A REVIEW OF ARTIFICIAL INTELLIGENCE – BASED LOGIC GATE SYNTHESIS AND OPTIMIZATION IN ELECTRONIC DESIGN AUTOMATION

This review examines the application of Artificial Intelligence (AI) and Machine Learning (ML) to logic gate synthesis and optimization within Electronic Design Automation (EDA). The paper discusses how AI-based approaches can assist in addressing the increasing complexity of modern digital circuits and the challenges associated with optimizing Power, Performance, and Area (PPA).

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-29
DOI
https://doi.org/10.5281/zenodo.23039011
Primary Topic
VLSI and FPGA Design Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

A REVIEW OF ARTIFICIAL INTELLIGENCE – BASED LOGIC GATE SYNTHESIS AND OPTIMIZATION IN ELECTRONIC DESIGN AUTOMATION

Larens Refil
Zenodo (CERN European Organization for Nuclear Research)
VLSI and FPGA Design Techniques
article

A REVIEW OF ARTIFICIAL INTELLIGENCE – BASED LOGIC GATE SYNTHESIS AND OPTIMIZATION IN ELECTRONIC DESIGN AUTOMATION

Larens Refil
article en

Abstract

This review examines the application of Artificial Intelligence (AI) and Machine Learning (ML) to logic gate synthesis and optimization within Electronic Design Automation (EDA). The paper discusses how AI-based approaches can assist in addressing the increasing complexity of modern digital circuits and the challenges associated with optimizing Power, Performance, and Area (PPA).

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 22%
VLSI and FPGA Design Techniques
DOIOpen Access PDFOpenAlex
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A REVIEW OF ARTIFICIAL INTELLIGENCE – BASED LOGIC GATE SYNTHESIS AND OPTIMIZATION IN ELECTRONIC DESIGN AUTOMATION — Larens Refil · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS