Embedded ML Inference for Cortex-M Systems

Designed to accelerate ML inference in area-constrained embedded and IoT devices, the Ethos-U55 NPU enables low-cost, power efficient AI solutions. The Ethos-U55, combined with the AI-capable Arm Cortex-M55 processor provides a 480 times uplift in ML performance over existing Cortex-M based systems.

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Features and Benefits

Partner Configurable

Multiple configurations allow designers to rapidly target a wide variety of AI applications with up to 480x increase in performance.

Extremely Small Area

 Ethos-U55 delivers up to 90% energy reduction in about 0.1mm2 for AI applications in cost-sensitive and energy-constrained devices.

Single Toolchain

A unified toolchain for Ethos-U55 and Cortex-M simplifies developer use and creation of AI applications. 

Future Proof

Provides native support for the most common ML network operations, including CNN and RNN, while allowing for future ML innovations. 

Unlock the Benefits of AI with this Best-in-Class Solution

The combination of world-class hardware IP, easy-to-use tools, open-source software, and a leading ecosystem means the Cortex-M55 processor is transforming the future of small embedded, automotive, and IoT devices. The Cortex-M55 processor is part of a wider solution that includes the following key components to enable the next generation of AI devices: 

Partner Collaboration Pushes Boundaries in Endpoint AI

 

Watch this video with Michal Gabrielczyk, Head of Edge AI at Cambridge Consultants to hear how Ethos-U55 is enabling endpoint AI for their customers, sparking innovation of voice activation, image classification and gesture recognition applications.

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Discover how the Ethos-U55 microNPU can deliver significant ML in deeply embedded systems.

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Mbed OS is an open-source, embedded operating system that includes all the necessary features for the development of IoT connected products, including standards-based security and connectivity stacks, an RTOS, and drivers for sensors and I/O devices.

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Common Microcontroller Software Interface Standard – Efficient Neural Network Implementation (CMSIS-NN) is a collection of efficient neural network kernels developed to maximize the performance and minimize the memory footprint of neural networks on Cortex-M processor cores.