CISE Research Resources: A Shared Data Cluster For Real Time Interaction With Massive Datasets

CISE 研究资源：与海量数据集实时交互的共享数据集群

• 批准号: 0130869
• 负责人: Benjamin Watson
• 金额: $ 10.53万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-15 至 2003-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0130869&HistoricalAwards=false
• 关键词: CISE; Research; Resources; Shared; Data

EIA-0130869 Benjamin WatsonNorthwestern UniversityCISE Research Resources: A Shared Data Cluster for Real Time Interaction With Massive DatasetsThe research at Northwestern is increasingly concerned with the issues involved in providing interactive and affordable access to massive (terabyte scale) datasets. In particular, they focus on visualization of these datasets using perceptually based computer graphics techniques and display the visualizations using a combination PC CAVE and Active Mural. They also study the issues involved with ubiquitous access to high-resolution spatial datasets from mobile devices, and leverage a powerful wireless network. They focus on prediction-based adaptation and scheduling for distributed interactive applications and are building a compute cluster to support this work.What is missing in the existing shared research infrastructure is a facility to store and serve massive datasets interactively, with low latency and high bandwidth. The researchers will build such a shared data cluster. The data cluster will be very high performance and capacity PC RAIDs interconnected with a multi-GB/sec SAN. The SAN will connect to their compute cluster, CAVE/Mural, mobile devices and wired client machines. The combined data and compute clusters will be sufficient to pump 200 MB/s from disk to the CAVE/Mural screens. The combination of the data cluster, compute cluster, CAVE/Mural, local network infrastructure, and desktop and mobile clients will let them study interactivity in the large.

EIA-0130869本杰明·沃森西北大学研究资源：用于与海量数据集实时交互的共享数据集群西北大学的研究越来越关注提供对海量(TB级)数据集的交互和负担得起的访问所涉及的问题。特别是，他们专注于使用基于感知的计算机图形技术来可视化这些数据集，并使用PC CAVE和活动壁画的组合来显示可视化。他们还研究了从移动设备无处不在地访问高分辨率空间数据集所涉及的问题，并利用了强大的无线网络。他们专注于分布式交互应用的基于预测的自适应和调度，并正在构建一个计算集群来支持这项工作。现有的共享研究基础设施缺少的是以交互方式存储和服务海量数据集的设施，具有低延迟和高带宽。研究人员将建立这样一个共享的数据集群。数据集群将是与多Gb/秒SAN互连的非常高性能和容量的PC Raid。SAN将连接到他们计算集群、CAVE/MALLAL、移动设备和有线客户端机器。组合的数据和计算集群将足以从磁盘向洞穴/壁画屏幕泵送200MB/S。数据集群、计算集群、CAVE/MALLAL、本地网络基础设施以及桌面和移动客户端的组合将使他们能够研究更大范围的互动性。