检索结果-南通市图书馆

A Survey of Accelerator architectures for Deep Neural Networks

Engineering 2020年第3期6卷 264-274页

作者： Yiran Chen Yuan Xie Linghao Song Fan Chen Tianqi Tang Department of Electrical and Computer Engineering Duke UniversityDurhamNC 27708USA Department of Electrical and Computer Engineering University of CaliforniaSanta BarbaraCA 93106-9560USA

Recently,due to the availability of big data and the rapid growth of computing power,artificial intelligence(AI)has regained tremendous attention and *** learning(ML)approaches have been successfully applied to solve many problems in academia and in *** the explosion of big data applications is driving the development of ML,it also imposes severe challenges of data processing speed and scalability on conventional computer *** platforms that are dedicatedly designed for AI applications have been considered,ranging from a complement to von Neumann platforms to a“must-have”and stand-alone technical *** platforms,which belong to a larger category named“domain-specific computing,”focus on specific customization for *** this article,we focus on summarizing the recent advances in accelerator designs for deep neural networks(DNNs)-that is,DNN *** discuss various architectures that support DNN executions in terms of computing units,dataflow optimization,targeted network topologies,architectures on emerging technologies,and accelerators for emerging *** also provide our visions on the future trend of AI chip designs.

关键词： Deep neural network domain-specific architecture Accelerator

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

A Survey on Graph Neural Network Acceleration: A Hardware Perspective

引用

Chinese Journal of Electronics 2024年第3期33卷 601-622页

作者： Shi CHEN Jingyu LIU Li SHEN School of Computer National University of Defense Technology Key Laboratory of Advanced Microprocessor Chips and Systems

Graph neural networks(GNNs) have emerged as powerful approaches to learn knowledge about graphs and *** rapid employment of GNNs poses requirements for processing *** to incompatibility of general platforms,dedicated hardware devices and platforms are developed to efficiently accelerate training and inference of *** conduct a survey on hardware acceleration for *** first include and introduce recent advances of the domain,and then provide a methodology of categorization to classify existing works into three ***,we discuss optimization techniques adopted at different *** finally we propose suggestions on future directions to facilitate further works.

关键词： Graph neural networks Deep learning acceleration domain-specific architecture Hardware accelerator

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：