MRI: Acquisition of the Bartik High-Performance Computing Cluster

该项目收购了一个名为Bartik的计算集群，支持所有研究人员和高级人员的家庭部门内使用高性能计算(HPC)需求的教师研究和本科教育，并为更多的教师创造机会，将计算方面实施到这个主要为本科生服务的机构的研究和/或教学工作中。(这个集群是以让·巴蒂克的名字命名的，她是计算机科学和编程领域的先驱女性，也是西北大学的校友。)在许多研究中，大数据集继续变得越来越常见。基于网络的商务使营销数据呈指数级增长，实验室技术的突破使以前无法获得的海量数据集的收集成为可能。这些数据不能再在台式计算机上存储、处理或分析，使得HPC成为许多研究的主要渠道。NWMSU与超级计算网络XSEDE进行交互，但需要其特殊资源的项目相对较少。计算集群将支持本提案中概述的项目，并允许在XSEDE资源上运行代码的基准测试和试验。巴蒂克将服务于西北密歇根州立大学本科生和研究生的研究和教育需求，以及一些经常从事教职研究的高中生。这些学生的研究经验是无价的，往往会提高科学、技术、工程和数学(STEM)领域的成功率和保留率。这个集群还将支持一个新的数据科学本科项目，该项目将于2016年秋季开始招生。在这门课程中，数学、计算机科学、商业、地理信息系统(GIS)和生物学的本科生将接受使用编码、统计和可视化方法处理大数据的培训。

This project, acquiring a computational cluster named Bartik, supports faculty research employing high-performance computing (HPC) needs and undergraduate education within the home departments of all investigators and senior personnel, and creates opportunities for additional faculty, new or existing, to implement computational aspects into research and/or teaching endeavors in this mainly undergraduate serving institution. (The cluster is named after Jean Bartik, a pioneering woman in the field of computer science and programming and a Northwest alumnus.) Large datasets continue to become increasingly common in many studies. Web-based commerce has allowed marketing data to grow exponentially, and breakthroughs in laboratory technology have enabled collection of vast datasets that were previously unattainable. These data can no longer be stored, manipulated, or analyzed on desktop computers, leaving HPC as a main outlet for many studies. NWMSU interacts with the supercomputing network XSEDE, but relatively few projects require its exceptional resources. The computational cluster would support projects outlined in this proposal and allow benchmarking and piloting of code to be run on XSEDE resources. Bartik would service both the research and education needs at NWMSU undergraduate and graduate students, as well as some high school students that are frequently engaged in faculty research. Research experiences for these students are invaluable and often lead to increased success and retention rates in Science, Technology, Engineering and Math (STEM) fields. This cluster would also support a new undergraduate program in Data Sciences that will begin accepting students in the Fall of 2016. Within this course of study, undergraduate students in Mathematics, Computer Science, Business, Geographic Information Systems (GIS), and Biology will be trained to work with big data using coding, statistical, and visualization approaches.