Fast Clifford Neural Layers

Tianxiang Xia; Max Neuwinger; Lin Xiao

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arXiv · 2507.01040

Fast Clifford Neural Layers

Tianxiang Xia·Max Neuwinger·Lin Xiao

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Abstract

Clifford Neural Layers improve PDE modeling by introducing Clifford Algebra into neural networks. In this project we focus on optimizing the inference of 2/3D Clifford convolutional layers and multivector activation layers for one core CPU performance. Overall, by testing on a real network block involving Clifford convolutional layers and multivector activation layers, we observe that our implementation is 30% faster than standard PyTorch implementation in relatively large data + network size (>L2 cache). We open source our code base at https://github.com/egretwAlker/c-opt-clifford-layers

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cs.LG cs.AI cs.NE cs.PF

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BibTeX RIS

Tianxiang Xia, Max Neuwinger, Lin Xiao. 2025-06-22. Fast Clifford Neural Layers. https://arxiv.org/abs/2507.01040

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