梨:PMaC习语Recognizer

C. Olschanowsky, A. Snavely, Mitesh R. Meswani, L. Carrington
{"title":"梨:PMaC习语Recognizer","authors":"C. Olschanowsky, A. Snavely, Mitesh R. Meswani, L. Carrington","doi":"10.1109/ICPPW.2010.36","DOIUrl":null,"url":null,"abstract":"The speed of the memory subsystem often constrains the performance of large-scale parallel applications. Experts tune such applications to use hierarchical memory subsystems efficiently. Hardware accelerators, such as GPUs, can potentially improve memory performance beyond the capabilities of traditional hierarchical systems. However, the addition of such specialized hardware complicates code porting and tuning. During porting and tuning expert application engineers manually browse source code and identify memory access patterns that are candidates for optimization and tuning. HPC applications typically contain thousands to hundreds of thousands of lines of code, creating a labor-intensive challenge for the expert. PIR, PMaC’s Static Idiom Recognizer, automates the pattern recognition process. PIR recognizes specified patterns and tags the source code where they appear using static analysis. This paper describes the PIR implementation and defines a subset of idioms commonly found in HPC applications. We examine the effectiveness of the tool, demonstrating 95% identification accuracy and present the results of using PIR on two HPC applications.","PeriodicalId":415472,"journal":{"name":"2010 39th International Conference on Parallel Processing Workshops","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"PIR: PMaC's Idiom Recognizer\",\"authors\":\"C. Olschanowsky, A. Snavely, Mitesh R. Meswani, L. Carrington\",\"doi\":\"10.1109/ICPPW.2010.36\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The speed of the memory subsystem often constrains the performance of large-scale parallel applications. Experts tune such applications to use hierarchical memory subsystems efficiently. Hardware accelerators, such as GPUs, can potentially improve memory performance beyond the capabilities of traditional hierarchical systems. However, the addition of such specialized hardware complicates code porting and tuning. During porting and tuning expert application engineers manually browse source code and identify memory access patterns that are candidates for optimization and tuning. HPC applications typically contain thousands to hundreds of thousands of lines of code, creating a labor-intensive challenge for the expert. PIR, PMaC’s Static Idiom Recognizer, automates the pattern recognition process. PIR recognizes specified patterns and tags the source code where they appear using static analysis. This paper describes the PIR implementation and defines a subset of idioms commonly found in HPC applications. We examine the effectiveness of the tool, demonstrating 95% identification accuracy and present the results of using PIR on two HPC applications.\",\"PeriodicalId\":415472,\"journal\":{\"name\":\"2010 39th International Conference on Parallel Processing Workshops\",\"volume\":\"72 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 39th International Conference on Parallel Processing Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPPW.2010.36\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 39th International Conference on Parallel Processing Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPPW.2010.36","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13

摘要

内存子系统的速度经常限制大规模并行应用程序的性能。专家对这类应用程序进行调优,以便有效地使用分层内存子系统。硬件加速器(如gpu)可以潜在地提高内存性能,超出传统分层系统的能力。然而,这种专用硬件的添加使代码移植和调优变得复杂。在移植和调优期间,专家应用程序工程师手动浏览源代码,并确定需要进行优化和调优的候选内存访问模式。HPC应用程序通常包含数千到数十万行代码,这对专家来说是一项劳动密集型的挑战。PMaC的静态成语识别器PIR使模式识别过程自动化。PIR识别指定的模式,并使用静态分析标记它们出现的源代码。本文描述了PIR实现,并定义了HPC应用程序中常见的习惯用法子集。我们检验了该工具的有效性,证明了95%的识别准确率,并展示了在两个高性能计算应用中使用PIR的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PIR: PMaC's Idiom Recognizer
The speed of the memory subsystem often constrains the performance of large-scale parallel applications. Experts tune such applications to use hierarchical memory subsystems efficiently. Hardware accelerators, such as GPUs, can potentially improve memory performance beyond the capabilities of traditional hierarchical systems. However, the addition of such specialized hardware complicates code porting and tuning. During porting and tuning expert application engineers manually browse source code and identify memory access patterns that are candidates for optimization and tuning. HPC applications typically contain thousands to hundreds of thousands of lines of code, creating a labor-intensive challenge for the expert. PIR, PMaC’s Static Idiom Recognizer, automates the pattern recognition process. PIR recognizes specified patterns and tags the source code where they appear using static analysis. This paper describes the PIR implementation and defines a subset of idioms commonly found in HPC applications. We examine the effectiveness of the tool, demonstrating 95% identification accuracy and present the results of using PIR on two HPC applications.
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:604180095
Book学术官方微信