vllm/docs/source/getting_started/tpu-installation.rst
2024-06-21 23:09:40 -07:00

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.. _installation_tpu:
Installation with TPU
=====================
vLLM supports Google Cloud TPUs using PyTorch XLA.
Requirements
------------
* Google Cloud TPU VM (single host)
* TPU versions: v5e, v5p, v4
* Python: 3.10
Installation options:
1. :ref:`Build a docker image with Dockerfile <build_docker_tpu>`.
2. :ref:`Build from source <build_from_source_tpu>`.
.. _build_docker_tpu:
Build a docker image with :code:`Dockerfile.tpu`
------------------------------------------------
`Dockerfile.tpu <https://github.com/vllm-project/vllm/blob/main/Dockerfile.tpu>`_ is provided to build a docker image with TPU support.
.. code-block:: console
$ docker build -f Dockerfile.tpu -t vllm-tpu .
You can run the docker image with the following command:
.. code-block:: console
$ # Make sure to add `--privileged --net host --shm-size=16G`.
$ docker run --privileged --net host --shm-size=16G -it vllm-tpu
.. _build_from_source_tpu:
Build from source
-----------------
You can also build and install the TPU backend from source.
First, install the dependencies:
.. code-block:: console
$ # (Recommended) Create a new conda environment.
$ conda create -n myenv python=3.10 -y
$ conda activate myenv
$ # Clean up the existing torch and torch-xla packages.
$ pip uninstall torch torch-xla -y
$ # Install PyTorch and PyTorch XLA.
$ export DATE="+20240601"
$ pip install https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch-nightly${DATE}-cp310-cp310-linux_x86_64.whl
$ pip install https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-nightly${DATE}-cp310-cp310-linux_x86_64.whl
$ # Install JAX and Pallas.
$ pip install torch_xla[tpu] -f https://storage.googleapis.com/libtpu-releases/index.html
$ pip install torch_xla[pallas] -f https://storage.googleapis.com/jax-releases/jax_nightly_releases.html -f https://storage.googleapis.com/jax-releases/jaxlib_nightly_releases.html
$ # Install other build dependencies.
$ pip install packaging aiohttp
Next, build vLLM from source. This will only take a few seconds:
.. code-block:: console
$ VLLM_TARGET_DEVICE="tpu" python setup.py develop
.. tip::
If you encounter the following error:
.. code-block:: console
from torch._C import * # noqa: F403
ImportError: libopenblas.so.0: cannot open shared object file: No such file or directory
You can install OpenBLAS with the following command:
.. code-block:: console
$ sudo apt-get install libopenblas-base libopenmpi-dev libomp-dev