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

评审分析：2006财年主要研究仪器（MRI）计划提案编号：CNS 06- 19843 PI：Kosar、Tevfik艾伦、Gabrielle D.; Seidel，Edward; Quinley，Robert R.; Wischusen，E. William机构：路易斯安那州立大学巴吞鲁日，LA 70803- 2701标题：MRI/开发：开发。PetaShare：一个分布式数据归档、分析和可视化系统 数据密集型协作研究评级：E，V，V，V小组排名：竞争力（C）结果：推荐申请金额：$957，678 收款金额：$957，678项目建议：该项目，开发一个分布式数据存档，分析和可视化工具（称为PetaShare），用于数据密集型合作研究，使底层数据共享，存档和检索机制的透明处理，并使数据可供科学家按需分析和可视化。该仪器旨在扩展到PB级，以满足科学家对大数据生成、共享和协作需求的迫切需求。涉及该州五所大学（LSU、LaTech、Tulane、PLAN和UNO），基础设施由分布在多个站点的三层存储组成：用于数据可视化的主超高速RAM存储;用于数据分析和处理的辅助磁盘存储;以及用于数据存档和长期研究的三级磁带存储。与现有方法不同，PetaShare将数据资源和与数据访问相关的任务视为第一类实体，就像计算资源和计算任务一样，而不仅仅是计算的副作用。预计的关键技术包括数据感知存储系统和数据感知存储器，它们负责管理数据资源和调度用户的数据任务，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、数值相对论和高能物理。更广泛的影响：该系统补充了EPSCoR州五个互联校园的高性能计算资源，促进了其中的跨学科研究。除了直接服务和促进研究外，PetaShare还为数百名学生的培训做出了贡献。该系统显示出提高风暴潮模型和飓风跟踪预测的准确性和效率的巨大潜力，从而能够迅速有效地应对可能影响世界上数百万人的灾害。

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.