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
SoC模型下有多种更新固件的方式:
(1)文件替换直接更新kernel、预编译的SDK库以及bootloader等文件:文件替换方式是指在SoC系统中直接通过替换对应文件的方式分别升级bootloader、kernel和SDK等其它软件。这种方式有一定的风险,如不同软件组件之间的版本匹配、文件损坏等。请参考《智算模组SM5软件开发指南》2.2软件更新 b.文件替换 章节。
1. 从网盘soc_upgrade目录下载下面的文件,scp到设备上。
2. 升级kernel: sudo cp emmcboot.itb /boot/;
3. 升级预编译的库:sudo tar xzf system.tgz -C /system;
4. 升级bootloader: sudo flash_update -i spi_flash.bin -b 0x6000000 -f 0x0;
5. 保存并重启使生效:sudo sync; sudo reboot.
(2)使用SD卡刷烧写整个固件:这种方式最为干净可靠,理论上只要您的SE5/SM5硬件没有损坏,都可以进行SD卡刷机,具体步骤请参考《SE5用户手册》6.1节 系统升级或《智算模组SM5软件开发指南》2.2软件更新 a.SD卡刷机 。(注意:带有预置算法应用的卡刷包和干净系统的卡刷包是不一样的,请在升级前核实清楚您的需求,并向技术支持获取相应卡刷包;卡刷会重写整个eMMC,也即您存储在eMMC的数据全部会丢失,请务必做好数据备份。)
(4)使用DDT设备扫描工具更新:请联系技术支持获取,目前仅提供Windows客户端。需要注意的是,DDT设备扫描工具依赖于我方安装在SE5/SM5中的服务程序,若您使用自己定制的固件和操作系统,本方式不一定适用。
DDT 设备扫描工具是算能科技SE5 和 SM5 产品(以下简称产品)配套的辅助工具,它主要提供如下两种功能:
- 自动扫描:发现同一局域网内的所有相关 SE5 或 SM5 产品,支持 IP 地址等基础信息更改。
- 软件升级:支持对勾选的指定产品进行单个或者批量软件升级。