def pltPwrLoadScaling(output, fileID, loadSize, plotName, pwrThresh=100):
loadSize = loadSize[::-1]
plt.figure()
plt.style.use('classic')
for size in loadSize:
file = output + fileID + size
df = pc.readMetrics(file)
# data,start,end = pc.getComputationStartEnd (dff,pwrThresh)
# df = pc.getStablePwr(data,start,end)
maxp = max(df['pwr'])
minp = min(df['pwr'])
meanp = df['pwr'].mean()
std = stdev(df['pwr'])
print("\nMax: ", maxp, "Min: ", minp, "Mean: ", meanp, "Std: ", std,
"\n")
plt.plot(df['time'], df['pwr'], label=size)
plt.xlabel('Time (s)')
#plt.xlim(0, 12)
# Set the y axis label of the current axis.
plt.ylabel('Power (W)')
#plt.ylim(0, 275)
plt.ticklabel_format(useOffset=False)
# Set a title of the current axes.
#plt.title('Power vs Load')
# show a legend on the plot
plt.legend()
#plt.show()
plt.grid()
plt.savefig(output + fileID + plotName)
def pltPwrcapTimeIF(arch, app, dataPath, pltPath, thresh):
tot_time = []
mean_pwr = []
r2r_time = []
r2r_mean_pwr = []
fID = ""
pls = []
for p in np.arange(125, 255, 5):
pls.append(p)
pl = str(p)
if arch == "P100":
fID = app + '-fp64-run-' + pl + '-P100-1328-'
elif arch == "V100":
fID = app + '-fp64-run-' + pl + '-V100-1380-'
r2r_mean_pwr.clear()
r2r_time.clear()
for r in range(3):
d = pc.readMetrics(dataPath + fID + str(r))
df, s, e = pc.getComputationStartEnd(d, thresh)
# striping non-computing power consumption
data = pc.getStablePwr(df, s, e)
r2r_mean_pwr.append(data['pwr'].mean())
seconds = max(data['time']) - min(data['time'])
r2r_time.append(seconds)
mean_pwr.append(mean(r2r_mean_pwr))
tot_time.append(mean(r2r_time))
#print ('\nTime: ',tot_time,'\n')
#print ('\nPower: ',mean_pwr,'\n')
return tot_time, mean_pwr, arch, app, pltPath, 'PWRCAP', pls
def getPwrPerfCounters(output, fileID, size, pwrThresh=100):
#os.chdir('../')
#baseDir = os.getcwd()
#file = baseDir+'/test/output/'+app+'-'+prec+'-'+mode+'-'+size
file = output + fileID + size
# striping non-computing power consumption
data = pc.readMetrics(file)
gdata, cpStartTime, cpEndTime = pc.getComputationStartEnd(data, pwrThresh)
df = pc.getStablePwr(gdata, cpStartTime, cpEndTime)
#gpu0Pwr['time'] = (df['time'] - (df['time'].iloc[0]))
tot_seconds = max(df['time']) - min(df['time'])
#timedelta = tot_time - datetime(1900, 1, 1)
#tot_seconds = timedelta.total_seconds()
print('\nTotal Seconds', tot_seconds)
s = 0.0
if size == '16' or size == '32' or size == '48' or size == '64' or size == '72':
s = float(size) * 320
else:
s = float(size)
gflop = 2 * s * s * s / 1e9
print('\nGFlops:', gflop)
if tot_seconds != 0:
gflops = gflop / tot_seconds
else:
gflops = gflop
return (df['pwr'].mean()), gflops
def getPyMMPwr(output,fileID,numRuns,pwrThresh = 100):
pyMMPwrs = []
for r in numRuns:
file = output+fileID+r
data = pc.readMetrics(file)
data,s,e = pc.getComputationStartEnd (data,pwrThresh)
# striping non-computing power consumption
df = pc.getStablePwr(data,s,e)
pyMMPwrs.append(df['pwr'].mean())
return pyMMPwrs
def pltIndividual(output, fileID, size):
file = output + fileID + size
gpu0Pwr = pc.readMetrics(file)
GPU0MeanPwr = gpu0Pwr['pwr'].mean()
plt.figure()
plt.plot(gpu0Pwr['time'], gpu0Pwr['pwr'], label="Real-time")
