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crespum
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Description

A curated list of resources for embedded AI

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AI at the edge

A curated list of hardware, software, frameworks and other resources for Artificial Intelligence at the edge. Inspired by awesome-dataviz.

Contents

Hardware

  • OpenMV - A camera that runs with MicroPython on ARM Cortex M6/M7 and great support for computer vision algorithms. Now with support for Tensorflow Lite too.
  • JeVois - A TensorFlow-enabled camera module.
  • Edge TPU - Google’s purpose-built ASIC designed to run inference at the edge.
  • Movidius - Intel's family of SoCs designed specifically for low power on-device computer vision and neural network applications.
    • UP AI Edge - Line of products based on Intel Movidius VPUs (including Myriad 2 and Myriad X) and Intel Cyclone FPGAs.
    • DepthAI - An embedded platform for combining Depth and AI, built around Myriad X
  • NVIDIA Jetson - High-performance embedded system-on-module to unlock deep learning, computer vision, GPU computing, and graphics in network-constrained environments.
    • Jetson TX1
    • Jetson TX2
    • Jetson Nano
  • Artificial Intelligence Radio - Transceiver (AIR-T) - High-performance SDR seamlessly integrated with state-of-the-art deep learning hardware.
  • Kendryte K210 - Dual-core, RISC-V chip with convolutional neural network acceleration using 64 KLUs (Kendryte Arithmetic Logic Unit).
    • Sipeed M1 - Based on the Kendryte K210, the module adds WiFi connectivity and an external flash memory.
    • M5StickV - AIoT(AI+IoT) Camera powered by Kendryte K210
    • UNIT-V - AI Camera powered by Kendryte K210 (lower-end M5StickV)
  • GreenWaves GAP8 - RISC-V-based chip with hardware acceleration for convolutional operations.
  • Ultra96 - Embedded development platform featuring a Xilinx UltraScale+ MPSoC FPGA.
  • Apollo3 Blue - SparkFun Edge Development Board powered by a Cortex M4 from Ambiq Micro.
  • Google Coral - Platform of hardware components and software tools for local AI products based on Google Edge TPU coprocessor.
    • Dev boards
    • USB Accelerators
    • PCIe / M.2 modules
  • Gyrfalcon Technology Lighspeeur - Family of chips optimized for edge computing.
  • ARM microNPU - Processors designed to accelerate ML inference (being the first one the Ethos-U55).
  • Espressif ESP32-S3 - SoC similar to the well-known ESP32 with support for AI acceleration (among many other interesting differences).

Software

  • TensorFlow Lite - Lightweight solution for mobile and embedded devices which enables on-device machine learning inference with low latency and a small binary size.
  • TensorFlow Lite for Microcontrollers - Port of TF Lite for microcontrollers and other devices with only kilobytes of memory. Born from a merge with uTensor.
  • Embedded Learning Library (ELL) - Microsoft's library to deploy intelligent machine-learned models onto resource constrained platforms and small single-board computers.
  • uTensor - AI inference library based on mbed (an RTOS for ARM chipsets) and TensorFlow.
  • CMSIS NN - 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.
  • ARM Compute Library - Set of optimized functions for image processing, computer vision, and machine learning.
  • Qualcomm Neural Processing SDK for AI - Libraries to developers run NN models on Snapdragon mobile platforms taking advantage of the CPU, GPU and/or DSP.
  • X-CUBE-AI - Toolkit for generating NN optimiezed for STM32 MCUs.
  • Neural Network on Microcontroller (NNoM) - Higher-level layer-based Neural Network library specifically for microcontrollers. Support for CMSIS-NN.
  • nncase - Open deep learning compiler stack for Kendryte K210 AI accelerator.
  • deepC - Deep learning compiler and inference framework targeted to embedded platform.
  • uTVM - MicroTVM is an open source tool to optimize tensor programs.
  • Edge Impulse - Interactive platform to generate models that can run in microcontrollers. They are also quite active on social netwoks talking about recent news on EdgeAI/TinyML.

Other interesting resources

Contributing

  • Please check for duplicates first.
  • Keep descriptions short, simple and unbiased.
  • Please make an individual commit for each suggestion.
  • Add a new category if needed.

Thanks for your suggestions!

License

CC0

To the extent possible under law, Xabi Crespo has waived all copyright and related or neighboring rights to this work.

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