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

MRI 联盟：收购异构、共享计算仪器，以支持马萨诸塞州的科学和计算研究。绿色高性能计算联盟

• 批准号: 1229059
• 负责人: Christopher Hill
• 金额: $ 162.28万
• 依托单位: University of Massachusetts Donahue Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-10-01 至 2015-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1229059&HistoricalAwards=false
• 关键词: MRI; Consortium; Acquisition; Heterogeneous; Shared

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.

这项工作包括联合收购共享高性能计算 (HPC) 仪器，强调基于 HPC 的科学和工程，并具有“按需”功能的优势。该仪器是一个混合平台，将最先进的集群计算机与具有前瞻性、可能面向百亿亿次计算的 GPU 加速器硬件集成在一起，这将使高等教育合作伙伴联盟的关键 STEM 应用取得进展，并进行研究跨越科学学科的议程。该系统的高水平响应能力将应用于免疫学系统建模和识别、交互式药物途径分析、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，以及研究物质的基础物理。在计算机科学领域，研究人员和行业合作者将使用该仪器作为受控、可配置的设施，具有先进的用户群和应用程序工作负载，推动对下一代 HPC 环境的抽象、大规模 HPC 的增强虚拟化方法以及定量分析的研究。大规模试验 HPC 云/服务范例。 此次收购将促进科学家、工程师、计算科学从业者和计算机科学家之间的合作，其研究兴趣包括：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；开发新的技术。更有吸引力的 HPC 方法，为跨软件到劳动力技能的后千万级 HPC 生态系统铺平道路，计划开展广泛的教育和外展活动，以提高机构研究社区以及社区大学当地合作者的参与度， K-12 教育和社区组织。该工具将以多种方式为网络基础设施做出贡献，并将成为更广泛的公私合作伙伴关系的重要组成部分，从而增强计算科学基础设施并促进高科技创新。