阵列处理器对Winograd矩阵乘法算法的线性加速

De-Lei Lee, M. A. Aboelaze
{"title":"阵列处理器对Winograd矩阵乘法算法的线性加速","authors":"De-Lei Lee, M. A. Aboelaze","doi":"10.1109/DMCC.1991.633203","DOIUrl":null,"url":null,"abstract":"Winogradi’s matrix multiplication algorithm halves the number of multiplication operations required of the conventional 0 ( N 3 ) matrix multiplication algoirithm by slightly increasing the number of addition operations. Such it technique can be computatiorially advantageous when the machine performing the matrix computation takes much more time for multiplication over addition operations. This is overwhelmingly the case in the massively parallel computing paradigm, where each processor is extremely simple by itself and the computing power is obtained by the use of a large number of such processors. In this paper, we describe a parallel version of Winograd’s imatrix multiplication algorithm using an array processor and show how to achieve nearly linear speedup over its sequential counterpart.","PeriodicalId":313314,"journal":{"name":"The Sixth Distributed Memory Computing Conference, 1991. Proceedings","volume":"604 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Linear Speedup of Winograd's Matrix Multiplication Algorithm Using an Array Processor\",\"authors\":\"De-Lei Lee, M. A. Aboelaze\",\"doi\":\"10.1109/DMCC.1991.633203\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Winogradi’s matrix multiplication algorithm halves the number of multiplication operations required of the conventional 0 ( N 3 ) matrix multiplication algoirithm by slightly increasing the number of addition operations. Such it technique can be computatiorially advantageous when the machine performing the matrix computation takes much more time for multiplication over addition operations. This is overwhelmingly the case in the massively parallel computing paradigm, where each processor is extremely simple by itself and the computing power is obtained by the use of a large number of such processors. In this paper, we describe a parallel version of Winograd’s imatrix multiplication algorithm using an array processor and show how to achieve nearly linear speedup over its sequential counterpart.\",\"PeriodicalId\":313314,\"journal\":{\"name\":\"The Sixth Distributed Memory Computing Conference, 1991. Proceedings\",\"volume\":\"604 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Sixth Distributed Memory Computing Conference, 1991. Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DMCC.1991.633203\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Sixth Distributed Memory Computing Conference, 1991. Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DMCC.1991.633203","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

Winogradi的矩阵乘法算法通过稍微增加加法运算的次数,将传统的0 (N - 3)矩阵乘法算法所需的乘法运算次数减半。当执行矩阵计算的机器需要更多的时间进行乘法运算而不是加法运算时,这种技术在计算上是有利的。这在大规模并行计算范例中是压倒性的情况,其中每个处理器本身都非常简单,计算能力是通过使用大量这样的处理器获得的。在本文中,我们描述了使用阵列处理器的Winograd矩阵乘法算法的并行版本,并展示了如何实现比其顺序对等体接近线性的加速。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Linear Speedup of Winograd's Matrix Multiplication Algorithm Using an Array Processor
Winogradi’s matrix multiplication algorithm halves the number of multiplication operations required of the conventional 0 ( N 3 ) matrix multiplication algoirithm by slightly increasing the number of addition operations. Such it technique can be computatiorially advantageous when the machine performing the matrix computation takes much more time for multiplication over addition operations. This is overwhelmingly the case in the massively parallel computing paradigm, where each processor is extremely simple by itself and the computing power is obtained by the use of a large number of such processors. In this paper, we describe a parallel version of Winograd’s imatrix multiplication algorithm using an array processor and show how to achieve nearly linear speedup over its sequential counterpart.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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