NS-PhD-Research / HACCS

Accelerating FL training by exploiting system and data heterogeneity at device level

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HACCS

This repository contains the code used to perform experiments for our heterogeneity-aware federated learning system. If you find this code useful, feel free to cite our releated research.

@INPROCEEDINGS{9820684,
  author={Wolfrath, Joel and Sreekumar, Nikhil and Kumar, Dhruv and Wang, Yuanli and Chandra, Abhishek},
  booktitle={2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS)}, 
  title={HACCS: Heterogeneity-Aware Clustered Client Selection for Accelerated Federated Learning}, 
  year={2022},
  volume={},
  number={},
  pages={985-995},
  doi={10.1109/IPDPS53621.2022.00100}
}

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Accelerating FL training by exploiting system and data heterogeneity at device level

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