Artificial Intelligence Hardware Design: Challenges and Solutions

Artificial Intelligence Hardware Design: Challenges and Solutions provides a comprehensive treatment of the design applications of specific circuits and systems for accelerating neural network processing. It covers neural networks, parallel architectures, streaming graphs, convolution optimization, 3D neural processing techniques, and near-memory architecture. The book is essential for hardware and software engineers and firmware developers working with Neural Processing Units.

Format: Hardback
Length: 240 pages
Publication date: 07 September 2021
Publisher: John Wiley and Sons Ltd

Artificial Intelligence Hardware Design: Challenges and Solutions delves into the intricate realm of Neural Processing Unit (NPU) design, offering a comprehensive exploration of foundational and advanced topics. Authored by esteemed researchers Drs. Albert Chun Chen Liu and Oscar Ming Kin Law, this authoritative text provides a rigorous and practical treatment of the design applications of specific circuits and systems for accelerating neural network processing.

The book begins by providing a comprehensive discussion and explanation of neural networks, tracing their developmental history and highlighting their significance in modern computing. It then delves into parallel architectures, streaming graphs for massive parallel computation, and convolution optimization, presenting cutting-edge techniques that have the potential to revolutionize the field.

To illustrate the practical applications of these concepts, the authors offer readers a glimpse into in-memory computation through Georgia Tech's Neurocube and Stanford's Tetris accelerator using the Hybrid Memory Cube. Additionally, they explore near-memory architecture through the embedded eDRAM of institutions such as the Institute of Computing Technology, the Chinese Academy of Science, and others.

Furthermore, the book delves into 3D neural processing techniques to support multiple layer neural networks, providing valuable insights into the latest advancements in this field. It also includes a thorough introduction to neural networks and neural network development history, as well as Convolutional Neural Network (CNN) models.

This comprehensive guide is ideal for hardware and software engineers, firmware developers, and researchers seeking to deepen their understanding of NPU design and its applications in artificial intelligence. With its rigorous approach and real-world examples, Artificial Intelligence Hardware Design: Challenges and Solutions serves as a valuable resource for anyone looking to stay at the forefront of this rapidly evolving field.

Weight: 462g
Dimension: 160 x 239 x 19 (mm)
ISBN-13: 9781119810452