edge-ai

Edge AI

A curated collection of resources for developing artificial intelligence at the edge of devices

A curated list of resources for embedded AI

GitHub
369 stars
25 watching
42 forks
last commit: 3 months ago
Linked from 1 awesome list

artificial-intelligenceawesome-listedge-computingembedded

Hardware
OpenMV A camera that runs with MicroPython on ARM Cortex M6/M7 and great support for computer vision algorithms. Now with
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

Hardware / Movidius
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

Hardware
NVIDIA Jetson High-performance embedded system-on-module to unlock deep learning, computer vision, GPU computing, and graphics in network-constrained environments
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)

Hardware / Kendryte K210
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)

Hardware
Kendryte K510 Tri-core RISC-V processor clocked with AI accelerators
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
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)
Maxim MAX78000 SoC based on a Cortex-M4 that includes a CNN accelerator
Beagleboard BeagleV Open Source RISC-V-based Linux board that includes a Neural Network Engine
Syntiant TinyML Development kit based on the Syntiant NDP101 Neural Decision Processor and a SAMD21 Cortex-M0+

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
Embedded Learning Library (ELL) 2,285 6 months ago Microsoft's library to deploy intelligent machine-learned models onto resource constrained platforms and small single-board computers
uTensor 1,729 20 days ago 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
ST X-CUBE-AI Toolkit for generating NN optimiezed for STM32 MCUs
ST NanoEdgeAIStudio Tool that generates a model to be loaded into an STM32 MCU
Neural Network on Microcontroller (NNoM) 950 8 months ago Higher-level layer-based Neural Network library specifically for microcontrollers. Support for CMSIS-NN
nncase 753 6 days ago Open deep learning compiler stack for Kendryte K210 AI accelerator
deepC 562 about 2 years ago Deep learning compiler and inference framework targeted to embedded platform
uTVM 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
Qeexo AutoML Interactive platform to generate AI models targetted to microcontrollers
mlpack C++ header-only fast machine learning library that focuses on lightweight deployment. It has a wide variety of machine learning algorithms with the possibility to realize on-device learning on MPUs
AIfES 222 9 months ago platform-independent and standalone AI software framework optimized for embedded systems
onnx2c 223 8 days ago ONNX to C compiler targeting "Tiny ML"

Other interesting resources
Benchmarking Edge Computing (May 2019)
Hardware benchmark for edge AI on cubesats - Open Source Cubesat Workshop 2018 12 about 6 years ago
Why Machine Learning on The Edge?
Tutorial: Low Power Deep Learning on the OpenMV Cam
TinyML: Machine Learning with TensorFlow on Arduino and Ultra-Low Power Micro-Controllers O'Reilly book written by Pete Warden, Daniel Situnayake
tinyML Summit Annual conference and monthly meetup celebrated in California, USA. Talks and slides are usually
TinyML Papers and Projects 757 18 days ago Compilation of the most recent paper's and projects in the TinyML/EdgeAI field
MinUn 0 over 1 year ago Accurate ML Inference on Microcontrollers

Backlinks from these awesome lists:

More related projects: