Xpeedic releases EDA 2027 version, 2026 User Ecosystem Conference focuses on STCO and AI for EDA

On October 30, the 2026 Xinhe Semiconductor User Ecosystem Conference was held in Shanghai under the theme "Chip Leaps Across Systems, Intelligence Masters All Changes." More than a thousand representatives from industry chain companies and universities exchanged views on STCO (chip-to-system co-optimization), system-level EDA, and AI for EDA. At the conference, Xinhe Semiconductor released the EDA2027 version.

Chen Wen, deputy secretary-general of the China Semiconductor Industry Association, said in her remarks that artificial intelligence is driving semiconductor industry innovation to shift from process scaling to system integration. She affirmed Xinhe's exploration in recent years of continuously expanding system-level EDA capabilities along the "from chip to system" direction, and expressed the hope that Xinhe will continue to consolidate multi-physics simulation as the "ballast stone" and promote the integration of AI multi-agent systems with EDA.

Zhou Feng, director of the Integrated Circuit Institute of the CCID Research Institute, further noted on this basis that advanced packaging, multi-chip integration, and EDA have been listed as priorities for industrial foundational capabilities in the "15th Five-Year Plan," and that EDA needs to move further from point tools toward systematization and intelligence.

Computing Power Depends on Systems, Design Requires Collaboration

In his opening keynote, Dr. Ling Feng, chairman of Xinhe Semiconductor, pointed out that AI is changing the way computing power is measured. In the past, chip performance was judged by a single chip; in the AI era, the computing unit has expanded to racks and even clusters, and computing power should be judged by the token output efficiency and overall cost of the entire system.

He explained this with the barrel theory: system computing power depends on the shortest stave among computing power, storage capacity, transport capacity, and power, and if any link falls behind, even the strongest chip will struggle to perform. Moreover, these "staves" are interconnected—heat affects power, and power in turn affects signals—so optimizing each in isolation can no longer solve the problem.

Therefore, Ling Feng believes STCO is imperative: design must start at the system level from the outset, aim at overall energy efficiency and cost, consider chips, packaging, boards, and even racks together, and enable multi-physics issues such as electrical, thermal, mechanical, and optical to be solved collaboratively in the early design stage.

According to his introduction, Xinhe, based on system-level design and multi-physics simulation capabilities, is introducing AI agents upward and extending simulation tools downward from chips all the way to complete machines, and has already promoted the implementation of STCO through multiple collaborations with industry chain partners.

Roundtable: STCO System Design in the AI Era

The morning roundtable "STCO System Design in the AI Era" was moderated by Dr. Dai Wenliang, president of Xinhe Semiconductor, and featured Peng Li, CTO of MetaX; Chen Qiongnan, CPO of Luxshare Technology; Feng Ming'an, SVP of Murata; Zhou Jun, CTO of Wuhan Xinxin; and Tian Fujun, senior technical expert at Longsys. The discussion covered key links in the AI hardware industry chain, including AI chips, storage, advanced packaging, high-speed interconnect, core components, and interconnect complete machines.

Guests from different positions in the industry reached a consistent judgment: in the AI era, local optimum is increasingly unable to guarantee system optimum. The interactions among chips, packaging, storage, interconnect, power supply, and heat dissipation are becoming stronger. Chen Qiongnan, CPO of Luxshare Technology, mentioned that without system-level joint simulation, problems often only emerge in later stages, and the cost of a single design change may be as high as tens of millions of yuan.

This is precisely where the value of STCO lies: enabling different links to collaborate earlier around the same system goal, and allowing models, data, and multi-physics simulation to truly run through the design process.

As the design space continues to expand, AI will also take on more solution exploration and optimization work, but ultimately professional EDA and trustworthy physics simulation are still needed to complete engineering verification.

"System-level EDA lets us see the system from the chip, while AI for EDA lets AI truly enter the main design flow," Dr. Dai Wenliang concluded.

