xlynx -用于混合XQuery处理的基于fpga的XML过滤器

IF 2.2 2区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS ACM Transactions on Database Systems Pub Date : 2013-11-01 DOI:10.1145/2536800
J. Teubner, L. Woods, Chongling Nie
{"title":"xlynx -用于混合XQuery处理的基于fpga的XML过滤器","authors":"J. Teubner, L. Woods, Chongling Nie","doi":"10.1145/2536800","DOIUrl":null,"url":null,"abstract":"While offering unique performance and energy-saving advantages, the use of Field-Programmable Gate Arrays (FPGAs) for database acceleration has demanded major concessions from system designers. Either the programmable chips have been used for very basic application tasks (such as implementing a rigid class of selection predicates) or their circuit definition had to be completely recompiled at runtime—a very CPU-intensive and time-consuming effort.\n This work eliminates the need for such concessions. As part of our XLynx implementation—an FPGA-based XML filter—we present skeleton automata, which is a design principle for data-intensive hardware circuits that offers high expressiveness and quick reconfiguration at the same time. Skeleton automata provide a generic implementation for a class of finite-state automata. They can be parameterized to any particular automaton instance in a matter of microseconds or less (as opposed to minutes or hours for complete recompilation).\n We showcase skeleton automata based on XML projection [Marian and Siméon 2003], a filtering technique that illustrates the feasibility of our strategy for a real-world and challenging task. By performing XML projection in hardware and filtering data in the network, we report on performance improvements of several factors while remaining nonintrusive to the back-end XML processor (we evaluate XLynx using the Saxon engine).","PeriodicalId":50915,"journal":{"name":"ACM Transactions on Database Systems","volume":"37 1","pages":"23"},"PeriodicalIF":2.2000,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"XLynx—An FPGA-based XML filter for hybrid XQuery processing\",\"authors\":\"J. Teubner, L. Woods, Chongling Nie\",\"doi\":\"10.1145/2536800\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"While offering unique performance and energy-saving advantages, the use of Field-Programmable Gate Arrays (FPGAs) for database acceleration has demanded major concessions from system designers. Either the programmable chips have been used for very basic application tasks (such as implementing a rigid class of selection predicates) or their circuit definition had to be completely recompiled at runtime—a very CPU-intensive and time-consuming effort.\\n This work eliminates the need for such concessions. As part of our XLynx implementation—an FPGA-based XML filter—we present skeleton automata, which is a design principle for data-intensive hardware circuits that offers high expressiveness and quick reconfiguration at the same time. Skeleton automata provide a generic implementation for a class of finite-state automata. They can be parameterized to any particular automaton instance in a matter of microseconds or less (as opposed to minutes or hours for complete recompilation).\\n We showcase skeleton automata based on XML projection [Marian and Siméon 2003], a filtering technique that illustrates the feasibility of our strategy for a real-world and challenging task. By performing XML projection in hardware and filtering data in the network, we report on performance improvements of several factors while remaining nonintrusive to the back-end XML processor (we evaluate XLynx using the Saxon engine).\",\"PeriodicalId\":50915,\"journal\":{\"name\":\"ACM Transactions on Database Systems\",\"volume\":\"37 1\",\"pages\":\"23\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2013-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Transactions on Database Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1145/2536800\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Database Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1145/2536800","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 16

摘要

在提供独特的性能和节能优势的同时,使用现场可编程门阵列(fpga)进行数据库加速已经要求系统设计师做出重大让步。可编程芯片要么用于非常基本的应用程序任务(例如实现一类严格的选择谓词),要么必须在运行时完全重新编译它们的电路定义——这是一项非常耗费cpu和时间的工作。这项工作消除了这种让步的需要。作为XLynx实现(基于fpga的XML过滤器)的一部分,我们提出了框架自动机,这是一种用于数据密集型硬件电路的设计原则,它同时提供了高表达性和快速重新配置。骨架自动机提供了一类有限状态自动机的通用实现。它们可以在几微秒或更短的时间内参数化为任何特定的自动机实例(完全重新编译需要几分钟或几小时)。我们展示了基于XML投影的骨架自动机[Marian and sim 2003],这是一种过滤技术,说明了我们的策略在现实世界中具有挑战性的任务中的可行性。通过在硬件中执行XML投影并在网络中过滤数据,我们报告了几个因素的性能改进,同时保持对后端XML处理器的非侵入性(我们使用Saxon引擎评估XLynx)。
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
XLynx—An FPGA-based XML filter for hybrid XQuery processing
While offering unique performance and energy-saving advantages, the use of Field-Programmable Gate Arrays (FPGAs) for database acceleration has demanded major concessions from system designers. Either the programmable chips have been used for very basic application tasks (such as implementing a rigid class of selection predicates) or their circuit definition had to be completely recompiled at runtime—a very CPU-intensive and time-consuming effort. This work eliminates the need for such concessions. As part of our XLynx implementation—an FPGA-based XML filter—we present skeleton automata, which is a design principle for data-intensive hardware circuits that offers high expressiveness and quick reconfiguration at the same time. Skeleton automata provide a generic implementation for a class of finite-state automata. They can be parameterized to any particular automaton instance in a matter of microseconds or less (as opposed to minutes or hours for complete recompilation). We showcase skeleton automata based on XML projection [Marian and Siméon 2003], a filtering technique that illustrates the feasibility of our strategy for a real-world and challenging task. By performing XML projection in hardware and filtering data in the network, we report on performance improvements of several factors while remaining nonintrusive to the back-end XML processor (we evaluate XLynx using the Saxon engine).
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
ACM Transactions on Database Systems
ACM Transactions on Database Systems 工程技术-计算机:软件工程
CiteScore
5.60
自引率
0.00%
发文量
15
审稿时长
>12 weeks
期刊介绍: Heavily used in both academic and corporate R&D settings, ACM Transactions on Database Systems (TODS) is a key publication for computer scientists working in data abstraction, data modeling, and designing data management systems. Topics include storage and retrieval, transaction management, distributed and federated databases, semantics of data, intelligent databases, and operations and algorithms relating to these areas. In this rapidly changing field, TODS provides insights into the thoughts of the best minds in database R&D.
期刊最新文献
Automated Category Tree Construction: Hardness Bounds and Algorithms Database Repairing with Soft Functional Dependencies Sharing Queries with Nonequivalent User-Defined Aggregate Functions A family of centrality measures for graph data based on subgraphs GraphZeppelin: How to Find Connected Components (Even When Graphs Are Dense, Dynamic, and Massive)
×
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