1. Complete this form to create a VPN account
2. Forward your request through your faculty in charge.
   Mention the requirement and the duration for which VPN access is needed in the request.
3. Inform CNC via email, once you’ve completed both forms.

*** Complete this form to enable VPN access to a particular computer (after discussing with the faculty managing the computer)

Windows

Step 1: Open Command Prompt as Administrator.

Step 2: Configure the NTP server:

w32tm /config /manualpeerlist:"ntp.nitc.ac.in" /syncfromflags:manual /reliable:YES /update

Step 3: Restart the time service:

net stop w32time
net start w32time

Step 4: Verify synchronization:

w32tm /query /status

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Ubuntu/Debian

Step 1: Install the NTP client:

sudo apt update
sudo apt install ntp -y

Step 2: Configure the NTP server:

sudo nano /etc/ntp.conf

Add the following line:

server ntp.nitc.ac.in iburst

Step 3: Restart the NTP service:

sudo systemctl restart ntp

Step 4: Verify synchronization:

ntpq -p

1. Submit User Creation Form
   • Fill out the GPU Server Access Request Form (provided CCC Website).
   • Submit the form to the NITC admin team for approval.
   • Once approved, you will receive your username and temporary password via email.
2. Connect to the Server
   • Open a terminal on your local machine.
   • Use SSH to connect to the server:
     

     ssh <your-username>@<server-ip>

   • Enter your password when prompted.
3. Check GPU Availability (This will display GPU usage, memory, and active processes.)
   

   nvidia-smi

4. Using Docker on the GPU Server ( Since the server runs Docker, you need to pull or create a container for your tasks. )
   • List Available Docker Images

     docker images

   • Run a Container with GPU Access

     docker run --gpus all -it <image-name> bash

5. Run Your Code on GPU
6. Logout and Cleanup
   • When you're done.Exit the Docker container

     exit

   • Logout from the server

     logout

   • If running background processes, check with docker ps and stop containers if necessary

     docker stop <container-id>