AIO-1684JD4

Octa-Core High Computing Power AI Mainboard

Powered by SOPHON AI processor BM1684, this mainboard can be configured with 12GB RAM. INT8 computing power is up to 17.6TOPS. It
supports mainstream frameworks and complete, easy-to-use toolchain, featuring low cost of algorithm migration. With various interfaces, it is
easy to integrate into various edge embedded products. It can be applied to various AI scenarios, such as visual computing, edge computing,
general computing power services, security surveillance, UAV etc.

New-gen AI processor BM1684

This mainboard is powered by SOPHON AI processor BM1684, which is octa-core ARM Cortex-A53, up to 2.3GHz clock speed and 12nm
lithography process. With up to 17.6Tops INT8 computing power or 2.2Tops FP32 high-precision computing power, it supports mainstream
programming frameworks, which can be widely used in artificial intelligence inference for cloud and edge applications.

Powerful video AI performance

Up to 32-channel 1080P H.264/H.265 video decoding is supported. It can process and analyze more than 16-channel HD video at the same
time, meeting the needs of various AI application scenarios, such as face detection on video streaming, license plate recognition, etc.

High throughput and energy efficiency ratio

Based on INT8 quantified Batch4 measured data, AIO-1684JD4 has higher throughput and energy efficiency ratio than the mainstream
intelligent computing module platform in the industry, and has more advantages in performance.

Strong network expansion capability

It supports dual 1000Mbps Ethernet, 2.4GHz/5GHz dual-band WiFi, expandable 5G/4G LTE network, enabling higher-rate communication.

One-stop toolkit, convenient and efficient

The BMNNSDK2 one-stop deep learning development toolkit provides a series of software tools including the underlying driver environment,
compiler and inference deployment tool. It supports mainstream frameworks: Caffe/TF/PyTorch/Mxnet/Paddle, mainstream network model and
custom operator development, Docker containerization, and rapid deployment of algorithm applications.

Complete software and hardware

With a complete software framework, Artificial Intelligence inference for cloud and edge applications can be easily achieved. All of them accelerate
development of edge applications, such as face recognition, video structuring, abnormal alarm, equipment inspection, and situation prediction, etc.

A variety of interfaces

With HDMI, mSATA, USB3.0, USB2.0, RS485 and RS232, this mainboard can be directly applied to AI edge computing products.

A wide range of applications

The mainboard can efficiently adapt to all AI algorithms on the market and integrate into edge computing boxes, which promote development of industries through AI, such as visual computing, edge computing, general computing power services, Artificial Intelligence, intelligent construction
site, intelligent transportation, smart classes, unmanned supermarkets, security surveillance.

Computing server
Edge calculation
AI
Traffic control
Self service market
Security

Specifications

Basic Specifications
SOC

SOPHON BM1684

CPU

Integrated high-performance octa-core ARM A53, 12nm lithography process, clock speed up to 2.3GHz

TPU

Built-in tensor computing module TPU, computing power up to:

17.6T (INT8) / 2.2T(FP32) / 35.2 T(INT8, enable winograd)

TPU contains 64 NPU arithmetic units. Each NPU contains 16 EU arithmetic units, 1024 EU in total.

Support mainstream programming frameworks, such as TensorFlow / Caffe / PyTorch / Paddle /

ONNX / MXNet / Tengine / DarkNet

VPU

Up to 32-channel H.265/H.264 1080p@30fps video decoding

1080p@50fps video encoding

MJPEG image encoding and decoding up to 1080P@480fps

RAM

12GB LPDDR4/LPDDR4X

Storage

16GB/32GB/64GB/128GB eMMC

Storage Expansion

M.2 SATA3.0 SSD(2242) ×1

TF card slot ×1

Hardware Specifications
Ethernet

1000Mbps Ethernet ×2

Wireless

2.4GHz/5GHz dual-band WiFi, 802.11a/b/g/n/ac

expanded with 4G LTE (Mini PCIe interface), 5G (M.2)

Video Output

HDMI1.4(1080p@30fps)×1

Audio Output

HDMI1.4 audio output×1

SATA

M.2 SATA3.0 (expanded with 2242 SATA SSD) ×1

USB

USB3.0 (current limit: 1A) ×2

USB2.0 (current limit: 500mA) ×2

Power

DC12V (DC5.5×2.5mm)

Other Interfaces

RS232×1

RS485×1

Debug(3P-2.0mm)×1

FAN(12V,4P-1.25mm)×1

OS/Software
OS

Ubuntu

General
Size

149mm × 97mm × 37.45mm

Power Consumption

Typical: 18W (12V/1500mA)

Max: 30W (12V/2500mA)

Environment

Operating Temperature: -20℃~60℃

Storage Temperature: -20℃~70℃

Operating humidity: 10%~90% (non-condensing)