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Commit f19a557c authored by Elizabeth's avatar Elizabeth
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Fixed bug in new config parsing

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llvm/projects/soc_simulator/src/driver_new_config.py
+ 72
− 68
View file @ f19a557c
......@@ -10,6 +10,7 @@ class Driver:
FP16 = 0
FP32 = 1
PROMISE = 2
PERF = 3
results_time_key = "Time"
results_energy_key = "Energy"
......@@ -23,14 +24,18 @@ class Driver:
return "PROMISE"
def driver(self):
#self.__parse_tensor_layer_file()
#self.__parse_tensor_table()
self.__parse_tensor_layer_file()
self.__parse_tensor_table()
#self.__run_simulations()
#self.__display_results()
config_file = open(self.__config_filename, "r")
line = config_file.readline().strip()
config_count = 0
prev_layer = Driver.ApproxTypes.FP32
curr_layer = None
while line:
print(line)
assert(line == "+++++")
print("CONFIGURATION")
......@@ -42,20 +47,63 @@ class Driver:
line = config_file.readline().strip()
# layers
layer_count = 0
while line != "-----":
print("LAYER", line == "-----")
layer_data = line.split(' ')
if layer_data[1] == "promise":
print(layer_count, len(self.__tensor_layers))
if line.find("softmax") != -1:
line = config_file.readline().strip()
continue
layer_table_data = self.__tensor_layers[layer_count]
layer_name = layer_table_data["name"]
layer_line = line.split(' ')
if layer_line[1] == "promise":
print("PROMISE")
elif layer_data[1] == "gpu":
curr_layer = Driver.ApproxTypes.PROMISE
time, energy = self.__run_promise_simulation(layer_line[3], layer_table_data)
print(time, energy)
self.__aggregate_results[results_time_key][config_count] += time
self.__aggregate_results[results_energy_key][config_count] += energy
elif layer_line[1] == "gpu":
print("GPU")
for i in range(2, len(layer_data), 3):
op_type = layer_data[i]
approx_type = layer_data[i + 1]
op_number = layer_data[i + 2]
print(op_type, approx_type, op_number)
total_time = 0
total_energy = 0
tensor_count = 0
for i in range(2, len(layer_line), 3):
op_type = layer_line[i]
approx_type = layer_line[i + 1]
op_number = layer_line[i + 2]
#print(op_type, approx_type, op_number)
if approx_type == "fp16":
curr_layer = Driver.ApproxTypes.FP16
elif approx_type == "fp32":
curr_layer = Driver.ApproxTypes.FP32
elif approx_type == "perf":
curr_layer = Driver.ApproxTypes.PERF
quant_time, quant_energy = self.__quantize(curr_layer, prev_layer, tensor_count, layer_table_data)
if curr_layer == Driver.ApproxTypes.PERF:
conv_time, conv_energy = self.__run_gpu_simulation(curr_layer, layer_name, tensor_count, op_number) # Only need op number for perf
else:
conv_time, conv_energy = self.__run_gpu_simulation(curr_layer, layer_name, tensor_count)
total_time += quant_time + conv_time
total_energy += quant_energy + conv_energy
prev_layer = curr_layer
tensor_count += 1
self.__aggregate_results[results_time_key][config_count] += total_time
self.__aggregate_results[results_energy_key][config_count] += total_energy
layer_count += 1
line = config_file.readline().strip()
prev_layer = curr_layer
config_count += 1
line = config_file.readline().strip()
config_file.close()
......@@ -182,7 +230,9 @@ class Driver:
def __quantize(self, curr_layer, prev_layer, h2f_f2h_operation_ind, layer_data):
print(self.__get_str(curr_layer), self.__get_str(prev_layer), h2f_f2h_operation_ind)
if curr_layer == prev_layer or curr_layer == Driver.ApproxTypes.PROMISE \
or prev_layer == Driver.ApproxTypes.PROMISE: # No quantization needed
or prev_layer == Driver.ApproxTypes.PROMISE \
or curr_layer == Driver.ApproxTypes.PERF \
or prev_layer == Driver.ApproxTypes.PERF: # No quantization needed
return 0.0, 0.0
layer_name = layer_data["Name"]
......@@ -235,69 +285,23 @@ class Driver:
return float(total_time_energy[0]), float(total_time_energy[1])
def __run_gpu_simulation(self, curr_layer, layer_name, tensor_ind):
def __run_gpu_simulation(self, curr_layer, layer_name, tensor_ind, perf_number = None):
tensor_info = self.__tensor_table[layer_name][tensor_ind]
if curr_layer == Driver.ApproxTypes.FP32:
conversion_time = tensor_info["fp32_time"]
conversion_energy = tensor_info["fp32_energy"]
else:
elif curr_layer == Driver.ApproxTypes.FP16:
conversion_time = tensor_info["fp16_time"]
conversion_energy = tensor_info["fp16_energy"]
print("GPU: (%f, %f)" % (conversion_time, conversion_energy))
return (conversion_time, conversion_energy)
def __run_simulations(self):
if not os.path.isfile(self.__config_filename):
print("ERROR: %s was not found" % self.__config_filename)
exit(1)
config_file = open(self.__config_filename, "r")
# each line = indepedent configuration
# layers are separated by commas
# tensor ops are separated by spaces
for config in config_file:
config_layers = config.strip().split(',')
prev_layer = Driver.ApproxTypes.FP32
curr_layer = None
for layer_ind, config_layer in enumerate(config_layers): # level
layer_data = self.__tensor_layers[layer_ind] # layer
layer_name = layer_data["Name"]
if Driver.is_promise(config_layer):
print("Running layer %s on PROMISE" % layer_name)
curr_layer = Driver.ApproxTypes.PROMISE
# Compute
time, energy = self.__run_promise_simulation(config_layer, layer_data)
self.__aggregate_results[Driver.results_time_key][self.__config_count] += time
self.__aggregate_results[Driver.results_energy_key][self.__config_count] += energy
else:
print("Running layer %s on the GPU" % layer_name)
tensor_ops = config_layer.split(' ')
total_time = 0
total_energy = 0
for tensor_ind, tensor_op in enumerate(tensor_ops): # sublevle
tensor_op = int(tensor_op)
if tensor_op == Driver.fp16_swing:
curr_layer = Driver.ApproxTypes.FP16
else:
curr_layer = Driver.ApproxTypes.FP32
quant_time, quant_energy = self.__quantize(curr_layer, prev_layer, tensor_ind, layer_data)
conv_time, conv_energy = self.__run_gpu_simulation(curr_layer, layer_name, tensor_ind)
total_time += quant_time + conv_time
total_energy += quant_energy + conv_energy
prev_layer = curr_layer
self.__aggregate_results[Driver.results_time_key][self.__config_count] += total_time
self.__aggregate_results[Driver.results_energy_key][self.__config_count] += total_energy
prev_layer = curr_layer
elif curr_layer == Driver.ApproxTypes.PERF:
# Then we care abut the following number
conversion_time = tensor_info["perf%d_time" % perf_number]
conversion_energy = tensor_info["perf%d_energy" % perf_number]
self.__config_count += 1
print("\n")
config_file.close()
print("GPU: (%f, %f)" % (conversion_time, conversion_energy))
return (conversion_time, conversion_energy)
def __display_results(self):
......
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