Efficiency-of-Neural-Archit.../amd_sample_draw.py

97 lines
2.6 KiB
Python

import os
import re
import pickle
import numpy as np
from warnings import warn
with open("frq", "r") as file:
frq = int(file.read())
with open("bay", "r") as file:
bay = int(file.read())
if frq == 1:
model_t = "freq"
with open("tmp", "r") as file:
size = float(file.read())
if bay == 1:
model_t = "bayes"
with open("tmp", "r") as file:
size = int(file.read())
pickle_name = "{}_wattdata_{}.pkl".format(model_t,size)
print("GPU energy file config: {}".format(pickle_name))
def get_sample_of_gpu():
from re import sub, findall
import subprocess
from subprocess import run
no_graph = "NVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver. Make sure that the latest NVIDIA driver is installed and running."
no_version = "Failed to initialize NVML: Driver/library version mismatch"
smi_string = run(['rocm-smi', '-P', '--showvoltage', '--showmemuse'], stdout=subprocess.PIPE)
smi_string = smi_string.stdout.decode('utf-8')
smi_string = smi_string.split("\n")
smi_string = list(filter(lambda x: x, smi_string))
if smi_string[0] == no_graph:
raise Exception("It seems that no AMD GPU is installed")
elif smi_string[0] == no_version:
raise Exception("rocm-smi version mismatch")
else:
results= []
gpuW0 = findall("[0-9]*\.[0-9]*",smi_string[2])
gpuW1 = findall("[0-9]*\.[0-9]*",smi_string[4])
gpuM0 = findall("[0-9]+",smi_string[7])
gpuM1 = findall("[0-9]+",smi_string[9])
gpuV0 = findall("[0-9]+",smi_string[13])
gpuV1 = findall("[0-9]+",smi_string[14])
results.append(float(gpuW0[0]) + float(gpuW1[0]))
if len(gpuM0) == 2 and len(gpuM1) == 2:
results.append(int(gpuM0[1]) + int(gpuM1[1]))
elif len(gpuM0) == 2:
results.append(gpuM0[1])
elif len(gpuM1) == 2:
results.append(gpuM1[1])
results.append(int(gpuV0[1]) + int(gpuV1[1]))
return results
#for l in smi_string:
#temp = findall("[0-9]*MiB | [0-9]*W",l)
#if temp:
#return temp
def total_watt_consumed():
with open(pickle_name, 'rb') as f:
x = pickle.load(f)
x = np.array(x)
x = x[:,0]
y = [int(re.findall("\d+",xi)[0]) for xi in x]
return sum(y)
if __name__ == '__main__':
dataDump = []
#var = True
#pickling_on = open("wattdata.pickle","wb")
while True:
#from run_service import retcode
try:
dataDump.append(get_sample_of_gpu())
with open(pickle_name, 'wb') as f:
pickle.dump(dataDump, f)
except EOFError:
warn('Pickle ran out of space')
size += 0.01
finally:
f.close()
#if retcode == 0:
#break
#pickle.dump(dataDump, pickling_on)
#pickling_on.close()