Accelerators for convolutional neural networks / (Record no. 96058)

000 -LEADER
fixed length control field 05666nam a22005057i 4500
001 - CONTROL NUMBER
control field 13462108
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260710113446.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS--GENERAL INFORMATION
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007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 231018s2024 nju o 000 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781394171880
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781394171910
Qualifying information (electronic bk. : oBook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1394171919
Qualifying information (electronic bk. : oBook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781394171897
Qualifying information electronic book
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1394171897
Qualifying information electronic book
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781394171903
Qualifying information (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1394171900
Qualifying information (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Cancelled/invalid ISBN 9781394171880
Qualifying information hardcover
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Cancelled/invalid ISBN 1394171889
Qualifying information hardcover
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1002/9781394171910
Source of number or code doi
035 #9 - SYSTEM CONTROL NUMBER
System control number (GOBI)99996250713
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)1404053066
037 ## - SOURCE OF ACQUISITION
Stock number 10296182
Source of stock number/acquisition IEEE
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title eng
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA76.87
Item number .M86 2024
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3/2
Edition number 23/eng/20231025
100 1# - MAIN ENTRY--PERSONAL NAME
Preferred name for the person Munir, Arslan,
Relator term author.
245 10 - TITLE STATEMENT
Title Accelerators for convolutional neural networks /
Statement of responsibility, etc Arslan Munir, Joonho Kong, Mahmood Azhar Qureshi.
264 #1 - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Hoboken, New Jersey :
Name of publisher, distributor, etc John Wiley & Sons, Inc.,
Date of publication, distribution, etc [2024]
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource.
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
505 0# - CONTENTS
Formatted contents note About the Authors xiii -- Preface xv -- Part I Overview 1 -- 1 Introduction 3 -- 1.1 History and Applications 5 -- 1.2 Pitfalls of High-Accuracy DNNs/CNNs 6 -- 1.2.1 Compute and Energy Bottleneck 6 -- 1.2.2 Sparsity Considerations 9 -- 1.3 Chapter Summary 11 -- 2 Overview of Convolutional Neural Networks 13 -- 2.1 Deep Neural Network Architecture 13 -- 2.2 Convolutional Neural Network Architecture 15 -- 2.3 Popular CNN Models 26 -- 2.4 Popular CNN Datasets 30 -- 2.5 CNN Processing Hardware 31 -- 2.6 Chapter Summary 37 -- Part II Compressive Coding for CNNs 39 -- 3 Contemporary Advances in Compressive Coding for CNNs 41 -- 3.1 Background of Compressive Coding 41 -- 3.2 Compressive Coding for CNNs 43 -- 3.3 Lossy Compression for CNNs 43 -- 3.4 Lossless Compression for CNNs 44 -- 3.5 Recent Advancements in Compressive Coding for CNNs 48 -- 3.6 Chapter Summary 50 -- 4 Lossless Input Feature Map Compression 51 -- 4.1 Two-Step Input Feature Map Compression Technique 52 -- 4.2 Evaluation 55 -- 4.3 Chapter Summary 57 -- 5 Arithmetic Coding and Decoding for 5-Bit CNN Weights 59 -- 5.1 Architecture and Design Overview 60 -- 5.2 Algorithm Overview 63 -- 5.3 Weight Decoding Algorithm 67 -- 5.4 Encoding and Decoding Examples 69 -- 5.5 Evaluation Methodology 74 -- 5.6 Evaluation Results 75 -- 5.7 