aligned_shape[3]
+ y * out.aligned_shape[2] * out.aligned_shape[3]
+ x * out.aligned_shape[3] + ch,
out.addr, out_dtype.width)
check = memory.read_word(
bat * out.aligned_shape[1] * out.aligned_shape[2] * out.aligned_shape[3]
+ y * out.aligned_shape[2] * out.aligned_shape[3]
+ x * out.aligned_shape[3] + ch,
check_addr, out_dtype.width)
if vthread.verilog.NotEql(orig, check):
print('NG (', bat, y, x, ch,
') orig: ', orig, ' check: ', check)
ok = False
# else:
# print('OK (', bat, y, x, ch,
# ') orig: ', orig, ' check: ', check)
if ok:
print('# verify: PASSED')
else:
print('# verify: FAILED')
vthread.finish()
th = vthread.Thread(m, 'th_ctrl', clk, rst, ctrl)
fsm = th.start()
uut = m.Instance(targ, 'uut',
params=m.connect_params(targ),
ports=m.connect_ports(targ))
# simulation.setup_waveform(m, uut)
simulation.setup_clock(m, clk, hperiod=5)
init = simulation.setup_reset(m, resetn, m.make_reset(), period=100, polarity='low')
init.add(
Delay(10000000),
Systask('finish'),
)
# output source code
if filename is not None:
m.to_verilog(filename)
# run simulation
sim = simulation.Simulator(m, sim=simtype)
rslt = sim.run(outputfile=outputfile)
lines = rslt.splitlines()
if simtype == 'verilator' and lines[-1].startswith('-'):
rslt = '\n'.join(lines[:-1])
return rslt
def run(a_shape=(7, 15),
b_shape=(7, 15),
a_dtype=ng.int32,
b_dtype=ng.int32,
c_dtype=ng.int32,
par=1,
axi_datawidth=32,
silent=False,
filename=None,
simtype='iverilog',
outputfile=None):
# model definition
model = MatrixAdd()
# Pytorch to ONNX
onnx_filename = 'onnx_matrix_add.onnx'
dummy_a = torch.randn(*a_shape)
dummy_b = torch.randn(*b_shape)
dummy_inputs = (dummy_a, dummy_b)
input_names = ['a', 'b']
output_names = ['c']
model.eval()
torch.onnx.export(model,
dummy_inputs,
onnx_filename,
input_names=input_names,
output_names=output_names)
# ONNX to NNgen
value_dtypes = {'a': a_dtype, 'b': b_dtype, 'c': c_dtype}
(outputs, placeholders, variables, constants,
operators) = ng.from_onnx(onnx_filename,
value_dtypes=value_dtypes,
default_placeholder_dtype=ng.int32,
default_variable_dtype=ng.int32,
default_constant_dtype=ng.int32,
default_operator_dtype=ng.int32,
default_scale_dtype=ng.int32,
default_bias_dtype=ng.int32,
disable_fusion=False)
# set attribute
for op in operators.values():
if isinstance(op, ng.add):
op.attribute(par=par)
# create target hardware
a = placeholders['a']
b = placeholders['b']
c = outputs['c']
targ = ng.to_veriloggen([c],
'onnx_matrix_add',
silent=silent,
config={'maxi_datawidth': axi_datawidth})
# verification data
va = np.arange(a.length, dtype=np.int64).reshape(a.shape) % [5]
vb = (np.arange(b.length, dtype=np.int64).reshape(b.shape) + [100]) % [6]
eval_outs = ng.eval([c], a=va, b=vb)
vc = eval_outs[0]
# exec on pytorch
model_a = va.astype(np.float32)
model_b = vb.astype(np.float32)
if a.perm is not None:
model_a = np.transpose(model_a, a.reversed_perm)
if b.perm is not None:
model_b = np.transpose(model_b, b.reversed_perm)
model.eval()
model_c = model(torch.from_numpy(model_a),
torch.from_numpy(model_b)).detach().numpy()
if a.perm is not None:
model_c = np.transpose(model_c, a.perm)
scaled_model_c = model_c * c.scale_factor
c_diff = vc - scaled_model_c
c_err = c_diff / (scaled_model_c + 0.00000001)
max_c_err = np.max(np.abs(c_err))
# if max_c_err > 0.1:
# raise ValueError("too large output error: %f > 0.1" % max_c_err)
# to memory image
param_data = ng.export_ndarray([c])
param_bytes = len(param_data)
variable_addr = int(
math.ceil(
max(a.addr + a.memory_size, b.addr + b.memory_size) / 4096)) * 4096
check_addr = int(math.ceil((variable_addr + param_bytes) / 4096)) * 4096
tmp_addr = int(math.ceil((check_addr + c.memory_size) / 4096)) * 4096
memimg_datawidth = 32
mem = np.zeros([1024 * 1024 * 8 // (memimg_datawidth // 8)],
dtype=np.int64)
mem = mem + [100]
# placeholder
axi.set_memory(mem, va, memimg_datawidth, a_dtype.width, a.addr,
max(int(math.ceil(axi_datawidth / a_dtype.width)), par))
axi.set_memory(mem, vb, memimg_datawidth, b_dtype.width, b.addr,
max(int(math.ceil(axi_datawidth / b_dtype.width)), par))
# parameters (variable and constant)
axi.set_memory(mem, param_data, memimg_datawidth, 8, variable_addr)
# verification data
axi.set_memory(mem, vc, memimg_datawidth, c_dtype.width, check_addr,
max(int(math.ceil(axi_datawidth / c_dtype.width)), par))
# test controller
m = Module('test')
params = m.copy_params(targ)
ports = m.copy_sim_ports(targ)
clk = ports['CLK']
resetn = ports['RESETN']
rst = m.Wire('RST')
rst.assign(Not(resetn))
# AXI memory model
if outputfile is None:
outputfile = os.path.splitext(os.path.basename(__file__))[0] + '.out'
memimg_name = 'memimg_' + outputfile
memory = axi.AxiMemoryModel(m,
'memory',
clk,
rst,
datawidth=axi_datawidth,
memimg=mem,
memimg_name=memimg_name,
memimg_datawidth=memimg_datawidth)
memory.connect(ports, 'maxi')
# AXI-Slave controller
_saxi = vthread.AXIMLite(m, '_saxi', clk, rst, noio=True)
_saxi.connect(ports, 'saxi')
# timer
time_counter = m.Reg('time_counter', 32, initval=0)
seq = Seq(m, 'seq', clk, rst)
seq(time_counter.inc())
num_rep = functools.reduce(lambda x, y: x * y, c.shape[:-1], 1)
def ctrl():
for i in range(100):
pass
ng.sim.set_global_addrs(_saxi, tmp_addr)
start_time = time_counter.value
ng.sim.start(_saxi)
print('# start')
ng.sim.wait(_saxi)
end_time = time_counter.value
print('# end')
print('# execution cycles: %d' % (end_time - start_time))
# verify
ok = True
for i in range(num_rep):
for j in range(c.shape[-1]):
orig = memory.read_word(i * c.aligned_shape[-1] + j, c.addr,
c_dtype.width)
check = memory.read_word(i * c.aligned_shape[-1] + j,
check_addr, c_dtype.width)
if vthread.verilog.NotEql(orig, check):
print('NG', i, j, orig, check)
ok = False
# else:
# print('OK', i, j, orig, check)
if ok:
print('# verify: PASSED')
else:
print('# verify: FAILED')
vthread.finish()
th = vthread.Thread(m, 'th_ctrl', clk, rst, ctrl)
fsm = th.start()
uut = m.Instance(targ,
'uut',
params=m.connect_params(targ),
