CHAMP: Coherent Hardware-Aware Magnitude Pruning of Integrated Photonic Neural Networks
We propose a novel hardware-aware magnitude pruning technique for coherent photonic neural networks. The proposed technique can prune 99.45 parameters and reduce the static power consumption by 98.23 accuracy loss.
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