MRI: Acquisition of a GPU-accelerated cluster for research, training and outreach

MRI：获取 GPU 加速集群用于研究、培训和推广

• 批准号: 2215734
• 负责人: Dukka KC
• 金额: $ 43.21万
• 依托单位: Michigan Technological 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 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2215734&HistoricalAwards=false
• 关键词: MRI; Acquisition; GPU; accelerated; cluster

This project will enable ground-breaking research at Michigan Technological University (Michigan Tech) by acquiring a high-performance computing cluster to be named DeepBlizzard. DeepBlizzard will accelerate scientific discoveries in basic research and technological innovations by addressing emergent and longer-term needs with broad societal impacts in multiple disciplines: chemistry, forestry, mathematics, physics, engineering (biomedical, mechanical, materials science), and computer science. DeepBlizzard will be utilized by over 125 users across 20 departments and 5 Colleges at Michigan Tech and by partners at North Carolina A&T University. DeepBlizzard will catalyze and accelerate research, enable dissemination of results, and expand opportunities for collaboration, thereby promoting the advancement of these diverse scientific domains. The project will also provide various training, teaching, and outreach activities to produce a highly trained and diverse technical workforce, including the next generation of scientists. Throughout its life, DeepBlizzard will serve as the epicenter of innovative research by enabling and supporting cross-disciplinary and collaborative research opportunities.The DeepBlizzard high-performance computing cluster is designed by a team of experts from Computer Science, Physics, Chemistry, and Biomedical Engineering in coordination with Information Technology (IT) professionals. The instrument architecture is based on graphical processing unit (GPU) based accelerators. DeepBlizzard is configured to meet three major requirements: high-performance deep learning and inference; high-performance single, double, and mixed-precision calculations; and the ability to execute codes using high levels of parallelism. These requirements map to the needs of ongoing and proposed computational research endeavors at Michigan Tech. In addition, several outreach and training activities – developed in partnership with Michigan Tech’s existing NSF Research Experience for Undergraduates (REU) site, NSF/NSA GenCyber Camp, and other programs involving K-12, undergraduate, and graduate student, and historically marginalized groups in STEM – will provide seamless integration of research activities with outreach.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.

该项目将通过收购一个名为 DeepBlizzard 的高性能计算集群来实现密歇根理工大学 (Michigan Tech) 的突破性研究。DeepBlizzard 将通过满足广泛的紧急和长期需求来加速基础研究和技术创新的科学发现。 DeepBlizzard 将在化学、林业、数学、物理、工程（生物医学、机械、材料科学）和计算机科学等多个学科领域产生社会影响，将被 20 个部门和超过 125 名用户使用。密歇根理工大学的 5 所学院和 DeepBlizzard 的合作伙伴将促进和加速研究，促进成果传播并扩大合作机会，从而促进这些不同科学领域的进步。该项目还将提供各种培训、 DeepBlizzard 将通过提供和支持跨学科和协作研究机会，成为创新研究的中心。 DeepBlizzard 高性能计算集群由来自计算机科学、物理、化学和生物医学工程的专家团队与信息技术 (IT) 专业人员合作设计，仪器架构基于基于 DeepBlizzard 的图形处理单元 (GPU) 加速器。配置满足三个主要要求：高性能深度学习和推理；高性能单精度、双精度和混合精度计算；以及使用高水平并行性执行代码的能力。此外，与密歇根理工学院现有的 NSF 本科生研究体验 (REU) 网站、NSF/NSA GenCyber​​ Camp 以及其他涉及 K- 的项目合作开发了多项外展和培训活动。 12、本科生、研究生以及 STEM 中历来边缘化的群体——将提供研究活动与推广的无缝整合。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。