mlsanityData to 14 Oct 2026

CHAMP: Coherent Hardware-Aware Magnitude Pruning of Integrated Photonic Neural Networks

arXiv 2112.06098 ↗First posted 11 Dec 2021cs.ET cs.LGcited by 2

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Abstract (arXiv)

We propose a novel hardware-aware magnitude pruning technique for coherent photonic neural networks. The proposed technique can prune 99.45% of network parameters and reduce the static power consumption by 98.23% with a negligible accuracy loss.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 0 of its 3 references that are in the map. First posted on arXiv 11 Dec 2021.

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Citing papers per year: 2022: 1; 2023: 0; 2024: 1.

2 papers.

  1. 2022Characterizing Coherent Integrated Photonic Neural Networks under Imperfectionscited by 4
  2. 2024Accelerating Neural Networks for Large Language Models and Graph Processing with Silicon Photonicscited by 1