High-performance and parallel computing with GPUs

Using Graphics Processing Units (GPUs) for general-purpose computing has made high-performance parallel computing very cost-effective for a wide variety of applications. However, programming these highly-parallel processors still remains somewhat of an art.

We have several projects investigating how GPUs can be applied to different application domains, including:

 

Selected papers

  • J. Myre, S.D.C. Walsh, D. J. Lilja, and M. O. Saar, “Performance analysis of single-phase, multiphase, and multicomponent lattice-Boltzmann fluid flow simulations on GPU clusters,” Concurrency and Computation: Practice and Experience, (to appear).
  • Xin Li and David J. Lilja, “A Highly Parallel GPU-Based Hash Accelerator for a Data Deduplication System,” IASTED International Conference on Parallel and Distributed Computing and Systems (PDCS), November, 2009, pp. 268-275.
  • Stuart D.C. Walsh, Martin O. Saar, Peter Bailey, and David J. Lilja, “Accelerating Geo-Science and Engineering System Simulations on Graphics Hardware,” Journal of Computers and Geosciences, Volume 35, No. 12, December, 2009, pp. 2353-2364.
  • Peter Bailey, Joe Myre, Stuart D. C. Walsh, David J. Lilja, and Martin O. Saar, “Accelerating Lattice Boltzmann Fluid Flow Simulations Using Graphics Processors,” International Conference on Parallel Processing (ICPP), September, 2009.
  • Stuart D.C. Walsh, Joe Myre, Martin O. Saar, and David J. Lilja, “Multi-GPU, Multi-core, Multi-phase Lattice-Boltzmann Simulations of Fluid Flow for the Geosciences,” Eos Trans. AGU,, Fall Meeting Supplement, December, 2009.
  • Stuart. D.C. Walsh, Joe Myre, Peter Bailey, Martin O. Saar, and David J. Lilja, “GPU implementation of Multiphase Lattice-Boltzmann Simulations,” Path to Petascale: Adapting GEO/CHEM/ASTRO Applications for Accelerators and Accelerator Clusters, National Center for Supercomputing Applications, April, 2009.
  • S. D. Walsh, M. O. Saar, P. Bailey, and D. J. Lilja, “Cheaper and faster: How to have your cake and eat it too with GPU implementations of Earth Science simulations,” Eos Trans. AGU, 89(53), Fall Meeting Supplement, Abstract IN23C-1102, 2008.