https://github.com/palaashatri/pytk-nvidia-smi-gui

A real-time graphical interface for monitoring NVIDIA GPU status using nvidia-smi, with color-coded metrics, process table, and power limit adjustment.
https://github.com/palaashatri/pytk-nvidia-smi-gui

gpu gui linux nvidia nvidia-smi python tk tools windows

Last synced: 3 months ago
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A real-time graphical interface for monitoring NVIDIA GPU status using nvidia-smi, with color-coded metrics, process table, and power limit adjustment.

• Host: GitHub
• URL: https://github.com/palaashatri/pytk-nvidia-smi-gui
• Owner: palaashatri
• License: mit
• Created: 2025-06-29T19:27:06.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2025-06-29T19:51:29.000Z (3 months ago)
• Last Synced: 2025-06-29T20:33:31.930Z (3 months ago)
• Topics: gpu, gui, linux, nvidia, nvidia-smi, python, tk, tools, windows
• Language: Python
• Homepage:
• Size: 13.7 KB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# NVIDIA-SMI GUI Monitor

A real-time graphical interface for monitoring NVIDIA GPU status using `nvidia-smi`, with color-coded metrics, process table, and power limit adjustment.

![NVIDIA-SMI GUI Screenshot](https://github.com/user-attachments/assets/baf6e177-a31d-49b8-9844-453eb241819a)

## Overview

This application provides a user-friendly GUI that displays key NVIDIA GPU information in real-time, updating every 2 seconds. It is built with Python's Tkinter library and uses the `nvidia-smi` command to fetch GPU status and running processes.

## Features

- 🔄 **Real-time monitoring** - Updates every 2 seconds automatically

- 🎨 **Color-coded display** - Visual indicators for utilization, memory, temperature, and power draw

- 📊 **Process monitoring** - Table of running GPU processes (PID, name, memory usage)

- ⚡ **Power limit control** - Adjust GPU power limits with validation (requires admin privileges)

- 📋 **Full nvidia-smi output** - Collapsible section showing complete nvidia-smi information

- 🛡️ **Error handling** - Graceful handling of missing drivers or command failures

- 🌐 **Cross-platform** - Compatible with Windows, Linux, and macOS

- 🪶 **Lightweight** - No external dependencies, uses only Python standard library

## Project Structure

```

pytk-nvidia-smi-gui/

├── App.py              # Main application file

├── requirements.txt    # Project dependencies (Python stdlib only)

├── LICENSE            # MIT License

└── README.md          # This file

```

## Prerequisites

### Hardware Requirements

- NVIDIA GPU with compatible drivers installed

- NVIDIA driver version that supports `nvidia-smi` command

### Software Requirements

- Python 3.6 or higher

- Tkinter (usually included with Python installation)

- NVIDIA drivers with `nvidia-smi` utility

## Installation

### Option 1: Download Pre-built Executable (Recommended for Windows)

1. **Go to the [Releases page](https://github.com/palaashatri/pytk-nvidia-smi-gui/releases)**

2. **Download the latest release:**

   - **Windows**: `nvidia-smi-gui-monitor.exe` - Ready to run, no Python required!

   - **Linux**: `nvidia-smi-gui-monitor` - Make executable with `chmod +x nvidia-smi-gui-monitor`

3. **Run the executable directly**

### Option 2: Run from Source

1. **Clone or download the project:**

   ```bash

   git clone https://github.com/yourusername/pytk-nvidia-smi-gui.git

   cd pytk-nvidia-smi-gui

   ```

2. **Verify Python installation:**

   ```bash

   python --version

   # or

   python3 --version

   ```

3. **Verify NVIDIA drivers:**

   ```bash

   nvidia-smi

   ```

   This command should display your GPU information. If it fails, install appropriate NVIDIA drivers.

## Usage

### Running the Application

**If using pre-built executable:**

- **Windows**: Double-click `nvidia-smi-gui-monitor.exe` or run from command prompt

- **Linux**: `./nvidia-smi-gui-monitor` (after making it executable with `chmod +x`)

**If running from source:**

```bash

python App.py

# or

python3 App.py

```

### Application Interface

- The application opens a window titled "NVIDIA-SMI GPU Monitor"

- The top displays the GPU name and a button to adjust the power limit

- Key metrics (utilization, memory, temperature, power) are shown in a color-coded table:

  - 🟢 **Green**: Normal/Good values

  - 🟠 **Orange**: Warning levels

  - 🔴 **Red**: Critical/High values

- A table lists all running GPU processes (PID, name, memory usage)

- A button toggles display of the full `nvidia-smi` output in a collapsible section

- Information updates automatically every 2 seconds

- Close the window to exit the application

### Adjusting Power Limit

- Click the "Adjust Power Limit" button to open a new window

- The window displays current, minimum, and maximum power limits

- Enter a new value within the allowed range and click "Apply"

- **Note:** Changing the power limit may require administrator/root privileges

## Configuration

### Update Interval

To change the refresh rate, modify the `root.after(2000, update_gui)` line in `App.py` (2000 ms = 2 seconds).

