Update Intel GPU Support on README

ghstack-source-id: c203a560e06d6ea5d228dbd55e23c87dffb459ca
Pull Request resolved: #126001

README.md

@@ -162,6 +162,7 @@ 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.
 
+##### 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:
 - [NVIDIA CUDA](https://developer.nvidia.com/cuda-downloads)
 - [NVIDIA cuDNN](https://developer.nvidia.com/cudnn) v8.5 or above
@@ -174,13 +175,18 @@ 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/)
 
+##### AMD ROCm Support
 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
 - ROCm is currently supported only for Linux systems.
 
 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`.
 
+##### Intel GPU Support
+If you want to compile with Intel GPU support for Linux system, 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.
+
 #### Install Dependencies
 
 **Common**