在线咨询
eetop公众号 创芯大讲堂 创芯人才网
切换到宽版

EETOP 创芯网论坛 (原名:电子顶级开发网)

手机号码,快捷登录

手机号码,快捷登录

找回密码

  登录   注册  

快捷导航
搜帖子
查看: 6109|回复: 47

[求助] 求Artificial Intelligence Hardware Design: Challenges and Solutions一书

[复制链接]
发表于 2021-12-2 17:42:53 | 显示全部楼层 |阅读模式

马上注册,结交更多好友,享用更多功能,让你轻松玩转社区。

您需要 登录 才可以下载或查看,没有账号?注册

x
9536220.jpg
Artificial Intelligence Hardware Design: Challenges and Solutions

[size=0.87][url=]Albert Chun-Chen Liu[/url]; [url=]Oscar Ming Kin Law[/url]










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.





发表于 2021-12-9 10:17:08 | 显示全部楼层
attached to find the file you expected

Artificial Intelligence Hardware Design Challenges and Solutions .pdf

17.19 MB, 下载次数: 277 , 下载积分: 资产 -6 信元, 下载支出 6 信元

 楼主| 发表于 2021-12-10 10:18:32 | 显示全部楼层
谢谢分享,太感谢了!
发表于 2021-12-16 10:50:55 | 显示全部楼层
Thank you for sharing.
发表于 2021-12-27 14:32:43 | 显示全部楼层
good material, thanks for sharing
发表于 2021-12-27 14:48:17 | 显示全部楼层
谢谢分享,太感谢了!
发表于 2022-4-15 18:38:24 | 显示全部楼层
好资料谢谢分享
发表于 2022-6-8 11:18:32 | 显示全部楼层
thanks
发表于 2022-7-17 22:00:07 | 显示全部楼层
为了留个记号
发表于 2022-7-18 07:38:56 | 显示全部楼层
谢谢分享
您需要登录后才可以回帖 登录 | 注册

本版积分规则

关闭

站长推荐 上一条 /2 下一条


小黑屋| 手机版| 关于我们| 联系我们| 在线咨询| 隐私声明| EETOP 创芯网
( 京ICP备:10050787号 京公网安备:11010502037710 )

GMT+8, 2024-12-22 09:11 , Processed in 0.022189 second(s), 8 queries , Gzip On, Redis On.

eetop公众号 创芯大讲堂 创芯人才网
快速回复 返回顶部 返回列表