Deep In-memory Architectures for Machine Learning (Record no. 75950)

000 -LEADER
fixed length control field 03446nam a22005535i 4500
001 - CONTROL NUMBER
control field 978-3-030-35971-3
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801214108.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 200130s2020 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783030359713
-- 978-3-030-35971-3
082 04 - CLASSIFICATION NUMBER
Call Number 621.3815
100 1# - AUTHOR NAME
Author Kang, Mingu.
245 10 - TITLE STATEMENT
Title Deep In-memory Architectures for Machine Learning
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2020.
300 ## - PHYSICAL DESCRIPTION
Number of Pages X, 174 p. 104 illus., 65 illus. in color.
505 0# - FORMATTED CONTENTS NOTE
Remark 2 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.
520 ## - SUMMARY, ETC.
Summary, etc 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.
700 1# - AUTHOR 2
Author 2 Gonugondla, Sujan.
700 1# - AUTHOR 2
Author 2 Shanbhag, Naresh R.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-030-35971-3
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2020.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electronic circuits.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Cooperating objects (Computer systems).
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Microprocessors.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer architecture.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electronic Circuits and Systems.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Cyber-Physical Systems.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Processor Architectures.
912 ## -
-- ZDB-2-ENG
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-- ZDB-2-SXE

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