MRI Consortium: Acquisition of a Heterogeneous, Shared, Computing Instrument to Enable Science and Computing Research by the Mass. Green High Performance Computing Consortium

这项工作包括一个财团收购一个共享的高性能计算（HPC）仪器，强调基于HPC的科学和工程，具有“按需”能力的优势。该仪器是一个混合平台，将最先进的集群计算机与前瞻性的、可能面向百亿亿级的GPU加速器硬件集成在一起，这将使跨越科学学科的高等教育合作伙伴联盟的关键STEM应用取得进展。这个系统吗?S高水平的响应性将应用于免疫学系统建模和识别、相互作用药物通路分析、生物分子静电学、虚拟地球建模和数据分析、多尺度环境建模、自适应实时模型数据合成、交互式虚拟材料设计和物质基础物理研究。在计算机科学领域，研究人员和行业合作者将把该仪器作为一个可控制的、可配置的设备，拥有先进的用户群和应用程序工作负载，推动下一代HPC环境的抽象研究，大规模HPC的增强虚拟化方法，以及大规模HPC的云/服务范例的定量实验。此次收购将促进科学家、工程师、计算科学实践者和计算机科学家之间的合作，他们的研究兴趣是——扩大HPC在关键科学和工程问题上的应用——推动地球科学、生命科学、材料科学和基础物理学方面的知识——开发新的、更有吸引力的HPC方法——为跨越软件到劳动力技能的后千兆级HPC生态系统铺平道路——计划了广泛的教育和推广活动，以增加机构研究社区以及社区大学、K-12教育和社区组织的当地合作者的参与。该工具将以多种方式为网络基础设施做出贡献，并将成为加强计算科学基础设施和促进高科技创新的更广泛的公私伙伴关系的重要组成部分。

This work includes a consortium acquisition of a shared high-performance computing (HPC) instrument emphasizing HPC-based science and engineering with the benefit of "on-demand" capabilities. The instrument is a hybrid platform, integrating a state-of-the-art cluster computer with forward-looking, potentially exascale-oriented, GPU accelerator hardware that will enable progress in key STEM applications across a consortium of higher-educational partners with a research agenda that spans science disciplines. The system?s high levels of responsiveness will be applied to systems modeling and identification for immunology, interactive drug pathway analysis, bio-molecular electrostatics, virtual earth modeling and data analysis, multi-scale environment modeling, adaptive real-time model data synthesis, interactive virtualized materials design, and studying fundamental physics of matter. In computer science, researchers and industry collaborators will use the instrument as a controlled, configurable facility with an advanced user base and application workload, driving forward research into abstractions for next-generation HPC environments, enhanced virtualization methodologies for large-scale HPC, and quantitatively experimenting in cloud/service paradigms at scale for HPC. The acquisition will catalyze collaboration among scientists, engineers, computational science practitioners and computer scientists with research interests in- broadening the use of HPC for critical science and engineering problems- driving knowledge in earth science, life science, material science and basic physics- developing new, more engaging approaches to HPC- paving the way for a post-petascale HPC ecosystem spanning software to workforce skills- ere are extensive education and outreach activities planned to grow participation across institutional research communities as well as among local collaborators at community colleges, in K-12 education, and in community organizations. The instrument will contribute to cyberinfrastructure in multiple ways and will be a valuable part of a broader public-private partnership enhancing computational science infrastructure and catalyzing high-tech innovation.