Parallel implementation of maximum-shift algorithm using OpenMp

String matching is considered as one of the center issues within the field of computer science, where there are numerous computer applications that supply the clients with string matching services. The increment within the number of databases which are created and protected in numerous computer gadg...

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Main Authors: AbdulRazzaq, Atheer Akram (Author), Hamad, Qusay Shihab (Author), Taha, Ahmed Majid (Author)
Format: EJournal Article
Published: Institute of Advanced Engineering and Science, 2021-06-01.
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001 ijeecs25239_15094
042 |a dc 
100 1 0 |a AbdulRazzaq, Atheer Akram  |e author 
100 1 0 |e contributor 
700 1 0 |a Hamad, Qusay Shihab  |e author 
700 1 0 |a Taha, Ahmed Majid  |e author 
245 0 0 |a Parallel implementation of maximum-shift algorithm using OpenMp 
260 |b Institute of Advanced Engineering and Science,   |c 2021-06-01. 
500 |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/25239 
520 |a String matching is considered as one of the center issues within the field of computer science, where there are numerous computer applications that supply the clients with string matching services. The increment within the number of databases which are created and protected in numerous computer gadgets had impacted researchers with the slant towards getting robust techniques in tending to this issue. In this study, the Maximum-Shift string matching algorithm is chosen to be executed with multi-core innovation through the utilization of OpenMP paradigm, in order to decrease the successive time, and increment the speedup and efficiency of the algorithm. The deoxyribonucleic acid (DNA), protein and the English text datasets are utilized to test the parallel execution that influences the Maximum-Shift algorithm execution when utilized with multi-core environment. The results demonstrated that the execution is affected by the performance between the parallel and consecutive execution of Maximum-Shift algorithm by data type. The English text appeared ideal comes about within the parallel execution time as compared to other datasets, whereas the DNA database set appeared the most elevated comes about when compared to other data types in terms of speedup and efficiency capabilities. 
540 |a Copyright (c) 2021 Institute of Advanced Engineering and Science 
540 |a http://creativecommons.org/licenses/by-nc/4.0 
546 |a eng 
690
690 |a database types; efficiency; maximum-shift algorithm; openMP directive; parallel execution time; speedup; 
655 7 |a info:eu-repo/semantics/article  |2 local 
655 7 |a info:eu-repo/semantics/publishedVersion  |2 local 
655 7 |2 local 
786 0 |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 22, No 3: June 2021; 1529-1539 
786 0 |n 2502-4760 
786 0 |n 2502-4752 
786 0 |n 10.11591/ijeecs.v22.i3 
787 0 |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/25239/15094 
856 4 1 |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/25239/15094  |z Get fulltext