Equipment: MRI: Track 2 Acquisition of a High-Performance Computing Cluster for Boosting Artificial Intelligence Enabled Science, Engineering, and Education in South Carolina

这一重大研究仪器(MRI)项目旨在南卡罗来纳大学(USC)建立一个新的高性能计算(HPC)仪器，该仪器具有平衡的中央处理器(CPU)和图形处理单元(GPU)节点。这一设施将显著改善南加州大学现有的高性能计算资源，这将促进材料科学、物理、化学、工程、计算机科学、生物信息学、健康科学和人文等不同领域的研究，所有这些都通过高性能计算、大数据和人工智能(AI)工具得到加强。此外，该工具将为南卡罗来纳州10多所本科院校的学生和教职员工提供HPC资源和人工智能培训，包括历史上为黑人和少数族裔服务的大学，为STEM中代表不足的群体创造尖端HPC/AI-for-Science研究的机会。该项目将通过南卡罗来纳州系统和南卡罗来纳州许多合作机构之间的合作，推动基础科学、工程学、卫生科学和人文学科的发展，并为国家在能源、气候和国家安全方面的研究重点做出贡献。新的HPC设施将使研究人员能够为AI模型训练执行大规模模拟数据采集。新仪器将用于最先进的分析、人工智能算法和数据可视化。围绕从头算量子物理和化学、分子动力学、计算fl用户动力学、多宇宙随机模型以及数据密集型深度学习和图形卷积神经网络的研究工作，将促进我们对网络物理系统和材料的了解。这些知识将有助于开发创新的应用，如材料的生成性设计、针对复杂疾病的有效干预和预防机制。该项目将极大地拓宽SC的HPC-AI计算设施的使用范围，并将通过技术研讨会、本科生研究奖学金、人工智能促进科学项目和高中夏令营提供全面的人工智能和HPC培训。该文书还将加强和促进地区联盟研究人员之间的跨学科合作，包括主要为历史上代表性不足的群体提供服务的本科机构(PUI)的科学家和学生，从而促进自然科学研究界的有机增长。超过3,000人，包括315名教职员工，2,550名研究生和本科生，90名高中生和南加州大学30个系以及10个PUI将立即受益于这种高性能计算机设备。该项目的公众访问网站将是http://ai4science.sc.edu.它将作为整个项目产生的所有研究产品的储存库，如数据、代码、结果、模拟器和模拟器。项目网站将在项目期后至少再保留5年。该项目由重大研究工具计划和既定的激励竞争性研究计划(EPSCoR)共同资助。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。

This Major Research Instrumentation (MRI) project aims to establish a new High-Performance Computing (HPC) instrument with balanced Central Processing Unit (CPU) and Graphics Processing Units (GPU) nodes at the University of South Carolina (USC). This facility will significantly improve the existing HPC resources at USC, which will boost research in diverse fields such as materials science, physics, chemistry, engineering, computer science, bioinformatics, health science and humanities, all enhanced by the HPC, big data and artificial intelligence (AI) tools. Moreover, this instrument will enable access to HPC resources and AI training for students and faculty at over 10 undergraduate institutions in South Carolina (SC), including historically black and minority-serving colleges, creating opportunities for cutting-edge HPC/AI-for-Science research for underrepresented groups in STEM.This project will advance fundamental science, engineering, health sciences and humanities, through collaboration among many partnering institutions across the USC system and SC state, and contribute to national research priorities in energy, climate and national security. The new HPC facility will enable researchers to perform large-scale simulated data acquisition for AI model training. The new instrument will be employed for state-of-the-art analytics, AI algorithms and data visualization. Research efforts centered on ab initio quantum physics and chemistry, molecular dynamics, computational fluid dynamics, multi-universe stochastic models and data-intensive deep learning and graph convolutional neural networks, will advance our knowledge of cyber-physical systems and materials. This knowledge will contribute to the development of innovative applications such as generative design of materials, effective intervention and prevention mechanisms for complex diseases.This project will greatly broaden access to the HPC-AI computing facility in SC and will provide holistic AI and HPC training through technical workshops, undergraduate research scholarships and AI-for-Science projects and high-school summer camps. This instrument will also enhance and promote interdisciplinary collaborations among regional consortium researchers, including scientists and students at Primarily Undergraduate Institutions (PUIs) serving historically underrepresented groups, leading to an organic growth of the research community in SC. Over 3,000 people including 315 faculty, 2,550 graduate and undergraduate students, 90 high school students and 30 departments across USC and 10 PUIs will immediately benefit from this HPC equipment.The project website for public access will be http://ai4science.sc.edu. It will serve as the depository for all research products generated throughout the project, such as data, codes, results, emulators and simulators. The project website will be maintained for at least 5 additional years beyond the project period.This project is jointly funded by the Major Research Instrumentation program and 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.