Research Infrastructure: CC* Campus Compute: Next-Generation Shared HPC Cluster to Coordinate Campus Cyberinfrastructure and Accelerate Interdisciplinary Research

研究基础设施：CC* 校园计算：下一代共享 HPC 集群，以协调校园网络基础设施并加速跨学科研究

• 批准号: 2321443
• 负责人: Ryan Knutson
• 金额: $ 49.27万
• 依托单位: Montana State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2321443&HistoricalAwards=false
• 关键词: Research; Infrastructure; CC; Campus; Compute

This project acquires and deploys state-of-the-art high-performance computing (HPC) resources to serve the researchers and educators of the four-campus Montana State University (MSU) System. The resources will significantly improve speed and capability of HPC-enabled simulations, computational modeling, data analysis, and machine learning, which will accelerate research productivity and capacity and enhance educational curricula. The resources will promote economic development around emerging technologies and strategic problem solving, such as advancing quantum science, addressing energy security, securing infrastructure, advancing semiconductor research, and improving environmental and climate forecasting. Combined with increased low-barrier access to HPC, new classes, trainings, workshops, and hands-on assistance enable more students and researchers to develop skills needed to apply HPC, and will thus broaden the workforce and research base for in-demand fields in a low-density and historically underinvested state. Targeted partnerships with minority-serving units on campus and institutions across Montana focus on increasing opportunities for underrepresented populations in or through the use of expanded computational science capabilities.The deployed resources are optimized for accelerating growing areas of data intensive research at MSU and partner institutions, including artificial intelligence, quantum computing and material science, bioinformatics, precision agriculture, microbiology, computational chemistry, spatial sciences, topological data analysis, optics and photonics, and more. Resources include next-generation machine learning optimized graphics processing units (GPUs) paired with the latest central processing units (CPUs) and leverage an established foundation of high-speed storage and networking for a high performance/cost ratio. A portion of these resources will be available to the national research community through Open Science Grid.This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Established Program to Stimulate Competitive Research (EPSCoR).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.

该项目获取并部署最先进的高性能计算(HPC)资源，为蒙大拿州立大学(MSU)四个校区的研究人员和教育工作者提供服务。这些资源将显著提高支持HPC的模拟、计算建模、数据分析和机器学习的速度和能力，这将加快研究生产率和能力，并改进教育课程。这些资源将围绕新兴技术和战略问题解决推动经济发展，如推进量子科学、解决能源安全、确保基础设施安全、推进半导体研究以及改善环境和气候预测。新的课程、培训、讲习班和实践援助，再加上获得高性能计算的低障碍机会，使更多的学生和研究人员能够发展应用高性能计算所需的技能，从而扩大低密度和历史上投资不足的需求领域的劳动力和研究基础。与蒙大拿州校园和机构中的少数族裔服务单位建立有针对性的合作伙伴关系，重点是在或通过使用扩展的计算科学能力为代表不足的人群增加机会。已部署的资源经过优化，用于加快密歇根州立大学及其合作机构数据密集型研究的增长领域，包括人工智能、量子计算和材料科学、生物信息学、精确农业、微生物学、计算化学、空间科学、拓扑数据分析、光学和光子学等。资源包括新一代机器学习优化图形处理单元(GPU)与最新的中央处理器(CPU)配对，并利用高速存储和网络的既定基础以实现高性价比。这些资源的一部分将通过开放科学网格提供给国家研究社区。这一奖项由高级网络基础设施办公室共同支持，由既定的激励竞争研究计划(EPSCoR)支持。该奖项反映了NSF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。