monitor gpu memory usage

initializedMemory-usage: Memory UtilizationVolatile gpu-util: Floating GPU UtilizationUncorr. ECC: Something about ECCCompute M.: Calculation modeProcesses shows the memory usage per process on each GPU.Note: Video

When using TensorFlow to run deep learning, there is often a lack of memory, so we want to be able to view the GPU usage at any time. If you are the NVIDIA GPU, you can do this at the command line with just one line of command.1. Show current GPU usageNvidia comes with a NVI

9. Cuda shared memory use ------ GPU revolutionPreface: I will graduate next year and plan for my future life in the second half of the year. In the past six months, it may be a decision and a decision. Maybe I have a strong sense of crisis and have always felt that I have not done well enough. I still need to accumulate and learn. Maybe it's awesome to know that you can go to Hong Kong from the Hill Valley

viewing memory and CPUcommand to view memory usage separately: free-mTo view memory and CPU usage commands: TopYou can also install the Htop tool, which is more intuitive,The installation commands are as follows: sudo apt-get install htopAfter installation, direct input comm

| awk' {SSD = NF-4} {print $ SSD} ''// obtain the process's CPU usage.Echo "CPU:" $ CPU>/home/user/share/test/proc_memlog.txt // write the CPU usage rate to the proc_memlog.txt file.Echo $ blank>/home/user/share/test/proc_memlog.txt // write a blank row into the proc_memlog.txt FileSleep $ IntervalDone// Run the script2. Monitoring scriptRun the terminal, switch to the directory where the script is created, and enter sh./***. Sh // to

display of DataView is inaccurate.Workaround (Pending validation):1. Use the built-in Zabbix variable proc.cpu.util[2. Modify the commands in the script, using the following method instead:First, get the PID of the process name, and then combine top to run the following command:Top-b-n 1-p $pid 2>1 | Awk-v pid= $pid ' {if (= = pid) print $9} '3. Modify the commands in the script, using the following method instead:The PID of the process name is obtained first, and then the relevant data is read

# extract the IP address of the server IP = 'ifconfigeth0 | grep "inetaddr" | cut-f2-d ": "| cut-f1-d" "'# Take the percentage of the current idle cpu (only integer) cpu_idle = 'top-b-n1 | grepCpu | awk' {print $5} '| cut-f1-d ". "'# Set the alarm value of idle cpu to 20%. if the current cpu usage exceeds 80% (that is, the remaining cpu usage is less than 20%), send an email to send an alarm if ($ cpu_idle

" fuquanjun@xxx.com Fi # chmod a+x/scripts/cpu-warning.sh Monitor system memory using free command: 1, use the free command to view the Linux system memory usage: (in m) Copy Code code as follows: # free-m Total used free shared buffers Cached mem:3952 3414 538 0 168 484 -/+ buffe

Tags: shell#!/bin/bash#获取cpu使用率Cpuusage=top -n 1 | awk -F ‘[ %]+‘ ‘NR==3 {print $2}‘#获取磁盘使用率Data_name= "/DEV/VDA1"Diskusage=df -h | grep $data_name | awk -F ‘[ %]+‘ ‘{print $5}‘Logfile=/tmp/jiankong.log#获取内存情况Mem_total=free -m | awk -F ‘[ :]+‘ ‘NR==2{print $2}‘Mem_used=free -m | awk -F ‘[ :]+‘ ‘NR==3{print $3}‘#统计内存使用率Mem_used_persent=awk ‘BEGIN{printf "%.0f\n",(‘$mem_used‘/‘$mem_total‘)*100}‘#获取报警时间Now_time=date ‘+%F %T‘function Send_mail () {Mail-s "Monitoring Alarm" [email protected] }functio

Use the shell to monitor CPU, disk, memory usage, reach alert thresholds and email notificationsAnd with the task plan, you can get the alarm information in time#!/bin/bash############################################## #Author:liuzhengwei-[email Protected] #QQ: 1135960569#lastmodified:2017-04-1921:50#filename:jiankong.sh#description : ############################

Use the top command to dynamically monitor the memory usage of programs with very short running times Solution: Top-d 0.01-N2000-B | grep lzma -D specifies the interval at which top data is collected. The value is 0.01 seconds. -N indicates the total number of statistics. Set this parameter to 2000 to ensure that the top node does not end the statistics d

One of the best known advantages of Java technology is that, unlike other languages such as C programmers, Java programmers do not have to be responsible for daunting memory allocations and releases. The Java runtime can manage these tasks for you. Each instantiated object automatically allocates memory in the heap, and the garbage collector periodically reclaims the me