ML-TN-006 — Keyword Spotting and Asymmetric Multiprocessing on Orca SBC

Info Box Applies to Machine Learning Applies to Machine Learning Technical Notes Applies to ORCA Technical Notes Applies to ORCA SBC Technical Notes

History

Version	Date	Notes
1.0.0	December 2021	First public release

Introduction

This Technical Note (TN) describes a demo application used to show the combination of an inference algorithm (keyword spotting) and an asymmetric multiprocessing configuration (AMP). This use case can serve as the basis for more complex applications that have to carry out the following tasks:

• Acquiring data from sensors in real-time
• Perform a computationally expensive inference algorithm on the collected data.

This scenario is quite common in the realm of AI at the edge and generally it can not be addressed with a microcontroller-based solution. On the other hand, a classic embedded processor running a complex operating systems such as Linux might not be suited either because unable to handle tight real-time constrained tasked.

In such cases, the power and the flexibility of the NXP i.MX8M Plus can be of much help, as this SoC features a heterogeneous architecture — an ARM Cortex-A53 complex and an ARM Cortex-M7 core — and a Neural Processing Unit (NPU).

The idea is to exploit the heterogeneous architecture to implement an AMP configuration where

• The Cortex-A53 complex running Yocto Linux is devoted to execute the inference algorithm
• The Cortex-M7 takes care of data acquisition from sensors.