Implementation of Sorting Algorithms with CUDA: An Empirical Study

Authors

  • Ali Yazici
  • Hakan Gokahmetoglu

DOI:

https://doi.org/10.18100/ijamec.53457

Keywords:

CUDA, sorting algorithms, GPGPU programming, parallel sorting

Abstract

Sorting algorithms have been studied for more than 3 decades now. The aim of this paper is to implement some of the sorting algorithms using the CUDA language in a GPU environment provided by the Nvidia graphics cards. This empirical study is done for comparing the performance of the sorting algorithms in a run-time environment provided by the GPUs and the CUDA programming language. This study considers the implementation of bubble sort, insertion sort, quicksort, selection sort and shell sort algorithms. It is shown that there is a significant amount of speed-up in using CUDA and the Nvidia architecture instead of a sequential code running on standard architectures.

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References

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Published

28-08-2016

Issue

Section

Research Articles

How to Cite

[1]
“Implementation of Sorting Algorithms with CUDA: An Empirical Study”, J. Appl. Methods Electron. Comput., vol. 4, no. 3, pp. 74–77, Aug. 2016, doi: 10.18100/ijamec.53457.

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