NICS Remote Data Analysis and Visualization Center

该提案将使用2009年美国复苏和再投资法案（公法111-5）提供的资金进行奖励，并符合2009年3月20日白宫备忘录第2节中规定的要求，该备忘录题为“确保复苏法案资金的负责任支出”。我还确认，作为认知项目官员，该提案不支持恢复法案A部分第1604节中描述的项目。近年来，来自越来越多科学领域的研究人员在生成复杂生物和物理系统数据并将这些数据转化为科学发现的能力方面存在越来越大的差距。我们的数据分析和可视化能力跟不上我们计算基础设施能力和数据采集系统分辨率和吞吐量的进步。将详细模拟生成的原始数据或先进仪器收集的原始数据转化为科学发现需要一套强大的硬件和软件能力，这些能力完全集成到我们的国家计算基础设施中。数据的数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，端到端的数据分析和可视化能力，跨越当地和国家资源。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，由实验和模拟产生的数据集正在迅速超出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大量数据中提取知识和意义，并理解相关性、趋势、模式，以及来自不断增长的数据源阵列的不同元素之间的相互关系。可视化、数据分析和知识发现比以往任何时候都更加重要，因为它们产生了数据洞察力和直觉，从而实现了科学发现。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。随着模拟规模越来越大、数量越来越多、越来越复杂，我们试图解开的科学问题也越来越具有挑战性，理解生成的数据的任务也越来越具有挑战性。该奖项旨在表彰一个数据可视化和分析中心，该中心位于田纳西大学，与NSF TeraGrid Kraken超级计算机相结合，将通过汇集独特的团队、成熟的软件技术、以及先进的计算和数据处理能力。该中心将提供TeraGrid XD的眼睛，我们的国家网络基础设施，因为它发展到XD时代，使科学家能够看到和理解非常大的测量或模拟数据集的集合。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，4 TB的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水平的共享内存并发性，用于分析和可视化。该系统由直接连接到Kraken超级计算机和TeraGrid网络的大型（1 PB）文件系统支持，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，为大规模数据理解提供软件资源。该团队还将得到专门的用户协助、系统支持、教育和应用程序发现人员的支持。

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.