MinUn: Accurate ML Inference on Microcontrollers. (arXiv:2210.16556v1 [cs.LG])

Running machine learning inference on tiny devices, known as TinyML, is an
emerging research area. This task requires generating inference code that uses
memory frugally, a task that standard ML frameworks are ill-suited for. A
deployment framework for TinyML must be a) parametric in the number
representation to take advantage of the emerging representations like posits,
b) carefully assign high-precision to a few tensors so that most tensors can be
kept in low-precision while still maintaining model accuracy, and c) …

arxiv inference microcontrollers