GPU Clusters for High-Performance Computing

被引：0

作者：

Kindratenko, Volodymyr V. ^{[1
]}

Enos, Jeremy J. ^{[1
]}

Shi, Guochun ^{[1
]}

Showerman, Michael T. ^{[1
]}

Arnold, Galen W. ^{[1
]}

Stone, John E. ^{[2
]}

Phillips, James C. ^{[2
]}

Hwu, Wen-mei ^{[3
]}

机构：

[1] Univ Illinois, Natl Ctr Supercomp Applicat, 1205 W Clark St, Urbana, IL 61801 USA

[2] Univ Illinois, Theoret & Computat Biophys Grp, Urbana, IL 61801 USA

[3] Univ Illinois, Coordinated Sci Lab, Urbana, IL 61801 USA

来源：

2009 IEEE INTERNATIONAL CONFERENCE ON CLUSTER COMPUTING AND WORKSHOPS | 2009年

基金：

美国国家科学基金会; 美国国家卫生研究院;

关键词：

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Large-scale GPU clusters are gaining popularity in the scientific computing community. However, their deployment and production use are associated with a number of new challenges. In this paper, we present our efforts to address some of the challenges with building and running GPU clusters in HPC environments. We touch upon such issues as balanced cluster architecture, resource sharing in a cluster environment, programming models, and applications for GPU clusters.

引用

页码：638 / +

页数：2

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