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update get start xpu document for v2.7 (#150397)

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update get start xpu document for v2.7
Pull Request resolved: https://github.com/pytorch/pytorch/pull/150397
Approved by: https://github.com/guangyey, https://github.com/EikanWang, https://github.com/atalman

Co-authored-by: Nikita Shulga <2453524+malfet@users.noreply.github.com>
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ZhaoqiongZ 2025-04-03 18:17:02 +00:00 committed by PyTorch MergeBot
parent 78d1165d76
commit 96f35f55e2
1 changed files with 34 additions and 15 deletions
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docs/source/notes/get_start_xpu.rst
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@ -4,27 +4,46 @@ Getting Started on Intel GPU
Hardware Prerequisite
---------------------
For Intel Data Center GPU
.. list-table::
:widths: 50 50
:widths: 50 50 50 50
:header-rows: 1
* - Supported OS
- Validated Hardware
* - Linux
- Intel® Client GPUs / Intel® Data Center GPU Max Series
* - Windows
- Intel® Client GPUs
* - WSL2 (experimental feature)
- Intel® Client GPUs
* - Device
- Red Hat* Enterprise Linux* 9.2
- SUSE Linux Enterprise Server* 15 SP5
- Ubuntu* Server 22.04 (>= 5.15 LTS kernel)
* - Intel® Data Center GPU Max Series (CodeName: Ponte Vecchio)
- yes
- yes
- yes
Intel GPUs support (Prototype) is ready in PyTorch* 2.6 for Intel® Client GPUs and Intel® Data Center GPU Max Series on both Linux and Windows, which brings Intel GPUs and the SYCL* software stack into the official PyTorch stack with consistent user experience to embrace more AI application scenarios.
For Intel Client GPU
+-------------------------------------+----------------------------------------------------------------------------------------------+
| Supported OS | Validated Hardware |
+=====================================+==============================================================================================+
|| Windows 10/11 & Ubuntu 24.10 || Intel® Arc A-Series Graphics (CodeName: Alchemist) |
|| || Intel® Arc B-Series Graphics (CodeName: Battlemage) |
|| || Intel® Core™ Ultra Processors with Intel® Arc™ Graphics (CodeName: Meteor Lake) |
|| || Intel® Core™ Ultra 200V Series with Intel® Arc™ Graphics (CodeName: Lunar Lake) |
|| || Intel® Core™ Ultra Series 2 Processors with Intel® Arc™ Graphics (CodeName: Arrow Lake) |
+-------------------------------------+----------------------------------------------------------------------------------------------+
|| Ubuntu 24.04 & WSL2 (Ubuntu 24.04) || Intel® Arc A-Series Graphics (CodeName: Alchemist) |
|| || Intel® Core™ Ultra Processors with Intel® Arc™ Graphics (CodeName: Meteor Lake) |
|| || Intel® Core™ Ultra 200V Series with Intel® Arc™ Graphics (CodeName: Lunar Lake) |
|| || Intel® Core™ Ultra Series 2 Processors with Intel® Arc™ Graphics (CodeName: Arrow Lake) |
+-------------------------------------+----------------------------------------------------------------------------------------------+
Intel GPUs support (Prototype) is ready from PyTorch* 2.5 for Intel® Client GPUs and Intel® Data Center GPU Max Series on both Linux and Windows, which brings Intel GPUs and the SYCL* software stack into the official PyTorch stack with consistent user experience to embrace more AI application scenarios.
Software Prerequisite
---------------------
To use PyTorch on Intel GPUs, you need to install the Intel GPUs driver first. For installation guide, visit `Intel GPUs Driver Installation <https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpu/2-6.html#driver-installation>`_.
To use PyTorch on Intel GPUs, you need to install the Intel GPUs driver first. For installation guide, visit `Intel GPUs Driver Installation <https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpu.html#driver-installation>`_.
Please skip the Intel® Deep Learning Essentials installation section if you install from binaries. For building from source, please refer to `PyTorch Installation Prerequisites for Intel GPUs <https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpu/2-6.html>`_ for both Intel GPU Driver and Intel® Deep Learning Essentials Installation.
Please skip the Intel® Deep Learning Essentials installation section if you install from binaries. For building from source, please refer to `PyTorch Installation Prerequisites for Intel GPUs <https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpu.html>`_ for both Intel GPU Driver and Intel® Deep Learning Essentials Installation.
Installation
@ -33,7 +52,7 @@ Installation
Binaries
^^^^^^^^
Now that we have `Intel GPU Driver <https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpu/2-6.html#driver-installation>`_ installed, use the following commands to install ``pytorch``, ``torchvision``, ``torchaudio`` on Linux.
Now that we have `Intel GPU Driver <https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpu.html#driver-installation>`_ installed, use the following commands to install ``pytorch``, ``torchvision``, ``torchaudio`` on Linux.
For release wheels
@ -52,7 +71,7 @@ For nightly wheels
From Source
^^^^^^^^^^^
Now that we have `Intel GPU Driver and Intel® Deep Learning Essentials <https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpu/2-6.html>`_ installed. Follow guides to build ``pytorch``, ``torchvision``, ``torchaudio`` from source.
Now that we have `Intel GPU Driver and Intel® Deep Learning Essentials <https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpu.html>`_ installed. Follow guides to build ``pytorch``, ``torchvision``, ``torchaudio`` from source.
Build from source for ``torch`` refer to `PyTorch Installation Build from source <https://github.com/pytorch/pytorch?tab=readme-ov-file#from-source>`_.
@ -88,7 +107,7 @@ If you are migrating code from ``cuda``, you would change references from ``cuda
The following points outline the support and limitations for PyTorch with Intel GPU:
#. Both training and inference workflows are supported.
#. Both eager mode and ``torch.compile`` is supported.
#. Both eager mode and ``torch.compile`` is supported. The feature ``torch.compile`` is also supported on Windows from PyTorch* 2.7 with Intel GPU, refer to `How to Use Inductor on Windows with CPU/XPU <https://pytorch.org/tutorials/prototype/inductor_windows_cpu.html>`_.
#. Data types such as FP32, BF16, FP16, and Automatic Mixed Precision (AMP) are all supported.
Examples