I’ve been using a GPU workstation with an RTX 4090 for almost a year now, and it’s been one of the best decisions I’ve made. With a personal GPU server, you no longer need to rely on cloud-based GPU instances from services like RunPod or Vast.ai every time you want to run a job or try new models. The best part? No stress about recurring GPU instance costs! :-)

However, I rarely work directly on my workstation. Instead, I prefer the flexibility of accessing the GPU remotely using my MacBook, whether I’m working from different locations within my home, from a co-working space, or a cozy cafe in another part of town.

In this blog, I will walk you through the steps to configure a personal GPU Ubuntu server.

For this guide, I assume you already have a workstation running Ubuntu with a GPU and it is connected to your local network

Setting Up Local Remote Access

Let’s start by setting up local access, which will allow you to ssh into your GPU server when you’re on the same home Wi-Fi network. This is ideal for a work-from-home (WFH) setup where your workstation is running in a corner of your living space.

  1. Install the SSH server

    First, we need to install an SSH (Secure Shell) server. This will allow you to securely access your GPU machine remotely. Open a terminal on your Ubuntu machine and run the following commands:

     sudo apt update &&
     sudo apt install openssh-server
    

    This command updates your package lists and installs the OpenSSH server.

  2. Start and Enable SSH Service

    Next, enable the SSH service using this command:

     sudo systemctl enable --now ssh
    

    You can verify if the service is enabled by running:

     sudo systemctl status ssh
    

    Look for a line starting with Active: active (running) for ssh.service. This indicates that the SSH service is up and running.

    Note: The OpenSSH server starts running on boot by default.

  3. Configure the firewall

    To allow SSH connections through the system firewall, you need to open the appropriate port. Ubuntu’s default firewall, UFW (Uncomplicated Firewall), makes this process straightforward:

     sudo ufw allow ssh
    

    This command adds an exception to your firewall rules, permitting incoming SSH connections. You can check the SSH status with:

     sudo ufw status
    

    You should see the output similar to:

     To                         Action      From
     --                         ------      ----
     22/tcp                     ALLOW       Anywhere
     22/tcp(v6)                 ALLOW       Anywhere (v6)
    
  4. Connect to the local server

    Now that your GPU server is set up, it’s time to test the connection. From your laptop (which should be on the same local network as your GPU machine), open a terminal and use the following command:

     ssh user@local-ip-address
    

    Replace user with your Ubuntu user and local-ip-address with the IP address of your GPU machine on the local network.

    • To find your username on the workstation, you can use the whoami command.
    • To find your local IP address, use one of these methods on your workstation:
      • Run hostname -I and use the first address listed.
      • Use ip addr show | grep -w inet for more detailed network information.
      • How to find my IP address on Ubuntu Linux is a great blog on it. It explains multiple commands like ip addr show | grep -w inet or networkctl status to get the local IP address.

    Your local IP address typically starts with 192.168.

    Note: If your router dynamically changes the local IP address of your workstation, it’s best to log into your router and assign a fixed local IP address to ensure consistent access.

    If everything is configured correctly, you’ll be prompted to enter your password, after which you’ll gain remote access to your GPU server.

  5. Set Up SSH Keys for Passwordless Login

    It is recommended to set up key-based authentication for better security and convenience purposes. This allows you to connect to your remote server without entering a password each time.

    • It is quite common to setup ssh key-based authentication.
    • For detailed instructions on setting up SSH keys, refer to the DigitalOcean guide on Setting up SSH keys on Ubuntu 20.04.

Setting Up External Remote Access

While local access is great for working within your home network, sometimes you need to access your GPU workstation from outside your local network, such as from co-working spaces or a cozy cafe.

One simple and secure way to achieve this is by using ngrok.

ngrok helps creates secure tunnels from public endpoints to locally running services. It allows you to expose your personal server to the internet, enabling remote access from anywhere without complex network configurations.

Here’s how to set it up:

  1. Install ngrok

    First, you need to install ngrok on your GPU workstation. Open a terminal and run this command:

     snap install ngrok
    
    • For more installation options, see https://dashboard.ngrok.com/get-started/setup/linux.
  2. Create and connect to ngrok Account

    Visit ngrok’s website and sign up for a free account if you haven’t already. After signing up, you’ll receive an auth token. On your GPU workstation, run:

     ngrok config add-authtoken YOUR_AUTH_TOKEN
    

    You can get the config file path and edit using ngrok config check and vim <path>, respectively.

  3. Start the ngrok Tunnel

    Now, you can create a secure tunnel to your SSH service:

     ngrok tcp 22
    

    This command will display a URL that looks like tcp://X.tcp.ngrok.io:PORT. Note down this URL.

  4. Connect to Your Workstation

    From any external laptop, you can now SSH into your GPU workstation using:

     ssh -p YYYY user@X.tcp.ngrok.io
    

    Replace PORT with the port number and X with the subdomain from the ngrok URL. Replace user with your Ubuntu username.

    The above steps ensure that you can remotely access the workstation from external network. However, no one is going to manually start the ngrok every time before heading out.

  5. Make ngrok start automatically on boot

    To ensure ngrok starts automatically when your workstation boots:

    • Create a new service file:
     sudo vim /etc/systemd/system/ngrok.service
    
    • Add the following content:
     [Unit]
     Description=start ngrok tunnel on startup
     After=network.target
    
     [Service]
     ExecStart=/snap/bin/ngrok tcp 22
     Restart=on-failure
     User=<your_username>
    
     [Install]
     WantedBy=multi-user.target
    

    Replace <your_username> with your Ubuntu username. Save the file and exit the editor.

    • Enable and start the service:
     sudo systemctl enable ngrok.service
     sudo systemctl start ngrok.service
    

    Now ngrok will automatically start and create a tunnel when your workstation boots.

    Note: With a free account, ngrok assigns a new port (YYYY) each time your workstation boots. You can get the new port from the ngrok dashboard.

  6. Paid ngrok account for dedicated port

    For a dedicated TCP endpoint port that doesn’t change on reboot, you need a paid ngrok personal account ($10/month).

    a. Reserve a tcp endpoint

    Once you have a paid account, reserve a TCP endpoint at https://dashboard.ngrok.com/cloud-edge/tcp-addresses.

    b. Update the ngrok service file

    Add the following content:

     [Unit]
     Description=start ngrok tunnel on startup
     After=network.target
    
     [Service]
     ExecStart=/snap/bin/ngrok tcp --region=<region> --remote-addr=<remote-address> 22
     Restart=on-failure
     User=<your_username>
    
     [Install]
     WantedBy=multi-user.target
    

    Replace <region>, <remote-address>, and <your_username> with the appropriate values from your reserved TCP endpoint config.

With this setup, your SSH remote endpoint will remain the same even if the system reboots.

  1. Ubuntu SSH Documentation
  2. DigitalOcean Guide on Setting Up SSH Keys
  3. ngrok Documentation
  4. IP Address Information for Ubuntu
  5. UFW (Uncomplicated Firewall) Guide

Thanks for reading! If you have any questions or feedback, please let me know on Twitter or LinkedIn.