tao-setup-nvidia-gpu-host
NVIDIA/skills
Checks and installs NVIDIA driver, CUDA Toolkit, and NVIDIA Container Toolkit for GPU-accelerated Docker and Kubernetes hosts. Supports multiple Linux distributions with automated install and read-only check modes.
...Expand allNVIDIA GPU Host Setup
Use this setup skill before TAO workflows run on the docker, local-docker,
or kubernetes backend. It standardizes the host GPU runtime on:
- NVIDIA driver branch
580(open kernel module preferred) - CUDA Toolkit package
cuda-toolkit-13-0 - NVIDIA Container Toolkit
1.19.0 - Docker engine — only installed for
docker/local-dockerbackends and only when Docker is missing. The package picked depends on the distro family (docker.ioon Debian-family by default,moby-engine/docker-cefromdownload.docker.comon RHEL-family,dockeron SUSE-family). Pass--skip-docker-installto opt out.
The check is safe and read-only by default — it works on any Linux
distribution because it only probes nvidia-smi, the CUDA toolkit path,
the installed container-toolkit package version (via dpkg/rpm/the
nvidia-ctk binary version), and the Docker daemon's NVIDIA runtime.
Installation must be explicitly authorized by the user and rerun with
--install. The install path is automated for these distro families:
| Family | Tested distros | Manager | Notes |
|---|---|---|---|
| debian | Ubuntu 22.04 / 24.04, Debian 12 (and derivatives Pop!_OS, Mint, Zorin, Raspbian, KDE Neon, etc. via UBUNTU_CODENAME / VERSION_CODENAME) |
apt-get |
Adds NVIDIA cuda-keyring + Container Toolkit .list. Docker via docker.io (override $DOCKER_PACKAGE_DEBIAN). |
| rhel | Fedora 39+, RHEL / Rocky / AlmaLinux 9 and 10 | dnf (or yum) |
Adds NVIDIA cuda- + Container Toolkit .repo. Docker via Fedora moby-engine when available, otherwise docker-ce from download.docker.com. |
| suse | openSUSE Leap 15, SLES 15 | zypper |
Adds the same NVIDIA .repo files. Docker via the distribution docker package. |
| other (Arch, Alpine, Gentoo, NixOS, FreeBSD, …) | n/a | n/a | --install exits with a clear error listing the version targets and the NVIDIA install-guide URLs. Install manually, then rerun --check-only. |
Quick Start
From the skill bank root:
# Check the local Docker backend host.
bash skills/platform/tao-setup-nvidia-gpu-host/scripts/setup-nvidia-gpu-host.sh --backend docker --check-only
# Install or repair after user approval.
bash skills/platform/tao-setup-nvidia-gpu-host/scripts/setup-nvidia-gpu-host.sh --backend docker --install
# Check a Kubernetes GPU worker host.
bash skills/platform/tao-setup-nvidia-gpu-host/scripts/setup-nvidia-gpu-host.sh --backend kubernetes --check-only
⚠️ Note — running non-interactively (agent/skill runs): a skill run has no terminal, so the installer's
Continue? [y/N]prompt cannot be answered. After running--check-onlyto preview and getting the user's approval, append the assume-yes flag (--yes) to the--installcommand so it proceeds without a prompt — this auto-confirms installation of system packages (NVIDIA driver, CUDA Toolkit, NVIDIA Container Toolkit, and Docker for Docker backends) and modifies the host, so only do this on a host you control. A person running--installdirectly at a terminal gets the prompt instead.
Workflow Contract
Docker and Kubernetes workflows must run the check before submitting GPU work:
SETUP_SCRIPT="${TAO_SKILL_BANK_ROOT:-$PWD}/platform/tao-setup-nvidia-gpu-host/scripts/setup-nvidia-gpu-host.sh"
bash "$SETUP_SCRIPT" --backend docker --check-only || {
echo "MISSING: TAO GPU host runtime is not ready."
echo "After user approval, run (append --yes for non-interactive agent runs):"
echo " bash \"$SETUP_SCRIPT\" --backend docker --install"
exit 1
}
Never install silently. If the check fails, explain what is missing, ask the user to authorize the fix, then run the install command and rerun the check.
What The Installer Does
The installer dispatches on the detected distribution family. On every
supported family it adds NVIDIA's CUDA and Container Toolkit repositories
(if missing), installs the pinned runtime packages, optionally installs
Docker, wires the NVIDIA Docker runtime, and adds the invoking user to
the docker group.
