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MRI: Acquisition of a High Performance Computational Cluster for Yale University

MRI：为耶鲁大学收购高性能计算集群

基本信息

批准号：
0821132
负责人：
Steven Girvin
金额：
$ 50万
依托单位：
Yale University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2008
资助国家：
美国
起止时间：
2008-07-15 至 2012-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=0821132&HistoricalAwards=false
关键词：
MRI Acquisition Performance Computational Cluster

项目摘要

Proposal #: CNS 08-21132PI(s): Girvin, Steve M. Basu, Sarbani; Batista, Victor S.; Ismail-Beigi, Sohrab; Smooke, Mitchell D.Institution: Yale University New Haven, CT 06520-8337Title: MRI/Acq.: Acq. of a High Performance Computational Cluster for Yale UniversityProject Proposed:This project, acquiring instrumentation for a large-scale computing system, enables research in the physical, biological, and social sciences, as well as engineering, linguistics, statistics, and many other fields, under the umbrella of a High Performance Computing (HPC) Center. The instrumentation complements the Biomedical HPC center. Supported by the Information Technology Services (ITS), these centers are considered a single virtual unit. This work services 52 research projects from faculty in 22 departments including physical sciences, engineering, linguistics, mathematics, ecology, economics, psychology, statistics, and the biological sciences. The very diverse research covers a wide range of topics from cosmological simulations to climate modeling, to neural circuit networks and simulation of internal dynamics, to economic modeling, to name a few. The research is supported by more than 35 current and more than 20 pending projects. Research computational scientists assist with the instrumentation, teach parallel programming techniques, optimize current code, and write new codes to support individual projects. The diverse needs capable of handling both CPU and memory bound tasks along with substantial mass storage and communication infrastructure will most likely be covered by a large CPU cluster consisting of 350 nodes with 16GB of memory shared by 8 cores per node and a large memory cluster consisting of 28 nodes sharing 7,168 GB memory. This 10-fold more CPUs, increased memory, and mass storage are expected to be heavily utilized and have immediate impact in research and education.Broader Impacts:The instrumentation leverages individual research of more than 350 faculty, research and postdoctoral staff, and graduate and undergraduate students. The latter will be able to train and learn how to optimally use such a facility. New courses will be developed for undergraduates focusing on HPC for nanoscale and biological systems. The institutional outreach program involves Howard and Xavier universities. Faculty from these universities will be trained via summer internships and allocated time in the HPC facilities.

提案编号：CNS 08- 21132 PI：吉尔文，Steve M. Basu，Sarbani; Batista，维克托S.; Ismail-Beigi，Sohrab; Smooke，Mitchell D. New Haven，CT 06520- 8337标题： MRI/采集：获取耶鲁大学高性能计算集群的项目建议：该项目，获得大规模计算系统的仪器，使物理，生物和社会科学，以及工程，语言学，统计学和许多其他领域的研究，在高性能计算（HPC）中心的保护伞下。该仪器补充了生物医学HPC中心。这些中心在信息技术处的支持下，被视为一个单一的虚拟单位。这项工作服务于22个部门的52个研究项目，包括物理科学，工程，语言学，数学，生态学，经济学，心理学，统计学和生物科学。非常多样化的研究涵盖了广泛的主题，从宇宙学模拟到气候建模，到神经电路网络和内部动态模拟，再到经济建模，仅举几例。该研究得到了35个以上现有项目和20多个待定项目的支持。研究计算科学家协助仪器，教授并行编程技术，优化当前代码，并编写新代码以支持单个项目。能够沿着大量大容量存储和通信基础设施来处理CPU和内存受限任务的各种需求很可能由大型CPU集群和大型内存集群来满足，其中大型CPU集群由350个节点组成，每个节点8个核心共享16 GB内存，而大型内存集群由28个节点共享7，168 GB内存组成。这10倍以上的CPU，增加内存和大容量存储预计将被大量利用，并在研究和教育中产生直接影响。更广泛的影响：仪器利用350多名教师，研究和博士后工作人员，研究生和本科生的个人研究。后者将能够培训和学习如何以最佳方式使用这种设施。将为本科生开发新的课程，重点是纳米级和生物系统的HPC。机构外展计划涉及霍华德和泽维尔大学。这些大学的教师将通过暑期实习和在HPC设施中分配时间进行培训。