Sophon SC5 + adopts standard half-height and half-length design, and is equipped with three BM1684 high-performance computing chips, which can provide up to 105.6T INT8 (Winograd Enable) and 6.6T FP32 performance, supporting high-precision computing.
The chip utilization rate exceeds 70%, and the actual AI performance gain ratio is higher
The third generation of mass-produced products, with higher maturity and stability
2880fps (more than 100 channels 1080P @ 25fps) HD video hardware decoding capability
Memory capacity up to 36GB / 48GB, unlimited applications
96MB cache SRAM, small model calculation can greatly speed up (more than 50% of similar products)
Video and picture decoding resolution range up to above 8K, suitable for all kinds of ultra-high-definition network cameras
Adapt to various x86 servers, and domestic CPU systems such as Feiteng, Shenwei, etc.
Adapt to various operating systems (CentOS / Ubuntu / Debian), including domestic Kylin, Deepin, etc.
SC5 + can be loaded on the standard server, and can be used in various face recognition, video structure, video transcoding, security monitoring, machine vision, high-performance computing environments, to accelerate the calculation of a variety of CNN / RNN / DNN and other neural network models.
BMNNSDK (BITMAIN Neural Network SDK) one-stop toolkit provides a series of software tools such as the underlying driver environment, compiler, inference deployment tool and so on. Easy to use and convenient, covering the model optimization, efficient runtime support and other capabilities required for the neural network inference stage, providing easy-to-use and efficient full-stack solutions for deep learning application development and deployment. BMNNSDK minimizes the development cycle and cost of algorithms and software. Users can quickly deploy deep learning algorithms on various AI hardware products of Fortune Group to facilitate intelligent applications.
AI Developer Portfolio
AI computing accelerator card
AI computing accelerator card
TPU core architecture
SOPHON
SOPHON
SOPHON
SOPHON
NPU core number
64
-
64
192
AI performance
FP32(FLOPS)
2.2T
-
2.2T
6.6T
INT8(OPS) Winograd OFF
17.6T
-
17.6T
52.8T
INT8(OPS) Winograd ON
35.2T
-
35.2T
105.6T
CPU
ARM 8-core A53 @ 2.3GHz
-
ARM 8-core A53 @ 2.3GHz
3x ARM 8-core A53 @ 2.3GHz
VPU
Video decoding capability
H.264:1080P @960fps
H.265:1080P @960fps
-
H.264:1080P @960fps
H.265:1080P @960fps
H.264:1080P @2880fps
H.265:1080P @2880fps
Video decoding resolution
CIF / D1 / 720P / 1080P / 4K(3840×2160) / 8K(8192×4096)
-
CIF / D1 / 720P / 1080P / 4K(3840×2160) / 8K(8192×4096)
CIF / D1 / 720P / 1080P / 4K(3840×2160) / 8K(8192×4096)
Video encoding capability
H.264:1080P @50fps
H.265:1080P @50fps
-
H.264:1080P @50fps
H.265:1080P @50fps
H.264:1080P @150fps
H.265:1080P @150fps
Video encoding resolution
CIF / D1 / 720P / 1080P / 4K(3840×2160)
-
CIF / D1 / 720P / 1080P / 4K(3840×2160)
CIF / D1 / 720P / 1080P / 4K(3840×2160)
Video transcoding capability (1080P to CIF)
Max. 18 channels
-
Max. 18 channels
Max. 54 channels
JPU
JPEG image decoding capability
480 images / second @ 1080p
-
480 images / second @ 1080p
1440 images / second @ 1080p
Maximum resolution (pixels)
32768×32768
-
32768×32768
32768×32768
System interface
Data link
EP PCIE X8
RC PCIE X8
PCIE X2
PCIE X16
PCIE X8
Operating mode
EP+RC
SOC extension
EP
EP
Physical / power interface
PCIE X16
12VDC Jack
PCIE X16
PCIE X16
RAM
Standard configuration
12GB
-
12GB
36GB
Maximum capacity
16GB
-
16GB
48GB
Power consumption
30W MAX
No load: 6W
With load: 30W
30W MAX
75W MAX
Heat dissipation mode
active
-
active
passive
Working status display
N/A
LED x3 (power / hard disk / status)
LED x1
LED x1
External I/O expansion *
SD-Card
1
-
-
RESET Button
1
-
-
RJ45
2 *1000Base-T
-
-
USB
4
-
-
SATA
1
-
-
4G/LTE
1
-
-
micro USB
1
-
-
working temperature
0℃-55℃
-10℃-55℃
0℃-55℃
Deep learning framework
Caffe / TensorFlow / Pytorch / Mxnet / Darknet / Paddle
Operating system support
Ubuntu / CentOS / Debian
compatibility
Compatible with mainstream x86 architecture and ARM architecture servers
Localization support
Support domestic CPU system such as Feiteng, Shenwei, Zhaoxin, etc.; support domestic Linux operating system such as Kylin, Deepin, etc.; support domestic AI framework Paddle Lite
Length x height x width (including bracket)
200x111.2x19.8mm
206x28.5x59.5mm
169.1x68.9x19mm
169.1x68.9x19.5mm
* All external I/O expansion interfaces in the AI developer portfolio must be used with SC5-IO
