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Parallelization of Shortest Path Finder on GPU: Floyd-Warshall

by Dhananjay Kulkarni, Neha Sharma, Prithviraj Shinde, Vaishali Varma
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 110 - Number 16
Year of Publication: 2015
Authors: Dhananjay Kulkarni, Neha Sharma, Prithviraj Shinde, Vaishali Varma
10.5120/19398-0920

Dhananjay Kulkarni, Neha Sharma, Prithviraj Shinde, Vaishali Varma . Parallelization of Shortest Path Finder on GPU: Floyd-Warshall. International Journal of Computer Applications. 110, 16 ( January 2015), 5-8. DOI=10.5120/19398-0920

@article{ 10.5120/19398-0920,
author = { Dhananjay Kulkarni, Neha Sharma, Prithviraj Shinde, Vaishali Varma },
title = { Parallelization of Shortest Path Finder on GPU: Floyd-Warshall },
journal = { International Journal of Computer Applications },
issue_date = { January 2015 },
volume = { 110 },
number = { 16 },
month = { January },
year = { 2015 },
issn = { 0975-8887 },
pages = { 5-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume110/number16/19398-0920/ },
doi = { 10.5120/19398-0920 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:46:30.853426+05:30
%A Dhananjay Kulkarni
%A Neha Sharma
%A Prithviraj Shinde
%A Vaishali Varma
%T Parallelization of Shortest Path Finder on GPU: Floyd-Warshall
%J International Journal of Computer Applications
%@ 0975-8887
%V 110
%N 16
%P 5-8
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The project deals with implementation of Floyd Warshall Algorithm i. e All Pair Shortest Path. This algorithm is implemented using parallel programming concept for faster solution. This is a research based project in which the serial and parallel computations are compared. Floyd Warshall algorithm has overcome the drawbacks of Dijkstra's and Bellman Ford Algorithm. For parallel programming, the project is implemented using NVIDIA GPU(NVIDIA GeForce 820M , 410M) for which CUDA(CUDA Toolkit 6. 0) is used . The purpose of developing this project is to find the shortest path between all the present nodes in a graph. This system is designed to work on a large dataset(set of 48 or 72 or 100 cities). This project can be implemented for Airline Systems,Transportation services, Courier Services, Networking.

References
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  6. http://www. nvidia. com/object/what-is-gpu-computing. html
  7. Efficient multi GPU algorithm for All pair shortest path.
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  9. P. Harish and P. Narayanan, Accelerating large graph algorithms on the GPU using CUDA, Lecture Notes in Computer Science
  10. A. Buluc, J. R. Gilbert, and C. Budak, Solving path problems on the GPU, Parallel Computing, vol. In Press, Corrected Proof, 2009.
  11. R. Seidel. On the all-pairs-shortest-path problem in unweighted undirected graphs. Journal of Computer and System Sciences
  12. U. Bondhugula, A. Devulapalli, J. Fernando, P. Wyckoff, and P. Sadayappan, Parallel fpga-based all-pairs shortest-paths in a directed graph, Parallel and Distributed Processing Symposium, International
Index Terms

Computer Science
Information Sciences

Keywords

Floyd Warshall Algorithm Parallel Programming CUDA NVIDIA GPU.

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