MRI: Acquisition of HPC at AU (Expanding Capabilities for Research and Research Training at American University through Shared High-Performance Computing)

该奖项允许美国大学获得高性能计算（HPC）系统，以扩大研究和研究培训的能力。收购HPC资源是实施Au 2008年战略计划的关键一步，该计划要求全校范围内的协调努力，以扩大研究和研究生教育。这个共享资源的研究人员在整个校园将建立在Au的实力在社会科学，同时支持计划，以扩大在科学项目。它将通过将可用计算速度提高近100倍来进一步提高研究人员的生产力。HPC系统将支持越来越多的研究人员，他们将应用计算科学的工具来理解经济学、教育、统计学、物理科学和计算机科学中的复杂问题。在经济学方面，研究人员将使用拟议的HPC系统来研究如何将所有可用的行为信息纳入设计受监管的市场，探索信息技术在增长地理中的作用，并模拟扩大联邦儿童福利补贴对儿童健康的影响。在教育方面，研究人员将开发有可能彻底改变有特殊需要的学生教育的手持设备，他们将开发研究工具，将跨学科方法融入教育史和教育政策。在统计学和科学领域，研究人员将使用拟议的HPC系统将“超级学习者”算法应用于流行病学的关键问题，为所有科学家提供利用志愿者计算机网络解决常见问题的方法，设计一种新方法来创建和探测超冷物质的量子态，并绘制酶中的协变残基，用于从医学到“绿色”工业化学的应用。研究人员将使用算法，建模，模拟，3D渲染和地理可视化来解决这些不同的科学和经济上重要的问题。计算科学中最先进的方法需要快速处理、大块RAM、专门的图形处理和高磁盘输入/输出速度，这些速度远远超过Au工作站上目前可用的速度，并且将由拟议的HPC系统提供。该HPC系统的采购将大大推进Au的研究使命和研究培训。当研究人员聚集在一起管理系统，培训系统的使用，并参加研讨会的研究与系统完成，他们将共同努力，以解决实质性的计算问题。该系统将加强研究生的研究密集型学习环境。本科生已经是许多研究团队的成员，他们将接受更好的培训，以便在研究生课程和工作场所做出贡献。在整个Au的校园增加沟通和合作将扩大现有的努力，包括在研究中代表性不足的群体，因为强大的计算共享资源将导致形成一个临界质量的同行和导师的支持。

This award permits American University to acquire a high-performance computing (HPC) system to expand capabilities for research and research training. Acquisition of HPC resources is a crucial step in the implementation of AU's 2008 strategic plan, which calls for campus-wide, coordinated efforts to expand research and graduate education. This shared resource for researchers across the campus will build on AU's strength in the social sciences, while supporting plans to expand programs in the sciences. It will further the productivity of researchers by increasing the available computing speed by a factor of almost 100-fold. The HPC system will support a growing community of researchers who will apply the tools of computational science to understand complex problems in economics, education, statistics, the physical sciences, and computer science. In economics, the researchers will use the proposed HPC system to investigate ways that incorporate all available behavioral information to design regulated markets, to explore the role of information technology in the geography of growth, and to simulate the effect of expanding federal subsidies for child welfare on the health of children. In education, researchers will develop handheld devices that have the potential to revolutionize the education of students with special needs, and they will develop research tools to integrate interdisciplinary methods into the history of education and educational policy. In statistics and the sciences, researchers will use the proposed HPC system to apply the "super learner" algorithm to key problems in epidemiology, to give all scientists the means to leverage volunteer computer networks to solve common problems, to design a new method for creating and probing quantum states of ultracold matter, and to map covarying residues in enzymes for applications ranging from medicine to "green" industrial chemistry. The researchers will address these diverse scientifically and economically important questions using algorithms, modeling, simulation, 3D rendering, and geographic visualization. State-of-of-the art methods in computational science require fast processing, large blocks of RAM, specialized graphics processing, and high disk input/output speeds that far exceed what is currently available on workstations at AU, and which will be provided by the proposed HPC system. The acquisition of this HPC system will significantly advance the research mission and research training at AU. As researchers come together to manage the system, to train on use of the system, and to attend seminars on research completed with the system, they will work together to solve substantive computational problems. The system will enhance the research-intensive learning environment of graduate students. Undergraduate students, already members of many research teams, will be better trained to contribute in graduate programs and in the workplace. Increased communication and collaboration across AU's campus will amplify existing efforts to include underrepresented groups in research because the shared resource for powerful computing will lead to the formation of a critical mass for peer and mentor support.