Add PyTorch 2.6 QuickStart for Intel GPU (#13024)

* Add quickstart for install IPEX-LLM with PyTorch 2.6 on Intel GPUs

* Add jump links

* Rename

* Small fix

* Small fix

* Update based on comments

* Small fix

docs/mddocs/Overview/install_gpu.md

@@ -2,6 +2,9 @@
 
 ## Windows
 
+> [!NOTE]
+> For installation with PyTorch 2.6, please refer to this [guide](../Quickstart/install_pytorch26_gpu.md#windows-quickstart) for more information.
+
 ### Prerequisites
 
 IPEX-LLM on Windows supports Intel iGPU and dGPU.
@@ -171,6 +174,9 @@ If you met error when importing `intel_extension_for_pytorch`, please ensure tha
 
 ## Linux
 
+> [!NOTE]
+> For installation with PyTorch 2.6, please refer to this [guide](../Quickstart/install_pytorch26_gpu.md#linux-quickstart) for more information.
+
 ### Prerequisites
 
 IPEX-LLM GPU support on Linux has been verified on:

docs/mddocs/Quickstart/install_linux_gpu.md

@@ -5,6 +5,9 @@
     
 This guide demonstrates how to install IPEX-LLM on Linux with Intel GPUs. It applies to Intel Data Center GPU Flex Series and Max Series, as well as Intel Arc Series GPU and Intel iGPU. 
 
+> [!NOTE]
+> For installation with PyTorch 2.6, please refer to this [guide](./install_pytorch26_gpu.md#linux-quickstart) for more information.
+
 > [!NOTE]
 > For installation on Intel Arc B-Series GPU (such as **B580**), please refer to this [guide](./bmg_quickstart.md).
 

docs/mddocs/Quickstart/install_linux_gpu.zh-CN.md

@@ -5,6 +5,9 @@
 
 本指南将引导你如何在带有 Intel GPU 的 Linux 系统上安装 IPEX-LLM。适用于 Intel 数据中心的 GPU Flex 和 Max 系列，以及 Intel Arc 系列 GPU 和 Intel iGPU。
 
+> [!NOTE]
+> 如果需要安装 IPEX-LLM PyTorch 2.6 版本，请参阅本[指南](./install_pytorch26_gpu.md#linux-quickstart)获取详细信息。
+
 > [!NOTE]
 > 如果是在 Intel Arc B 系列 GPU 上安装(例，**B580**)，请参阅本[指南](./bmg_quickstart.md)。
 

