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.

该奖项授予北达科他州立大学（NDUS）为高性能计算（HPC）工具提供了收购和调试，该工具将大大扩展和更新NDSU和北达科他州的科学研究和教育。 HPC系统将提供全州的区域资源，为北达科他大学系统（NDUS）的教职员工和学生提供适当的基础设施，以有效地参与需要平行计算的挑战研究。它将在HPC技术中进行实践培训，以进行大规模计算和数据密集型分析。新的计算设施对于不断增长的研究和培训活动至关重要，将用于与北达科他州以及国际和国际上的研究和教育伙伴建立合作关系。在NDSU及其他地区，新的HPC系统将在多个领域进行尖端研究，包括流体动力学，生物医学工程，物理，化学，材料科学和工程，精密农业，植物科学和植物病理学，人工智能，医疗保健以及金融和商业分析。除了NDSU之外，新工具还将为北达科他州部落学院（TCS）的研究人员和学生提供HPC资源，以及NDUS内的主要本科机构（PUIS）和硕士学院/大学（MCUS）。计划持续进行目前的宣传活动以激发该州内科学和工程的兴趣。该项目将提供一种新工具，该工具由具有并行文件系统和分布式内存混合HPC群集（CPU，GPU，GPU，GPU，GPU，Big-Memory Nodes，高速互连接）组成的快速构成，以高度处理大量的数据，并进行了多种多样的数据。计算节点将能够具有98个TFLOPS的总理论峰性能，而使用64位双精度GPU将导致140个TFLOPS的合并理论峰。对于计算集群，这给出了238个TFLOPS的总峰值性能。研究小组进行的研究项目将为多个领域（包括上面列出的领域）做出贡献。因此，超过15个NDSU的主要计算研究人员及其小组（100多名科学家和学生）加入了该项目，使用广泛的HPC仪器架构，以增强对建模，数据收集，生成，分析，存储，存储，出处，策划和共享的支持。该项目的PI将将学生整合到他们的研究项目中，并将HPC纳入多个研究生和本科课程。培训研讨会系列和实习机会也将由本仪器的调试和运作提供和支持使用HPC计算研究的学生和研究人员。这将为培训下一代HPC系统专家提供绝佳的机会。高级网络基础设施办公室（OAC）的奖项由材料研究部（DMR），数学和物理科学局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的法定任务，并通过评估了基金会的智力效果，并诚实地对其进行了评估。

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