How to Advance Chip Design with Digital Twins and EDA

Key takeaways

Digital twin technology is transforming semiconductor design by allowing real-time simulation and optimization.
Electronic Design Automation (EDA) has significantly evolved, supporting the complexities of modern semiconductor technologies.
Integrating digital twins into EDA enhances testing accuracy, speeds up time to market, and supports sustainable practices in manufacturing.
Collaboration with industry partners is vital in validating models and achieving accurate results in semiconductor design and testing.
Future advancements will require higher abstraction levels in EDA, supported by AI and enhanced data flow mechanisms.

Summary

Introduction of Co-Host and Focus Topic

In this episode of Advanced TalkSimmie, the hosts introduce Mr. Don Long as the new co-host and delve into the intersecting realms of digital twin technology and Electronic Design Automation (EDA). They emphasize the pivotal role these technologies play in enhancing chip design and manufacturing processes.

Understanding Digital Twins and EDA

The essence of digital twins is elaborately discussed as virtual representations of physical systems, emphasizing their capability to simulate, optimize and monitor real-time systems. The hosts dive into how EDA has evolved over the decades to become the software core for semiconductor innovation.

The Evolution of Electronic Design Automation

Ron Press provides an in-depth look into the history of EDA, highlighting its development in response to increasing semiconductor complexity. Strategies like scan technology and automatic test pattern generation (ATPG) are discussed as critical elements that enhance defect detection rates and streamline testing processes.

Role of Digital Twins in Testing and Manufacturing

The pivotal impact of digital twins on accelerating time-to-market and improving the sustainability of manufacturing is discussed. The conversation elaborates on digital twin's application in failure analysis and how it allows for virtual analysis thus saving time and costs in semiconductor testing.

Synergies between EDA and Digital Twins

The integration of digital twin technology into EDA workflows is explored. Partners in the industry are essential in validating models and ensuring accurate results, with a focus on machine learning applications that can enhance yield learning and diagnosis processes.

Future Trends and Conclusion

In analyzing future trends, there is an emphasis on higher abstraction levels in EDA to tackle the complexities of semiconductor designs. The emergence of AI integration, enhanced data sharing through data lakes, and collaborative efforts with industry partners are highlighted as crucial for advancing semiconductor technologies.

Show notes

Transform your understanding of semiconductor design and testing with the latest episode of Advantest Talks Semi. We are thrilled to introduce our new co-host, Don Ong, and welcome Ron Press, and Marc Hutner, from Siemens as they share groundbreaking insights into Electronic Design Automation (EDA).

Ron Press is the Senior Director for Technology Enablement at Siemens, where he leads a team dedicated to ensuring the successful implementation and use of Siemens' Tessent DFT and test product capabilities. His responsibilities include enabling application engineers, developing reference flows, and supporting customers in utilizing Siemens' released products effectively.

Ron began his career at Raytheon, working on AI and neural networks, and in 1993, he co-authored a paper on using neural networks to address built-in self-test (BIST) false alarms, highlighting his early contributions to AI in semiconductor testing. He worked as a Design for Test (DFT) architect at Raytheon before moving to Harris RF, where he focused on communication systems. Ron later joined Mentor Graphics, which was subsequently acquired by Siemens. Throughout his career, he has integrated AI and machine learning into semiconductor testing and design, significantly advancing the field.

Marc Hutner is the Director of Product Management for Yield Learning Products at Siemens. In his role, Marc focuses on yield learning and silicon debugging, aiming to identify yield limiters and improve semiconductor testing processes.

Marc joined Siemens over a year ago, bringing more than 20 years of experience in the semiconductor test industry. Before joining Siemens, he spent two years at proteanTecs as the Senior Director of Product Marketing for IP and Analytics for silicon health. Marc’s background includes working as an architect for test equipment and developing innovative concepts in semiconductor testing. His extensive experience positions him as a key figure in advancing Siemens' yield learning and debug capabilities.

Don Ong is the Director and Head of Innovation for the Advantest Field Service Business Group, a division of Advantest Inc. In his role, Don is responsible for driving the strategic development and implementation of innovative solutions that enhance Advantest’s Field Service business and operations. His responsibilities include identifying emerging technologies, leading cross-functional innovation projects, and fostering a culture of continuous improvement to optimize service efficiency, customer satisfaction, and business growth. Don works closely with internal teams and external partners, including startups, universities, and third parties, to ensure the successful integration of new technologies that meet the evolving needs of the semiconductor industry.

With over 20 years of experience in the semiconductor industry, Don has held multiple roles, including program management, product, application, and test engineering in both Silicon Valley and Asia. He holds a Bachelor's degree in Electrical and Electronics Engineering from Nanyang Technological University in Singapore and a Master’s of Studies from the University of Cambridge in the United Kingdom.

In this episode we will discover how scan technology and automatic test pattern generation (ATPG) have revolutionized the testing process, significantly boosting defect detection rates. Mark delves into digital twins, explaining their pivotal role in creating virtual representations for real-time system optimization.

Explore the exciting integration of digital twins within the EDA workflow, where collaboration with industry giants ensures model accuracy through rigorous real silicon testing. Learn about the benefits that digital twins bring, from reducing time to market to achieving regulatory compliance in critical sectors such as automotive and medical. The discussion dives into how Streaming Scan Networks an

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