Basic PPFL Training

APPFL provides users with the capabilities of simulating and training PPFL on either a single machine, a cluster, or multiple heterogeneous machines. We refer

• simulation as running PPFL experiments on a single machine or a cluster without actual data decentralization

• training as running PPFL experiments on multiple (heterogeneous) machines with actual decentralization of client datasets

We provide examples for both simulation and training in the following sections. Particularly, simulating PPFL is useful for those who develop, test, and validate new models and algorithms for PPFL, whereas training PPFL for those who consider actual PPFL settings in practice.

• Simulating PPFL (Serial)
• Simulating PPFL (MPI)
• Training PPFL

In additional to the examples above, we also provide instructions on how to define models, datasets, and configurations for your own FL applications.

• How to define model
• How to define loss
• How to define metric
• How to load datasets