ports=m.connect_ports(targ))
# simulation.setup_waveform(m, uut)
simulation.setup_clock(m, clk, hperiod=5)
init = simulation.setup_reset(m,
resetn,
m.make_reset(),
period=100,
polarity='low')
init.add(
Delay(1000000),
Systask('finish'),
)
# output source code
if filename is not None:
m.to_verilog(filename)
# run simulation
sim = simulation.Simulator(m, sim=simtype)
rslt = sim.run(outputfile=outputfile)
lines = rslt.splitlines()
if simtype == 'verilator' and lines[-1].startswith('-'):
rslt = '\n'.join(lines[:-1])
return rslt
def run(act_shape=(1, 7, 7, 3),
weight0_shape=(9, 3, 3, 3),
weight1_shape=(9, 3, 3, 9),
act_dtype=ng.int32,
weight_dtype=ng.int32,
out_dtype=ng.int32,
stride0=1,
stride1=1,
padding0=0,
padding1=0,
with_batchnorm0=False,
with_batchnorm1=False,
act_func0='relu',
act_func1='relu',
disable_fusion=False,
par_ich=1,
par_och=1,
par_col=1,
par_row=1,
concur_och=None,
stationary='filter',
chunk_size=64,
axi_datawidth=32,
silent=False,
filename=None,
simtype='iverilog',
outputfile=None):
# model definition
layers = []
layers.append(
nn.Conv2d(weight0_shape[3],
weight0_shape[0],
weight0_shape[1],
stride=stride0,
padding=padding0))
if with_batchnorm0:
layers.append(nn.BatchNorm2d(weight0_shape[0]))
if act_func0 == 'relu':
layers.append(nn.ReLU(inplace=True))
elif act_func0 == 'leaky_relu':
layers.append(nn.LeakyReLU(inplace=True))
layers.append(
nn.Conv2d(weight1_shape[3],
weight1_shape[0],
weight1_shape[1],
stride=stride1,
padding=padding1))
if with_batchnorm1:
layers.append(nn.BatchNorm2d(weight1_shape[0]))
if act_func1 == 'relu':
layers.append(nn.ReLU(inplace=True))
elif act_func1 == 'leaky_relu':
layers.append(nn.LeakyReLU(inplace=True))
model = nn.Sequential(*layers)
# Pytorch to ONNX
onnx_filename = 'onnx_matrix_conv2d_conv2d.onnx'
dummy_input = torch.randn(*act_shape).transpose(1, 3)
input_names = ['act']
output_names = ['out']
model.eval()
torch.onnx.export(model,
dummy_input,
onnx_filename,
input_names=input_names,
output_names=output_names)
# ONNX to NNgen
value_dtypes = {
'act': act_dtype,
'0.weight': weight_dtype,
'1.weight': weight_dtype,
'out': act_dtype
}
(outputs, placeholders, variables, constants,
operators) = ng.from_onnx(onnx_filename,
value_dtypes=value_dtypes,
default_placeholder_dtype=act_dtype,
default_variable_dtype=weight_dtype,
default_constant_dtype=weight_dtype,
default_operator_dtype=out_dtype,
default_scale_dtype=ng.int32,
default_bias_dtype=ng.int32,
disable_fusion=disable_fusion)
# default linear quantization
if act_dtype.width >= 8:
value_ranges = {'act': (-120, 120)}
else:
value_ranges = {
'act': (-(2**(act_dtype.width - 1)), (2**(act_dtype.width - 1)))
}
ng.quantize(outputs, value_ranges=value_ranges)
# set attribute
for op in operators.values():
if isinstance(op, ng.conv2d):
op.attribute(par_ich=par_ich,
par_och=par_och,
par_row=par_row,
par_col=par_col,
concur_och=concur_och)
# create target hardware
act = placeholders['act']
out = outputs['out']
targ = ng.to_veriloggen([out],
'onnx_matrix_conv2d_conv2d',
silent=silent,
config={
'maxi_datawidth': axi_datawidth,
'chunk_size': chunk_size
})
# verification data
# if act_dtype.width > 4:
# vact = np.arange(act.length, dtype=np.int64).reshape(act.shape) % [11] + [1]
# else:
# vact = np.arange(act.length, dtype=np.int64).reshape(act.shape) % [5] + [1]
#vact = np.ones(act.shape)
vact = np.random.normal(size=act.length).reshape(act.shape)
vact = np.clip(vact, -3.0, 3.0)
vact_min_val, vact_max_val = value_ranges['act']
vact_max_abs_range = max(abs(vact_min_val), abs(vact_max_val))
vact_width = vact_max_abs_range.bit_length() + 1
vact = vact * (1.0 * (2**(vact_width - 1) - 1)) / 3.0
vact = np.round(vact).astype(np.int64)
eval_outs = ng.eval([out], act=vact)
vout = eval_outs[0]
# exec on pytorch
model_input = vact.astype(np.float32)
if act.perm is not None:
model_input = np.transpose(model_input, act.reversed_perm)
model.eval()
model_out = model(torch.from_numpy(model_input)).detach().numpy()
if act.perm is not None:
model_out = np.transpose(model_out, act.perm)
scaled_model_out = model_out * out.scale_factor
out_diff = vout - scaled_model_out
out_err = out_diff / (scaled_model_out + 0.00000001)
max_out_err = np.max(np.abs(out_err))
# if max_out_err > 0.1:
# raise ValueError("too large output error: %f > 0.1" % max_out_err)
# to memory image
param_data = ng.make_param_array(variables, constants, chunk_size)
param_bytes = len(param_data)
variable_addr = int(math.ceil(
(act.addr + act.memory_size) / chunk_size)) * chunk_size
check_addr = int(math.ceil(
(variable_addr + param_bytes) / chunk_size)) * chunk_size
tmp_addr = int(math.ceil(
(check_addr + out.memory_size) / chunk_size)) * chunk_size
memimg_datawidth = 32
mem = np.zeros([1024 * 1024 * 8 // memimg_datawidth], dtype=np.int64)
mem = mem + [100]
# placeholder
axi.set_memory(
mem, vact, memimg_datawidth, act_dtype.width, act.addr,
max(int(math.ceil(axi_datawidth / act_dtype.width)), par_ich))
# parameters (variable and constant)
axi.set_memory(mem, param_data, memimg_datawidth, 8, variable_addr)
# verification data
axi.set_memory(
mem, vout, memimg_datawidth, out_dtype.width, check_addr,
max(int(math.ceil(axi_datawidth / out_dtype.width)), par_och))
# test controller
m = Module('test')
params = m.copy_params(targ)
ports = m.copy_sim_ports(targ)
clk = ports['CLK']
resetn = ports['RESETN']
rst = m.Wire('RST')
rst.assign(Not(resetn))
# AXI memory model
if outputfile is None:
outputfile = os.path.splitext(os.path.basename(__file__))[0] + '.out'
memimg_name = 'memimg_' + outputfile
memory = axi.AxiMemoryModel(m,
'memory',
clk,
rst,
datawidth=axi_datawidth,
memimg=mem,
memimg_name=memimg_name,
memimg_datawidth=memimg_datawidth)
memory.connect(ports, 'maxi')
# AXI-Slave controller
_saxi = vthread.AXIMLite(m, '_saxi', clk, rst, noio=True)
_saxi.connect(ports, 'saxi')
# timer
time_counter = m.Reg('time_counter', 32, initval=0)
seq = Seq(m, 'seq', clk, rst)
seq(time_counter.inc())
def ctrl():
for i in range(100):
