README.md

Federated XGBoost Demo using NVFlare

This directory contains a demo of Federated Learning using NVFlare.

To run the demo, first build XGBoost with the federated learning plugin enabled (see the README).

Install NVFlare:

pip install nvflare

Prepare the data:

./prepare_data.sh

Start the NVFlare federated server:

./poc/server/startup/start.sh

In another terminal, start the first worker:

./poc/site-1/startup/start.sh

And the second worker:

./poc/site-2/startup/start.sh

Then start the admin CLI, using admin/admin as username/password:

./poc/admin/startup/fl_admin.sh

In the admin CLI, run the following commands:

upload_app hello-xgboost
set_run_number 1
deploy_app hello-xgboost all
start_app all

Once the training finishes, the model file should be written into ./poc/site-1/run_1/test.model.json and ./poc/site-2/run_1/test.model.json respectively.

Finally, shutdown everything from the admin CLI:

shutdown client
shutdown server