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Ascend AI Processor Architecture and Programming: Principles and Applications of CANN offers in-depth AI applications using Huawei’s Ascend chip, presenting and analyzing the unique performance and attributes of this processor. The title introduces the fundamental theory of AI, the software and hardware architecture of the Ascend AI processor, related tools and programming technology, and typical application cases. It demonstrates internal software and hardware design principles, system tools and programming techniques for the processor, laying out the elements of AI programming technology needed by researchers developing AI applications.
Chapters cover the theoretical fundamentals of AI and deep learning, the state of the industry, including the current state of Neural Network Processors, deep learning frameworks, and a deep learning compilation framework, the hardware architecture of the Ascend AI processor, programming methods and practices for developing the processor, and finally, detailed case studies on data and algorithms for AI.
- Presents the performance and attributes of the Huawei Ascend AI processor
- Describes the software and hardware architecture of the Ascend processor
- Lays out the elements of AI theory, processor architecture, and AI applications
- Provides detailed case studies on data and algorithms for AI
- Offers insights into processor architecture and programming to spark new AI applications
System designers, programmers, application developers, and system software developers; Researchers in academia and industry specializing in artificial intelligence
1 Basic Theory
1.1 Brief History of Artificial Intelligence
1.2 Introduction to Deep Learning
1.3 Neural Network Theory
2 Industry Background
2.1 Current Status of the Neural Network Chips
2.2 Neural Network Chip Acceleration Theory
2.3 Deep learning framework
2.4 Deep Learning Compilation Framework – TVM
3 Hardware Architecture
3.1 Hardware Architecture Overview
3.2 DaVinci Architecture
3.3 Convolution Acceleration Principle
4 Software Architecture
4.1 Ascend AI Software Stack Overview
4.2 Neural Network Software Flow
4.3 Development Tool Chain
5 Programming Methods
5.1 Basics of Deep Learning Development
5.2 Techniques of Ascend AI Software Stack
5.3 Customized Operator Development
6 Case Studies
6.1 Evaluation Criteria
6.2 Image Classification
6.3 Object Detection
- No. of pages:
- © Elsevier 2020
- 27th July 2020
- Paperback ISBN:
- eBook ISBN:
Liang Xiaoyao is a Professor, Supervisor and Academic Leader in the Department of Computer Science and Engineering at Shanghai Jiaotong University, in China. He graduated from Harvard University in the USA, and has held roles at a number of international companies. His research interests include computer architecture, integrated circuit design, general graphics processors, and artificial intelligence chip architecture. He has published over 80 papers, and is a leader in the field.
Professor, Supervisor and Academic Leader, Department of Computer Science and Engineering, Shanghai Jiaotong University, China
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