Collaborative Research: CyberTraining: Pilot: Research Workforce Development for Deep Learning Systems in Advanced GPU Cyberinfrastructure
协作研究:网络培训:试点:高级 GPU 网络基础设施中深度学习系统的研究人员开发
基本信息
- 批准号:2230098
- 负责人:
- 金额:$ 9.87万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-12-01 至 2023-06-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
With the recent advancements in artificial intelligence, deep learning systems and applications have become a driving force in multiple transdisciplinary domains. While this evolution has been largely supported by the rapid improvements in advanced GPU cyberinfrastructure, comprehensive training materials are generally absent that combine application-driven deep learning techniques with the implementation of such techniques using the GPU cyberinfrastructure. To fill in this gap, this project develops an online workshop that comprises of a set of interdisciplinary cutting-edge training sessions offered by six faculty members from five disciplines. With a focus on the latest innovations in GPU-based deep learning systems and applications, this workshop fosters a community of the next-generation cyberinfrastructure users and contributors, who can use, develop, and improve advanced GPU cyberinfrastructure for their deep learning research. Such training efforts enhance the knowledge of the deep learning and GPU cyberinfrastructure workforce, and subsequently contribute to the solutions of important scientific and societal problems, including hydrographic mapping in geography, space environment nowcasting in aerospace, and autonomous driving and traffic monitoring in transportation. The workshop will also attract trainees from underrepresented groups, including minority students and researchers from rural areas.The interdisciplinary workshop developed in this project aims at enabling participants, including undergraduate seniors, graduate students, and researchers, to improve their multidisciplinary skillsets, extend their academic research portfolios, develop their remote collaboration capacities, and significantly strengthen their career competitiveness. To achieve this goal, the intensive workshop includes 1) a set of hands-on lecture modules that provide trainees with comprehensive knowledge and skills on the full stack of deep learning systems in advanced GPU cyberinfrastructure, 2) a series of talks on the cutting-edge research in advanced GPU cyberinfrastructure and deep learning systems and application given by renowned scientists invited from academic and industrial research institutes, and 3) a remote open-ended interdisciplinary collaborative project of applying techniques introduced in lectures into practice. In addition, a prototype of an interactive online training system is developed to provide computing resources for the trainees and to track their learning progress, for more effective and efficient training activities. The project is expected to develop a future research workforce in deep learning systems and applications and to broaden the adoption of advanced GPU cyberinfrastructure in research and education.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.
