FedHF is a Python-based simulator for flexible, heterogeneous, and asynchronous federated learning research. It provides configurable resource models, supports asynchronous protocols, and accelerates experimentation.
Features
- Loose coupling of client/server for FL simulations
- Supports asynchronous federated protocols
- Models heterogeneous device/resource performance
- Configurable via Python APIs
- Accelerates prototyping of FL algorithms
- Apache‑2.0 licensed with documentation
Categories
Federated Learning FrameworksLicense
Apache License V2.0Follow Fedhf
Other Useful Business Software
Build Securely on AWS with Proven Frameworks
Moving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of Fedhf!