MRI: Acquisition of a High-Performance Computing Cluster for Research and Teaching at Rutgers University-Newark

这项授予纽瓦克罗格斯大学的奖项支持购买和部署高性能计算(HPC)集群(命名为PRICE)，致力于研究、教学和社会推广工作。普莱斯将拥有60个通用计算(CPU)节点和一个图形处理单元(GPU)节点，以及适合机器整个生命周期计划使用的存储空间。使能研究沿着三个主要方向发展：原子建模、神经科学和数据科学。一些由价格驱动的原子模型将研究蛋白质的结构和动力学，以解决与阿尔茨海默氏症等疾病相关的问题。新材料的建模和设计既受价格的影响，也得益于新的量子模拟方法的发展。启用的模拟还将考虑通过遗传算法进行的新材料设计。这项神经科学研究着眼于对实验数据的计算分析，以了解大脑功能、连接性和人类行为。使能数据科学研究包括制定新的协作式人工智能(AI)算法，这些算法将改善机器学习(ML)模型的结果，具有广泛的适用性。除了实现新的科学，该项目还实现了几个更广泛的社会影响，包括扩大未被充分代表的少数民族的HPC素养，在课堂上使用HPC培训未来的新泽西州劳动力，以及开发新的本科生和研究生课程。PRICE将包括60个计算节点(52核/节点)、700 TB冗余存储和一个GPU节点(4个GPU/节点)将安装在罗格斯大学-纽瓦克。普赖斯将支持罗格斯-纽瓦克和NJIT的PI、共同PI和主要用户进行的几个额外的研究项目。图形处理器部分能够实现最先进的分子动力学模拟，阐明蛋白质的结构和动力学，以了解阿尔茨海默氏症等疾病。图形处理器还能够高效和及时地执行旨在提高预测性的合作人工智能算法。CPU节点将通过密度泛函理论计算实现针对材料工程的量子模拟。这些模拟有助于发展基于密度泛函理论的量子模型、其子系统公式(在普赖斯的低延迟网络上高效并行)以及基于多组分系统薛定谔方程的精确因式分解的量子力学框架。CPU和GPU节点将实现与神经科学实验相关的数据分析，这些实验旨在揭示大脑如何调节行为和与视觉相关的任务，以及研究神经元连接以了解大脑功能。这些实验的数据正在呈指数级增长，这是因为来自新的fMRI单元的仪器数据流增加，以及改进的技术允许记录数百个神经元上的局部场电位。该项目还支持新的科学以及实现更广泛的社会影响，例如扩大未被充分代表的少数群体的高性能计算素养，培训未来的新泽西州劳动力和招聘新教师。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 award to Rutgers University-Newark supports the acquisition and deployment of a High-Performance Computing (HPC) cluster (named PRICE) dedicated to research, teaching and societal outreach efforts. PRICE will have 60 general compute (CPU) nodes and one graphical processing unit (GPU) node as well as storage appropriate for the planned usage over the lifetime of the machine. The enabled research develops along three main directions: atomistic modeling, neuroscience, and data science. Some atomistic models enabled by PRICE will study the structure and dynamics of proteins to address questions related to diseases such as Alzheimer’s. New materials modeling and design is enabled both by PRICE and by the development of new quantum simulation methods. The enabled simulations will also regard new materials design by way of genetic algorithms. The enabled neuroscience research regards computational analysis of experimental data to understand brain function, connectivity, and human behavior. Enabled data science research includes the formulation of novel cooperative artificial intelligence (AI) algorithms that will improve the outcome of machine learning (ML) models of broad applicability. In addition to enabling new science, the project realizes several societal broader impacts including broadening HPC literacy of underrepresented minorities and training the future NJ workforce using HPC in the classroom and development of new undergraduate and graduate curricula.PRICE will comprise 60 compute nodes (52 cores/node), 700 TB of redundant storage and one GPU node (4 GPUs/node) to be housed at Rutgers University-Newark. PRICE will enable several additional research projects carried out by the PI, co-PIs, and major users at Rutgers-Newark and NJIT. The GPU portion enables state-of-the-art molecular dynamics simulations that elucidate structure and dynamics of proteins for the understanding of diseases, such as Alzheimer’s. GPUs also enable the efficient and timely execution of cooperative AI algorithms aimed at improving predictivity. The CPU nodes will enable quantum simulations aimed at materials engineering through density-functional theory calculations. These simulations facilitate the development of quantum models based on density functional theory, its subsystem formulation (which parallelizes efficiently over PRICE’s low-latency network) as well as quantum mechanical frameworks based on the exact factorization of the Schrödinger equation for multicomponent systems. CPU and GPU nodes will enable data analysis associated with neuroscience experiments aimed at uncovering how the brain modulates behavior and vision-related tasks as well as the study of neuron connectivity to understand brain function. Data from these experiments is growing exponentially due to increased instrument data flow from new fMRI units and improved technology allowing recordings of local field potentials from hundreds on neurons. The project also enables new science as well as the realization of societal broader impacts, such as broadening high-performance computing literacy of underrepresented minorities, training the future NJ workforce and recruitment of new faculty.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.