SC5H is equipped with intelligent vision deep learning processor BM1684, which can be integrated into servers and industrial computers, efficiently adapt to all deep learning algorithms in the market, and realize applications such as video structuring, face recognition, behavior analysis, state monitoring, and empower smart cities, smart transportation, smart energy, smart finance, smart telecommunications, smart industries and other fields
Support intelligent analysis of 16-channel HD video
High performance/power ratio, for edge-side deep learning applications.
Support multiple precision calculations such as FP32 and INT8
32 channels full HD video hard decoding capability, applicable to high-speed high-frame rate industrial cameras
2-channel HD video hard-coding capability, supporting 4K level semi-real-time encoding output
Video and picture decoding resolution range up to above 8K, suitable for all kinds of ultra-high-definition network cameras
Adapt to local workstation environments and domestic RISC-V systems such as Phytium and Shenwei.
Can be together used with SC5+ and accelerator cards and graphic cards of other brands to build a heterogeneous computing platform
SC5H is mainly applied in distributed deep learning computing and analysis scenarios on the edge side, such as traffic, urban management, communities and industrial inspection that require front-deep learning computing power; it can also be together used with other cards such as SC5 + on the same computing platform.
SOPHON SDK one-stop toolkit provides a series of software tools including the underlying driver environment, compiler and inference deployment tool. The easy-to-use and convenient toolkit covers the model optimization, efficient runtime support and other capabilities required for neural network inference. It provides easy-to-use and efficient full-stack solutions for the development and deployment of deep learning applications. SOPHON SDK minimizes the development cycle and cost of algorithms and software. Users can quickly deploy deep learning algorithms on various deep learning hardware products of SOPHGO to facilitate intelligent applications.
Deep learning developer portfolio
Intelligent Accelerator Card SC5H
Intelligent Accelerator Card SC5+
TPU core architecture
SOPHON
SOPHON
SOPHON
SOPHON
NPU core number
64
-
64
192
Processor
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 processor systems such as Feiteng, Shenwei, Godson, Haiguang, etc. Support domestic Linux operating systems such as Kirin and UOS; Support domestic frameworks Paddle Lite, Tengine, etc.
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 deep learning developer portfolio must be used with SC5-IO