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This document discusses the integration of deep learning techniques in Electronic Design Automation (EDA), focusing on the application of point clouds as a data representation. It reviews challenges and potential applications of point clouds in EDA, including routing tree construction and hotspot detection, while also summarizing previous deep learning methods used in the field. The paper aims to stimulate future research by presenting case studies and highlighting the advantages of point clouds over tradit

Author

Shubrata Barua

Language

EN