Late Breaking Results: Parallelizing Net Routing with cGANs

Obstacle-avoiding multiterminal net routing approach is proposed. The approach is inspired by deep learning image processing. The key idea is based on training a conditional generative adversarial network (cGAN) to interpret a routing task as a graphical bitmap and consequently map it to an optimal...

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Bibliographic Details

Published in:	2021 58th ACM/IEEE Design Automation Conference (DAC) pp. 1372 - 1373
Main Authors:	Utyamishev, Dmitry, Partin-Vaisband, Inna
Format:	Conference Proceeding
Language:	English
Published:	IEEE 05.12.2021
Subjects:	Benchmark testing cGAN Deep learning Design automation generative models GPU Graphics processing units Imaging inpainting multiterminal Net routing neural network Training Very large scale integration
Online Access:	Get full text
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