书目名称 | Machine Learning and Non-volatile Memories | 编辑 | Rino Micheloni,Cristian Zambelli | 视频video | | 概述 | Applies novel concepts from machine learning and Artificial Intelligence (AI) to tackle complex problems.Presents the basics of both NAND Flash storage and machine learning, detailing the memories pro | 图书封面 |  | 描述 | This book presents the basics of both NAND flash storage and machine learning, detailing the storage problems the latter can help to solve. At a first sight, machine learning and non-volatile memories seem very far away from each other. Machine learning implies mathematics, algorithms and a lot of computation; non-volatile memories are solid-state devices used to store information, having the amazing capability of retaining the information even without power supply. This book will help the reader understand how these two worlds can work together, bringing a lot of value to each other. In particular, the book covers two main fields of application: analog neural networks (NNs) and solid-state drives (SSDs)..After reviewing the basics of machine learning in Chapter 1, Chapter 2 shows how neural networks can mimic the human brain; to accomplish this result, neural networks have to perform a specific computation called vector-by-matrix (VbM) multiplication, which isparticularly power hungry. In the digital domain, VbM is implemented by means of logic gates which dictate both the area occupation and the power consumption; the combination of the two poses serious challenges to the hardwar | 出版日期 | Book 2022 | 关键词 | Artificial Intelligence; 3D NAND Flash Memory; Autonomous Solid-state-drive; NAND-specific Neural Netwo | 版次 | 1 | doi | https://doi.org/10.1007/978-3-031-03841-9 | isbn_softcover | 978-3-031-03843-3 | isbn_ebook | 978-3-031-03841-9 | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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