MRI: Acquisition of a GPU Cluster for Multi-Disciplinary Research and Education at University of Nevada, Las Vegas

该项目资助内华达大学拉斯维加斯分校（UNLV）的高性能图形处理单元（GPU）集群的购买和调试。该项目将解决跨多个学科的研究和教育工作的紧急和长期需求、挑战和机遇：生物医学研究、智能交通系统和自动车辆、基因组学、天文学和物理学。该项目将有助于推进国家在大数据、战略计算、人工智能和智能基础设施系统方面的举措。这些将整合、综合、建模和可视化来自不同来源的大量数据，以及开发和应用人工智能（AI）技术来辅助决策。对于该项目的应用和基础研究方面，GPU集群将利用计算硬件、软件、传感器网络和通信系统方面的先进技术。该项目的一些要素将解决近期的社会需求，以保护和提高个人和家庭的生活质量，支持经济竞争力和商业增长，并促进社区的活力。其中包括与公共卫生、交通、环境和能源有关的主题。该项目的长期计划将涉及这些领域以及天文学、物理学和基因组学的基础研究的探索和创新。这些活动将包括与学术界、政府实体和私营部门组织建立伙伴关系。该项目将支持本科生和研究生的课程和课外活动，以增加他们对相关教育、研究和就业机会的兴趣。作为少数族裔服务机构和西班牙裔服务机构，这笔赠款将帮助UNLV大大扩大来自不同社会经济和社会人口社区的学生的机会。因此，该项目的一个成果将是帮助培养来自不同背景的熟练劳动力。GPU集群将支持基础和应用研究，以及跨多个学科的教育项目。研究工作的共同要素包括集成、综合、建模和可视化大量数据，以及各种人工智能技术的开发和应用，以支持决策。生物医学的努力将是使用可解释的深度学习技术，使用公开的多能性转录因子数据集，对苯二氮卓类药物和阿片类药物过量的风险个体进行分层。与智能交通系统和自动驾驶汽车相关的活动将解决交通网络近实时应用的综合轨迹预测挑战，以帮助加速联网自动驾驶汽车和基础设施系统的部署；他们将使用来自各种车载、道路和路边传感器的数据。基因组学的研究将更好地了解内源性逆转录病毒（ERV）整合产生的新型转录因子（TF）结合位点的进化。天文学相关的努力将是使用卷积神经网络（CNN）从原行星盘图像估计行星质量。物理学方面的努力将是发展旋转等变CNN来模拟和评估材料原子尺度上的力场。该项目的教育方面将包括本科和研究生阶段的课程和课外活动，以帮助提醒、吸引、激发和激励学生在相关领域追求教育、研究和职业机会。该项目将包括与公共和私营部门组织以及学术界建立伙伴关系。该项目由主要研究仪器（MRI）计划、刺激竞争性研究的既定计划（EPSCoR）和计算机与信息科学与工程理事会（CISE）联合资助。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 project funds the purchase and commissioning of a high-performance graphical processing unit (GPU) cluster at the University of Nevada, Las Vegas (UNLV). The project will address emergent and longer-term needs, challenges, and opportunities in research and educational efforts across multiple disciplines: biomedical research, intelligent transportation systems and automated vehicles, genomics, astronomy, and physics. The project will help advance national initiatives in big data, strategic computing, artificial intelligence, and smart infrastructure systems. These will integrate, synthesize, model, and visualize large volumes of data from various sources as well as develop and apply Artificial Intelligence (AI) techniques to assist decision making. For applied and basic research aspects of the project, the GPU cluster will leverage advances in computing hardware, software, sensor networks, and communications systems. Some elements of the project will address near-term societal needs to preserve and enhance the quality of living of individuals and families, support economic competitiveness and growth of businesses, and foster the vitality of communities. These include topics related to public health, transportation, environment, and energy. The project’s longer-term initiatives will address explorations and innovations in basic research in these domains as well as in astronomy, physics, and genomics. These activities will include partnerships with academia, government entities, and private sector organizations. The project will support curricular and co-curricular activities for undergraduate and graduate students to increase their interests in related education, research, and career opportunities. As a Minority-Serving Institution and Hispanic Serving Institution, this grant will help UNLV to significantly expand such opportunities for students from varied socio-economic and socio-demographic communities. Thus, an outcome of the project will be to help develop skilled work-forces from diverse backgrounds. The GPU cluster will support basic and applied research, as well as educational programs across multiple disciplines. Common elements for the research efforts include integrating, synthesizing, modeling, and visualizing large volumes of data along with the development and application of various AI techniques to support decision making. Efforts in Biomedicine will be to stratify individuals at risk for benzodiazepine and opioid overdose using interpretable deep learning techniques using publicly available pluripotency transcription factors datasets. Activities related to intelligent transportation systems and automated vehicles will address comprehensive trajectory prediction challenges for near real-time applications on transportation networks to help accelerate the deployment of Connected Automated Vehicles and Infrastructure Systems; they will use data from various in-vehicle, on-roadway, and roadside sensors. Research in Genomics will be to better understand the evolution of novel transcription factor (TF) binding sites originating from endogenous retrovirus (ERV) integration. Astronomy related endeavors will be to estimate planet mass from protoplanetary disk images using Convolutional Neural Networks (CNN). Efforts in Physics will be to develop rotationally equivariant CNN to simulate and evaluate force fields at atomistic scales of materials. Educational aspects of the project will include curricular and co-curricular initiatives at the undergraduate and graduate levels to help alert, engage, excite, and motivate students to pursue education, research, and career opportunities in related fields. The project will include partnerships with public and private sector organizations and academia.This project is jointly funded by the Major Research Instrumentation (MRI) program, the Established Program to Stimulate Competitive Research (EPSCoR), and the Computer & Information Science & Engineering (CISE) Directorate.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.