
Computing Power Algorithm Management Platform
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Computing Power Algorithm Management Platform
The computing power algorithm platform is a computing power algorithm application and management platform created by Huazi Supercomputing, dedicated to helping customers quickly build AI capabilities. The platform relies on self-developed algorithms to establish a unified and diverse data entry point, providing on-demand deployment capabilities for "edge-cloud" algorithms, achieving a self-closed loop of AI capabilities. It also enables low-cost integration of AI with business through a visual interactive window, intelligent application services, and standard API interfaces, allowing for the rapid construction of intelligent applications.
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Software platform
Basic software
The computing algorithm platform is a computing algorithm application and management platform created by Huazi Supercomputing, dedicated to helping customers quickly build AI capabilities. The platform relies on self-developed algorithms to establish a unified and diverse data entry point, providing on-demand deployment capabilities for 'edge-cloud' algorithms, achieving a self-closed loop of AI capabilities. It also combines AI with business at a low cost through a visual interactive window, intelligent application services, and standard API interfaces, enabling the rapid construction of intelligent applications. The platform includes functions such as algorithm management, computing power allocation, algorithm tasks, algorithm strategies, and plan templates, providing users with a full-process service for AI algorithm deployment and AI application release.

Technical Features
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Optimal Management of Computing Power |
Flexible Deployment of Algorithms |
Containerized Deployment |
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The platform manages resource quotas and isolates devices and data through algorithm computing power management, flexibly supporting adjustments to computing power resource quotas and flexible algorithm deployment. At the same time, through task queuing and failure retry mechanisms, it maximizes the utilization of computing resources.
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The platform can remotely and flexibly deploy algorithms through self-developed algorithms in conjunction with self-developed terminals, while reasonably utilizing algorithm resources by formulating plan templates and task strategies.
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The platform adopts a containerized deployment method, which not only completely encapsulates algorithm code and inference code but also encapsulates the entire dependency library and hardware library. By simply pushing the image to the platform's algorithm repository, the entire runtime environment can be shared through the image repository, allowing inference services to run in a container environment. |
