MRI: Development of PetaShare: A Distributed Data Archival, Analysis and Visualization System for Data Intensive Collaborative Research

MRI：PetaShare 的开发：用于数据密集型协作研究的分布式数据存档、分析和可视化系统

• 批准号: 0619843
• 负责人: Tevfik Kosar
• 金额: --
• 依托单位: Louisiana State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-15 至 2011-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0619843&HistoricalAwards=false
• 关键词: MRI; Development; PetaShare; Distributed; Data

Review Analysis: Major Research Instrumentation (MRI) Program FY06Proposal #: CNS 06-19843PI(s): Kosar, Tevfik Allen, Gabrielle D.; Seidel, Edward; Twilley, Robert R.; Wischusen, E. WilliamInstitution: Louisiana State University Baton Rouge, LA 70803-2701Title: MRI/Dev: Dev. of PetaShare: A Distributed Data Archival, Analysis and Visualization System for Data Intensive Collaborative ResearchRatings: E, V, V, V Panel Ranking: Competitive (C) Result: RecommendAmount Req: $ 957,678 Amount Rec: $ 957,678Project Proposed:This project, developing a distributed data archival, analysis, and visualization instrument (called PetaShare) for data intensive collaborative research, enables transparent handling of underlying data sharing, archival, and retrieval mechanisms and makes data available to the scientist for analysis and visualization on demand. Designed to scale to the petabyte level, the instrument responds to an urgent need of scientists working with large data generation, sharing, and collaboration requirements. Involving five universities in the state (LSU, LaTech, Tulane, ULL, and UNO), the infrastructure consists of three layers of storage distributed at multiple sites:Primary very high speed RAM storage for data visualization;Secondary disk storage for data analysis and processing; andTertiary tape storage for data archival and long term studies.Unlike existing approaches, PetaShare treats data resources and the tasks related to data access as first class entities just like computational resources and compute tasks, and not simply the side effect of computation. Expected key technologies include data-aware storage systems and data-aware schedulers, which take the responsibility of managing data resources and scheduling data tasks from the user, performing these tasks transparently. The instrument supports many important data intensive applications from different fields, including coastal and environmental modeling, geospatial analysis, bioinformatics, medical imaging, fluid dynamics, petroleum engineering, numerical relativity, and high energy physics. Broader Impact: The system complements the high-performance computing resources at the five interconnected campuses in this EPSCoR state, boosting interdisciplinary research among them. In addition to directly servicing and promoting research, PetaShare contributes in the training of hundreds of students. The system exhibits a high potential of increasing the accuracy and efficiency of storm surge models and hurricane tracking predictions, thereby enabling rapid and effective disaster responses that could affect millions of people in the world.

评论分析：主要研究仪器（MRI）计划FY06 Propoposs＃：CNS 06-19843PI（S）：Kosar，Tevfik Allen，Gabrielle D。；塞德尔（Edward）； Twilley，Robert R。； Wischusen，E。Williaminstitution：路易斯安那州立大学巴吞鲁日，洛杉矶70803-2701Title：MRI/DEV：DEV。 of PetaShare: A Distributed Data Archival, Analysis and Visualization System for Data Intensive Collaborative ResearchRatings: E, V, V, V Panel Ranking: Competitive (C) Result: RecommendAmount Req: $ 957,678 Amount Rec: $ 957,678Project Proposed:This project, developing a distributed data archival, analysis, and visualization instrument (called PetaShare) for data intensive collaborative research, enables transparent handling潜在的数据共享，档案和检索机制，并使科学家可以根据需要进行分析和可视化。该仪器旨在扩展到PB级别，迫切需要科学家与大型数据生成，共享和协作要求一起工作。涉及该州的五所大学（LSU，LATECH，TULANE，ULL和UNO），基础设施由在多个地点分布的三层存储组成：主要高速RAM存储以进行数据可视化；用于数据分析和处理的次级磁盘存储；用于数据档案和长期研究的大型磁带存储。与现有方法一样，PetAshare将数据资源和与数据访问有关的任务视为一流实体，就像计算资源和计算任务一样，而不仅仅是计算的副作用。预期的关键技术包括数据感知的存储系统和数据感知调度程序，这些调度程序负责管理数据资源并从用户调度数据任务，透明地执行这些任务。该仪器支持来自不同领域的许多重要数据密集型应用，包括沿海和环境建模，地理空间分析，生物信息学，医学成像，流体动力学，石油工程，数值相对性和高能量物理学。更广泛的影响：该系统补充了这个Epscor州五个相互联系的校园的高性能计算资源，从而促进了它们之间的跨学科研究。除了直接维修和促进研究外，Petashare还为数百名学生的培训做出了贡献。该系统具有提高风暴潮模型和飓风跟踪预测的准确性和效率的高潜力，从而实现了可能影响世界上数百万人的快速有效灾难反应。