分析GPU架构中内存引用的局部性

Saurabh Gupta, Ping Xiang, Huiyang Zhou
{"title":"分析GPU架构中内存引用的局部性","authors":"Saurabh Gupta, Ping Xiang, Huiyang Zhou","doi":"10.1145/2492408.2492423","DOIUrl":null,"url":null,"abstract":"In this paper we advocate formal locality analysis on memory references of GPGPU kernels. We investigate the locality of reference at different cache levels in the memory hierarchy. At the L1 cache level, we look into the locality behavior at the warp-, the thread block- and the streaming multiprocessor-level. Using matrix multiplication as a case study, we show that our locality analysis accurately captures some interesting and counter-intuitive behavior of the memory accesses. We believe that such analysis will provide very useful insights in understanding the memory accessing behavior and optimizing the memory hierarchy in GPU architectures.","PeriodicalId":130040,"journal":{"name":"Workshop on Memory System Performance and Correctness","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Analyzing locality of memory references in GPU architectures\",\"authors\":\"Saurabh Gupta, Ping Xiang, Huiyang Zhou\",\"doi\":\"10.1145/2492408.2492423\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we advocate formal locality analysis on memory references of GPGPU kernels. We investigate the locality of reference at different cache levels in the memory hierarchy. At the L1 cache level, we look into the locality behavior at the warp-, the thread block- and the streaming multiprocessor-level. Using matrix multiplication as a case study, we show that our locality analysis accurately captures some interesting and counter-intuitive behavior of the memory accesses. We believe that such analysis will provide very useful insights in understanding the memory accessing behavior and optimizing the memory hierarchy in GPU architectures.\",\"PeriodicalId\":130040,\"journal\":{\"name\":\"Workshop on Memory System Performance and Correctness\",\"volume\":\"76 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Workshop on Memory System Performance and Correctness\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2492408.2492423\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Workshop on Memory System Performance and Correctness","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2492408.2492423","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

摘要

本文提倡对GPGPU内核的内存引用进行形式化局部性分析。我们研究了在内存层次结构中不同缓存级别上引用的局部性。在L1缓存级别,我们研究了warp、线程块和流多处理器级别的局部性行为。使用矩阵乘法作为案例研究,我们表明我们的局部性分析准确地捕获了内存访问的一些有趣的和反直觉的行为。我们相信这样的分析将为理解内存访问行为和优化GPU架构中的内存层次结构提供非常有用的见解。
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
Analyzing locality of memory references in GPU architectures
In this paper we advocate formal locality analysis on memory references of GPGPU kernels. We investigate the locality of reference at different cache levels in the memory hierarchy. At the L1 cache level, we look into the locality behavior at the warp-, the thread block- and the streaming multiprocessor-level. Using matrix multiplication as a case study, we show that our locality analysis accurately captures some interesting and counter-intuitive behavior of the memory accesses. We believe that such analysis will provide very useful insights in understanding the memory accessing behavior and optimizing the memory hierarchy in GPU architectures.
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
All-window data liveness Cache rationing for multicore Software-controlled transparent management of heterogeneous memory resources in virtualized systems Program-centric cost models for locality A study of data structures with a deep heap shape
×
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