Particle Swarm Optimization with CUDA

International Journal of Research and Engineering

View Publication Info
 
 
Field Value
 
Title Particle Swarm Optimization with CUDA
 
Creator taherian dehkordi, somayeh
 
Description In recent years, particles’ optimization algorithm has highly been used as an effective method in solving complex and difficult optimization problems. Since particles algorithm is based on recurring population and it can be very inefficient in terms of the time required for implementation and speed to solve optimization problems with large-scale including ones which need a very large population to search in problem solution space. The main reason for this issue is that this algorithm optimization process requires a large number of function evaluations which are usually run serially. This article aims to implement particles’ optimization algorithm in parallel on graphics processing unit and to improve running efficiency and speed. The implementation results on the graphics processor show that the performance of this algorithm has greatly increased as to its implementation in parallel and with change in kernel implementation. In fact, in this study, implementation and velocity evaluation of particles algorithm implementation in parallel and based on CUDA framework has been investigated and compared. Then, there have been efforts to improve acceleration in this method in part and a new method will be proposed in CUDA framework to improve acceleration in particles algorithm and graphic processor setting.
 
Publisher IJRE Publisher
 
Date 2017-08-16
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier https://digital.ijre.org/index.php/int_j_res_eng/article/view/277
 
Source International Journal of Research and Engineering; Vol 4 No 6 (2017): June 2017 Edition; 177-183
2348-7860
2348-7852
 
Language eng
 
Relation https://digital.ijre.org/index.php/int_j_res_eng/article/view/277/268
 
Rights Copyright (c) 2017 somayeh taherian dehkordi
http://creativecommons.org/licenses/by/4.0
 

Contact Us

The PKP Index is an initiative of the Public Knowledge Project.

For PKP Publishing Services please use the PKP|PS contact form.

For support with PKP software we encourage users to consult our wiki for documentation and search our support forums.

For any other correspondence feel free to contact us using the PKP contact form.

Find Us

Twitter

Copyright © 2015-2018 Simon Fraser University Library