FedOps: Federated Learning Lifecycle Operations Management Platform

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FedOps (fedops) is a platform that helps organizations effectively manage and coordinate their federated learning operations:

  • FLScalize: It simplifies the application of data and models in a FL environment by leveraging Flower's Client and Server.

  • Manager: The manager oversees and manages the real-time FL progress of both clients and server

  • CE/CS: Contribution Evaluation and Client Selection processes based on their performance.

  • CI/CD/CFL: the CI/CD/CFL system seamlessly integrates with a Code Repo, enabling code deployment to multiple clients and servers for continuous or periodic federated learning.

  • Monitoring: The FL dashboard is available for monitoring and observing the lifecycle of FL clients and server

FedOps Tutorial

FedOps has developed a web service to manage the lifecycle operations of federated learning on real devices.

  • Install FedOps Library
$ pip install fedops

Real Devices

Single Machine

Community

Paper

FLScalize: Federated Learning Lifecycle Management

@article{Cognitive Computing Lab,
  title={FLScalize: Federated Learning Lifecycle Management},
  author={Semo Yang; Jihwan Moon; Jinsoo Kim; Kwangkee Lee; Kangyoon Lee}, 
  journal={IEEE Access},
  Page(s)={47212 - 47222}
  DOI={10.1109/ACCESS.2023.3275439}
  year={2023}
}

Support

For any questions or issues, please contact the FedOps support team at gyom1204@gachon.ac.kr

Project links

Key dates

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  • Released:
Newer release available (1.1.30.17)

2 maintainers

PyPI data
Data sourced directly from PyPI's database.
Avatar for Semo from gravatar.com Semo Avatar for z8086486 from gravatar.com z8086486

Credits

PyPI data
Data sourced directly from PyPI's database.

Author: Semo Yang

License

MIT License

Classifiers

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