课题基金 / 基金详情

MRI: Acquisition of an Advanced Computing Instrument to Integrate Data-Driven Research and Data intensive computing at Johns Hopkins University

MRI: Acquisition of an Advanced Computing Instrument to Integrate Data-Driven Research and Data intensive computing at Johns Hopkins University
MRI:约翰·霍普金斯大学购买先进计算仪器以集成数据驱动研究和数据密集型计算
批准号:
1920103
负责人:
Dennice Gayme
金额:
$279.5万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-10-01 至 2022-09-30

项目摘要

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中文摘要
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英文摘要
The project funds the purchase of a high-performance computing and storage system to create a Data Intensive Scientific Computing (DISCO) environment that will be located at Johns Hopkins University (JHU). DISCO will support research in a range of science and engineering areas including wind energy, ocean circulation, materials by design, additive manufacturing, big data, genomics, and biological function on membrane to organ scales. It provides a framework for creating new data from simulations, analyzing data, and making data available for analysis by remote users. DISCO will also enable the development and sharing of new code and data analysis methods across institutions. This project addresses two of NSF's big ideas: Growing Convergence Research and Harnessing the Data Revolution, as well as the Materials Genome initiative. DISCO will immediately support over 40 faculty research projects involving over 200 scientists. DISCO will be managed in collaboration with Morgan State University, a historically black university, which will be allocated at least 5% of resources to support its educational and computational research programs. Other users nationally will be offered 20% of the resources to be managed through a partnership with XSEDE. Opportunities for training on a diverse set of scientific computing topics will be directly integrated into regular courses across JHU and Morgan State. Courses on computational chemistry, genomics, molecular dynamics, machine learning and protein chemistry are planned. Course materials will be made available through the web and the existing set of Massive Open Online Courses (MOOCs) at JHU will be expanded. These materials will ensure training in the proper use of resources, share best practices between different disciplines and promote interdisciplinary collaboration.The objective of this Major Research Instrumentation (MRI) project is to create a Data Intensive Scientific Computing (DISCO) environment that integrates high performance computing with tools for generating, analyzing and disseminating data sets of ever increasing size. The cluster will contain over 5 petabytes of storage and heterogeneous compute nodes optimized for different research projects and complex, optimized work flows: standard dual processor nodes, large memory nodes, and Graphics Processing Unit (GPU) enhanced nodes. An instance of SciServer software will enhance analysis and provide a platform for disseminating data through a web portal. This robust capability will become a powerful resource for developing and sharing code and infrastructure tools used by interdisciplinary data scientists at Johns Hopkins University, Morgan State University and beyond. DISCO will enable computational fluid dynamics studies of wind farms, ocean flow and physiological fluid dynamics. Research in multiscale modeling of materials will use machine learning to tailor material properties and integrate physical models at different scales to improve performance of additive manufacturing and connect defects and microstructures to macroscopic performance of crystals, polymers and other soft materials. DISCO will also enable sequencing of new genomes, study of variance within species and research on the microbiome. On larger scales, research on the dynamics of biological systems will examine function of proteins, membranes, cells and organs, including the impact of nanoparticles on function. This new integrated environment will reshape computational research practices and will be conducive to radical transformative research.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(26)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1063/5.0042573
发表时间: 2020-09
期刊: Journal of Renewable and Sustainable Energy
影响因子: 2.5
作者: [Genevieve M. Starke;C. Meneveau;J. King;D. Gayme]
通讯作者: Genevieve M. Starke;C. Meneveau;J. King;D. Gayme
DOI: 10.1016/j.isci.2021.102696
发表时间: 2021-06-25
期刊: iScience
影响因子: 5.8
作者: [Ahmed O, Rossi M, Kovaka S, Schatz MC, Gagie T, Boucher C, Langmead B]
通讯作者: Langmead B
DOI: 10.1186/s12859-019-3208-4
发表时间: 2019-12-17
期刊: BMC BIOINFORMATICS
影响因子: 3
作者: [Aganezov, Sergey, Zban, Ilya, Schatz, Michael C.]
通讯作者: Schatz, Michael C.
DOI: 10.1093/bioinformatics/btaa911
发表时间: 2021-03-15
期刊: BIOINFORMATICS
影响因子: 5.8
作者: [Kirsche, Melanie, Das, Arun, Schatz, Michael C.]
通讯作者: Schatz, Michael C.
8
    Travel Support for the 2022 American Control Conference; Atlanta, Georgia; June 8-10, 2022
    • 批准号:
      2218987
    • 项目类别:
      Standard Grant
    • 资助金额:
      $1.48万
    • 财政年份:
      2022
    • 负责人:
      Dennice Gayme
    • 依托单位:
    Collaborative Research: Empowering Next Generation Offshore Wind Farms Through Systematic Characterization of Floating Wind Turbine Array Dynamics
    • 批准号:
      2034111
    • 项目类别:
      Standard Grant
    • 资助金额:
      $33.81万
    • 财政年份:
      2021
    • 负责人:
      Dennice Gayme
    • 依托单位:
    CAREER: The restricted nonlinear framework: A new paradigm for modeling, analysis and control of wall-bounded turbulent flows
    • 批准号:
      1652244
    • 项目类别:
      Standard Grant
    • 资助金额:
      $53.15万
    • 财政年份:
      2017
    • 负责人:
      Dennice Gayme
    • 依托单位:
    Modeling, Analysis and Control Design for Spatially Distributed Systems with Application to Wind Farms
    • 批准号:
      1635430
    • 项目类别:
      Standard Grant
    • 资助金额:
      $32.43万
    • 财政年份:
      2016
    • 负责人:
      Dennice Gayme
    • 依托单位:
    海外基金