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CC* Compute: Shared Computing Infrastructure for Large-scale Science Problems

CC* Compute: Shared Computing Infrastructure for Large-scale Science Problems
CC* 计算:解决大规模科学问题的共享计算基础设施
批准号:
1925716
负责人:
Richard Jones
金额:
$40.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-08-01 至 2022-07-31

项目摘要

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中文摘要
翻译
在过去十年中,科学仪器的进步导致各种科学领域的数据的规模和复杂性都出现了惊人的增长。康涅狄格大学的研究人员正在扩展现有共享高性能计算机设施的能力,通过增加28个节点的集群来应对这一挑战,每个节点拥有40个英特尔核心和192 GB内存,以及1000 TB的共享存储。这一资源平衡被选择来满足康涅狄格大学研究人员使用的粒子物理、天体物理、地球物理和统计学领域的应用程序,以满足该大学所有科学和工程领域对数据密集型计算日益增长的需求。此外,该集群将被配置为开放科学网格(OSG)上的共享科学计算资源。OSG是一个由大学和国家研究机构组成的联盟,他们使用网格技术将各自的计算机集群聚合成一个统一的国家科学计算基础设施。通过将该集群加入OSG,康涅狄格州大学的研究人员将看到比仅依靠本地资源运行的吞吐量高得多的吞吐量,使他们能够更快地周转,并访问比本地存储和处理更大的数据。该集群将能够在研究生一级的现有科学计算课程中引入一个新的大数据组成部分。这个奖项反映了NSF的法定使命,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,被认为是值得支持的。
英文摘要
Advances in scientific instrumentation over the past decade have led to phenomenal growth in both the size and complexity of data across a wide variety of scientific domains. Researchers at the University of Connecticut are expanding the capabilities of the existing shared high-performance computer facility to meet this challenge by the addition of a 28-node cluster, each node with 40 Intel cores and 192 GB of memory, and 1000 TB of shared storage.This balance of resources has been chosen to accommodate applications in the areas of particle physics, astrophysics, geophysics, and statistics in use by UConn researchers, with a view to meet a rising need for data-intensive computing across all of science and engineering at the University. Furthermore, the cluster will be configured as a shared scientific computing resource on the Open Science Grid (OSG). OSG is a consortium of universities and national research facilities who are using grid technology to aggregate their individual computer clusters into a single unified national compute infrastructure for science. In joining this cluster to the OSG, UConn researchers will see a much higher throughput than they would see running on local resources alone, granting them faster turn-around and access to bigger data than could be stored and processed locally. The cluster will enable the introduction of a new big data component within an existing course on scientific computing at the graduate level. It will also be used to produce visualizations of astronomical observations that will be used in K-12 outreach.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.
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  • 财政年份:
    2022
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  • 依托单位:
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  • 批准号:
    1812415
  • 项目类别:
    Continuing Grant
  • 资助金额:
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    2018
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海外基金