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Implementation of GPU using Fine-Grained Parallel Genetic Algorithm

by R.k.nayak, B.s.p.mishra
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 120 - Number 19
Year of Publication: 2015
Authors: R.k.nayak, B.s.p.mishra
10.5120/21333-4311

R.k.nayak, B.s.p.mishra . Implementation of GPU using Fine-Grained Parallel Genetic Algorithm. International Journal of Computer Applications. 120, 19 ( June 2015), 5-8. DOI=10.5120/21333-4311

@article{ 10.5120/21333-4311,
author = { R.k.nayak, B.s.p.mishra },
title = { Implementation of GPU using Fine-Grained Parallel Genetic Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 120 },
number = { 19 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 5-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume120/number19/21333-4311/ },
doi = { 10.5120/21333-4311 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:06:37.111572+05:30
%A R.k.nayak
%A B.s.p.mishra
%T Implementation of GPU using Fine-Grained Parallel Genetic Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 120
%N 19
%P 5-8
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Many optimization problems have complex search space, which either increase the solving problem time or finish searching without obtaining the best solution. Genetic Algorithm (GA) is an optimization technique used in solving many practical problems in science, engineering, and business domains. Parallel Genetic Algorithm (PGA) has been widely used to increase speed of GA, especially after the spread of parallel platforms such as GPUs, FPGA, and Multi-Core Processors. In this paper, we introduce a type of PGA called Fine-grained Parallel Genetic Algorithm, which has the advantages of maintaining better population diversity, and inhibiting premature. Fine-grained PGA is implemented on graphics hardware.

References
  1. Goldberg, D. E. 1989 . Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Professional, First Edition.
  2. Umbarkar1, A. J. and Joshi2, M. S. and Rothe3, N. M. and Tomassini, M. 1995. A survey of parallel genetic algorithms. World Scientific III.
  3. Konfrst, Z. 2004. Parallel genetic algorithms: advances, computing rends, applications and perspectives. In Parallel and Distributed Processing Symposium.
  4. Wang, Chen,K. and Ong, Y. S. (Eds. ). 2005. Parallel Genetic Algorithms on Programmable Graphics Hardware. Springer-Verlag Berlin Heidelberg.
  5. M. Nowostawski, M. and Poli,R . 1999. Parallel Genetic Algorithm Taxonomy. Vol. 13, MAY, 1999.
  6. Umbarkar, A. J. and Joshi, M. S. Joshi and Rothe, N. M. 2013. Genetic algorithm on general purpose graphics processing unit: parallelism review ictact journal on soft computing, january 2013, volume: 03, issue: 02
  7. Hassani,A. and Treijs,J. 2009. An Overview of Standard and Parallel Genetic Algorithms.
  8. Al-marakeby, A. 2013. FPGA on FPGA: Implementation of Fine-grained Parallel Genetic Algorithm on Field Programmable Gate Array,IJCA, vol-80, No 6, 2013.
  9. XUE Shengjun and GUO Shaoyong and BAI Dongling,2008. The Analysis and Research of Parallel Genetic Algorithm. Wireless Communications, Networking and Mobile Computing.
  10. Jian-Ming Li and Xiao-Jing Wang and Rong-Sheng He and Zhong-Xian Chi. 2007. An Efficient Fine-grained Parallel Genetic Algorithm Based on GPU-Accelerated. International Conference on Network and Parallel Computing.
  11. Raghuwanshi, M. , Kakde, O. : Survey on multiobjective evolutionary and real coded genetic algorithms. In: The 8th Asia Pacific Symposium on Intelligent and Evolutionary Systems, Cairns, Australia (2004)
  12. Michalewicz, Z. 1996. Genetic Algorithms + Data Structures = Evolution Programs.
  13. Press, W. H. and Teukolsky, S. A. and Vetterling, W. T. 2002. Flannery, B. P. : Numerical Recipes in C++. The Art of Scientific Computing. Cambridge University.
  14. Lukac, R. . and Plataniotis, K. N. and Smolka, B. 2004. Venetsanopoulos, A. N. Color image filtering and enhancement based on genetic algorithms. IEEE International Symposium on Circuits and Systems.
  15. Houston, M. and Fatahalian, K. and Sugerman, J. and Buck, I. and Hanrahan, P. 2004. Parallel computation on a cluster of gpus. ACM Workshop on General-Purpose Computing on Graphics Processors, Los Angeles,California.
Index Terms

Computer Science
Information Sciences

Keywords

Parallel Genetic algorithm FPGA GPU Parallel Processing

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