Common steps (all families):
- Adds NVIDIA's CUDA repository if missing (apt
cuda-keyringdeb,cuda-for dnf/zypper)..repo - Adds NVIDIA's Container Toolkit repository if missing (
.listfor apt,.repofor dnf/zypper). - Installs the matching kernel header / devel package for the running kernel.
- Installs the driver branch 580 packages,
cuda-toolkit-13-0, and the Container Toolkit pinned to1.19.0(the dpkg-suffixed1.19.0-1is the same upstream version expressed for apt). - For Docker backends and when Docker is missing, installs Docker
(override / opt-out flags below), enables/starts the daemon, then runs
nvidia-ctk runtime configure --runtime=dockerand restarts Docker whensystemctlis available. - Adds the invoking user (
$SUDO_USERif available, else$USER) to thedockergroup so subsequent shells can rundockerwithoutsudo— opt out with--skip-docker-group. The new group membership does not take effect in the current shell: log out and back in, or runnewgrp dockerin each new shell. - Attempts
modprobe nvidiaso verification can pass before reboot.
Family-specific package selections:
| Step | debian-family | rhel-family | suse-family |
|---|---|---|---|
| Kernel headers | linux-headers-$(uname -r) |
kernel-devel-$(uname -r), kernel-headers-$(uname -r) |
kernel-default-devel |
| Driver | nvidia-driver-pinning-580, nvidia-open-580 (override: $NVIDIA_DRIVER_PACKAGE_DEBIAN) |
nvidia-driver-cuda, kmod-nvidia-open-dkms (override: $NVIDIA_DRIVER_PACKAGE_RHEL, $NVIDIA_DRIVER_KMOD_RHEL) |
nvidia-open-driver-G06-signed-kmp-default (override: $NVIDIA_DRIVER_PACKAGE_SUSE) |
| CUDA toolkit | cuda-toolkit-13-0 |
cuda-toolkit-13-0 |
cuda-toolkit-13-0 |
| Container Toolkit | nvidia-container-toolkit=1.19.0-1 + base/tools/libs |
nvidia-container-toolkit-1.19.0 + base/tools/libs |
same as rhel |
| Docker | docker.io (override: $DOCKER_PACKAGE_DEBIAN) |
moby-engine+moby-cli on Fedora when available, else docker-ce docker-ce-cli containerd.io from download.docker.com |
docker |
Verification
After installation, verify:
nvidia-smi
/usr/local/cuda-13.0/bin/nvcc --version
docker info --format '{{json .Runtimes}}' | grep nvidia
sudo docker run --rm --runtime=nvidia --gpus all ubuntu nvidia-smi
Expected nvidia-smi output includes driver 580.x and CUDA Version 13.0.
Expected nvcc output includes release 13.0.
Kubernetes Notes
For self-managed Kubernetes clusters, run the host installer on every GPU worker node or bake the same package set into the node image before installing the NVIDIA GPU Operator or device plugin.
The workflow check also warns if kubectl is available but the cluster reports
no nvidia.com/gpu allocatable capacity. In that case, install/configure the
NVIDIA GPU Operator after the worker host runtime is ready:
helm repo add nvidia https://helm.ngc.nvidia.com/nvidia
helm repo update
helm install --wait gpu-operator -n gpu-operator --create-namespace nvidia/gpu-operator
Managed Kubernetes providers may own driver installation through node images or GPU Operator policy. Do not overwrite a provider-managed GPU node without user approval and a rollback plan.
Failure Modes
Unsupported distribution family: --install automates debian-, rhel-,
and suse-family hosts. On Arch, Alpine, Gentoo, NixOS, FreeBSD, or anything
without /etc/os-release (e.g. macOS), the script exits with a clear error
that lists the four version targets and the upstream NVIDIA install-guide
URLs:
https://docs.nvidia.com/cuda/cuda-installation-guide-linux/https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.htmlhttps://docs.docker.com/engine/install/
Install those four pieces using your distribution's package manager and
rerun the script with --check-only to verify. The check is universally
portable — it only queries the binaries / package databases — so once the
runtime is in place the workflow contract is satisfied regardless of the
underlying distro.
Unsupported Ubuntu/Debian derivative: When ID is e.g. pop, mint,
zorin, raspbian, or another debian-family derivative, the script maps
the host onto the upstream Ubuntu/Debian CUDA repo via UBUNTU_CODENAME /
VERSION_CODENAME (focal/jammy/noble → Ubuntu 20.04/22.04/24.04;
bullseye/bookworm/trixie → Debian 11/12/12). If the host's codename
doesn't match a known upstream release, --install exits with the same
manual-install guidance described above.
