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Reseach Article

Performance Analysis of Parallel Sorting Algorithms using GPU Computing

Published on September 2016 by Neetu Faujdar, S. P. Ghrera
Recent Innovations in Computer Science and Information Technology
Foundation of Computer Science USA
RICSIT2016 - Number 2
September 2016
Authors: Neetu Faujdar, S. P. Ghrera

Neetu Faujdar, S. P. Ghrera . Performance Analysis of Parallel Sorting Algorithms using GPU Computing. Recent Innovations in Computer Science and Information Technology. RICSIT2016, 2 (September 2016), 5-11.

author = { Neetu Faujdar, S. P. Ghrera },
title = { Performance Analysis of Parallel Sorting Algorithms using GPU Computing },
journal = { Recent Innovations in Computer Science and Information Technology },
issue_date = { September 2016 },
volume = { RICSIT2016 },
number = { 2 },
month = { September },
year = { 2016 },
issn = 0975-8887,
pages = { 5-11 },
numpages = 7,
url = { /proceedings/ricsit2016/number2/26189-2024/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Proceeding Article
%1 Recent Innovations in Computer Science and Information Technology
%A Neetu Faujdar
%A S. P. Ghrera
%T Performance Analysis of Parallel Sorting Algorithms using GPU Computing
%J Recent Innovations in Computer Science and Information Technology
%@ 0975-8887
%N 2
%P 5-11
%D 2016
%I International Journal of Computer Applications

Sorting is a well interrogating issue in computer science. Many authors have invented numerous sorting algorithms on CPU (Central Processing Unit). In today's life sorting on the CPU is not so efficient. To get the efficient sorting parallelization should be done. There are many ways of parallelization of sorting but at the present time GPU (Graphics Processing Unit) computing is the most preferable way to parallelize the sorting algorithms. Many authors have implemented the some sorting algorithms using GPU computing with CUDA. This paper mentioned the roadmap of research direction of a GPU based sorting algorithms and the various research aspects to work on GPU based sorting algorithms. These research directions include the various sorting algorithms which are parallel (Merge, Quick, Bitonic, Odd-Even, Count, Radix etc. ) sort algorithms using GPU computing with CUDA (Compute Unified Device Architecture). In this paper, we have tested and compared the parallel and sequential (Merge, Quick, Count and Odd-Even sort) using dataset. The testing of parallel algorithms is done using GPU computing with CUDA. The speedup is also measured of various parallel sorting algorithms. The results have depicted that, the count sort is the most efficient sort due to based on the key value. Future research will refine the performance of sorting algorithms in GPU architecture.

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Index Terms

Computer Science
Information Sciences


Gpu Cuda Parallel Sorting Algorithms.