🌀 Hashnet Compute Shader

A blazingly fast 2D particle simulator written in Rust, capable of handling up to 89,478,485 particles simultaneously on modern GPUs.

✨ Features

• 🚀 High Performance: Leverages GPU compute shaders for massive parallelism
• 🔢 Scale: Handles tens of millions of particles with stable frame rates
• 🖱️ Interactive: Particles respond to mouse movements in real-time
• 🎮 Multiple Modes: Switch between different particle behaviors
• 🔧 Configurable: Easy customization via JSON configuration

📋 Requirements

• 🦀 Rust 1.70 or newer
• 🖥️ A GPU with WebGPU support (most modern GPUs)
• 🐧 Windows/Linux/macOS

🛠️ Build from Source

1. Clone the repository

git clone https://github.com/Paladynee/hashnet_compute_shader
cd hashnet_compute_shader

2. Build with Cargo

cargo build --release

3. Run the application

cargo run --release

⚠️ Note: Make sure to use the release build for optimal performance when running with millions of particles!

🎮 Controls

• Mouse Movement: Particles gravitate toward cursor
• R key: Switch to Roam mode (particles gravitate around the cursor)
• S key: Switch to Shuffle mode (particles are randomly offset)

⚙️ Configuration

Customize the simulation by modifying the config.json file:

{
    "num_particles": 89478485,
    "quad_size": 0.001
}

• num_particles: Number of particles to simulate
• quad_size: Size of each particle on screen

🔬 How It Works

Hashnet Compute Shader uses WebGPU through the wgpu Rust library to run highly parallelized compute shaders. The simulation follows these steps:

1. Initialization: Particles are created with random positions and velocities
2. Compute Phase: GPU updates particle positions and velocities in parallel
3. Render Phase: Particles are rendered as small quads with velocity-based coloring

The application dispatches compute workgroups in a 2D grid to overcome the 65535 limit per dimension, allowing it to handle many millions of particles.

📈 Performance Tips

• Adjust particle count based on your GPU capabilities
• For integrated GPUs, try starting with 1-5 million particles
• For high-end dedicated GPUs, you can push well beyond 50 million particles

🤝 Contributing

Contributions are welcome! Feel free to:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• The wgpu team for their excellent WebGPU implementation
• The Rust community for building an amazing ecosystem for systems programming