MLIA Ethos-U Plugin

This package contains the MLIA target plugin for Arm Ethos-U platforms and packages the Ethos-U backend integrations used by MLIA.

The package is distributed as mlia-ethos-u and contributes:

• The ethos_u target plugin.
• The vela backend plugin.
• The corstone backend plugin.
• Bundled Ethos-U target profiles and Vela configuration assets.

Table of Contents

• Overview
• Supported targets
• Backends in this package
• Installation
• Reporting bugs
• Development setup
• Common commands
• Project layout
• Documentation
• Trademarks and copyrights

Overview

mlia-ethos-u is the main MLIA plugin package for Ethos-U inference analysis. It extends the core MLIA framework with Arm Ethos-U target knowledge, operator analysis, bundled target profiles, and the backend integrations required for Vela compilation and Corstone-based performance flows.

This is the package to install when you want MLIA to analyse LiteRT / TensorFlow Lite .tflite models for Ethos-U55, Ethos-U65, or Ethos-U85 targets, or when you want to run the Corstone-based ExecuTorch AOT path for supported PyTorch inputs.

Supported targets

Bundled target profiles include:

• ethos-u55-128
• ethos-u55-256
• ethos-u65-256
• ethos-u65-512
• ethos-u85-128
• ethos-u85-256
• ethos-u85-512
• ethos-u85-1024
• ethos-u85-2048

These profiles are shipped under src/mlia/resources/target_profiles/.

Backends in this package

Vela

The Vela backend is used for compiler-oriented analysis, compatibility checks, and Ethos-U performance-related reporting based on the Vela toolchain.

Corstone

The Corstone backend supports simulation-oriented performance flows for Corstone platforms used in Ethos-U analysis and validation. It is also the backend path used for supported ExecuTorch .pte workloads.

Installation

Install into an environment that already contains mlia:

pip install mlia-ethos-u

If you want MLIA to accept PyTorch .pt2 inputs directly for the ExecuTorch flow, install the matching converter plugin as well:

pip install mlia-converters-pytorch

A typical MLIA workflow then references one of the bundled profiles, for example:

mlia check model.tflite --target-profile ethos-u55-256

For supported ExecuTorch AOT flows, a PyTorch-originating run can look like:

mlia check model.pt2 --target-profile ethos-u55-256 --performance --backend corstone-300

Direct .pt2 support depends on mlia-converters-pytorch, and the current Corstone ExecuTorch path is only available for selected target and backend combinations.

The package depends on mlia>=0.11.0.dev36 and is intended to be used as part of a wider MLIA installation rather than as a standalone CLI.

Reporting bugs

Report bugs by creating GitHub issues. Use the arm/mlia issue tracker by default.

Only open an issue in arm/mlia-ethos-u when the bug is clearly and specifically in this plugin.

Development setup

Create a local environment with the project and all development dependencies:

uv sync --group dev

If you only need the test dependencies:

uv sync --group test

This repository currently does not use a committed lock file (uv.lock).

Common commands

Run the quick test suite used in CI:

uv run pytest -m "not slow" tests/

Run the full test suite with coverage:

uv sync --group test
uv run pytest tests/

Run the local quality checks:

uv run pre-commit run --all-files

Build the package:

uv build

Project layout

• src/mlia/target/ethos_u/: target integration, advisor logic, reporting, and analysis pipeline for Ethos-U.
• src/mlia/backend/vela/: Vela backend integration.
• src/mlia/backend/corstone/: Corstone backend integration.
• src/mlia/resources/target_profiles/: bundled Ethos-U target profiles.
• src/mlia/resources/vela/: bundled Vela configuration.
• tests/: unit, integration, and CLI coverage for targets and backends.

Documentation

Additional package documentation lives in docs/README.md.

Trademarks and copyrights

• Arm, Arm Ethos-U, Arm Cortex-M, and Arm Corstone are registered trademarks or trademarks of Arm Limited (or its subsidiaries) in the U.S. and/or elsewhere.
• TensorFlow is a trademark of Google LLC.
• PyTorch and ExecuTorch are trademarks of The Linux Foundation.
• Linux is the registered trademark of Linus Torvalds in the U.S. and elsewhere.
• Python is a registered trademark of the PSF.