What is WarpTorch?​

WarpTorch is a high-performance, GPU-accelerated General Relativity toolkit designed for simulating, analyzing, and visualizing warp drive spacetimes. By porting and optimizing numerical relativity methods to modern PyTorch, we enable physicists and enthusiasts to solve Einstein's field equations at unprecedented speeds.

Key Features​

• Massive Acceleration: GPU-accelerated tensor computations with CUDA, ROCm, and Intel Arc support
• Comprehensive Library: Vectorized implementations of classical and novel warp metrics
• Advanced Solvers: 4th-order finite difference stencils for Einstein's field equations
• Web-Ready Export: JSON exporters for WebGL frontend integration

Getting Started​

Check out our quick start guide to get started with WarpTorch. Whether you prefer interactive 3D visualization in your browser or direct Python programming in Jupyter Lab, we have you covered.

Stay Tuned​

Follow this blog for:

• Tutorials: Step-by-step guides for warp drive simulations
• Research Updates: Latest developments in warp drive physics
• Performance Tips: Optimize your simulations for maximum speed
• Community Highlights: Interesting projects from the WarpTorch community

Join the Community​

• GitHub: https://github.com/just-omar/WarpTorch
• Issues: Report bugs and request features
• Contributions: We welcome contributions from the community

Welcome aboard the WarpTorch project! 🚀

Why Contribute?​

WarpTorch is a community-driven project focused on making GPU-accelerated general relativity simulations accessible to everyone. Whether you're a physicist, developer, or enthusiast, your contributions matter!

Ways to Contribute​

Code Contributions​

• Fix bugs and implement new features
• Optimize existing CUDA kernels
• Add support for new spacetime metrics
• Improve documentation

Research & Science​

• Contribute novel warp drive metrics
• Share simulation results
• Write physics tutorials
• Validate numerical methods

Community​

• Help new users on GitHub Issues
• Write blog posts about your projects
• Share WarpTorch on social media
• Organize study groups

Getting Started​

1. Fork the repository on GitHub
2. Clone your fork: git clone https://github.com/YOUR_USERNAME/WarpTorch
3. Create a branch: git checkout -b feature/my-feature
4. Make your changes and test thoroughly
5. Submit a pull request with a clear description

Coding Standards​

• Follow the existing code style
• Add docstrings to new functions
• Include tests for new features
• Update relevant documentation

What We're Looking For​

High Priority​

• Performance optimizations for CUDA kernels
• Additional spacetime metrics
• Better error handling and validation
• Improved test coverage

Medium Priority​

• Documentation improvements
• Bug fixes
• UI/UX enhancements
• Example notebooks

Nice to Have​

• New visualization features
• Additional export formats
• Integration with other physics libraries
• Multi-language support

Recognition​

All contributors are:

• Listed in our contributors section
• Mentioned in release notes
• Eligible for contributor badges
• Part of our decision-making process

Join the Team​

Active contributors may be invited to join the core team! Core team members have:

• Write access to the repository
• Voting rights on project decisions
• Official contributor status
• Access to development resources

Resources​

• GitHub: https://github.com/just-omar/WarpTorch
• Issues: Report bugs and request features
• Discussions: Ask questions and share ideas
• Documentation: https://warptorch.org

Next Steps​

Ready to contribute? Check out our good first issues or start with the documentation!

This guide will be updated as the project grows. Have suggestions? Open an issue or PR!