MRI: Acquisition of FASTER - Fostering Accelerated Sciences Transformation Education and Research
MRI: Acquisition of FASTER - Fostering Accelerated Sciences Transformation Education and Research
批准号:
2019129
负责人:
Honggao Liu
金额:
$309.0万
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
项目状态:
已结题
起止时间:
2020-09-01 至 2024-08-31
中文摘要
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英文摘要
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.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
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:
PEARC '22: Practice and Experience in Advanced Research Computing
影响因子:
--
作者:
[Medina-Gurrola, Edmundo, Chakravorty, Dhruva K., Dugas, Diana V., Cockerill, Tim, Perez, Lisa M., Hunt, Emily]
通讯作者:
Hunt, Emily
DOI:
10.1145/3491418.3530772
发表时间:
2022-07
期刊:
Practice and Experience in Advanced Research Computing
影响因子:
--
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:
PEARC '22: Practice and Experience in Advanced Research Computing
影响因子:
--
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
Category II: ACES - Accelerating Computing for Emerging Sciences
-
批准号:2112356
-
项目类别:Cooperative Agreement
-
资助金额:$500.0万
-
财政年份:2021
-
负责人:Honggao Liu
-
依托单位:
CC-NIE Network Infrastructure: CADIS -- Cyberinfrastructure Advancing Data-Interactive Sciences
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批准号:1246443
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项目类别:Standard Grant
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资助金额:$49.98万
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财政年份:2013
-
负责人:Honggao Liu
-
依托单位:
HPCOPS: The LONI Grid - Leveraging HPC Resources of the Louisiana Optical Network Initiative for Science and Engineering Research and Education
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批准号:0710874
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项目类别:Cooperative Agreement
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资助金额:$220.0万
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财政年份:2007
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负责人:Honggao Liu
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依托单位:
海外基金