Advancing VLSI Design with AI and Machine Learning: Opportunities, Challenges, and Security Considerations
Keywords:
Artificial intelligence in VLSI, Edge AI, Machine learning, Next-generation VLSI, Reconfigurable computingAbstract
The incorporation of Artificial Intelligence (AI) and Machine Learning (ML) in Very-Large-Scale Integration (VLSI) design has created new opportunities for creativity, efficiency, and automation in electronic systems. This study examines the advanced use of AI/ML in VLSI, emphasizing their role in expediting design processes, improving performance, and optimizing power usage. AI/ML algorithms automate previously laborious and time-intensive operations in VLSI design and testing, reducing both time and resource expenditures. Additionally, the article explores the intricate security difficulties stemming from this integration, analyzes potential vulnerabilities, and recommends effective security methods to alleviate risks. The evolution of the VLSI industry, in conjunction with AI/ML, offers remarkable breakthroughs while requiring diligent risk management and novel strategies to ensure the integrity and reliability of future electronic systems.
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