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Commit 182c4a05 authored by Elizabeth's avatar Elizabeth
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Added computations for relative speedup

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llvm/projects/soc_simulator/src/driver_new_config.py
+ 102
− 54
View file @ 182c4a05
......@@ -34,9 +34,8 @@ class Driver:
# Operation names need to be stored in order of insertion
self.__tensor_table = defaultdict(lambda: list(defaultdict(str)))
# [Time/Energy][config name] = time/energy
self.__aggregate_results = defaultdict(lambda: defaultdict(float))
self.__config_count = 0
self.__conf_results = [] # indexed
#self.__conf_results = {} # {conf name: (first line, [[layer value if promise], [tensor vals if gpu]])}
@staticmethod
......@@ -79,7 +78,6 @@ class Driver:
if not os.path.isfile(self.__layer_filename):
print("ERROR: %s was not found." % self.__layer_filename)
exit(1)
layer_file = open(self.__layer_filename, "r")
for line in layer_file:
layer_data = line.strip().split(',')
......@@ -141,14 +139,14 @@ class Driver:
operation_data["Name"] = op_name
# Number of data items (#s) needs to match up with the # of cols
#print(len(op_data) - 1, len(col_names))
#print(op_data)
#print(col_names)
print(len(op_data) - 1, len(col_names))
print(op_data)
print(col_names)
#assert(len(op_data) - 1 == len(col_names))
assert(len(op_data) - 1 == len(col_names))
# Go through all data items (each col element) per operation
for i in range(len(col_names)):
#print(col_names[i], float(op_data[i + 1]))
print(col_names[i], float(op_data[i + 1]))
operation_data[col_names[i]] = float(op_data[i + 1])
layer_operations.append(operation_data)
......@@ -173,11 +171,14 @@ class Driver:
while line:
assert(line == "+++++")
print("CONFIGURATION")
curr_conf_results = []
prev_layer = Driver.PrecisionTypes.FP32
curr_layer = None
line = config_file.readline().strip()
first_line = line
conf_name = line.split(' ')[0]
assert(conf_name.startswith("conf"))
line = config_file.readline().strip()
......@@ -193,6 +194,7 @@ class Driver:
layer_table_data = self.__tensor_layers[layer_ind]
layer_name = layer_table_data["Name"]
layer_results = []
if Driver.is_promise(layer_as_lst[1]):
print("Running layer %s on PROMISE" % layer_name)
curr_layer = Driver.PrecisionTypes.PROMISE
......@@ -207,17 +209,11 @@ class Driver:
time, energy = self.__run_promise_simulation(param_val, layer_table_data)
total_time += time
total_energy += energy
self.__aggregate_results[Driver.results_time_key][conf_name] += total_time
self.__aggregate_results[Driver.results_energy_key][conf_name] += total_energy
print(total_time, total_energy)
#print("AGGREGATE RESULTS: ", self.__aggregate_results)
layer_results.append((total_time, total_energy, ' '.join(layer_as_lst[1:])))
elif Driver.is_gpu(layer_as_lst[1]):
print("Running layer %s on the GPU" % layer_name)
total_time = 0
total_energy = 0
tensor_count = 0
# 3 elements per tensor operation
......@@ -246,20 +242,16 @@ class Driver:
tensor_count, layer_table_data)
conv_time, conv_energy = self.__run_gpu_simulation(curr_layer, layer_name, \
tensor_count, approx_type, op_number)
total_time += quant_time + conv_time
total_energy += quant_energy + conv_energy
layer_results.append((quant_time + conv_time, quant_energy + conv_energy, ' '.join(layer_as_lst[i : i + 3])))
prev_layer = curr_layer
tensor_count += 1
print(total_time, total_energy)
self.__aggregate_results[Driver.results_time_key][conf_name] += total_time
self.__aggregate_results[Driver.results_energy_key][conf_name] += total_energy
print(Driver.results_energy_key, conf_name)
#print("AGGREGATE RESULTS", self.__aggregate_results)
line = config_file.readline().strip()
prev_layer = curr_layer
curr_conf_results.append(layer_results)
#self.__conf_results[conf_name] = (first_line, curr_conf_results)
self.__conf_results.append( (first_line, curr_conf_results) )
line = config_file.readline().strip()
config_file.close()
#print("AGGREGATE RESULTS", self.__aggregate_results)
......@@ -307,7 +299,7 @@ class Driver:
elif Driver.is_fc(layer_name):
rows_a = layer_data["RA"]
cols_a = layer_data["CA"]
rows_b = cols_a
rows_b = cols_
cols_b = layer_data["CB"]
else:
print("PROMISE can't run whatever this layer is.")
