Computational Science Technical Note CSTN-073


Data Parallel Three-Dimensional Cahn-Hilliard Field Equation Simulation on GPUs with CUDA

D. P. Playne and K. A. Hawick

Archived January 2009


Computational scientific simulations have long used parallel computers to increase their performance. Recently graphics cards have been utilised to provide this functionality. GPGPU APIs such as NVIDIA's CUDA can be used to harness the power of GPUs for purposes other than computer graphics. GPUs are designed for processing two-dimensional data. In previous work we have presented several two-dimensional Cahn-Hilliard simulations that each utilise different CUDA memory types and compared their results. In this paper we extend these ideas to three dimensions. As GPUs are not intended for processing three-dimensional data arrays, the performance of the memory optimisations is expected to change. Here we present several three-dimensional Cahn-Hilliard simulations to explore the challenges and the performance of the different memory types in three-dimensions. The results show that the simulation design with the best performance in three-dimensions uses a different memory type to the optimal two-dimensional simulation.

Keywords: GPU; CUDA; scientific simulation; field equation.

Full Document Text: PDF version.

Citation Information: BiBTeX database for CSTN Notes.

BiBTeX reference:

  author = {D.P. Playne and K.A. Hawick},
  title = {{Data Parallel Three-Dimensional Cahn-Hilliard Field Equation Simulation
	on GPUs with CUDA}},
  booktitle = {Proc. 2009 International Conference on Parallel and Distributed Processing
	Techniques and Applications (PDPTA'09)},
  year = {2009},
  pages = {104-110},
  address = {Las vegas, USA},
  month = {13-16 July},
  organization = {WorldComp},
  institution = {Massey University},
  timestamp = {2009.02.28}

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