The integration of artificial intelligence and scientific computing is reaching new heights. On June 29, the full-stack platform "Yisan Fangzhou" for the domestic computing system software ecosystem was officially launched in Beijing. This platform was jointly developed by the Center for Computer Network Information of the Chinese Academy of Sciences, University of Science and Technology of China, Institute of Mechanics of the Chinese Academy of Sciences, and Inspur, aiming to provide a scientific, efficient, and practical software ecosystem solution for domestic GPU computing infrastructure.

Currently, the domestic heterogeneous computing environment still faces many barriers in the application of scientific computing software. To break down the barriers between algorithms, code, and practical applications, "Yisan Fangzhou" has built a complete technical chain from underlying algorithms to intelligent applications.

On core computing capabilities, the platform introduced the "Jiu Yan Shu" algorithm library, which integrates 16 high-performance solvers for mainstream scenarios such as linear algebra, fluid simulation, bio-computation, and deep learning. These algorithms are deeply adapted and optimized for domestic GPU architecture, with significant performance improvements in core modules, providing researchers with a powerful computing "core".

Code migration has been a major obstacle to the implementation of domestic computing power. Relying on the platform's powerful code conversion large model, developers can quickly migrate existing CUDA code to the domestic environment. The system supports intelligent analysis and automatic compilation, greatly reducing the time cost for researchers in code refactoring, and helping existing research code run smoothly on the domestic platform.

In addition, the platform introduced an automated simulation intelligent agent, which handles processes such as parameter configuration, solving, and fault diagnosis through a multi-intelligent agent architecture. Users need only natural language instructions to efficiently complete complex simulation tasks, achieving a transformation in scientific tools from "high professional barriers" to "simple and easy to use".

The release of "Yisan Fangzhou" marks that China's scientific computing software ecosystem has initially formed a complete closed loop with solid algorithm kernels, interconnected ecosystems, and practical business scenarios. In the future, the development team will continue to drive platform iteration, deeply connect with various computing bases and research scenarios, and help the new paradigm of AI-driven scientific research (AI4S) accelerate its implementation in China.