TPU processor, 16 channels HD video intelligent analysis, 32 channels of full HD video decoding
TPU processor, 32 channels HD video intelligent analysis, 32 channels of full HD video decoding, 12 channels of full HD video encoding
Based on the RISC-V core, operating at a frequency of 2GHz, the processor features a single SOC with 64 cores and 64MB shared L3 cache.
Based on RISC-V 3-5M slightly intelligent deep learning vision processor
Based on RISC-V 5M light intelligent deep learning vision processor
RISC-V 5M light intelligent deep learning vision processor
5M light intelligent deep learning vision processor
4K Super Definition Deep learning vision processor
5M high-performance Deep learning vision processor
5M light intelligent Deep learning vision processor
960-channel HD video decoding, 480-channel HD video analysis
576-channel HD video decoding, 288-channel HD video analysis
BM1684X, 416-channel HD video analysis
X86 host processor,288-channel HD video analysis
BM1684X, 32-channel HD Video Analysis
BM1684, 16-Channel HD Video Analysis
BM1684, 192-channel HD video analysis
BM1684, 8-channel HD video analysis
CV186AH, 8-channel HD Video Analysis
BM1688, 16-channel HD Video Analysis
72-channel HD video decoding, 72-channel HD video analysis
96-channel HD video decoding,48-channel HD video analysis
32-channel HD video decoding,16-channel HD video analysis
32-channel HD video decoding, 32-channel HD video analysis
32-channel HD video decoding, 32-channel HD video analysis
32-channel HD video decoding, 16-channel HD video analysis
32-channel HD video decoding, 16-channel HD video analysis
Deep Learning Developer Product Portfolio
Deep learning intelligent analysis helps make city management more efficient and precise
Using deep learning video technology to analyze sources of dust generation and dust events, contributing to ecological environmental protection
Empower prison management with intelligent monitoring of key controlled areas through smart video analysis
Using deep learning intelligent analysis to monitor scenarios such as safety production, urban firefighting, and unexpected incidents for emergency regulation.
Using specific deep learning algorithms to watermark, blur, or apply other methods to streaming videos, achieving video confidentiality and preventing leaks
SOPHGO with the SOPHON.TEAM ecosystem to build a data intelligence content governance solution.
Using deep learning technology to detect and analyze individuals, vehicles, and security incidents in grassroots governance
Real-time compression and transcoding of video to the cloud and monitoring of abnormal events, enhancing the ability to detect and handle road safety incidents
Empowering the problems of traffic congestion, driving safety, vehicle violations, and road pollution control
Utilizing domestically developed computational power to support the structured analysis of massive volumes of videos, catering to practical applications in law enforcement
Build a "smart, collaborative, efficient, innovative" gait recognition big data analysis system centered around data
To rapidly construct business capabilities that integrate multidimensional data including people, vehicles, and traffic flow for users
Effectively resolving incidents of objects thrown from height, achieving real-time monitoring of such incidents, pinpointing the location of the thrown object, triggering alerts, and effectively safeguarding the safety of the public from falling objects
Using edge computing architecture to timely and accurately monitor community emergencies and safety hazards
SOPHGO with SOPHON.TEAM ecosystem partners to build a deep learning supervision solution for smart hospitals, enhancing safety management efficiency in hospitals
SOPHGO with SOPHON.TEAM ecosystem partners to build a smart safe campus solution
Using a combination of cloud-edge deep learning methods to address food safety supervision requirements across multiple restaurant establishments, creating a closed-loop supervision system for government and enterprise-level stakeholders
Providing deep learning capabilities for the financial, insurance, and various business service industries to enhance operational efficiency and improve service quality
SOPHGO with SOPHON.TEAM ecosystem partners to offer a "Deep Learning Video Analysis + Restaurant Front-of-House Management" solution
SOPHON's self-developed computing hardware devices, such as SG6/SE5/SE6, equipped with SOPHON.TEAM video analysis algorithms, are used to make industrial safety production become smarter
Provided safety monitoring solutions for violations and abnormal events in offices, quality inspection, weighing rooms, storage areas and other areas of large storage parks such as granaries and cotton warehouses
SOPHON.TEAM is collaborating with ecological partners to develop a comprehensive solution for ensuring the safety of tobacco industry production and control
In collaboration with SOPHON.TEAM and its ecological partners, SOPHGO utilizes domestically developed computing power products as the hardware foundation to build a safety production management system and improve the safety production management level of liquor enterprises
Combining deep learning, edge computing and other technologies, it has the ability to intelligently identify people, objects, things and their specific behaviors in the refueling area and unloading area. It also automatically detects and captures illegal incidents at gas stations to facilitate effective traceability afterwards and provide data for safety management.
SOPHGO, in collaboration with SOPHON.TEAM and its ecosystem partners, is focusing on three major scene requirements: "Production Safety Supervision," "Comprehensive Park Management," and "Personnel Safety & Behavioral Standard Supervision." Together, they are developing a comprehensive deep learning scenario solution, integrating "algorithm + computing power + platform."
SOPHGO, cooperates with SOPHON.TEAM ecological partners to build a deep learning monitoring solution for safety risks in chemical industry parks
SOPHGO with SOPHON.TEAM ecosystem partners to build a Smart Computing Center solution, establishing a unified management and scheduling cloud-edge collaborative smart computing center
SOPHGO, in collaboration with SOPHON.TEAM ecosystem, have jointly developed a set of hardware leveraging domestically-produced deep learning computational power products. This is based on an AutoML zero-code automated deep learning training platform, enabling rapid and efficient implementation of deep learning engineering solutions
2.1 SC5快速安装指南:
2.1.1 在主机关机状态下将SC5安装至PCIe插槽,需要插到位,SC5从PCIe接口直接供电,不需要外接ATX 2x3电源。注意,服务器最好是拔掉 220V电源再安装,某些服务器,在220V输入时,PCIe插槽有漏电。
2.1.2 安装完后,先不要盖好后盖,power on上电,从上侧观察LED状态,如下图所示,4个灯的状态,蓝蓝绿红,为SC5上电正常。
2.1.3 进入系统,输入命令lspci|grep 1684,正常识别的话,会看到1684设备,如下图所示。
lspci | grep 1684
06:00.0 Processing accelerators: Device 1e30:1684 (rev 01)
06:00.1 Processing accelerators: Device 1e30:1684 (rev 01)
06:00.2 Processing accelerators: Device 1e30:1684 (rev 01)
2.1.4 如没有1684设备,请再次确认LED状态是否正常;
2.1.5 如LED 异常,关机,断电,断开220V,重新上电,再次观察LED 状态,如正常,请操作步骤4 2.1.6 如LED正常,lspci命令下,仍无法识别设备,请收集硬件信息,和OS版本,反馈给我们。