MRI: Acquisition of a GPU-based High Performance Computing Instrumentation for Smart City Research at Cleveland State University

MRI：克利夫兰州立大学为智能城市研究采购基于 GPU 的高性能计算仪器

• 批准号: 2215388
• 负责人: Hongkai Yu
• 金额: $ 43.44万
• 依托单位: Cleveland State University
• 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: 2022-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2215388&HistoricalAwards=false
• 关键词: MRI; Acquisition; GPU; based; Performance

This project will establish a Graphics Processing Unit (GPU)-based High Performance Computing Instrumentation (HPCI) at Cleveland State University (CSU) to facilitate and promote Smart City research. The research goal is to transform Cleveland to a modern smart city with shorter commute time even during rush hours, ultra-low crime rate, a highly robust and secure electric power grid, and successful professional sports teams contending for championships. The requested major research instrumentation will enable research in the following five areas: 1) Smart Traffic; 2) Smart Vehicle; 3) Smart Internet of Things (IoT); 4) Smart Microgrid; and 5) Smart Sports. The Smart Traffic project will develop novel deep learning methods to extract useful information from remote sensing traffic images under complex urban environments. The Smart Vehicle project will improve the state-of-the-art in reliable communications and in data processing among 5G-enabled Connected Vehicles and the Vehicle-to-Everything. The Smart IoT project will develop novel machine learning methods for wireless data-driven communication and wireless intelligent sensing. The Smart Microgrid project will develop novel hybrid learning methods to ensure system resiliency, cost effectiveness, efficiency, and security of microgrid. The Smart Sports project will develop new computer vision methods to recognize and evaluate fine-grained player activities towards more efficient training and player evaluation. The research has the potential to transform Cleveland into an exemplary smart city, and the research outcome could be applicable to many other urban areas in the US. The requested HPCI will make a substantial improvement to the CSU high performance computing capabilities, which will positively attract potential collaborative research in the Cleveland Metropolitan Area and greatly improve the quality of research training at CSU. The requested HPCI will support the undergraduate/graduate student research, education and training in several computer science/engineering and civil engineering courses at CSU. The research supports the K-12 education of Cleveland Metropolitan Area and also supports the Hispanic-minority research and education. The website for the project is at https://engineering.csuohio.edu/mri-hpc/ The project website is maintained by the Computer Systems Specialist of the Washkewicz College of Engineering at Cleveland State University. The research outcome, user guidance, news, and project related information will be provided and updated in this website over the expected lifetime of the requested instrument.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.

该项目将在克利夫兰州立大学 (CSU) 建立基于图形处理单元 (GPU) 的高性能计算仪器 (HPCI)，以促进和促进智慧城市研究。研究目标是将克利夫兰转变为现代化的智慧城市，即使在高峰时段通勤时间也更短，犯罪率超低，电网高度强大和安全，并且拥有成功的职业运动队争夺冠军。所要求的主要研究仪器将支持以下五个领域的研究：1）智能交通； 2）智能汽车； 3）智能物联网（IoT）； 4）智能微电网； 5) 智能运动。 智能交通项目将开发新颖的深度学习方法，以在复杂的城市环境下从遥感交通图像中提取有用的信息。智能汽车项目将提高 5G 联网汽车和车联网之间可靠通信和数据处理的最先进水平。智能物联网项目将为无线数据驱动通信和无线智能传感开发新颖的机器学习方法。智能微电网项目将开发新颖的混合学习方法，以确保微电网的系统弹性、成本效益、效率和安全性。智能体育项目将开发新的计算机视觉方法来识别和评估细粒度的球员活动，以实现更有效的训练和球员评估。该研究有潜力将克利夫兰转变为典范的智慧城市，研究成果也可适用于美国许多其他城市地区。此次申请的HPCI将使CSU高性能计算能力得到实质性提升，这将积极吸引克利夫兰都会区潜在的合作研究，并大大提高CSU的研究培训质量。所请求的 HPCI 将支持科罗拉多州立大学多个计算机科学/工程和土木工程课程的本科生/研究生研究、教育和培训。该研究支持克利夫兰都会区的 K-12 教育，也支持西班牙裔少数族裔的研究和教育。该项目的网站位于 https://engineering.csuohio.edu/mri-hpc/ 该项目网站由克利夫兰州立大学 Washkewicz 工程学院的计算机系统专家维护。研究成果、用户指南、新闻和项目相关信息将在所请求仪器的预期使用寿命内在此网站上提供和更新。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值进行评估，被认为值得支持以及更广泛的影响审查标准。