VLSI Design for Artificial Intelligence and Machine Learning Applications

Unlock the next generation of AI chip design with this comprehensive guide to overcoming VLSI challenges, combining state-of-the-art nanomaterials, semiconductor modeling, and low-power circuit design into an essential roadmap for researchers and engineers.

Very large-scale integration (VLSI) is the interdisciplinary science of utilizing advanced semiconductor technology to create various functions of a computer system. By combining VLSI technology, a very powerful computer architecture is possible to overcome the problems at different design stages. AI techniques such as knowledge-based and expert systems first define the problem and then choose the best solution from a range of possible approaches.

This book comprehensively covers nanomaterials, semiconductor devices, and modeling and simulation techniques used to address the challenges of low-power VLSI chip design. It explores process variability, device sizing, power supply scaling, conventional and emerging materials, leakage mitigation techniques, and critical design tradeoffs. The book presents state-of-the-art research in nanomaterials and semiconductor technologies alongside practical design considerations for low-power VLSI circuits, making it an essential resource for scientists, researchers, and postgraduate students interested in AI hardware, semiconductor devices, modeling, and simulation.