CC* Compute: The MSU Data Machine - a high-memory, GPU-enabled compute cluster for data-intensive and AI applications

MSU数据机解决了许多研究领域中大型和复杂数据集的指数增长，特别是那些计算尚未被广泛使用的领域，或者那些研究和教学方法需要处理“大数据”的领域，这些领域呈现出与传统高性能计算不同的计算要求。数据机通过拥有具有大量内存的计算节点、高速文件系统、针对机器学习和基于人工智能的分析技术进行优化的图形处理单元以及高速文件系统，促进了数据密集型研究。它还包括软件、使用策略和培训，使用户可以轻松地交互式分析和可视化他们的数据。该项目侧重于四个特定的研究领域——微生物基因组学、社会系统建模、空间和群落生态学以及数据驱动的湍流建模——然而，数据机器广泛地使密歇根州立大学的研究社区能够通过降低与这些类型资源接触的障碍来追求数据密集型研究项目。该项目还通过开放科学网格和密歇根州立大学nsf资助的科学非军事区项目为国家提供了宝贵的计算资源，促进了广泛领域的研究。此外，密歇根州立大学的本科生和研究生正在参与数据机器的部署和管理，并将其用于研究和教育活动，为培养具有全球竞争力的STEM劳动力做出贡献，并促进在计算和数据科学方面代表性不足的群体的进步。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。

The MSU Data Machine addresses the exponential growth of large and complex datasets in many fields of study, particularly those where computing has not been widely used or where the research and teaching approaches needed to work with “big data”, which present a different set of computing requirements than in traditional high performance computing. The Data Machine facilitates data-intensive research by having computing nodes with large amounts of memory, a high speed file system, graphics processing units that are optimized for machine learning and artificial intelligence-based analysis techniques, and a high speed file system. It also includes software, usage policies, and training that makes it easy for users to interactively analyze and visualize their data. This project focuses on four specific research areas - in the areas of microbial genomics, social system modeling, spatial and community ecology, and data-driven turbulence modeling - however, the Data Machine broadly enables MSU’s research community to pursue data-intensive research projects by lowering barriers to engaging with these types of resources. The project also provides a valuable computational resource to the nation via the Open Science Grid and MSU’s NSF-funded Science DMZ project, advancing research in a wide spectrum of areas. Furthermore, MSU undergraduate and graduate students are participating in the deployment and administration of the Data Machine as well as using it for research and educational activities, contributing to the development of a globally competitive STEM workforce and promoting the advancement of under-represented groups in computational and data science.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.