Docker not installed: --check-only reports MISSING: Docker is not installed and prints the exact rerun command appropriate to the detected
distro family. The default --install path installs Docker (docker.io /
moby-engine / docker-ce / docker depending on family), enables/starts
the daemon, configures the NVIDIA runtime, and adds the invoking user to
the docker group. If you prefer to manage Docker yourself, install it
before rerunning the script or pass --skip-docker-install.
Docker installed but docker run still needs sudo: The script adds the
invoking user to the docker group, but Linux only refreshes group
membership on a new login session. Log out and back in, or run
newgrp docker in each new shell, until the new membership is active.
Docker runtime still missing: Restart Docker, then rerun
nvidia-ctk runtime configure --runtime=docker.
Driver branch detected != 580: The driver-branch pin is exact on
debian-family (nvidia-open-580). On rhel-/suse-family the script
installs the latest open driver shipped in NVIDIA's CUDA 13.0 repo for
the detected distro, which is always ≥ 580. If your host needs a stricter
pin, set $NVIDIA_DRIVER_PACKAGE_RHEL / $NVIDIA_DRIVER_KMOD_RHEL /
$NVIDIA_DRIVER_PACKAGE_SUSE to the exact package names you want before
running --install.
Driver installed but nvidia-smi fails: Load the module with
sudo modprobe nvidia or reboot. Secure Boot may require MOK enrollment on
systems where it is enabled.
Kubernetes still has no GPU capacity: Confirm the driver works on each GPU
node with nvidia-smi, then check the GPU Operator/device plugin pods and node
labels.
---
name: tao-setup-nvidia-gpu-host
description: Checks and installs NVIDIA driver, CUDA Toolkit, and NVIDIA Container Toolkit for GPU-accelerated Docker and Kubernetes hosts. Supports multiple Linux distributions with automated install and read-only check modes.
license: Apache-2.0
---
# NVIDIA GPU Host Setup
Use this setup skill before TAO workflows run on the `docker`, `local-docker`,
or `kubernetes` backend. It standardizes the host GPU runtime on:
- NVIDIA driver branch `580` (open kernel module preferred)
- CUDA Toolkit package `cuda-toolkit-13-0`
- NVIDIA Container Toolkit `1.19.0`
- Docker engine — only installed for `docker` / `local-docker` backends and
only when Docker is missing. The package picked depends on the distro
family (`docker.io` on Debian-family by default, `moby-engine` /
`docker-ce` from `download.docker.com` on RHEL-family, `docker` on
SUSE-family). Pass `--skip-docker-install` to opt out.
The check is safe and read-only by default — it works on any Linux
distribution because it only probes `nvidia-smi`, the CUDA toolkit path,
the installed container-toolkit package version (via `dpkg`/`rpm`/the
`nvidia-ctk` binary version), and the Docker daemon's NVIDIA runtime.
Installation must be explicitly authorized by the user and rerun with
`--install`. The install path is automated for these distro families:
| Family | Tested distros | Manager | Notes |
|---|---|---|---|
| debian | Ubuntu 22.04 / 24.04, Debian 12 (and derivatives Pop!_OS, Mint, Zorin, Raspbian, KDE Neon, etc. via `UBUNTU_CODENAME` / `VERSION_CODENAME`) | `apt-get` | Adds NVIDIA `cuda-keyring` + Container Toolkit `.list`. Docker via `docker.io` (override `$DOCKER_PACKAGE_DEBIAN`). |
| rhel | Fedora 39+, RHEL / Rocky / AlmaLinux 9 and 10 | `dnf` (or `yum`) | Adds NVIDIA `cuda-<distro>.repo` + Container Toolkit `.repo`. Docker via Fedora `moby-engine` when available, otherwise `docker-ce` from `download.docker.com`. |
| suse | openSUSE Leap 15, SLES 15 | `zypper` | Adds the same NVIDIA `.repo` files. Docker via the distribution `docker` package. |
| other (Arch, Alpine, Gentoo, NixOS, FreeBSD, …) | n/a | n/a | `--install` exits with a clear error listing the version targets and the NVIDIA install-guide URLs. Install manually, then rerun `--check-only`. |
## Quick Start
From the skill bank root:
```bash
# Check the local Docker backend host.
bash skills/platform/tao-setup-nvidia-gpu-host/scripts/setup-nvidia-gpu-host.sh --backend docker --check-only
