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| Title | NANO-CHIPS 2030 : On-Chip AI for an Efficient Data-Driven World |
| Author(s) | Murmann, Boris;Hoefflinger, Bernd |
| Publication | Cham, Springer International Publishing, 2020. |
| Description | XXIII, 592 p. 374 illus., 296 illus. in color : online resource |
| Abstract Note | 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. |
| ISBN,Price | 9783030183387 |
| Keyword(s) | 1. EBOOK
2. EBOOK - SPRINGER
3. ECONOMIC POLICY
4. ELECTRONICS
5. Electronics and Microelectronics, Instrumentation
6. MICROELECTRONICS
7. Nanoscale science
8. Nanoscale Science and Technology
9. NANOSCIENCE
10. Nanostructures
11. NANOTECHNOLOGY
12. R & D/Technology Policy
13. SEMICONDUCTORS
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| Item Type | eBook |
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Call# | Status | Issued To | Return Due On | Physical Location |
| I09717 |
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