Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into arti?cial 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.
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Table of Contents
1. Hardware accelerator systems for artificial intelligence and machine learningShiho Kim
2. Introduction to Hardware Accelerator Systems for Artificial Intelligence and Machine Learning
Neha Gupta
3. Deep Learning with GPUs
Won Woo Ro
4. Edge Computing Optimization of Deep Learning Models for Specialized Tensor Processing Architectures-Yuri Gordienko
Yuri Gordienko
5. Architecture of NPU for DNN
Kyuho Lee
6. Hardware Architecture for Convolutional Neural Network for Image Processing
Vardhana M
7. FPGA based Neural Network Accelerators
Joo-Young Kim
8. Energy-Efficient Deep Learning Inference on Edge Devices
Massimo Poncino
9. Hardware accelerator systems for Embedded systems
William Jinho Song
10. Generic Quantum Hardware Accelerators for Conventional systems
Parth Bir
11. Music recommender system using Restricted Boltzmann Machine with Implicit Feedback
Malaya Dutta Borah
12. Embedded system for Automated Monitoring in Agriculture and Healthcare
Prashanta Kumar Das
