Open Access   Article Go Back

Finding the best network for laying renewable energy based solar panel roads: A GPU parallel algorithm implemented on CUDA

Aayush Kapur1 , Nirut Gupta2

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-6 , Page no. 255-260, Jun-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i6.255260

Online published on Jun 30, 2019

Copyright © Aayush Kapur, Nirut Gupta . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: Aayush Kapur, Nirut Gupta, “Finding the best network for laying renewable energy based solar panel roads: A GPU parallel algorithm implemented on CUDA,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.255-260, 2019.

MLA Style Citation: Aayush Kapur, Nirut Gupta "Finding the best network for laying renewable energy based solar panel roads: A GPU parallel algorithm implemented on CUDA." International Journal of Computer Sciences and Engineering 7.6 (2019): 255-260.

APA Style Citation: Aayush Kapur, Nirut Gupta, (2019). Finding the best network for laying renewable energy based solar panel roads: A GPU parallel algorithm implemented on CUDA. International Journal of Computer Sciences and Engineering, 7(6), 255-260.

BibTex Style Citation:
@article{Kapur_2019,
author = {Aayush Kapur, Nirut Gupta},
title = {Finding the best network for laying renewable energy based solar panel roads: A GPU parallel algorithm implemented on CUDA},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2019},
volume = {7},
Issue = {6},
month = {6},
year = {2019},
issn = {2347-2693},
pages = {255-260},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4539},
doi = {https://doi.org/10.26438/ijcse/v7i6.255260}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i6.255260}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4539
TI - Finding the best network for laying renewable energy based solar panel roads: A GPU parallel algorithm implemented on CUDA
T2 - International Journal of Computer Sciences and Engineering
AU - Aayush Kapur, Nirut Gupta
PY - 2019
DA - 2019/06/30
PB - IJCSE, Indore, INDIA
SP - 255-260
IS - 6
VL - 7
SN - 2347-2693
ER -

VIEWS PDF XML
323 318 downloads 176 downloads
  
  
           

Abstract

The objective of this paper is implementation of ACO algorithm on GPU to combat real life problems of road network identification along with an application focusing on renewable energy. GPUs are specialized microprocessors that accelerates graphics operation. Parallel processing is required when we consider a heavy code with so much of similar iterations. CUDA is NVIDIA’s architecture for parallel computing that is used for extensive parallel computing and increases the performance by employing the GPU (Graphical Processing Unit). We have Ant colony optimisation algorithm implementation that is a bit different than others. Also, we compare it with the sequential code and the results are that it is very fast as compared to sequential code. To deal with the execution of optimisation we will propose two different approaches, one will be the serial approach of the ACO algorithm to generate the network and other will be GPU / CUDA based approach. We will compare the execution time in both the cases and then find out the speed up. An applicability of this approach is for generating the best possible road network for city coordinates where we try to get the network with least cost. This is of immense applicability for developing countries where road networks are upcoming.

Key-Words / Index Term

CUDA, GPU, Parallel Processing, travelling salesman problem, Road network identification

References

[1] Akihiro Uchida, Yasuaki Ito, Koji Nakano, “An Efficient GPU Implementation of Ant Colony Optimization for the Traveling Salesman Problem”, IEEE
[2] Zhou Y, He F Z, Qiu Y M. June 2017, Vol. 60 068102:1–068102:3. SCIENCE CHINA Information Sciences
[3] Dawson, Stewart. 2013. IEEE
[4] Zhoua, Hea, Houa, Qiub . 14 october 2017. ELSEVIER , future generation computer systems
[5] Akihiro, Ito, Nakano. 2012. IEEE
[6] Ceciliaa , Llanesa, Abellána, Gómez-Lunab, Changc, Hwud .15December2017. ELSEVIER, Journal of parallel Distributed computing
[7] Dawson, Stewart. 2014. IEEE
[8] Johny and John. 25 May 2018. ELSEVIER Computer Languages,Systems & Structures
[9] Ermiş , Çatay. May 2017. Transportation Research Procedia
[10] Souza, Pozo. 2014. IEEE
[11] Patil, Pandel. March 2016. International Journal of Innovative Research in Computer and Communication Engineering
[12] Skinderowicz. 2016. ACM
[13] Papenhausen, Mueller. 25 May 2018. ELSEVIER Computer Languages,Systems & Structures
[14] Khatri, Gupta. 2014. IEEE
[15] Johny, John. March– 2017. International Journal of Recent Innovation in Engineering and Research
[16] Alimi, Bali, Elloumi, Abraham. 2017. Springer
[17] Kulkarni. May-Jun 2013. International Journal of Engineering Research and Applications
[18] Michaël Krajeck, Gravel, Delévacqa.2012.IEEE
[19] Shingate. 16 November 2017
[20] SHI, Zhi. 2012. Springer
[21] Rocki, Suda. 2013. IEEE 27th International Symposium on Parallel & Distributed Processing
[22] Zhao, Cai, Lan. 2012. International Conference
[23] Youness, Ibraheim, Moness, Osama. 2012. IEEE
[24] Diaz, caro. 2012. IEEE
[25] Jain, Vanita & Jain, Aarushi & Jain, Achin & Kumar Dubey, Arun. (2018) Comparative Study between FA, ACO, and PSO, ijsrcse