Performance modeling for GPUs using abstract kernel emulation

Changwan Hong, Aravind Sukumaran-Rajam, Jinsung Kim, P. Rawat, S. Krishnamoorthy, L. Pouchet, F. Rastello, P. Sadayappan
{"title":"Performance modeling for GPUs using abstract kernel emulation","authors":"Changwan Hong, Aravind Sukumaran-Rajam, Jinsung Kim, P. Rawat, S. Krishnamoorthy, L. Pouchet, F. Rastello, P. Sadayappan","doi":"10.1145/3178487.3178524","DOIUrl":null,"url":null,"abstract":"Performance modeling of GPU kernels is a significant challenge. In this paper, we develop a novel approach to performance modeling for GPUs through abstract kernel emulation along with latency/gap modeling of resources. Experimental results on all benchmarks from the Rodinia suite demonstrate good accuracy in predicting execution time on multiple GPU platforms.","PeriodicalId":193776,"journal":{"name":"Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3178487.3178524","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Performance modeling of GPU kernels is a significant challenge. In this paper, we develop a novel approach to performance modeling for GPUs through abstract kernel emulation along with latency/gap modeling of resources. Experimental results on all benchmarks from the Rodinia suite demonstrate good accuracy in predicting execution time on multiple GPU platforms.
使用抽象内核仿真的gpu性能建模
GPU内核的性能建模是一个重大的挑战。在本文中,我们通过抽象内核仿真以及资源的延迟/间隙建模开发了一种新的gpu性能建模方法。在Rodinia套件的所有基准测试上的实验结果表明,在多个GPU平台上预测执行时间具有良好的准确性。
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