Ara-1 M.2 (M-Key) Module for AI-Integrated Cameras and Embedded Systems

ARA-1-M2-MODULE
Not Recommended for New Designs

  • This page contains information on a product not recommended for new designs. Specifications and information herein are subject to change without notice. For additional information, please contact NXP support or your NXP sales representative.

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The Ara-1 M.2 module is a compact AI accelerator designed for edge computing, offering real-time AI inferencing with low power consumption and fast processing speeds. It integrates the Ara-1 Discrete Neural Processing Unit, 1 GB LPDDR4 memory, and supports AI frameworks like TensorFlow, PyTorch and ONNX. It enables on-device AI without cloud connectivity, ensuring low latency and enhanced privacy.

Block Diagram

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NXP Applications Processor and Ara DNPU Connection

ARA-1-DNPU-BD-2

Integration of Ara DNPU and Applications Processors Host with Drivers

ARA-1-DNPU-BD-3

Machine learning deployment flow

ARA-1-DNPU-BD
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Supported Devices

Processors and Microcontrollers

Discrete Neural Processing Units

  • ARA-1-DNPU: Ara-1: Discrete NPU for Optimized Edge-AI

i.MX 8 Applications Processors

  • i.MX8MPLUS: i.MX 8M Plus – Arm® Cortex®-A53, Machine Learning, Vision, Multimedia and Industrial IoT

i.MX 9 Processors

  • i.MX95: i.MX 95 Applications Processor Family: High-Performance, Safety Enabled Platform with eIQ® Neutron NPU

Features

AI model frameworks supported

  • TensorFlow
  • PyTorch
  • ONNX

Form factor

  • M.2-2280 (M-Key) compliant; (22 mm x 80 mm x 10 mm)

AI Model Architectures Supported

  • Convolutional Neural Networks (CNNs)

Performance1

  • Up to 6 eTOPS*

Interface

  • PCIe Gen3 x4

Memory

  • 1 GB LPDDR4 (stores all user models)

Operating system support (Runtime)

  • Linux

Operating voltage (DC supply)

  • 5 V ±10 %

1Maximum performance based on peak computational throughput of Ara-1 (800 MHz) and Host System. Specification subject to change without notice. Performance may vary depending on system configuration.

*eTOPS = equivalent TOPS.

Documentation

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Software

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Note: For better experience, software downloads are recommended on desktop.

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