CC* Regional Computing: Great Plains Extended Network of GPUs for Interactive Experimenters (GP-ENGINE)
CC* 区域计算:用于交互式实验者的 Great Plains GPU 扩展网络 (GP-ENGINE)
基本信息
- 批准号:2322218
- 负责人:
- 金额:$ 98.12万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-07-01 至 2025-06-30
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
The GP-ENGINE project advances the adoption of advanced computing and data resources in the Great Plains Network region. This project will increase the number of researchers and students served by both local and national computing resources, strengthen the capacity and capabilities of campus research computing professionals, and expand the regional capacity for research. Researchers will be able to transition nascent ideas and codes into advanced computing code using locally provisioned advanced computing resources. These codes can be later executed on national high-throughput computing resources. These successes will enhance institutional buy-in for sustainable regional and national research computing systems.The project leverages strong existing collaborations to provision and manage graphics processing unit resources in Missouri, North Dakota, South Dakota, Kansas, Oklahoma, and Arkansas. It trains and supports researchers to adapt their workbench codes into high-throughput computing codes that can be executed on national platforms such as the Open Science Grid and the National Research Platform. The project addresses computing needs of a diverse set of science drivers from across the consortium, including problems in 3D protein molecule generation, satellite image deep learning for wildfire burn area mapping, dark matter and neutrino detection, real-time monitoring of land surface phenology, cybersecurity attack graph generation, and intelligent manufacturing with digital twins. The project improves STEM research and education through adoption of JupyterLab computing notebooks. The deployed cyberinfrastructure supports research and education in a region whose sparse population and geographic size are ideal for developing advanced computing, data, and networking in under-resourced EPSCoR states.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.
GP-ENGINE项目推动了大平原网络地区先进计算和数据资源的采用。 该项目将增加由地方和国家计算资源服务的研究人员和学生人数,加强校园研究计算专业人员的能力,并扩大区域研究能力。研究人员将能够使用本地提供的高级计算资源将新生的想法和代码转换为高级计算代码。 这些代码以后可以在国家高吞吐量计算资源上执行。这些成功将增强可持续的区域和国家研究计算系统的机构购买。该项目利用强大的现有合作来提供和管理密苏里州、北达科他州、南达科他州、堪萨斯、俄克拉荷马州和阿肯色州的图形处理单元资源。它培训和支持研究人员将他们的工作台代码调整为可以在开放科学网格和国家研究平台等国家平台上执行的高吞吐量计算代码。该项目解决了来自整个联盟的各种科学驱动因素的计算需求,包括3D蛋白质分子生成,野火燃烧区域映射的卫星图像深度学习,暗物质和中微子检测,陆地表面物候的实时监测,网络安全攻击图生成以及数字双胞胎的智能制造。 该项目通过采用QuixyterLab计算笔记本电脑来改善STEM研究和教育。部署的网络基础设施支持该地区的研究和教育,该地区人口稀少,地理面积小,非常适合在资源不足的EPSCoR州开发先进的计算、数据和网络。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(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Grant Scott其他文献
Clinical Outcome of Drug-Eluting Balloon Angioplasty in Patients With Femoropopliteal Disease: Real-World Single Center Experience
- DOI:
10.1016/j.jvs.2018.10.022 - 发表时间:
2019-01-01 - 期刊:
- 影响因子:
- 作者:
Ali F. AbuRahma;Zachary AbuRahma;Grant Scott;Elliot Adams;Matthew Beasley;Meghan Davis;L. Scott Dean;Elaine Davis - 通讯作者:
Elaine Davis
RS07. The Incidence of Carotid In-Stent Stenosis Is Underestimated: Is It 50% or 80% and Its Clinical Implications
- DOI:
10.1016/j.jvs.2018.03.241 - 发表时间:
2018-06-01 - 期刊:
- 影响因子:
- 作者:
Ali F. AbuRahma;Zachary T. AbuRahma;Elliot Adams;Luis Mata;Grant Scott;Matthew Beasley;Scott Dean;Elaine Davis - 通讯作者:
Elaine Davis
Grant Scott的其他文献
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{{ truncateString('Grant Scott', 18)}}的其他基金
CC* Team: Great Plains Regional CyberTeam
CC* 团队:Great Plains 区域网络团队
- 批准号:
1925681 - 财政年份:2019
- 资助金额:
$ 98.12万 - 项目类别:
Continuing Grant
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