随着人工智能的最新进展,深度学习系统和应用已经成为多个跨学科领域的驱动力。虽然先进的图形处理器网络基础设施的快速改进在很大程度上支持了这一演变,但普遍缺乏将应用程序驱动的深度学习技术与利用图形处理器网络基础设施实施这种技术相结合的全面培训材料。为了填补这一空白,该项目开发了一个在线研讨会,其中包括一套由来自五个学科的六名教员提供的跨学科尖端培训课程。本次研讨会聚焦于基于GPU的深度学习系统和应用程序的最新创新,培养了新一代网络基础设施用户和贡献者的社区,他们可以使用、开发和改进先进的GPU网络基础设施,用于他们的深度学习研究。这类培训工作增进了深度学习和GPU网络基础设施工作人员的知识,并随后有助于解决重要的科学和社会问题,包括地理中的水文测绘、航空航天中的空间环境预报以及交通运输中的自动驾驶和交通监测。研讨会还将吸引来自代表性不足群体的学员,包括少数民族学生和来自农村地区的研究人员。该项目开发的跨学科研讨会旨在使参与者,包括本科生、研究生和研究人员,提高他们的多学科技能,扩大他们的学术研究组合,发展他们的远程协作能力,并显著增强他们的职业竞争力。为了实现这一目标,密集的研讨会包括1)一套实践讲座模块,为学员提供先进的GPU网络基础设施中全套深度学习系统的全面知识和技能;2)由学术和工业研究机构邀请的知名科学家举办的关于先进GPU网络基础设施和深度学习系统的前沿研究和应用的一系列讲座;以及3)将讲座中介绍的技术应用于实践的远程开放式跨学科协作项目。此外,还开发了一个交互式在线培训系统的原型,为受训者提供计算资源,并跟踪他们的学习进度,以便更有效和高效地开展培训活动。该项目预计将在深度学习系统和应用程序方面培养一支未来的研究队伍,并扩大在研究和教育中采用先进的GPU网络基础设施。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势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)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Xin Liang其他文献
A remarkable catalyst combination to widen the operating temperature window of the selective catalytic reduction of NO by NH3 (Cover Paper)
一种出色的催化剂组合,可拓宽 NH3 选择性催化还原 NO 的操作温度范围(封面论文)
- DOI:
- 发表时间:
2014 - 期刊:
- 影响因子:4.5
- 作者:
Xin Liang;Biaohua Chen;D. Duprez;S. Royer - 通讯作者:
S. Royer
The reaction of NO + C3H6 + O2 over the mesoporous SBA-15 supported transition metal catalysts
NO C3H6 O2在介孔SBA-15负载过渡金属催化剂上的反应
- DOI:
10.1016/j.cattod.2011.04.014 - 发表时间:
2011-10 - 期刊:
- 影响因子:5.3
- 作者:
Xin Liang;Zhigang Lei;Yanli Zhao;Jun Xue;Dongjun Shi;Biaohua Chen;Runduo Zhang - 通讯作者:
Runduo Zhang
A new high-capacity and safe energy storage system: lithium-ion sulfur batteries
新型大容量安全储能系统:锂离子硫电池
- DOI:
10.1039/c9nr05670j - 发表时间:
2019 - 期刊:
- 影响因子:6.7
- 作者:
Xin Liang;Jufeng Yun;Yong Wang;Hongfa Xiang;Yi Sun;Yuezhan Feng;Yan Yu - 通讯作者:
Yan Yu
The liver X receptors agonist GW3965 attenuates depressive‐like behaviors and suppresses microglial activation and neuroinflammation in hippocampal subregions in a mouse depression model
肝脏 X 受体激动剂 GW3965 可减轻小鼠抑郁模型中的抑郁样行为并抑制海马亚区域的小胶质细胞活化和神经炎症
- DOI:
10.1002/cne.25380 - 发表时间:
2022-06 - 期刊:
- 影响因子:0
- 作者:
Jing Li;Peilin Zhu;Yue Li;Kai Xiao;Jing Tang;Xin Liang;Yanmin Luo;Jin Wang;Yuhui Deng;Lin Jiang;Qian Xiao;Yijing Guo;Yong Tang;Chunxia Huang - 通讯作者:
Chunxia Huang
The effects of fluoxetine on oligodendrocytes in the hippocampus of chronic unpredictable stress-induced depressed model rats
氟西汀对慢性不可预测应激抑郁模型大鼠海马少突胶质细胞的影响
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:0
- 作者:
Jin Wang;Yanmin Luo;Jing Tang;Xin Liang;Chunxia Huang;Yuan Gao;Yingqiang Qi;Chunmao Yang;FengLei Chao;Yang Zhang;Yong Tang - 通讯作者:
Yong Tang
Xin Liang的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Xin Liang', 18)}}的其他基金
RII Track-4: NSF: Scalable MPI with Adaptive Compression for GPU-based Computing Systems
RII Track-4:NSF:适用于基于 GPU 的计算系统的具有自适应压缩的可扩展 MPI
- 批准号:
2327266 - 财政年份:2024
- 资助金额:
$ 9.87万 - 项目类别:
Standard Grant
Collaborative Research: OAC Core: Topology-Aware Data Compression for Scientific Analysis and Visualization
合作研究:OAC 核心:用于科学分析和可视化的拓扑感知数据压缩
- 批准号:
2313122 - 财政年份:2023
- 资助金额:
$ 9.87万 - 项目类别:
Standard Grant
Collaborative Research: Elements: ProDM: Developing A Unified Progressive Data Management Library for Exascale Computational Science
协作研究:要素:ProDM:为百亿亿次计算科学开发统一的渐进式数据管理库
- 批准号:
2311756 - 财政年份:2023
- 资助金额:
$ 9.87万 - 项目类别:
Standard Grant
CRII: OAC: Enabling Quantities-of-Interest Error Control for Trust-Driven Lossy Compression
CRII:OAC:为信任驱动的有损压缩启用感兴趣数量错误控制
- 批准号:
2330367 - 财政年份:2023
- 资助金额:
$ 9.87万 - 项目类别:
Standard Grant
Collaborative Research: CyberTraining: Pilot: Research Workforce Development for Deep Learning Systems in Advanced GPU Cyberinfrastructure
