Deep In-memory Architectures for Machine Learning

Kang, Mingu; Gonugondla, Sujan; Shanbhag, Naresh R.

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.

Details

Published by: Springer

Publication Date: 2021-01-31

Format: Paperback

ISBN-13: 9783030359737

DOI: 10.1007/978-3-030-35971-3

Dimensions: 235cm x155cm

Pages: 174