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Designing a Graphics Processing Unit Accelerated Petaflop Capable Lattice Boltzmann Solver: Read Aligned Data Layouts and Asynchronous Communication

Fredrik Robertsén, Jan Westerholm, Keijo Mattila, Designing a Graphics Processing Unit Accelerated Petaflop Capable Lattice Boltzmann Solver: Read Aligned Data Layouts and Asynchronous Communication. The International Journal of High Performance Computing Applications , 1094342016658109, 2016.

http://dx.doi.org/10.1177/1094342016658109

Abstract:

The lattice Boltzmann method is a well-established numerical approach for complex fluid flow simulations. Recently, general-purpose graphics processing units (GPUs) have become available as high-performance computing resources at large scale. We report on designing and implementing a lattice Boltzmann solver for multi-GPU systems that achieves 1.79 PFLOPS performance on 16,384 GPUs. To achieve this performance, we introduce a GPU compatible version of the so-called bundle data layout and eliminate the halo sites in order to improve data access alignment. Furthermore, we make use of the possibility to overlap data transfer between the host central processing unit and the device GPU with computing on the GPU. As a benchmark case, we simulate flow in porous media and measure both strong and weak scaling performance with the emphasis being on large-scale simulations using realistic input data.

BibTeX entry:

@ARTICLE{aconv27989,
  title = {Designing a Graphics Processing Unit Accelerated Petaflop Capable Lattice Boltzmann Solver: Read Aligned Data Layouts and Asynchronous Communication},
  author = {Robertsén, Fredrik and Westerholm, Jan and Mattila, Keijo},
  journal = {The International Journal of High Performance Computing Applications},
  publisher = {Sage Science Press},
  pages = {1094342016658109},
  year = {2016},
  ISSN = {1741-2846},
}

Belongs to TUCS Research Unit(s): Software Engineering Laboratory (SE Lab)

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