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Syberfeldt, A. & Ekblom, T. (2017). A comparative evaluation of the GPU vs. the CPU for parallelization of evolutionary algorithms through multiple independent runs. International Journal of Computer Science & Information Technology (IJCSIT), 9(3), 1-14
Open this publication in new window or tab >>A comparative evaluation of the GPU vs. the CPU for parallelization of evolutionary algorithms through multiple independent runs
2017 (English)In: International Journal of Computer Science & Information Technology (IJCSIT), ISSN 0975-4660, E-ISSN 0975-3826, Vol. 9, no 3, p. 1-14Article in journal (Refereed) Published
Abstract [en]

Multiple independent runs of an evolutionary algorithm in parallel are often used to increase the efficiency of parameter tuning or to speed up optimizations involving inexpensive fitness functions. A GPU platform is commonly adopted in the research community to implement parallelization, and this platform has been shown to be superior to the traditional CPU platform in many previous studies. However, it is not clear how efficient the GPU is in comparison with the CPU for the parallelizing multiple independent runs, as the vast majority of the previous studies focus on parallelization approaches in which the parallel runs are dependent on each other (such as master-slave, coarse-grained or fine-grained approaches). This study therefore aims to investigate the performance of the GPU in comparison with the CPU in the context of multiple independent runs in order to provide insights into which platform is most efficient. This is done through a number of experiments that evaluate the efficiency of the GPU versus the CPU in various scenarios. An analysis of the results shows that the GPU is powerful, but that there are scenarios where the CPU outperforms the GPU. This means that a GPU is not the universally best option for parallelizing multiple independent runs and that the choice of computation platform therefore should be an informed decision. To facilitate this decision and improve the efficiency of optimizations involving multiple independent runs, the paper provides a number of recommendations for when and how to use the GPU.

Keywords
Evolutionary algorithms, parallelization, multiple independent runs, GPU, CPU
National Category
Other Engineering and Technologies not elsewhere specified
Research subject
Production and Automation Engineering; INF201 Virtual Production Development
Identifiers
urn:nbn:se:his:diva-13923 (URN)10.5121/ijcsit.2017.9301 (DOI)
Available from: 2017-07-15 Created: 2017-07-15 Last updated: 2019-01-24Bibliographically approved
Syberfeldt, A., Danielsson, O., Holm, M. & Ekblom, T. (2014). Augmented Reality at the Industrial Shop-Floor. In: Lucio Tommaso De Paolis, Antonio Mongelli (Ed.), Augmented and Virtual Reality: . Paper presented at 1st International on Augmented and Virtual Reality, Lecce, September 17-20 (pp. 201-209). Springer Berlin/Heidelberg
Open this publication in new window or tab >>Augmented Reality at the Industrial Shop-Floor
2014 (English)In: Augmented and Virtual Reality / [ed] Lucio Tommaso De Paolis, Antonio Mongelli, Springer Berlin/Heidelberg, 2014, p. 201-209Conference paper, Published paper (Refereed)
Abstract [en]

This paper describes a study of the potential of using augmented real-ityat the industrial shop-floor with the aim ofimprovingthe capability of the shop-floor operators. In the study, aprototype systemfor augmented reality is developed based on the Oculus Rift platform. The systemisevaluated through an experimentin which a physical three-dimensionalpuzzleis to be assembled.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2014
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 8853
Keywords
augmented reality, industrial shop-floor, assembling, oculus rift
National Category
Engineering and Technology
Research subject
Technology; Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-9994 (URN)10.1007/978-3-319-13969-2_16 (DOI)000354698400016 ()2-s2.0-84918585836 (Scopus ID)978-3-319-13968-5 (ISBN)978-3-319-13969-2 (ISBN)
Conference
1st International on Augmented and Virtual Reality, Lecce, September 17-20
Projects
Young Operator 2020
Funder
Knowledge Foundation
Available from: 2014-09-22 Created: 2014-09-22 Last updated: 2018-03-29Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-3705-5553

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