AI/ML algorithms and applications in VLSI design and technology

Deepthi Amuru, Andleeb Zahra, Harsha V. Vudumula, Pavan K. Cherupally, Sushanth R. Gurram, Amir Ahmad, Zia Abbas

Research output: Contribution to journalReview articlepeer-review

7 Citations (Scopus)

Abstract

An evident challenge ahead for the integrated circuit (IC) industry is the investigation and development of methods to reduce the design complexity ensuing from growing process variations and curtail the turnaround time of chip manufacturing. Conventional methodologies employed for such tasks are largely manual, time-consuming, and resource-intensive. In contrast, the unique learning strategies of artificial intelligence (AI) provide numerous exciting automated approaches for handling complex and data-intensive tasks in very-large-scale integration (VLSI) design and testing. Employing AI and machine learning (ML) algorithms in VLSI design and manufacturing reduces the time and effort for understanding and processing the data within and across different abstraction levels. It, in turn, improves the IC yield and reduces the manufacturing turnaround time. This paper thoroughly reviews the AI/ML automated approaches introduced in the past toward VLSI design and manufacturing. Moreover, we discuss the future scope of AI/ML applications to revolutionize the field of VLSI design, aiming for high-speed, highly intelligent, and efficient implementations.

Original languageEnglish
Article number102048
JournalIntegration
Volume93
DOIs
Publication statusPublished - Nov 2023

Keywords

  • Artificial intelligence (AI)
  • CMOS
  • Machine learning (ML)
  • Manufacturing
  • VLSI design

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Electrical and Electronic Engineering

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