Arithmetic for digital neural networks

Dapeng Zhang, G. Jullien, W. Miller, E. Swartzlander
{"title":"Arithmetic for digital neural networks","authors":"Dapeng Zhang, G. Jullien, W. Miller, E. Swartzlander","doi":"10.1109/ARITH.1991.145534","DOIUrl":null,"url":null,"abstract":"The implementation of large input digital neurons using designs based on parallel counters is described. The implementation of the design uses a two-cell library, in which each cell is implemented using switching trees which are pipelined binary trees of n-channel transistors. Results obtained from initial switching trees realized with a 3- mu m CMOS process indicate that the design is capable of being pipelined at 40 MHz sample rates, with better performance expected for more advanced technologies. It appears feasible to develop a wafer-scale implementation with 2000 neurons (each with 1000 inputs) that would perform 3*10/sup 12/ additions/s.<<ETX>>","PeriodicalId":190650,"journal":{"name":"[1991] Proceedings 10th IEEE Symposium on Computer Arithmetic","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1991] Proceedings 10th IEEE Symposium on Computer Arithmetic","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ARITH.1991.145534","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 23

Abstract

The implementation of large input digital neurons using designs based on parallel counters is described. The implementation of the design uses a two-cell library, in which each cell is implemented using switching trees which are pipelined binary trees of n-channel transistors. Results obtained from initial switching trees realized with a 3- mu m CMOS process indicate that the design is capable of being pipelined at 40 MHz sample rates, with better performance expected for more advanced technologies. It appears feasible to develop a wafer-scale implementation with 2000 neurons (each with 1000 inputs) that would perform 3*10/sup 12/ additions/s.<>
数字神经网络的算法
描述了基于并行计数器设计的大输入数字神经元的实现。该设计的实现使用一个双单元库,其中每个单元都使用n通道晶体管的流水线二叉树开关树来实现。用3 μ m CMOS工艺实现的初始开关树的结果表明,该设计能够在40 MHz采样率下流水线化,并有望在更先进的技术中具有更好的性能。开发具有2000个神经元(每个神经元有1000个输入)的晶圆级实现似乎是可行的,该实现将执行3*10/sup / 12/ add /s。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信