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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… Read more
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Immediately download your ebook while waiting for your print delivery. No promo code needed.
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.
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
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