Hardware/Software Codesign

Description

The course gives a high-level introduction to topics in hardware/software codesign and the elements of a codesign process. The theoretical foundations and practical implementation of machine learning models on resource constrained devices (commonly denoted embedded AI) are explored with lectures, hands-on exercises, and project work. Through a series of lectures and hands-on exercises, students are expected to be able to train, evaluate, and deploy a machine learning model to a microcontroller-based system at the end of the course. Methods for exploring trade-offs in pure software vs hardware-accelerated implementations are explored including multi-parametric optimization to account for various metrics including accuracy, inference latency, memory use, and energy consumption.