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Antoine Doucet
Université de La Rochelle
Electrical & Electronics Engineering

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The influence of data size on a high-performance computing memetic algorithm in fingerprint dataset Priati Assiroj; Harco Leslie Hendric Spits Warnars; Edi Abdurachman; Achmad Imam Kistijantoro; Antoine Doucet
Bulletin of Electrical Engineering and Informatics Vol 10, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i4.2760

Abstract

The fingerprint is one kind of biometric. This biometric unique data have to be processed well and secure. The problem gets more complicated as data grows. This work is conducted to process image fingerprint data with a memetic algorithm, a simple and reliable algorithm. In order to achieve the best result, we run this algorithm in a parallel environment by utilizing a multi-thread feature of the processor. We propose a high-performance computing memetic algorithm (HPCMA) to process a 7200 image fingerprint dataset which is divided into fifteen specimens based on its characteristics based on the image specification to get the detail of each image. A combination of each specimen generates a new data variation. This algorithm runs in two different operating systems, Windows 7 and Windows 10 then we measure the influence of data size on processing time, speed up, and efficiency of HPCMA with simple linear regression. The result shows data size is very influencing to processing time more than 90%, to speed up more than 30%, and to efficiency more than 19%.
Co-Authors Achmad Imam Kistijantoro Edi Abdurachman Priati Assiroj Warnars, Harco Leslie Hendric Spits