Hardware Accelerator Systems for Artificial Intelligence and Machine Learning: Advances in Computers, cartea 122
Shiho Kim, Ganesh Chandra Dekaen Limba Engleză Hardback – 7 apr 2021
- Updates on new information on the architecture of GPU, NPU and DNN
- Discusses In-memory computing, Machine intelligence and Quantum computing
- Includes sections on Hardware Accelerator Systems to improve processing efficiency and performance
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Specificații
ISBN-13: 9780128231234
ISBN-10: 0128231238
Pagini: 416
Dimensiuni: 152 x 229 mm
Greutate: 0.72 kg
Editura: ELSEVIER SCIENCE
Seria Advances in Computers
ISBN-10: 0128231238
Pagini: 416
Dimensiuni: 152 x 229 mm
Greutate: 0.72 kg
Editura: ELSEVIER SCIENCE
Seria Advances in Computers
Public țintă
Reference Book for Final year Undergraduate student for Project on Embedded system, Master’s and PhD ScholarsCuprins
1. Hardware accelerator systems for artificial intelligence and machine learning
Shiho 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
Shiho 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