MRI: Acquisition of a High-Performance Computing System for Scientific Research and Education at NDSU

MRI：NDSU 采购用于科学研究和教育的高性能计算系统

• 批准号: 2019077
• 负责人: Bakhtiyor Rasulev
• 金额: $ 88.46万
• 依托单位: North Dakota State University Fargo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2019077&HistoricalAwards=false
• 关键词: MRI; Acquisition; Performance; Computing; System

This award to North Dakota State University (NDSU) funds the acquisition and commissioning of a high-performance computing (HPC) instrument that will significantly expand and update the resources at NDSU and in the state of North Dakota for scientific research and education. The HPC system will provide a state-wide regional resource giving faculty and students of the North Dakota University System (NDUS) appropriate infrastructure to engage efficiently in challenging research that requires parallel computing. It will facilitate hands-on training in HPC techniques for large-scale compute- and data-intensive analyses. The new computing facility is essential to the growing spectrum of research and training activities and will be used to foster collaborative relationships with research and education partners within North Dakota as well as nationally and internationally. At NDSU and beyond, the new HPC system will enable cutting-edge research in multiple areas, including fluid dynamics, biomedical engineering, physics, chemistry, materials science and engineering, precision agriculture, plant sciences and plant pathology, artificial intelligence, health care, and financial and business analytics. Beyond NDSU, the new instrument will provide HPC resources to researchers and students at the tribal colleges (TCs) in the state of North Dakota and the primarily undergraduate institutions (PUIs) and Master’s colleges/universities (MCUs) within NDUS. Continuing present outreach activities is planned to stimulate interest in science and engineering within the state.The project will provide a new instrument that consists of a fast, tiered storage subsystem with a parallel file system and a distributed memory hybrid HPC cluster (CPUs, GPUs, big-memory nodes, and high speed interconnect) specifically designed to efficiently process massive amounts of data as well as handle compute-intensive applications. The compute nodes will be capable of a combined theoretical peak performance of 98 TFLOPS whilst using 64-bit double precision GPUs will lead to a combined theoretical peak of 140 TFLOPS. This gives a total peak performance of 238 TFLOPS for the compute cluster. The research projects undertaken by the research groups will contribute to multiple fields, including those listed above. Consequently, more than 15 NDSU lead computational researchers and their groups (100+ scientists and students) have joined in this project to use an extensible HPC instrument architected for enhanced support for modeling, data collection, generation, analysis, storage, provenance, curation, and sharing. The PIs of the project will integrate students into their research projects and incorporate HPC into several graduate and undergraduate courses. Training workshop series and internship opportunities to train students and research staff in computational research using HPC will also be provided and supported by the commissioning and operations of this instrument. This will provide an excellent opportunity to train the next generation of HPC systems specialists. This award by the Office of Advanced Cyberinfrastructure (OAC) is jointly funded with the Division of Materials Research (DMR), part of the Mathematical and Physical Sciences Directorate, 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.

授予北达科他州州立大学（NDSU）的这项奖项为高性能计算（HPC）仪器的采购和调试提供资金，该仪器将显着扩展和更新NDSU和北达科他州的科学研究和教育资源。HPC系统将提供全州范围的区域资源，为北达科他州大学系统（NDUS）的教师和学生提供适当的基础设施，以有效地参与需要并行计算的具有挑战性的研究。它将促进用于大规模计算和数据密集型分析的HPC技术的实践培训。新的计算设施是必不可少的研究和培训活动的不断增长的频谱，并将用于促进与北达科他州以及国内和国际的研究和教育合作伙伴的合作关系。在NDSU及其他地方，新的HPC系统将支持多个领域的尖端研究，包括流体动力学，生物医学工程，物理，化学，材料科学与工程，精准农业，植物科学和植物病理学，人工智能，医疗保健以及财务和商业分析。除了NDSU，新仪器还将为北达科他州部落学院（TC）的研究人员和学生以及NDUS内的主要本科院校（PUI）和硕士学院/大学（MCU）提供HPC资源。该项目将提供一种新的仪器，包括一个快速的分层存储子系统和一个并行文件系统，以及一个分布式内存混合HPC集群（CPU、GPU、大内存节点和高速互连），专门设计用于有效处理大量数据以及处理计算密集型应用程序。计算节点将能够实现98 TFLOPS的综合理论峰值性能，而使用64位双精度GPU将导致140 TFLOPS的综合理论峰值。这为计算集群提供了238 TFLOPS的总峰值性能。研究小组开展的研究项目将有助于多个领域，包括上述领域。因此，超过15名NDSU首席计算研究人员及其团队（100多名科学家和学生）加入了该项目，使用可扩展的HPC工具，该工具旨在增强对建模，数据收集，生成，分析，存储，出处，策展和共享的支持。该项目的PI将使学生融入他们的研究项目，并将HPC纳入多门研究生和本科生课程中。还将提供培训讲习班系列和实习机会，以培训学生和研究人员使用HPC进行计算研究，并通过该仪器的调试和运行提供支持。这将为培养下一代HPC系统专家提供绝佳的机会。该奖项由高级网络基础设施办公室（OAC）与材料研究部（DMR）、数学和物理科学理事会的一部分以及刺激竞争性研究的既定计划（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。

项目成果

Quantitative Structure─Permittivity Relationship Study of a Series of Polymers

系列聚合物的定量结构—介电常数关系研究

• DOI: 10.1021/acsmaterialsau.3c00079
• 发表时间: 2024
• 期刊: ACS Materials Au
• 作者: Zhuravskyi, Yevhenii;Iduoku, Kweeni;Erickson, Meade E.;Karuth, Anas;Usmanov, Durbek;Casanola-Martin, Gerardo;Sayfiyev, Maqsud N.;Ziyaev, Dilshod A.;Smanova, Zulayho;Mikolajczyk, Alicja
• 通讯作者: Mikolajczyk, Alicja

Rare-earth defects in GaN: A systematic investigation of the lanthanide series

GaN 中的稀土缺陷：对镧系元素的系统研究

• DOI: 10.1103/physrevmaterials.6.044601
• 发表时间: 2022
• 期刊: Physical Review Materials
• 影响因子: 3.4
• 作者: Hoang, Khang

Manipulating Conjugated Polymer Backbone Dynamics through Controlled Thermal Cleavage of Alkyl Side Chains

通过烷基侧链的受控热裂解控制共轭聚合物主链动力学

• DOI: 10.1002/marc.202200533
• 发表时间: 2022
• 期刊: Macromolecular Rapid Communications
• 影响因子: 4.6
• 作者: Zhao, Haoyu;Shanahan, Jordan J.;Samson, Stephanie;Li, Zhaofan;Ma, Guorong;Prine, Nathaniel;Galuska, Luke;Wang, Yunfei;Xia, Wenjie;You, Wei
• 通讯作者: You, Wei

Computational Methods for Fluid-Structure Interaction Simulation of Heart Valves in Patient-Specific Left Heart Anatomies

• DOI: 10.3390/fluids7030094
• 发表时间: 2022-03
• 期刊: Fluids
• 影响因子: 1.9
• 作者: T. Le;M. Usta;C. Aidun;A. Yoganathan;F. Sotiropoulos

A Hybrid Continuum-Particle Approach for Fluid-Structure Interaction Simulation of Red Blood Cells in Fluid Flows

• DOI: 10.3390/fluids6040139
• 发表时间: 2021-04
• 期刊: Fluids
• 影响因子: 1.9
• 作者: Lahcen Akerkouch;T. Le