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

该项目由主要研究仪器和刺激竞争研究的既定计划（EPSCoR）计划共同资助。该项目资助了datmountain的建设，这是佛蒙特大学（UVM）用于高性能计算的大型数据库集群。这台大内存机器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稀缺环境转变为数据丰富环境，许多重要的研究领域将受益于这台新机器，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。datmountain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来有效分析、描述和解释快速增长的数据集的项目。datmountain将为UVM的计算研究增加近两个数量级的最大随机存取存储器机器，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研究，目前不可能给定现有的硬件。它还将增强高性能计算集群BlueMoon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，该机器将允许通过http://storywrangling.org和http://hedonometer.org对超过50tb的社交媒体数据进行交互式访问，以便及时分析与COVID-19大流行相关的人群身心健康数据的变化。此外，datmountain将允许大量增加计算化学模拟的空间和时间分辨率，用于下一代抗菌肽的数据驱动设计，以对抗抗生素耐药性。datmountain还将在未来十年内对全美10,000名青少年的fMRI、基因、任务表现和调查数据进行pb级的探索。此外，该机器还将加速利用无人机监视成像进行树冠评估的研究，促进全球作物农业多样性和营养结果的网络科学建模，并帮助量化2019冠状病毒病大流行对粮食不安全的影响。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知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.