Fixed-point arithmetic error analysis of sparse LU decomposition on FPGAs

M. S. Feali, A. Ahmadi, A. Hamidi, M. Ahmadi
{"title":"Fixed-point arithmetic error analysis of sparse LU decomposition on FPGAs","authors":"M. S. Feali, A. Ahmadi, A. Hamidi, M. Ahmadi","doi":"10.1109/ISSCS.2017.8034900","DOIUrl":null,"url":null,"abstract":"FPGAs are becoming an attractive platform for accelerating many computations including scientific applications. These applications demand high performance and high precision arithmetic. Decomposition of a matrix into lower and upper triangular matrices (LU decomposition) is a vital part of many scientific and engineering applications. This paper evaluates the accuracy of a fixed-point LU decomposition based on FPGA. Fixed-point architecture of LU decomposition is implemented on FPGA. Then several matrices with different sizes and random elements are decomposed using this architecture by various word-lengths. Using random matrices and different word-lengths, descriptive analysis of error is performed.","PeriodicalId":338255,"journal":{"name":"2017 International Symposium on Signals, Circuits and Systems (ISSCS)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Symposium on Signals, Circuits and Systems (ISSCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSCS.2017.8034900","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

FPGAs are becoming an attractive platform for accelerating many computations including scientific applications. These applications demand high performance and high precision arithmetic. Decomposition of a matrix into lower and upper triangular matrices (LU decomposition) is a vital part of many scientific and engineering applications. This paper evaluates the accuracy of a fixed-point LU decomposition based on FPGA. Fixed-point architecture of LU decomposition is implemented on FPGA. Then several matrices with different sizes and random elements are decomposed using this architecture by various word-lengths. Using random matrices and different word-lengths, descriptive analysis of error is performed.
fpga稀疏LU分解的定点算法误差分析
fpga正在成为加速包括科学应用在内的许多计算的有吸引力的平台。这些应用需要高性能和高精度的算法。矩阵分解为上下三角矩阵(LU分解)是许多科学和工程应用的重要组成部分。本文对一种基于FPGA的定点逻辑单元分解方法的精度进行了评价。在FPGA上实现了逻辑单元分解的定点结构。然后利用该体系结构按不同的字长对不同大小和随机元素的矩阵进行分解。使用随机矩阵和不同的字长,对错误进行描述性分析。
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