# Install or repair after user approval.
bash skills/platform/tao-setup-nvidia-gpu-host/scripts/setup-nvidia-gpu-host.sh --backend docker --install
# Check a Kubernetes GPU worker host.
bash skills/platform/tao-setup-nvidia-gpu-host/scripts/setup-nvidia-gpu-host.sh --backend kubernetes --check-only
```
> ⚠️ **Note — running non-interactively (agent/skill runs):** a skill run has no terminal, so the
> installer's `Continue? [y/N]` prompt cannot be answered. After running `--check-only` to preview and
> getting the user's approval, append the assume-yes flag (`--yes`) to the `--install` command so it
> proceeds without a prompt — this auto-confirms installation of system packages (NVIDIA driver, CUDA
> Toolkit, NVIDIA Container Toolkit, and Docker for Docker backends) and modifies the host, so only do
> this on a host you control. A person running `--install` directly at a terminal gets the prompt instead.
## Workflow Contract
Docker and Kubernetes workflows must run the check before submitting GPU work:
```bash
SETUP_SCRIPT="${TAO_SKILL_BANK_ROOT:-$PWD}/platform/tao-setup-nvidia-gpu-host/scripts/setup-nvidia-gpu-host.sh"
bash "$SETUP_SCRIPT" --backend docker --check-only || {
echo "MISSING: TAO GPU host runtime is not ready."
echo "After user approval, run (append --yes for non-interactive agent runs):"
echo " bash \"$SETUP_SCRIPT\" --backend docker --install"
exit 1
}
```
Never install silently. If the check fails, explain what is missing, ask the
user to authorize the fix, then run the install command and rerun the check.
## What The Installer Does
The installer dispatches on the detected distribution family. On every
supported family it adds NVIDIA's CUDA and Container Toolkit repositories
(if missing), installs the pinned runtime packages, optionally installs
Docker, wires the NVIDIA Docker runtime, and adds the invoking user to
the `docker` group.
Common steps (all families):
1. Adds NVIDIA's CUDA repository if missing (apt `cuda-keyring` deb,
`cuda-<distro>.repo` for dnf/zypper).
2. Adds NVIDIA's Container Toolkit repository if missing (`.list` for apt,
`.repo` for dnf/zypper).
3. Installs the matching kernel header / devel package for the running
kernel.
4. Installs the driver branch 580 packages, `cuda-toolkit-13-0`, and the
Container Toolkit pinned to `1.19.0` (the dpkg-suffixed `1.19.0-1` is
the same upstream version expressed for apt).
5. For Docker backends and when Docker is missing, installs Docker
(override / opt-out flags below), enables/starts the daemon, then runs
`nvidia-ctk runtime configure --runtime=docker` and restarts Docker
when `systemctl` is available.
6. Adds the invoking user (`$SUDO_USER` if available, else `$USER`) to the
`docker` group so subsequent shells can run `docker` without `sudo` —
opt out with `--skip-docker-group`. **The new group membership does not
take effect in the current shell**: log out and back in, or run
`newgrp docker` in each new shell.
7. Attempts `modprobe nvidia` so verification can pass before reboot.
Family-specific package selections:
| Step | debian-family | rhel-family | suse-family |
|---|---|---|---|
| Kernel headers | `linux-headers-$(uname -r)` | `kernel-devel-$(uname -r)`, `kernel-headers-$(uname -r)` | `kernel-default-devel` |
| Driver | `nvidia-driver-pinning-580`, `nvidia-open-580` (override: `$NVIDIA_DRIVER_PACKAGE_DEBIAN`) | `nvidia-driver-cuda`, `kmod-nvidia-open-dkms` (override: `$NVIDIA_DRIVER_PACKAGE_RHEL`, `$NVIDIA_DRIVER_KMOD_RHEL`) | `nvidia-open-driver-G06-signed-kmp-default` (override: `$NVIDIA_DRIVER_PACKAGE_SUSE`) |
| CUDA toolkit | `cuda-toolkit-13-0` | `cuda-toolkit-13-0` | `cuda-toolkit-13-0` |
| Container Toolkit | `nvidia-container-toolkit=1.19.0-1` + base/tools/libs | `nvidia-container-toolkit-1.19.0` + base/tools/libs | same as rhel |
| Docker | `docker.io` (override: `$DOCKER_PACKAGE_DEBIAN`) | `moby-engine`+`moby-cli` on Fedora when available, else `docker-ce docker-ce-cli containerd.io` from `download.docker.com` | `docker` |
## Verification
After installation, verify:
```bash
nvidia-smi
/usr/local/cuda-13.0/bin/nvcc --version
docker info --format '{{json .Runtimes}}' | grep nvidia
sudo docker run --rm --runtime=nvidia --gpus all ubuntu nvidia-smi
```
Expected `nvidia-smi` output includes driver `580.x` and CUDA Version `13.0`.
