학술논문
Accelerating Chip Design With Machine Learning
Document Type
Periodical
Author
Source
IEEE Micro Micro, IEEE. 40(6):23-32 Jan, 2020
Subject
Language
ISSN
0272-1732
1937-4143
1937-4143
Abstract
Recent advancements in machine learning provide an opportunity to transform chip design workflows. We review recent research applying techniques such as deep convolutional neural networks and graph-based neural networks in the areas of automatic design space exploration, power analysis, VLSI physical design, and analog design. We also present a future vision of an AI-assisted automated chip design workflow to aid designer productivity and automate optimization tasks.