available_registers = [['B', 'C', 'D', 'E'], ['B', 'C', 'D', 'E'],
['B', 'C', 'D', 'E']]
filename_prefix = '_out_conv_'
for k in range(3):
csimProgram, _, _ = generate(kernels[k],
search_time,
start_reg=start_register[k],
target_reg=start_register[k],
available_regs=[start_register[k]] +
available_registers[k],
verbose=0,
out_format='CSIM',
approx_depth=approx_depth,
pair_props=pair_props)
scamp5Program = csim_to_scamp5(csimProgram)
# Output to files
with open(filename_prefix + str(k + 1) + '.txt', 'w') as f:
for l in scamp5Program:
f.write(l + '\n')
#################################################
# Generate the 3 convolutions with incrementally less registers
#################################################
# Generate CSIM code, with all registers available
start_register = ['A', 'B', 'C']
available_registers = [['B', 'C', 'D', 'E'], ['C', 'D', 'E'], ['D', 'E']]
filename_prefix = '_out_conv_bis_'
for k in range(3):
available_registers = [['B', 'C', 'D', 'E'], ['C', 'D', 'E'], ['C', 'D', 'E'],
['C', 'D', 'E']]
filename_prefix = '_out_conv1_'
for k in range(4):
csimProgram, _, _ = generate(w1_val[:, :, 0, k],
search_time,
start_reg=start_register[k],
target_reg=start_register[k],
available_regs=[start_register[k]] +
available_registers[k],
verbose=0,
out_format='CSIM',
approx_depth=approx_depth,
pair_props=pair_props)
scamp5Program = csim_to_scamp5(csimProgram)
# Output to files
with open(filename_prefix + str(k + 1) + '.txt', 'w') as f:
for l in scamp5Program:
f.write(l + '\n')
#################################################
# Generate the remaining 4*8 convolutions (second layer)
# conv_2_1 to conv_2_8 are computed in AREG C.
#################################################
def sparsify_kernel(original_kernel):
out = np.zeros((5, 5))
out[::2, ::2] = original_kernel
return out