CC* Campus Compute: UTEP Cyberinfrastructure for Scientific and Machine Learning Applications

CC* 校园计算：用于科学和机器学习应用的 UTEP 网络基础设施

• 批准号: 2346717
• 负责人: Shirley Moore
• 金额: $ 49.84万
• 依托单位: University of Texas at El Paso
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-04-01 至 2026-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2346717&HistoricalAwards=false
• 关键词: CC; Campus; Compute; UTEP; Cyberinfrastructure

A major revolution taking place in High Performance Computing (HPC) today is the increasing use of machine learning to complement simulation. This project at University of Texas at El Paso is providing researchers in computational science and engineering fields with access to state-of-the-art GPU-accelerated hardware and software resources. The choice of resources was motivated by the requirements of science drivers that address important societal and national problems in the areas of renewable energy, advanced manufacturing, advanced materials, electric power systems, cybersecurity, and quantum computing using simulation and/or machine learning. The new hardware is integrated with the existing campus HPC cluster. The hardware is shared with the broader academic research community through participation in the Open Science Grid. In addition to providing a valuable resource for faculty, the augmented HPC cluster is available for use by students for projects related to their thesis and dissertation work as well as for class projects. The software stack on the campus HPC cluster reflects that available on NSF supercomputer systems with similar architectures. Student researchers provide assistance with operation and maintenance of the cluster, thus equipping them with skills needed for future careers in HPC and large-scale machine learning fields. Expected outcomes of the project include: 1) increased use of HPC across disciplines, 2) improvement in faculty and student skills in using state-of-the art HPC technologies, and 3) increased rate of producing research results and publications.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.

当今高性能计算 (HPC) 领域正在发生的一场重大革命是越来越多地使用机器学习来补充模拟。德克萨斯大学埃尔帕索分校的该项目为计算科学和工程领域的研究人员提供最先进的 GPU 加速硬件和软件资源。资源选择的动机是科学驱动力的要求，这些驱动力通过模拟和/或机器学习解决可再生能源、先进制造、先进材料、电力系统、网络安全和量子计算领域的重要社会和国家问题。新硬件与现有园区 HPC 集群集成。通过参与开放科学网格，与更广泛的学术研究社区共享硬件。除了为教师提供宝贵的资源外，增强的 HPC 集群还可供学生用于与其论文和学位论文工作相关的项目以及课堂项目。校园 HPC 集群上的软件堆栈反映了具有类似架构的 NSF 超级计算机系统上可用的软件堆栈。学生研究人员为集群的运维提供帮助，从而为他们提供未来在高性能计算和大规模机器学习领域职业所需的技能。 该项目的预期成果包括：1) 增加跨学科 HPC 的使用，2) 提高教师和学生使用最先进 HPC 技术的技能，3) 提高研究成果和出版物的产出率。该奖项反映了通过使用基金会的智力价值和更广泛的影响审查标准进行评估，NSF 的法定使命被认为值得支持。