CSA1-N8S1684 AI Server
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.
BM1684 octa-core AI SoC
with high computing power
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.
Eight computing modules, flexible configuration
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.
140.8TOPS powerful computing power
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.
Incredible multi-channel video processing capability
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.
Various algorithms, strong adaptability
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.
Open SDK, one-stop AI development kit
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 management system
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 meet high bandwidth requirements
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.
Support SATA3.0 hard disk expansion
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
Standard 1U rack server chassis design, its depth is 576mm, fully matching most
types of cabinets in the data center.
A wide range of application scenarios
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
|
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
|
