Installing the PWstudio GPU version on Rocky Linux 8.10

Applies to: Rocky Linux 8.10
Includes: NVIDIA GPU driver, Docker, nvidia-container-toolkit

Before you start, we strongly recommend reading Read this before installing PWstudio first, especially the notes about “copy-paste” and “the command prompt is not part of the command.” If you don't yet know how to use a tool to log in to a server or upload/download files, read the MobaXterm beginner tutorial first.

The first command stops the firewall immediately; the second prevents it from starting automatically at boot:

sudo systemctl stop firewalld
sudo systemctl disable firewalld

These two commands normally produce no output, or just a brief message — as long as there's no error in red, they succeeded.

# Install the hardware inspection tool
sudo dnf install pciutils -y
 
# Detect the GPU
lspci | grep -i nvidia

The first command installs a small tool called pciutils (which includes the lspci command). If it's already installed, this command will just say something like “already up to date” — that's normal and doesn't stop you from continuing. The second command is the actual GPU check:

• There's output (a line containing “NVIDIA”): the system detected an NVIDIA GPU — continue on.
• No output at all: an NVIDIA GPU wasn't detected. Contact your administrator to confirm the hardware before continuing with the GPU driver install.

nvidia-smi

If you see the GPU model, driver version, CUDA version (CUDA Version: 12.1 or later), etc., the driver is already installed correctly, and you can skip straight to step 3, “Install Docker” — skipping 2.3~2.7 entirely. If it says “command not found” (no driver version detected), the driver isn't installed yet, so continue with 2.3~2.7 below.

# Install the development tools group
sudo dnf groupinstall "Development Tools" -y
 
# Install development packages matching the current kernel
sudo dnf install -y kernel-devel-$(uname -r) kernel-headers
 
# Enable the necessary repository
sudo dnf install epel-release -y
 
# Install DKMS, which helps rebuild the driver automatically after kernel updates
sudo dnf install -y dkms

The $(uname -r) in this command gets automatically substituted with your current kernel version — you don't need to manually change it to anything else (e.g. your own username). Just copy and paste the entire line exactly as it is.

We recommend copying and pasting these four commands together as a block. Each one will scroll through some package installation output as it runs — that's normal, as long as it finishes without a red Error.

sudo grubby --args="nouveau.modeset=0 rd.driver.blacklist=nouveau" --update-kernel=ALL
 
# Reboot to apply the change
sudo reboot

sudo reboot immediately reboots the server — this is expected and necessary. Your terminal connection will drop after this — that's normal, don't worry. Wait 1-2 minutes for the server to finish rebooting, then log back in to the server (using MobaXterm or a similar tool), and continue with 2.5.

# Enable the necessary repository
sudo dnf config-manager --set-enabled powertools
 
# Add the official NVIDIA repository
sudo tee /etc/yum.repos.d/cuda-rhel8.repo << 'EOF'
[cuda-rhel8-x86_64]
name=cuda-rhel8-x86_64
baseurl=https://developer.download.nvidia.com/compute/cuda/repos/rhel8/x86_64
enabled=1
gpgcheck=1
gpgkey=https://developer.download.nvidia.com/compute/cuda/repos/rhel8/x86_64/D42D0685.pub
EOF
 
# Enable the latest-dkms stream of the nvidia-driver module (DKMS is recommended)
sudo dnf module enable nvidia-driver:570-dkms -y
 
# Install the driver
sudo dnf install -y cuda-drivers

We recommend copying and pasting the sudo tee … « 'EOF' … EOF block as a single whole (from sudo tee all the way to the final EOF) rather than running it piece by piece, since it's writing a multi-line configuration file. After running it, the screen will print this content back out exactly as it is — that's normal, not an error. The final command, dnf install -y cuda-drivers, is what actually installs the driver; it downloads and installs quite a few packages, which may take a few minutes depending on your network speed — please be patient.

sudo reboot

Again, the connection will drop after this — that's normal. Wait 1-2 minutes, then log back in to the server.

nvidia-smi

Note that nvidia-smi has a hyphen in the middle and no space — we recommend copying and pasting it directly rather than typing it manually.

If you see a table with the GPU model, driver version, CUDA version, etc., the driver was installed successfully — continue to the next step. If it still says “command not found,” check whether the install process in 2.5 reported any errors.

# Install dependency tools
sudo dnf install -y dnf-utils device-mapper-persistent-data lvm2
 
# Add the official Docker repository (using an Alibaba Cloud mirror for speed)
sudo dnf config-manager --add-repo \
  https://mirrors.aliyun.com/docker-ce/linux/centos/docker-ce.repo

The second command adds a Docker package repository hosted on Alibaba Cloud's mirror to your system, which makes downloading Docker faster and more reliable afterward (less likely to time out due to accessing servers outside mainland China).

sudo dnf install -y docker-ce docker-ce-cli containerd.io

This installs Docker itself; it may take a minute or two depending on your network speed, and you'll see a lot of package information scroll by — that's normal.

If this step fails with a conflict involving podman (Rocky/CentOS 8 systems sometimes come with podman pre-installed), see q102: Docker install error on Rocky 8.10 for the fix.

sudo systemctl start docker
sudo systemctl enable docker

The first command starts the Docker service, the second sets it to start automatically at boot; these usually produce no output, or just a brief message — that's normal.

sudo docker run --rm swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/hello-world:latest

If you see text starting with “Hello from Docker!”, Docker was installed successfully.

sudo usermod -aG docker $USER

$USER is a system variable that automatically gets substituted with your current login username — no manual editing needed, just copy and paste it as-is.

Note: you need to log out and back in (or restart your session) for this to take effect — that is, after running this, exit first and then log back in to the server.

This step lets the Docker container use the NVIDIA GPU on the host machine.

If you're installing the PWstudio CPU version, please go back to the previous page.

sudo dnf install -y nvidia-container-toolkit

sudo nvidia-ctk runtime configure --runtime=docker

# Be sure to restart the Docker service for the configuration to take effect
sudo systemctl restart docker

Steps 4.2 and 4.3 only need to be run once — you don't need to redo them every time you use Docker; once configured, they stay in effect.

sudo docker run --rm --gpus all swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvidia/cuda:12.4.0-base-ubuntu22.04 nvidia-smi

If nvidia-smi inside the container produces normal output (GPU model, driver version, etc.), nvidia-container-toolkit was installed successfully and the container can now use the GPU.

Once all three pieces of base environment are installed, click the link to continue installing PWstudio itself, starting from “Install the server.py service on the host machine”: Go to "Install the server.py service on the host machine", and follow the guide through to the end.