pass
ng.sim.set_global_addrs(_saxi, tmp_addr)
start_time = time_counter.value
ng.sim.start(_saxi)
print('# start')
ng.sim.wait(_saxi)
end_time = time_counter.value
print('# end')
print('# execution cycles: %d' % (end_time - start_time))
# verify
ok = True
for bat in range(out.shape[0]):
for y in range(out.shape[1]):
for x in range(out.shape[2]):
for ch in range(out.shape[3]):
orig = memory.read_word(
bat * out.aligned_shape[1] * out.aligned_shape[2] *
out.aligned_shape[3] +
y * out.aligned_shape[2] * out.aligned_shape[3] +
x * out.aligned_shape[3] + ch, out.addr,
out_dtype.width)
check = memory.read_word(
bat * out.aligned_shape[1] * out.aligned_shape[2] *
out.aligned_shape[3] +
y * out.aligned_shape[2] * out.aligned_shape[3] +
x * out.aligned_shape[3] + ch, check_addr,
out_dtype.width)
if vthread.verilog.NotEql(orig, check):
print('NG (', bat, y, x, ch, ') orig: ', orig,
' check: ', check)
ok = False
# else:
# print('OK (', bat, y, x, ch,
# ') orig: ', orig, ' check: ', check)
if ok:
print('# verify: PASSED')
else:
print('# verify: FAILED')
vthread.finish()
th = vthread.Thread(m, 'th_ctrl', clk, rst, ctrl)
fsm = th.start()
uut = m.Instance(targ,
'uut',
params=m.connect_params(targ),
ports=m.connect_ports(targ))
# simulation.setup_waveform(m, uut)
simulation.setup_clock(m, clk, hperiod=5)
init = simulation.setup_reset(m,
resetn,
m.make_reset(),
period=100,
polarity='low')
init.add(
Delay(10000000),
Systask('finish'),
)
# output source code
if filename is not None:
m.to_verilog(filename)
# run simulation
sim = simulation.Simulator(m, sim=simtype)
rslt = sim.run(outputfile=outputfile)
lines = rslt.splitlines()
if simtype == 'verilator' and lines[-1].startswith('-'):
rslt = '\n'.join(lines[:-1])
return rslt
def run(act_shape=(1, 7, 7, 15),
act_dtype=ng.int32,
out_dtype=ng.int32,
factors=(1, 2, 2, 1),
par=1,
axi_datawidth=32,
silent=False,
filename=None,
simtype='iverilog',
outputfile=None):
# create target hardware
act = ng.placeholder(act_dtype, shape=act_shape, name='act')
out = ng.upsampling2d(act, factors=factors, dtype=out_dtype, par=par)
targ = ng.to_veriloggen([out],
'matrix_upsampling2d',
silent=silent,
config={'maxi_datawidth': axi_datawidth})
# verification data
vact = np.arange(act.length, dtype=np.int64).reshape(act.shape)
vout = ng.verify.upsampling2d(vact, factors=factors, dtype=out_dtype)
# to memory image
size_max = int(math.ceil(
max(act.memory_size, out.memory_size) / 4096)) * 4096
check_addr = max(act.addr, out.addr) + size_max
size_check = size_max
tmp_addr = check_addr + size_check
memimg_datawidth = 32
mem = np.zeros([1024 * 1024 * 8 // memimg_datawidth], dtype=np.int64)
mem = mem + [100]
axi.set_memory(mem, vact, memimg_datawidth, act_dtype.width, act.addr,
max(int(math.ceil(axi_datawidth / act_dtype.width)), par))
axi.set_memory(mem, vout, memimg_datawidth, out_dtype.width, check_addr,
max(int(math.ceil(axi_datawidth / out_dtype.width)), par))
# test controller
m = Module('test')
params = m.copy_params(targ)
ports = m.copy_sim_ports(targ)
clk = ports['CLK']
resetn = ports['RESETN']
rst = m.Wire('RST')
rst.assign(Not(resetn))
# AXI memory model
if outputfile is None:
outputfile = os.path.splitext(os.path.basename(__file__))[0] + '.out'
memimg_name = 'memimg_' + outputfile
memory = axi.AxiMemoryModel(m,
'memory',
clk,
rst,
datawidth=axi_datawidth,
memimg=mem,
memimg_name=memimg_name,
memimg_datawidth=memimg_datawidth)
memory.connect(ports, 'maxi')
# AXI-Slave controller
_saxi = vthread.AXIMLite(m, '_saxi', clk, rst, noio=True)
_saxi.connect(ports, 'saxi')
# timer
time_counter = m.Reg('time_counter', 32, initval=0)
seq = Seq(m, 'seq', clk, rst)
seq(time_counter.inc())
def ctrl():
for i in range(100):
pass
ng.sim.set_global_addrs(_saxi, tmp_addr)
start_time = time_counter.value
ng.sim.start(_saxi)
print('# start')
ng.sim.wait(_saxi)
end_time = time_counter.value
print('# end')
print('# execution cycles: %d' % (end_time - start_time))
# verify
ok = True
for bat in range(out.shape[0]):
for y in range(out.shape[1]):
for x in range(out.shape[2]):
for ch in range(out.shape[3]):
orig = memory.read_word(
bat * out.aligned_shape[1] * out.aligned_shape[2] *
out.aligned_shape[3] +
y * out.aligned_shape[2] * out.aligned_shape[3] +
x * out.aligned_shape[3] + ch, out.addr,
out_dtype.width)
check = memory.read_word(
bat * out.aligned_shape[1] * out.aligned_shape[2] *
out.aligned_shape[3] +
y * out.aligned_shape[2] * out.aligned_shape[3] +
x * out.aligned_shape[3] + ch, check_addr,
out_dtype.width)
if vthread.verilog.NotEql(orig, check):
print('NG (', bat, y, x, ch, ') orig: ', orig,
' check: ', check)
ok = False
# else:
# print('OK (', bat, y, x, ch,
# ') orig: ', orig, ' check: ', check)
if ok:
print('# verify: PASSED')
else:
print('# verify: FAILED')
vthread.finish()
th = vthread.Thread(m, 'th_ctrl', clk, rst, ctrl)
fsm = th.start()
uut = m.Instance(targ,
'uut',
params=m.connect_params(targ),
ports=m.connect_ports(targ))
# simulation.setup_waveform(m, uut)
simulation.setup_clock(m, clk, hperiod=5)
init = simulation.setup_reset(m,
resetn,
m.make_reset(),
period=100,
polarity='low')
init.add(
Delay(1000000),
Systask('finish'),
)
# output source code
if filename is not None:
m.to_verilog(filename)
# run simulation
sim = simulation.Simulator(m, sim=simtype)
rslt = sim.run(outputfile=outputfile)
lines = rslt.splitlines()
if simtype == 'verilator' and lines[-1].startswith('-'):
rslt = '\n'.join(lines[:-1])
return rslt
def run(act_shape=(1, 32, 32, 3),
act_dtype=ng.int32, weight_dtype=ng.int32,
bias_dtype=ng.int32, scale_dtype=ng.int32,
out_dtype=ng.int32,
with_batchnorm=True, disable_fusion=False,
conv2d_par_ich=1, conv2d_par_och=1, conv2d_par_col=1, conv2d_par_row=1,
conv2d_concur_och=None, conv2d_stationary='filter',
pool_par=1, elem_par=1,
chunk_size=64,
axi_datawidth=32, silent=False,
filename=None, simtype='iverilog', outputfile=None):
if not with_batchnorm:
raise ValueError('with_batchnorm must be True for ResNet18.')
# pytorch model
model = torchvision.models.resnet18(pretrained=False)
model.conv1.in_channels = act_shape[-1]
model.fc = nn.Linear(in_features=model.fc.in_features,
out_features=10, bias=True)
# Pytorch to ONNX
onnx_filename = 'resnet18.onnx'
dummy_input = torch.randn(*act_shape).transpose(1, 3)
input_names = ['act']
output_names = ['out']
model.eval()
torch.onnx.export(model, dummy_input, onnx_filename,
input_names=input_names, output_names=output_names)
# ONNX to NNgen
dtypes = {}
(outputs, placeholders, variables,
constants, operators) = ng.from_onnx(onnx_filename,
value_dtypes=dtypes,
default_placeholder_dtype=act_dtype,
default_variable_dtype=weight_dtype,
default_constant_dtype=weight_dtype,
default_operator_dtype=out_dtype,
default_scale_dtype=scale_dtype,
default_bias_dtype=bias_dtype,
disable_fusion=disable_fusion)
# default linear quantization
value_ranges = {'act': (0, 255)}
ng.quantize(outputs, value_ranges=value_ranges)
# set attribute
for op in operators.values():
if isinstance(op, ng.conv2d):
op.attribute(par_ich=conv2d_par_ich,
par_och=conv2d_par_och,
par_col=conv2d_par_col,
par_row=conv2d_par_row,
concur_och=conv2d_concur_och,
stationary=conv2d_stationary)
if isinstance(op, (ng.avg_pool, ng.max_pool,
ng.avg_pool_serial, ng.max_pool_serial)):
op.attribute(par=pool_par)
if ng.is_elementwise_operator(op):
op.attribute(par=elem_par)
# create target hardware
act = placeholders['act']
out = outputs['out']
targ = ng.to_veriloggen([out], 'onnx_resnet18', silent=silent,
config={'maxi_datawidth': axi_datawidth})
# verification data
vact = np.random.normal(size=act.length).reshape(act.shape)
vact = np.clip(vact, -3.0, 3.0)
vact_min_val, vact_max_val = value_ranges['act']
vact_max_abs_range = max(abs(vact_min_val), abs(vact_max_val))
vact_width = vact_max_abs_range.bit_length() + 1
vact = vact * (1.0 * (2 ** (vact_width - 1) - 1)) / 3.0
vact = np.round(vact).astype(np.int64)
eval_outs = ng.eval([out], act=vact)
vout = eval_outs[0]
# exec on pytorch
model_input = vact.astype(np.float32)
if act.perm is not None:
model_input = np.transpose(model_input, act.reversed_perm)
model.eval()
model_out = model(torch.from_numpy(model_input)).detach().numpy()
if act.perm is not None and len(model_out.shape) == len(act.shape):
model_out = np.transpose(model_out, act.perm)
scaled_model_out = model_out * out.scale_factor
mout = scaled_model_out.astype(np.int64)
for bat in range(vout.shape[0]):
vout_max = np.max(vout[bat])
vout_max_index = list(vout[bat]).index(vout_max)
mout_max = np.max(mout[bat])
mout_max_index = list(mout[bat]).index(mout_max)
print("# vout[%d]: max = %d, index = %d" % (bat, vout_max, vout_max_index))
print("# mout[%d]: max = %d, index = %d" % (bat, mout_max, mout_max_index))
# out_diff = vout - scaled_model_out
# out_err = out_diff / (scaled_model_out + 0.00000001)
# max_out_err = np.max(np.abs(out_err))
# breakpoint()
# if max_out_err > 0.1:
# raise ValueError("too large output error: %f > 0.1" % max_out_err)
# to memory image
param_data = ng.make_param_array(variables, constants, chunk_size)
param_bytes = len(param_data)
variable_addr = int(math.ceil((act.addr + act.memory_size) / chunk_size)) * chunk_size
check_addr = int(math.ceil((variable_addr + param_bytes) / chunk_size)) * chunk_size
tmp_addr = int(math.ceil((check_addr + out.memory_size) / chunk_size)) * chunk_size
memimg_datawidth = 32
mem = np.zeros([1024 * 1024 * 256 // memimg_datawidth], dtype=np.int64)
mem = mem + [100]
# placeholder
axi.set_memory(mem, vact, memimg_datawidth,
act_dtype.width, act.addr,
max(int(math.ceil(axi_datawidth / act_dtype.width)), conv2d_par_ich))
# parameters (variable and constant)
axi.set_memory(mem, param_data, memimg_datawidth,
8, variable_addr)
# verification data
axi.set_memory(mem, vout, memimg_datawidth,
act_dtype.width, check_addr,
max(int(math.ceil(axi_datawidth / act_dtype.width)), conv2d_par_och))
# test controller
m = Module('test')
params = m.copy_params(targ)
ports = m.copy_sim_ports(targ)
clk = ports['CLK']
resetn = ports['RESETN']
rst = m.Wire('RST')
rst.assign(Not(resetn))
# AXI memory model
if outputfile is None:
outputfile = os.path.splitext(os.path.basename(__file__))[0] + '.out'
memimg_name = 'memimg_' + outputfile
memory = axi.AxiMemoryModel(m, 'memory', clk, rst,
datawidth=axi_datawidth,
memimg=mem, memimg_name=memimg_name,
memimg_datawidth=memimg_datawidth)
memory.connect(ports, 'maxi')
# AXI-Slave controller
_saxi = vthread.AXIMLite(m, '_saxi', clk, rst, noio=True)
_saxi.connect(ports, 'saxi')
# timer
time_counter = m.Reg('time_counter', 32, initval=0)
seq = Seq(m, 'seq', clk, rst)
seq(
time_counter.inc()
)
def ctrl():
for i in range(100):
pass
ng.sim.set_global_addrs(_saxi, tmp_addr)
start_time = time_counter.value
ng.sim.start(_saxi)
print('# start')
ng.sim.wait(_saxi)
end_time = time_counter.value
print('# end')
print('# execution cycles: %d' % (end_time - start_time))
# verify
ok = True
for bat in range(out.shape[0]):
for y in range(out.shape[1]):
for x in range(out.shape[2]):
for ch in range(out.shape[3]):
orig = memory.read_word(
bat * out.aligned_shape[1] * out.aligned_shape[2] * out.aligned_shape[3] +
y * out.aligned_shape[2] * out.aligned_shape[3] +
x * out.aligned_shape[3] + ch,
out.addr, out_dtype.width)
check = memory.read_word(
bat * out.aligned_shape[1] * out.aligned_shape[2] * out.aligned_shape[3] +
y * out.aligned_shape[2] * out.aligned_shape[3] +
x * out.aligned_shape[3] + ch,
check_addr, out_dtype.width)
if vthread.verilog.NotEql(orig, check):
print('NG (', bat, y, x, ch,
') orig: ', orig, ' check: ', check)
ok = False
# else:
# print('OK (', bat, y, x, ch,
# ') orig: ', orig, ' check: ', check)
if ok:
print('# verify: PASSED')
else:
print('# verify: FAILED')
vthread.finish()
th = vthread.Thread(m, 'th_ctrl', clk, rst, ctrl)
fsm = th.start()
uut = m.Instance(targ, 'uut',
params=m.connect_params(targ),
ports=m.connect_ports(targ))
# simulation.setup_waveform(m, uut)
simulation.setup_clock(m, clk, hperiod=5)
init = simulation.setup_reset(m, resetn, m.make_reset(), period=100, polarity='low')
init.add(
