Skip to main content

FL Lifecycle Operations Management Platform

Reason this release was yanked:

이전 버전으로 롤백

Project description

FedOps: Federated Learning Lifecycle Operations Management Platform

FedOps | Slack | LinkedIn | CCL Site | Youtube

GitHub license Slack

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 details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

fedops-1.1.30.2.tar.gz (38.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

fedops-1.1.30.2-py3-none-any.whl (48.3 kB view details)

Uploaded Python 3

File details

Details for the file fedops-1.1.30.2.tar.gz.

File metadata

  • Download URL: fedops-1.1.30.2.tar.gz
  • Upload date:
  • Size: 38.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.9

File hashes

Hashes for fedops-1.1.30.2.tar.gz
Algorithm Hash digest
SHA256 deea8e5345d87cbfd980fd3a652808d2d510047f97e199d7a3154a4a27e9703c
MD5 04b87b84a764494cc33ee1a1d95f10aa
BLAKE2b-256 eb3a0da85aff785c8adb1158b24e8193ec3b00e719fe3c48e50759642445818c

See more details on using hashes here.

File details

Details for the file fedops-1.1.30.2-py3-none-any.whl.

File metadata

  • Download URL: fedops-1.1.30.2-py3-none-any.whl
  • Upload date:
  • Size: 48.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.9

File hashes

Hashes for fedops-1.1.30.2-py3-none-any.whl
Algorithm Hash digest
SHA256 6811a0e5a08e57ed446dd43c408c850a7e519ee5b444e6b7b8adeb0b691c1425
MD5 751dd10d5cc2e0b3df72a04395fce45b
BLAKE2b-256 73cf95369e64838f805e80750e1b13c908e0ec61de5ea00a8868d52dc2682af1

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page