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A survey on machine learning-based routing for VLSI physical design

Published: 01 September 2022 Publication History

Abstract

Routing is one of the most important and time-consuming stages of physical design. As the process node of semiconductors keeps scaling down, the routing process faces increasing challenges, and the traditional solutions are not sufficiently efficient. In recent years, machine learning has aroused much interest in this context, and an increasing number of algorithms have introduced advanced machine learning techniques to help solve the routing problem. In this paper, we survey the recent development of machine learning-based routing algorithms.

Highlights

This paper provides an overview of recent published machine learning-based routing algorithms.
Some trends on the development of machine learning-based routing algorithms are revealed.
The possible advantages and disadvantages on machine learning-based routing methods are discussed.

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  • (2023)AI/ML algorithms and applications in VLSI design and technologyIntegration, the VLSI Journal10.1016/j.vlsi.2023.06.00293:COnline publication date: 1-Nov-2023

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Published In

cover image Integration, the VLSI Journal
Integration, the VLSI Journal  Volume 86, Issue C
Sep 2022
98 pages

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 September 2022

Author Tags

  1. Survey
  2. Routing
  3. Machine learning

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  • (2023)AI/ML algorithms and applications in VLSI design and technologyIntegration, the VLSI Journal10.1016/j.vlsi.2023.06.00293:COnline publication date: 1-Nov-2023

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