Deep in-memory architectures for machine learning / Mingu Kang, Sujan Gonugondla, Naresh R. Shanbhag.
2020
TK7895.M4
Linked e-resources
Linked Resource
Online Access
Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks
Details
Title
Deep in-memory architectures for machine learning / Mingu Kang, Sujan Gonugondla, Naresh R. Shanbhag.
Author
Kang, Mingu.
ISBN
9783030359713 (electronic book)
3030359719 (electronic book)
3030359700
9783030359706
3030359719 (electronic book)
3030359700
9783030359706
Imprint
Cham : Springer, 2020.
Language
English
Description
1 online resource
Call Number
TK7895.M4
Dewey Decimal Classification
004.5
Summary
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. Describes deep in-memory architectures for AI systems from first principles, covering both circuit design and architectures; Discusses how DIMAs pushes the limits of energy-delay product of decision-making machines via its intrinsic energy-SNR trade-off; Offers readers a unique Shannon-inspired perspective to understand the system-level energy-accuracy trade-off and robustness in such architectures; Illustrates principles and design methods via case studies of actual integrated circuit prototypes with measured results in the laboratory; Presents DIMA's various models to evaluate DIMA's decision-making accuracy, energy, and latency trade-offs with various design parameter.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Added Author
Gonugondla, Sujan.
Shanbhag, Naresh R., 1966-
Shanbhag, Naresh R., 1966-
Available in Other Form
Print version: 9783030359706
Linked Resources
Online Access
Record Appears in
Online Resources > Ebooks
All Resources
All Resources
Table of Contents
Introduction
The Deep In-memory Architecture (DIMA)
DIMA Prototype Integrated Circuits
A Variation-Tolerant DIMA via On-Chip Training
Mapping Inference Algorithms to DIMA
PROMISE: A DIMA-based Accelerator
Future Prospects
Index.
The Deep In-memory Architecture (DIMA)
DIMA Prototype Integrated Circuits
A Variation-Tolerant DIMA via On-Chip Training
Mapping Inference Algorithms to DIMA
PROMISE: A DIMA-based Accelerator
Future Prospects
Index.