CHINA’S largest scientific intelligent computing cluster has been put into operation at the core node of the national supercomputing network in Zhengzhou, central China’s Henan Province, according to a report by China Media Group (CMG).

This marks a key breakthrough in the country’s computing infrastructure for AI-driven scientific research, helping China to seize the high ground in industrial AI applications.

The node began trial operation on Feb. 5 with over 30,000 domestically made AI accelerator chips. On Tuesday, the number of such chips increased to 60,000 units, CMG reported. The core node has established an integrated, inclusive, domestically developed ecosystem combining data, computing power, models and applications. It brings together diverse datasets and tools alongside thousands of open-source large models, enabling rapid deployment and development.

On the supercomputing network platform, users are freed from software configuration and IT workflows. Instead, they can simply express their needs in natural language, and a super scientific computing agent will automatically break down tasks, invoke models, and schedule computing resources to deliver end-to-end results, drastically shortening the time required to complete research tasks, CMG said.

This infrastructure will continue to follow an open path, covering all scenarios in research and industry while providing accessible and user-friendly services. It is expected to help China achieve greater breakthroughs in AI and gain an early advantage in global technological competition, according to the CMG report.

Equipped with advanced AI accelerator hardware and supported by a standardized, open service layer, the Zhengzhou node is designed to make large-scale scientific computing both faster and more accessible for researchers and enterprises. By enabling seamless access to domestically developed computing resources, software components, and large-model capabilities, it can reduce barriers to experimentation and support a wider range of AI-driven projects — from chemistry and materials discovery to industrial optimization. (Xinhua)