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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Scientific Journal of Informatics Sinkron : Jurnal dan Penelitian Teknik Informatika Data Science: Journal of Computing and Applied Informatics Journal of Information System, Applied, Management, Accounting and Research Indonesian Journal of Electrical Engineering and Computer Science Journal of Research in Mathematics Trends and Technology Jurnal EduHealth
Mahyuddin K. M. Nasution, Mahyuddin K. M.
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Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Health Professions Mathematics Public Health Veterinary

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Journal : Data Science: Journal of Computing and Applied Informatics

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Enhancing Performance of Parallel Self-Organizing Map on Large Dataset with Dynamic Parallel and Hyper-Q Alexander F.K. Sibero; Opim Salim Sitompul; Mahyuddin K.M. Nasution
Data Science: Journal of Computing and Applied Informatics Vol. 2 No. 2 (2018): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1212.692 KB) | DOI: 10.32734/jocai.v2.i2-324

Abstract

Self-Organizing Map (SOM) is an unsupervised artificial neural network algorithm. Even though this algorithm is known to be an appealing clustering method,many efforts to improve its performance are still pursued in various research works. In order to gain faster computation time, for instance, running SOM in parallel had been focused in many previous research works. Utilization of the Graphics Processing Unit (GPU) as a parallel calculation engine is also continuously improved. However, total computation time in parallel SOM is still not optimal on processing large dataset. In this research, we propose a combination of Dynamic Parallel and Hyper-Q to further improve the performance of parallel SOM in terms of faster computing time. Dynamic Parallel and Hyper-Q are utilized on the process of calculating distance and searching best-matching unit (BMU), while updating weight and its neighbors are performed using Hyper-Q only. Result of this study indicates an increase in SOM parallel performance up to two times faster compared to those without using Dynamic Parallel and Hyper-Q.
Co-Authors Al Khowarizmi Alexander F.K. Sibero Arif Ridho Lubis Azmi, Zulfian - Elviawaty Muisa Zamzami Herman Mawengkang Marischa Elveny Muhammad Zarlis Muhammad Zarlis, Muhammad Opim Salim Sitompul Rahmad Syah Rahman Aulia, Rahman Verdi Yasin Zarlis, M Zarlis, M Zulfian Azmi