A SURVEY ON MACHINE LEARNING APPLICATIONS IN VLSI CAD

The incorporation of machine learning (ML) methodologies into VLSI computer-aided design (CAD) procedures is gaining prominence owing to its capacity to enhance design efficiency, forecast performance, and diminish time-to market. This literature overview examines the advanced machine learning techniques used at many phases of VLSI design. This review synthesizes data from current research articles, emphasizing the strengths, limits, and prospective avenues for machine learning implementations in VLSI CAD.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-16
DOI
https://doi.org/10.5281/zenodo.17137520
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
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article

A SURVEY ON MACHINE LEARNING APPLICATIONS IN VLSI CAD

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

A SURVEY ON MACHINE LEARNING APPLICATIONS IN VLSI CAD

article en

Abstract

The incorporation of machine learning (ML) methodologies into VLSI computer-aided design (CAD) procedures is gaining prominence owing to its capacity to enhance design efficiency, forecast performance, and diminish time-to market. This literature overview examines the advanced machine learning techniques used at many phases of VLSI design. This review synthesizes data from current research articles, emphasizing the strengths, limits, and prospective avenues for machine learning implementations in VLSI CAD.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 44%
Geochemistry and Geologic Mapping
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A SURVEY ON MACHINE LEARNING APPLICATIONS IN VLSI CAD · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS