Artificial Intelligence and Machine Learning in Chip Design
Artificial intelligence (AI) and machine learning (ML) techniques are being rapidly introduced into modern chip design methodologies and the underlying electronic design automation (EDA) tools. This offers integrated-circuit (IC) chip companies and their engineers the potential to improve product quality in key dimensions – speed, energy efficiency, and cost – with less engineering resources and faster time-to-market. Understanding these technical advances and their potential applications can help engineers improve their design methods while preparing for the coming fundamental shifts in how chip design is performed. This course will provide broad coverage of what engineers need to know about AI and ML in chip design and EDA: why AI and ML technologies are the future; high-value applications in chip design and design automation; the AI and ML technologies most relevant to chip design; infrastructure and deployment considerations; and what lies ahead.
Brought to you by IEEE Educational Activities in partnership with IEEE Future Directions and IEEE Global Semiconductors.
What you will learn:
- Essential knowledge to leverage AI and ML effectively in chip design and EDA
- Understanding of the rationale behind these technological shifts to identifying high-value applications and selecting relevant AI and ML technologies, and
- Insights into optimizing design methods and preparing for the future of chip design
Courses included in this program:
Course Program Length: 4 hours
Who Should Attend: IC Designers, IC Design Project Managers, IC CAD Integrators, EDA Researchers, Developers, and Educators, AI and ML Researchers, Developers, and Educators, R&D Program Managers
Instructor
Andrew B Kahng, Distinguished Professor of CSE and ECE and holder of the endowed chair in high-performance computing at the University of California at San Diego.
Publication Year: 2024
ISBN: 978-1-7281-7861-5