Delay(10000000),
Systask('finish'),
)
# output source code
if filename is not None:
m.to_verilog(filename)
# run simulation
sim = simulation.Simulator(m, sim=simtype)
rslt = sim.run(outputfile=outputfile)
lines = rslt.splitlines()
if simtype == 'verilator' and lines[-1].startswith('-'):
rslt = '\n'.join(lines[:-1])
return rslt
def run(a_shape=(15, 15),
b_shape=(15, 15),
bias_shape=None,
scale_shape=None,
a_dtype=ng.int32,
b_dtype=ng.int32,
bias_dtype=ng.int32,
scale_dtype=ng.int32,
c_dtype=ng.int32,
rshift_mul=None,
rshift_sum=None,
rshift_out=None,
act_func=None,
par_left_col=1,
par_left_row=1,
par_out_col=1,
concur_out_col=None,
stationary='right',
left_ram_size=None,
right_ram_size=None,
bias_ram_size=None,
scale_ram_size=None,
out_ram_size=None,
axi_datawidth=32,
silent=False,
filename=None,
simtype='iverilog',
outputfile=None):
# create target hardware
a = ng.placeholder(a_dtype, shape=a_shape, name='a')
b = ng.placeholder(b_dtype, shape=b_shape, name='b')
if bias_shape is not None:
bias = ng.placeholder(bias_dtype, bias_shape, name='bias')
else:
bias = None
if scale_shape is not None:
scale = ng.placeholder(scale_dtype, scale_shape, name='scale')
else:
scale = None
transposed_a = False
transposed_b = True
c = ng.matmul(a, b, bias, scale, transposed_a, transposed_b, rshift_mul,
rshift_sum, rshift_out, act_func, c_dtype, ng.int32,
ng.int32, 'matmul', par_left_col, par_left_row, par_out_col,
concur_out_col, stationary, left_ram_size, right_ram_size,
bias_ram_size, scale_ram_size, None, None, None,
out_ram_size)
targ = ng.to_veriloggen([c],
'matrix_matmul',
silent=silent,
config={'maxi_datawidth': axi_datawidth})
# verification data
va = np.arange(a.length, dtype=np.int64).reshape(a.shape) % [5]
vb = np.arange(b.length, dtype=np.int64).reshape(b.shape) % [5] - [3]
if bias is not None:
vbias = np.arange(bias.length, dtype=np.int64).reshape(
bias.shape) % [4]
else:
vbias = None
if scale is not None:
vscale = np.arange(scale.length, dtype=np.int64).reshape(
scale.shape) % [6]
else:
vscale = None
vc = ng.verify.matmul(va, vb, bias, scale, False, True, rshift_mul,
rshift_sum, rshift_out, act_func, c_dtype, ng.int32,
ng.int32, 'matmul', par_left_col, par_left_row,
par_out_col, concur_out_col, stationary,
left_ram_size, right_ram_size, bias_ram_size,
scale_ram_size, None, None, None, out_ram_size,
False, a_dtype, b_dtype, bias_dtype, scale_dtype)
# to memory image
size_max = int(
math.ceil(
max(a.memory_size, b.memory_size,
bias.memory_size if bias is not None else 0, scale.memory_size
if scale is not None else 0, c.memory_size) / 4096)) * 4096
check_addr = max(a.addr, b.addr, bias.addr if bias is not None else -1,
scale.addr if scale is not None else -1,
c.addr) + size_max
size_check = size_max
tmp_addr = check_addr + size_check
memimg_datawidth = 32
mem = np.zeros([1024 * 1024 * 8 // memimg_datawidth], dtype=np.int64)
mem = mem + [100]
axi.set_memory(
mem, va, memimg_datawidth, a_dtype.width, a.addr,
max(int(math.ceil(axi_datawidth / a_dtype.width)), par_left_col))
axi.set_memory(
mem, vb, memimg_datawidth, b_dtype.width, b.addr,
max(int(math.ceil(axi_datawidth / b_dtype.width)), par_left_col))
if bias is not None:
axi.set_memory(
mem, vbias, memimg_datawidth, bias_dtype.width, bias.addr,
max(int(math.ceil(axi_datawidth / bias_dtype.width)), par_out_col))
if scale is not None:
axi.set_memory(
mem, vscale, memimg_datawidth, scale_dtype.width, scale.addr,
max(int(math.ceil(axi_datawidth / scale_dtype.width)),
par_out_col))
axi.set_memory(
mem, vc, memimg_datawidth, c_dtype.width, check_addr,
max(int(math.ceil(axi_datawidth / c_dtype.width)), par_out_col))
# test controller
m = Module('test')
params = m.copy_params(targ)
ports = m.copy_sim_ports(targ)
clk = ports['CLK']
resetn = ports['RESETN']
rst = m.Wire('RST')
rst.assign(Not(resetn))
# AXI memory model
if outputfile is None:
outputfile = os.path.splitext(os.path.basename(__file__))[0] + '.out'
memimg_name = 'memimg_' + outputfile
memory = axi.AxiMemoryModel(m,
'memory',
clk,
rst,
datawidth=axi_datawidth,
memimg=mem,
memimg_name=memimg_name,
memimg_datawidth=memimg_datawidth)
memory.connect(ports, 'maxi')
# AXI-Slave controller
_saxi = vthread.AXIMLite(m, '_saxi', clk, rst, noio=True)
_saxi.connect(ports, 'saxi')
# timer
time_counter = m.Reg('time_counter', 32, initval=0)
seq = Seq(m, 'seq', clk, rst)
seq(time_counter.inc())
def ctrl():
for i in range(100):
pass
ng.sim.set_global_addrs(_saxi, tmp_addr)
start_time = time_counter.value
ng.sim.start(_saxi)
print('# start')
ng.sim.wait(_saxi)
end_time = time_counter.value
print('# end')
print('# execution cycles: %d' % (end_time - start_time))
# verify
ok = True
for i in range(c.shape[0]):
for j in range(c.shape[1]):
orig = memory.read_word(i * c.aligned_shape[1] + j, c.addr,
c_dtype.width)
check = memory.read_word(i * c.aligned_shape[1] + j,
check_addr, c_dtype.width)
if vthread.verilog.NotEql(orig, check):
print(i, j, orig, check)
ok = False
if ok:
print('# verify: PASSED')
else:
print('# verify: FAILED')
vthread.finish()
th = vthread.Thread(m, 'th_ctrl', clk, rst, ctrl)
fsm = th.start()
uut = m.Instance(targ,
'uut',
params=m.connect_params(targ),
ports=m.connect_ports(targ))
# simulation.setup_waveform(m, uut)
simulation.setup_clock(m, clk, hperiod=5)
init = simulation.setup_reset(m,
resetn,
m.make_reset(),
period=100,
polarity='low')
init.add(
Delay(1000000),
Systask('finish'),
)
# output source code
if filename is not None:
m.to_verilog(filename)
# run simulation
sim = simulation.Simulator(m, sim=simtype)
rslt = sim.run(outputfile=outputfile)
lines = rslt.splitlines()
if simtype == 'verilator' and lines[-1].startswith('-'):
rslt = '\n'.join(lines[:-1])
return rslt
def run(a_shape=(15, 15),
b_shape=(15, 15),
a_dtype=ng.int32,
b_dtype=ng.int32,
c_dtype=ng.int32,
par=1,
axi_datawidth=32,
interrupt_name='irq',
silent=False,
filename=None,
simtype='iverilog',
outputfile=None):
# create target hardware
a = ng.placeholder(a_dtype, shape=a_shape, name='a')
b = ng.placeholder(b_dtype, shape=b_shape, name='b')
d = ng.add(a, b, dtype=c_dtype, par=par)
