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[Doc] Update Intel GPU Support on README (#126001)

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Pull Request resolved: https://github.com/pytorch/pytorch/pull/126001
Approved by: https://github.com/jgong5, https://github.com/albanD, https://github.com/gujinghui, https://github.com/EikanWang
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Yu, Guangye
2024-05-11 17:49:47 +00:00
committed by PyTorch MergeBot
parent 812534d27e
commit d0f3ae8e67
1 changed files with 13 additions and 0 deletions
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README.md
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@ -24,6 +24,9 @@ Our trunk health (Continuous Integration signals) can be found at [hud.pytorch.o
- [NVIDIA Jetson Platforms](#nvidia-jetson-platforms) - [NVIDIA Jetson Platforms](#nvidia-jetson-platforms)
- [From Source](#from-source) - [From Source](#from-source)
- [Prerequisites](#prerequisites) - [Prerequisites](#prerequisites)
- [NVIDIA CUDA Support](#nvidia-cuda-support)
- [AMD ROCm Support](#amd-rocm-support)
- [Intel GPU Support](#intel-gpu-support)
- [Install Dependencies](#install-dependencies) - [Install Dependencies](#install-dependencies)
- [Get the PyTorch Source](#get-the-pytorch-source) - [Get the PyTorch Source](#get-the-pytorch-source)
- [Install PyTorch](#install-pytorch) - [Install PyTorch](#install-pytorch)
@ -162,6 +165,7 @@ If you are installing from source, you will need:
We highly recommend installing an [Anaconda](https://www.anaconda.com/download) environment. You will get a high-quality BLAS library (MKL) and you get controlled dependency versions regardless of your Linux distro. We highly recommend installing an [Anaconda](https://www.anaconda.com/download) environment. You will get a high-quality BLAS library (MKL) and you get controlled dependency versions regardless of your Linux distro.
##### NVIDIA CUDA Support
If you want to compile with CUDA support, [select a supported version of CUDA from our support matrix](https://pytorch.org/get-started/locally/), then install the following: If you want to compile with CUDA support, [select a supported version of CUDA from our support matrix](https://pytorch.org/get-started/locally/), then install the following:
- [NVIDIA CUDA](https://developer.nvidia.com/cuda-downloads) - [NVIDIA CUDA](https://developer.nvidia.com/cuda-downloads)
- [NVIDIA cuDNN](https://developer.nvidia.com/cudnn) v8.5 or above - [NVIDIA cuDNN](https://developer.nvidia.com/cudnn) v8.5 or above
@ -174,6 +178,7 @@ Other potentially useful environment variables may be found in `setup.py`.
If you are building for NVIDIA's Jetson platforms (Jetson Nano, TX1, TX2, AGX Xavier), Instructions to install PyTorch for Jetson Nano are [available here](https://devtalk.nvidia.com/default/topic/1049071/jetson-nano/pytorch-for-jetson-nano/) If you are building for NVIDIA's Jetson platforms (Jetson Nano, TX1, TX2, AGX Xavier), Instructions to install PyTorch for Jetson Nano are [available here](https://devtalk.nvidia.com/default/topic/1049071/jetson-nano/pytorch-for-jetson-nano/)
##### AMD ROCm Support
If you want to compile with ROCm support, install If you want to compile with ROCm support, install
- [AMD ROCm](https://rocm.docs.amd.com/en/latest/deploy/linux/quick_start.html) 4.0 and above installation - [AMD ROCm](https://rocm.docs.amd.com/en/latest/deploy/linux/quick_start.html) 4.0 and above installation
- ROCm is currently supported only for Linux systems. - ROCm is currently supported only for Linux systems.
@ -181,6 +186,14 @@ If you want to compile with ROCm support, install
If you want to disable ROCm support, export the environment variable `USE_ROCM=0`. If you want to disable ROCm support, export the environment variable `USE_ROCM=0`.
Other potentially useful environment variables may be found in `setup.py`. Other potentially useful environment variables may be found in `setup.py`.
##### Intel GPU Support
If you want to compile with Intel GPU support, follow these
- [PyTorch Prerequisites for Intel GPUs](https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpus.html) instructions.
- Intel GPU is currently supported only for Linux systems.
If you want to disable Intel GPU support, export the environment variable `USE_XPU=0`.
Other potentially useful environment variables may be found in `setup.py`.
#### Install Dependencies #### Install Dependencies
**Common** **Common**