Core-1684JD4
8-Core High Computing Power AI Core Board
Powered by SOPHON AI processor BM1684, this core board can be configured with 12GB RAM.INT8 computing power is up to 17.6TOPS. It supports mainstream frameworks and a complete, easy-to-use toolchain, featuring a low cost algorithm migration. Backplane reference design is provided for users to make further customization. It can be applied to various AI scenarios, such as visual computing, edge computing, general computing power services, intelligent transportation, unmanned supermarkets, security surveillance, UAVs, etc.
New-gen AI processor BM1684
This core board is powered by SOPHON AI processor BM1684, octa-core ARM Cortex-A53, up to 2.3GHz clock speed and a 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 simultaneously,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, Core-1684JD4 has a higher throughput and energy efficiency ratio than thindustry's e mainstream intelligent computing module platfory, and has more advantages in performance.
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 PCIe3.0, GMAC, SDIO3.0, I2C, PWM, UART and GPIO, it is easy to integrate into various edge embedded products and accelerate product development.
High-performance mainboard
The core board adopts 260P standard SODIMM interface with immersion gold technology, which is small in size. It can be combined with a backplane to form a complete high-performance mainboard with richer expansion interfaces.
Provide backplane reference design
Backplane reference design and complete technical information are provided, so users can efficiently proceed with secondary development to quickly create independent and controllable products.
A wide range of applications
The core board 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.
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 |
6GB/12GB LPDDR4/LPDDR4X |
| Storage |
32GB/64GB/128GB eMMC |
| Hardware Specifications | |
| Ethernet |
Dual 1000Mbps Ethernet can be extended through GMAC |
| Power |
12V/5A |
| Interfaces |
PCIe3.0、GMAC、SDIO3.0、I2C、PWM、UART、GPIO |
| OS/Software | |
| OS |
Linux |
| General | |
| Size |
69.6mm × 55mm |
| Power Consumption |
Typical：≈ 8.2W(12V/680mA) Max：≈ 19W(12V/1580mA) |
| Environment |
Operating Temperature: -20℃～60℃ Storage Temperature: -20℃～70℃ Operating humidity: 10%～90% (non-condensing) |
