CubelaPetarandClaude Opus 4.8
75296ce58c
- rename host/group/folder everywhere to match the server's actual hostname and physical label - share-analysis.ps1: sanitize the output filename prefix — '-Paths "D:"' produced 'D:-file-types.csv' and Export-Csv failed with 'path format not supported', so no CSVs were written - share-analysis.ps1: new -FolderDepth so folders can be aggregated at D:\Abteilungen\<Share> level, which matches the share layout - list-shares.ps1: -WithSize walks local paths instead of UNC when run on the server itself (UNC was orders of magnitude slower and looked stuck) and prints progress every 50k files Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2.8 KiB
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
and only works with the open kernel modules — the proprietary ones load but
fail at RmInitAdapter, leaving nvidia-smi with "No devices were found".
Use the -server-open 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 --no-install-recommends nvidia-driver-595-server-open
--no-install-recommends keeps nvidia-settings and its GTK dependency chain
off this headless 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