Chapter Summary 84 -- Part III Dense CNN Accelerators 85 -- 6 Contemporary Dense CNN Accelerators 87 -- 6.1 Background on Dense CNN Accelerators 87 -- 6.2 Representation of the CNNWeights and Feature Maps in Dense Format 87 -- 6.3 Popular Architectures for Dense CNN Accelerators 89 -- 6.4 Recent Advancements in Dense CNN Accelerators 92 -- 6.5 Chapter Summary 93 -- 7 iMAC: Image-to-Column and General Matrix Multiplication-Based Dense CNN Accelerator 95 -- 7.1 Background and Motivation 95 -- 7.2 Architecture 97 -- 7.3 Implementation 99 -- 7.4 Chapter Summary 100 -- 8 NeuroMAX: A Dense CNN Accelerator 101 -- 8.1 RelatedWork 102 -- 8.2 Log Mapping 103 -- 8.3 Hardware Architecture 105 -- 8.4 Data Flow and Processing 108 -- 8.5 Implementation and Results 118 -- 8.6 Chapter Summary 124 -- Part IV Sparse CNN Accelerators 125 -- 9 Contemporary Sparse CNN Accelerators 127 -- 9.1 Background of Sparsity in CNN Models 127 -- 9.2 Background of Sparse CNN Accelerators 128 -- 9.3 Recent Advancements in Sparse CNN Accelerators 131 -- 9.4 Chapter Summary 133 -- 10 CNN Accelerator for In Situ Decompression and Convolution of Sparse Input Feature Maps 135 -- 10.1 Overview 135 -- 10.2 Hardware Design Overview 135 -- 10.3 Design Optimization Techniques Utilized in the Hardware Accelerator 140 -- 10.4 FPGA Implementation 141 -- 10.5 Evaluation Results 143 -- 10.6 Chapter Summary 149 -- 11 Sparse-PE: A Sparse CNN Accelerator 151 -- 11.1 RelatedWork 155 -- 11.2 Sparse-PE 156 -- 11.3 Implementation and Results 174 -- 11.4 Chapter Summary 184 -- 12 Phantom: A High-Performance Computational Core for Sparse CNNs 185 -- 12.1 RelatedWork 189 -- 12.2 Phantom 190 -- 12.3 Phantom-2D 201 -- 12.4 Experiments and Results 209 -- 12.5 Chapter Summary 218 -- Part V HW/SW Co-Design and Co-Scheduling for CNN Acceleration 221 -- 13 State-of-the-Art in HW/SW Co-Design and Co-Scheduling for CNN Acceleration 223 -- 13.1 HW/SW Co-Design 223 -- 13.2 HW/SW Co-Scheduling 228 -- 13.3 Chapter Summary 230 -- 14 Hardware/Software Co-Design for CNN Acceleration 231 -- 14.1 Background of iMAC Accelerator 231 -- 14.2 Software Partition for iMAC Accelerator 232 -- 14.3 Experimental Evaluations 235 -- 14.4 Chapter Summary 237 -- 15 CPU-Accelerator Co-Scheduling for CNN Acceleration 239 -- 15.1 Background and Preliminaries 240 -- 15.2 CNN Acceleration with CPU-Accelerator Co-Scheduling 242 -- 15.3 Experimental Results 251 -- 15.4 Chapter Summary 257 -- 16 Conclusions 259 -- References 265 -- Index 285.
588 ## - SOURCE OF DESCRIPTION NOTE
Source of description note Description based on online resource; title from digital title page (viewed on October 25, 2023).
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Neural networks (Computer science)
655 #4 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Electronic books.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Kong, Joonho,
Relator term author.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Qureshi, Mahmood Azhar,
Relator term author.
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Print version:
International Standard Book Number 1394171889
-- 9781394171880
Record control number (OCoLC)1368339666
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://onlinelibrary.wiley.com/book/10.1002/9781394171910
Link text Full text is available at Wiley Online Library. Click here to view.
901 ## - LOCAL DATA ELEMENT A, LDA (RLIN)
a YBPebook
942 ## - ADDED ENTRY ELEMENTS
Source of classification or shelving scheme
Item type EBOOK
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Use restrictions Not for loan Permanent Location Current Location Date acquired Full call number Date last seen Price effective from Item type
        In Process   COLLEGE LIBRARY COLLEGE LIBRARY 2026-07-10 006.3/2 2026-07-10 2026-07-10 EBOOK

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