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AI Computing Systems,
Edition 1
An Application Driven Perspective
By Yunji Chen, Ling Li, Wei Li, Qi Guo, Zidong Du and Zichen Xu
Publication Date:
18 Jan 2023
Description
AI Computing Systems: An Application Driven Perspective adopts the principle of "application-driven, full-stack penetration" and uses the specific intelligent application of "image style migration" to provide students with a sound starting place to learn. This approach enables readers to obtain a full view of the AI computing system. A complete intelligent computing system involves many aspects such as processing chip, system structure, programming environment, software, etc., making it a difficult topic to master in a short time.
Key Features
- Provides an in-depth analysis of the underlying principles behind the use of knowledge in intelligent computing systems
- Centers around application-driven and full-stack penetration, focusing on the knowledge required to complete this application at all levels of the software and hardware technology stack
- Supporting experimental tutorials covering key knowledge points in each chapter provide practical guidance and formalization tools for developing a simple AI computing system
About the author
By Yunji Chen, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China; Ling Li, Institute of Software, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China; Wei Li, State Key Lab of Processors, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China; Qi Guo, State Key Lab of Processors, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China; Zidong Du, State Key Lab of Processors, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China and Zichen Xu, School of Mathematics and Computer Science, The Nanchang University, Nanchang, China
Table of Contents
1. Introduction
2. Neural Networks
3. Deep Learning
4. Fundamentals of Learning Frameworks
5. Learning Framework Principles
6. Theory behind Deep Learning Processors
7. Architecture for AI Computing Systems
8. AI Programming Language for AI Computing Systems
9. AI Computing Systems Labs
2. Neural Networks
3. Deep Learning
4. Fundamentals of Learning Frameworks
5. Learning Framework Principles
6. Theory behind Deep Learning Processors
7. Architecture for AI Computing Systems
8. AI Programming Language for AI Computing Systems
9. AI Computing Systems Labs
Book details
ISBN:
9780323953993
Page Count: 600
Retail Price
:
£76.95
9780134610993; 9781558601918; 9780262039246
Instructor Resources
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Audience
Graduate level students taking advanced artificial intelligence courses within computer science and computer engineering; AI researchers
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The book is excellent to beginners and engineering students, I strongly recommend this for the budding AI Engineers