MRI: Acquisition of a High Performance Computing Cluster to Enhance the Undergraduate Discovery Experience

MRI：收购高性能计算集群以增强本科生的发现体验

• 批准号: 1920220
• 负责人: Sudeep Bhattacharyay
• 金额: $ 35万
• 依托单位: University of Wisconsin-Eau Claire
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2020-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1920220&HistoricalAwards=false
• 关键词: MRI; Acquisition; Performance; Computing; Cluster

This project will fund the acquisition of a graphical processing unit (GPU)/central processing unit (CPU) hybrid high performance computing cluster (HPC) to enable undergraduate research and education. The cluster will be used for high impact research, discovery, and learning across several disciplines encompassing Biology, Chemistry, Computer Science, Geography, Material Science and Engineering, Mathematics, and Physics. The additional compute capacity will promote research-embedded classrooms and integrating computational science into the standard curriculum. It will provide a significant push to student development, code development, program profiling, system tuning, and system administration. In addition the infrastructure will enable discovery of modeling and simulation technologies that may elucidate molecular mechanisms for drug delivery, computational design catalysts for renewable energy and chemical synthesis, advanced computational analysis tools for next generation informatics and big data, and improved understanding of risk and resistance to breast cancer. The instrumentation will serve studies that employ hybrid quantum/classical simulations, for example investigation of the influence of protein dynamics on catalysis and inhibitions involving electron transfer and group reaction in two important families of enzymes (quinine reductases and aminoacyl-tRNA synthetases). The inhibitory mechanisms in these proteins are actively studied in the development of drugs with anti-cancer and anti-pathogenic properties. These studies may pave the way to design mechanism-based inhibitors of these enzymes.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.

该项目将资助购买图形处理单元（GPU）/中央处理单元（CPU）混合高性能计算集群（HPC），以支持本科生的研究和教育。该集群将用于跨多个学科的高影响力研究，发现和学习，包括生物学，化学，计算机科学，地理学，材料科学与工程，数学和物理学。额外的计算能力将促进研究嵌入式教室，并将计算科学融入标准课程。它将为学生开发，代码开发，程序分析，系统调优和系统管理提供重要的推动力。此外，该基础设施将使建模和模拟技术的发现，可能阐明药物输送的分子机制，可再生能源和化学合成的计算设计催化剂，下一代信息学和大数据的先进计算分析工具，以及提高对乳腺癌风险和耐药性的理解。 该仪器将服务于采用混合量子/经典模拟的研究，例如研究蛋白质动力学对两个重要酶家族（奎宁还原酶和氨酰-tRNA合成酶）中涉及电子转移和基团反应的催化和抑制的影响。这些蛋白质中的抑制机制在具有抗癌和抗病原体特性的药物的开发中被积极研究。该奖项反映了NSF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。