Aug 2024
2 Hour
Access this Course
Previously Recorded -- In this course, we cover reasons for incorporation of AI and ML in modern chip design methods and design automation tools. The most important reason: the inexorable “Moore’s Law” need to scale cost, schedule efficiency, and IC product quality in terms of key metrics such as speed, energy efficiency, and manufacturing cost. We explain how AI and machine learning provide new levers for chip design: adding human-like intelligence to search and optimization, and leveraging collected data from past design iterations and experiences. Benefits include the lowering of expertise barriers, and the augmentation – and, reduction – of human engineering effort. Brought to you by IEEE Educational Activities in partnership with IEEE Future Directions.
Author Keywords: artificial intelligence, AI, machine learning, ML, chip design, chip engineering, artificial intelligence chip design, AI chip design, machine learning chip design, ML chip design, AI and ML, AI ML, integrated circuit chip, IC chip, IC engineer, IC engineering, chip speed, chip efficiency, electronic design automation, EDA, AI applications, ML applications, Moore's Law, IC product, IC product quality, AI search, artificial intelligence search, ML search, machine learning search, AI search optimization, ML search optimization, chip performance, chip performance data, augmenting human engineering, augment human engineering, chip designers, IC chip designers, chip design quality, tool output, AI agents, AI powered tools, mechanical engineering, mechanical engineer, chip design tasks, AI solutions, EDA tools, chip design method, chip design challenge, data privacy, EDA advances, hyperparameter search, GPU acceleration, chip design infrastructure, AI/ML deployment, AI ML deployment, EDA scale, generative AI, machine learning models, synthetic data generation
Persistent Link: https://ieeexplore.ieee.org/servlet/opac?mdnumber=EW1788 More »
Level: Intermediate
Instructor
Andrew Kahng
Andrew Kahng is Distinguished Professor of CSE and ECE and holder of the endowed chair in high-performance computing at the University of California at San Diego. He received the A.B. degree in applied mathematics (physics) from Harvard College, and the M.S. and Ph.D. degrees in computer science fro... Show More
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