Hardware-acceleration of Semantic Web databases with runtime reconfigurable FPGAs

使用运行时可重新配置 FPGA 进行语义 Web 数据库的硬件加速

• 批准号: 241700592
• 负责人: Professor Dr. Sven Groppe
• 金额: --
• 依托单位: Institut für Informationssysteme (IFIS)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2013
• 资助国家: 德国
• 起止时间: 2012-12-31 至 2018-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/241700592?language=en
• 关键词: Hardware; acceleration; Semantic; Web; databases

The relevance of the Semantic Web has been increased steadily over the recent years. This can be shown by the increasing number of developed and used Semantic Web tools and applications.The main idea of the Semantic Web is to consider the semantic of symbols to enable a more precise machine processing. For this purpose, the necessary links between data sets are stored in database systems. The continuously increasing size of the data sets leads to performance issues for traditional databases and even specialized Semantic Web databases. In the scope of Semantic Web databases data sets with billions of entries are available and processing of these data sets on software-based solutions is highly time consuming.Thus, in this project a hardware/software system will be investigated and developed to outsource time consuming tasks to a programmable logic chip (FPGA, Field Programmable Gate Array). The hardware acceleration of cost intensive tasks will cover the index generation as well as query processing in Semantic Web databases. During query processing the determination of which function should be mapped to the FPGA will be decided at runtime. As the mapping of the data path to the basic elements uses partial runtime reconfiguration, an optimal hardware accelerator can be provided for any query.

近年来，语义网的相关性一直在稳步提高。这可以从越来越多的开发和使用的语义网工具和应用程序中可见一斑。语义网的主要思想是考虑符号的语义，以便能够进行更精确的机器处理。为此，数据集之间的必要链接存储在数据库系统中。不断增加的数据集大小导致了传统数据库甚至专门的语义Web数据库的性能问题。在语义网数据库领域，数十亿个条目的数据集是可用的，而基于软件的解决方案对这些数据集的处理非常耗时，因此，本项目将研究和开发一个硬件/软件系统，将耗时的任务外包给可编程逻辑芯片(FPGA，现场可编程门阵列)。成本密集型任务的硬件加速将涵盖语义Web数据库中的索引生成和查询处理。在查询处理期间，将在运行时决定应该将哪个函数映射到FPGA。由于数据路径到基本元素的映射使用部分运行时重新配置，因此可以为任何查询提供最佳硬件加速器。

项目成果

Hybrid FPGA approach for a B+ tree in a Semantic Web database system

用于语义 Web 数据库系统中 B 树的混合 FPGA 方法

• DOI: 10.1109/recosoc.2015.7238093
• 发表时间: 2015
• 期刊: 2015 10th International Symposium on Reconfigurable Communication-centric Systems-on-Chip (ReCoSoC)
• 作者: Dennis Heinrich;Stefan Werner;Marc Stelzner;Christopher Blochwitz;Thilo Pionteck;Sven Groppe
• 通讯作者: Sven Groppe

Accelerated join evaluation in Semantic Web databases by using FPGAs

• DOI: 10.1002/cpe.3502
• 发表时间: 2016-05
• 期刊: Concurrency and Computation: Practice and Experience
• 作者: Stefan Werner;Dennis Heinrich;Marc Stelzner;V. Linnemann;Thilo Pionteck;Sven Groppe

An optimized radix-tree for hardware-accelerated dictionary generation for semantic web databases

用于语义网络数据库硬件加速字典生成的优化基数树

• DOI: 10.1109/reconfig.2015.7393291
• 发表时间: 2015
• 期刊: 2015 International Conference on ReConFigurable Computing and FPGAs (ReConFig)
• 作者: Christopher Blochwitz;Jan Moritz Joseph;Rico Backasch;Stefan Werner;Dennis Heinrich;Sven Groppe;Thilo Pionteck
• 通讯作者: Thilo Pionteck

Hardware-Accelerated Radix-Tree Based String Sorting for Big Data Applications

适用于大数据应用的基于硬件加速基数树的字符串排序

• DOI: 10.1007/978-3-319-54999-6_4
• 发表时间: 2017
• 作者: Christopher Blochwitz;Julian Wolff;Jan Moritz Joseph;Stefan Werner;Dennis Heinrich;Sven Groppe;Thilo Pionteck
• 通讯作者: Thilo Pionteck