Editors:
- Presents key elements of a new epoch in nanoelectronics that follows the end of the Nanometer Roadmap
- A timely compendium that will inspire and shape the future of nanoelectronics
- Explores the next generation of intelligent and energy-efficient chip-systems related to health and information technology
- Broadens perspectives of the existing chip-savvy audience while appealing to new readers in system design
Part of the book series: The Frontiers Collection (FRONTCOLL)
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Table of contents (30 chapters)
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Front Matter
About this book
Reviews
“NANO-CHIPS 2030 provides an up-to-date and exhaustive guide on integrated circuits, systems and applications with a focus on artificial intelligence, synthesizing the most relevant ground-breaking research of the past decade. It serves as an excellent resource for researchers to broaden their horizons and identify parallel efforts in adjacent fields. Electronic designers looking to exploit full-stack optimization will certainly get their money’s worth. Through topics like extreme energy efficiency, 3D integration and brain-inspired design, the book discusses solutions to the end of traditional CMOS scaling. Neuromorphic engineering clearly surfaces as the way forward: AR/VR and human-machine interfacing shall leverage perception science, neuro-inspired architectures and AI algorithms to the extreme. All these and more are presented in an approachable manner, rewarding the reader with the ability to deepen their expertise, connect the dots and disentangle the mysteries of on-chip AI.” (Dr. Hans Reyserhove, Research Scientist in Intelligent Vision Systems, Facebook Reality Labs Research)
Editors and Affiliations
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Department of Electrical Engineering, Stanford University, Stanford, USA
Boris Murmann
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Sindelfingen, Germany
Bernd Hoefflinger
About the editors
Bernd Hoefflinger became an Assistant Professor at Cornell University, Ithaca, NY, USA, after completing his Ph.D. at the Technical University of Munich, Germany. He was a co-founder of the MOS Division of Siemens in Munich, and founded the Electrical Engineering Department of the University of Dortmund, Germany, which houses the first Ion-Implanted BiCMOS production line. After serving as Head of the Electrical Engineering Departments at the University of Minnesota and then at Purdue University in Indiana, he established the Institute of Microelectronics Stuttgart, Germany, as the first ISO 9000-certified research and manufacturing facility – a leader in ASICs, HDR vision, and e-beam-driven nanotechnology.
Boris Murmann received his Ph.D. degree from the University of California, Berkeley, in 2003, and serves as a Professor of Electrical Engineering at Stanford University. His research interests are in mixed-signal integrated circuit design, with a focus on sensor interfaces, data converters, and custom circuits for embedded machine learning. He has served as an Associate Editor of the IEEE Journal of Solid-State Circuits, an AdCom member and a Distinguished Lecturer of the IEEE Solid-State Circuits Society, as well as the Data Converter Subcommittee Chair and the Technical Program Chair of the IEEE International Solid-State Circuits Conference (ISSCC). He is a Fellow of the IEEE.
Bibliographic Information
Book Title: NANO-CHIPS 2030
Book Subtitle: On-Chip AI for an Efficient Data-Driven World
Editors: Boris Murmann, Bernd Hoefflinger
Series Title: The Frontiers Collection
DOI: https://doi.org/10.1007/978-3-030-18338-7
Publisher: Springer Cham
eBook Packages: Physics and Astronomy, Physics and Astronomy (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-18337-0Published: 09 June 2020
Softcover ISBN: 978-3-030-18340-0Published: 16 July 2021
eBook ISBN: 978-3-030-18338-7Published: 08 June 2020
Series ISSN: 1612-3018
Series E-ISSN: 2197-6619
Edition Number: 1
Number of Pages: XXIII, 592
Number of Illustrations: 78 b/w illustrations, 296 illustrations in colour
Topics: Nanoscale Science and Technology, Electronics and Microelectronics, Instrumentation, Nanotechnology, Semiconductors, R & D/Technology Policy