| CSB1-N10R3588 |
Technical Specifications
|
Server form |
1U rack-mounted computing power server
|
| Framework |
ARM architecture
|
| Number of
nodes |
10 distributed computing nodes (up to 80 ARM cores) + 1 control node
|
| Compute nodes |
Octa-core 64-bit processor RK3588, main frequency up to 2.4GHz
|
| Control nodes |
Octa-core 64-bit processor RK3588, main frequency up to 2.4GHz, the highest computing power is 6TOPS
|
| AI computing
power |
60TOPS (INT8)
|
| RAM |
16GB LPDDR4 × 10 (Number of compute nodes)(Optional: 4GB/8GB/16GB/32GB)
|
| Storage |
256GB eMMC × 10 (Number of compute nodes)(Optional: 16GB/32GB/64GB/128GB/256GB)
|
| Storage
Expansion |
3.5-inch/2.5-inch SATA3.0/SSD hard drive slot × 1 (BMC can directly operate the hard drive, and computing child nodes can
indirectly access the hard drive through the network sharing method provided by BMC)
|
| Power |
550W AC power supply (Input: 90V AC~264V AC, 47 Hz~63 Hz, 8A) (Hot swappable not supported)
|
| Fan module |
6 high-speed cooling fans
|
Physical Specifications
|
Size |
420.0mm(L) × 421.3mm(W) × 44.4mm(H)
|
| Installation
requirements |
IEC 297 Universal Cabinet Installation: 19 inches wide and 800 mm deep and above
Retractable slideway installation: The distance between the front and rear holes of the cabinet is 543.5mm~848.5mm
|
| Full weight |
Server net weight: 8.1kg, total weight with packaging: 10.3kg
|
| Environment |
Operating Temperature: 0ºC ~ 45ºC, Storage Temperature: -40ºC ~ 60ºC, Operating Humidity: 5% ~ 90%RH(non-condensing)
|
Software Specifications
|
BMC
|
The BMC management system is integrated with the web-based management interface, supporting Redfish, VNC, NTP,
monitoring advanced and virtual media, and the BMC management system can be redeveloped
|
| Large model |
Support the privatization deployment of ultra-large-scale parametric models under the Transformer architecture, such as
Gemma-2B, ChatGLM3-6B, Qwen-1.8B, Phi-3-3.8B and other large language models
|
| Deep learning |
It supports traditional network architectures such as CNN, RNN, and LSTM, and supports the import and export of RKNN models;
Support a variety of deep learning frameworks, including TensorFlow, TensorFlow Lite, PyTorch, Caffe, ONNX and Darknet.
It also supports the development of custom operators
|
Interface Specifications
|
Internet |
2 × 10G Ethernet (SFP+), 2 × Gigabit Ethernet (RJ45), 1 × Gigabit Ethernet (RJ45, MGNT is used as BMC management network)
|
| Console
|
1 × Console (RJ45, BMC debug serial port, baud rate 115200)
|
| Display
|
1 × VGA (maximum resolution 1080P, BMC management display)
|
| USB |
2 × USB3.0 (The lower USB is USB3.0 OTG, and the BMC can be upgraded OTG by using a USB flash drive)
|
| Button
|
1 × Reset, 1 × UID, 1 × Power button
|
| Other interfaces
|
1 × RS232 (DB9, baud rate 115200),1 × RS485 (DB9, baud rate 115200)
|