Mo Zhijian, chief engineer and director at Lenovo Group, shared the practice of Lenovo and Xinhe jointly building EDA Agent 2.0 over more than a year. In the live demonstration, EDA Agent has moved from point assistance to multi-agent collaboration, from answering design specifications and undertaking library creation and place-and-route to checking while designing, covering multiple R&D links. From reading device manuals to outputting DDR analysis reports, the entire process was completed automatically. This process increased design iteration efficiency by about 5 times and reduced manual operations by about 90%.

Jiang Liguo, vice president of R&D at Xinhe Semiconductor, released the EDA2027 version on site. In addition to the all-new 3DIC PDK and optoelectronic joint simulation platform, the more important change in this release is that AI for EDA is beginning to move from point functions toward platformization and productization. The Agentic AI super agent platform AgentEvo is responsible for understanding design tasks, orchestrating engineering workflows, and invoking professional EDA tools, pushing AI from assisting operations further into the real design flow.

The Physics AI trustworthy physics intelligence foundation XAI uses AI for modeling, prediction, and optimization, expanding the design space engineers can explore. These two core AI capabilities are ultimately built on Xinhe's system-level EDA and multi-physics simulation capabilities, forming a closed loop of "AI exploration, professional EDA verification."

Sub-forums

STCO and AI for EDA in Real Engineering Practice

In the afternoon sub-forum session, Xinhe and its user ecosystem partners further brought STCO and AI for EDA into real engineering practice.

English text is being prepared.

Technology Sub-forum

In the AI for EDA direction, NovaStar shared practical applications of AI entering board-level design and multi-physics simulation. Shanghai Jiao Tong University and Zhejiang University also released related academic research.

Ecosystem Exhibition Area, Industrial Collaboration

During the conference, a Xinhe user ecosystem exhibition area was also set up. Nine industry partners from different links such as EDA, IP, design services, advanced packaging, PCB, and core components—Primarius, X-Epic, Lianfang Electronics, CoreLink, Shengliantek, Innosilicon, Edadoc, and Murata Manufacturing—showcased cutting-edge products and technical practices, jointly presenting an industrial collaboration chain from chip design toward larger systems.

Ecosystem Exhibition Area

For Xinhe, STCO means not only changes in design tools and methods, but also changes in the way the industry collaborates. From chips, IP, packaging, PCB, and components to complete machine systems, no single company can independently complete all links. One of the values of system-level EDA is to enable more industry partners to collaborate earlier around the same system goal.

At this conference, it can be seen that along the two main lines of STCO and AI for EDA, Xinhe's system-level EDA is continuously expanding the value boundary of domestic EDA, and also provides a new practical sample for Chinese EDA to enter AI computing infrastructure and next-generation intelligent system design.

In the AI for EDA direction, NovaStar shared practical applications of AI entering board-level design and multi-physics simulation. Shanghai Jiao Tong University and Zhejiang University also released related academic research.

Ecosystem Exhibition Area, Industrial Collaboration

During the conference, a Xinhe user ecosystem exhibition area was also set up. Nine industry partners from different links such as EDA, IP, design services, advanced packaging, PCB, and core components—Primarius, X-Epic, Lianfang Electronics, CoreLink, Shengliantek, Innosilicon, Edadoc, and Murata Manufacturing—showcased cutting-edge products and technical practices, jointly presenting an industrial collaboration chain from chip design toward larger systems.

Ecosystem Exhibition Area

For Xinhe, STCO means not only changes in design tools and methods, but also changes in the way the industry collaborates. From chips, IP, packaging, PCB, and components to complete machine systems, no single company can independently complete all links. One of the values of system-level EDA is to enable more industry partners to collaborate earlier around the same system goal.

At this conference, it can be seen that along the two main lines of STCO and AI for EDA, Xinhe's system-level EDA is continuously expanding the value boundary of domestic EDA, and also provides a new practical sample for Chinese EDA to enter AI computing infrastructure and next-generation intelligent system design.