intel xpu-container-run
Intel GPUs do not plug into Docker via --gpus all. There is no
nvidia-container-toolkit equivalent. Pass the kernel's Direct
Rendering Manager (DRM) character devices into the container and
grant the right group ownership.
CUDA → Intel cheat sheet
| CUDA | Intel |
|---|---|
docker run --gpus all |
--device /dev/dri --group-add "$(getent group render | cut -d: -f3)" |
docker run --gpus '"device=0"' |
-e ZE_AFFINITY_MASK=0 |
--ipc=host |
same |
--shm-size=16g |
same (alternative to --ipc=host) |
--runtime nvidia |
nothing — xe/i915 is in-kernel |
nvidia-smi inside container |
xpu-smi discovery |
No "Intel container toolkit" needed; passing the DRM nodes is enough.
Image source
Comes from the runner skill:
- vLLM serving → vllm-xpu-run (
vllm/vllm-openai-xpu:latest) - SGLang → sglang-xpu-run (built from upstream
docker/xpu.Dockerfile) - PyTorch / Transformers → torch-xpu-run
<image> below is whichever you picked.
Quickstart — interactive shell, one GPU
Confirm the image name with the user before running — this binds host GPU devices into the container.
docker run --rm -it \
--device /dev/dri \
--group-add "$(getent group render | cut -d: -f3)" \
--ipc=host \
-e ZE_AFFINITY_MASK=0 \
-e HF_TOKEN="$HF_TOKEN" \
-v "$HOME/.cache/huggingface:/root/.cache/huggingface" \
--entrypoint /bin/bash \
<image>
| Flag | Why |
|---|---|
--device /dev/dri |
Pass every Intel GPU's DRM nodes. Use --device /dev/dri/renderD128 for just the first GPU's render node (least privilege). |
--group-add "$(getent group render | cut -d: -f3)" |
Joins the container user to the host's render group by GID (not name) so it works in images where a render group with a different GID — or no render group at all — exists. Required when nodes are mode 0660/0640. Skip causes EACCES on Level Zero init. |
--ipc=host |
vLLM and torch.distributed use /dev/shm and POSIX semaphores. --shm-size=16g is a private-IPC alternative. |
-e ZE_AFFINITY_MASK=0 |
Pin to GPU 0. See xpu-discover for IDs. Always set explicitly. |
-v ~/.cache/huggingface:... |
Share the host model cache; avoid re-download. |
--entrypoint /bin/bash |
Override server-image autostart for interactive use. |
When --privileged is needed
Exception, not rule. Required only for:
unitrace/ VTune collectors that read PMU MSRs.- GPU firmware updates (
xpu-smi updatefw). xpu-smi diag --singletest 5(PCIe bandwidth) and similar low-level diag tests.
For running models and most profiling, --device /dev/dri is
enough. Add --privileged only when you hit a specific permission
failure pointing at it.
Server mode, multi-GPU, --net=host
See references/server-and-multi-gpu.md for daemon-style server
launches, one-process-per-GPU vs single-process TP / PP layouts,
the oneCCL CCL_ZE_IPC_EXCHANGE=pidfd setting for multi-XPU TP,
and when --net=host is actually needed.
Verifying the container sees the GPU
xpu-smi discovery
| Symptom | Cause | Fix |
|---|---|---|
xpu-smi: command not found |
image lacks xpu-smi |
use a different image or skip this check |
empty discovery table |
no /dev/dri passed |
add --device /dev/dri |
Level Zero init failed / EACCES |
user not in render group |
add `--group-add "$(getent group render |
| wrong GPU count | ZE_AFFINITY_MASK inherited from host |
pass mask explicitly with -e |
diag works on host, fails in container |
container not privileged | add --privileged, or skip diag inside container |
Common errors
failed to create shim task: permission denied→ container runtime can't open/dev/dri/card0. Add--privilegedor check host file mode.LIBZE_LOADER: Failed to load level-zero loader→ image missinglibze1/intel-level-zero-gpu. Use a different image.RuntimeError: Cannot find any XPU devices(PyTorch) → Level Zero loaded but no device visible. Re-checkZE_AFFINITY_MASKand runxpu-smi discoveryin the container.bus errorearly in vLLM/PyTorch startup → shared memory too small. Use--ipc=hostor raise--shm-size.
Env vars
| Variable | Purpose |
|---|---|
ZE_AFFINITY_MASK |
Which XPU(s) visible. |
HF_TOKEN |
Hugging Face auth. |
HF_HOME |
Override in-container HF cache path. |
HUGGINGFACE_HUB_CACHE |
Older alias; some images still use it. |
OMP_NUM_THREADS |
Cap CPU threads; 1 for single-process serving. |
CCL_ZE_IPC_EXCHANGE=pidfd |
Multi-GPU-friendly oneCCL IPC mechanism. |
IGC_EnableAluBinding=1 |
Battlemage matmul-codegen hint; bench both. |
ONEAPI_DEVICE_SELECTOR=level_zero:0 |
Belt-and-suspenders pin alongside ZE_AFFINITY_MASK. |
References
references/server-and-multi-gpu.md— server mode, multi-GPU,--net=host- Linux DRM device interface: https://docs.kernel.org/gpu/drm-uapi.html
- Level Zero loader: https://oneapi-src.github.io/level-zero-spec/
- Intel
xedriver: https://docs.kernel.org/gpu/xe/index.html