CubelaPetarandClaude Fable 5
43054f32b8
- run.yml: base plays (geerlingguy.security) for jira and git; gpu01 play with security + docker + nvidia_gpu - roles/nvidia_gpu: driver pinned >=580 (Blackwell), CUDA repo, container toolkit incl. the nvidia-ctk runtime configure step - manuals/20260714-nvidia-driver-install.md: dated per convention, corrected (pinned -server driver instead of autoinstall+cuda-drivers mix, toolkit optional, added missing nvidia-ctk/docker restart step) - gpu01 folder: planning docs under notes/, runbooks under manuals/, scripts/; convention documented in CLAUDE.md - scripts/share-analysis.ps1: read-only SMB share analysis for the Windows server (projektplan §2.1) - TODO.md: Phase-0 pre-work items from the projektplan Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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Manual nvidia driver, cuda repo and container toolkit
Automated by the Ansible role ansible/roles/nvidia_gpu — this manual documents the steps.
Disable Secure Boot in BIOS first (unsigned kernel modules won't load otherwise).
NVIDIA driver
Check if GPUs are recognized by the base OS:
sudo lspci | grep -i nvidia
Which should show some output if it finds nvidia devices.
Search for available drivers for your GPUs:
sudo ubuntu-drivers devices
Install the driver pinned. The RTX PRO 6000 (Blackwell) needs driver >= 580;
use the -server variant and prefer a pinned install over ubuntu-drivers autoinstall
so the choice is explicit and reproducible (re-check for a newer branch at install time):
sudo apt install -y nvidia-driver-580-server
Note: do not additionally install
cuda-driversfrom the NVIDIA repo — that would mix the Ubuntu-archive driver with the NVIDIA-repo driver and the two can conflict. Pick one source; we use the Ubuntu archive.
Reboot the system for changes to take effect:
sudo reboot
Show GPU stats with:
nvidia-smi
CUDA repository (toolkit optional)
Add the NVIDIA CUDA apt repository:
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2404/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt update
The full CUDA toolkit is not needed for Docker-based workloads (vLLM etc. — the driver plus container toolkit suffice). Only if compiling on the host:
sudo apt install -y cuda-toolkit # meta package, pulls the current release
Container toolkit
Install the Nvidia Container toolkit:
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/stable/deb/nvidia-container-toolkit.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 update
sudo apt install -y nvidia-container-toolkit
Configure Docker to use the NVIDIA runtime (writes /etc/docker/daemon.json) and restart it —
without this step docker run --gpus all fails:
sudo nvidia-ctk runtime configure --runtime=docker
sudo systemctl restart docker
Test a simple cuda container and nvidia-smi command inside:
docker run --rm --gpus all nvidia/cuda:13.0.0-base-ubuntu24.04 nvidia-smi