AIO-3399C(AI) Six-Core Open Source Main Board with Bundles

Six-Core Open Source Main Board
Adopts Rockchip six-core 64 bit processor, carries modular neural deep-learning accelerator NPU with no external buffer memory needed. It has strong peak power and super high performance, supports Pytorch, Caffe deep-learning framework, and provides complete and user-friendly model training tools and web training model cases, enabling it to be rapidly used for mobile edge computing.

Available in 3 Packages
Board
USB Type A to A Male/Male Cable, 12V PSU, USB Type A to C Male/Male Cable & Antenna
Basic Package
As above plus Heat sink, USB to UART and 128GB USB stick
Advanced Package
As above plus 10.1" Monitor, 1080P Camera, 16GB TF Card and 4G Module

64-bit High-performance Core
Equipped with ARM Cortex-A72 architecture, six-core 64-bit high-performance processor, frequency up to 2.0 GHz. It integrates a quad-core Mali-T860 GPU, supports H.265 HEVC and VP9, H.264 encoding and 4K HDR, and with a powerful hard decoding capability as high as 4K. 

Artificial Intelligence Processor NPU
Carried an Al embedded neural network processor NPU, which has the peak  performance of up to 5.6 Tops and computing performance 2.8 Tops, with an energy efficiency of up to 9.3 Tops/W. with an energy efficiency of up to 9.3 Tops/W. This ensures a powerful peak power while maintaining extremely low power consumption, giving it huge advantages in the field of edge computing used in terminal devices.

Unique Al Architecture APiM
AIO-3399C (Al)adopts Al-specific MPE matrix engine and APiM (Al processing in Memory) architecture, local parallel Al computing that combines storage and computing, one-time upgrade network preload with no need of instructions,
bus, and external DDR cache. This configuration improves the processing speed hugely and lowers processing energy consumption a lot compared with processors built in traditional architecture approaches.

Supporting Model Training Tools
It provides complete and easy-to-use PyTorch-based model training tool PLAI (People Learn Al), can be developed on Windows 10 and Ubuntu 16.04 systems, and supports fast and easy adding of custom network models, greatly reducing the technical barriers of using Al and allowing more people to open the gate of Al easily.

Provide Network Training Models
Supports the following three network training model examples such as GNet1, GNet18 and GNetfc with more network instances continuing to emerge subsequently, making it possible to easily test a large number of deep learning applications on the device.

Excellent Industrial Applicability
Equipped with industrial grade metal casing, featuring small size, fanless efficient heat dissipation, dustproof and anti-disruption. It has various installation methods and can be flexibly embedded in various smart devices.

Rich External Interfaces
AIO-3399C(AI) can be powered by POE+ (802.3 AT, output power 30W) enhanced Ethernet. It with external expansion interfaces such as RS232, RS485 and 2 TTL, which is convenient for connecting various industrial devices.