Randomized selection on the GPU
Laura Monroe,Joanne Wendelberger,Sarah E. Michalak +2 more
- 05 Aug 2011
- pp 89-98
TL;DR: A fast and memory-sparing probabilistic top k selection algorithm on the GPU that always gives a correct result and always terminates.
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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.
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References
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David G. Kendall
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Time bounds for selection
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Parallel Prefix Sum (Scan) with CUDA
Mark J. Harris
- 01 Jan 2011
TL;DR: The water needs of this region have changed in recent years from being primarily for agricultural purposes to domestic and industrial uses now, and the needs of these industries have changed as well.
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Randomized Algorithms
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- 05 Mar 2013
TL;DR: For many applications, a randomized algorithm is either the simplest or the fastest algorithm available, and sometimes both. as discussed by the authors introduces the basic concepts in the design and analysis of randomized algorithms and provides a comprehensive and representative selection of the algorithms that might be used in each of these areas.
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