docs/mddocs/Quickstart/install_pytorch26_gpu.md

@@ -0,0 +1,223 @@
+# Install IPEX-LLM on Intel GPU with PyTorch 2.6
+
+This guide demonstrates how to install IPEX-LLM on Intel GPUs with PyTorch 2.6 support.
+
+IPEX-LLM with PyTorch 2.6 provides a simpler prerequisites setup process, without requiring manual installation of oneAPI. Besides, it offers broader platform support with AOT (Ahead of Time) Compilation.
+
+> [!TIP]
+> For details on which device IPEX-LLM PyTorch 2.6 supports with AOT compilation, you could refer to here ([Windows](https://pytorch-extension.intel.com/installation?platform=gpu&version=v2.6.10%2Bxpu&os=windows&package=pip#:~:text=following%20system%20requirements%3A-,1.1.%20Hardware,-Supported%20by%20prebuilt) or [Linux](https://pytorch-extension.intel.com/installation?platform=gpu&version=v2.6.10%2Bxpu&os=linux%2Fwsl2&package=pip#:~:text=following%20system%20requirements%3A-,1.1.%20Hardware,-Supported%20by%20prebuilt)) for more information.
+
+## Table of Contents
+- [Windows Quickstart](#windows-quickstart)
+  - [Install Prerequisites](#install-prerequisites)
+  - [Install `ipex-llm`](#install-ipex-llm)
+  - [Runtime Configurations](#runtime-configurations)
+  - [Verify Installation](#verify-installation)
+- [Linux Quickstart](#linux-quickstart)
+  - [Install Prerequisites](#install-prerequisites-1)
+  - [Install `ipex-llm`](#install-ipex-llm-1)
+  - [Runtime Configurations](#runtime-configurations-1)
+  - [Verify Installation](#verify-installation-1)
+
+## Windows Quickstart
+
+### Install Prerequisites
+
+#### Update GPU Driver
+
+We recommend updating your GPU driver to the [latest](https://www.intel.com/content/www/us/en/download/785597/intel-arc-iris-xe-graphics-windows.html). A system reboot is necessary to apply the changes after the installation is complete.
+
+#### Setup Python Environment
+
+Visit [Miniforge installation page](https://conda-forge.org/download/), download the **Miniforge installer for Windows**, and follow the instructions to complete the installation.
+
+<div align="center">
+<img src="https://llm-assets.readthedocs.io/en/latest/_images/quickstart_windows_gpu_miniforge_download.png"  width=80%/>
+</div>
+
+After installation, open the **Miniforge Prompt**, create a new python environment `llm-pt26`:
+```cmd
+conda create -n llm-pt26 python=3.11
+```
+Activate the newly created environment `llm-pt26`:
+```cmd
+conda activate llm-pt26
+```
+
+### Install `ipex-llm`
+
+With the `llm-pt26` environment active, use `pip` to install `ipex-llm` for GPU:
+
+- For **Intel Core™ Ultra Processors (Series 2) with processor number 2xxH (code name Arrow Lake)**:
+
+  Choose either US or CN website for `extra-index-url`:
+
+  - For **US**:
+
+    ```cmd
+    pip install --pre --upgrade ipex-llm[xpu_2.6_arl] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/arl/us/
+    ```
+
+  - For **CN**:
+
+    ```cmd
+    pip install --pre --upgrade ipex-llm[xpu_2.6_arl] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/arl/cn/
+    ```
+
+> [!TIP]
+> For other Intel Core™ Ultra Processors, such as 2xxHX, please refer to the installation instruction below (i.e. for **other Intel iGPU and dGPU**).
+
+- For **other Intel iGPU and dGPU**:
+
+   ```cmd
+   pip install --pre --upgrade ipex-llm[xpu_2.6] --extra-index-url https://download.pytorch.org/whl/xpu
+   ```
+
+### Runtime Configurations
+
+For optimal performance, it is recommended to set several environment variables. Please check out the suggestions based on your device.
+
+With the `llm-pt26` environment active:
+
+- For **Intel Arc™ A-Series GPU (code name Alchemist)**
+
+  ```cmd
+  set SYCL_CACHE_PERSISTENT=1
+  set UR_L0_USE_IMMEDIATE_COMMANDLISTS=0
+  ```
+
+> [!TIP]
+> It is recommanded to experiment with `UR_L0_USE_IMMEDIATE_COMMANDLISTS=0` or `1` for best performance on Intel Arc™ A-Series GPU.
+
+- For **other Intel iGPU and dGPU**:
+
+  ```cmd
+  set SYCL_CACHE_PERSISTENT=1
+  :: [optional] The following environment variable may improve performance, but in some cases, it may also lead to performance degradation
+  set SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
+  ```
+
+> [!NOTE]
+> The environment variable `SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS` determines the usage of immediate command lists for task submission to the GPU. It is highly recommanded to experiment with `SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1` or `0` on your device for best performance.
+>
+> You could refer to [here](https://www.intel.com/content/www/us/en/developer/articles/guide/level-zero-immediate-command-lists.html) regarding more information about Level Zero Immediate Command Lists.
+
+### Verify Installation
+
+You can verify if `ipex-llm` is successfully installed following below steps:
