In [1]:

    

%matplotlib inline

import time
import datetime
import numpy as np
import pandas as pd
#import seaborn as sns
import matplotlib.pyplot as plt
from IPython import display
from collections import OrderedDict

from pynvml import (nvmlInit,
                     nvmlDeviceGetCount, 
                     nvmlDeviceGetHandleByIndex, 
                     nvmlDeviceGetUtilizationRates,
                     nvmlDeviceGetName)


    

In [2]:

    

def gpu_info():
    "Returns a tuple of (GPU ID, GPU Description, GPU % Utilization)"
    nvmlInit()
    deviceCount = nvmlDeviceGetCount()
    info = []
    for i in range(0, deviceCount): 
        handle = nvmlDeviceGetHandleByIndex(i) 
        util = nvmlDeviceGetUtilizationRates(handle)
        desc = nvmlDeviceGetName(handle) 
        info.append((i, desc, util.gpu)) #['GPU %i - %s' % (i, desc)] = util.gpu
    return info


    

In [3]:

    

utils = []
while True:
    try:
        dt = datetime.datetime.now()
        util = gpu_info()
        utils.append([dt] + [x[2] for x in util])
        # Don't plot anything on the first pass
        if len(utils) == 1:
            continue
        df = pd.DataFrame(utils, columns=['dt'] + 
                          ['GPU %i - %s' % (x[0], x[1]) for x in util]).set_index('dt')
        ax = df.plot();
        vals = ax.get_yticks();
        #ax.set_yticklabels(['{:3.0f}%'.format(x) for x in vals]);
        ax.set_ylabel('GPU Utilization');
        ax.set_xlabel('Time');
        ax.set_ylim([0, 100])
        display.clear_output(wait=True)
        display.display(plt.gcf())
        time.sleep(1)
    except KeyboardInterrupt:
        break


    

In [ ]:

    

ax = df.plot();
vals = ax.get_yticks();
ax.set_yticklabels(['{:3.0f}%'.format(x) for x in vals]);
ax.set_ylabel('GPU Utilization');
ax.set_xlabel('Time');


    

In [ ]: