Machine learning is a hot topic in the automotive industry. Deploying machine learning algorithms to electronic control units (ECUs) is often a bottleneck because of the memory, CPU throughput, and software development and integration techniques required to support machine learning algorithms.

In this presentation, Gokhan Atinc provides an overview of machine learning technologies and deployment workflows for embedded processors. He will also discuss advanced capabilities that are of interest for automotive and adjacent industries, including in-place modification support, Simulink^® support, and fixed-point conversion.