Computational Science Technical Note CSTN-099

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Asynchronous Communication Schemes for Finite Difference Methods on Multiple GPUs

D. P. Playne and K. A. Hawick

Archived June 2009

Abstract

Finite difference methods continue to provide an important and parallelisable approach to many numerical simulations problems. Iterative multigrid and multilevel algorithms can converge faster than ordinary finite difference methods but can be more difficult to parallelise. Data parallel paradigms tend to lend themselves particularly well to solving regular mesh PDEs whereby low latency communications and high compute to communications ratios can yield high levels of computational efficiency and raw performance. We report on some practical algorithmic and data layout approaches and on performance data on a range of Graphical Processing Units (GPUs) with CUDA. We focus on the use of multiple GPU devices with a single CPU host.

Keywords: finite differences methods; packed-data; GPUs; simulations.

Full Document Text: PDF version.

Citation Information: BiBTeX database for CSTN Notes.

BiBTeX reference:

@INPROCEEDINGS{CSTN-099,
  author = {D.P. Playne and K.A. Hawick},
  title = {{Hierarchical and Multi-level Schemes for Finite Difference Methods
	on GPUs}},
  booktitle = {Proc. CCGrid 2010, Melbourne, Australia},
  year = {2010},
  pages = {763-768},
  address = {Melbourne, Australia},
  month = {17-20 May},
  organization = {ACM/IEEE},
  institution = {Computer Science, Massey University},
  timestamp = {2009.12.16}
}


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