Appfl Files

New Features

• Introduce support for streamed aggregation in gRPC communication, enabling memory-efficient federated learning for large models and datasets. [Documentation].
• Add a new example demonstrating federated learning with Graph Neural Networks (GNNs) using PyTorch Geometric from @trucndt. [Documentation].
• Integrate additional privacy-preserving mechanisms from @aash-mohammad, including: secure aggregation and differential privacy via Opacus-Privacy.
• Add tutorial notebooks for running APPFL on NERSC systems, available here.
• Add tutorial notebooks for running APPFL on AI-READI datasets, available here.

Bug Fixes

• Resolve race conditions in the FedCompass implementation.
• Fix issues when running FedCompass with Globus Compute.
• Improve GitHub workflows and CI/CD actions for testing and deployment stability.