Randomized Selection on the GPU
Laura Monroe, Joanne Wendelberger, Sarah Michalak
High-Performance Graphics, 2011, pp. 89--98.
Abstract: We implement here a fast and memory-sparing probabilistic top k selection algorithm on the GPU. The algorithm proceeds via an iterative probabilistic guess-and-check process on pivots for a three-way partition. When the guess is correct, the problem is reduced to selection on a much smaller set. This probabilistic algorithm always gives a correct result and always terminates. Las Vegas algorithms of this kind are a form of stochastic optimization and can be well suited to more general parallel processors with limited amounts of fast memory.
Article URL: http://dx.doi.org/10.1145/2018323.2018338
BibTeX format:
@inproceedings{Monroe:2011:RSO,
  author = {Laura Monroe and Joanne Wendelberger and Sarah Michalak},
  title = {Randomized Selection on the GPU},
  booktitle = {High-Performance Graphics},
  pages = {89--98},
  year = {2011},
}
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