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Ascend AI Processor Architecture and Programming

Principles and Applications of CANN

  • 1st Edition - July 27, 2020
  • Latest edition
  • Author: Xiaoyao Liang
  • Language: English

Ascend AI Processor Architecture and Programming: Principles and Applications of CANN offers in-depth AI applications using Huawei’s Ascend chip, presenting and analyzing… Read more

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Description

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.

Key features

  • 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

Readership

System designers, programmers, application developers, and system software developers; Researchers in academia and industry specializing in artificial intelligence.

Table of contents

1 Basic Theory1.1 Brief History of Artificial Intelligence1.2 Introduction to Deep Learning1.3 Neural Network Theory

2 Industry Background2.1 Current Status of the Neural Network Chips2.2 Neural Network Chip Acceleration Theory2.3 Deep learning framework2.4 Deep Learning Compilation Framework – TVM

3 Hardware Architecture3.1 Hardware Architecture Overview3.2 DaVinci Architecture3.3 Convolution Acceleration Principle

4 Software Architecture4.1 Ascend AI Software Stack Overview4.2 Neural Network Software Flow4.3 Development Tool Chain

5 Programming Methods5.1 Basics of Deep Learning Development5.2 Techniques of Ascend AI Software Stack5.3 Customized Operator Development

6 Case Studies6.1 Evaluation Criteria6.2 Image Classification6.3 Object Detection

Product details

  • Edition: 1
  • Latest edition
  • Published: July 29, 2020
  • Language: English

About the author

XL

Xiaoyao Liang

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.
Affiliations and expertise
Professor, Supervisor and Academic Leader, Department of Computer Science and Engineering, Shanghai Jiaotong University, China

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