Parallel bucket sorting on graphics processing units based on convex optimization

Beliakov, Gleb, Li, Gang and Liu, Shaowu 2015, Parallel bucket sorting on graphics processing units based on convex optimization, Optimization, vol. 64, no. 4, pp. 1033-1055, doi: 10.1080/02331934.2013.836645.

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Title Parallel bucket sorting on graphics processing units based on convex optimization
Author(s) Beliakov, GlebORCID iD for Beliakov, Gleb
Li, GangORCID iD for Li, Gang
Liu, Shaowu
Journal name Optimization
Volume number 64
Issue number 4
Start page 1033
End page 1055
Total pages 23
Publisher Taylor & Francis
Place of publication Abingdon, Eng.
Publication date 2015
ISSN 0233-1934
Keyword(s) convex optimization
cutting plane method
order statistic
parallel selection
parallel sorting
Summary We found an interesting relation between convex optimization and sorting problem. We present a parallel algorithm to compute multiple order statistics of the data by minimizing a number of related convex functions. The computed order statistics serve as splitters that group the data into buckets suitable for parallel bitonic sorting. This led us to a parallel bucket sort algorithm, which we implemented for many-core architecture of graphics processing units (GPUs). The proposed sorting method is competitive to the state-of-the-art GPU sorting algorithms and is superior to most of them for long sorting keys.
Language eng
DOI 10.1080/02331934.2013.836645
Field of Research 080109 Pattern Recognition and Data Mining
080204 Mathematical Software
080205 Numerical Computation
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2013, Taylor & Francis
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Created: Thu, 17 Oct 2013, 09:03:57 EST by Gleb Beliakov

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