Enhancing Efficiency of Hybrid Transactional Memory Via Dynamic Data Partitioning Schemes

Pedro Raminhas, S. Issa, P. Romano
{"title":"Enhancing Efficiency of Hybrid Transactional Memory Via Dynamic Data Partitioning Schemes","authors":"Pedro Raminhas, S. Issa, P. Romano","doi":"10.1109/CCGRID.2018.00020","DOIUrl":null,"url":null,"abstract":"Transactional Memory (TM) is an emerging paradigm that promises to significantly ease the development of parallel programs. Hybrid TM (HyTM) is probably the most promising implementation of the TM abstraction, which seeks to combine the high efficiency of hardware implementations (HTM) with the robustness and flexibility of software-based ones (STM). Unfortunately, though, existing Hybrid TM systems are known to suffer from high overheads to guarantee correct synchronization between concurrent transactions executing in hardware and software. This article introduces DMP-TM (Dynamic Memory Partitioning-TM), a novel HyTM algorithm that exploits, to the best of our knowledge for the first time in the literature, the idea of leveraging operating system-level memory protection mechanisms to detect conflicts between HTM and STM transactions. This innovative design allows for employing highly scalable STM implementations, while avoiding instrumentation on the HTM path. This allows DMP-TM to achieve up to ~ 20× speedups compared to state of the art Hybrid TM solutions in uncontended workloads. Further, thanks to the use of simple and lightweight self-tuning mechanisms, DMP-TM achieves robust performance even in unfavourable workload that exhibits high contention between the STM and HTM path.","PeriodicalId":321027,"journal":{"name":"2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCGRID.2018.00020","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Transactional Memory (TM) is an emerging paradigm that promises to significantly ease the development of parallel programs. Hybrid TM (HyTM) is probably the most promising implementation of the TM abstraction, which seeks to combine the high efficiency of hardware implementations (HTM) with the robustness and flexibility of software-based ones (STM). Unfortunately, though, existing Hybrid TM systems are known to suffer from high overheads to guarantee correct synchronization between concurrent transactions executing in hardware and software. This article introduces DMP-TM (Dynamic Memory Partitioning-TM), a novel HyTM algorithm that exploits, to the best of our knowledge for the first time in the literature, the idea of leveraging operating system-level memory protection mechanisms to detect conflicts between HTM and STM transactions. This innovative design allows for employing highly scalable STM implementations, while avoiding instrumentation on the HTM path. This allows DMP-TM to achieve up to ~ 20× speedups compared to state of the art Hybrid TM solutions in uncontended workloads. Further, thanks to the use of simple and lightweight self-tuning mechanisms, DMP-TM achieves robust performance even in unfavourable workload that exhibits high contention between the STM and HTM path.
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
通过动态数据分区方案提高混合事务性内存的效率
事务性内存(Transactional Memory, TM)是一种新兴的范式,有望极大地简化并行程序的开发。混合TM (HyTM)可能是最有前途的TM抽象实现,它寻求将硬件实现(HTM)的高效率与基于软件的实现(STM)的健壮性和灵活性结合起来。然而,不幸的是,已知现有的Hybrid TM系统在保证硬件和软件中执行的并发事务之间的正确同步方面存在很高的开销。本文介绍DMP-TM(动态内存分区- tm),这是一种新颖的HyTM算法,据我们所知,在文献中首次利用了利用操作系统级内存保护机制来检测HTM和STM事务之间冲突的思想。这种创新的设计允许采用高度可伸缩的STM实现,同时避免在HTM路径上进行检测。这使得DMP-TM在无竞争的工作负载中与最先进的Hybrid TM解决方案相比,可以实现高达20倍的速度提升。此外,由于使用了简单和轻量级的自调优机制,DMP-TM即使在STM和HTM路径之间表现出高度竞争的不利工作负载中也能实现健壮的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Extreme-Scale Realistic Stencil Computations on Sunway TaihuLight with Ten Million Cores RideMatcher: Peer-to-Peer Matching of Passengers for Efficient Ridesharing Nitro: Network-Aware Virtual Machine Image Management in Geo-Distributed Clouds Improving Energy Efficiency of Database Clusters Through Prefetching and Caching Main-Memory Requirements of Big Data Applications on Commodity Server Platform
×
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