MRI: Development of a System for Interactive Analysis and Visualization of Multi-Terabyte Datasets

MRI：开发用于多 TB 数据集交互式分析和可视化的系统

• 批准号: 0421423
• 负责人: Paul Woodward
• 金额: --
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-01 至 2007-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0421423&HistoricalAwards=false
• 关键词: MRI; Development; System; Interactive; Analysis

This project, creating a new cluster computer design targeted at interactive exploration of datasets tens of terabytes in scale, supports analysis and visualization of massive datasets. Research efforts concentrate mainly on genomics and bioinformatics, cosmology and geophysics, and computational fluid dynamic (turbulence and stellar convections). For the purpose of rendering, in near real-time, datasets whose render information requires up to 2TB of simultaneously active storage, a large system consisting of 80 dual processor nodes with a massive amount of disk space will be used for the visualization task. The visualization system will allow slightly more leeway for exploratory viewing of interactions among multiple variables at multiple time slices. Motivated by the need to interactively explore voluminous datasets, the system supports interactive analysis and visualization that follows any interactively specified and/or modified path through the 4 dimensions examining all the data along that path by streaming this data, potentially replicated at each of 80 network nodes, into the memories at a rate that matches the node's ability to perform significant analysis and/or visualization operations on the data and to display the results for the user at high resolution on viewing screens as large as the LCSE's 13 Mpixels Power Wall. Volume visualization and various kinds of pattern matching and cross correlation target this data. The design goals require significant research in scientific visualization, data management, data storage and cluster data sharing, as well as prority-based job scheduling.Broader Impacts: The development of this system involves many students and postdocs in the collaborating disciplines. The system will be used in instruction as well as in research leading to advance degrees. The computer science department at Fond du Lac Tribal and community College in Cloquet Minnesota will also benefit from this project due to the existing collaboration of the Laboratory for Computational Science and Engineering (LCSE) with this Native American serving college. LCSE has also shared its technology developments and software. Once again, the developed software will be made available over the Web in Open source format.

该项目创建了一种新的集群计算机设计，该设计针对的是对数据集的交互式探索数十个比例尺，支持大规模数据集的分析和可视化。研究工作主要集中于基因组学和生物信息学，宇宙学和地球物理，以及计算流体动力学（湍流和恒星对流）。出于渲染目的，在几乎实时的数据集中，其渲染信息的数据集最多需要2TB同时进行活跃存储，一个由80个双处理器节点组成的大系统将用于可视化任务。可视化系统将允许在多个时间切片的多个变量之间进行探索性查看。由于需要进行交互性探索大量数据集的需要，该系统支持交互式分析和可视化，遵循任何交互式和/或修改的路径，通过4个维度进行了互动的指定和/或修改的路径，通过流式传输该数据的所有数据，可能在80个网络节点中复制该数据，以使其能够匹配80个网络节点的记忆，从而匹配了use或可视化的速率。查看与LCSE的13 mpixels Power Wall一样大的屏幕。音量可视化以及各种模式匹配和互相关的目标。设计目标需要在科学可视化，数据管理，数据存储和集群数据共享以及基于PRORITY的工作计划方面进行重大研究。Broader的影响：该系统的开发涉及许多学生和博士后协作学科中的研究。该系统将用于指导和研究，从而导致提前学位。明尼苏达州Cloquet的Fond du Lac部落和社区学院的计算机科学系也将受益于该项目，因为计算科学与工程实验室（LCSE）与这所美国原住民服务学院的现有合作。 LCSE还分享了其技术开发和软件。再次，将以开源格式通过Web提供开发的软件。