Catalyst-Neuromorphic/shd-snn-benchmark

Catalyst SHD SNN Benchmark (N3)

Spiking Neural Network for spoken digit classification on SHD. Achieves 91.0% with adaptive LIF neurons.

Model Description

• Architecture (N3): 700 → 1536 (recurrent adLIF) → 20
• Neuron model: Adaptive Leaky Integrate-and-Fire (adLIF) with learnable per-neuron thresholds
• Training: Surrogate gradient BPTT, fast-sigmoid surrogate (scale=25)
• Hardware target: Catalyst N3 neuromorphic processor

Results

Metric	Value
Float accuracy	91.0%
Parameters	3,470,484

Reproduce

git clone https://github.com/catalyst-neuromorphic/catalyst-benchmarks.git
cd catalyst-benchmarks
pip install -e .
python shd/train.py --neuron adlif --hidden 1536 --epochs 200 --device cuda:0 --amp

Links

• Benchmark repo: catalyst-neuromorphic/catalyst-benchmarks
• Cloud API: catalyst-neuromorphic.com
• N3 paper: Zenodo DOI 10.5281/zenodo.18881283
• N2 paper: Zenodo DOI 10.5281/zenodo.18728256
• N1 paper: Zenodo DOI 10.5281/zenodo.18727094

Citation

@misc{catalyst-benchmarks-2026,
  author = {Shulayev Barnes, Henry},
  title = {Catalyst Neuromorphic Benchmarks},
  year = {2026},
  url = {https://github.com/catalyst-neuromorphic/catalyst-benchmarks}
}