MRI: Acquisition of FASTER - Fostering Accelerated Sciences Transformation Education and Research
MRI:收购 FASTER - 促进加速科学转型教育和研究
基本信息
- 批准号:2019129
- 负责人:
- 金额:$ 309万
- 依托单位:
- 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:2020-09-01 至 2024-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The project funds the acquisition of a composable high-performance data-analysis and computing instrument, named FASTER (Fostering Accelerated Scientific Transformations, Education, and Research). FASTER will enable transformative advances in scientific fields that rely on artificial intelligence and machine learning (AI/ML) techniques, big data practices, and high-performance computing (HPC) technologies. The FASTER platform removes significant bottlenecks in research computing by leveraging a technology that can dynamically allocate resources to support workflows. It will support researchers from across the Texas A&M University System and their collaborating institutions. Thirty percent of FASTER’s computing resources will also be allocated to researchers nationwide by the National Science Foundation (NSF) XSEDE (Extreme Science and Engineering Discovery Environment) program. FASTER’s composable interface allows it to simultaneously support both emerging and traditional workloads in research computing. Transformative research projects benefiting from FASTER will include the development of AI/ML models, cybersecurity, health population informatics, genomics, bioinformatics, computer-aided drug design, agricultural sciences, life sciences, oil and gas simulations, de novo materials design, climate modeling, multi-scale simulations, quantum computing architectures, biomedical imaging, geosciences, and quantum chemistry. In addition to supporting a wide-range of fields of research, the project contributes to code development, education, and the workforce development goals of several NSF Big Ideas.FASTER adopts the innovative Liqid composable software-hardware approach combined with cutting-edge technologies such as state of the art CPUs and GPUs, NVMe (Non-Volatile Memory Express) based storage, and thigh speed interconnect. Workflows on FASTER will be able to dynamically integrate disaggregated GPUs and NVMe to compose a single node, allowing them to scale beyond traditional hardware limits. The composable and configurable techniques will allow researchers to use resources efficiently, enabling more science. Best practices gathered from managing the resource will be shared with the community. FASTER will coordinate a three-pronged effort to effectively broaden participation in computing by focusing on training, education and outreach. FASTER will leverage existing efforts that promote STEM (Science, Technology, Engineering and Mathematics) and broaden participation in computing at the K-12, collegiate, and professional levels to have a transformative impact nationally. FASTER activities are designed to expand the participation of traditionally underrepresented groups in computing and STEM, particularly at minority-serving institutions.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.
该项目资助了一个可组合的高性能数据分析和计算工具,名为FASTER(促进加速科学变革,教育和研究)。FASTER将在依赖人工智能和机器学习(AI/ML)技术、大数据实践和高性能计算(HPC)技术的科学领域实现变革性进步。FASTER平台通过利用可以动态分配资源以支持工作流程的技术,消除了研究计算中的重大瓶颈。它将支持来自德克萨斯州A M大学系统及其合作机构的研究人员。 FASTER 30%的计算资源也将通过美国国家科学基金会(NSF)XSEDE(极端科学与工程发现环境)计划分配给全国的研究人员。FASTER的可组合接口使其能够同时支持研究计算中的新兴和传统工作负载。受益于FASTER的变革性研究项目将包括AI/ML模型的开发,网络安全,健康人口信息学,基因组学,生物信息学,计算机辅助药物设计,农业科学,生命科学,石油和天然气模拟,从头材料设计,气候建模,多尺度模拟,量子计算架构,生物医学成像,地球科学和量子化学。除了支持广泛的研究领域外,该项目还为代码开发、教育和NSF几个大创意的劳动力发展目标做出了贡献。FASTER采用创新的Liquid可组合软硬件方法,结合尖端技术,如最先进的CPU和GPU、基于NVMe(Non-Volatile Memory Express)的存储和大腿速度互连。FASTER上的工作流将能够动态集成分散的GPU和NVMe,以组成单个节点,使它们能够超越传统的硬件限制。可组合和可配置的技术将使研究人员能够有效地使用资源,从而实现更多的科学。从管理资源中收集的最佳做法将与社区分享。FASTER将协调一项三管齐下的努力,通过侧重于培训、教育和外联,有效地扩大对计算的参与。FASTER将利用现有的促进STEM(科学,技术,工程和数学)的努力,并扩大K-12,大学和专业水平的计算参与,以在全国范围内产生变革性的影响。FASTER活动旨在扩大传统上代表性不足的群体在计算和STEM领域的参与,特别是在少数民族服务机构。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
