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
• 负责人: Xin Liang
• 金额: $ 9.87万
• 依托单位: University of Kentucky Research Foundation
• 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 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2330364&HistoricalAwards=false
• 关键词: Collaborative; Research; CyberTraining; Pilot; Workforce

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成为多个跨学科领域的推动力。尽管这种进化在很大程度上得到了高级GPU网络基础架构的快速改善，但通常不存在全面的培训材料，这些培训材料将以应用程序驱动的深度学习技术与使用GPU Cyber​​infradstruct的实施相结合。为了填补这一差距，该项目开发了一个在线研讨会，该研讨会由五个学科的六位教职员工提供的一组跨学科的尖端培训课程。该研讨会重点关注基于GPU的深度学习系统和应用的最新创新，促进了下一代网络基础设施用户和贡献者的社区，他们可以使用，开发和改善先进的GPU Cyber​​infrastructure进行深度学习研究。这样的培训工作增强了深入学习和GPU网络基础设施劳动力的了解，并随后为重要的科学和社会问题提供了解决方案，包括地理位置上的水文图，航空航天中的空间环境以及运输中的自主驾驶和交通监控。该研讨会还将吸引来自代表性不足的群体，包括少数群体学生和农村地区的研究人员的学员。该项目中开发的跨学科研讨会旨在使包括大学生，研究生和研究人员在内的参与者能够提高他们的多学科技能，以提高他们的多学科技能，扩大他们的学术研究人员的协作竞争力，并具有重要的竞争力量，并具有重要的竞争力。为了实现这一目标，密集的研讨会包括1）一组动手讲座模块，为受训者提供全面的知识和技能，在高级GPU网络架构中深度学习系统的完整堆栈中，2）一系列关于高级GPU Cyber​​infrasture和Deep Internation Antivalient Intivalion和Intivalion Intivalitiant in International的促进研究的谈话应用讲座中引入的技术的跨学科协作项目实践。此外，开发了交互式在线培训系统的原型，旨在为受训者提供计算资源，并跟踪他们的学习进度，以进行更有效，有效的培训活动。预计该项目将在深度学习系统和应用中发展未来的研究劳动力，并扩大研究和教育中先进的GPU Cyber​​infrastructure的采用。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的审查标准通过评估来通过评估来支持的。