Three High Performance Architectures in the Parallel APMC Boat

Hamidouche, Khaled; Borghi, Alexandre; Esterie, Pierre; Falcou, Joel; Peyronnet, Sylvain

doi:10.1109/pdmc-hibi.2010.12

Cited by 6 publications

(3 citation statements)

References 26 publications

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“…This is due to the increase in the communication time. When the number of cores in parallel and pattern length increase, the parallel and sequential times are decrease in the long and short pattern lengths [13], [23].…”

Section: Discussion and Analysismentioning

confidence: 99%

“…The DNA dataset obtained good performance with all number of cores because there are only four characters in the DNA dataset which possesses short parallel time in comparison to the sequential time for the same data type. Moreover, the parallel time decreased when the pattern length increased [23]. Furthermore, the algorithm technique is dependent upon the hash function that is used to calculate the hash value of three characters only in the first step.…”

Section: Discussion and Analysismentioning

confidence: 99%

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Parallel processing of E-Atheer algorithm using pthread paradigm

Abdulrazzaq

Fadhel

Alzubaidi

et al. 2023

IJEECS

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The development in the field of computer technology, and the increase in the growth rate of database, alongside the extraction of certain data from a huge pool of database involve intricate and complex processes. The processes comprise text mining, pattern recognition, retrieval of information and text processing. Thus, the need for enhancing the performance of string matching algorithms is required, which is considered as one of the challenges to the researchers. Consequently, one of the resolution to address this problem is the parallelization for exact string matching algorithms. In this study, we implemented the parallel exact string matching algorithm termed as E-Atheer with multi-core processing utilizing Pthread (POSIX) for the reduction of time consumption. The Pitch, XML, Protein, and DNA database types are utilized to test the impact of the proposed parallel algorithm. The parallelization algorithm obtained positive results in the parallel execution time, and a more superior expediting capabilities, in comparison to the sequential result. The Pitch database indicated optimal results in parallel execution time, and when utilizing long and short pattern lengths. The DNA database indicated optimal speedup performance when utilizing short and long pattern length, meanwhile the XML and Protein on the other hand indicated the worst results.

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Section: Discussion and Analysismentioning

confidence: 99%

Section: Discussion and Analysismentioning

confidence: 99%

Parallel processing of E-Atheer algorithm using pthread paradigm

Abdulrazzaq

Fadhel

Alzubaidi

et al. 2023

IJEECS

View full text Add to dashboard Cite

show abstract

“…The overhead increases when the number of cores increases, due to the increase in the communication time, alongside the increase in the number of cores [24]. Through the use of 1GB data size of DNA, Protein and English database types as shown in Tables 1, 2, and 3.…”

Section: Parallel Execution Time Evaluationmentioning

confidence: 99%

Parallel implementation of maximum-shift algorithm using OpenMp

Abdulrazzaq

Hamad

Taha

2021

IJEECS

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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.

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