Accelerating Chip Design with Machine Learning

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.


Saad Godil (NVIDIA)
Robert Kirby (NVIDIA)
Alicia Klinefelter (NVIDIA)
Bryan Catanzaro (NVIDIA)

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