This book covers the new field of straintronics, using strain switched nanomagnets for extremely energy-efficient computing, information processing, communication, and signal generation. Based on well-established CMOS technology, traditional electronics have two significant shortcomings: excessive energy dissipation and volatility, which is the inability to retain information after power has been switched off. Straintronics is more energy-efficient and non-volatile (but also more error-prone), allowing it to eclipse traditional electronics in niche areas that are increasingly attracting attention, such as image processing and probabilistic computing, computer vision, machine learning, neuromorphic networks, probabilistic computing, and belief networks.

Magnetic Straintronics: An Energy-Efficient Hardware Paradigm for Digital and Analog Information Processing introduces straintronics and the technology's myriad applications for researchers, engineers, and scientists in electrical engineering, physics, and computer engineering.

Supriyo Bandyopadhyay, Ph.D., is Commonwealth Professor of Electrical and Computer Engineering at Virginia Commonwealth University, where he directs the Quantum Device Laboratory. Research conducted in the laboratory has been frequently featured in international media, journals, TV, newspapers, and internet blogs. He has authored over 400 research publications and given over 150 invited keynote or plenary talks across four continents. Professor Bandyopadhyay was named "Virginia's Outstanding Scientist" by Governor Terrence McAuliffe in 2016 and won the State Council of Higher Education for Virginia Outstanding Faculty Award in 2018. He was given the "University Award of Excellence" by his university in 2017; it is the highest award given by his university to one faculty member in a given year. Dr. Bandyopadhyay is the 2020 recipient of the IEEE Pioneer in Nanotechnology Award. He is a Fellow of IEEE, American Physical Society, Institute of Physics, the Electrochemical Society, and the American Association for the Advancement of Science.

Introduction to Straintronics.- The Physics Behind Straintronics.- Straintronic Logic and Memory.- Energy-efficiency Versus Reliability of Straintronic Logic and Memory.- Ternary Content-addressable Memory.- Analog Computing With Straintronic Devices.- High-Frequency Signal Generation With Straintronics.- Non-boolean Computing - Image Processing, Computer Vision, Belief Networks for Computing in the Presence of Uncertainty, and Probabilistic Computing.- Straintronic Antennas - Acoustic and Electromagnetic.- Long Term Vision.