Hardware Accelerator Systems for Artificial Intelligence and Machine Learning
- 1st Edition, Volume 122 - March 28, 2021
- Editors: Shiho Kim, Ganesh Chandra Deka
- Language: English
- Hardback ISBN:9 7 8 - 0 - 1 2 - 8 2 3 1 2 3 - 4
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 2 3 1 2 4 - 1
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 N… Read more
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Request a sales quote- 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
Final year Undergraduate student for Project on Embedded system, Master’s and PhD Scholars
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
- No. of pages: 416
- Language: English
- Edition: 1
- Volume: 122
- Published: March 28, 2021
- Imprint: Academic Press
- Hardback ISBN: 9780128231234
- eBook ISBN: 9780128231241
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Shiho Kim
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