CISE Research Instrumentation: Enabling Technology for High-Performance Heterogeneous Clusters Focusing on Grid Middleware, Fault Tolerance & Sparse Matrix Computations
CISE Research Instrumentation: Enabling Technology for High-Performance Heterogeneous Clusters Focusing on Grid Middleware, Fault Tolerance & Sparse Matrix Computations
批准号:
9818334
负责人:
Jack Dongarra
金额:
$15.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1999
资助国家:
美国
项目状态:
已结题
起止时间:
1999-03-01 至 2002-02-28
中文摘要
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英文摘要
9818334Dongarra, Jack J.Plank, James S.University of TennesseeEnabling Technology for High-Performance Heterogeneous Clusters Focusing on Grid Middleware, Fault Tolerance and Sparse Matrix ComputationsThis research instrumentation enables research projects in:- Harnessing Cluster Resources for Distributed Scientific Computing,- Fast and Portable Checkpointing in Clusters and Clusters-of-Clusters, and- Tools for Large-Scale Sparse Matrix Applications on Clusters.To support the aforementioned projects, this award contributes to the purchase of a 32-node high performance cluster, some switches, workstations, and interface to existing clusters and visualization lab atthe University of Tennessee. High-performance, low-latency clusters assembled from commodity computers and interconnects are clearly the cost-effective alternative to parallel supercomputers. But the software environment on such clusters is primitive at best; there is an obvious need of tools for application development and cluster management. The three projects in this proposal address this need. Their common goal is the development of enabling technology for advanced scientific computing applications on large-scale clusters and heterogeneous clusters-of-clusters. The proposed instrumentation is for a high-performance networked cluster of workstations. This cluster will be connected to two small clusters (available in the department) to provide a sizable, heterogeneous ``cluster-of-clusters'' with visualization capabilities. This cluster-of-clusters parallel platform will be used for algorithm, software and tool development research in the three projects.
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负责人:Jack Dongarra
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依托单位:
SHF: Small: Bench-testing Environment for Automated Software Tuning (BEAST)
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项目类别:Standard Grant
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资助金额:$50.0万
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财政年份:2013
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负责人:Jack Dongarra
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依托单位:
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EAGER: PaRSEC: Parallel Runtime Scheduling and Execution Control
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资助金额:$50.0万
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依托单位:
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项目类别:Standard Grant
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资助金额:$40.0万
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依托单位:
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财政年份:2011
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财政年份:2011
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负责人:Jack Dongarra
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依托单位:
国内基金
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