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RUHMI Framework

Solution Toolkit

RUHMI Framework for RA8 MCU (GitHub)RUHMI Framework for RZ/V2 MPU (GitHub)

Overview

Simple for beginners and powerful for experts

Renesas Robust Unified Heterogenous Model Integration (RUHMI) Framework is a set of tools supporting AI application development for Renesas MCU/MPU products. Generate highly optimized models in minutes to run efficiently on Renesas embedded processors.

Why RUHMI Framework?

With a robust compiler and software framework, our solution enables seamless deployment of the latest neural network models across multiple frameworks. By leveraging a common front-end compiler engine* for Renesas' broad portfolio of AI MCU and MPU products, we deliver enhanced user convenience through standardized frameworks and interfaces, ensuring cross-device compatibility and a consistent development experience.

  • Seamless deployment of pre-trained deep neural networks from graph compilation to AI inference using integrated tools, APIs, automated code generation, and runtime support
  • Workflow integration and flexible customization through a standardized Python library across Renesas MCU/MPU families
  • Native support for leading ML frameworks, with ongoing expansion to enable importing common models across devices
  • Framework-independent post-training calibration and quantization for user-defined models
  • Multiple application examples, including models optimized for each supported device
  • Automatic conversion to optimized embedded code for onboard CPUs (RUHMI feature for MCUs) for simplified deployment
  • User-friendly design for smooth model selection, conversion, and storage across supported frameworks and devices
    • Highly configurable CLI environment for Linux
    • Windows environment with an intuitive GUI and expert-level CLI for MCU implementation, supporting diverse development environments

* Powered by EdgeCortix® MERA™ 2.0

Software diagram featuring RUHMI framework, AI framework, and e2studio.
RUHMI Framework with AI Navigator (Windows GUI)
Software diagram featuring RUHMI framework, AI framework, and e2studio.
RUHMI Framework with AI Navigator (Windows GUI)
  • RA8 MCUs
    • Supported frameworks: TensorFlow Lite (.tflite), ONNX (.onnx), PyTorch/ExecuTorch (.pte)
    • OS: Windows (GUI, CLI), Linux (CLI)
  • RZ/V MPUs
    • Supported frameworks: Tensorflow, ONNX, Pytorch
    • OS: Linux (CLI)

For additional information and links, visit GitHub.

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Documentation

Design & Development

Videos & Training

Learn how the Renesas Robust Unified Heterogenous Model Integration (RUHMI) Framework simplifies AI model integration. This tool combines an embedded AI compiler with e2 studio to quickly generate optimized models for Renesas embedded processors, making it ideal for both beginners and experts.

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