+
+- Open the **Miniforge Prompt** and activate the Python environment `llm-pt26` you previously created:
+
+  ```cmd
+  conda activate llm-pt26
+  ```
+
+- Set environment variables according to the [Runtime Configurations section](#runtime-configurations).
+
+- Launch the Python interactive shell by typing `python` in the Miniforge Prompt window and then press Enter.
+
+- Copy following code to Miniforge Prompt **line by line** and press Enter **after copying each line**.
+
+  ```python
+  import torch
+  from ipex_llm.transformers import AutoModel, AutoModelForCausalLM
+  tensor_1 = torch.randn(1, 1, 40, 128).to('xpu')
+  tensor_2 = torch.randn(1, 1, 128, 40).to('xpu')
+  print(torch.matmul(tensor_1, tensor_2).size())
+  ```
+
+  It should output following content at the end:
+
+  ```
+  torch.Size([1, 1, 40, 40])
+  ```
+
+- To exit the Python interactive shell, simply press Ctrl+Z then press Enter (or input `exit()` then press Enter).
+
+
+## Linux Quickstart
+
+### Install Prerequisites
+
+#### Install GPU Driver
+
+We recommend following [Intel client GPU driver installation guide](https://dgpu-docs.intel.com/driver/client/overview.html) to install your GPU driver.
+
+#### Setup Python Environment
+ 
+Download and install the Miniforge as follows if you don't have conda installed on your machine:
+
+```bash
+wget https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-x86_64.sh
+bash Miniforge3-Linux-x86_64.sh
+source ~/.bashrc
+```
+
+You can use `conda --version` to verify you conda installation.
+
+After installation, create a new python environment `llm-pt26`:
+```bash
+conda create -n llm-pt26 python=3.11
+```
+Activate the newly created environment `llm-pt26`:
+```bash
+conda activate llm-pt26
+```
+
+### Install `ipex-llm`
+
+With the `llm-pt26` environment active, use `pip` to install `ipex-llm` for GPU:
+
+```bash
+pip install --pre --upgrade ipex-llm[xpu_2.6] --extra-index-url https://download.pytorch.org/whl/xpu
+```
+
+### Runtime Configurations
+
+For optimal performance, it is recommended to set several environment variables. Please check out the suggestions based on your device.
+
+With the `llm-pt26` environment active:
+
+```bash
+unset OCL_ICD_VENDORS
+export SYCL_CACHE_PERSISTENT=1
+# [optional] The following environment variable may improve performance, but in some cases, it may also lead to performance degradation
+export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
+```
+
+> [!NOTE]
+> The environment variable `SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS` determines the usage of immediate command lists for task submission to the GPU. It is highly recommanded to experiment with `SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1` or `0` on your device for best performance.
+>
+> You could refer to [here](https://www.intel.com/content/www/us/en/developer/articles/guide/level-zero-immediate-command-lists.html) regarding more information about Level Zero Immediate Command Lists.
+
+### Verify Installation
+
+You can verify if `ipex-llm` is successfully installed following below steps:
+
+- Activate the Python environment `llm-pt26` you previously created:
+
+  ```cmd
+  conda activate llm-pt26
+  ```
+
+- Set environment variables according to the [Runtime Configurations section](#runtime-configurations-1).
+
+- Launch the Python interactive shell by typing `python` in the terminal and then press Enter.
+
+- Copy following code to Miniforge Prompt **line by line** and press Enter **after copying each line**.
+
+  ```python
+  import torch
+  from ipex_llm.transformers import AutoModel, AutoModelForCausalLM
+  tensor_1 = torch.randn(1, 1, 40, 128).to('xpu')
+  tensor_2 = torch.randn(1, 1, 128, 40).to('xpu')
+  print(torch.matmul(tensor_1, tensor_2).size())
+  ```
+
+  It should output following content at the end:
+
+  ```
+  torch.Size([1, 1, 40, 40])
+  ```
+
+- To exit the Python interactive shell, simply press Ctrl+C then press Enter (or input `exit()` then press Enter).

docs/mddocs/Quickstart/install_windows_gpu.md

@@ -5,6 +5,9 @@
     
 This guide demonstrates how to install IPEX-LLM on Windows with Intel GPUs. 
 
+> [!NOTE]
+> For installation with PyTorch 2.6, please refer to this [guide](./install_pytorch26_gpu.md#windows-quickstart) for more information.
+
 > [!NOTE]
 > For installation on Intel Arc B-Series GPU (such as **B580**), please refer to this [guide](./bmg_quickstart.md).
 

docs/mddocs/Quickstart/install_windows_gpu.zh-CN.md

@@ -5,6 +5,9 @@
     
 本指南将引导你如何在具有 Intel GPUs 的 Windows 系统上安装 IPEX-LLM。 
 
+> [!NOTE]
+> 如果需要安装 IPEX-LLM PyTorch 2.6 版本，请参阅本[指南](./install_pytorch26_gpu.md#windows-quickstart)获取详细信息。
+
 > [!NOTE]
 > 如果是在 Intel Arc B 系列 GPU 上安装(例，**B580**)，请参阅本[指南](./bmg_quickstart.md)。