GPU Cluster for High Performance Computing

  • Authors:
  • Zhe Fan;Feng Qiu;Arie Kaufman;Suzanne Yoakum-Stover

  • Affiliations:
  • State University of New York at Stony Brook;State University of New York at Stony Brook;State University of New York at Stony Brook;State University of New York at Stony Brook

  • Venue:
  • Proceedings of the 2004 ACM/IEEE conference on Supercomputing
  • Year:
  • 2004

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Abstract

Inspired by the attractive Flops/dollar ratio and the incredible growth in the speed of modern graphics processing units (GPUs), we propose to use a cluster of GPUs 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 0.31second/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.