### Color Thresholds

You can adjust the warning/danger thresholds for utilization, memory, temperature, and power in the respective color functions in `App.py`:

## Troubleshooting

### Common Issues

1. **"nvidia-smi not found" error:**

   - Install NVIDIA drivers

   - Ensure `nvidia-smi` is in your system PATH

   - Verify GPU is NVIDIA brand

2. **Python not found:**

   - Install Python from [python.org](https://python.org)

   - Ensure Python is added to system PATH

3. **Tkinter import error:**

   - On Ubuntu/Debian:

     ```bash

     sudo apt-get install python3-tk

     ```

   - On CentOS/RHEL:

     ```bash

     sudo yum install tkinter

     ```

   - On macOS: Usually included with Python

4. **Permission denied (Linux/macOS):**

   ```bash

   chmod +x App.py

   ```

5. **Setting Power Limit Fails:**

   - You may need to run the app as administrator/root to change the power limit

   - On Linux: `sudo python App.py`

   - On Windows: Run Command Prompt/PowerShell as Administrator

## Building a Standalone Executable (Optional)

### Automated Builds

This project includes GitHub Actions workflows that automatically build executables:

- **Release Builds**: When you create a git tag (e.g., `v1.0.0`), executables for Windows and Linux are automatically built and attached to the GitHub release

- **Test Builds**: Every push to main/master branch runs build tests to ensure the code compiles correctly

### Manual Build

You can also compile this app into a single-file executable using PyInstaller:

1. **Install PyInstaller:**

   ```bash

   pip install pyinstaller

   ```

2. **Build the executable:**

   ```bash

   pyinstaller --onefile --name nvidia-smi-gui-monitor App.py

   ```

3. **Find the executable:**

   - The executable will be created in the `dist/` directory

   - On Linux: `dist/nvidia-smi-gui-monitor`

   - On Windows: `dist/nvidia-smi-gui-monitor.exe`

### Creating a Release (for maintainers)

To create a new release with automatic executable builds:

1. **Create and push a version tag:**

   ```bash

   git tag v1.0.0

   git push origin v1.0.0

   ```

2. **GitHub Actions will automatically:**

   - Build Windows and Linux executables

   - Create a GitHub release with the tag name

   - Attach the executables to the release

   - Generate release notes with download instructions

### Notes

- The resulting executable is portable and does not require Python to be installed on the target system

- On Linux, you may need to run `chmod +x nvidia-smi-gui-monitor` before executing

- If you encounter issues with missing libraries (e.g., tkinter), ensure all dependencies are installed on your build system

## Technical Details

### Performance

- **Memory Usage**: ~10-20MB RAM

- **CPU Usage**: Minimal (periodic nvidia-smi calls)

- **Update Frequency**: 2 seconds (configurable)

- **Dependencies**: Python standard library only

### Tested Platforms

- **Windows**: 10, 11

- **Linux**: Ubuntu 20.04+, CentOS 7+, Fedora 35+

- **macOS**: 10.14+

- **NVIDIA GPUs**: GTX, RTX, Tesla, Quadro series

### Color Coding System

- **Utilization/Memory**:

  - Green: < 70%

  - Orange: 70-90%

  - Red: > 90%

- **Temperature**:

  - Green: < 65°C

  - Orange: 65-80°C

  - Red: > 80°C

- **Power Draw**:

  - Green: < 80% of limit

  - Orange: 80-95% of limit

  - Red: > 95% of limit

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

1. Fork the repository

2. Create a feature branch (`git checkout -b feature/AmazingFeature`)

3. Commit your changes (`git commit -m 'Add some AmazingFeature'`)

4. Push to the branch (`git push origin feature/AmazingFeature`)

5. Open a Pull Request

## Support

For issues and questions:

1. Check the troubleshooting section above

2. Verify system requirements

3. Create an issue in the repository with:

   - Your operating system

   - Python version

   - NVIDIA driver version

   - Error message (if any)

## Author

Palaash Atri

## Acknowledgments

- NVIDIA for the `nvidia-smi` utility

- Python Software Foundation for Tkinter

- The open-source community for inspiration and feedback

---

Made with ❤️ for GPU monitoring enthusiasts