meanGPUPwr = [GPU0MeanPwr for x in range(len(gpu0Pwr))]
plt.plot(gpu0Pwr['time'], meanGPUPwr, linestyle='--', label="Mean")
plt.xlabel('Time')
plt.ylabel('GPU Power Consumption (W)')
plt.title('Matrix size: ' + size + 'x' + size)
plt.legend()
plt.grid()
plt.ticklabel_format(useOffset=False)
plt.savefig(output + fileID + size + '.png')
meanGPUPwr.clear()
def getPyMMPwr(output, fileID, numRuns, pwrThresh=100):
pyMMPwrs = []
for r in numRuns:
'''
if fileID+r == 'dgemm-fp64-run-250-V100-135-8' or fileID+r == 'dgemm-fp64-run-250-V100-135-9':
print ("\n ***SKIPPING*** \n")
print (fileID+r)
print ("\n ***SKIPPING*** \n")
continue
'''
file = output + fileID + r
data = pc.readMetrics(file)
data, s, e = pc.getComputationStartEnd(data, pwrThresh)
# striping non-computing power consumption
df = pc.getStablePwr(data, s, e)
pyMMPwrs.append(df['pwr'].mean())
return pyMMPwrs
def pltVarations(output, fileID, r, pwrThresh=100):
file = output + fileID + r
gpu0Pwr = pc.readMetrics(file)
# striping non-computing power consumption
data, start, end = pc.getComputationStartEnd(gpu0Pwr, pwrThresh)
rampUp, stable, rampDown = getVariationSlices(data, start, end)
'''
print ('\ntotal length:', len(gpu0Pwr))
print('\nrampUp:',rampUp)
print ('\nrampUp length:',len(rampUp))
print('\nStable:',stable)
print ('\nStable length:',len(stable))
print('\nrampDown:',rampDown)
print ('\nrampDown length:',len(rampDown))
'''
pltRampUp(rampUp, output, fileID)
pltStable(stable, output, fileID)
pltRampDown(rampDown, output, fileID)
def pltDVFSTimeIF(arch, app, dataPath, pltPath, thresh):
tot_time = []
mean_pwr = []
r2r_time = []
r2r_mean_pwr = []
freqs = []
if arch == 'V100':
alt = 0
f = 135
while f <= upper_freq:
fID = app + '-fp64-run-250-V100-' + str(f) + '-'
freqs.append(f)
r2r_mean_pwr.clear()
r2r_time.clear()
if f == 1005:
thresh = 85
for r in range(3):
d = pc.readMetrics(dataPath + fID + str(r))
df, s, e = pc.getComputationStartEnd(d, thresh)
# striping non-computing power consumption
data = pc.getStablePwr(df, s, e)
r2r_mean_pwr.append(data['pwr'].mean())
seconds = max(data['time']) - min(data['time'])
r2r_time.append(seconds)
mean_pwr.append(mean(r2r_mean_pwr))
tot_time.append(mean(r2r_time))
if alt == 0:
f += 7
alt = 1
else:
f += 8
alt = 0
#print ('\nTime: ',tot_time,'\n')
print('\nPower: ', mean_pwr, '\n')
return tot_time, mean_pwr, arch, app, pltPath, 'DVFS', freqs
elif arch == 'P100':
f = 544
while f <= 1329: # 1328
fID = app + '-fp64-run-250-P100-' + str(f) + '-'
freqs.append(f)
r2r_mean_pwr.clear()
r2r_time.clear()
if f > 1005:
thresh = 85
for r in range(3):
d = pc.readMetrics(dataPath + fID + str(r))
df, s, e = pc.getComputationStartEnd(d, thresh)
# striping non-computing power consumption
data = pc.getStablePwr(df, s, e)
r2r_mean_pwr.append(data['pwr'].mean())
seconds = max(data['time']) - min(data['time'])
r2r_time.append(seconds)
mean_pwr.append(mean(r2r_mean_pwr))
tot_time.append(mean(r2r_time))
if f == 1328:
break
if (path.exists(dataPath + app + '-fp64-run-250-P100-' +
str(f + 12) + '-0')):
f += 12
elif (path.exists(dataPath + 'dgemm-fp64-run-250-P100-' +
str(f + 13) + '-0')):
f += 13
return tot_time, mean_pwr, arch, app, pltPath, 'DVFS', freqs
