Y. Priya,
S. Archana,
- Assistant Professor, Department of ECE, Sphoorthy Engg. College, Hyderabad, India
- Assistant Professor, Department of ECE, Sphoorthy Engg. College, Hyderabad, India
Abstract
It represents the first use of AI in the domain of integrating circuits, which has been impacted by it. The conventional VLSI design process that is now in use is replaced by this technology. The laborious manual concepts created by people have been replaced with automated design innovations. This development would trigger a profound change in the fields of AI education and hardware computation. With the introduction of contemporary chips, which are extremely intricate, designing with human involvement is a laborious and lengthy operation. The field of artificial intelligence (AI) has been gaining substantial ground in both the development and production of semiconductors using VLSI (Very Large-S Scale Integration). While the reliability, preciseness, as well as effectiveness of many areas of design for VLSI are being improved by AI technologies, there is still little prospect for the traditional methods of verifying essential architectures. For this reason, during the past four decades, many other sophisticated tasks have been automated in addition to a number of other tasks. The drafting workflow becomes automatic when an inventive concept is generated (with regard to calculation, thinking about, optimization, and interconnecting fabrication). Businesses having their own in-house CAD organizations, like IBM and Intel, are equipped to manage certain computerized procedures. Numerous businesses, including Cadence, Brief, and Mentor Illustration, sell CAD tools that are used to integrate AI in chip design. In various technological domains, data mining has extended its reach to provide workable solutions for a wide range of issues. Machine learning significance in the software for the electronic device industry has grown, as has its promise to lower costs, increase product production, and shorten designing and implementing times. In this study, we constructed mathematical modeling (ML) BIST and discussed the role of deep learning in VLSI chip layout.
Keywords: ML, AI, VLSI, BIST, CAD, EDA
[This article belongs to Trends in Machine design (tmd)]
Y. Priya, S. Archana. The Integration of Machine Learning in VLSI IC Design. Trends in Machine design. 2024; 11(02):1-8.
Y. Priya, S. Archana. The Integration of Machine Learning in VLSI IC Design. Trends in Machine design. 2024; 11(02):1-8. Available from: https://journals.stmjournals.com/tmd/article=2024/view=176408
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Trends in Machine design
| Volume | 11 |
| Issue | 02 |
| Received | 10/04/2024 |
| Accepted | 03/05/2024 |
| Published | 30/09/2024 |
