AI-Driven Optimization and Automation of Integrated Circuit Design
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Product details:
- Publisher Elsevier
- Date of Publication 1 October 2026
- ISBN 9780443416521
- Binding Paperback
- No. of pages400 pages
- Size 235x191 mm
- Weight 450 g
- Language English 700
Categories
Long description:
AI-Driven Optimization and Automation of Integrated Circuit Design discusses the latest AI-based methods, algorithms, architectures, and frameworks for digital, analog, and mixed-signal VLSI circuit design, verification and testability, physical design and related areas. The book considers the issues with traditional circuit design and explains how machine learning techniques can optimize and automate the process. It goes on to explain how AI-driven design can impact logic synthesis, circuit placement and routing, and behavioral simulation. Final sections include cases studies and a look at future developments for implementations of VLSI design, IC design, and hardware realization using AI tools and techniques.
Artificial Intelligence (AI) offers a solution to the bottleneck issues in the design of integrated circuits (IC) by optimizing and automating tasks in the design and fabrication process. As the world focuses on the development of skilled manpower and automation tools for chip design, verification, testing and fabrication, AI can be utilized to optimize and automate various steps in design cycle, saving time, reducing errors, and managing power consumption.
- Explains how AI algorithms can significantly speed up the IC design process by automating tasks
- Describes how AI can enhance precision in circuit design by reducing errors and improving design verification through predictive analysis
- Offers insights into how to integrate AI tools and techniques into existing EDA (Electronic Design Automation) workflows
Table of Contents:
1. Automation in Analog Circuit Design using AI
2. Neural Network for Logic Synthesis Optimization
3. Machine Learning Approaches to Fault Detection in Circuit Design
4. Enhancing Chip Verification using AI
5. AI Applications in Digital Design for Testability (DFT
6. Machine leaning based power estimation in VLSI Design
7. Next-Gen IC Fault Detection using Advanced Machine Learning Algorithms - A Comprehensive Survey
8. AI-driven high level synthesis and behavioral simulation in VLSI design
9. Leveraging machine learning algorithms for designing analog and RF integrated circuits
10. Challenges with traditional integrated circuits design methods
11. Optimization techniques in ML for VLSI design
