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Domain-Specific Computer Architectures for Emerging Applications: Machine Learning and Neural Networks

By (author) Chao Wang

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normal price: R 4 979.95

Price: R 4 730.95


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With the end of Moore’s Law, domain-specific architecture (DSA) has become a crucial mode of implementing future computing architectures. This book discusses the system-level design methodology of DSAs and their applications, providing a unified design process that guarantees functionality, performance, energy efficiency, and real-time responsiveness for the target application. DSAs often start from domain-specific algorithms or applications, analyzing the characteristics of algorithmic applications, such as computation, memory access, and communication, and proposing the heterogeneous accelerator architecture suitable for that particular application. This book places particular focus on accelerator hardware platforms and distributed systems for various novel applications, such as machine learning, data mining, neural networks, and graph algorithms, and also covers RISC-V open-source instruction sets. It briefly describes the system design methodology based on DSAs and presents the latest research results in academia around domain-specific acceleration architectures. Providing cutting-edge discussion of big data and artificial intelligence scenarios in contemporary industry and typical DSA applications, this book appeals to industry professionals as well as academicians researching the future of computing in these areas.

| product details |



Normally shipped | This title will be printed on demand for your order. Delivery will be 6 weeks or less.
Publisher | Taylor & Francis Ltd
Published date | 4 Jun 2024
Language |
Format | Hardback
Pages | 402
Dimensions | 234 x 156 x 0mm (L x W x H)
Weight | 929g
ISBN | 978-0-3673-7453-2
Readership Age |
BISAC | computers / neural networks


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Normally shipped | Available from overseas. Usually dispatched in 14 days
Readership Age |
Normal Price | R 5 771.95
Price | R 5 483.95 | on special |



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