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

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
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-10-01 至 2023-09-30

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英文摘要
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.
期刊论文(32)
专著(0)
科研奖励(0)
会议论文
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
影响因子: --
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]
通讯作者: 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
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]
通讯作者: T. Le;M. Usta;C. Aidun;A. Yoganathan;F. Sotiropoulos
17
    RII Track-4: NSF: Data-driven Computational and Machine Learning Assessment of Structure-Toxicity Relationship of Micro/NanoPlastics
    • 批准号:
      2229755
    • 项目类别:
      Standard Grant
    • 资助金额:
      $19.18万
    • 财政年份:
      2023
    • 负责人:
      Bakhtiyor Rasulev
    • 依托单位:
    D3SC: Integrated Studies on Designing Organometallic Complexes with Nonlinear Absorption and Near-Infrared Emission
    • 批准号:
      1800476
    • 项目类别:
      Standard Grant
    • 资助金额:
      $46.8万
    • 财政年份:
      2018
    • 负责人:
      Bakhtiyor Rasulev
    • 依托单位:
    海外基金