协作研究:网络培训:试点:高级 GPU 网络基础设施中深度学习系统的研究人员开发
- 批准号:
2330364 - 财政年份:2023
- 资助金额:
$ 9.87万 - 项目类别:
Standard Grant
CRII: OAC: Enabling Quantities-of-Interest Error Control for Trust-Driven Lossy Compression
CRII:OAC:为信任驱动的有损压缩启用感兴趣数量错误控制
- 批准号:
2153451 - 财政年份:2022
- 资助金额:
$ 9.87万 - 项目类别:
Standard Grant
相似国自然基金
Research on Quantum Field Theory without a Lagrangian Description
- 批准号:24ZR1403900
- 批准年份:2024
- 资助金额:0.0 万元
- 项目类别:省市级项目
Cell Research
- 批准号:31224802
- 批准年份:2012
- 资助金额:24.0 万元
- 项目类别:专项基金项目
Cell Research
- 批准号:31024804
- 批准年份:2010
- 资助金额:24.0 万元
- 项目类别:专项基金项目
Cell Research (细胞研究)
- 批准号:30824808
- 批准年份:2008
- 资助金额:24.0 万元
- 项目类别:专项基金项目
Research on the Rapid Growth Mechanism of KDP Crystal
- 批准号:10774081
- 批准年份:2007
- 资助金额:45.0 万元
- 项目类别:面上项目
相似海外基金
Collaborative Research: CyberTraining: Pilot: PowerCyber: Computational Training for Power Engineering Researchers
协作研究:CyberTraining:试点:PowerCyber:电力工程研究人员的计算培训
- 批准号:
2319895 - 财政年份:2024
- 资助金额:
$ 9.87万 - 项目类别:
Standard Grant
Collaborative Research: CyberTraining: Implementation: Medium: Training Users, Developers, and Instructors at the Chemistry/Physics/Materials Science Interface
协作研究:网络培训:实施:媒介:在化学/物理/材料科学界面培训用户、开发人员和讲师
- 批准号:
2321102 - 财政年份:2024
- 资助金额:
$ 9.87万 - 项目类别:
Standard Grant
Collaborative Research: CyberTraining: Implementation: Medium: Transforming the Molecular Science Research Workforce through Integration of Programming in University Curricula
协作研究:网络培训:实施:中:通过将编程融入大学课程来改变分子科学研究人员队伍
- 批准号:
2321045 - 财政年份:2024
- 资助金额:
$ 9.87万 - 项目类别:
Standard Grant
Collaborative Research: CyberTraining: Implementation: Medium: Training Users, Developers, and Instructors at the Chemistry/Physics/Materials Science Interface
协作研究:网络培训:实施:媒介:在化学/物理/材料科学界面培训用户、开发人员和讲师
- 批准号:
2321103 - 财政年份:2024
- 资助金额:
$ 9.87万 - 项目类别:
Standard Grant
Collaborative Research: CyberTraining: Implementation: Medium: Transforming the Molecular Science Research Workforce through Integration of Programming in University Curricula
协作研究:网络培训:实施:中:通过将编程融入大学课程来改变分子科学研究人员队伍
- 批准号:
2321044 - 财政年份:2024
- 资助金额:
$ 9.87万 - 项目类别:
Standard Grant
Collaborative Research: CyberTraining: Pilot: PowerCyber: Computational Training for Power Engineering Researchers
协作研究:CyberTraining:试点:PowerCyber:电力工程研究人员的计算培训
- 批准号:
2319896 - 财政年份:2024
- 资助金额:
$ 9.87万 - 项目类别:
Standard Grant
Collaborative Research: CyberTraining: Implementation: Small: Inclusive Cyberinfrastructure and Machine Learning Training to Advance Water Science Research
合作研究:网络培训:实施:小型:包容性网络基础设施和机器学习培训,以推进水科学研究
- 批准号:
2320980 - 财政年份:2024
- 资助金额:
$ 9.87万 - 项目类别:
Standard Grant
Collaborative Research: CyberTraining: Implementation: Small: Inclusive Cyberinfrastructure and Machine Learning Training to Advance Water Science Research
合作研究:网络培训:实施:小型:包容性网络基础设施和机器学习培训,以推进水科学研究
- 批准号:
2320979 - 财政年份:2024
- 资助金额:
$ 9.87万 - 项目类别:
Standard Grant
Collaborative Research: CyberTraining: Implementation: Medium: Training Users, Developers, and Instructors at the Chemistry/Physics/Materials Science Interface
协作研究:网络培训:实施:媒介:在化学/物理/材料科学界面培训用户、开发人员和讲师
- 批准号:
2321104 - 财政年份:2024
- 资助金额:
$ 9.87万 - 项目类别:
Standard Grant
Collaborative Research: CyberTraining: Pilot: Cyberinfrastructure-Enabled Machine Learning for Understanding and Forecasting Space Weather
合作研究:网络培训:试点:网络基础设施支持的机器学习用于理解和预测空间天气
- 批准号:
2320148 - 财政年份:2023
- 资助金额:
$ 9.87万 - 项目类别:
Standard Grant