e = ng.add(b, a, dtype=c_dtype, par=par)
# SW returns ng.add(x, y)
f = ng.extern([d, e], shape=a_shape, opcode=0x1, func=lambda x, y: x + y)
g = ng.sub(f, a)
# SW returns d as-is
h = ng.extern([g], shape=a_shape, opcode=0x2, func=lambda x: x)
c = ng.sub(h, b)
targ = ng.to_veriloggen([c],
'matrix_extern',
silent=silent,
config={
'maxi_datawidth': axi_datawidth,
'interrupt_name': interrupt_name
})
# verification data
va = np.arange(a.length, dtype=np.int64).reshape(a.shape) % [16]
vb = np.arange(b.length, dtype=np.int64).reshape(b.shape) % [32] + [16]
eval_outs = ng.eval([c], a=va, b=vb)
vc = eval_outs[0]
# to memory image
size_max = int(
math.ceil(
max(a.memory_size, b.memory_size, c.memory_size) / 4096)) * 4096
check_addr = max(a.addr, b.addr, c.addr) + size_max
size_check = size_max
tmp_addr = check_addr + size_check
memimg_datawidth = 32
mem = np.zeros([1024 * 1024 * 8 // (memimg_datawidth // 8)],
dtype=np.int64)
mem = mem + [100]
axi.set_memory(mem, va, memimg_datawidth, a_dtype.width, a.addr,
max(int(math.ceil(axi_datawidth / a_dtype.width)), par))
axi.set_memory(mem, vb, memimg_datawidth, b_dtype.width, b.addr,
max(int(math.ceil(axi_datawidth / b_dtype.width)), par))
axi.set_memory(mem, vc, memimg_datawidth, c_dtype.width, check_addr,
max(int(math.ceil(axi_datawidth / c_dtype.width)), par))
# test controller
m = Module('test')
params = m.copy_params(targ)
ports = m.copy_sim_ports(targ)
clk = ports['CLK']
resetn = ports['RESETN']
irq = ports[interrupt_name]
rst = m.Wire('RST')
rst.assign(Not(resetn))
# AXI memory model
if outputfile is None:
outputfile = os.path.splitext(os.path.basename(__file__))[0] + '.out'
memimg_name = 'memimg_' + outputfile
memory = axi.AxiMemoryModel(m,
'memory',
clk,
rst,
datawidth=axi_datawidth,
memimg_datawidth=memimg_datawidth,
memimg=mem,
memimg_name=memimg_name)
memory.connect(ports, 'maxi')
# AXI-Slave controller
_saxi = vthread.AXIMLite(m, '_saxi', clk, rst, noio=True)
_saxi.connect(ports, 'saxi')
# timer
time_counter = m.Reg('time_counter', 32, initval=0)
seq = Seq(m, 'seq', clk, rst)
seq(time_counter.inc())
num_rep = functools.reduce(lambda x, y: x * y, c.shape[:-1], 1)
def irq_join(saxi, irq_bit):
while irq == 0:
pass
araddr = ng.control_reg_interrupt_isr * 4
irq_stat = saxi.read(araddr)
if irq_stat != irq_bit:
print('# Unexpected irq signal: %d' % irq_stat)
print('# verify: FAILED')
vthread.finish()
print('# irq stat = %d' % irq_stat)
awaddr = ng.control_reg_interrupt_iar * 4
saxi.write(awaddr, irq_bit)
def ctrl():
for i in range(100):
pass
ng.sim.set_global_addrs(_saxi, tmp_addr)
araddr_ext_snd = ng.control_reg_extern_send * 4
awaddr_ext_rcv = ng.control_reg_extern_recv * 4
awaddr_irq_ier = ng.control_reg_interrupt_ier * 4
araddr_irq_isr = ng.control_reg_interrupt_isr * 4
awaddr_irq_iar = ng.control_reg_interrupt_iar * 4
_saxi.write(awaddr_irq_ier, 3) # irq enable
ng.sim.sw_rst(_saxi)
print('# 0st software reset (during idle)')
for i in range(100):
pass
irq_stat = _saxi.read(araddr_irq_isr)
if irq_stat != 0:
print('# Unexpected irq signal: %d' % irq_stat)
print('# verify: FAILED')
vthread.finish()
print('# irq stat = %d' %
irq_stat) # no irq busy by software reset when idle
start_time = time_counter.value
ng.sim.start(_saxi)
print('# 1st test start')
# from extern-send
irq_join(_saxi, 2)
v = _saxi.read(araddr_ext_snd)
print('# opcode = %d' % v)
for i in range(num_rep):
for j in range(c.shape[-1]):
x_offset = tmp_addr - d.default_global_addr
y_offset = tmp_addr - e.default_global_addr
z_offset = tmp_addr - f.default_global_addr
x = memory.read_word(i * c.aligned_shape[-1] + j,
d.addr + x_offset, c_dtype.width)
y = memory.read_word(i * c.aligned_shape[-1] + j,
e.addr + y_offset, c_dtype.width)
z = x + y
memory.write_word(i * c.aligned_shape[-1] + j,
f.addr + z_offset, z, c_dtype.width)
# to extern-recv
_saxi.write(awaddr_ext_rcv, 1)
# from extern-send
irq_join(_saxi, 2)
v = _saxi.read(araddr_ext_snd)
print('# opcode = %d' % v)
# software reset
ng.sim.sw_rst(_saxi)
print('# 1st software reset (before resume)')
# from extern-send
irq_join(_saxi, 1)
# restart
ng.sim.start(_saxi)
print('# Restart')
# from extern-send
irq_join(_saxi, 2)
v = _saxi.read(araddr_ext_snd)
print('# opcode = %d' % v)
for i in range(num_rep):
for j in range(c.shape[-1]):
x_offset = tmp_addr - d.default_global_addr
y_offset = tmp_addr - e.default_global_addr
z_offset = tmp_addr - f.default_global_addr
x = memory.read_word(i * c.aligned_shape[-1] + j,
d.addr + x_offset, c_dtype.width)
y = memory.read_word(i * c.aligned_shape[-1] + j,
e.addr + y_offset, c_dtype.width)
z = x + y
memory.write_word(i * c.aligned_shape[-1] + j,
f.addr + z_offset, z, c_dtype.width)
# to extern-recv
_saxi.write(awaddr_ext_rcv, 1)
# from extern-send
irq_join(_saxi, 2)
v = _saxi.read(araddr_ext_snd)
print('# opcode = %d' % v)
for i in range(num_rep):
for j in range(c.shape[-1]):
x_offset = tmp_addr - g.default_global_addr
z_offset = tmp_addr - h.default_global_addr
x = memory.read_word(i * c.aligned_shape[-1] + j,
g.addr + x_offset, c_dtype.width)
z = x
memory.write_word(i * c.aligned_shape[-1] + j,
h.addr + z_offset, z, c_dtype.width)
# to extern-recv
_saxi.write(awaddr_ext_rcv, 1)
# from extern-send
irq_join(_saxi, 1)
#ng.sim.wait(_saxi)
end_time = time_counter.value
print('# end')
print('# execution cycles: %d' % (end_time - start_time))
# verify
ok_1st = True
for i in range(num_rep):
for j in range(c.shape[-1]):
orig = memory.read_word(i * c.aligned_shape[-1] + j, c.addr,
c_dtype.width)
check = memory.read_word(i * c.aligned_shape[-1] + j,
check_addr, c_dtype.width)
if vthread.verilog.NotEql(orig, check):
print('NG', i, j, orig, check)
ok_1st = False
# else:
# print('OK', i, j, orig, check)
# 2nd test
# start
start_time = time_counter.value
ng.sim.start(_saxi)
print('# 2nd test start')
# from extern-send
irq_join(_saxi, 2)
v = _saxi.read(araddr_ext_snd)
print('# opcode = %d' % v)
for i in range(num_rep):
for j in range(c.shape[-1]):
x_offset = tmp_addr - d.default_global_addr
y_offset = tmp_addr - e.default_global_addr
z_offset = tmp_addr - f.default_global_addr
