vllm/docs/source/getting_started/xpu-installation.rst

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.. _installation_xpu:
Installation with XPU
========================
vLLM initially supports basic model inferencing and serving on Intel GPU platform.
Table of contents:
#. :ref:`Requirements <xpu_backend_requirements>`
#. :ref:`Quick start using Dockerfile <xpu_backend_quick_start_dockerfile>`
#. :ref:`Build from source <build_xpu_backend_from_source>`
.. _xpu_backend_requirements:
Requirements
------------
* OS: Linux
* Supported Hardware: Intel Data Center GPU, Intel ARC GPU
* OneAPI requirements: oneAPI 2024.2
.. _xpu_backend_quick_start_dockerfile:
Quick start using Dockerfile
----------------------------
.. code-block:: console
$ docker build -f Dockerfile.xpu -t vllm-xpu-env --shm-size=4g .
$ docker run -it \
--rm \
--network=host \
--device /dev/dri \
-v /dev/dri/by-path:/dev/dri/by-path \
vllm-xpu-env
.. _build_xpu_backend_from_source:
Build from source
-----------------
- First, install required driver and intel OneAPI 2024.2 or later.
- Second, install Python packages for vLLM XPU backend building:
.. code-block:: console
$ source /opt/intel/oneapi/setvars.sh
$ pip install --upgrade pip
$ pip install -v -r requirements-xpu.txt
- Finally, build and install vLLM XPU backend:
.. code-block:: console
$ VLLM_TARGET_DEVICE=xpu python setup.py install
.. note::
- FP16 is the default data type in the current XPU backend. The BF16 data
type will be supported in the future.