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）的高性能基础设施，以支持其围绕可扩展基础设施的大数据分析进行的研究和教育。增强的计算集群将提供可扩展的基础设施，以支持大规模数据分析研究，沿着许多重要方向，包括（1）一个成熟的软件平台，用于无缝支持大规模连续和重复的工作负载，以流窗口为中心的查询处理，（2）可扩展的注释和出处管理，用于原生地支持注释作为第一-大数据上的类公民，并在查询处理和质量推断中利用它们的语义，（3）复杂事件分析，其将复杂事件处理与OLAP技术相结合，用于在高速大容量数据中进行有效的多维事件模式检测，以及（4）高速数据流上的多模型驱动的分析系统，其具有对导出的模型和模式的可视化探索。这些项目共同解决了与大量、高速和各种数据分析相关的关键研究挑战，预计该基础设施将显著增强WPI本科和研究生水平的研究和教育整合，特别是WPI的项目导向本科课程，该课程要求每个本科生完成为期一年的研究项目。该基础设施还将使WPI不同部门的不同研究人员群体受益-就像当前的计算集群一样-进行数据密集型研究。通过基础设施，包括研究出版物、开放源码软件和教育材料，广泛传播研究成果，预计将使整个科学界受益。