GPU cluster for high performance computing

Zhe Fan; Feng Qiu; Arie Kaufman; Suzanne Yoakum-Stover

GPU cluster for high performance computing

Zhe Fan
, Feng Qiu
, Arie Kaufman
, Suzanne Yoakum-Stover

Computer Science

Stony Brook University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

243 Scopus citations

Abstract

Inspired by the attractive Flops/dollar ratio and the incredible growth in the speed of modern graphics processing units (CPUs), we propose to use a cluster of CPUs for high performance scientific computing. As an example application, we have developed a parallel flow simulation using the lattice Boltzmann model (LBM) on a GPU cluster and have simulated the dispersion of airborne contaminants in the Times Square area of New York City. Using 30 GPU nodes, our simulation can compute a 480x400x80 LBM in 0.31 second/step, a speed which is 4.6 times faster than that of our CPU cluster implementation. Besides the LBM, we also discuss other potential applications of the GPU cluster, such as cellular automata, PDE solvers, and FEM.

Original language	English
Title of host publication	IEEE/ACM SC2004 Conference - Bridging Communities, Proceedings
Pages	297-308
Number of pages	12
State	Published - 2004
Event	IEEE/ACM SC2004 Conference - Bridging Communities - Pittsburgh, PA, United States Duration: Nov 6 2004 → Nov 12 2004

Publication series

Name	IEEE/ACM SC2004 Conference, Proceedings

Conference

Conference	IEEE/ACM SC2004 Conference - Bridging Communities
Country/Territory	United States
City	Pittsburgh, PA
Period	11/6/04 → 11/12/04

Keywords

Computational fluid dynamics
Data intensive computing
GPU cluster
Lattice Boltzmann model
Urban airborne dispersion

Cite this

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title = "GPU cluster for high performance computing",

abstract = "Inspired by the attractive Flops/dollar ratio and the incredible growth in the speed of modern graphics processing units (CPUs), we propose to use a cluster of CPUs for high performance scientific computing. As an example application, we have developed a parallel flow simulation using the lattice Boltzmann model (LBM) on a GPU cluster and have simulated the dispersion of airborne contaminants in the Times Square area of New York City. Using 30 GPU nodes, our simulation can compute a 480x400x80 LBM in 0.31 second/step, a speed which is 4.6 times faster than that of our CPU cluster implementation. Besides the LBM, we also discuss other potential applications of the GPU cluster, such as cellular automata, PDE solvers, and FEM.",

keywords = "Computational fluid dynamics, Data intensive computing, GPU cluster, Lattice Boltzmann model, Urban airborne dispersion",

author = "Zhe Fan and Feng Qiu and Arie Kaufman and Suzanne Yoakum-Stover",

year = "2004",

language = "English",

isbn = "0769521533",

series = "IEEE/ACM SC2004 Conference, Proceedings",

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note = "IEEE/ACM SC2004 Conference - Bridging Communities ; Conference date: 06-11-2004 Through 12-11-2004",

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TY - GEN

T1 - GPU cluster for high performance computing

AU - Fan, Zhe

AU - Qiu, Feng

AU - Kaufman, Arie

AU - Yoakum-Stover, Suzanne

PY - 2004

Y1 - 2004

N2 - Inspired by the attractive Flops/dollar ratio and the incredible growth in the speed of modern graphics processing units (CPUs), we propose to use a cluster of CPUs for high performance scientific computing. As an example application, we have developed a parallel flow simulation using the lattice Boltzmann model (LBM) on a GPU cluster and have simulated the dispersion of airborne contaminants in the Times Square area of New York City. Using 30 GPU nodes, our simulation can compute a 480x400x80 LBM in 0.31 second/step, a speed which is 4.6 times faster than that of our CPU cluster implementation. Besides the LBM, we also discuss other potential applications of the GPU cluster, such as cellular automata, PDE solvers, and FEM.

AB - Inspired by the attractive Flops/dollar ratio and the incredible growth in the speed of modern graphics processing units (CPUs), we propose to use a cluster of CPUs for high performance scientific computing. As an example application, we have developed a parallel flow simulation using the lattice Boltzmann model (LBM) on a GPU cluster and have simulated the dispersion of airborne contaminants in the Times Square area of New York City. Using 30 GPU nodes, our simulation can compute a 480x400x80 LBM in 0.31 second/step, a speed which is 4.6 times faster than that of our CPU cluster implementation. Besides the LBM, we also discuss other potential applications of the GPU cluster, such as cellular automata, PDE solvers, and FEM.

KW - Computational fluid dynamics

KW - Data intensive computing

KW - GPU cluster

KW - Lattice Boltzmann model

KW - Urban airborne dispersion

UR - https://www.scopus.com/pages/publications/23944462603

M3 - Conference contribution

AN - SCOPUS:23944462603

SN - 0769521533

SN - 9780769521534

T3 - IEEE/ACM SC2004 Conference, Proceedings

SP - 297

EP - 308

BT - IEEE/ACM SC2004 Conference - Bridging Communities, Proceedings

T2 - IEEE/ACM SC2004 Conference - Bridging Communities

Y2 - 6 November 2004 through 12 November 2004

ER -

GPU cluster for high performance computing

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Publication series

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Keywords

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