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.

Features

  • 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

Project Samples

NVIDIA FLARE Screenshot 1

Project Activity

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Categories

Artificial Intelligence, Machine Learning, Federated Learning Frameworks

License

Apache License V2.0

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NVIDIA FLARE Web Site

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Additional Project Details

Programming Language

Python

Related Categories

Python Artificial Intelligence Software, Python Machine Learning Software, Python Federated Learning Frameworks

Registered

2023-03-24
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