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Cornerstone Intelligent Computing – An AI computing power cloud service platform launched by QingCloud Technology

Author: AI小集 · Original source: AI工具集

What is Cornerstone Intelligent Computing

Cornerstone Intelligent Computing is an AI computing power cloud service platform launched by QingCloud Technology, dedicated to providing users with efficient, flexible, and intelligent AI computing power support. Its core advantage lies in powerful computing power resources, with a single node equipped with high-performance GPUs and CPUs, combined with high-speed network and storage technologies, capable of meeting the needs of large-scale AI training and inference. The platform supports multiple service models such as public cloud, private deployment, and dedicated cloud, allowing flexible selection according to user needs.

Cornerstone Intelligent Computing

Main features of Cornerstone Intelligent Computing

  • Unified scheduling of diverse computing power: Supports unified management of multiple heterogeneous computing power resources such as NVIDIA GPUs, domestic GPUs, and NPUs, building a flexible computing power pool.
  • Distributed scheduling and management: Automatically allocates and manages computing power resources, optimizes task scheduling efficiency, and shortens task execution time.
  • Elastic scaling: Expands computing power resources in real time according to business needs, with pay-as-you-go billing.
  • One-stop full-process AI computing service: Covers the entire process from algorithm development to model deployment, with built-in mainstream deep learning frameworks such as TensorFlow and PyTorch.
  • Model repository and management: Provides a model repository (MaaS) and one-click deployment and delivery of various large AI models, supporting rapid model management and application.
  • Model services: Supports online inference, one-click deployment, and online fine-tuning of models; users can call models via API.
  • Multi-dimensional monitoring: Adds functions such as node monitoring, task monitoring, and container group monitoring, providing comprehensive monitoring of resource usage and hardware status.
  • Intelligent alerting: Supports multiple notification channels such as email, WeCom, and webhook, ensuring users stay informed of operating status in a timely manner.
  • Open application framework: Supports integration with ecosystem applications from multiple vendors in the industry, creating a rich set of SaaS application services.
  • Seamless integration and deployment: Supports multiple access methods, simplifies the development process, and enables non-technical users to get started quickly.
  • Automated operations: Provides full-process self-service management including specification pricing, online recharge, and product purchase, reducing operational costs.
  • Customized resource pool services: Supports public resource groups and dedicated resource groups to meet the needs of different users.
  • Multimodal model support: Provides multiple types of model services such as text generation, speech recognition, and image generation.
  • Intelligent interaction features: Supports JSON mode output, providing structured and standardized data results, making it convenient for users to develop intelligent applications.

How to use Cornerstone Intelligent Computing

  • Register and log in: Visit theofficial websiteof Cornerstone Intelligent Computing, register, and log in to your account.
  • Create an API key: In the top navigation bar, select "Products and Services" - "Large Model Services" to enter the large model service platform. In the left navigation bar, select "API Key Management", click "Create API Key", enter the key name, and click "Confirm". After creation is complete, copy the API key.
  • Call the API directly：
    • In "Online Inference Service", select the target model, obtain the model's API documentation, and confirm the API domain (for example:https://openapi.coreshub.cn/v1）。
    • Use the API key and domain to call the model via HTTP requests or tools that support the OpenAI interface (such as Python's OpenAI dependency).
  • One-click cloud deployment：
    • In "AI Computing Cloud Service" - "Model Square", select a model such as DeepSeek-R1 and click "Model Deployment".
    • Select computing resources and click "Create". After deployment is complete, obtain the external access address and API key.
  • Configure third-party tools：
    • Take the Cline plugin for VSCode as an example. After installing the plugin, fill in the API key, API domain, and model name (such as DeepSeek-V3) in the settings to use the model for functions such as code completion.
    • Take the Cursor programming tool as an example. Download and install the Cursor client, configure the API key and domain, and select the DeepSeek-R1 model to use the model to generate code in the editor.
  • Call the model directly: Use a browser or HTTP tool to call the model through the external access address and API key to obtain inference results.
  • Monitoring and management: On the Cornerstone Smart Computing platform, users can monitor model running status and resource usage in real time, and perform elastic scaling up or down as needed.

Application scenarios of Cornerstone Smart Computing

  • AI model training and development: Cornerstone Smart Computing provides powerful GPU computing resources and distributed scheduling capabilities, supporting the full process from model design to training and deployment. Users can quickly launch multi-machine, multi-node distributed training tasks through the platform. The system automatically schedules computing resources and completes the computation, and automatically releases resources after the task ends.
  • High-performance computing: Cornerstone Smart Computing supports large-scale parallel computing tasks and optimizes network communication to ensure efficient execution of high-performance computing tasks. The powerful scheduling engine can manage computing resources at the scale of thousands to tens of thousands of cards, meeting complex computing needs.
  • Data science and analysis: The platform provides flexible computing resources to meet the diverse computing needs of data science and analysis tasks. Users can use the platform's computing resources for data processing, analysis, and modeling to improve the efficiency of data science projects.
  • AI model services and inference: Cornerstone Smart Computing provides a model repository (MaaS) and one-click deployment and delivery of various large AI models, allowing users to quickly deploy online inference services.