Deep In-memory Architectures for Machine Learning (1st ed. 2020)

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Synopsis
This book describes the recent innovation of deep in-memory architectures for realizing AI systems that operate at the edge of energy-latency-accuracy trade-offs. From first principles to lab prototypes, this book provides a comprehensive view of this emerging topic for both the practicing engineer in industry and the researcher in academia. The book is a journey into the exciting world of AI systems in hardware.
Copyright:
2020

Book Details

Book Quality:
Publisher Quality
ISBN-13:
9783030359713
Related ISBNs:
9783030359706
Publisher:
Springer International Publishing
Date of Addition:
Copyrighted By:
Springer
Adult content:
No
Language:
English
Has Image Descriptions:
No
Categories:
Nonfiction, Computers and Internet, Technology
Submitted By:
Bookshare Staff
Usage Restrictions:
This is a copyrighted book.

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