x = memory.read_word(i * c.aligned_shape[-1] + j,
d.addr + x_offset, c_dtype.width)
y = memory.read_word(i * c.aligned_shape[-1] + j,
e.addr + y_offset, c_dtype.width)
z = x + y
memory.write_word(i * c.aligned_shape[-1] + j,
f.addr + z_offset, z, c_dtype.width)
# to extern-recv
_saxi.write(awaddr_ext_rcv, 1)
while (memory.waddr.awvalid) == 0:
pass
ng.sim.sw_rst(_saxi)
print('# 2nd software reset (during Master AXI transaction)')
irq_join(_saxi, 1) # irq busy by software reset
# restart
ng.sim.start(_saxi)
print('# Restart')
# from extern-send
irq_join(_saxi, 2)
araddr = ng.control_reg_extern_send * 4
print('# opcode = %d' % v)
for i in range(num_rep):
for j in range(c.shape[-1]):
x_offset = tmp_addr - d.default_global_addr
y_offset = tmp_addr - e.default_global_addr
z_offset = tmp_addr - f.default_global_addr
x = memory.read_word(i * c.aligned_shape[-1] + j,
d.addr + x_offset, c_dtype.width)
y = memory.read_word(i * c.aligned_shape[-1] + j,
e.addr + y_offset, c_dtype.width)
z = x + y
memory.write_word(i * c.aligned_shape[-1] + j,
f.addr + z_offset, z, c_dtype.width)
# to extern-recv
_saxi.write(awaddr_ext_rcv, 1)
# from extern-send
irq_join(_saxi, 2)
v = _saxi.read(araddr_ext_snd)
print('# opcode = %d' % v)
for i in range(num_rep):
for j in range(c.shape[-1]):
x_offset = tmp_addr - g.default_global_addr
z_offset = tmp_addr - h.default_global_addr
x = memory.read_word(i * c.aligned_shape[-1] + j,
g.addr + x_offset, c_dtype.width)
z = x
memory.write_word(i * c.aligned_shape[-1] + j,
h.addr + z_offset, z, c_dtype.width)
# to extern-recv
_saxi.write(awaddr_ext_rcv, 1)
# termination
irq_join(_saxi, 1)
#ng.sim.wait(_saxi)
end_time = time_counter.value
print('# end')
print('# execution cycles: %d' % (end_time - start_time))
# verify
ok_2nd = True
for i in range(num_rep):
for j in range(c.shape[-1]):
orig = memory.read_word(i * c.aligned_shape[-1] + j, c.addr,
c_dtype.width)
check = memory.read_word(i * c.aligned_shape[-1] + j,
check_addr, c_dtype.width)
if vthread.verilog.NotEql(orig, check):
print('NG', i, j, orig, check)
ok_2nd = False
# else:
# print('OK', i, j, orig, check)
if ok_1st and ok_2nd:
print('# verify: PASSED')
else:
print('# verify: FAILED')
vthread.finish()
th = vthread.Thread(m, 'th_ctrl', clk, rst, ctrl)
fsm = th.start()
uut = m.Instance(targ,
'uut',
params=m.connect_params(targ),
ports=m.connect_ports(targ))
# simulation.setup_waveform(m, uut)
simulation.setup_clock(m, clk, hperiod=5)
init = simulation.setup_reset(m,
resetn,
m.make_reset(),
period=100,
polarity='low')
init.add(
Delay(1000000),
Systask('finish'),
)
# output source code
if filename is not None:
m.to_verilog(filename)
# run simulation
sim = simulation.Simulator(m, sim=simtype)
rslt = sim.run(outputfile=outputfile)
lines = rslt.splitlines()
if simtype == 'verilator' and lines[-1].startswith('-'):
rslt = '\n'.join(lines[:-1])
return rslt
def mkTest(ich=3, och=10, ch=64, ksize=3, stride=1, col=28, row=28):
# create target hardware
# layer 0: conv2d, max_pool_serial, relu
input_layer = ng.placeholder(ng.int32,
shape=(1, row, col, ich),
name='input_layer')
w0 = ng.variable(ng.int32, shape=(ch, ksize, ksize, ich), name='w0')
a0 = ng.conv2d(input_layer, w0, strides=(1, stride, stride, 1))
a0 = ng.max_pool_serial(a0, ksize=(1, 2, 2, 1), strides=(1, 2, 2, 1))
a0 = ng.relu(a0)
# layer 1: conv2d, relu, reshape
w1 = ng.variable(ng.int32,
shape=(ch, ksize, ksize, a0.shape[-1]),
name='w1')
a1 = ng.conv2d(a0, w1, strides=(1, stride, stride, 1))
a1 = ng.relu(a1)
a1 = ng.reshape(a1, [-1])
# layer 2: full-connection
w2 = ng.variable(ng.int32, shape=(16, a1.shape[-1]), name='w2')
a2 = ng.matmul(a1, w2, transposed_b=True)
a2 = ng.relu(a2)
# layer 3: full-connection
w3 = ng.variable(ng.int32, shape=(och, a2.shape[-1]), name='w3')
output_layer = ng.matmul(a2, w3, transposed_b=True, name='output_layer')
targ = ng.to_veriloggen([output_layer], 'cnn')
#targ = ng.to_ipxact([output_layer], 'cnn')
# test controller
m = Module('test')
params = m.copy_params(targ)
ports = m.copy_sim_ports(targ)
clk = ports['CLK']
resetn = ports['RESETN']
rst = m.Wire('RST')
rst.assign(Not(resetn))
# AXI memory model
memory = axi.AxiMemoryModel(m, 'memory', clk, rst, mem_addrwidth=23)
memory.connect(ports, 'maxi')
# AXI-Slave controller
_saxi = vthread.AXIMLite(m, '_saxi', clk, rst, noio=True)
_saxi.connect(ports, 'saxi')
# timer
time_counter = m.Reg('time_counter', 32, initval=0)
seq = Seq(m, 'seq', clk, rst)
seq(time_counter.inc())
def ctrl():
for i in range(100):
pass
start_time = time_counter.value
ng.sim.start(_saxi)
print('# start')
ng.sim.wait(_saxi)
end_time = time_counter.value
print('# end')
print('# execution cycles: %d' % (end_time - start_time))
vthread.finish()
th = vthread.Thread(m, 'th_ctrl', clk, rst, ctrl)
fsm = th.start()
uut = m.Instance(targ,
'uut',
params=m.connect_params(targ),
ports=m.connect_ports(targ))
# simulation.setup_waveform(m, uut)
simulation.setup_clock(m, clk, hperiod=5)
init = simulation.setup_reset(m,
resetn,
m.make_reset(),
period=100,
polarity='low')
init.add(
Delay(10000000),
Systask('finish'),
)
return m
def run(a_shape=(15, 15), b_shape=(15, 15),
a_dtype=ng.int32, b_dtype=ng.int32, c_dtype=ng.int32,
par=1, axi_datawidth=32, silent=False,
filename=None, simtype='iverilog', outputfile=None):
# create target hardware
a = ng.placeholder(a_dtype, shape=a_shape, name='a')
b = ng.placeholder(b_dtype, shape=b_shape, name='b')
d = ng.add(a, b, dtype=c_dtype, par=par)
e = ng.add(b, a, dtype=c_dtype, par=par)
# SW returns ng.add(x, y)
f = ng.extern([d, e], shape=a_shape, opcode=0x1)
g = ng.sub(f, a)
# SW returns d as-is
h = ng.extern([g], shape=a_shape, opcode=0x2)
c = ng.sub(h, b)
targ = ng.to_veriloggen([c], 'matrix_extern', silent=silent,
config={'maxi_datawidth': axi_datawidth})
# verification data
va = np.arange(a.length, dtype=np.int64).reshape(a.shape) % [16]
vb = np.arange(b.length, dtype=np.int64).reshape(b.shape) % [32] + [16]
vd = ng.verify.add(va, vb, dtype=c_dtype, par=par,
x_dtype=a_dtype, y_dtype=b_dtype)
ve = ng.verify.add(vb, va, dtype=c_dtype, par=par,
