https://github.com/theemptynessproject/particletest
https://github.com/theemptynessproject/particletest
Last synced: 16 days ago
JSON representation
- Host: GitHub
- URL: https://github.com/theemptynessproject/particletest
- Owner: TheEmptynessProject
- License: mit
- Created: 2024-09-07T20:34:15.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-09-07T21:14:33.000Z (over 1 year ago)
- Last Synced: 2026-02-07T20:42:57.843Z (4 months ago)
- Language: C++
- Size: 10.7 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# ParticleTest 🌟
## 📖 About
ParticleTest is an advanced particle simulation project developed entirely by artificial intelligence systems. This project showcases the power of modern GPUs and DirectX 11 in handling millions of particles in real-time.
**Disclaimer:** I acknowledge that I hold no copyright or rights over this work.
## 🎯 Purpose
The primary aim of this project is educational. It serves as a comprehensive demonstration for learning:
- Windows API
- DirectX 11
- HLSL Shaders
- High-performance GPU computing
- Real-time graphics programming
## 🏆 Highscore and Optimization
Our current achievement:
| Metric | Value |
|--------|-------|
| Window Size | 800x600 |
| Max Particles | 5,000,000 |
| Highest FPS | 27.88 |
| Metric | Value |
|--------|-------|
| Window Size | 1920x1080 |
| Max Particles | 5,000,000 |
| Highest FPS | 23.03 |
## 🚀 Features
- GPU-accelerated particle simulation
- Double buffering for smooth rendering
- Compute shader for particle updates
- Instanced rendering for efficient drawing
- Dynamic particle recycling
## 🛠️ Technologies Used
- C++
- DirectX 11
- HLSL (High-Level Shading Language)
- Windows API
## 📊 Performance Insights
The project achieves high performance through:
1. Offloading particle computations to the GPU
2. Minimizing CPU-GPU data transfer
3. Efficient memory management with structured buffers
4. Optimized rendering techniques
## 🔧 Setup and Running
1. Ensure you have DirectX 11 SDK installed
2. Clone this repository
3. Open the project in Visual Studio
4. Build and run the solution
## 🔮 Future Improvements
- Optimize for even higher particle counts
- Explore multi-GPU support
## 📜 License
This project is open-source and available under the MIT License.
## 🤝 Contributing
While this project was AI-generated, contributions for improvements and optimizations are welcome. Please feel free to fork the repository and submit pull requests.
## 📞 Contact
For any queries or discussions about this project, please open an issue in the GitHub repository.
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Made by AI, few changes and updates by humans to make it runnable