VLSI Design for Artificial Intelligence and Machine Learning Applications - Hardcover

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Balwinder Raj, PhD is an Associate Professor at the National Institute of Technology Jalandhar, India, with more than 15 years of teaching, research, and administrative experience. He has authored and co-authored eight books, 15 book chapters, and more than 150 research papers. His research interests include nanoscale semiconductor device modeling, nanoelectronics, hardware security, sensors, circuit design, and FinFET-based memory design.

Koushik Guha, PhD is an Associate Professor and Head of the Department of Electronics and Communication Engineering at the National Institute of Technology, Silchar, India. He has published more than 200 journal and conference papers, authored over 35 book chapters, and two books. His research interests include MEMS, RF MEMS, BIO-MEMS, smart sensors for IoT, and VLSI circuit design and optimization.

Shiromani Balmukund Rahi, PhD is an Assistant Professor in the School of Information and Communication Technology at Gautam Buddha University, Greater Noida, India. He has published 25 research articles, two conference proceedings, 25 book chapters, and seven books. His research focuses on low-power VLSI design, quantum-dot cellular automata, non-volatile memory devices, logic-in-memory computing, and neuromorphic computing.

Nehru Kandasamy, PhD is a Professor in the Department of Electronics and Communication Engineering at the Madanapalle Institute of Technology and Science, India. He has published numerous peer-reviewed articles and serves as a reviewer for more than 15 journals. His research interests include low-power VLSI design, quantum-dot cellular automata, non-volatile memory devices, logic-in-memory computing, and neuromorphic computing.

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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.