II-EN: Compute Infrastructure for Large-Scale Data Analytics

II-EN：大规模数据分析的计算基础设施

• 批准号: 1305258
• 负责人: Mohamed Eltabakh
• 金额: $ 19万
• 依托单位: Worcester Polytechnic Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-01 至 2016-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1305258&HistoricalAwards=false
• 关键词: II; EN; Compute; Infrastructure; Large

This Computing Research Infrastructure project aims to enhance Worcester Polytechnic Institute's (WPI) high-performance infrastructure to support its ongoing research and education centered around big data analytics over scalable infrastructure. The enhanced compute clustering will provide a scalable infrastructure to support large-scale data analytics research along a number of important directions, including (1) a full-fledged software platform for seamlessly supporting large-scale continuous and recurring workloads with stream-window-centric query processing, (2) scalable annotation and provenance management for natively supporting annotations as first-class citizen over big data and exploiting their semantics in query processing and quality inference, (3) complex event analytics that combines complex event processing with OLAP techniques for efficient multi-dimensional event pattern detection in high-speed large-volume data, and (4) multi-model-driven analytics system on high-velocity data streams with visual exploration of the derived models and patterns. The projects collectively address key research challenges related to the analysis of large volume, high velocity, and wide variety of data.The infrastructure is expected to significantly enhance the integration of research and education at both the undergraduate and graduate levels at WPI, including in particular, WPI's project-oriented undergraduate curriculum, which requires each undergraduate to complete a year-long research project. The infrastructure will also benefit a diverse group of researchers at WPI in different departments -- as is the case with the current compute cluster -- to conduct their data-intensive research. Broad dissemination of results of research enabled by the infrastructure including research publications, open-source software, and educational materials are expected to benefit the scientific community at large.

该计算研究基础设施项目旨在增强伍斯特理工学院（WPI）的高性能基础架构，以支持其正在进行的研究和教育，围绕大数据分析，围绕大数据分析，而不是可扩展的基础架构。 The enhanced compute clustering will provide a scalable infrastructure to support large-scale data analytics research along a number of important directions, including (1) a full-fledged software platform for seamlessly supporting large-scale continuous and recurring workloads with stream-window-centric query processing, (2) scalable annotation and provenance management for natively supporting annotations as first-class citizen over big data and exploiting their semantics在查询处理和质量推理中，（3）将复杂的事件处理与高速大容量数据中有效的多维事件模式检测相结合的复杂事件分析，以及（4）多模型驱动的分析系统在高速度数据流上与衍生模型和模型的可视化模型和模型探索。这些项目集体应对与大量分析，高速度和各种数据的分析相关的关键研究挑战。预计，基础架构将显着增强WPI的本科和研究生水平的研究和教育的整合，包括WPI的项目项目不足的研究课程，该课程需要每年的研究不足的研究项目，该研究年度研究生的研究年度研究了一年的研究。基础设施还将受益于不同部门WPI的一群研究人员，就像当前的计算集群一样 - 进行数据密集型研究。基础设施启用的研究结果的广泛传播，包括研究出版物，开源软件和教育材料将受益于整个科学界。