NANO-CHIPS 2030
On-Chip AI for an Efficient Data-Driven World
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Beschreibung
In this book, a global team of experts from academia, research institutes and industry presents their vision on how new nano-chip architectures will enable the performance and energy efficiency needed for AI-driven advancements in autonomous mobility, healthcare, and man-machine cooperation. Recent reviews of the status quo, as presented in CHIPS 2020 (Springer), have prompted the need for an urgent reassessment of opportunities in nanoelectronic information technology. As such, this book explores the foundations of a new era in nanoelectronics that will drive progress in intelligent chip systems for energy-efficient information technology, on-chip deep learning for data analytics, and quantum computing. Given its scope, this book provides a timely compendium that hopes to inspire and shape the future of nanoelectronics in the decades to come.
In this book, a global team of experts from academia, research institutes and industry presents their vision on how new nano-chip architectures will enable the performance and energy efficiency needed for AI-driven advancements in autonomous mobility, healthcare, and man-machine cooperation. Recent reviews of the status quo, as presented in CHIPS 2020 (Springer), have prompted the need for an urgent reassessment of opportunities in nanoelectronic information technology. As such, this book explores the foundations of a new era in nanoelectronics that will drive progress in intelligent chip systems for energy-efficient information technology, on-chip deep learning for data analytics, and quantum computing. Given its scope, this book provides a timely compendium that hopes to inspire and shape the future of nanoelectronics in the decades to come.
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
Autor*in
Boris Murmann
Themen in »NANO-CHIPS 2030«
Nano-Electronics Artificial Intelligence CMOS Chips Energy Efficiency 3D Integration Acquisition of Information Ultra-Low-Power Processing Deep Learning Graphics Accelerators Implanted Chips HDR Vision Energy Autonomy Hardware for Robots Embedded Systems
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“Less than 10 years ago, the Springer book Chips 2020 laid out the path to the future of nano-electronics in an era where energy-efficient and sustainable integrated circuits should become a new style of living. Now, Bernd Hoefflinger and Boris Murmann have re-emerged onto the scene with NANO-CHIPS 2030, highlighting novel solutions for energy-aware micro- and nano-electronics. These solutions come as a sum of actions at all levels: from manufacturing solutions that enable new ‘More than Moore’ silicon technologies to entirely new system and design opportunities. The two major paradigm changes in data processing – artificial intelligence towards virtual reality and quantum computing – are largely debated as THE solutions for the 2030 world of sustainable electronics. In thirty chapters, the editors, along with a stellar line-up of senior experts from throughout industry and academia, outline their vision for the nano-electronics roadmap of the future. A must read, enlightening and visionary!” (Dr. Andreia Cathelin, Technology R&D Fellow, STMicroelectronics)
“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)
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