Artificial Intelligence Hardware Design: Challenges and Solutions

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(as of Aug 09, 2026 01:25:35 UTC – Details)

ARTIFICIAL INTELLIGENCE HARDWARE DESIGN

Learn foundational and advanced topics in Neural Processing Unit design with real-world examples from leading voices in the field

In Artificial Intelligence Hardware Design: Challenges and Solutions, distinguished researchers and authors Drs. Albert Chun Chen Liu and Oscar Ming Kin Law deliver a rigorous and practical treatment of the design applications of specific circuits and systems for accelerating neural network processing. Beginning with a discussion and explanation of neural networks and their developmental history, the book goes on to describe parallel architectures, streaming graphs for massive parallel computation, and convolution optimization.

The authors offer readers an illustration of in-memory computation through Georgia Tech’s Neurocube and Stanford’s Tetris accelerator using the Hybrid Memory Cube, as well as near-memory architecture through the embedded eDRAM of the Institute of Computing Technology, the Chinese Academy of Science, and other institutions.

Readers will also find a discussion of 3D neural processing techniques to support multiple layer neural networks, as well as information like:

A thorough introduction to neural networks and neural network development history, as well as Convolutional Neural Network (CNN) modelsExplorations of various parallel architectures, including the Intel CPU, Nvidia GPU, Google TPU, and Microsoft NPU, emphasizing hardware and software integration for performance improvementDiscussions of streaming graph for massive parallel computation with the Blaize GSP and Graphcore IPUAn examination of how to optimize convolution with UCLA Deep Convolutional Neural Network accelerator filter decomposition

Perfect for hardware and software engineers and firmware developers, Artificial Intelligence Hardware Design is an indispensable resource for anyone working with Neural Processing Units in either a hardware or software capacity.

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Programming & Neural Networks

Programming & Neural Networks

Programming & Neural Networks

Programming & Neural Networks

Programming & Neural Networks

Programming & Neural Networks

Programming & Neural Networks

Publisher ‏ : ‎ Wiley-IEEE Press
Publication date ‏ : ‎ August 31, 2021
Edition ‏ : ‎ 1st
Language ‏ : ‎ English
Print length ‏ : ‎ 240 pages
ISBN-10 ‏ : ‎ 1119810450
ISBN-13 ‏ : ‎ 978-1119810452
Item Weight ‏ : ‎ 14.1 ounces
Dimensions ‏ : ‎ 6.24 x 0.73 x 9.24 inches
Best Sellers Rank: #2,129,437 in Books (See Top 100 in Books) #64 in Memory Management Algorithms #910 in Computer Neural Networks #17,498 in Computer Science (Books)
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