MRI: Acquisition of iMARC: High Performance Computing for STEM Research and Education in Southeast Wisconsin

区域资源iMARC（马奎特计算基础设施）位于威斯康星州东南部，为教师和学生提供适当的基础设施，以有效地参与需要并行计算的挑战，并促进大规模计算和数据密集型分析的HPS技术的实践培训。iMARC是一个替换系统，具有现代CPU，大内存容量，快速存储和图形处理单元（GPU）加速器，旨在增加60+折叠计算能力，为威斯康星州东南部20多个主要用户提供新的研究和教育能力。它集成了用于计算科学的MUGrid（马奎特大学计算网格）和区域SeWHiP（威斯康星高性能网络基础设施），从而使马奎特大学和邻近机构的下一代大规模计算和数据密集型研究和教育成为可能。iMARC的高性能数据存储使多个部门和机构的教师能够解决新的前沿问题。这个集群，加上支持基础设施更新的举措，解决了对区域科学计算资源和高性能计算技术高质量培训日益增长的需求。iMARC为数据分析中的并行计算创造了独特的资源，以应对大规模计算中的挑战，并为大规模并行计算任务提供了一个开发环境，便于部署到XSEDE（国家计算基础设施）。大多数用户依赖于仅使用cpu的节点所提供的集群的一般计算能力，并从中受益匪浅。新系统将把生物分子建模和人工智能的研究能力提升到一个新的水平。纯cpu节点的峰值性能将达到176 TFLOPS，比旧机器的峰值性能提高了30倍。该奖项反映了美国国家科学基金会的法定使命，并通过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，被认为值得支持。

The regional resource, iMARC (infrastructure for MARquette Computing), in south east Wisconsin, provides faculty and students with appropriate infrastructure to engage efficiently in the challenges that require parallel computing and facilitate hands-on training in HPS techniques for large-scale compute- and data-intensive analyses.iMARC is a replacement system that features a modern CPU, large RAM volumes, fast storage, and graphical processing unit (GPU) accelerators, aiming to increase 60+-folding computational power affording a new level of capabilities for research and education for more than 20 major users across Southeastern Wisconsin. It integrates MUGrid (Marquette University Computational Grid) and regional SeWHiP (Se Wisconsin High Performance cyberinfrastructure) for computational sciences, thus enabling the next generation of large-scale compute- and data-intensive research and education at Marquette and neighboring institutions. The high performance data storage of iMARC enables faculty across multiple departments and institutions to tackle new cutting-edge questions. This cluster, coupled with initiatives to support infrastructure renewals, addresses the growing demand for regional scientific computing resources and high-quality training in HPC technologies. iMARC creates a unique resource for parallel computing in data analytics for the challenges in large-scale computing and provides a development environment for large-scale parallel computing tasks that facilitate deployment to XSEDE (the national computing infrastructure). The majority of the users rely on and greatly benefit from the general computational capabilities of the cluster delivered by the CPU-only nodes. The new system will bring the capabilities related to the research in biomolecular modeling and artificial intelligence to a new level. The peak performance of the CPU-only nodes will be at 176 TFLOPS, which is a 30-fold increase over the peak performance of the old machine.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.