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

位于威斯康星州东南部的地区性资源IMARC(基础设施)为教职员工和学生提供适当的基础设施，以有效地应对需要并行计算的挑战，并促进针对大规模计算和数据密集型分析的HPS技术实践培训。iMARC是一个替代系统，具有现代CPU、大容量RAM、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多个主要用户的研究和教育提供新水平的能力。它集成了MUGrid(马奎特大学计算网格)和区域SeWHiP(威斯康星州高性能网络基础设施)用于计算科学，从而使马奎特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系和机构的教职员工能够解决新的前沿问题。这一组群，加上支持基础设施更新的举措，满足了对区域科学计算资源和高质量高性能计算技术培训的日益增长的需求。IMARC为数据分析中的并行计算创建了一个独特的资源，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，有助于部署到XSEDE(国家计算基础设施)。大多数用户依赖于仅使用CPU的节点提供的集群的通用计算能力，并从中受益匪浅。新系统将把与生物分子建模和人工智能研究相关的能力带到一个新的水平。纯CPU节点的峰值性能将达到176 TFLOPS，这是旧机器峰值性能的30倍。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.