Power-Performance Characterization of TinyML Systems
Yujie Zhang, Dhananjaya Wijerathne, Zhaoying Li, Tulika Mitra · 2022 IEEE 40th International Conference on Computer Design (ICCD) · 2022
TinyML systems are enabling machine learning (ML) inference at the edge. However, there exists little quantitative analysis of such systems. This paper presents a systematic performance and power characterization of diverse TinyML applications on micro-controllers (MCUs), spanning neural network models, software libraries, operating systems, and hardware architectures. We focus on the impact of the multiple layers of abstractions that provide higher programmability at the expense of performance and energy efficiency. We propose a model to estimate the costs of different abstraction layers and make recommendations for minimizing those costs. Our findings can help designers with Neural Architecture Search (NAS) and CNN inference optimization on edge devices.