Ubuntu Nvidia Gpu Enablement

Ubuntu NVIDIA GPU Enablement

Bring a fresh UEFI Ubuntu server with NVIDIA GPUs to a serving-ready state. Order matters: driver → IOMMU cmdline → CUDA → persistence → container access → verify. Driver and cmdline changes each need a reboot — batch them (Steps 1 + 2 reboot together).

Run as a sudo user (over SSH is fine). [REFERENCE.md](REFERENCE.md) holds the why, GRUB/AMD variants, and troubleshooting. Boot-affecting steps are deliberate — keep BMC/console access as a fallback.

Pre-flight

• UEFI: [ -d /sys/firmware/efi ].
• Secure Boot: mokutil --sb-state. If enabled, DKMS modules need MOK enrollment at the console — plan

for it or disable SB. (Off is typical with a custom bootloader; verify, don't assume.)

• GPUs present: sudo apt-get install -y pciutils && lspci -nn | grep -i nvidia. Note the architecture.
• Bootloader = GRUB or ZFSBootMenu? (decides where the cmdline lives — Step 2.)
• Egress to archive.ubuntu.com (+ nvidia.github.io for the container repo).

Step 1 — Driver (OPEN kernel module)

sudo apt-get update
sudo apt-get install -y nvidia-driver-580-server-open   # example version

• Blackwell requires the open modules (proprietary won't support it); Hopper too. Pick the right branch

with ubuntu-drivers devices. Datacenter / "Server Edition" cards → nvidia-driver--server-open.

• Auto-blacklists nouveau; needs a reboot (do it with Step 2).
• Fabric Manager is only for NVLink/NVSwitch systems — skip it if your GPUs have no NVLink.

Step 2 — IOMMU kernel cmdline

Add intel_iommu=on iommu=pt (AMD: amd_iommu=on iommu=pt). iommu=pt = passthrough/identity DMA: ~zero bare-metal cost and preserves GPU P2P (full translation can disable P2P → NCCL falls back to SHM).

• GRUB: append to GRUB_CMDLINE_LINUX_DEFAULT in /etc/default/grub, then sudo update-grub.
• ZFSBootMenu (no GRUB): the cmdline is the ZFS property org.zfsbootmenu:commandline on the boot ROOT

dataset. Read-then-APPEND — never clobber existing tokens (e.g. zfs_force=1): ``bash cur=$(zfs get -H -o value org.zfsbootmenu:commandline rpool/ROOT) sudo zfs set org.zfsbootmenu:commandline="$cur intel_iommu=on iommu=pt" rpool/ROOT ``

• Reboot now (applies Steps 1 + 2 together).

Step 3 — CUDA toolkit

sudo apt-get install -y cuda-toolkit        # often already pulled by the driver

• nvcc is not on PATH by default — add it system-wide:

``bash printf 'export CUDA_HOME=/usr/local/cuda\nexport PATH=$CUDA_HOME/bin:$PATH\n' | sudo tee /etc/profile.d/cuda.sh ``

• ⚠️ On bleeding-edge Ubuntu (glibc ≥ 2.41), some CUDA versions can't compile C++ (rsqrt/rsqrtf header

clash). Serving is unaffected — prebuilt wheels use the driver + libcudart, not nvcc. See REFERENCE §3.

Step 4 — Persistence

sudo systemctl enable --now nvidia-persistenced

• ⚠️ Ubuntu ships the unit static → enable won't stick at boot. Force it:

``bash sudo install -d /etc/systemd/system/nvidia-persistenced.service.d printf '[Install]\nWantedBy=multi-user.target\n' | sudo tee /etc/systemd/system/nvidia-persistenced.service.d/install.conf sudo systemctl daemon-reload && sudo systemctl enable --now nvidia-persistenced ``

• ⚠️ nvidia-smi keeps showing Persistence-M: Disabled — that is correct. The daemon (not the

deprecated flag) provides persistence; do not "fix" it with nvidia-smi -pm 1.

Step 5 — Container access (optional)

5a — Container engine. The toolkit only wires an existing engine, so install one first. Docker's official docker-ce repo lags new Ubuntu releases by months — if it has no suite for your codename (curl -fsI download.docker.com/linux/ubuntu/dists/$(. /etc/os-release; echo $VERSION_CODENAME)/Release → 404/000, e.g. 26.04 resolute), install Ubuntu's own docker.io (current — 26.04 ships Docker 29.x). Both provide docker + the nvidia runtime hook.

sudo apt-get install -y docker.io          # or docker-ce once the repo carries your codename
sudo usermod -aG docker "$USER"            # rootless docker CLI — re-login to take effect

5b — NVIDIA repo + toolkit. Add the repo (REFERENCE §5), then EITHER:

• Full (required for Docker/containerd): sudo apt-get install -y nvidia-container-toolkit → nvidia-ctk
• an auto-generated CDI spec. Wire the engine, then restart it:

``bash sudo nvidia-ctk runtime configure --runtime=docker # or containerd sudo systemctl restart docker ` Adds only a runtimes.nvidia block to /etc/docker/daemon.json; default runtime stays runc (opt in per container with --gpus`). Podman needs no wiring (uses CDI directly).

• Minimal (enumeration only): sudo apt-get install -y libnvidia-container-tools → nvidia-container-cli.

5c — Verify the GPU reaches a container:

sudo docker run --rm --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all ubuntu:24.04 nvidia-smi -L   # lists every GPU

NVIDIA_DRIVER_CAPABILITIES=all is what injects nvidia-smi/CUDA libs — --gpus all selects the GPUs but caps decide the userspace, so bare --gpus all can return "executable not found". CDI path (Podman, or Docker ≥ 25): nvidia-ctk cdi list; run with --device nvidia.com/gpu=all.

Step 6 — BIOS (max serving perf / passthrough)

Generic GPU-serving profile: Above-4G + Resize BAR on, Performance power/EPP, disable deep C-states / C1E-promotion / ASPM, SR-IOV on (for VM passthrough), VT-d/IOMMU available, ACS off for fast bare-metal P2P (flip on only when isolating GPUs for VFIO), Sub-NUMA Clustering off. Full table in REFERENCE §6. For ASUS ESC8000-E12P exact attribute tokens + apply/verify, use the asus-esc8000-gpu-bios-tuning skill.

Verify (final)

nvidia-smi                                   # all GPUs, VRAM, ECC, driver ver
cat /proc/driver/nvidia/version              # "Open Kernel Module"
cat /proc/cmdline                            # iommu flags present (+ preserved tokens)
sudo dmesg | grep -iE 'DMAR|IOMMU'           # "IOMMU enabled"
ls /sys/kernel/iommu_groups | wc -l          # > 0
nvidia-smi topo -p2p r                        # P2P "OK" across GPUs (multi-GPU)
systemctl is-enabled nvidia-persistenced     # enabled
bash -lc 'nvcc --version'                      # runs (login shell)

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: soulmachine
• Source: soulmachine/skills
• License: MIT

Install and usage instructions live in the source repository linked above.