Powered by the third-generation TPU BM1684, this server is equipped with up to 8 BM1684 computing modules. It supports up to 140.8TOPS
of INT8 peak computing power or 17.6TOPS of FP32 high-precision computing power, with the power of multi-channel video encoding and
decoding. It provides multiple algorithm migration and a one-stop deep learning development toolkit. With the BMC management system, it
supports secondary development.
Powered by BM1684 SoC with AI computing power, each computing module features octa-core Cortex-A53 architecture, 2.3GHz
frequency and up to 17.6Tops of AI computing power. It provides 12GB LPDDR4 and 128GB eMMC large storage capacity.
The server can be equipped with up to 8 BM1684 computing modules. Users can customize the number and storage configuration of
computing modules, which are flexibly used in various scenarios.
It supports up to 140.8TOPS of INT8 peak computing power or 17.6TOPS of FP32 high-precision computing power, which can
meet the application requirements of deep-learning model development and training.
With the power of multi-channel video processing, it supports up to 128-channel 1080P HD video whole-process (decoding + AI)
processing, which can bring excellent performance.
This server supports algorithm migration of pedestrian/vehicle/object recognition, video structuring, trajectory behavior
analysis, etc, featuring high security and reliability. So it can be flexibly applied to various product development.
SOPHON SDK (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.
BMC intelligent management system provides a visualization console interface through HDMI output. It easily achieves real-time monitoring,
software configuration, hardware management, troubleshooting and system upgrade. The system supports secondary development.
Dual 10GbE ports and a GbE port meet business scenarios with high bandwidth requirements. The independent BMC management network
interface separates management network and service network,
ensuring the security and reliability of network communication.
A 3.5-inch hard disk bay supports SATA3.0 HDD/SSD hard drive expansion, allowing the device to be
easily expanded to TB storage capacity.
Standard 1U rack server chassis design, its depth is 576mm, fully matching most types of cabinets in the data center.
It supports flexible deployment in multiple fields and scenarios, such as intelligent park, security surveillance, intelligent retail,
intelligent transportation, intelligent finance, intelligent city, intelligent industry, smart energy and more.
Intelligent park
Security surveillance
Intelligent retail
Transportation
Intelligent finance
Intelligent industry
Specifications | |
Product Name |
Computing Power Cluster Server |
Product Model |
CSA1-N8S1684 |
AI Computing Power |
140T@INT8 peak computing power, 17.6TFLOPS@FP32 high-precision computing power |
VPU |
Video decoding: H.264 & H.265: 1080P @11520fps Video decoding resolution: 8192 * 8192 / 8K / 4K / 1080P / 720P / D1 / CIF Video encoding: H.264 & H.265: 1080P @600fps Video encoding resolution: 4K / 1080P / 720P / D1 / CIF JPEG decoding: JPEG: 4800 images per second @1080P |
Nodes |
8 compute nodes (up to 64 ARM cores) + 1 control node |
CPU |
Compute node: BM1684 octa-core (A53*8) 64-bit processor, frequency up to 2.3GHz Control node: RK3588S octa-core (4×Cortex-A76+4×Cortex-A55) 64-bit processor, frequency up to 2.4GHz |
RAM |
12GB LPDDR4 × 8 (compute nodes) |
Storage |
32GB eMMC × 8 (compute nodes) 3.5-inch SATA3.0 hard disk × 1 |
Network |
GE RJ45 Gigabit Ethernet port×2 (a control node port and a common Ethernet port) SFP 10GE × 2 4G/LTE/5G network (optional) |
Display |
HDMI 2.0, 4K@60Hz (main processor core board display) |
USB |
2 × USB3.0 HOST, 1×Type-C (for processor core board debugging) |
Fan |
5 high-speed fans |
Power |
300W AC power supply (input: 100V AC~240V AC) |
OS |
Linux |
BMC |
Integrated BMC management system provides management interface based on Web. This system supports secondary development. |
Deep Learning Framework |
TensorFlow / PyTorch / Paddle / Caffe / ONNX / MXNet / DarkNet |
Dimension |
Standard 1U rack-mounted server: 490mm x 390mm x 44.4mm |
Operating Temperature |
0ºC - 50ºC |
Operating Humidity |
8%RH~95%RH |
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