硬件加速应用集成处理:工业论文

Daniel Ritter, Jonas Dann, Norman May, S. Rinderle-Ma
{"title":"硬件加速应用集成处理:工业论文","authors":"Daniel Ritter, Jonas Dann, Norman May, S. Rinderle-Ma","doi":"10.1145/3093742.3093911","DOIUrl":null,"url":null,"abstract":"The growing number of (cloud) applications and devices massively increases the communication rate and volume pushing integration systems to their (throughput) limits. While the usage of modern hardware like Field Programmable Gate Arrays (FPGAs) led to low latency when employed for query and event processing, application integration adds yet unexplored processing opportunities. In this industry paper, we explore how to program integration semantics (e. g., message routing and transformation) in form of Enterprise Integration Patterns (EIP) on top of an FPGA, thus complementing the existing research on FPGA data processing. We focus on message routing, re-define the EIP for stream processing and propose modular hardware implementations as templates that are synthesized to circuits. For our real-world \"connected car\" scenario (i. e., composed patterns), we discuss common and new optimizations especially relevant for hardware integration processes. Our experimental evaluation shows competitive throughput compared to modern general-purpose CPUs and discusses the results.","PeriodicalId":325666,"journal":{"name":"Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Hardware Accelerated Application Integration Processing: Industry Paper\",\"authors\":\"Daniel Ritter, Jonas Dann, Norman May, S. Rinderle-Ma\",\"doi\":\"10.1145/3093742.3093911\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The growing number of (cloud) applications and devices massively increases the communication rate and volume pushing integration systems to their (throughput) limits. While the usage of modern hardware like Field Programmable Gate Arrays (FPGAs) led to low latency when employed for query and event processing, application integration adds yet unexplored processing opportunities. In this industry paper, we explore how to program integration semantics (e. g., message routing and transformation) in form of Enterprise Integration Patterns (EIP) on top of an FPGA, thus complementing the existing research on FPGA data processing. We focus on message routing, re-define the EIP for stream processing and propose modular hardware implementations as templates that are synthesized to circuits. For our real-world \\\"connected car\\\" scenario (i. e., composed patterns), we discuss common and new optimizations especially relevant for hardware integration processes. Our experimental evaluation shows competitive throughput compared to modern general-purpose CPUs and discusses the results.\",\"PeriodicalId\":325666,\"journal\":{\"name\":\"Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3093742.3093911\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3093742.3093911","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12

摘要

越来越多的(云)应用程序和设备极大地提高了通信速率和容量,将集成系统推向了它们的(吞吐量)极限。虽然使用现场可编程门阵列(fpga)等现代硬件可以降低查询和事件处理的延迟,但应用程序集成增加了尚未开发的处理机会。在这篇行业论文中,我们探索了如何在FPGA之上以企业集成模式(EIP)的形式编程集成语义(如消息路由和转换),从而补充了现有的FPGA数据处理研究。我们专注于消息路由,重新定义流处理的EIP,并提出模块化硬件实现作为合成电路的模板。对于我们现实世界的“联网汽车”场景(即组合模式),我们讨论了与硬件集成过程特别相关的常见和新的优化。我们的实验评估显示了与现代通用cpu相比具有竞争力的吞吐量,并讨论了结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hardware Accelerated Application Integration Processing: Industry Paper
The growing number of (cloud) applications and devices massively increases the communication rate and volume pushing integration systems to their (throughput) limits. While the usage of modern hardware like Field Programmable Gate Arrays (FPGAs) led to low latency when employed for query and event processing, application integration adds yet unexplored processing opportunities. In this industry paper, we explore how to program integration semantics (e. g., message routing and transformation) in form of Enterprise Integration Patterns (EIP) on top of an FPGA, thus complementing the existing research on FPGA data processing. We focus on message routing, re-define the EIP for stream processing and propose modular hardware implementations as templates that are synthesized to circuits. For our real-world "connected car" scenario (i. e., composed patterns), we discuss common and new optimizations especially relevant for hardware integration processes. Our experimental evaluation shows competitive throughput compared to modern general-purpose CPUs and discusses the results.
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:481959085
Book学术官方微信