CC-NIE Network Infrastructure: Expanding Connectivity to Campus-Wide Resources for Computational Discovery
CC-NIE Network Infrastructure: Expanding Connectivity to Campus-Wide Resources for Computational Discovery
批准号:
1245488
负责人:
Brian Noble
金额:
$48.69万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-01-01 至 2015-06-30
中文摘要
密歇根大学在支持研究和教育的协作计算资源方面有着悠久的历史。这些资源包括高性能计算集群、数据存储和归档系统以及可视化资源。该项目改善了这些系统内部以及这些系统与大学在美国和全球的合作者之间的连通性。连接性得到改善的资源包括NYX,一个共享租户高性能集群;Flux,一个大学范围内的共享计算集群;以及UM 3D可视化实验室,这是一个跨学科的服务设施,部分用于可视化探索大型科学数据集。该项目支持改善这些资产和更广泛的互联网之间的网络连接性,支持广泛的基于计算的科学探索,包括以下示例。密歇根大学的大气、海洋和空间科学学院正在使用福洛斯和UM3D实验室来探索气候变化。密歇根大学的化学工程系正在使用Nyx和UM3D实验室在分子水平上开发“设计者结构”。密歇根和其他地方的物理学教师将能够更好地探索暗物质的宇宙学影响,以及利用日内瓦大型强子对撞机的数据深入研究基本粒子物理。除了这些基本的科学进步外,基础设施的改善还通过远程学习努力,在从行星天气到计算科学本身作为一门学科的领域对整个大学和其他地方的本科生和研究生的培训发挥了作用。
英文摘要
The University of Michigan has a long history of collaborative computational resources supporting research and education. Such resources include high-performance computaitonal clusters, data storage and archival systems, and visualization resources. This project improves connectivity between these systems internally and between these systems and the University's collaborators in the US and around the globe. Resources with improved connectivity include Nyx, a shared-tenancy high performance cluster; Flux, a University-wide shared compute cluster; and the UM 3D Visulation Lab, an interdisciplinary service facility used in part for visual exploration of large scientific data sets.This project's support of improved network connectivity between these assets and the broader Internet supports a broad swath of computationally-enabled scientific explorations, including the following examples. Atmospheric, Oceanic, and Space Sciences faculty at Michigan are using Flux and the UM3D lab to explore climate change. Chemical Engineering faculty at Michgian are using Nyx and the UM3D Lab to develop "designer structures" at the molecular level. Physics faculty at Michigan and elsewhere will be better able to explore cosmological impacts of dark matter, as well as delve into the fundamental partical physics with data from the Large Hadron Collider in Geneva. In addition to these fundamental scientific advances, the infrastructure improvements also play a role in the training of undergraduate and graduate students across the University and beyond, through distance learning efforts, in fieldsfrom planetary weather through computational science as a discipline unto itself.
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