期刊论文数量(3)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Regional Collaborations Supporting Cyberinfrastructure-Enabled Research During a Pandemic: The Structure and Support Plan of the SWEETER CyberTeam
大流行期间支持网络基础设施研究的区域合作:SWEETER CyberTeam 的结构和支持计划
- DOI:10.1145/3491418.3535186
- 发表时间:2022
- 期刊:
- 影响因子:0
- 作者:Medina-Gurrola, Edmundo;Chakravorty, Dhruva K.;Dugas, Diana V.;Cockerill, Tim;Perez, Lisa M.;Hunt, Emily
- 通讯作者:Hunt, Emily
Benchmarking the Performance of Accelerators on National Cyberinfrastructure Resources for Artificial Intelligence / Machine Learning Workloads
- DOI:10.1145/3491418.3530772
- 发表时间:2022-07
- 期刊:
- 影响因子:0
- 作者:Abhinand Nasari;Hieu Hanh Le;Richard Lawrence;Zhenhua He;Xin Yang;Mario Krell;A. Tsyplikhin;M. Tatineni;Tim Cockerill;Lisa M. Perez;Dhruva K. Chakravorty;Honggao Liu
- 通讯作者:Abhinand Nasari;Hieu Hanh Le;Richard Lawrence;Zhenhua He;Xin Yang;Mario Krell;A. Tsyplikhin;M. Tatineni;Tim Cockerill;Lisa M. Perez;Dhruva K. Chakravorty;Honggao Liu
Expanding the Reach of Research Computing: A Landscape Study: Pathways Bringing Research Computing to Smaller Universities and Community Colleges
扩大研究计算的范围:景观研究:将研究计算引入小型大学和社区学院的途径
- DOI:10.1145/3491418.3535169
- 发表时间:2022
- 期刊:
- 影响因子:0
- 作者:Chakravorty, Dhruva;Janes, Sarah;Howell, James;Perez, Lisa;Schultz, Amy;Goldie, Marie;Gamble, Austin;Malkan, Rajiv;Liu, Honggao;Mireles, Daniel
- 通讯作者:Mireles, Daniel
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Honggao Liu其他文献
Rapid and accurate identification of <em>Gastrodia elata</em> Blume species based on FTIR and NIR spectroscopy combined with chemometric methods
- DOI:
10.1016/j.talanta.2024.126910 - 发表时间:
2025-01-01 - 期刊:
- 影响因子:
- 作者:
Guangyao Li;Jieqing Li;Honggao Liu;Yuanzhong Wang - 通讯作者:
Yuanzhong Wang
Effect of drying temperature on composition of edible mushrooms: Characterization and assessment via HS-GC-MS and IR spectral based volatile profiling and chemometrics
- DOI:
10.1016/j.crfs.2024.100819 - 发表时间:
2024-01-01 - 期刊:
- 影响因子:
- 作者:
Chuanmao Zheng;Jieqing Li;Honggao Liu;Yuanzhong Wang - 通讯作者:
Yuanzhong Wang
Rapid and non-invasive estimation of total phenol content and species identification in dried wild edible bolete using FT-NIR spectroscopy
- DOI:
10.1016/j.arabjc.2024.106011 - 发表时间:
2024-12-01 - 期刊:
- 影响因子:
- 作者:
Chuanmao Zheng;Jieqing Li;Honggao Liu;Yuanzhong Wang - 通讯作者:
Yuanzhong Wang
Leucocalocybe mongolica Fungus Enhances Rice Growth by Reshaping Root Metabolism, and Hormone-Associated Pathways
- DOI:
10.1186/s12284-025-00813-4 - 发表时间:
2025-06-16 - 期刊:
- 影响因子:5.000
- 作者:
Mingzheng Duan;Ming Tao;Fuhan Wei;Honggao Liu;Sirui Han;Jieming Feng;Qiuyue Ran;Xiande Duan;Zhifang He;Shunqiang Yang;Muhammad Junaid Rao - 通讯作者:
Muhammad Junaid Rao
Numerical studies of reactive polymer flows in porous materials
多孔材料中反应性聚合物流动的数值研究
- DOI:
10.31390/gradschool_dissertations.1065 - 发表时间:
2002 - 期刊:
- 影响因子:0
- 作者:
Honggao Liu - 通讯作者:
Honggao Liu
Honggao Liu的其他文献
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{{ truncateString('Honggao Liu', 18)}}的其他基金
Category II: ACES - Accelerating Computing for Emerging Sciences
类别 II:ACES - 加速新兴科学的计算
- 批准号:
2112356 - 财政年份:2021
- 资助金额:
$ 309万 - 项目类别:
Cooperative Agreement
CC-NIE Network Infrastructure: CADIS -- Cyberinfrastructure Advancing Data-Interactive Sciences
CC-NIE 网络基础设施:CADIS——推动数据交互科学的网络基础设施
- 批准号:
1246443 - 财政年份:2013
- 资助金额:
$ 309万 - 项目类别:
Standard Grant
HPCOPS: The LONI Grid - Leveraging HPC Resources of the Louisiana Optical Network Initiative for Science and Engineering Research and Education
HPCOPS:LONI 网格 - 利用路易斯安那光网络计划的 HPC 资源进行科学和工程研究与教育
- 批准号:
0710874 - 财政年份:2007
- 资助金额:
$ 309万 - 项目类别:
Cooperative Agreement
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