Skip to content
forked from NVIDIA/NVFlare

NVIDIA Federated Learning Application Runtime Environment

License

Notifications You must be signed in to change notification settings

siomvas/NVFlare

This branch is up to date with NVIDIA/NVFlare:dev.

Folders and files

NameName
Last commit message
Last commit date

Latest commit

5aef697 · Aug 16, 2023
Jun 6, 2023
Jun 22, 2023
Apr 12, 2023
Sep 19, 2022
Jul 29, 2023
Aug 4, 2023
Aug 4, 2023
Aug 4, 2023
Aug 16, 2023
Aug 4, 2023
Mar 8, 2022
Mar 21, 2023
Mar 9, 2023
Nov 3, 2022
May 12, 2022
Mar 15, 2023
Apr 6, 2023
Nov 23, 2021
Mar 8, 2022
Mar 15, 2023
Feb 22, 2023
Sep 8, 2022
Jan 26, 2023
Nov 4, 2022
Aug 2, 2023
Aug 2, 2023
Jul 29, 2023
Mar 8, 2022

Repository files navigation

NVIDIA Federated Learning Application Runtime Environment

NVIDIA FLARE is a domain-agnostic, open-source, extensible SDK that allows researchers and data scientists to adapt existing ML/DL workflows(PyTorch, TensorFlow, Scikit-learn, XGBoost etc.) to a federated paradigm. It enables platform developers to build a secure, privacy-preserving offering for a distributed multi-party collaboration.

NVIDIA FLARE is built on a componentized architecture that allows you to take federated learning workloads from research and simulation to real-world production deployment. Key components include:

  • Support both deep learning and traditional machine algorithms
  • Support horizontal and vertical federated learning
  • Built-in FL algorithms (e.g., FedAvg, FedProx, FedOpt, Scaffold, Ditto )
  • Support multiple training workflows (e.g., scatter & gather, cyclic) and validation workflows (global model evaluation, cross-site validation)
  • Support both data analytics (federated statistics) and machine learning lifecycle management
  • Privacy preservation with differential privacy, homomorphic encryption
  • Security enforcement through federated authorization and privacy policy
  • Easily customizable and extensible
  • Deployment on cloud and on premise
  • Simulator for rapid development and prototyping
  • Dashboard UI for simplified project management and deployment
  • Built-in support for system resiliency and fault tolerance

Installation

To install the current release, you can simply run:

$ python3 -m pip install nvflare

Getting started

You can quickly get started using the FL simulator.

A detailed getting started guide is available in the documentation.

Examples and notebook tutorials are located here.

Related talks and publications

For a list of talks, blogs, and publications related to NVIDIA FLARE, see here.

License

NVIDIA FLARE has Apache 2.0 license, as found in LICENSE file.

About

NVIDIA Federated Learning Application Runtime Environment

Resources

License

Code of conduct

Citation

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Python 89.3%
  • Jupyter Notebook 10.1%
  • Other 0.6%