def SRAM_estimate_energy(self, interface):
width = interface['attributes']['width']
depth = interface['attributes']['depth']
action_name = interface['action_name']
arguments = interface['arguments']
this_dir, this_filename = os.path.split(__file__)
csv_file_path = os.path.join(this_dir,'data/SRAM.csv')
energy = None
with open(csv_file_path) as csv_file:
reader = csv.DictReader(csv_file)
for row in reader:
if row['action_name'] == action_name and\
int(row['width']) == width and \
int(row['depth']) == depth:
if DummyTableInterpolation.matched_arguments(row, arguments):
energy = float(row['energy'])
break
# no exact energy recorded in the table, do linear interpolation
if energy is None:
if 12 < depth < 24:
known_list = [{'x':12, 'y': 0.0}, {'x':224, 'y': 0.0}] # x is the depth, y is the energy
elif 24 < depth < 224:
known_list = [{'x':24, 'y': 0.0}, {'x':224, 'y': 0.0}]
with open(csv_file_path) as csv_file:
reader = csv.DictReader(csv_file)
for row in reader:
if int(row['width']) == width and int(row['depth']) == known_list[0]['x'] and row['action_name'] == action_name:
if DummyTableInterpolation.matched_arguments(row, arguments):
known_list[0]['y'] = float(row['energy'])
if int(row['width']) == width and int(row['depth']) == known_list[1]['x'] and row['action_name'] == action_name:
if DummyTableInterpolation.matched_arguments(row, arguments):
known_list[1]['y'] = float(row['energy'])
energy = oneD_linear_interpolation(depth, known_list)
return energy
def intadder_estimate_energy(self, interface):
this_dir, this_filename = os.path.split(__file__)
nbit = interface['attributes']['datawidth']
csv_nbit = 32
csv_file_path = os.path.join(this_dir, 'data/adder.csv')
energy = AladdinTable.query_csv_using_latency(interface, csv_file_path)
if not nbit == csv_nbit:
energy = oneD_linear_interpolation(nbit, [{
'x': 0,
'y': 0
}, {
'x': csv_nbit,
'y': energy
}])
return energy
def intadder_estimate_area(self, interface):
this_dir, this_filename = os.path.split(__file__)
nbit = interface['attributes']['datawidth']
csv_nbit = 32
csv_file_path = os.path.join(this_dir, 'data/adder.csv')
area = AladdinAreaQueires.query_csv_area_using_latency(
interface, csv_file_path)
if not nbit == csv_nbit:
area = oneD_linear_interpolation(nbit, [{
'x': 0,
'y': 0
}, {
'x': csv_nbit,
'y': area
}])
return area
def intadder_estimate_energy(self, interface):
this_dir, this_filename = os.path.split(__file__)
nbit = interface['attributes']['datawidth']
csv_nbit = 32
csv_file_path = os.path.join(this_dir, 'data/adder.csv')
energy = AladdinTable.query_csv_using_latency(interface, csv_file_path)
if not nbit == csv_nbit:
energy = oneD_linear_interpolation(nbit, [{
'x': 0,
'y': 0
}, {
'x': csv_nbit,
'y': energy
}])
if 'type' in interface['attributes'].keys() and \
interface['attributes']['type'] == 'fft':
print('DEBUGGING: using fft type')
energy = energy * 4
return energy
def test_oneD_linear_interpolation(self):
""" linear interpolation on one hardware attribute """
# Rough estimation of simple ripple carry adder: E_adder = E_full_adder * bitwidth + E_misc
E_full_adder = 4
E_misc = 2
bitwidth_0 = 32
bitwidth_1 = 8
energy_0 = E_full_adder * bitwidth_0 + E_misc
energy_1 = E_full_adder * bitwidth_1 + E_misc
bitwidth_desired = 16
# expected output
energy_desired = E_full_adder * bitwidth_desired + E_misc
energy_interpolated = hf.oneD_linear_interpolation(bitwidth_desired,[{'x':bitwidth_0, 'y': energy_0},
{'x':bitwidth_1, 'y':energy_1}])
self.assertEqual(energy_interpolated, energy_desired)
def fpadder_estimate_energy(self, interface):
this_dir, this_filename = os.path.split(__file__)
nbit_exponent = interface['attributes']['exponent']
nbit_mantissa = interface['attributes']['mantissa']
nbit = nbit_mantissa + nbit_exponent
if nbit_exponent + nbit_mantissa <= 32:
csv_nbit = 32
csv_file_path = os.path.join(this_dir, 'data/fp_sp_adder.csv')
else:
csv_nbit = 64
csv_file_path = os.path.join(this_dir, 'data/fp_dp_adder.csv')
energy = AladdinTable.query_csv_using_latency(interface, csv_file_path)
if not nbit == csv_nbit:
energy = oneD_linear_interpolation(nbit, [{
'x': 0,
'y': 0
}, {
'x': csv_nbit,
'y': energy
}])
return energy
