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gpu_list.py
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gpu_list.py
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#!/usr/bin/env python
# coding: utf-8
import os, sys, time, subprocess, re
import numpy as np
import pickle
from os.path import join, isfile, isdir
from collections import deque
from visdom import Visdom
import matplotlib.pyplot as plt
plt.switch_backend('agg')
from subprocess import STDOUT, check_output
import HTML
# In[12]
def filter_num(line):
return re.findall(r"[-+]?\d*\.\d+|\d+", line)
def ssh_host(hosts, mode='memory', num_gpus=4, verbose=False):
info, info2, info3 = [], [], []
for host in hosts:
if mode != 'all':
COMMAND=f"python3 {PWD}/py_gpu_status.py --mode {mode}"
else:
COMMAND = f'''
python3 {PWD}/py_gpu_status.py --mode all
free -th
'''
try:
result = check_output(["ssh", host, COMMAND],
stderr=STDOUT,
timeout=10)
except Exception as e:
print('Catch exception when ssh {}! Skip! {}'.format(host,e.args))
info.append([-1]*4)
if mode == 'all':
info2.append([-1]*4)
info3.append([-1]*4)
else:
if mode != 'all':
result_ = result.decode("utf-8")
gpu_memory = list(map(float,result_.strip('\n').split(',')))
if len(gpu_memory) < num_gpus:
gpu_memory.extend([-1,]*(num_gpus-len(gpu_memory)))
info.append(gpu_memory)
else:
result_ = result.decode("utf-8").strip('\n').split('\n')
gpu_memory = list(map(float,result_[0].split(',')))
gpu_usage = list(map(float,result_[1].split(',')))
cpu_memory = list(map(float,filter_num(result_[3])))
#cpu_swap = list(map(float,filter_num(result_[4])))
if len(gpu_memory) < num_gpus:
gpu_memory.extend([-1,]*(num_gpus-len(gpu_memory)))
if len(gpu_usage) < num_gpus:
gpu_usage.extend([-1,]*(num_gpus-len(gpu_usage)))
info.append(gpu_memory)
info2.append(gpu_usage)
info3.append(cpu_memory)
if mode == 'all':
return info, info2, info3
else:
return info
def get_gpu_health(mem, use, th=[1,15]):
if mem<1 and use<=th[0]:
return 'Empty'
elif mem>1 and use<th[0]:
return 'Error?'
elif mem>1 and th[0]<=use<=th[1]:
return 'Unhealthy'
elif mem>1 and use>th[1]:
return 'Healthy'
else:
#print(f'Confused: mem-{mem},use-{use}')
return 'Error?'
def get_tablerow(host_name,status):
items = []
for s in status:
try:
color = color_map2[s]
except:
color = 'white'
items.append([s,color])
return [host_name, ] + items
class GPU_logger():
def __init__(self,host_names,time_interval,time_range,
show_summary=True, show_monitor=True, show_cpu_mem=False,
port=8098, env_name='main', verbose=False):
self.viz = Visdom(port=port)
self.env = env_name
self.hosts = host_names
self.sleep = time_interval
self.range = time_range
self.show_summary = show_summary
self.show_monitor = show_monitor
self.show_cpu_mem = show_cpu_mem
self.verbose=verbose
self.win = {}
self.num_gpus = 4
self.max_length = self.range // self.sleep
self.tick_ds = self.max_length//6
self.time_indices = deque()
self.memory_queue = np.zeros([len(host_names), self.num_gpus, 0])
self.usages_queue = np.zeros([len(host_names), self.num_gpus, 0])
self.table_W = 780
self.table_H = 470
self.restore(PWD)
def reset(self):
self.viz.close(win=None, env=self.env)
def save(self, output_dir):
if not isdir(output_dir):
os.makedirs(output_dir)
with open(join(output_dir, 'cached_data'), 'wb') as f:
pickle.dump({'time': self.time_indices,
'memory':self.memory_queue,
'usages':self.usages_queue}, f, pickle.HIGHEST_PROTOCOL)
def restore(self, output_dir):
