Appfl

APPFL (Advanced Privacy-Preserving Federated Learning) is a Python framework enabling researchers to easily build and benchmark privacy-aware federated learning solutions. It supports flexible algorithm development, differential privacy, secure communications, and runs efficiently on HPC and multi-GPU setups.

Features

Implements differential privacy and client authentication
Modular plug-and-play aggregation, scheduling, trainers
Supports synchronous and asynchronous FL algorithms
Multi-GPU training via PyTorch DDP
Integrates with MONAI for healthcare workflows
Scalable on HPC using MPI/gRPC-based client-server setup

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License

MIT License

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

Python

Related Categories

Python Federated Learning Frameworks

Registered

2025-07-15

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