VALib and SimpleVector: tools for rapid initial research on vector architectures

Milan Stanic, Oscar Palomar, Ivan Ratković, M. Duric, O. Unsal, A. Cristal
{"title":"VALib and SimpleVector: tools for rapid initial research on vector architectures","authors":"Milan Stanic, Oscar Palomar, Ivan Ratković, M. Duric, O. Unsal, A. Cristal","doi":"10.1145/2597917.2597919","DOIUrl":null,"url":null,"abstract":"Vector architectures have been traditionally applied to the supercomputing domain with many successful incarnations. The energy efficiency and high performance of vector processors, as well as their applicability in other emerging domains, encourage pursuing further research on vector architectures. However, there is a lack of appropriate tools to perform this research. This paper presents two tools for measuring and analyzing an application's suitability for vector microarchitectures. The first tool is VALib, a library that enables hand-crafted vectorization of applications and its main purpose is to collect data for detailed instruction level characterization and to generate input traces for the second tool. The second tool is SimpleVector, a fast trace-driven simulator that is used to estimate the execution time of a vectorized application on a candidate vector microarchitecture. The potential of the tools is demonstrated using six applications from emerging application domains such as speech and face recognition, video encoding, bioinformatics, machine learning and graph search. The results indicate that 63.2% to 91.1% of these contemporary applications are vectorizable. Then, over multiple use cases, we demonstrate that the tools can facilitate rapid evaluation of various vector architecture designs.","PeriodicalId":194910,"journal":{"name":"Proceedings of the 11th ACM Conference on Computing Frontiers","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 11th ACM Conference on Computing Frontiers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2597917.2597919","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

Vector architectures have been traditionally applied to the supercomputing domain with many successful incarnations. The energy efficiency and high performance of vector processors, as well as their applicability in other emerging domains, encourage pursuing further research on vector architectures. However, there is a lack of appropriate tools to perform this research. This paper presents two tools for measuring and analyzing an application's suitability for vector microarchitectures. The first tool is VALib, a library that enables hand-crafted vectorization of applications and its main purpose is to collect data for detailed instruction level characterization and to generate input traces for the second tool. The second tool is SimpleVector, a fast trace-driven simulator that is used to estimate the execution time of a vectorized application on a candidate vector microarchitecture. The potential of the tools is demonstrated using six applications from emerging application domains such as speech and face recognition, video encoding, bioinformatics, machine learning and graph search. The results indicate that 63.2% to 91.1% of these contemporary applications are vectorizable. Then, over multiple use cases, we demonstrate that the tools can facilitate rapid evaluation of various vector architecture designs.
VALib和SimpleVector:用于矢量架构快速初始研究的工具
矢量架构传统上已经被应用到超级计算领域,有许多成功的实例。矢量处理器的能效和高性能,以及它们在其他新兴领域的适用性,鼓励了对矢量架构的进一步研究。然而,缺乏适当的工具来进行这项研究。本文介绍了两种工具,用于测量和分析应用程序对矢量微架构的适用性。第一个工具是VALib,它是一个支持手工向量化应用程序的库,它的主要目的是为详细的指令级表征收集数据,并为第二个工具生成输入跟踪。第二个工具是SimpleVector,这是一个快速跟踪驱动的模拟器,用于估计矢量化应用程序在候选矢量微体系结构上的执行时间。这些工具的潜力通过六个新兴应用领域的应用来展示,如语音和人脸识别、视频编码、生物信息学、机器学习和图形搜索。结果表明,这些当代应用中有63.2%至91.1%是可向量化的。然后,通过多个用例,我们证明了这些工具可以促进各种向量架构设计的快速评估。
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:604180095
Book学术官方微信