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NVIDIA/NVFlare

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NVIDIA/NVFlare

Description: NVIDIA Federated Learning Application Runtime Environment

Language: Python

License: Apache-2.0

Stars: 939

Forks: 262

Open issues: 23

Created: 2021-07-23T17:26:12Z

Pushed: 2026-06-11T01:48:57Z

Default branch: main

Fork: no

Archived: no

README:

NVIDIA FLARE

Website | Paper | Blogs | Talks & Papers | Webinars | [Research](./research/README.md) | Documentation

![Blossom-CI](https://github.com/NVIDIA/nvflare/actions) ![documentation](https://nvflare.readthedocs.io/en/main/?badge=main) ![pypi](https://badge.fury.io/py/nvflare) ![downloads](https://pepy.tech/project/nvflare) ![Ask DeepWiki](https://deepwiki.com/NVIDIA/NVFlare)

NVIDIA FLARE (NVIDIA Federated Learning Application Runtime Environment) is a domain-agnostic, open-source, extensible Python SDK that allows researchers and data scientists to adapt existing ML/DL workflows to a federated paradigm. It enables platform developers to build a secure, privacy-preserving offering for a distributed multi-party collaboration.

Features

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

Application Features

  • Support both deep learning and traditional machine learning algorithms (e.g., PyTorch, TensorFlow, scikit-learn, XGBoost, etc.)
  • Support horizontal and vertical federated learning
  • Built-in Federated Learning algorithms (e.g., FedAvg, FedProx, FedOpt, Scaffold, Ditto, etc.)
  • Support multiple server and client-controlled 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, private set intersection (PSI)

From Simulation to Real-World

  • FLARE Client API to transition seamlessly from ML/DL to FL with minimal code changes
  • Simulator and POC mode for rapid development and prototyping
  • Fully customizable and extensible components with modular design
  • Deployment on cloud and on-premise
  • Dashboard for project management and deployment
  • Security enforcement through federated authorization and privacy policy
  • Built-in support for system resiliency and fault tolerance

> _Take a look at NVIDIA FLARE Overview for a complete overview, and What's New for the latest changes._

Installation

To install the current release:

$ python -m pip install nvflare

For detailed installation please refer to NVIDIA FLARE installation.

Getting Started

  • Structured, self-paced learning is available through curated tutorials and training paths on the website.
  • DLI courses:
  • https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-FX-28+V1
  • https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-FX-29+V1
  • Visit the developer portal.

Community

We welcome community contributions! Please refer to the [contributing guidelines](./CONTRIBUTING.md) for more details.

Ask and answer questions, share ideas, and engage with other community members at NVFlare Discussions.

Related Talks and Publications

Take a look at our growing list of talks and publications, and technical blogs related to NVIDIA FLARE.

License

NVIDIA FLARE is released under an [Apache 2.0 license](./LICENSE).