[D] Federated Learning Libraries in 2022?

• CommEfficient

  2 69 0.0 Python

  PyTorch for benchmarking communication-efficient distributed SGD optimization algorithms

The libraries I've worked on for Simulation and Production might fit your usecase depending on what your experiment is. I have worked with all the libraries you've mentioned and generally did not feel that they were conducive to the FL research that I do, but without knowing more details about what your experiment is I can't say much more.

• flower

  27 4,166 9.9 Python

  Flower: A Friendly Federated Learning Framework (by adap)

  

I like Flower as it's relatively lightweight, giving you many options to plug and play averaging algorithms on the fly. Also, if necessary to you, they seem to make a big deal about edge devices support in their paper (which I recommend reading regardless of which framework you pick, full of good info!).

• InfluxDB

  www.influxdata.com sponsored

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• FATE

  2 5,498 9.9 Python

  An Industrial Grade Federated Learning Framework

  

FATE is very popular in China.

Suggest a related project