cpu利用率控制脚本：/data/nlu/cpu_tools/test_image_cpu.py

import os
import threading
import multiprocessing
import argparse
def dead_circle(n):
    i = n
    while True:
        i += 1
        n = i * (i + 1)
        m = n * (n + 1)
        l = m * n + i
        if i == 5000000:
            i = 0

parser = argparse.ArgumentParser()
parser.add_argument(
    "--cores",
    type=int,
    default=5,
    help="core nums")
flags, unparsed = parser.parse_known_args()
for i in range(flags.cores):
   # t = threading.Thread(target=dead_circle,args=(i,))
   # t.start()
    p = multiprocessing.Process(target=dead_circle,args=(i,))
    p.start()

启动脚本 /data/nlu/cpu_tools/start.sh

#! /bin/sh 
num=10   # python脚本中默认跑5个核，32核的机器cpu利用率大概能到15%，可根据自己机器的核数设定数值来调整cpu利用率
cd /data/nlu/cpu_tools
nohup python test_image_cpu.py --cores ${num} & 2>&1 

停止脚本 /data/nlu/cpu_tools/stop.sh

#! /bin/sh 
ps -ef | grep test_image_cpu | grep -v grep | awk '{print $2}' | xargs kill -9

定时任务提高cpu利用率

cpu_idle=`top -b -n 1 | grep Cpu | awk '{print int($8)}'`
current_time=`date +%H`
num=10
process_num=`ps -ef | grep test_image_cpu  | grep -v grep  | wc -l`

if [ ${current_time} -gt 15 -a ${current_time} -lt 20 -a ${cpu_idle} -gt 80 ]; then
	if [ ${process_num} -eq 0 ]; then
		cd /home/home/nlu
		nohup python test_image_cpu.py --cores ${num} & 2>&1 
	fi
else
	if [ ${process_num} -gt 0 ]; then
		ps -ef | grep test_image_cpu  | grep -v grep  | awk '{print $2}' | xargs kill -9
	fi
fi

参考：
1.性能监控：shell脚本获取cpu/内存/IO数据