NANO-CHIPS 2030 [E-Book] : On-Chip AI for an Efficient Data-Driven World / edited by Boris Murmann, Bernd Hoefflinger.
Hoefflinger, Bernd, (editor)
Murmann, Boris, (editor)
1st edition 2020.
Cham : Springer, 2020
XXIII, 592 pages 374 illustrations, 296 illustrations in color (online resource)
The Frontiers Collection
Full Text
Table of Contents:
  • New Programs after the End of the Nanometer Roadmap
  • Real-World Electronics
  • Silicon Complementary MOS (CMOS) Technology in its 7th Decade
  • The Future of Ultra-Low-Power SOTBC CMOS
  • Energy-Efficient and High-Throughput Digital CMOS
  • Update on Monolithic 3D Integration
  • Heterogeneous 3D Integration
  • 3D High-Speed Memories Enabling the AI Future
  • Minimum Nano-Features with EUV Lithography
  • Acquisition of Information
  • Machine-Learning Inference
  • Multi-Sensor, Intelligent Microsystems
  • 3D for efficient, Application-Specific Circuits (ASICs and FPGAs)
  • Field-Programmable Arrays
  • Coarse-Grained Reconfigurable Architectures
  • Graphics-Accelerators and -Processors
  • 1,000x Improvement of the Processor-Memory Gap
  • Supercomputers
  • Deep Learning On-Chip
  • Digital Neural Networks
  • Brain-Inspired Spiking-Neurons Systems
  • Energy-Autonomous Chip-Systems
  • Wearable and Implanted Chips
  • Electronics for the Human Visual System
  • Subretinal Implants in their Third Decade
  • Update on Perception-Inspired HDR Video
  • High-Dynamic-Range and High-Color Gamut Video
  • Augmented and Virtual Reality
  • Machine-Learning for Robotics - Hardware Requirements for Care Robots
  • Prospects of Quantum Computing
  • Man-Machine Cooperation and Cognitronics.