HIFI: Heterogeneous Spiking Framework
with Self-Inhibiting Neurons

This is the official PyTorch implementation for Biologically inspired heterogeneous learning for accurate, efficient and low-latency neural network.

The paper has been accepted by National Science Review (NSR).

Installation

Install requirements by typing pip install -r requirements.txt.

System Requirements

• No special system requirements.
• The software has been tested on the Linux desktop (Ubuntu 20.04.3 LTS operation system) with Intel(R) Xeon(R) Gold 6226R CPU and NVIDIA Geforce RTX 3090 (Driver Version: 535.171.04, CUDA Version: 12.2).

Citation

Please cite our paper if you find it useful in your research:

@article{wang2024biologically,
  title={Biologically inspired heterogeneous learning for accurate, efficient and low-latency neural network},
  author={Wang, Bo and Zhang, Yuxuan and Li, Hongjue and Dou, Hongkun and Guo, Yuchen and Deng, Yue},
  journal={National Science Review},
  pages={nwae301},
  year={2024},
  publisher={Oxford University Press}
}

License

HIFI is released under the MIT License. See the LICENSE file for more details.