As AI and machine learning are becoming important in EDA, Si2 launched a special interest group.
Through this, SIG will fill the industry gaps to enable AI and ML in EDA.
The group will identify current solutions and technology gaps in AI and ML strategies for EDA digital design.
Silicon Integration Initiative (Si2) has launched a special interest group to focus on the growing needs and opportunities in artificial intelligence and machine learning for electronic design automation (EDA).
The group will recognize solutions and technology gaps that are currently applied in Artificial Intelligence (AI) and Machine Learning (ML) strategies. It will make changes in electronic design in EDA as they are changing semiconductor design and improving performance and time to market.
“Based on member company interest, we expect the SIG to propose prototype projects to accelerate the development of standards in areas such as machine learning training, and data handling and sharing.”
Leigh Anne Clevenger, Design Automation Data scientist, Si2
He also explained high manufacturing costs and the growing complexity of chip development are spurring disruptive technologies such as AI and ML. "Si2 provides a unique opportunity for semiconductor companies, EDA suppliers and IP providers to voice their needs and focus resources on common solutions, including leveraging university research."
The SIG is open to all Si2 members and is chaired by Joydip Das, Senior Engineer I, Samsung Austin R&D Center, and co-chaired by Kerim Kalafala, senior technical staff member, EDA, IBM.
"In recent years, the EDA industry has significantly expanded the use of AI and ML technology and techniques in its design tools,” Das said.
��We’ve identified the need for a common industry-wide infrastructure to help share this information. This will help eliminate duplicative work and open up avenues for new breakthroughs."
Joydip Das, Sr. Engineer, Samsung Austin
Other Si2 members participating in the SIG include Advanced Micro Devices, ANSYS, Cadence Design Systems, Hewlett Packard Enterprise, Intel, Intento Design, NC State University, PDF Solutions, Sandia Labs, Synopsys and the University of California, Berkeley.
Background: EDA in the era of AI and ML
For years, analysts and developers have been saying that artificial intelligence and electronic design automation are a perfect match. EDA problems have high dimensionality, discontinuities, nonlinearities, and high-order interactions. What better way to grapple with this level of complexity than to ?
The complexity of integrated circuits (ICs) means the number of possible design iterations that need to be evaluated continues to increase, but their regularity means design rules that work well can have a massive positive impact across large parts of the design. Using AI and ML to move from ‘maybe’ to ‘definitely’ in fewer iterative steps can deliver greater productivity in an automated flow.
As the , it’s increasingly clear that AI and its many derivatives (deep learning, machine learning, etc.) will lead to profound socioeconomic changes of a magnitude the world hasn’t seen since the industrial revolution. While it can sometimes be a controversial topic in terms of its , and potential impact on global socioeconomics, one thing is certain: AI is, even in its infancy, being effectively deployed to vastly improve and better automate a number of tasks ranging from data collection, communications, robotics/factory automation, automotive design—and to even our own small but mighty industry, EDA, in chip design.
To help companies deliver more sophisticated AI technologies, EDA companies are doing two things:
1. Developing tools to help companies design AI-accelerators faster.
2. Leveraging machine-learning algorithms to improve IC design tools so that they can deliver better results for customers faster.
Founded in 1988, Si2 is a leading research and development joint venture that . Its activities include support of OpenAccess, the world’s most widely used standard API and reference database for integrated circuit design. All Si2 activities are carried out under the auspices of The National Cooperative Research and Production Act of 1993, the fundamental law that defines R&D joint ventures and offers them a large measure of protection against federal antitrust laws.