logo
Product categories

EbookNice.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link.  https://ebooknice.com/page/post?id=faq


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookNice Team

(Ebook) Artificial Intelligence Hardware Design: Challenges and Solutions by Albert Chun-Chen Liu, Oscar Ming Kin Law ISBN 9781119810452, 1119810450

  • SKU: EBN-34464284
Zoomable Image
$ 32 $ 40 (-20%)

Status:

Available

4.4

5 reviews
Instant download (eBook) Artificial Intelligence Hardware Design: Challenges and Solutions after payment.
Authors:Albert Chun-Chen Liu, Oscar Ming Kin Law
Pages:240 pages.
Year:2021
Editon:1
Publisher:Wiley-IEEE Press
Language:english
File Size:47.14 MB
Format:epub
ISBNS:9781119810452, 1119810450
Categories: Ebooks

Product desciption

(Ebook) Artificial Intelligence Hardware Design: Challenges and Solutions by Albert Chun-Chen Liu, Oscar Ming Kin Law ISBN 9781119810452, 1119810450

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) models
  • Explorations of various parallel architectures, including the Intel CPU, Nvidia GPU, Google TPU, and Microsoft NPU, emphasizing hardware and software integration for performance improvement
  • Discussions of streaming graph for massive parallel computation with the Blaize GSP and Graphcore IPU
  • An 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.

*Free conversion of into popular formats such as PDF, DOCX, DOC, AZW, EPUB, and MOBI after payment.

Related Products