Ubuntu Server Preparation

To prepare a server on Ubuntu for the FindFace Multi deployment, follow the instructions below minding the sequence.

Note

For other platforms, please refer to the following resources:

In this section:

GPU: Install NVIDIA Drivers

The first step of the server preparation is the NVIDIA driver installation. It’s applicable only for the GPU configuration. Go straight to the Docker installation if your configuration is CPU-accelerated.

With the GPU-accelerated FindFace Multi, you’ll need the NVIDIA driver version 530 or above. Add the NVIDIA repository and install an applicable driver from it.

Warning

We do not recommend using a .run installer from NVIDIA Driver Downloads instead, as its drivers may conflict with the drivers installed by packages.

To install the 530 driver from a repository, do the following:

  1. Install the repository signature key:

    arch=$(uname -m); version=$(. /etc/os-release; echo $ID$VERSION_ID | sed -r 's/\.//g'); sudo bash -c \
"sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/$ID$version/$arch/3bf863cc.pub \
&& apt update"

  2. Install aptitude:

    sudo apt-get install aptitude

  3. Install nvidia-driver-530:

    sudo aptitude install nvidia-driver-530

  4. Reboot the system:

    sudo reboot

Install Docker Products

Docker products must be installed on both CPU and GPU servers. Do the following:

  1. Update the apt package index and install packages to allow apt to use a repository over HTTPS.

    sudo apt-get update

sudo apt-get install \
  ca-certificates \
  curl \
  gnupg \
  lsb-release

    Tip

    You may receive the following errors when running sudo apt-get install \:

    E: Could not get lock /var/lib/dpkg/lock-frontend - open (11: Resource temporarily unavailable)
E: Unable to acquire the dpkg frontend lock (/var/lib/dpkg/lock-frontend), is another process using it?

    There are two ways to resolve them:

    1. Forcibly terminate all the apt-get processes currently running in the system.

      sudo killall apt apt-get

    2. If the previous command didn’t help, run the set of commands below. It’s fine if some of the to-be-deleted directories do not exist — just keep going.

      sudo rm /var/lib/apt/lists/lock
sudo rm /var/cache/apt/archives/lock
sudo rm /var/lib/dpkg/lock
sudo rm /var/lib/dpkg/lock-frontend
sudo dpkg --configure -a

  2. Add the Docker’s official GPG key (GNU Privacy Guard key) to the host.

    sudo mkdir -m 0755 -p /etc/apt/keyrings
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /etc/apt/keyrings/docker.gpg

  3. Set up the Docker repository.

    echo \
  "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.gpg] https://download.docker.com/linux/ubuntu \
  $(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null

  4. Update the apt package index one more time.

    sudo apt-get update

    Tip

    If you have received a GPG error when running this command, try granting read permission for the Docker public key file before updating the package index.

    sudo chmod a+r /etc/apt/keyrings/docker.gpg
sudo apt-get update

  5. Install 24.* versions of Docker products.

    sudo apt-get install docker-ce=5:24* docker-ce-cli=5:24* containerd.io docker-buildx-plugin

  6. Check whether the Docker installation was a success. The following command downloads a test image and runs it in a container. When the container runs, it prints a confirmation message and exits.

    sudo docker run hello-world

Unable to find image 'hello-world:latest' locally
latest: Pulling from library/hello-world
2db29710123e: Pull complete
Digest: sha256:aa0cc8055b82dc2509bed2e19b275c8f463506616377219d9642221ab53cf9fe
Status: Downloaded newer image for hello-world:latest

Hello from Docker!
This message shows that your installation appears to be working correctly.

To generate this message, Docker took the following steps:
1. The Docker client contacted the Docker daemon.
2. The Docker daemon pulled the "hello-world" image from the Docker Hub.
   (amd64)
3. The Docker daemon created a new container from that image which runs the
   executable that produces the output you are currently reading.
4. The Docker daemon streamed that output to the Docker client, which sent it
   to your terminal.

To try something more ambitious, you can run an Ubuntu container with:
$ docker run -it ubuntu bash

Share images, automate workflows, and more with a free Docker ID:
https://hub.docker.com/

For more examples and ideas, visit:
https://docs.docker.com/get-started/

  7. Install docker-compose.

    sudo curl -SL https://github.com/docker/compose/releases/download/v2.15.1/docker-compose-linux-x86_64 -o /usr/local/bin/docker-compose
sudo chmod +x /usr/local/bin/docker-compose
sudo ln -s /usr/local/bin/docker-compose /usr/bin/docker-compose

  8. Perform the Docker Engine post-installation procedures to ease your future work with Docker and FindFace Multi containers. Once you can manage Docker as a non-root user, you don’t have to apply sudo in the commands related to Docker.

    sudo groupadd docker
sudo usermod -aG docker $USER
newgrp docker

  9. Configure the Docker network.

    sudo su
BIP=10.$((RANDOM % 256)).$((RANDOM % 256)).1
cat > /etc/docker/daemon.json <<EOF
{
    "bip": "$BIP/24",
    "fixed-cidr": "$BIP/24"
}
EOF

GPU: Install NVIDIA Container Runtime

To deploy containerized GPU-accelerated FindFace Multi, you need NVIDIA Container Runtime. We recommend installing NVIDIA Container Toolkit that includes this runtime. Do the following:

  1. Specify the repository and install NVIDIA Container Toolkit from it by executing the following commands.

    distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \
      && curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \
      && curl -s -L https://nvidia.github.io/libnvidia-container/$distribution/libnvidia-container.list | \
            sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
            sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
sudo apt-get update
sudo apt-get install -y nvidia-container-toolkit
sudo nvidia-ctk runtime configure --runtime=docker
sudo systemctl restart docker

  2. Configure the Docker network. Configure usage of the NVIDIA Container Runtime installed along with NVIDIA Container Toolkit.

    sudo su
BIP=10.$((RANDOM % 256)).$((RANDOM % 256))
cat > /etc/docker/daemon.json <<EOF
{
   "default-address-pools":
        [
                {"base":"$BIP.0/16","size":24}
        ],
    "bip": "$BIP.1/24",
    "fixed-cidr": "$BIP.0/24",
    "runtimes": {
         "nvidia": {
             "path": "nvidia-container-runtime",
             "runtimeArgs": []
         }
    },
    "default-runtime": "nvidia"
}
EOF

  3. Restart Docker.

    systemctl restart docker

Now you are all set to install FindFace Multi. Refer to the following sections: