CSA1-N8S1684X AI Computing Power Server
Powered by high-computing BM1684X, this server features up to 8 BM1684X computing modules. It delivers
exceptional computing power,
enabling up to 256TOPS (INT8) peak computing power, or 128TFLOPS (FP16/BF16) computing power, or 16TFLOPS (FP32)
high-precision
computing power, with the power of multi-channel video processing capability. It provides multiple algorithm
migration and a one-stop deep
learning development toolkit. With the BMC management system, secondary development is supported
AI processor BM1684X
The BM1684X SoC with AI computing power features an octa-core Cortex-A53 + NPU. Cortex-A53 with a frequency of
2.3G. NPU
delivers 32Tops(INT8) / 16TFLOPS(FP16/BF6) / 2TFLOPS(FP32) computing power. The server provides 16GB LPDDR4 and
128GB
eMMC large storage capacity
Eight computing modules, flexible configuration
The server can be equipped with up to 8 BM1684X computing modules. Users can customize the number and storage
configuration of
modules. This flexibility makes it suitable for various scenarios
256TOPS powerful computing power
It supports up to 256TOPS (INT8) peak computing power, or 128TFLOPS (FP16/BF16) computing power, or 16TFLOPS
(FP32) high-precision
computing power, which can meet the application requirements for deep-learning model development
Incredible multi-channel video processing capability
The server supports up to 256-channel H.265/H.264 1080p@25fps video decoding, 256-channel H.265/H.264
1080P@25fps HD video processing
(decoding + AI analysis), and 96-channel H.265/H.264 1080p@25fps video encoding
Various algorithms, strong practicality
This server supports algorithm migration for 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), a 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. Secondary development is also
supported
Dual 10GbE meets high bandwidth requirements
Dual 10GbE ports and GbE ports meet business scenarios with high bandwidth requirements. The independent BMC
management network
interface separates the management network and the 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 a TB storage capacity
Standard 1U rack server
Featuring a standard 1U rack server chassis design with a depth of 576mm, this
server perfectly matches a wide range of data center cabinets
A wide range of application scenarios
This server can be widely used in various scenarios, including edge computing, cloud storage, blockchain,
multi-channel video
encoding and decoding, and intelligent security
Edge computing
Security
Cloud storage
Blockchain
Multi-channel video
encoding and decoding
Financial industry
Specifications
|
Specifications |
| Product Name |
Computing Power Cluster Server
|
| Product Model |
CSA1-N8S1684X
|
| AI Computing Power |
256T@INT8 peak computing power, 16TFLOPS@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 |
16GB LPDDR4 × 8 (compute nodes)
|
| Storage |
32GB eMMC × 8 (compute nodes)
3.5-inch SATA3.0 hard disk ×
|
| 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 |
10%～90%RH
|
