TY  - BOOK
AU  - Kim,Shiho
AU  - Deka ,Ganesh Chandra
TI  - Hardware accelerator systems for artificial intelligence and machine learning
T2  - Advances in computers,
SN  - 9780128231234
AV  - QA76.9.B56 HAR 
PY  - 2021///
PB  - Academic Press, an imprint of Elsevier
KW  - Computer Systems
KW  - Artificial Intelligence
KW  - Machine learning
N1  - Introduction to hardware accelerator systems for artificial intelligence and machine learning / Neha Gupta Hardware accelerator systems for embedded systems / William J. Song Hardware accelerator systems for artificial intelligence and machine learning / Hyunbin Park and Shiho Kim Generic quantum hardware accelerators for conventional systems / Parth Bir FPGA based neural network accelerators / Joo-Young Kim Deep Learning with GPUs / Won Jeon, Gun Ko, Jiwon Lee, Hyunwuk Lee, Dongho Ha, and Won Woo Ro Architecture of neural processing unit for deep neural networks / Kyuho J. Lee Energy-Efficient Deep Learning Inference on Edge Devices / Francesco Daghero, Daniele Jahier Pagliari, and Massimo Poncino "Last mile" optimization of edge computing ecosystem with deep learning models and specialized tensor processing architectures / Yuri Gordienko, Yuriy Kocccchura, Vlad Taran, Nikita Gordienko, Oleksandr Rokovyi, Oleg Alienin, and Sergii Stirenko Hardware accelerator for training with integer backpropagation and probabilistic weight update / Hyunbin Park and Shiho Kim Music recommender system using restricted Boltzmann machine with implicit feedback / Amitabh Biswal, Malaya Dutta Borah, and Zakir Hussain
N2  - Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into artificial Intelligence and the growth it has seen with the advent of Deep Neural Networks (DNNs) and Machine Learning. Updates in this release include chapters on Hardware accelerator systems for artificial intelligence and machine learning, Introduction to Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Deep Learning with GPUs, Edge Computing Optimization of Deep Learning Models for Specialized Tensor Processing Architectures, Architecture of NPU for DNN, Hardware Architecture for Convolutional Neural Network for Image Processing, FPGA based Neural Network Accelerators, and much more--Publisher's description
ER  -