NICS Remote Data Analysis and Visualization Center

NICS远程数据分析与可视化中心

• 批准号: 0906324
• 负责人: Sean Ahern
• 金额: $ 1000万
• 依托单位: University of Tennessee Knoxville
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2013-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0906324&HistoricalAwards=false
• 关键词: NICS; Remote; Data; Analysis; Visualization

This proposal will be awarded using funds made available by the American Recovery and Reinvestment Act of 2009 (Public Law 111-5), and meets the requirements established in Section 2 of the White House Memorandum entitled, Ensuring Responsible Spending of Recovery Act Funds, dated March 20, 2009. I also affirm, as the cognizant Program Officer, that the proposal does not support projects described in Section 1604 of Division A of the Recovery Act.In recent years, researchers from a growing range of scientific domains haveexperienced a widening gap in their abilities to generate data on complex biological and physical systems and translate these data into scientific discovery. Our data analysis and visualization capabilities have failed to keep pace with advances in both the capacity of our computing infrastructure and the resolution and throughput of our data acquisition systems.Translating raw data generated by detailed simulation or collected by advancedinstruments into scientific discovery requires a coherent suite of powerful hardware and software capabilities that is fully integrated into our national computational infrastructure. The volume of the data and the complexity of the underlying phenomena require an infrastructure that allows scientists to develop and operate flexible, and the same time dependable, end-to-end data analysis and visualization capabilities that span local and national resources. A 2007 report composed by data analysis, management,and visualization experts concluded that datasets being produced by experiments and simulations are rapidly outstripping our ability to explore and understand them.One of the most significant challenges to scientific discovery today is the extraction of knowledge and meaning from this vast array of data and the understanding of the correlations, trends, patterns, and interrelationships among disparate elements from an ever-growing array of data sources. Visualization, data analysis, and knowledge discovery are more vital than ever because they generate the data insight and intuition that enable scientific discovery. Scientific simulation has become the third pillar ofscience, supporting frameworks and experimental studies in our understanding ofnatural phenomena. As simulations become larger, more numerous, more complex, and as the scientific problems we seek to unlock become more challenging, so does the task of understanding the data generated.This award presents a data visualization and analysis center, based at the University of Tennessee and coupled with the NSF TeraGrid Kraken supercomputer, that will narrow this gap by bringing together a unique team, proven software technologies, and advanced computing and data-handling capabilities. The center will provide the eyes of the TeraGrid XD, our national cyberinfrastructure, as it evolves to the XD era byempowering scientists to see and understand very large collections of measured or simulated datasets.The hardware that undergirds the center is a large shared memory SGI UltraViolet system, able to provide 1,024 processors with 4 TB of shared memory for processing large datasets. No other system in the world has this level of shared memory concurrency for analysis and visualization.Supported by a large (1 PB) filesystem directly connected to the Kraken supercomputer and the TeraGrid network, this system will provide NSF researchers with an unparalleled data understanding resource.The team of people comprising the center will draw upon experience in visualization,statistical analysis, workflow delivery, portal and dashboard development, remote access, and application development to provide software resources for large scale data understanding. This team will also be supported by dedicated user assistance, system support, education, and application discovery staff.

该提案将使用2009年美国复苏和再投资法案（公法111-5）提供的资金，并符合2009年3月20日白宫备忘录第2节的要求，题为“确保负责任的复苏法案资金支出”。我还确认，作为认可的项目官员，该提案不支持《复苏法案》A部分第1604条所述的项目。近年来，越来越多的科学领域的研究人员在生成复杂生物和物理系统的数据并将这些数据转化为科学发现的能力方面遇到了越来越大的差距。我们的数据分析和可视化能力未能跟上我们的计算基础设施能力和数据采集系统的分辨率和吞吐量的进步。将由详细模拟产生的原始数据或由先进仪器收集的原始数据转化为科学发现需要一套连贯的强大硬件和软件功能，这些功能完全集成到我们的国家计算基础设施中。数据量和潜在现象的复杂性需要一个基础设施，使科学家能够开发和操作灵活，同时可靠，端到端数据分析和可视化能力跨越地方和国家资源。2007年，一份由数据分析、管理和可视化专家撰写的报告得出结论，通过实验和模拟产生的数据集正在迅速超越我们探索和理解它们的能力。当今科学发现面临的最重大挑战之一是从海量数据中提取知识和意义，并从不断增长的数据源中理解不同元素之间的相关性、趋势、模式和相互关系。可视化、数据分析和知识发现比以往任何时候都更加重要，因为它们产生了能够实现科学发现的数据洞察力和直觉。科学模拟已经成为科学的第三大支柱，支持我们理解自然现象的框架和实验研究。随着模拟变得越来越大、越来越多、越来越复杂，随着我们试图解开的科学问题变得越来越具有挑战性，理解生成的数据的任务也变得越来越艰巨。该奖项提出了一个数据可视化和分析中心，该中心设在田纳西大学，并与美国国家科学基金会的TeraGrid Kraken超级计算机相结合，将通过汇集一个独特的团队、经过验证的软件技术以及先进的计算和数据处理能力来缩小这一差距。该中心将为我们的国家网络基础设施TeraGrid XD提供眼睛，使科学家能够看到和理解非常大的测量或模拟数据集，从而向XD时代发展。支撑该中心的硬件是一个大型共享内存SGI UltraViolet系统，能够提供1,024个处理器和4tb共享内存，用于处理大型数据集。世界上没有其他系统具有这种级别的用于分析和可视化的共享内存并发性。由直接连接到Kraken超级计算机和TeraGrid网络的大型（1pb）文件系统支持，该系统将为NSF研究人员提供无与伦比的数据理解资源。组成该中心的人员团队将利用可视化、统计分析、工作流交付、门户和仪表板开发、远程访问和应用程序开发方面的经验，为大规模数据理解提供软件资源。该团队还将由专门的用户协助、系统支持、教育和应用程序发现人员提供支持。