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Advances in Computers, Volume 122

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Volume 122, 2021

Hardware Accelerator Systems for Artificial Intelligence and Machine Learning

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Shiho Kim, Ganesh Chandra Deka:
Preface. xi-xii
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Neha Gupta:
Chapter One - Introduction to hardware accelerator systems for artificial intelligence and machine learning. 1-21
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William J. Song:
Chapter Two - Hardware accelerator systems for embedded systems. 23-49
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Hyunbin Park, Shiho Kim:
Chapter Three - Hardware accelerator systems for artificial intelligence and machine learning. 51-95
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Parth Bir:
Chapter Four - Generic quantum hardware accelerators for conventional systems. 97-133
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Joo-Young Kim:
Chapter Five - FPGA based neural network accelerators. 135-165
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Won Jeon, Gun Ko, Jiwon Lee, Hyunwuk Lee, Dongho Ha, Won Woo Ro:
Chapter Six - Deep learning with GPUs. 167-215
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Kyuho Jason Lee:
Chapter Seven - Architecture of neural processing unit for deep neural networks. 217-245
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Francesco Daghero, Daniele Jahier Pagliari, Massimo Poncino:
Chapter Eight - Energy-efficient deep learning inference on edge devices. 247-301
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Yuri G. Gordienko, Yuriy Kochura, Vlad Taran, Nikita Gordienko, Oleksandr Rokovyi, Oleg Alienin, Sergii G. Stirenko:
Chapter Nine - "Last mile" optimization of edge computing ecosystem with deep learning models and specialized tensor processing architectures. 303-341
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Hyunbin Park, Shiho Kim:
Chapter Ten - Hardware accelerator for training with integer backpropagation and probabilistic weight update. 343-365
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Amitabh Biswal, Malaya Dutta Borah, Zakir Hussain:
Chapter Eleven - Music recommender system using restricted Boltzmann machine with implicit feedback. 367-402

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