......@@ -356,48 +348,104 @@ class Driver:
elif curr_layer == Driver.PrecisionTypes.FP16:
time_key = "fp16_time"
energy_key = "fp16_energy"
#print(time_key, energy_key)
print(time_key, energy_key)
conversion_time = tensor_info[time_key]
conversion_energy = tensor_info[energy_key]
#print(conversion_time, conversion_energy)
print(conversion_time, conversion_energy)
print("GPU: (%f, %f)" % (conversion_time, conversion_energy))
return conversion_time, conversion_energy
def __write_output(self):
# Need to write the time/energy pairs to the configuration file
results_file = open(self.__results_filename, "w")
# Layout is based off the configuration filename
config_file = open(self.__config_filename, "r")
baseline_time = baseline_energy = None
results_file = open(self.__results_filename, "w")
def write_conf_to_file(conf_name, final_conf, time_speedup, energy_speedup):
# conf = [layer value if promise], [tensor vals if gpu]]
conf_str = ["+++++"]
# process the first line
first_line, layers = final_conf
first_line_lst = first_line.split(' ')
assert first_line_lst[0] == conf_name
new_header = [conf_name]
new_header.append(repr(time_speedup))
new_header.append(repr(energy_speedup))
new_header.append(first_line_lst[-1])
new_header.append(first_line_lst[-2])
conf_str.append(' '.join(new_header))
for ind, layer in enumerate(layers):
layer_lst = [str(ind + 1)]
for op_time, op_energy, tensor_op in layer:
layer_lst.append(tensor_op)
conf_str.append(' '.join(layer_lst))
conf_str.append("-----\n")
results_file.write('\n'.join(conf_str))
baseline_conf = None
baseline_total_time = baseline_total_energy = 0
def get_baseline_times_enegies():
curr_time = curr_energy = 0
for layer in baseline_conf[1]:
for op_time, op_energy, tensor_op in layer:
curr_time += op_time
curr_energy += op_energy
return curr_time, curr_energy
def get_final_times_energies_conf(curr_conf):
final_time = final_energy = 0
final_conf = [] # List (conf) of lists (layers) of tuples (operation data)
for layer_ind, layer in enumerate(curr_conf[1]):
final_conf_layer = []
for tensor_ind, (op_time, op_energy, tensor_op) in enumerate(layer):
baseline_time, baseline_energy, baseline_op = baseline_conf[1][layer_ind][tensor_ind]
final_tensor_op = tensor_op
if op_time > baseline_time:
final_time += baseline_time
final_tensor_op = baseline_op
else:
final_time += op_time
# Ignoring bigger energies for now
'''
if op_energy > baseline_energy:
print("BIGGER ENERGY")
final_energy += baseline_energy
final_tensor_op = baseline_op
else:
final_energy += op_energy
'''
final_energy += op_energy
final_conf_layer.append((None, None, final_tensor_op)) # Don't care about the times and energies when writing
final_conf.append(final_conf_layer)
return final_time, final_energy, (curr_conf[0], final_conf)
conf_index = 0
for line in config_file:
if line.startswith("conf"): # Write in the time and energy
if line.startswith("conf"):
orig_line_lst = line.split(' ')
conf_header = []
conf_name = orig_line_lst[0]
if not baseline_time:
baseline_time = self.__aggregate_results[Driver.results_time_key][conf_name]
if not baseline_energy:
baseline_energy = self.__aggregate_results[Driver.results_energy_key][conf_name]
print("FP32 Baseline time is %f and baseline energy is %f" % (baseline_time, baseline_energy))
print(conf_name, self.__aggregate_results[Driver.results_time_key][conf_name], self.__aggregate_results[Driver.results_energy_key][conf_name])
conf_header.append(conf_name)
conf_header.append(repr(baseline_time / self.__aggregate_results[Driver.results_time_key][conf_name]))
conf_header.append(repr(baseline_energy / self.__aggregate_results[Driver.results_energy_key][conf_name]))
# TODO Accuracy/accuracy loss
conf_header.append(orig_line_lst[-2])
conf_header.append(orig_line_lst[-1])
results_file.write("%s" % ' '.join(conf_header))
else:
results_file.write("%s" % line) # Copy the line
config_file.close()
if not baseline_conf:
baseline_conf = self.__conf_results[conf_index] #conf_name]
print("FOUND baseline", baseline_conf)
baseline_total_time, baseline_total_energy = get_baseline_times_enegies()
results_file.write("%s\n" % repr(baseline_total_time)) # write baseline time to top of file
write_conf_to_file(conf_name, baseline_conf, 1, 1)
else:
curr_conf = self.__conf_results[conf_index] #conf_name]
final_time, final_energy, curr_conf = get_final_times_energies_conf(curr_conf)
assert(final_time <= baseline_total_time)
#assert(final_energy <= baseline_total_energy)
write_conf_to_file(conf_name, curr_conf, baseline_total_time / final_time, baseline_total_energy / final_energy)
conf_index += 1
results_file.close()
config_file.close()
if __name__ == "__main__":
if len(sys.argv) != 5:
......
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