docs: add Ubuntu 22.04 LTS CUDA acceleration setup guide

Add a new README_Ubuntu_CUDA_Acceleration_en_US.md document to provide users with a
setup guide for enabling and testing CUDA acceleration on Ubuntu 22.04 LTS. The guideincludes steps to check and install NVIDIA drivers, install Anaconda, create a conda
environment, install required applications, download and verify models, configure theenvironment, and test CUDA acceleration.

This addition addresses the need for clear, concise instructions on achieving better
performance with CUDA-enabled graphics cards and

docs/README_Ubuntu_CUDA_Acceleration_en_US.md

+
+# Ubuntu 22.04 LTS
+
+### 1. Check if NVIDIA Drivers Are Installed
+   ```sh
+   nvidia-smi
+   ```
+   If you see information similar to the following, it means that the NVIDIA drivers are already installed, and you can skip Step 2.
+   ```plaintext
+   +---------------------------------------------------------------------------------------+
+   | NVIDIA-SMI 537.34                 Driver Version: 537.34       CUDA Version: 12.2     |
+   |-----------------------------------------+----------------------+----------------------+
+   | GPU  Name                     TCC/WDDM  | Bus-Id        Disp.A | Volatile Uncorr. ECC |
+   | Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
+   |                                         |                      |               MIG M. |
+   |=========================================+======================+======================|
+   |   0  NVIDIA GeForce RTX 3060 Ti   WDDM  | 00000000:01:00.0  On |                  N/A |
+   |  0%   51C    P8              12W / 200W |   1489MiB /  8192MiB |      5%      Default |
+   |                                         |                      |                  N/A |
+   +-----------------------------------------+----------------------+----------------------+
+   ```
+
+### 2. Install the Driver
+   If no driver is installed, use the following command:
+   ```sh
+   sudo apt-get update
+   sudo apt-get install nvidia-driver-545
+   ```
+   Install the proprietary driver and restart your computer after installation.
+   ```sh
+   reboot
+   ```
+
+### 3. Install Anaconda
+   If Anaconda is already installed, skip this step.
+   ```sh
+   wget https://repo.anaconda.com/archive/Anaconda3-2024.06-1-Linux-x86_64.sh
+   bash Anaconda3-2024.06-1-Linux-x86_64.sh
+   ```
+   In the final step, enter `yes`, close the terminal, and reopen it.
+
+### 4. Create an Environment Using Conda
+   Specify Python version 3.10.
+   ```sh
+   conda create -n MinerU python=3.10
+   conda activate MinerU
+   ```
+
+### 5. Install Applications
+   ```sh
+   pip install magic-pdf[full]==0.6.2b1 detectron2 --extra-index-url https://wheels.myhloli.com
+   ```
+❗ After installation, make sure to check the version of `magic-pdf` using the following command:
+   ```sh
+   magic-pdf --version
+   ```
+   If the version number is less than 0.6.2, please report the issue.
+
+### 6. Download Models
+   Refer to detailed instructions on how to download model files.
+   After downloading, move the `models` directory to an SSD with more space.
+   
+❗ After downloading the models, ensure they are complete:
+   - Check that the file sizes match the description on the website.
+   - If possible, verify the integrity using SHA256.
+
+### 7. Configuration Before First Run
+   Obtain the configuration template file `magic-pdf.template.json` from the root directory of the repository.
+   
+❗ Execute the following command to copy the configuration file to your home directory, otherwise the program will not run:
+   ```sh
+   wget https://github.com/opendatalab/MinerU/raw/master/magic-pdf.template.json
+   cp magic-pdf.template.json ~/magic-pdf.json
+   ```
+   Find the `magic-pdf.json` file in your home directory and configure `"models-dir"` to be the directory where the model weights from Step 6 were downloaded.
+   
+❗ Correctly specify the absolute path of the directory containing the model weights; otherwise, the program will fail due to missing model files.
+   ```json
+   {
+     "models-dir": "/tmp/models"
+   }
+   ```
+
+### 8. First Run
+   Download a sample file from the repository and test it.
+   ```sh
+   wget https://github.com/opendatalab/MinerU/raw/master/demo/small_ocr.pdf
+   magic-pdf pdf-command --pdf small_ocr.pdf
+   ```
+
+### 9. Test CUDA Acceleration
+
+If your graphics card has at least 8GB of VRAM, follow these steps to test CUDA acceleration:
+
+1. Modify the value of `"device-mode"` in the `magic-pdf.json` configuration file located in your home directory.
+   ```json
+   {
+     "device-mode": "cuda"
+   }
+   ```
+2. Test CUDA acceleration with the following command:
+   ```sh
+   magic-pdf pdf-command --pdf small_ocr.pdf
+   ```
+
+### 10. Enable CUDA Acceleration for OCR
+
+❗ The following operations require a graphics card with at least 16GB of VRAM; otherwise, the program may crash or experience reduced performance.
+    
+1. Download `paddlepaddle-gpu`. Installation will automatically enable OCR acceleration.
+   ```sh
+   python -m pip install paddlepaddle-gpu==3.0.0b1 -i https://www.paddlepaddle.org.cn/packages/stable/cu118/
+   ```
+2. Test OCR acceleration with the following command:
+   ```sh
+   magic-pdf pdf-command --pdf small_ocr.pdf
+   ```