if isfile(join(output_dir, 'cached_data')):
with open(join(output_dir, 'cached_data'), 'rb') as f:
cache = pickle.load(f)
self.time_indices = cache['time']
self.memory_queue = cache['memory']
self.usages_queue = cache['usages']
def record(self):
if self.show_summary:
gpu_tabel_opts = {'title':'README', 'resize':False, 'width':self.table_W, 'height':self.table_H}
col_W = self.table_W/len(self.hosts)
self.win['summary'] = self.viz.text(README, env=self.env, opts=gpu_tabel_opts)
if self.show_cpu_mem:
cpu_tabel_opts = {'title':'CPU Memory', 'resize':True, 'width':self.table_W, 'height':150}
col_W_c = self.table_W/len(self.hosts)
self.win['cpu_mem'] = self.viz.text('', env=self.env, opts=cpu_tabel_opts)
while True:
if len(self.time_indices) >= self.max_length:
self.time_indices.popleft()
self.time_indices.append(time.strftime("%H:%M"))
if isfile(join(HOME,'.tcshrc')): # hotfix to handle my zsh
os.rename(join(HOME,'.tcshrc'), join(HOME,'.tcshrc.bak'))
#gpu_memory = ssh_host(self.hosts, mode='memory')
#gpu_usage = ssh_host(self.hosts, mode='gpu')
gpu_memory, gpu_usage, cpu_memory = ssh_host(self.hosts, mode='all')
if self.verbose:
print('gpu memory:', gpu_memory)
print('gpu usage:', gpu_usage)
print('cpu memory:', cpu_memory)
if isfile(join(HOME,'.tcshrc.bak')):
os.rename(join(HOME,'.tcshrc.bak'), join(HOME,'.tcshrc'))
if self.memory_queue.shape[-1] < self.max_length:
self.memory_queue = np.append(self.memory_queue,
np.reshape(gpu_memory,[len(self.hosts), self.num_gpus, 1]),
-1)
self.usages_queue = np.append(self.usages_queue,
np.reshape(gpu_usage, [len(self.hosts), self.num_gpus, 1]),
-1)
else:
self.memory_queue = np.append(np.delete(self.memory_queue, 0, -1),
np.reshape(gpu_memory,[len(self.hosts), self.num_gpus, 1]),
-1)
self.usages_queue = np.append(np.delete(self.usages_queue, 0, -1),
np.reshape(gpu_usage, [len(self.hosts), self.num_gpus, 1]),
-1)
gpu_status_table, cpu_status_table = [], []
gpu_status_table.append(get_tablerow('',['GPU:01','GPU:02','GPU:03','GPU:04']))
cpu_status_table.append(get_tablerow('',['Total:', 'Used:', 'Available:']))
for k,host in enumerate(self.hosts):
fig = plt.figure(figsize=(20, 2.7))
fig.suptitle(host, size=24, fontweight="bold", y=1.)
gpu_status_row = []
for idx in range(4):
memory_, usage_ = self.memory_queue[k,idx,:], self.usages_queue[k,idx,:]
nonzero_idx = np.where(memory_>1)[0]
m_memory_ = np.mean(memory_[nonzero_idx[0]:]) if len(nonzero_idx) > 0 else np.mean(memory_)
m_usage_ = np.mean(usage_[nonzero_idx]) if len(nonzero_idx) > 0 else np.mean(usage_)
if m_memory_ == -1: # I've set empty gpu to -1
gpu_status_row.append(' ')
continue
if np.any(memory_[-5:]>1): #if last 5 checkpoint is empty -> not used now
status = get_gpu_health(m_memory_, m_usage_)
else:
status = status_kw[0]
box_prop = dict(facecolor=color_map[status], edgecolor='none', pad=2, alpha=0.6)
gpu_status_row.append(status)
plt.subplot(1,4,idx+1)
plt.xticks(np.arange(0, len(self.time_indices), self.tick_ds))
plt.fill_between(list(self.time_indices), memory_, color='r', label="Memory", alpha=0.4)
plt.fill_between(list(self.time_indices), usage_, color='g', label="Usages", alpha=0.4)
plt.ylim(-1, 101)
plt.title('GPU-{:02d}'.format(idx),size=15,bbox=box_prop)
plt.xlabel('Average Memory: {:.1f}% Average Usage: {:.1f}%'\
.format(m_memory_, m_usage_), size=14)
plt.tight_layout()
plt.legend()
gpu_status_table.append(get_tablerow(host.replace('emon','-'),gpu_status_row)) #shorten hostname
