A curated list of edge devices for AI applications.

• Development Platforms
• Custom Accelerators
• Software Libraries

• Baidu EdgeBoard - Xilinx FPGA based edge computing board.
• BeagleBone AI - Linux Board powered by ARM CPU,TI C66x digital-signal-processor (DSP) cores and embedded-vision-engine (EVE). It has 1GB RAM.
• Google Coral Dev Board - It is single board solution which contains ARM CPU and Edge TPU as accelerator with 1GB RAM.
• Google Coral USB Accelerator - Edge TPU accelerator module connects with USB interface. It needs host device.
• Intel Neural Compute Stick 1 - First generation ASIC chip designed by Movidius that runs as module board via USB interface. It needs host device.
• Intel Neural Compute Stick 2 - Second generation module stick which is faster than previous one based TOPS measure. It needs host device.
• Nvidia Jetson AGX Xavier - Most power single board computer from NVIDIA designed for autonomous systems (cars etc.). Contains 512 Cuda core Volta GPU with Tensor Cores and 16 GB RAM.
• Nvidia Jetson Nano - Cost efficient alternative to NVIDIA boards. Performance is equivalent to the TX1. Contains ARM CPU and 128 Cuda core Maxwell GPU and has 4 GB RAM.
• Nvidia Jetson TX1 - Contains ARM CPU and 128 Cuda core Maxwell GPU. It seems like this board is replaced by Nano.
• Nvidia Jetson TX2 - Contains ARM CPU and 256 Cuda core Pascal GPU and has 8 GB/4 GB RAM.
• OrangePi AI Stick - ASIC based neural accelerator. It needs host device.
• Sipeed MAIX Go Suit - Single board computer based on RISC-V AI chip, KPU(Neural Network Processor) and APU(Audio Processor). It contains on-board DVP camera and LCD screen for visual output.
• SmartEdge Agile - Modular Edge Device with IOT capabilities.
• SparkFun Edge Development Board - Apollo3 Blue microcontroller based board that contains microphones and 3-axis accelerometer and OV7670 camera interface. Runs on single coin battery. Supports Tensorflow-lite.
• UP Squared AI Vision X - Single board computer contains Intel ATOM CPU and Movidius Myriad as neural accelerator. It has 4 GB RAM.
• Xnor.ai Solar Powered Module - Very low power unit which can be running with only using solar panels. More technical specifications needed.

• Google Edge TPU
• Intel Movidius Myriad VPU 2
• Intel Movidius Myriad X VPU
• Kendryte K210
• Lightspeeur 280-X Neural Accelerators
• Sipeed MAIX
• TI Vision AcclerationPac

• Tensorflow Lite
• TinyDNN
• uTensor
• EdgeML
• nncase

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