Who is this for?
This is an introductory topic for developers and data scientists new to TinyML who want to observe ExecuTorch performance on a physical device.
What will you learn?
Upon completion of this Learning Path, you will be able to:
- Bring up a custom ExecuTorch `executor_runner` firmware on the FRDM i.MX 93 Cortex-M33 using Linux RemoteProc
- Compile an ExecuTorch `.pte` model for Ethos-U65 and run inference with NPU acceleration
- Understand how heterogeneous Arm systems split responsibilities across application cores, microcontrollers, and NPUs
Prerequisites
Before starting, you will need the following:
- An NXP
FRDM i.MX 93
development board
- A USB Mini-B to USB Type-A cable, or a USB Mini-B to USB Type-C cable
- Completion of
Use Linux on an NXP FRDM i.MX 93 board
(Linux setup, login access, and file transfer)
- Basic knowledge of Machine Learning concepts
- A host computer to compile ExecuTorch libraries