NANO-CHIPS 2030 = on-chip AI for an ...
Murmann, Boris.

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  • NANO-CHIPS 2030 = on-chip AI for an efficient data-driven world /
  • Record Type: Electronic resources : Monograph/item
    Title/Author: NANO-CHIPS 2030/ edited by Boris Murmann, Bernd Hoefflinger.
    Reminder of title: on-chip AI for an efficient data-driven world /
    other author: Murmann, Boris.
    Published: Cham :Springer International Publishing : : 2020.,
    Description: xxiii, 592 p. :ill., digital ;24 cm.
    [NT 15003449]: 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.
    Contained By: Springer eBooks
    Subject: Systems on a chip. -
    Online resource: https://doi.org/10.1007/978-3-030-18338-7
    ISBN: 9783030183387
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