FedOps: Federated Learning Lifecycle Operations Management Platform
FedOps |
Slack |
LinkedIn |
CCL Site |
Youtube
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
Run FedOps Agent Studio
Docker Desktop 또는 Docker Engine이 설치된 환경에서 다음 명령으로 실행합니다.
fedops run agent-studio
이 명령은 현재 OS와 CPU architecture에 맞는
gachonccl/fedops-agent-studio:latest 이미지를 확인하고,
~/fedops-workspace를 로컬 Workspace로 연결한 뒤 브라우저를 엽니다.
NVIDIA Container Runtime이 준비된 Linux/Windows 환경에서는 GPU를 자동 사용하고,
그 외 환경에서는 CPU 모드로 실행합니다.
실제 컨테이너를 변경하지 않고 실행 구성을 먼저 확인할 수 있습니다.
fedops run agent-studio --dry-run
Workspace, Studio port 또는 GPU 모드를 명시하려면 다음 옵션을 사용합니다.
fedops run agent-studio --workspace ~/fedops-workspace --port 24368 --gpu auto
Agent Studio와 로컬 Host integration을 종료하고 결과를 확인하려면 다음 명령을 사용합니다.
fedops stop agent-studio
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
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file fedops-1.1.30.15.tar.gz.
File metadata
- Download URL: fedops-1.1.30.15.tar.gz
- Upload date:
- Size: 66.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/7.0.0 CPython/3.11.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
67aa9e16da020f9cb5edf4b1c2f06ae220a9d9fc45a9f674b132bac13b8f67b5
|
|
| MD5 |
72596083e5caad4381e08c2aae0cb76b
|
|
| BLAKE2b-256 |
d74ff06c7bf80f84d1d350479c5d38ad81bb1f8bdbcc30dced5e39db7944efda
|
File details
Details for the file fedops-1.1.30.15-py3-none-any.whl.
File metadata
- Download URL: fedops-1.1.30.15-py3-none-any.whl
- Upload date:
- Size: 76.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/7.0.0 CPython/3.11.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
57bf250d8d14eb17d6699d6dca60de75cbd332b600b026115fdad55c679c0f0e
|
|
| MD5 |
0a5ad3824338bda86c874d81e216503e
|
|
| BLAKE2b-256 |
1a3489aba68d4a307c47ae7e376b1fb8a66271416bd09776593c6e5d44c9fcdf
|
