Deep In-memory Architectures for Machine Learning

Mingu Kang; Sujan Gonugondla; Naresh R. Shanbhag

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

Deep In-memory Architectures for Machine Learning

Mingu Kang, Sujan Gonugondla, Naresh R. Shanbhag

Research output: Book/Report/Conference proceeding › Book

Abstract

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.

Original language	English (US)
Publisher	Springer
Number of pages	174
ISBN (Electronic)	9783030359713
ISBN (Print)	9783030359706
DOIs	https://doi.org/10.1007/978-3-030-35971-3
State	Published - Jan 1 2020

ASJC Scopus subject areas

General Engineering
General Computer Science

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10.1007/978-3-030-35971-3

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Deep In-memory Architectures for Machine Learning

Abstract

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