cpu_status_table.append(get_tablerow(host.replace('emon','-'),
[str(cpu_memory[k][0])+'G',str(cpu_memory[k][1])+'G',str(cpu_memory[k][-1])+'G']))
if self.show_monitor:
opts = {'title':host, 'resizable':True, 'height':190, 'width':1400}
if host not in self.win.keys():
self.win[host] = self.viz.matplot(plt, env=self.env, opts=opts)
else:
self.viz.matplot(plt, win=self.win[host], env=self.env, opts=opts)
plt.close()
TIMESTAMP=f"Updated at {time.strftime('%Y/%m/%d-%H:%M:%S')}<br>"
if 'summary' in self.win.keys():
status_table_g = [list(t) for t in zip(*gpu_status_table)]
table_ = HTML.table(status_table_g,border='3',cellpadding=5,
col_width=[col_W]*(len(self.hosts)+1),
col_align=['center']*(len(self.hosts)+1))
self.viz.text(README+table_+TIMESTAMP+ACKNOWLEDGE,
env=self.env,win=self.win['summary'],
opts=gpu_tabel_opts)
if 'cpu_mem' in self.win.keys():
status_table_c = [list(t) for t in zip(*cpu_status_table)]
table_c = HTML.table(status_table_c,border='2',cellpadding=2,
col_width=[col_W_c]*(len(self.hosts)+1),
col_align=['center']*(len(self.hosts)+1))
self.viz.text(table_c+TIMESTAMP,
env=self.env,win=self.win['cpu_mem'],
opts=cpu_tabel_opts)
time.sleep(self.sleep)
if __name__ == '__main__':
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--env', type=str, default='GPUs', help='Env name')
parser.add_argument('-i', '--interval', type=int, default=60, help='Time interval for monitoring (sec.)')
parser.add_argument('-r', '--time-range', type=int, default=10800, help='Time range for showing data (sec.)')
args = parser.parse_args()
HOME = os.getenv('HOME')
PWD = os.path.dirname(os.path.abspath(__file__))
HOSTS = ['doraemon{:02d}'.format(i) for i in range(1,13)]
status_kw = ['Empty','Error?','Healthy','Unhealthy']
color_map = {status_kw[0]:'none', status_kw[1]:'red',status_kw[2]:'green',status_kw[3]:'yellow'}
color_map2 = {status_kw[0]:'white',status_kw[1]:'red',status_kw[2]:'lime', status_kw[3]:'yellow'}
interval = args.interval #second
time_range = args.time_range #second
s = ' '*4
README = f"""
こんにちは！より効率的に計算サーバーを使うために、このGPUモニタリングを作りました。<br><br>
現在約{interval/60:0.1f}分ごとに更新します。表示範囲は約{time_range/3600:0.1f}時間です。<br>
<b>Memory</b>: GPUメモリ使用量, <b>Usage</b>:GPU計算使用率<br>
<h4>そして、ご参考にGPU使用状況を簡単に分析しました。リソースの無駄遣いはダメです🙁</h4>
<font color="black">{s}<b>{status_kw[0]}</b></font>: 使用していません<br>
<font color="lime">{s}<b>{status_kw[2]}</b></font>: (usage>15%) 効率的に使ってます！👍<br>
<font color="gold">{s}<b>{status_kw[3]}</b></font>: (usage<15%) 計算の効率が悪い, プログラムの改善をおすすめ🤔<br>
<font color="red">{s}<b>{status_kw[1]}</b></font>: (usage≈0%) メモリは使ってるが、GPUは動いてない。ジョブのチェックお願いします🙏<br>
<br>
"""
ACKNOWLEDGE = f"""
<br> PS1: You can focus on single manchine using <i>Filter text</i>.
<br> PS2: Please dont change env <b>'GPUs'</b> in Environment setting!
<br> PS3: If you accidently closed the window, it will appear after {interval} seconds.
<br><br> Driven by <a href='https://ai.facebook.com/tools/visdom/'><b>Visdom</b></a>, coded by <b>CL.Wang</b>
"""
logger = GPU_logger(HOSTS, interval, time_range,
show_summary=True,
show_monitor=True,
show_cpu_mem=True,
env_name=args.env, verbose=False)
try:
logger.record()
except KeyboardInterrupt:
logger.save(PWD)
logger.reset()
except Exception as e:
logger.save(PWD)
logger.reset()
#exc_type, exc_obj, exc_tb = sys.exc_info()
logger.viz.text(f"GPU monitor crashed at \
{time.strftime('%Y/%m/%d-%H:%M:%S')}!\n \
{e}", env=logger.env)