yyyanbj/fedhf
🔨 A Flexible Federated Learning Simulator for Heterogeneous and Asynchronous.
This is a tool for machine learning researchers and practitioners who are experimenting with federated learning. It allows you to simulate and test different federated learning algorithms on various data and hardware configurations. You provide your decentralized datasets and choose an algorithm, and the tool simulates how a model would be trained collaboratively across many devices without centralizing data.
No commits in the last 6 months.
Use this if you need to research or develop federated learning models and want a flexible simulator to test different aggregation strategies, especially with heterogeneous computing resources and asynchronous updates.
Not ideal if you are looking for a tool to deploy federated learning models in a production environment, as this is primarily a research and simulation framework.
Stars
23
Forks
1
Language
Python
License
Apache-2.0
Category
Last pushed
Aug 19, 2022
Commits (30d)
0
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