Optimizing the Deployment of Tiny Transformers on Low-Power MCUs

arXiv:2404.02945v1 Announce Type: new
Abstract: Transformer networks are rapidly becoming SotA in many fields, such as NLP and CV. Similarly to CNN, there is a strong push for deploying Transformer models at the extreme edge, ultimately fitting the tiny power budget and memory footprint of MCUs. However, the early approaches in this direction are mostly ad-hoc, platform, and model-specific. This work aims to enable and optimize the flexible, multi-platform deployment of encoder Tiny Transformers on commercial MCUs. We propose a …

abstract arxiv budget cnn cs.ai cs.dc cs.lg cs.pf deployment edge fields however low mcus memory networks nlp power sota transformer transformer models transformers type