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.
Deep In-memory Architectures for Machine Learning
Mingu Kang, Sujan Gonugondla, Naresh R. Shanbhag
Springer
2020
186 páginas
6h 12m
ISBN-13: 9783030359706
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