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

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将加速基础研究和技术创新方面的科学发现，解决多个学科的紧急和长期需求，并产生广泛的社会影响：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。DeepBlizzard将被密歇根理工大学20个系和5所学院的125多名用户以及北卡罗来纳州AT大学的合作伙伴使用。DeepBlizzard将催化和加速研究，促进成果的传播，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、教学和外联活动，以培养一支训练有素的多样化技术队伍，包括下一代科学家。DeepBlizzard的高性能计算集群是由来自计算机科学、物理、化学和生物医学工程的专家团队与信息技术（IT）专业人士合作设计的，它将成为创新研究的中心，为跨学科和合作研究提供支持。仪器架构基于图形处理单元（GPU）加速器。DeepBlizzard的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;以及使用高级别并行执行代码的能力。这些要求映射到密歇根理工大学正在进行的和拟议的计算研究工作的需求。此外，一些推广和培训活动-与密歇根理工大学现有的NSF本科生研究经验（REU）网站，NSF/NSA GenCyber Camp以及其他涉及K-12，本科生和研究生的项目合作开发，和历史上被边缘化的群体-该奖项反映了NSF的法定使命，并被认为是值得支持的，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。

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.