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Performance Analysis of Single Source Shortest Path Algorithm over Multiple GPUs in a Network of Workstations using OpenCL and MPI

by Krishnahari Thouti, S. R. Sathe
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 77 - Number 9
Year of Publication: 2013
Authors: Krishnahari Thouti, S. R. Sathe
10.5120/13424-1104

Krishnahari Thouti, S. R. Sathe . Performance Analysis of Single Source Shortest Path Algorithm over Multiple GPUs in a Network of Workstations using OpenCL and MPI. International Journal of Computer Applications. 77, 9 ( September 2013), 31-36. DOI=10.5120/13424-1104

@article{ 10.5120/13424-1104,
author = { Krishnahari Thouti, S. R. Sathe },
title = { Performance Analysis of Single Source Shortest Path Algorithm over Multiple GPUs in a Network of Workstations using OpenCL and MPI },
journal = { International Journal of Computer Applications },
issue_date = { September 2013 },
volume = { 77 },
number = { 9 },
month = { September },
year = { 2013 },
issn = { 0975-8887 },
pages = { 31-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume77/number9/13424-1104/ },
doi = { 10.5120/13424-1104 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:48:59.160734+05:30
%A Krishnahari Thouti
%A S. R. Sathe
%T Performance Analysis of Single Source Shortest Path Algorithm over Multiple GPUs in a Network of Workstations using OpenCL and MPI
%J International Journal of Computer Applications
%@ 0975-8887
%V 77
%N 9
%P 31-36
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Graphics Processing Units (GPUs) are being heavily used in various graphics and non-graphics applications. Many practical problems in computing can be represented as graphs to arrive at a particular solution. These graphs contains very large number, up to millions pairs of vertices and edges. In this paper, we present performance analysis of Dijkstra's single source shortest path algorithm over multiple GPU devices in a single machine as well as over a network of workstations using OpenCL and MPI. Experimental results prove that parallel execution of Dijkstra's algorithm has good performance when algorithm is run over multi-GPU devices in a single workstation as opposed to multi-GPU devices over a network of workstations. For our experimentation, we have used workstation having Intel Xeon 6-core Processor; supporting hyper-threading and a total of 24 threads with NVIDIA Quadro FX 3800 GPU device. The two GPU devices are connected by SLI Bridge. Overall, on average we achieved performance improvement up to an order of 10-15x.

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Index Terms

Computer Science
Information Sciences

Keywords

GPU Computing OpenCL Multi-node GPU Cluster Dijkstra's algorithm Single source shortest path

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