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

MRI：罗格斯大学纽瓦克分校采购高性能计算集群用于研究和教学

基本信息

批准号：
2117429
负责人：
Michele Pavanello
金额：
$ 55.93万
依托单位：
Rutgers University Newark
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-10-01 至 2024-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2117429&HistoricalAwards=false
关键词：
MRI Acquisition Performance Computing Cluster

项目摘要

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.

该奖项授予罗格斯大学 - 纽瓦克大学，支持收购和部署高性能计算（HPC）集群（命名为价格），致力于研究，教学和社会推广工作。价格将具有60个通用计算（CPU）节点和一个图形处理单元（GPU）节点，以及适合于机器寿命中计划使用的存储。启用了沿三个主要方向的研究发展：原子建模，神经科学和数据科学。价格实现的一些原子模型将研究蛋白质的结构和动态，以解决与阿尔茨海默氏病有关的疾病有关的问题。新材料建模和设计都是通过价格和开发新的量子模拟方法来实现的。启用模拟还将通过遗传算法涉及新材料设计。启用神经科学研究考虑了实验数据的计算分析，以了解大脑功能，连通性和人类行为。启用的数据科学研究包括新型合作人工智能（AI）算法的公式，这些算法将改善广泛适用性的机器学习（ML）模型的结果。除了启用新科学外，该项目还实现了几种社会的更广泛的影响，包括扩大代表性不足的少数群体的HPC素养和培训未来在课堂上使用HPC使用HPC的NJ劳动力以及新的本科和研究生货币的发展。罗格斯大学 - 纽瓦克。 Price将使PI，Co-Pis以及Rutgers-Newark和NJIT的主要用户进行其他几项研究项目。 GPU部分可以实现最先进的分子动力学模拟，从而阐明蛋白质的结构和动力学，以理解诸如阿尔茨海默氏病的疾病。 GPU还使旨在提高预测性的合作AI算法的有效，及时执行。 CPU节点将通过密度功能理论计算实现针对材料工程的量子模拟。这些仿真支持基于密度功能理论的量子模型的开发，其子系统公式（在Price的低路线网络上有效地平行）以及基于多组分系统的Schrödinger方程的精确分解的量子机械框架。 CPU和GPU节点将启用与旨在发现大脑如何调节行为和视力相关任务的神经科学实验以及神经元连接性研究以了解大脑功能的研究分析。这些实验的数据是由于新的fMRI单元的仪器数据流增加以及改进的技术，从而使数百个神经元上的局部现场电位记录。该项目还可以实现新的科学以及社会广泛影响的实现，例如扩大代表性不足的少数群体的高绩效计算素养，培训未来的NJ劳动力和新教师的招聘。该奖项反映了NSF的法规使命，并认为通过基金会的知识绩效和广泛的范围进行评估，这是值得通过评估来进行评估的。

项目成果

期刊论文数量（10）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Explainable AI for medical imaging: Explaining pneumothorax diagnoses with Bayesian Teaching

DOI：
10.1117/12.2585967
发表时间：
2021-01-01
期刊：
ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING FOR MULTI-DOMAIN OPERATIONS APPLICATIONS III
影响因子：
0
作者：
Folke, Tomas;Yang, Scott Cheng-Hsin;Shafto, Patrick
通讯作者：
Shafto, Patrick

Entropy is a good approximation to the electronic (static) correlation energy

熵是电子（静态）相关能的良好近似

DOI：
10.1063/5.0171981
发表时间：
2023
期刊：
The Journal of Chemical Physics
影响因子：
0
作者：
Martinez B, Jessica A.;Shao, Xuecheng;Jiang, Kaili;Pavanello, Michele
通讯作者：
Pavanello, Michele

Orbital-Free Density Functional Theory: An Attractive Electronic Structure Method for Large-Scale First-Principles Simulations

DOI：
10.1021/acs.chemrev.2c00758
发表时间：
2023-10-23
期刊：
CHEMICAL REVIEWS
影响因子：
62.1
作者：
Mi，Wenhui;Luo，Kai;Pavanello，Michele
通讯作者：
Pavanello，Michele

Which Physical Phenomena Determine the Ionization Potential of Liquid Water?

哪些物理现象决定液态水的电离势？

DOI：
10.1021/acs.jpcb.2c07639
发表时间：
2023
期刊：
The Journal of Physical Chemistry B
影响因子：
0
作者：
Martinez B, Jessica A.;Paetow, Lukas;Tölle, Johannes;Shao, Xuecheng;Ramos, Pablo;Neugebauer, Johannes;Pavanello, Michele
通讯作者：
Pavanello, Michele

Sequential cooperative Bayesian inference

顺序合作贝叶斯推理