Difference between revisions of "BPI-EAI80 AI board"

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= Introduction=
 
[[File:Banana_PI_BPI-EAI80_3.JPG|thumb|BPI-EAI80 AI board Gree EAI80 chip design]]
 
[[File:Banana_PI_BPI-EAI80_5.JPG|thumb|[[BPI-EAI80 AI board]] Gree EAI80 chip design]]
 
[[File:BPI-AI_1.JPG|thumb|[[BPI-AI]] Kendryte K210 RISC-V]]
 
[[File:Webduino_gif.gif|thumb|[[BPI-Bit]] with ESP32 design ]]
 
[[File:BPI-K210_1.JPG|thumb|[[BPI-K210 RISC-V AIoT board]]]]
 
  
BPI-EAI80 board use Edgeless EAI80 chip design .
 
 
 
=About Edgeless EAI series=
 
 
EAI series crossover AI MCU, CPU core is based on ARM Cortex-M4, ARMv7-M supports a
 
predefined 32-bit address space, with subdivision for code, data, and peripherals, and regions for
 
on-chip and off-chip resources, where on-chip refers to resources that are tightly coupled to the
 
processor.
 
EAI is a multi-core microcontroller implementing Dual-ARM Cortex-M4 cores. All cores have
 
access to the complete memory map. One ARM Cortex-M4 is used as the master processor. The
 
other ARM Cortex-M4 core can be used as a co-processor to off-load the ARM Cortex-M4 and to
 
perform complicated mathematical calculations.
 
CNN processor is integrated in EAI, which can handle image detection and recognition use deep
 
learning methods with high performance and low energy consumption. It supports mainstream
 
CNN model such as Resnet-18, Resnet-34, Vgg16, GoogleNet, Lenet etc, convolutional with kernel
 
size from 1 up to 7, channel/feature number up to 512, max/average pooling function with kernel
 
 
EAI chip Device Summary
 
 
[[File:Eai80_chip.png]]
 

Latest revision as of 20:41, 17 April 2020