MRI: Acquisition of a Massive Database to Accelerate Data Science Discovery

MRI：获取海量数据库以加速数据科学发现

• 批准号: 2117345
• 负责人: Christopher Danforth
• 金额: $ 72.5万
• 依托单位: University of Vermont & State Agricultural College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2117345&HistoricalAwards=false
• 关键词: MRI; Acquisition; Massive; Database; Accelerate

This project is jointly funded by the Major Research Instrumentation and the Established Program to Stimulate Competitive Research (EPSCoR) programs. The project funds construction of DataMountain, a massive database cluster for high performance computing at the University of Vermont (UVM). The large-memory machine will enhance the Vermont Advanced Computing Core, a virtual laboratory supporting the research of over 500 scientists in the state of Vermont. With so many fields transitioning from data-scarce to data-rich environments, many important research areas will benefit from this new machine including research into addiction, mental illness, climate change, drug discovery, food systems, and the spread of online misinformation. DataMountain will allow for fast access to enormous datasets, supporting several projects that require computational power and speed to effectively analyze, describe, and explain rapidly growing datasets.DataMountain will increase by nearly two orders of magnitude the largest random access memory machine available for computational research at UVM, accelerating large-scale data-driven research requiring rapid reading and writing, and facilitating a broad and diverse set of important scientific investigations not currently possible given the existing hardware. It will also enhance the functionality of the high performance computing clusters BlueMoon and DeepGreen, which are dedicated to parallel processing and machine learning respectively. For example, the machine will allow for interactive access to over 50 terabytes of social media data through http://storywrangling.org and http://hedonometer.org for timely analysis of changes related to the COVID-19 pandemic in population-scale physical and mental health data. In addition, DataMountain will allow for massive increases in the spatial and temporal resolution of computational chemistry simulations being performed for data-driven design of next-generation antimicrobial peptides to combat antibiotic resistance. DataMountain will also enable exploration of petabytes of fMRI, genetic, task performance, and survey data associated with 10,000 adolescents across the United States over the next decade. In addition, the machine will accelerate research using unmanned aerial surveillance imaging for tree canopy assessments, facilitate network science modeling of agricultural diversity of crops and nutritional outcomes globally, and help quantify the impacts of the COVID-19 pandemic on food insecurity.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目由主要研究仪器和已建立的激励竞争性研究计划(EPSCoR)共同资助。该项目为建设DataMountain提供资金，DataMountain是佛蒙特州大学(UVM)用于高性能计算的大型数据库集群。这台大内存计算机将增强佛蒙特州高级计算核心，这是一个支持佛蒙特州500多名科学家进行研究的虚拟实验室。随着如此多的领域从数据匮乏过渡到数据丰富的环境，许多重要的研究领域将从这台新机器中受益，包括对成瘾、精神疾病、气候变化、药物发现、食品系统和在线错误信息传播的研究。DataMountain将允许快速访问庞大的数据集，支持几个需要计算能力和速度的项目，以有效地分析、描述和解释快速增长的数据集。DataMountain将使UVM可用于计算研究的最大随机存取存储机增加近两个数量级，加速需要快速读写的大规模数据驱动研究，并促进广泛和多样化的重要科学调查，目前在现有硬件下是不可能的。它还将增强高性能计算集群蓝月亮和DeepGreen的功能，这两个集群分别致力于并行处理和机器学习。例如，这台机器将允许通过http://storywrangling.org和http://hedonometer.org交互访问超过50TB的社交媒体数据，以及时分析与新冠肺炎大流行相关的人口规模身心健康数据的变化。此外，DataMountain将大幅提高正在进行的计算化学模拟的空间和时间分辨率，以数据驱动设计下一代抗菌肽，以对抗抗生素耐药性。DataMountain还将在未来十年内探索与全美10,000名青少年相关的PB级功能磁共振成像、遗传、任务绩效和调查数据。此外，该机器将加快利用无人机空中监视成像进行树冠评估的研究，促进全球农业作物多样性和营养结果的网络科学建模，并帮助量化新冠肺炎大流行对食品安全的影响。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。