图形处理单元的多精度BLAS库

K. Isupov, V. Knyazkov
{"title":"图形处理单元的多精度BLAS库","authors":"K. Isupov, V. Knyazkov","doi":"10.36227/techrxiv.12580301.v1","DOIUrl":null,"url":null,"abstract":"The binary32 and binary64 floating-point formats provide good performance on current hardware, but also introduce a rounding error in almost every arithmetic operation. Consequently, the accumulation of rounding errors in large computations can cause accuracy issues. One way to prevent these issues is to use multiple-precision floating-point arithmetic. This preprint, submitted to Russian Supercomputing Days 2020, presents a new library of basic linear algebra operations with multiple precision for graphics processing units. The library is written in CUDA C/C++ and uses the residue number system to represent multiple-precision significands of floating-point numbers. The supported data types, memory layout, and main features of the library are considered. Experimental results are presented showing the performance of the library.","PeriodicalId":221771,"journal":{"name":"Russian Supercomputing Days","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Multiple-Precision BLAS Library for Graphics Processing Units\",\"authors\":\"K. Isupov, V. Knyazkov\",\"doi\":\"10.36227/techrxiv.12580301.v1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The binary32 and binary64 floating-point formats provide good performance on current hardware, but also introduce a rounding error in almost every arithmetic operation. Consequently, the accumulation of rounding errors in large computations can cause accuracy issues. One way to prevent these issues is to use multiple-precision floating-point arithmetic. This preprint, submitted to Russian Supercomputing Days 2020, presents a new library of basic linear algebra operations with multiple precision for graphics processing units. The library is written in CUDA C/C++ and uses the residue number system to represent multiple-precision significands of floating-point numbers. The supported data types, memory layout, and main features of the library are considered. Experimental results are presented showing the performance of the library.\",\"PeriodicalId\":221771,\"journal\":{\"name\":\"Russian Supercomputing Days\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Russian Supercomputing Days\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.36227/techrxiv.12580301.v1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Russian Supercomputing Days","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36227/techrxiv.12580301.v1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

摘要

binary32和binary64浮点格式在当前硬件上提供了良好的性能,但也在几乎每个算术运算中引入了舍入误差。因此,在大型计算中,舍入误差的累积可能导致准确性问题。防止这些问题的一种方法是使用多精度浮点运算。这份预印本提交给2020年俄罗斯超级计算日,展示了一个新的基本线性代数运算库,用于图形处理单元,具有多种精度。该库是用CUDA C/ c++编写的,并使用剩余数系统来表示浮点数的多精度有效位数。考虑了支持的数据类型、内存布局和库的主要特性。实验结果显示了该库的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Multiple-Precision BLAS Library for Graphics Processing Units
The binary32 and binary64 floating-point formats provide good performance on current hardware, but also introduce a rounding error in almost every arithmetic operation. Consequently, the accumulation of rounding errors in large computations can cause accuracy issues. One way to prevent these issues is to use multiple-precision floating-point arithmetic. This preprint, submitted to Russian Supercomputing Days 2020, presents a new library of basic linear algebra operations with multiple precision for graphics processing units. The library is written in CUDA C/C++ and uses the residue number system to represent multiple-precision significands of floating-point numbers. The supported data types, memory layout, and main features of the library are considered. Experimental results are presented showing the performance of the library.
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
期刊最新文献
A Visual-Based Approach for Evaluating Global Optimization Methods Multiple-Precision BLAS Library for Graphics Processing Units Towards High Performance Relativistic Electronic Structure Modelling: The EXP-T Program Package Solving Inverse Problems of Ultrasound Tomography in a Nondestructive Testing on a Supercomputer Use of a Desktop Grid to Effectively Discover Hits in Virtual Drug Screening
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1