Ascend AI Processor Architecture and Programming: Principles and Applications of CANN
Language: English
Published by Elsevier, 2020
- Softcover
- New

Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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In English.
Seller Inventory # ria9780128234884_new
- Title
- Ascend AI Processor Architecture and Programming: Principles and Applications of CANN
- Author
- Liang, Xiaoyao
- Publisher
- Elsevier
- Publication year
- 2020
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 0128234881
- ISBN 13
- 9780128234884
- Item weight
- 750 grams
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
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Ria Christie Collections
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