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AI-Processor Electronics: Basic technology of artificial intelligence(IOP ebooks)

AI-Processor Electronics: Basic technology of artificial intelligence(IOP ebooks)


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About the Book

The revolutionary impact of advances in artificial intelligence on consumer and industrial electronics has significantly increased the demand for specialized processing units for AI workloads. AI-Processor Electronics: Basic Technology of Artificial Intelligence explores the principles and technology behind these processors, which perform fast, energy-efficient data processing and complex computations. The book begins with an overview of AI, machine learning, and deep learning, and a brief introduction to digital computer electronics. It highlights the limitations of traditional CPUs in modern AI, discussing parallel computing and AI-optimized hardware that are specially tailored and adapted to meet AI requirements. The book then covers various AI processors, including graphical, tensor, neural, convolutional neural network, vision, sparse neural network, graph analytics, associative memory, and quantum processing units. Key features: Provides a review of the physics of operation of a diverse variety of representative AI processors, and the key concepts and innovations underlying their development Covers the underlying principles, technologies, opportunities and future prospects Highlights the inadequacies of general-purpose processors in meeting the computationally intensive needs of artificial intelligence workloads Elucidates the use of parallel processing architecture in simultaneously performing multiple calculations across data streams Explores the concepts of neuromorphic and quantum computing to address the growing demands of big data in AI

Table of Contents:
Chapter 1: Artificial intelligence, machine learning, deep learning and generative artificial intelligence Chapter 2: Computing electronics fundamentals Chapter 3: Central processing unit and the von Neumann bottleneck Chapter 4: Parallel computing architecture Chapter 5: Optimised AI-computing within physical limites of transitors Chapter 6: Graphical processing unit Chapter 7: Tensor processing unit Chapter 8: Neural processing unit Chapter 9: Convolution neural network processor, and the vision processing unit Chapter 10: Conpressed and sparse neural network processors Chapter 11: Graph analytics processor for graph algorithm computations Chapter 12: Associative processing unit Chapter 13: Quantum computing principles and devices Chapter 14: Quantum logic gates and circuits Chapter 15: Quantum processing unit

About the Author :
Vinod Kumar Khanna, Ph.D. (Physics), is an independent researcher at Chandigarh, India; a former emeritus scientist, Council of Scientific and Industrial Research (CSIR), India, and Emeritus Professor, Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India; a retired chief scientist, CSIR-Central Electronics Engineering Research Institute, Pilani, India and professor, AcSIR, India. He has worked for more than 37 years on the design, fabrication, and characterization of power semiconductor devices, MEMS, and nanotechnology-based sensors. He has published 194 research papers in refereed journals and conference proceedings, 21 books, and 6 chapters in edited books. He has five patents to his credit, two US and three Indian.


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Product Details
  • ISBN-13: 9780750362597
  • Publisher: Institute of Physics Publishing
  • Publisher Imprint: Institute of Physics Publishing
  • Language: English
  • Sub Title: Basic technology of artificial intelligence
  • ISBN-10: 0750362596
  • Publisher Date: 29 Jan 2025
  • Binding: Digital (delivered electronically)
  • Series Title: IOP ebooks


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