Expected `nvcc` output includes `release 13.0`.
## Kubernetes Notes
For self-managed Kubernetes clusters, run the host installer on every GPU
worker node or bake the same package set into the node image before installing
the NVIDIA GPU Operator or device plugin.
The workflow check also warns if `kubectl` is available but the cluster reports
no `nvidia.com/gpu` allocatable capacity. In that case, install/configure the
NVIDIA GPU Operator after the worker host runtime is ready:
```bash
helm repo add nvidia https://helm.ngc.nvidia.com/nvidia
helm repo update
helm install --wait gpu-operator -n gpu-operator --create-namespace nvidia/gpu-operator
```
Managed Kubernetes providers may own driver installation through node images or
GPU Operator policy. Do not overwrite a provider-managed GPU node without user
approval and a rollback plan.
## Failure Modes
**Unsupported distribution family**: `--install` automates debian-, rhel-,
and suse-family hosts. On Arch, Alpine, Gentoo, NixOS, FreeBSD, or anything
without `/etc/os-release` (e.g. macOS), the script exits with a clear error
that lists the four version targets and the upstream NVIDIA install-guide
URLs:
- `https://docs.nvidia.com/cuda/cuda-installation-guide-linux/`
- `https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html`
- `https://docs.docker.com/engine/install/`
Install those four pieces using your distribution's package manager and
rerun the script with `--check-only` to verify. The check is universally
portable — it only queries the binaries / package databases — so once the
runtime is in place the workflow contract is satisfied regardless of the
underlying distro.
**Unsupported Ubuntu/Debian derivative**: When `ID` is e.g. `pop`, `mint`,
`zorin`, `raspbian`, or another debian-family derivative, the script maps
the host onto the upstream Ubuntu/Debian CUDA repo via `UBUNTU_CODENAME` /
`VERSION_CODENAME` (`focal`/`jammy`/`noble` → Ubuntu 20.04/22.04/24.04;
`bullseye`/`bookworm`/`trixie` → Debian 11/12/12). If the host's codename
doesn't match a known upstream release, `--install` exits with the same
manual-install guidance described above.
**Docker not installed**: `--check-only` reports `MISSING: Docker is not
installed` and prints the exact rerun command appropriate to the detected
distro family. The default `--install` path installs Docker (`docker.io` /
`moby-engine` / `docker-ce` / `docker` depending on family), enables/starts
the daemon, configures the NVIDIA runtime, and adds the invoking user to
the `docker` group. If you prefer to manage Docker yourself, install it
before rerunning the script or pass `--skip-docker-install`.
**Docker installed but `docker run` still needs sudo**: The script adds the
invoking user to the `docker` group, but Linux only refreshes group
membership on a new login session. Log out and back in, or run
`newgrp docker` in each new shell, until the new membership is active.
**Docker runtime still missing**: Restart Docker, then rerun
`nvidia-ctk runtime configure --runtime=docker`.
**Driver branch detected != 580**: The driver-branch pin is exact on
debian-family (`nvidia-open-580`). On rhel-/suse-family the script
installs the latest open driver shipped in NVIDIA's CUDA 13.0 repo for
the detected distro, which is always ≥ 580. If your host needs a stricter
pin, set `$NVIDIA_DRIVER_PACKAGE_RHEL` / `$NVIDIA_DRIVER_KMOD_RHEL` /
`$NVIDIA_DRIVER_PACKAGE_SUSE` to the exact package names you want before
running `--install`.
**Driver installed but `nvidia-smi` fails**: Load the module with
`sudo modprobe nvidia` or reboot. Secure Boot may require MOK enrollment on
systems where it is enabled.
**Kubernetes still has no GPU capacity**: Confirm the driver works on each GPU
node with `nvidia-smi`, then check the GPU Operator/device plugin pods and node
labels.
Install tao-setup-nvidia-gpu-host
Download and extract the skill files to your .claude/skills/ directory.
Download ZIPClone the repository and copy the skill files to your project.
git clone https://github.com/NVIDIA/skills/tree/main/skills/tao-setup-nvidia-gpu-host # Copy SKILL.md to your .claude/skills/ directory
Copy





Home