x_dtype=b_dtype, y_dtype=a_dtype)
vf = ng.verify.extern([vd, ve], shape=a_shape, opcode=0x1,
func=lambda x, y: x + y)
vg = ng.verify.sub(vf, va,
x_dtype=c_dtype, y_dtype=c_dtype)
vh = ng.verify.extern([vg], shape=a_shape, opcode=0x2,
func=lambda x: x)
vc = ng.verify.sub(vh, vb,
x_dtype=c_dtype, y_dtype=c_dtype)
# to memory image
size_max = int(math.ceil(max(a.memory_size, b.memory_size, c.memory_size) / 4096)) * 4096
check_addr = max(a.addr, b.addr, c.addr) + size_max
size_check = size_max
tmp_addr = check_addr + size_check
memimg_datawidth = 32
mem = np.zeros([1024 * 1024 * 8 // memimg_datawidth], dtype=np.int64)
mem = mem + [100]
axi.set_memory(mem, va, memimg_datawidth,
a_dtype.width, a.addr,
max(int(math.ceil(axi_datawidth / a_dtype.width)), par))
axi.set_memory(mem, vb, memimg_datawidth,
b_dtype.width, b.addr,
max(int(math.ceil(axi_datawidth / b_dtype.width)), par))
axi.set_memory(mem, vc, memimg_datawidth,
c_dtype.width, check_addr,
max(int(math.ceil(axi_datawidth / c_dtype.width)), par))
# test controller
m = Module('test')
params = m.copy_params(targ)
ports = m.copy_sim_ports(targ)
clk = ports['CLK']
resetn = ports['RESETN']
rst = m.Wire('RST')
rst.assign(Not(resetn))
# AXI memory model
if outputfile is None:
outputfile = os.path.splitext(os.path.basename(__file__))[0] + '.out'
memimg_name = 'memimg_' + outputfile
memory = axi.AxiMemoryModel(m, 'memory', clk, rst,
datawidth=axi_datawidth,
memimg_datawidth=memimg_datawidth,
memimg=mem, memimg_name=memimg_name)
memory.connect(ports, 'maxi')
# AXI-Slave controller
_saxi = vthread.AXIMLite(m, '_saxi', clk, rst, noio=True)
_saxi.connect(ports, 'saxi')
# timer
time_counter = m.Reg('time_counter', 32, initval=0)
seq = Seq(m, 'seq', clk, rst)
seq(
time_counter.inc()
)
num_rep = functools.reduce(lambda x, y: x * y, c.shape[:-1], 1)
def ctrl():
for i in range(100):
pass
ng.sim.set_global_addrs(_saxi, tmp_addr)
start_time = time_counter.value
ng.sim.start(_saxi)
print('# start')
# from extern-send
araddr = ng.control_reg_extern_send * 4
v = _saxi.read(araddr)
while v == 0:
v = _saxi.read(araddr)
print('# opcode = %d' % v)
for i in range(num_rep):
for j in range(c.shape[-1]):
x_offset = tmp_addr - d.default_global_addr
y_offset = tmp_addr - e.default_global_addr
z_offset = tmp_addr - f.default_global_addr
x = memory.read_word(i * c.aligned_shape[-1] + j,
d.addr + x_offset, c_dtype.width)
y = memory.read_word(i * c.aligned_shape[-1] + j,
e.addr + y_offset, c_dtype.width)
z = x + y
memory.write_word(i * c.aligned_shape[-1] + j,
f.addr + z_offset, z, c_dtype.width)
# to extern-recv
awaddr = ng.control_reg_extern_recv * 4
_saxi.write(awaddr, 1)
# from extern-send
araddr = ng.control_reg_extern_send * 4
v = _saxi.read(araddr)
while v == 0:
v = _saxi.read(araddr)
print('# opcode = %d' % v)
for i in range(num_rep):
for j in range(c.shape[-1]):
x_offset = tmp_addr - g.default_global_addr
z_offset = tmp_addr - h.default_global_addr
x = memory.read_word(i * c.aligned_shape[-1] + j,
g.addr + x_offset, c_dtype.width)
z = x
memory.write_word(i * c.aligned_shape[-1] + j,
h.addr + z_offset, z, c_dtype.width)
# to extern-recv
awaddr = ng.control_reg_extern_recv * 4
_saxi.write(awaddr, 1)
ng.sim.wait(_saxi)
end_time = time_counter.value
print('# end')
print('# execution cycles: %d' % (end_time - start_time))
# verify
ok = True
for i in range(num_rep):
for j in range(c.shape[-1]):
orig = memory.read_word(i * c.aligned_shape[-1] + j,
c.addr, c_dtype.width)
check = memory.read_word(i * c.aligned_shape[-1] + j,
check_addr, c_dtype.width)
if vthread.verilog.NotEql(orig, check):
print('NG', i, j, orig, check)
ok = False
# else:
# print('OK', i, j, orig, check)
if ok:
print('# verify: PASSED')
else:
print('# verify: FAILED')
vthread.finish()
th = vthread.Thread(m, 'th_ctrl', clk, rst, ctrl)
fsm = th.start()
uut = m.Instance(targ, 'uut',
params=m.connect_params(targ),
ports=m.connect_ports(targ))
# simulation.setup_waveform(m, uut)
simulation.setup_clock(m, clk, hperiod=5)
init = simulation.setup_reset(m, resetn, m.make_reset(), period=100, polarity='low')
init.add(
Delay(1000000),
Systask('finish'),
)
# output source code
if filename is not None:
m.to_verilog(filename)
# run simulation
sim = simulation.Simulator(m, sim=simtype)
rslt = sim.run(outputfile=outputfile)
lines = rslt.splitlines()
if simtype == 'verilator' and lines[-1].startswith('-'):
rslt = '\n'.join(lines[:-1])
return rslt
def mkTest(n_input=784, n_classes=10):
# create target hardware
x = ng.placeholder(ng.int32, shape=[n_input])
w1 = ng.variable(ng.int32, shape=(n_input, n_input), name='h1')
w2 = ng.variable(ng.int32, shape=(n_input, n_input), name='h2')
w3 = ng.variable(ng.int32, shape=(n_classes, n_input), name='out')
l1 = ng.matmul(x, w1, transposed_b=True)
l1 = ng.relu(l1)
l2 = ng.matmul(l1, w2, transposed_b=True)
l2 = ng.relu(l2)
out = ng.matmul(l2, w3, transposed_b=True)
targ = ng.to_veriloggen([out], 'mlp')
#targ = ng.to_ipxact([model], 'mlp')
# test controller
m = Module('test')
params = m.copy_params(targ)
ports = m.copy_sim_ports(targ)
clk = ports['CLK']
resetn = ports['RESETN']
rst = m.Wire('RST')
rst.assign(Not(resetn))
# AXI memory model
memory = axi.AxiMemoryModel(m, 'memory', clk, rst)
memory.connect(ports, 'maxi')
# AXI-Slave controller
_saxi = vthread.AXIMLite(m, '_saxi', clk, rst, noio=True)
_saxi.connect(ports, 'saxi')
# timer
time_counter = m.Reg('time_counter', 32, initval=0)
seq = Seq(m, 'seq', clk, rst)
seq(time_counter.inc())
def ctrl():
for i in range(100):
pass
start_time = time_counter.value
ng.sim.start(_saxi)
print('# start')
ng.sim.wait(_saxi)
end_time = time_counter.value
print('# end')
print('# execution cycles: %d' % (end_time - start_time))
vthread.finish()
th = vthread.Thread(m, 'th_ctrl', clk, rst, ctrl)
fsm = th.start()
uut = m.Instance(targ,
'uut',
params=m.connect_params(targ),
ports=m.connect_ports(targ))
# simulation.setup_waveform(m, uut)
simulation.setup_clock(m, clk, hperiod=5)
init = simulation.setup_reset(m,
resetn,
m.make_reset(),
period=100,
polarity='low')
init.add(
Delay(1000000),
Systask('finish'),
)
return m