Si2 Publishes White Paper on Expanding Use of AI/ML in Semiconductor Electronic Design

A new Silicon Integration Initiative white paper identifies a common data model as the most critical need to accelerate the use of artificial intelligence and machine learning in semiconductor electronic design automation.

The white paper, produced by a 20-member Si2 Special Interest Group, reports on findings of a global survey that identifies planned usage and structural gaps for AI and ML in EDA. It is available at  https://si2.org/product/collaborative-data-model/

Leigh Anne Clevenger, Si2 senior data scientist, said that the white paper identifies “a standard, common model for classifying and structuring machine learning and inference data as being crucial to accelerating the use of AI/ML in EDA. This data model would provide a foundation for addressing the data organization gap for chip developers, EDA tool developers, IP providers, and researchers. It would support design data and derived data for high-interest use cases.”

The survey also identifies a common reference flow, on-line AI/ML courses and organized training data as industry needs.

The white paper addresses:

  • Machine Learning and IC Design
  • Demand for Data
  • Structure of a Data Model
  • A Unified Data Model: Digital and Analog Examples
  • Definition and Characteristics of Derived Data for ML Applications
  • Need for IP Protection
  • Unique Requirements for Inferencing Models
  • Key Analysis Domains
  • Conclusions and Proposed Future Work

Member of the Si2 Special Interest Group include:

  • Advanced Micro Devices
  • Ansys
  • Cadence Design Systems
  • GLOBALFOUNDRIES
  • Hewlett Packard Enterprise
  • IBM
  • Intel Corp.
  • Intento Design
  • Keysight Technologies
  • Mentor, a Siemens Business
  • NC State University
  • PDF Solutions
  • Qualcomm
  • Samsung
  • Sandia National Laboratories
  • Silvaco
  • SK Hynix
  • Synopsys
  • Texas Instruments
  • Thrace Systems

 

Si2 Launches Survey on Artificial Intelligence and Machine Learning in EDA

Si2 has launched an industry-wide survey to identify planned usage and structural gaps for prioritizing and implementing artificial intelligence and machine learning in semiconductor electronic design automation.

The survey is organized by a recently formed Si2 Special Interest Group chaired by Joydip Das, senior engineer, Samsung Electronics, and co-chaired by Kerim Kalafala, senior technical staff member, EDA, and master inventor, IBM. The 18-member group will identify where industry collaboration will help eliminate deficiencies caused by a lack of common languages, data models, labels, and access to robust and categorized training data.

This SIG is open to all Si2 members. Current members include:

  • Advanced Micro Devices
  • ANSYS
  • Cadence Design Systems
  • Hewlett Packard Enterprise
  • IBM
  • Intel
  • Intento Design
  • Keysight Technologies
  • Mentor, a Siemens Business
  • NC State University
  • PFD Solutions
  • Qualcomm
  • Samsung Electronics
  • Sandia National Laboratories
  • Silvaco
  • Synopsys
  • Thrace Systems
  • Texas Instruments

The survey is open April 15 – May 15.

The survey link is:  https://bit.ly/SI2_AI_ML_Survey

Leigh Anne Clevenger, Si2 senior data scientist, said that the survey results would help prioritize SIG activities and timelines. “The SIG will identify and develop requirements for standards that ensure data and software interoperability, enabling the most efficient design flows for production,” Clevenger said. “The ultimate goal is to remove duplicative work and the need for data model translators, and focus on opening avenues for breakthroughs from suppliers and users alike.”

“High manufacturing costs and the growing complexity of chip development are spurring disruptive technologies such as AI and ML,” Clevenger explained. “The Si2 platform provides a unique opportunity for semiconductor companies, EDA suppliers and IP providers to voice their needs and focus resources on common solutions, including enabling and leveraging university research.