Hardware accelerator systems for artificial intelligence and machine learning /
Kim, Shiho
Hardware accelerator systems for artificial intelligence and machine learning / created by Shiho Kim and Ganesh Chandra Deka - xii, 402 pages : illustrations ; 24 cm - Advances in computers, 122 .
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
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
9780128231234
Computer Systems
Artificial Intelligence
Machine learning
QA76.9.B56 HAR
Hardware accelerator systems for artificial intelligence and machine learning / created by Shiho Kim and Ganesh Chandra Deka - xii, 402 pages : illustrations ; 24 cm - Advances in computers, 122 .
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
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
9780128231234
Computer Systems
Artificial Intelligence
Machine learning
QA76.9.B56 HAR